mrna purification  (Qiagen)

 
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    Name:
    miRNeasy Mini Kit
    Description:
    For purification of microRNA and total RNA from tissues and cells Kit contents Qiagen miRNeasy Mini Kit 50 preps 50 to 100mg Sample 30L Elution Volume Tissue Cells Sample miRNA Total RNA Purification Spin Column Format Silica Technology Ideal for PCR qPCR Real time RT PCR Microarray For Purification of microRNA and Total RNA from Tissues and Cells Includes 50 RNeasy Mini Spin Columns Collection Tubes 1 5 and 2mL QIAzol Lysis Reagent RNase free Reagents and Buffers Benefits Effective purification of miRNA and total RNA Efficient enrichment of miRNA and RNAs 200 nucleotides High purity RNA suitable for all downstream applications Protocols for copurification or isolation of separate fractio
    Catalog Number:
    217004
    Price:
    368
    Category:
    miRNeasy Mini Kit
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    Structured Review

    Qiagen mrna purification
    miRNeasy Mini Kit
    For purification of microRNA and total RNA from tissues and cells Kit contents Qiagen miRNeasy Mini Kit 50 preps 50 to 100mg Sample 30L Elution Volume Tissue Cells Sample miRNA Total RNA Purification Spin Column Format Silica Technology Ideal for PCR qPCR Real time RT PCR Microarray For Purification of microRNA and Total RNA from Tissues and Cells Includes 50 RNeasy Mini Spin Columns Collection Tubes 1 5 and 2mL QIAzol Lysis Reagent RNase free Reagents and Buffers Benefits Effective purification of miRNA and total RNA Efficient enrichment of miRNA and RNAs 200 nucleotides High purity RNA suitable for all downstream applications Protocols for copurification or isolation of separate fractio
    https://www.bioz.com/result/mrna purification/product/Qiagen
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    mrna purification - by Bioz Stars, 2020-08
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    Images

    1) Product Images from "Macrophage-Derived Slit3 Controls Cell Migration and Axon Pathfinding in the Peripheral Nerve Bridge"

    Article Title: Macrophage-Derived Slit3 Controls Cell Migration and Axon Pathfinding in the Peripheral Nerve Bridge

    Journal: Cell Reports

    doi: 10.1016/j.celrep.2018.12.081

    Ectopic Schwann Cell Migration in the Nerve Bridge of Sox2 KO Mice and Sox2 Regulating Robo1 Expression in SCs (A) Schwann cell (GFP+) migration from both proximal and distal nerve stumps in control mice 6 days after sciatic nerve transection injury. (B) Ectopic Schwann cell migration (white arrows) in the nerve bridge of Sox2 KO mice 6 days after transection injury. (C) Higher magnification image from (B, dotted-line square) showing regenerating axons (labeled with neurofilament, red, indicated by arrowheads) following the ectopic migrating Schwann cells (white arrows) and leaving the nerve bridge. (D) Schwann cells stayed in the nerve bridge in control mice at 14 days following sciatic nerve transection injury. (E) Ectopic migrating Schwann cells (white arrows) leaving the nerve bridge in Sox2 KO mice at 14 days after injury. (F) Ectopic migrating Schwann cells (white arrows) localizing in front of regenerating axons (indicated by arrowheads) of Sox2 KO mice. Scale bar in (A, B, D and E) represents 200 μm, in (C) represents 60 μm, and in (F) represents 30 μm. (G and H) Microarray data (G) and RT-PCR (H) from control and Sox2-overexpressing Schwann cells. Values in (G) represent the fluorescence intensity of dye-labeled cDNA fragments that have hybridized to the probes on the microarray chip. (I) qRT-PCR validation of Robo1 mRNA upregulation in Sox2-overexpressing Schwann cells, n = 3. (J) Quantification of Robo1 protein levels in the distal nerve stump of control (Con) and Sox2 KO mice at 4 and 7 days after injury, n = 3. (K) Western blots showing Robo1 and Robo2 protein upregulation in Sox2-overexpressing Schwann cells. (L) Western blots comparing Robo1 and Robo2 protein levels in the distal nerve stump of control and Sox2 KO mice at 4 and 7 days after injury. (M) Western blot comparing Robo1 protein levels in the distal nerve stump of control (Con) and Sox2-overexpressing (OE) mice at 7 days following injury. (N) Quantification of Robo1 protein levels from (M), n = 3. (O) RT-PCR showing that Slit3 is highly expressed in the nerve bridge at 7 days after injury; dorsal root ganglion (DRG) samples have been used as positive controls. ∗∗ in (I), (J), and (N) indicate p
    Figure Legend Snippet: Ectopic Schwann Cell Migration in the Nerve Bridge of Sox2 KO Mice and Sox2 Regulating Robo1 Expression in SCs (A) Schwann cell (GFP+) migration from both proximal and distal nerve stumps in control mice 6 days after sciatic nerve transection injury. (B) Ectopic Schwann cell migration (white arrows) in the nerve bridge of Sox2 KO mice 6 days after transection injury. (C) Higher magnification image from (B, dotted-line square) showing regenerating axons (labeled with neurofilament, red, indicated by arrowheads) following the ectopic migrating Schwann cells (white arrows) and leaving the nerve bridge. (D) Schwann cells stayed in the nerve bridge in control mice at 14 days following sciatic nerve transection injury. (E) Ectopic migrating Schwann cells (white arrows) leaving the nerve bridge in Sox2 KO mice at 14 days after injury. (F) Ectopic migrating Schwann cells (white arrows) localizing in front of regenerating axons (indicated by arrowheads) of Sox2 KO mice. Scale bar in (A, B, D and E) represents 200 μm, in (C) represents 60 μm, and in (F) represents 30 μm. (G and H) Microarray data (G) and RT-PCR (H) from control and Sox2-overexpressing Schwann cells. Values in (G) represent the fluorescence intensity of dye-labeled cDNA fragments that have hybridized to the probes on the microarray chip. (I) qRT-PCR validation of Robo1 mRNA upregulation in Sox2-overexpressing Schwann cells, n = 3. (J) Quantification of Robo1 protein levels in the distal nerve stump of control (Con) and Sox2 KO mice at 4 and 7 days after injury, n = 3. (K) Western blots showing Robo1 and Robo2 protein upregulation in Sox2-overexpressing Schwann cells. (L) Western blots comparing Robo1 and Robo2 protein levels in the distal nerve stump of control and Sox2 KO mice at 4 and 7 days after injury. (M) Western blot comparing Robo1 protein levels in the distal nerve stump of control (Con) and Sox2-overexpressing (OE) mice at 7 days following injury. (N) Quantification of Robo1 protein levels from (M), n = 3. (O) RT-PCR showing that Slit3 is highly expressed in the nerve bridge at 7 days after injury; dorsal root ganglion (DRG) samples have been used as positive controls. ∗∗ in (I), (J), and (N) indicate p

    Techniques Used: Migration, Mouse Assay, Expressing, Labeling, Microarray, Reverse Transcription Polymerase Chain Reaction, Fluorescence, Chromatin Immunoprecipitation, Quantitative RT-PCR, Western Blot

    2) Product Images from "Identification of the X-linked germ cell specific miRNAs (XmiRs) and their functions"

    Article Title: Identification of the X-linked germ cell specific miRNAs (XmiRs) and their functions

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0211739

    Relationship between target mRNAs of XmiRs and generation of ΔXmiRs mice. (A) A dendrogram of hierarchical clustering analysis of target mRNAs of XmiRs and their neighboring miRNAs. (B) Venn diagram showing the relationship among putative target mRNAs of miR-741-3p, miR-871-3p, and miR-880-3p. Corresponding gene lists are shown in S3 Table . (C) A schematic presentation of the WT and ΔXmiRs locus. gR-741 and gR-871 represent positions of guide RNAs used for genome editing. (D) Representative PCR for genotyping of WT and ΔXmiRs (OT84) mice. Arrows in the right panel represent primers used for PCR. (E) Expression of XmiRs in WT and a ΔXmiRs testes (F2 of OT84) determined with semi-quantitative RT-PCR analysis. U6 snRNA was used as an internal control. (F) HE-stained sections of seminiferous tubules in WT (left) and ΔXmiR (F2 of OT100) (right) testes at 8, 12, 16, and 30 weeks of age. The second and fourth panels for 30 weeks show higher magnification views corresponding to the rectangular area in the first and third panels. Lower two panels show mildly affected seminiferous tubules. Arrowheads show abnormal seminiferous tubules. Scale bar = 50 μm (8, 12, 16 weeks), 200 μm (30 weeks, lower magnification), 100 μm (30 weeks, higher magnification).
    Figure Legend Snippet: Relationship between target mRNAs of XmiRs and generation of ΔXmiRs mice. (A) A dendrogram of hierarchical clustering analysis of target mRNAs of XmiRs and their neighboring miRNAs. (B) Venn diagram showing the relationship among putative target mRNAs of miR-741-3p, miR-871-3p, and miR-880-3p. Corresponding gene lists are shown in S3 Table . (C) A schematic presentation of the WT and ΔXmiRs locus. gR-741 and gR-871 represent positions of guide RNAs used for genome editing. (D) Representative PCR for genotyping of WT and ΔXmiRs (OT84) mice. Arrows in the right panel represent primers used for PCR. (E) Expression of XmiRs in WT and a ΔXmiRs testes (F2 of OT84) determined with semi-quantitative RT-PCR analysis. U6 snRNA was used as an internal control. (F) HE-stained sections of seminiferous tubules in WT (left) and ΔXmiR (F2 of OT100) (right) testes at 8, 12, 16, and 30 weeks of age. The second and fourth panels for 30 weeks show higher magnification views corresponding to the rectangular area in the first and third panels. Lower two panels show mildly affected seminiferous tubules. Arrowheads show abnormal seminiferous tubules. Scale bar = 50 μm (8, 12, 16 weeks), 200 μm (30 weeks, lower magnification), 100 μm (30 weeks, higher magnification).

    Techniques Used: Mouse Assay, Polymerase Chain Reaction, Expressing, Quantitative RT-PCR, Staining

    The expression profile of miRNAs in various tissues and cell lines. (A) A heat map of hierarchical clustering of miRNAs detected in small RNA-seq data used in this study. (B) A heat map of 20 miRNAs highly expressed in PGCs. Relative miRNA expression is described according to the color scale. Red and green indicate high and low expression, respectively. Mouse embryonic fibroblasts (MEFs), embryonic stem (ES) cells, primordial germ cells (PGCs), spermatogonia (SPG), spermatozoa (SPZ). (C) The locus of XmiR genes on the X chromosome. (D) The expression of XmiRs in testes, ES cells, and MEFs determined by quantitative RT-PCR. Each expression level was normalized to the expression of U6 snRNA. The expression in ES cells was set as 1.0. Error bars show standard errors of three biological replicates. **P
    Figure Legend Snippet: The expression profile of miRNAs in various tissues and cell lines. (A) A heat map of hierarchical clustering of miRNAs detected in small RNA-seq data used in this study. (B) A heat map of 20 miRNAs highly expressed in PGCs. Relative miRNA expression is described according to the color scale. Red and green indicate high and low expression, respectively. Mouse embryonic fibroblasts (MEFs), embryonic stem (ES) cells, primordial germ cells (PGCs), spermatogonia (SPG), spermatozoa (SPZ). (C) The locus of XmiR genes on the X chromosome. (D) The expression of XmiRs in testes, ES cells, and MEFs determined by quantitative RT-PCR. Each expression level was normalized to the expression of U6 snRNA. The expression in ES cells was set as 1.0. Error bars show standard errors of three biological replicates. **P

    Techniques Used: Expressing, RNA Sequencing Assay, Quantitative RT-PCR

    3) Product Images from "SNL fibroblast feeder layers support derivation and maintenance of human induced pluripotent stem cells"

    Article Title: SNL fibroblast feeder layers support derivation and maintenance of human induced pluripotent stem cells

    Journal: Journal of genetics and genomics = Yi chuan xue bao

    doi: 10.1016/S1673-8527(09)60042-4

    Genes’ expressions analyzed by the TaqMan Human Stem Cell Pluripotency Array. Relative gene expression level of 25 pluripotent marker genes of 4 cell lines represents fold changes relative to that of IMR90 cells normalized to GAPDH expression level.
    Figure Legend Snippet: Genes’ expressions analyzed by the TaqMan Human Stem Cell Pluripotency Array. Relative gene expression level of 25 pluripotent marker genes of 4 cell lines represents fold changes relative to that of IMR90 cells normalized to GAPDH expression level.

    Techniques Used: Expressing, Marker

    Generation of lentivirus-induced hiPS on SNL feeders. A: morphology of iPS-IMR90 when grown over SNL feeders. Scale bar = 100 μm. B: human iPS cells colonies cultured on SNL feeders stain positive for alkaline phosphatase, an indicator of pluripotency (brightfield: 50 × (left), 100 × (right); scale bar = 100 μm). C: immunofluorescent staining of Nanog, Oct4 and TRA-1-60 in iPS cells derived from IMR90 cells using SNL as feeders. Scale bar = 20 μm.
    Figure Legend Snippet: Generation of lentivirus-induced hiPS on SNL feeders. A: morphology of iPS-IMR90 when grown over SNL feeders. Scale bar = 100 μm. B: human iPS cells colonies cultured on SNL feeders stain positive for alkaline phosphatase, an indicator of pluripotency (brightfield: 50 × (left), 100 × (right); scale bar = 100 μm). C: immunofluorescent staining of Nanog, Oct4 and TRA-1-60 in iPS cells derived from IMR90 cells using SNL as feeders. Scale bar = 20 μm.

    Techniques Used: Cell Culture, Staining, Derivative Assay

    The promoters of Nanog and Oct4 analyzed by bisulfite genomic sequencing for DNA methylation status in hES-H1 cells (passage 52), iPS-IMR90 cells (passage 15) and IMR90 fibroblasts (passage 10). Open and closed circles indicate unmethylated and methylated CpGs, respectively. Numbers represent the sequence coverage of examined CpG relative to the transcription start site (TSS).
    Figure Legend Snippet: The promoters of Nanog and Oct4 analyzed by bisulfite genomic sequencing for DNA methylation status in hES-H1 cells (passage 52), iPS-IMR90 cells (passage 15) and IMR90 fibroblasts (passage 10). Open and closed circles indicate unmethylated and methylated CpGs, respectively. Numbers represent the sequence coverage of examined CpG relative to the transcription start site (TSS).

    Techniques Used: Genomic Sequencing, DNA Methylation Assay, Methylation, Sequencing

    4) Product Images from "SNL fibroblast feeder layers support derivation and maintenance of human induced pluripotent stem cells"

    Article Title: SNL fibroblast feeder layers support derivation and maintenance of human induced pluripotent stem cells

    Journal: Journal of genetics and genomics = Yi chuan xue bao

    doi: 10.1016/S1673-8527(09)60042-4

    Genes’ expressions analyzed by the TaqMan Human Stem Cell Pluripotency Array. Relative gene expression level of 25 pluripotent marker genes of 4 cell lines represents fold changes relative to that of IMR90 cells normalized to GAPDH expression level.
    Figure Legend Snippet: Genes’ expressions analyzed by the TaqMan Human Stem Cell Pluripotency Array. Relative gene expression level of 25 pluripotent marker genes of 4 cell lines represents fold changes relative to that of IMR90 cells normalized to GAPDH expression level.

    Techniques Used: Expressing, Marker

    Generation of lentivirus-induced hiPS on SNL feeders. A: morphology of iPS-IMR90 when grown over SNL feeders. Scale bar = 100 μm. B: human iPS cells colonies cultured on SNL feeders stain positive for alkaline phosphatase, an indicator of pluripotency (brightfield: 50 × (left), 100 × (right); scale bar = 100 μm). C: immunofluorescent staining of Nanog, Oct4 and TRA-1-60 in iPS cells derived from IMR90 cells using SNL as feeders. Scale bar = 20 μm.
    Figure Legend Snippet: Generation of lentivirus-induced hiPS on SNL feeders. A: morphology of iPS-IMR90 when grown over SNL feeders. Scale bar = 100 μm. B: human iPS cells colonies cultured on SNL feeders stain positive for alkaline phosphatase, an indicator of pluripotency (brightfield: 50 × (left), 100 × (right); scale bar = 100 μm). C: immunofluorescent staining of Nanog, Oct4 and TRA-1-60 in iPS cells derived from IMR90 cells using SNL as feeders. Scale bar = 20 μm.

    Techniques Used: Cell Culture, Staining, Derivative Assay

    The promoters of Nanog and Oct4 analyzed by bisulfite genomic sequencing for DNA methylation status in hES-H1 cells (passage 52), iPS-IMR90 cells (passage 15) and IMR90 fibroblasts (passage 10). Open and closed circles indicate unmethylated and methylated CpGs, respectively. Numbers represent the sequence coverage of examined CpG relative to the transcription start site (TSS).
    Figure Legend Snippet: The promoters of Nanog and Oct4 analyzed by bisulfite genomic sequencing for DNA methylation status in hES-H1 cells (passage 52), iPS-IMR90 cells (passage 15) and IMR90 fibroblasts (passage 10). Open and closed circles indicate unmethylated and methylated CpGs, respectively. Numbers represent the sequence coverage of examined CpG relative to the transcription start site (TSS).

    Techniques Used: Genomic Sequencing, DNA Methylation Assay, Methylation, Sequencing

    5) Product Images from "MicroRNAs Circulate in the Hemolymph of Drosophila and Accumulate Relative to Tissue microRNAs in an Age-Dependent Manner"

    Article Title: MicroRNAs Circulate in the Hemolymph of Drosophila and Accumulate Relative to Tissue microRNAs in an Age-Dependent Manner

    Journal: Genomics Insights

    doi: 10.4137/GEI.S38147

    Presence of stable miRNAs in Drosophila melanogaster hemolymph. ( A , B ) Clear HL droplets extruded from fly head and thorax. ( C – F ) Real-time qPCR amplification of selected HL miRNAs and mRNAs. Total RNA including small RNA was extracted from HL samples and analyzed with qPCR to measure the levels of miRNAs and mRNAs. The y -axis represents the relative fluorescence units (RFU) in a semi-log scale. The x -axis represents the cycle at which fluorescence was detected above an automatically determined threshold. ( C ) Amplification plots for miR-14, miR-8, and miR-184 measured in a representative HL sample. ( D ) Amplification plots for miR-14, let-7, bantam, and spiked-in synthetic C. elegans cel-miR-39 RNA in representative HL sample. ( E ) The amplification plots for tubulin, actin, and gapdh mRNAs determined by qPCR using total RNA from HL and S2 cells. Sample from S2 cells are used as a positive control for detecting Drosophila mRNAs by qPCR. The amplification curves of all three mRNAs are superimposed on one another, reflecting the presence of similar amounts of these mRNA in S2 cells. Amplification curves from HL samples show that fluorescent products appear after about 30 cycles, reflecting the significantly lower abundance of these mRNAs in HL relative to S2 cells. ( F ) The cycle threshold (Ct) fold-change of selected miRNA amplified in the absence or presence of RNase A and DNase I. Total RNA was extracted from HL samples spiked with 10 fmoles of cel-miR-39 RNA. The x -axis represents the ratio of raw Ct values from control samples divided by raw Ct values from samples incubated with RNase A and DNase I. The significantly higher magnitude of the Ct fold change of the spiked-in synthetic miRNA relative to those of the miRNA indicates that the HL-miRNA are present in nuclease-resistant, stable form.
    Figure Legend Snippet: Presence of stable miRNAs in Drosophila melanogaster hemolymph. ( A , B ) Clear HL droplets extruded from fly head and thorax. ( C – F ) Real-time qPCR amplification of selected HL miRNAs and mRNAs. Total RNA including small RNA was extracted from HL samples and analyzed with qPCR to measure the levels of miRNAs and mRNAs. The y -axis represents the relative fluorescence units (RFU) in a semi-log scale. The x -axis represents the cycle at which fluorescence was detected above an automatically determined threshold. ( C ) Amplification plots for miR-14, miR-8, and miR-184 measured in a representative HL sample. ( D ) Amplification plots for miR-14, let-7, bantam, and spiked-in synthetic C. elegans cel-miR-39 RNA in representative HL sample. ( E ) The amplification plots for tubulin, actin, and gapdh mRNAs determined by qPCR using total RNA from HL and S2 cells. Sample from S2 cells are used as a positive control for detecting Drosophila mRNAs by qPCR. The amplification curves of all three mRNAs are superimposed on one another, reflecting the presence of similar amounts of these mRNA in S2 cells. Amplification curves from HL samples show that fluorescent products appear after about 30 cycles, reflecting the significantly lower abundance of these mRNAs in HL relative to S2 cells. ( F ) The cycle threshold (Ct) fold-change of selected miRNA amplified in the absence or presence of RNase A and DNase I. Total RNA was extracted from HL samples spiked with 10 fmoles of cel-miR-39 RNA. The x -axis represents the ratio of raw Ct values from control samples divided by raw Ct values from samples incubated with RNase A and DNase I. The significantly higher magnitude of the Ct fold change of the spiked-in synthetic miRNA relative to those of the miRNA indicates that the HL-miRNA are present in nuclease-resistant, stable form.

    Techniques Used: Real-time Polymerase Chain Reaction, Amplification, Fluorescence, Positive Control, Incubation

    Outline of the experimental design and workflow for the integrated analysis of the miRNA-Seq and mRNA-Seq data. Genes that are potentially regulated by the HL-miRNAs were determined by integrating miRNA-Seq and mRNA-Seq data using the following three steps: Step 1 (depicted in green): After identifying the HL-miRNAs enriched relative to BT in either young or old, or both young and old ( Tables 1 and 2 ), we retrieved their computationally predicted target genes from the m 3 RNA database ( http://m3rna.cnb.csic.es ). Step 2 (depicted in blue): mRNA-Seq was utilized to identify three groups of genes that were differentially expressed with age, either upregulated, downregulated, or unchanged in BT. Step 3 (depicted in red): The three groups of genes predicted in step1 as targets of HL-miRNAs were intersected with the three groups of genes identified in step 2. In the figure, ( A ) depicts the derivation of genes that are predicted to be targets of HL-miRNAs enriched in young which are also upregulated with age in BT. These genes (Supplementary Table 1 ) are likely upregulated in BT of old flies because their expression is no longer repressed by HL-miRNAs that are enriched only in young flies. ( B ) Depicts the derivation of genes which are the predicted to be targets of HL-miRNAs enriched in old which are also downregulated with age in BT. These genes (Supplementary Table 2 ) are likely downregulated in BT of old flies because their expression is repressed by HL-miRNAs which are enriched only in old flies. ( C ) Depicts the derivation of genes which are predicted to be targets of HL-miRNAs enriched in both young and old which also do not change expression with age in BT. These genes (Supplementary Table 3) do not change expression with age because the concentration of their regulatory miRNAs in HL does not change with age.
    Figure Legend Snippet: Outline of the experimental design and workflow for the integrated analysis of the miRNA-Seq and mRNA-Seq data. Genes that are potentially regulated by the HL-miRNAs were determined by integrating miRNA-Seq and mRNA-Seq data using the following three steps: Step 1 (depicted in green): After identifying the HL-miRNAs enriched relative to BT in either young or old, or both young and old ( Tables 1 and 2 ), we retrieved their computationally predicted target genes from the m 3 RNA database ( http://m3rna.cnb.csic.es ). Step 2 (depicted in blue): mRNA-Seq was utilized to identify three groups of genes that were differentially expressed with age, either upregulated, downregulated, or unchanged in BT. Step 3 (depicted in red): The three groups of genes predicted in step1 as targets of HL-miRNAs were intersected with the three groups of genes identified in step 2. In the figure, ( A ) depicts the derivation of genes that are predicted to be targets of HL-miRNAs enriched in young which are also upregulated with age in BT. These genes (Supplementary Table 1 ) are likely upregulated in BT of old flies because their expression is no longer repressed by HL-miRNAs that are enriched only in young flies. ( B ) Depicts the derivation of genes which are the predicted to be targets of HL-miRNAs enriched in old which are also downregulated with age in BT. These genes (Supplementary Table 2 ) are likely downregulated in BT of old flies because their expression is repressed by HL-miRNAs which are enriched only in old flies. ( C ) Depicts the derivation of genes which are predicted to be targets of HL-miRNAs enriched in both young and old which also do not change expression with age in BT. These genes (Supplementary Table 3) do not change expression with age because the concentration of their regulatory miRNAs in HL does not change with age.

    Techniques Used: Expressing, Concentration Assay

    6) Product Images from "Identification of a novel β-adrenergic octopamine receptor-like gene (βAOR-like) and increased ATP-binding cassette B10 (ABCB10) expression in a Rhipicephalus microplus cell line derived from acaricide-resistant ticks"

    Article Title: Identification of a novel β-adrenergic octopamine receptor-like gene (βAOR-like) and increased ATP-binding cassette B10 (ABCB10) expression in a Rhipicephalus microplus cell line derived from acaricide-resistant ticks

    Journal: Parasites & Vectors

    doi: 10.1186/s13071-016-1708-x

    βAOR PCR in Rhipicephalus cell lines. a Detection of βAOR in genomic DNA (gDNA) and complementary DNA (cDNA) of Rhipicephalus microplus cell lines. The expected amplicon of 183 bp was detected in gDNA and cDNA of cell lines BME/CTVM2 (2), BME/CTVM5 (5), BME/CTVM23 (23), BME/CTVM30 (30) and BmVIII-SCC (SCC). BME/CTVM6 (6) gave an alternative amplicon of ~220 bp from both gDNA and cDNA. Additional amplicons of ~245 bp and ~220 bp were also detected in gDNA of BME/CTVM5. b Detection of βAOR in gDNA and cDNA of other tick cell lines. The expected amplicon was detected in gDNA and cDNA of cell lines RAN/CTVM3 (RAN), REN/CTVM32 (REN), RSE/PILS35 (RSE) and RA243, and only in gDNA of RML-RSE (RML). No βAOR gene or transcript was detected in cell lines AVL/CTVM13 (AVL), HAE/CTVM9 (HAE) or IRE/CTVM19 (IRE). Abbreviations : M, Marker; NTC, Non-template control; −ve, reverse transcription negative control
    Figure Legend Snippet: βAOR PCR in Rhipicephalus cell lines. a Detection of βAOR in genomic DNA (gDNA) and complementary DNA (cDNA) of Rhipicephalus microplus cell lines. The expected amplicon of 183 bp was detected in gDNA and cDNA of cell lines BME/CTVM2 (2), BME/CTVM5 (5), BME/CTVM23 (23), BME/CTVM30 (30) and BmVIII-SCC (SCC). BME/CTVM6 (6) gave an alternative amplicon of ~220 bp from both gDNA and cDNA. Additional amplicons of ~245 bp and ~220 bp were also detected in gDNA of BME/CTVM5. b Detection of βAOR in gDNA and cDNA of other tick cell lines. The expected amplicon was detected in gDNA and cDNA of cell lines RAN/CTVM3 (RAN), REN/CTVM32 (REN), RSE/PILS35 (RSE) and RA243, and only in gDNA of RML-RSE (RML). No βAOR gene or transcript was detected in cell lines AVL/CTVM13 (AVL), HAE/CTVM9 (HAE) or IRE/CTVM19 (IRE). Abbreviations : M, Marker; NTC, Non-template control; −ve, reverse transcription negative control

    Techniques Used: Polymerase Chain Reaction, Amplification, Marker, Negative Control

    7) Product Images from "Establishment of a Predictive In Vitro Assay for Assessment of the Hepatotoxic Potential of Oligonucleotide Drugs"

    Article Title: Establishment of a Predictive In Vitro Assay for Assessment of the Hepatotoxic Potential of Oligonucleotide Drugs

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0159431

    miR-122 release. (A) Mouse hepatocyte-NPC co-cultures or (B) hepatocyte monocultures were treated with the respective SSOs for 48 or 64 hours and cell-free supernatant was collected. The levels of miR-122 at 48 h and 64 h were assessed using real-time qPCR. miRNA levels were normalized to vehicle treated cells. Data are means ± SD.
    Figure Legend Snippet: miR-122 release. (A) Mouse hepatocyte-NPC co-cultures or (B) hepatocyte monocultures were treated with the respective SSOs for 48 or 64 hours and cell-free supernatant was collected. The levels of miR-122 at 48 h and 64 h were assessed using real-time qPCR. miRNA levels were normalized to vehicle treated cells. Data are means ± SD.

    Techniques Used: Real-time Polymerase Chain Reaction

    8) Product Images from "Curcumin targets the TFEB-lysosome pathway for induction of autophagy"

    Article Title: Curcumin targets the TFEB-lysosome pathway for induction of autophagy

    Journal: Oncotarget

    doi: 10.18632/oncotarget.12318

    Curcumin directly targets TFEB for activation A. HCT116 cells were treated with 10 μM Curcumin for 12 hours and cell lysates were prepared followed by immunoblotting for TFEB and β-actin (up panel). HCT116 cells were labeled with Curcumin-probe (30 μM) for 4 hours and western blotting was performed to validate Curcumin-probe targeted TFEB (down panel). B. Enhanced TFEB nuclear translocation in response to Curcumin treatment (10 μM; 12 hours). Live imaging of GFP-TFEB (green) and DAPI (blue) in HCT116 cells showed an enrichment of the GFP-TFEB signal in the nuclear. Five fields containing 20 to 30 cells were analyzed for TFEB nuclear localization. Scale bar, 10 μm. C. HCT116 cells were treated with 10 μM Curcumin as indicated. Cytosolic and nuclear fraction from control and Curcumin-treated cells were probed for TFEB. The same membrane was then stripped and reprobed for α-tubulin or Lamin AC as loading control. D. HCT116 cells were transient transfected with the TFEB-3x Flag (kindly provided by Dr. A Ballabio) and then treated with 10 μM Curcumin for 12 hours. Cells were lysed and subjected to immunoprecipitation with anti-FLAG antibody followed by immunoblotting for 14-3-3. TFEB was also determined using anti-FLAG antibody. E. HCT116 cells were transiently transfected with the TFEB-luc reporter construct (kindly provided by Dr. A Ballabio). After 24 hours, the cells were treated with Curcumin (10 μM) for another 12 hours and the relative luciferase activity was measured. RLU refers to relative luciferase units. Error bars represent the standard deviation from two independent experiments. F. HCT116 cells were treated with Curcumin (10 μM) for 12 hours and cells were harvested for RNA extraction. Real-time PCR was performed to determine mRNA level changes in the known TFEB target genes, such as Lamp1, Atp6v1a, Uvrag and Atg9b . Gapdh was used as a loading control. All values are means ± SD at least 3 independent experiments. Student's t test, * P
    Figure Legend Snippet: Curcumin directly targets TFEB for activation A. HCT116 cells were treated with 10 μM Curcumin for 12 hours and cell lysates were prepared followed by immunoblotting for TFEB and β-actin (up panel). HCT116 cells were labeled with Curcumin-probe (30 μM) for 4 hours and western blotting was performed to validate Curcumin-probe targeted TFEB (down panel). B. Enhanced TFEB nuclear translocation in response to Curcumin treatment (10 μM; 12 hours). Live imaging of GFP-TFEB (green) and DAPI (blue) in HCT116 cells showed an enrichment of the GFP-TFEB signal in the nuclear. Five fields containing 20 to 30 cells were analyzed for TFEB nuclear localization. Scale bar, 10 μm. C. HCT116 cells were treated with 10 μM Curcumin as indicated. Cytosolic and nuclear fraction from control and Curcumin-treated cells were probed for TFEB. The same membrane was then stripped and reprobed for α-tubulin or Lamin AC as loading control. D. HCT116 cells were transient transfected with the TFEB-3x Flag (kindly provided by Dr. A Ballabio) and then treated with 10 μM Curcumin for 12 hours. Cells were lysed and subjected to immunoprecipitation with anti-FLAG antibody followed by immunoblotting for 14-3-3. TFEB was also determined using anti-FLAG antibody. E. HCT116 cells were transiently transfected with the TFEB-luc reporter construct (kindly provided by Dr. A Ballabio). After 24 hours, the cells were treated with Curcumin (10 μM) for another 12 hours and the relative luciferase activity was measured. RLU refers to relative luciferase units. Error bars represent the standard deviation from two independent experiments. F. HCT116 cells were treated with Curcumin (10 μM) for 12 hours and cells were harvested for RNA extraction. Real-time PCR was performed to determine mRNA level changes in the known TFEB target genes, such as Lamp1, Atp6v1a, Uvrag and Atg9b . Gapdh was used as a loading control. All values are means ± SD at least 3 independent experiments. Student's t test, * P

    Techniques Used: Activation Assay, Labeling, Western Blot, Translocation Assay, Imaging, Transfection, Immunoprecipitation, Construct, Luciferase, Activity Assay, Standard Deviation, RNA Extraction, Real-time Polymerase Chain Reaction

    9) Product Images from "CD63, MHC class 1, and CD47 identify subsets of extracellular vesicles containing distinct populations of noncoding RNAs"

    Article Title: CD63, MHC class 1, and CD47 identify subsets of extracellular vesicles containing distinct populations of noncoding RNAs

    Journal: Scientific Reports

    doi: 10.1038/s41598-018-20936-7

    RNAs enriched in CD47 + EVs. Analysis of specific classes of RNAs in the 272 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in CD47 + EVs versus CD47 − EVs from the scatter graph in Fig. 3a . A table was generated for each type of enriched RNA in CD47 + EV samples. (a) log 2 total RPM values are plotted for the indicated snoRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (c) Log 2 RPM values are plotted for the indicated lncRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (d) Log 2 total RPM values are plotted for the indicated mitochondrial and other RNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. Blue stars indicate RNAs that are also enriched in CD63 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.
    Figure Legend Snippet: RNAs enriched in CD47 + EVs. Analysis of specific classes of RNAs in the 272 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in CD47 + EVs versus CD47 − EVs from the scatter graph in Fig. 3a . A table was generated for each type of enriched RNA in CD47 + EV samples. (a) log 2 total RPM values are plotted for the indicated snoRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (c) Log 2 RPM values are plotted for the indicated lncRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (d) Log 2 total RPM values are plotted for the indicated mitochondrial and other RNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. Blue stars indicate RNAs that are also enriched in CD63 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.

    Techniques Used: Generated

    Noncoding RNA content of CD47 + , CD63 + and MHC1 + captured EVs versus the respective uncaptured EVs. ( a–c ) Individual classes of noncoding RNAs were extracted from linear total RPKM Gene Table by name and a table was generated for each type of RNA. The cutoff threshold 0.02 log2 total RPKM was used to filter RNAs isolated from CD47 + , CD63 + and MHC1 + EVs, and the numbers of mapped genes in each class are shown in pie charts. (d–f) Similarly, the number and type of non-coding RNAs identified in CD47 − , CD63 − and MHC1 − EVs and are shown as pie charts. Abbreviations: PIWI RNA, piwi-interacting RNA; Y-RNA, small non-coding RNA components of the Ro ribonucleoprotein particle; MT-RNA, mitochondrial RNA; SRP RNA, signal recognition particle RNA; Vault RNA RNA family of the vault ribonucleoprotein complex; SCA RNA, small Cajal body-specific RNA; SnRNA, small nuclear RNA; lncRNA, long non-coding RNA; SnoRNA, small nucleolar RNAs; RPRNA, ribosomal protein RNA; tRNA, transfer RNA; LOCRNA, nonannotated gene transcripts.
    Figure Legend Snippet: Noncoding RNA content of CD47 + , CD63 + and MHC1 + captured EVs versus the respective uncaptured EVs. ( a–c ) Individual classes of noncoding RNAs were extracted from linear total RPKM Gene Table by name and a table was generated for each type of RNA. The cutoff threshold 0.02 log2 total RPKM was used to filter RNAs isolated from CD47 + , CD63 + and MHC1 + EVs, and the numbers of mapped genes in each class are shown in pie charts. (d–f) Similarly, the number and type of non-coding RNAs identified in CD47 − , CD63 − and MHC1 − EVs and are shown as pie charts. Abbreviations: PIWI RNA, piwi-interacting RNA; Y-RNA, small non-coding RNA components of the Ro ribonucleoprotein particle; MT-RNA, mitochondrial RNA; SRP RNA, signal recognition particle RNA; Vault RNA RNA family of the vault ribonucleoprotein complex; SCA RNA, small Cajal body-specific RNA; SnRNA, small nuclear RNA; lncRNA, long non-coding RNA; SnoRNA, small nucleolar RNAs; RPRNA, ribosomal protein RNA; tRNA, transfer RNA; LOCRNA, nonannotated gene transcripts.

    Techniques Used: Generated, Isolation

    Validation of small RNA enrichment in CD47 + , CD63 + and MHC1 + captured EVs. ( a,b ) Validation of tRNAs using rtStar™ Pre-designed Human tRNA primer sets for TRE-CTC, TRR-CCG and internal spike control using total RNA from captured and uncaptured CD63 and MHC1 EVs. ( c ) The table presents RPM of SnoRNAs in CD47 + , CD63 + , and MHC1 + EVs. ( d ) Expression of SNHG5, SNHG10 and SNORDA116@ snoRNAs using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via TaqMan real-time PCR. (e) U6 using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via real-time PCR. ( f ) snRNA expression of RNU6ATAC using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via TaqMan assay. ( g,h ) miRNA expression of mir-320a and mir-320b using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs determined using real-time PCR.
    Figure Legend Snippet: Validation of small RNA enrichment in CD47 + , CD63 + and MHC1 + captured EVs. ( a,b ) Validation of tRNAs using rtStar™ Pre-designed Human tRNA primer sets for TRE-CTC, TRR-CCG and internal spike control using total RNA from captured and uncaptured CD63 and MHC1 EVs. ( c ) The table presents RPM of SnoRNAs in CD47 + , CD63 + , and MHC1 + EVs. ( d ) Expression of SNHG5, SNHG10 and SNORDA116@ snoRNAs using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via TaqMan real-time PCR. (e) U6 using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via real-time PCR. ( f ) snRNA expression of RNU6ATAC using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via TaqMan assay. ( g,h ) miRNA expression of mir-320a and mir-320b using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs determined using real-time PCR.

    Techniques Used: Expressing, Real-time Polymerase Chain Reaction, TaqMan Assay

    Micro-RNA enrichment in captured EVs determined by microarray analysis. (a) Preparation of CD47 + and CD63 + EVs for miRNA microarray analysis. (b) Hierarchical clustering of human miRNAs identifies differential expression between CD47 +b and CD47 −b EVs (Student-t test). (c) Heat map of hierarchical clustering Human miRNA differentially expressed between CD63 +b /CD63 −b EVs. (d) The table presents enriched hsa-miRNAs in CD47 + EVs. (e) The table presents enriched hsa-miRNAs in CD63 + EVs.
    Figure Legend Snippet: Micro-RNA enrichment in captured EVs determined by microarray analysis. (a) Preparation of CD47 + and CD63 + EVs for miRNA microarray analysis. (b) Hierarchical clustering of human miRNAs identifies differential expression between CD47 +b and CD47 −b EVs (Student-t test). (c) Heat map of hierarchical clustering Human miRNA differentially expressed between CD63 +b /CD63 −b EVs. (d) The table presents enriched hsa-miRNAs in CD47 + EVs. (e) The table presents enriched hsa-miRNAs in CD63 + EVs.

    Techniques Used: Microarray, Expressing

    Micro-RNA enrichment in captured EVs determined by RNAseq. (a) Heat map of hierarchical clustering of 109 miRNAs (All species) differentially enriched in CD47 + versus CD47 − EVs at p
    Figure Legend Snippet: Micro-RNA enrichment in captured EVs determined by RNAseq. (a) Heat map of hierarchical clustering of 109 miRNAs (All species) differentially enriched in CD47 + versus CD47 − EVs at p

    Techniques Used:

    Differential enrichment of miRNAs in CD47 + , CD63 + and MHC1 + EVs. (a) Hierarchical clustering of 208 miRNAs (p
    Figure Legend Snippet: Differential enrichment of miRNAs in CD47 + , CD63 + and MHC1 + EVs. (a) Hierarchical clustering of 208 miRNAs (p

    Techniques Used:

    Enrichment of small RNAs in antibody captured EVs. (a) Scatter graph of data from 3 biological replicates comparing RNA abundance in CD47 + and CD47 − EVs. A total of 680 transcripts were significantly enriched or depleted in captured EVs (CD47_CAP) versus uncaptured EVs (CD47_UnCap, p
    Figure Legend Snippet: Enrichment of small RNAs in antibody captured EVs. (a) Scatter graph of data from 3 biological replicates comparing RNA abundance in CD47 + and CD47 − EVs. A total of 680 transcripts were significantly enriched or depleted in captured EVs (CD47_CAP) versus uncaptured EVs (CD47_UnCap, p

    Techniques Used:

    RNAs enriched in CD63 + EVs. Analysis of specific classes of RNAs in the 271 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in CD63 + EVs versus CD63 - EVs were extracted from the scatter graph in Fig. 3b . A table was generated for each type of upregulated RNAs of captured CD63 + EVs. (a) Log 2 total RPM values are plotted for the indicated snoRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (c) Log 2 total RPM values are plotted for the indicated lncRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (d) Log 2 total RPM values are plotted for the indicated small nuclear RNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. Blue stars indicate RNAs that are also enriched in CD47 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.
    Figure Legend Snippet: RNAs enriched in CD63 + EVs. Analysis of specific classes of RNAs in the 271 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in CD63 + EVs versus CD63 - EVs were extracted from the scatter graph in Fig. 3b . A table was generated for each type of upregulated RNAs of captured CD63 + EVs. (a) Log 2 total RPM values are plotted for the indicated snoRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (c) Log 2 total RPM values are plotted for the indicated lncRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (d) Log 2 total RPM values are plotted for the indicated small nuclear RNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. Blue stars indicate RNAs that are also enriched in CD47 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.

    Techniques Used: Generated

    Characterization of Jurkat T cell EV fractions and CD47 expression. (a,b) EVs were extracted from wild type ( a ) and CD47-deficient Jurkat T cells ( b ) using the Exo-Quick kit, and vesicle size and concentration were quantified by Nanosight analysis. ( c) EVs released by Jurkat cells were labeled using Bodipy-FL and captured with anti-CD63-MNPs (upper panel) or with anti-MHC I-MNPs (lower panel) and stained with PE-conjugated anti-CD47 or isotype control antibodies. Representative experiment out of 3. ( d) EVs released by CD47-deficient JinB8 cells were captured with anti-CD63-MNPs (upper panel) or with anti-MHC I-MNPs (lower panel) and stained with anti-CD47 or with isotype control antibodies. Representative experiment of out of 3. ( e ) Size distribution of CD47 + EVs captured with anti-CD63-MNPs (red bars) or with anti-MHC1-MNPs (black bars). Representative experiment out of 3. (f) EVs released by Jurkat cells were captured with anti-CD47-MNPs and stained for CD63 antigen. Volumetric control was used to estimate concentration of CD47 + CD63 + EVs. One representative experiment is presented out of 2 performed.
    Figure Legend Snippet: Characterization of Jurkat T cell EV fractions and CD47 expression. (a,b) EVs were extracted from wild type ( a ) and CD47-deficient Jurkat T cells ( b ) using the Exo-Quick kit, and vesicle size and concentration were quantified by Nanosight analysis. ( c) EVs released by Jurkat cells were labeled using Bodipy-FL and captured with anti-CD63-MNPs (upper panel) or with anti-MHC I-MNPs (lower panel) and stained with PE-conjugated anti-CD47 or isotype control antibodies. Representative experiment out of 3. ( d) EVs released by CD47-deficient JinB8 cells were captured with anti-CD63-MNPs (upper panel) or with anti-MHC I-MNPs (lower panel) and stained with anti-CD47 or with isotype control antibodies. Representative experiment of out of 3. ( e ) Size distribution of CD47 + EVs captured with anti-CD63-MNPs (red bars) or with anti-MHC1-MNPs (black bars). Representative experiment out of 3. (f) EVs released by Jurkat cells were captured with anti-CD47-MNPs and stained for CD63 antigen. Volumetric control was used to estimate concentration of CD47 + CD63 + EVs. One representative experiment is presented out of 2 performed.

    Techniques Used: Expressing, Concentration Assay, Labeling, Staining

    RNAs enriched in MHC1 + EVs. Analysis of specific classes of RNAs in the 268 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in MHC1 + EVs versus MHC1 − EVs were extracted from the scatter graph in Fig. 3c . A table was generated for each type of upregulated RNAs of captured MHC1 + EVs. (a) Log 2 total RPM values are plotted for the indicated snoRNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (c) Log 2 total RPM values are plotted for the indicated lncRNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (d) Log 2 total RPM values are plotted for the indicated small nuclear RNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. Blue stars indicate RNAs that are also enriched in CD63 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.
    Figure Legend Snippet: RNAs enriched in MHC1 + EVs. Analysis of specific classes of RNAs in the 268 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in MHC1 + EVs versus MHC1 − EVs were extracted from the scatter graph in Fig. 3c . A table was generated for each type of upregulated RNAs of captured MHC1 + EVs. (a) Log 2 total RPM values are plotted for the indicated snoRNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (c) Log 2 total RPM values are plotted for the indicated lncRNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (d) Log 2 total RPM values are plotted for the indicated small nuclear RNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. Blue stars indicate RNAs that are also enriched in CD63 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.

    Techniques Used: Generated

    10) Product Images from "CD63, MHC class 1, and CD47 identify subsets of extracellular vesicles containing distinct populations of noncoding RNAs"

    Article Title: CD63, MHC class 1, and CD47 identify subsets of extracellular vesicles containing distinct populations of noncoding RNAs

    Journal: Scientific Reports

    doi: 10.1038/s41598-018-20936-7

    RNAs enriched in CD47 + EVs. Analysis of specific classes of RNAs in the 272 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in CD47 + EVs versus CD47 − EVs from the scatter graph in Fig. 3a . A table was generated for each type of enriched RNA in CD47 + EV samples. (a) log 2 total RPM values are plotted for the indicated snoRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (c) Log 2 RPM values are plotted for the indicated lncRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (d) Log 2 total RPM values are plotted for the indicated mitochondrial and other RNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. Blue stars indicate RNAs that are also enriched in CD63 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.
    Figure Legend Snippet: RNAs enriched in CD47 + EVs. Analysis of specific classes of RNAs in the 272 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in CD47 + EVs versus CD47 − EVs from the scatter graph in Fig. 3a . A table was generated for each type of enriched RNA in CD47 + EV samples. (a) log 2 total RPM values are plotted for the indicated snoRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (c) Log 2 RPM values are plotted for the indicated lncRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (d) Log 2 total RPM values are plotted for the indicated mitochondrial and other RNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. Blue stars indicate RNAs that are also enriched in CD63 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.

    Techniques Used: Generated

    Noncoding RNA content of CD47 + , CD63 + and MHC1 + captured EVs versus the respective uncaptured EVs. ( a–c ) Individual classes of noncoding RNAs were extracted from linear total RPKM Gene Table by name and a table was generated for each type of RNA. The cutoff threshold 0.02 log2 total RPKM was used to filter RNAs isolated from CD47 + , CD63 + and MHC1 + EVs, and the numbers of mapped genes in each class are shown in pie charts. (d–f) Similarly, the number and type of non-coding RNAs identified in CD47 − , CD63 − and MHC1 − EVs and are shown as pie charts. Abbreviations: PIWI RNA, piwi-interacting RNA; Y-RNA, small non-coding RNA components of the Ro ribonucleoprotein particle; MT-RNA, mitochondrial RNA; SRP RNA, signal recognition particle RNA; Vault RNA RNA family of the vault ribonucleoprotein complex; SCA RNA, small Cajal body-specific RNA; SnRNA, small nuclear RNA; lncRNA, long non-coding RNA; SnoRNA, small nucleolar RNAs; RPRNA, ribosomal protein RNA; tRNA, transfer RNA; LOCRNA, nonannotated gene transcripts.
    Figure Legend Snippet: Noncoding RNA content of CD47 + , CD63 + and MHC1 + captured EVs versus the respective uncaptured EVs. ( a–c ) Individual classes of noncoding RNAs were extracted from linear total RPKM Gene Table by name and a table was generated for each type of RNA. The cutoff threshold 0.02 log2 total RPKM was used to filter RNAs isolated from CD47 + , CD63 + and MHC1 + EVs, and the numbers of mapped genes in each class are shown in pie charts. (d–f) Similarly, the number and type of non-coding RNAs identified in CD47 − , CD63 − and MHC1 − EVs and are shown as pie charts. Abbreviations: PIWI RNA, piwi-interacting RNA; Y-RNA, small non-coding RNA components of the Ro ribonucleoprotein particle; MT-RNA, mitochondrial RNA; SRP RNA, signal recognition particle RNA; Vault RNA RNA family of the vault ribonucleoprotein complex; SCA RNA, small Cajal body-specific RNA; SnRNA, small nuclear RNA; lncRNA, long non-coding RNA; SnoRNA, small nucleolar RNAs; RPRNA, ribosomal protein RNA; tRNA, transfer RNA; LOCRNA, nonannotated gene transcripts.

    Techniques Used: Generated, Isolation

    Validation of small RNA enrichment in CD47 + , CD63 + and MHC1 + captured EVs. ( a,b ) Validation of tRNAs using rtStar™ Pre-designed Human tRNA primer sets for TRE-CTC, TRR-CCG and internal spike control using total RNA from captured and uncaptured CD63 and MHC1 EVs. ( c ) The table presents RPM of SnoRNAs in CD47 + , CD63 + , and MHC1 + EVs. ( d ) Expression of SNHG5, SNHG10 and SNORDA116@ snoRNAs using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via TaqMan real-time PCR. (e) U6 using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via real-time PCR. ( f ) snRNA expression of RNU6ATAC using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via TaqMan assay. ( g,h ) miRNA expression of mir-320a and mir-320b using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs determined using real-time PCR.
    Figure Legend Snippet: Validation of small RNA enrichment in CD47 + , CD63 + and MHC1 + captured EVs. ( a,b ) Validation of tRNAs using rtStar™ Pre-designed Human tRNA primer sets for TRE-CTC, TRR-CCG and internal spike control using total RNA from captured and uncaptured CD63 and MHC1 EVs. ( c ) The table presents RPM of SnoRNAs in CD47 + , CD63 + , and MHC1 + EVs. ( d ) Expression of SNHG5, SNHG10 and SNORDA116@ snoRNAs using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via TaqMan real-time PCR. (e) U6 using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via real-time PCR. ( f ) snRNA expression of RNU6ATAC using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via TaqMan assay. ( g,h ) miRNA expression of mir-320a and mir-320b using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs determined using real-time PCR.

    Techniques Used: Expressing, Real-time Polymerase Chain Reaction, TaqMan Assay

    Micro-RNA enrichment in captured EVs determined by microarray analysis. (a) Preparation of CD47 + and CD63 + EVs for miRNA microarray analysis. (b) Hierarchical clustering of human miRNAs identifies differential expression between CD47 +b and CD47 −b EVs (Student-t test). (c) Heat map of hierarchical clustering Human miRNA differentially expressed between CD63 +b /CD63 −b EVs. (d) The table presents enriched hsa-miRNAs in CD47 + EVs. (e) The table presents enriched hsa-miRNAs in CD63 + EVs.
    Figure Legend Snippet: Micro-RNA enrichment in captured EVs determined by microarray analysis. (a) Preparation of CD47 + and CD63 + EVs for miRNA microarray analysis. (b) Hierarchical clustering of human miRNAs identifies differential expression between CD47 +b and CD47 −b EVs (Student-t test). (c) Heat map of hierarchical clustering Human miRNA differentially expressed between CD63 +b /CD63 −b EVs. (d) The table presents enriched hsa-miRNAs in CD47 + EVs. (e) The table presents enriched hsa-miRNAs in CD63 + EVs.

    Techniques Used: Microarray, Expressing

    Micro-RNA enrichment in captured EVs determined by RNAseq. (a) Heat map of hierarchical clustering of 109 miRNAs (All species) differentially enriched in CD47 + versus CD47 − EVs at p
    Figure Legend Snippet: Micro-RNA enrichment in captured EVs determined by RNAseq. (a) Heat map of hierarchical clustering of 109 miRNAs (All species) differentially enriched in CD47 + versus CD47 − EVs at p

    Techniques Used:

    Differential enrichment of miRNAs in CD47 + , CD63 + and MHC1 + EVs. (a) Hierarchical clustering of 208 miRNAs (p
    Figure Legend Snippet: Differential enrichment of miRNAs in CD47 + , CD63 + and MHC1 + EVs. (a) Hierarchical clustering of 208 miRNAs (p

    Techniques Used:

    Enrichment of small RNAs in antibody captured EVs. (a) Scatter graph of data from 3 biological replicates comparing RNA abundance in CD47 + and CD47 − EVs. A total of 680 transcripts were significantly enriched or depleted in captured EVs (CD47_CAP) versus uncaptured EVs (CD47_UnCap, p
    Figure Legend Snippet: Enrichment of small RNAs in antibody captured EVs. (a) Scatter graph of data from 3 biological replicates comparing RNA abundance in CD47 + and CD47 − EVs. A total of 680 transcripts were significantly enriched or depleted in captured EVs (CD47_CAP) versus uncaptured EVs (CD47_UnCap, p

    Techniques Used:

    RNAs enriched in CD63 + EVs. Analysis of specific classes of RNAs in the 271 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in CD63 + EVs versus CD63 - EVs were extracted from the scatter graph in Fig. 3b . A table was generated for each type of upregulated RNAs of captured CD63 + EVs. (a) Log 2 total RPM values are plotted for the indicated snoRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (c) Log 2 total RPM values are plotted for the indicated lncRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (d) Log 2 total RPM values are plotted for the indicated small nuclear RNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. Blue stars indicate RNAs that are also enriched in CD47 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.
    Figure Legend Snippet: RNAs enriched in CD63 + EVs. Analysis of specific classes of RNAs in the 271 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in CD63 + EVs versus CD63 - EVs were extracted from the scatter graph in Fig. 3b . A table was generated for each type of upregulated RNAs of captured CD63 + EVs. (a) Log 2 total RPM values are plotted for the indicated snoRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (c) Log 2 total RPM values are plotted for the indicated lncRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (d) Log 2 total RPM values are plotted for the indicated small nuclear RNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. Blue stars indicate RNAs that are also enriched in CD47 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.

    Techniques Used: Generated

    Characterization of Jurkat T cell EV fractions and CD47 expression. (a,b) EVs were extracted from wild type ( a ) and CD47-deficient Jurkat T cells ( b ) using the Exo-Quick kit, and vesicle size and concentration were quantified by Nanosight analysis. ( c) EVs released by Jurkat cells were labeled using Bodipy-FL and captured with anti-CD63-MNPs (upper panel) or with anti-MHC I-MNPs (lower panel) and stained with PE-conjugated anti-CD47 or isotype control antibodies. Representative experiment out of 3. ( d) EVs released by CD47-deficient JinB8 cells were captured with anti-CD63-MNPs (upper panel) or with anti-MHC I-MNPs (lower panel) and stained with anti-CD47 or with isotype control antibodies. Representative experiment of out of 3. ( e ) Size distribution of CD47 + EVs captured with anti-CD63-MNPs (red bars) or with anti-MHC1-MNPs (black bars). Representative experiment out of 3. (f) EVs released by Jurkat cells were captured with anti-CD47-MNPs and stained for CD63 antigen. Volumetric control was used to estimate concentration of CD47 + CD63 + EVs. One representative experiment is presented out of 2 performed.
    Figure Legend Snippet: Characterization of Jurkat T cell EV fractions and CD47 expression. (a,b) EVs were extracted from wild type ( a ) and CD47-deficient Jurkat T cells ( b ) using the Exo-Quick kit, and vesicle size and concentration were quantified by Nanosight analysis. ( c) EVs released by Jurkat cells were labeled using Bodipy-FL and captured with anti-CD63-MNPs (upper panel) or with anti-MHC I-MNPs (lower panel) and stained with PE-conjugated anti-CD47 or isotype control antibodies. Representative experiment out of 3. ( d) EVs released by CD47-deficient JinB8 cells were captured with anti-CD63-MNPs (upper panel) or with anti-MHC I-MNPs (lower panel) and stained with anti-CD47 or with isotype control antibodies. Representative experiment of out of 3. ( e ) Size distribution of CD47 + EVs captured with anti-CD63-MNPs (red bars) or with anti-MHC1-MNPs (black bars). Representative experiment out of 3. (f) EVs released by Jurkat cells were captured with anti-CD47-MNPs and stained for CD63 antigen. Volumetric control was used to estimate concentration of CD47 + CD63 + EVs. One representative experiment is presented out of 2 performed.

    Techniques Used: Expressing, Concentration Assay, Labeling, Staining

    RNAs enriched in MHC1 + EVs. Analysis of specific classes of RNAs in the 268 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in MHC1 + EVs versus MHC1 − EVs were extracted from the scatter graph in Fig. 3c . A table was generated for each type of upregulated RNAs of captured MHC1 + EVs. (a) Log 2 total RPM values are plotted for the indicated snoRNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (c) Log 2 total RPM values are plotted for the indicated lncRNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (d) Log 2 total RPM values are plotted for the indicated small nuclear RNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. Blue stars indicate RNAs that are also enriched in CD63 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.
    Figure Legend Snippet: RNAs enriched in MHC1 + EVs. Analysis of specific classes of RNAs in the 268 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in MHC1 + EVs versus MHC1 − EVs were extracted from the scatter graph in Fig. 3c . A table was generated for each type of upregulated RNAs of captured MHC1 + EVs. (a) Log 2 total RPM values are plotted for the indicated snoRNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (c) Log 2 total RPM values are plotted for the indicated lncRNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (d) Log 2 total RPM values are plotted for the indicated small nuclear RNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from MHC1 + EVs (blue bars) and uncaptured MHC1 − EVs. Blue stars indicate RNAs that are also enriched in CD63 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.

    Techniques Used: Generated

    11) Product Images from "MicroRNA-34a dependent regulation of AXL controls the activation of dendritic cells in inflammatory arthritis"

    Article Title: MicroRNA-34a dependent regulation of AXL controls the activation of dendritic cells in inflammatory arthritis

    Journal: Nature Communications

    doi: 10.1038/ncomms15877

    MiR-34a −/− mice are resistant to arthritis. ( a – e ) WT ( n =15) and miR-34a −/− ( n =14) mice were sensitized according to the protocol in Methods. Mice were monitored for disease onset and paw swelling from day 10. Mice were killed on day 33 and tissue samples harvested. ( a , b ) miR-34a −/− mice had a reduced incidence ( a ) and severity ( b ) of arthritis; P
    Figure Legend Snippet: MiR-34a −/− mice are resistant to arthritis. ( a – e ) WT ( n =15) and miR-34a −/− ( n =14) mice were sensitized according to the protocol in Methods. Mice were monitored for disease onset and paw swelling from day 10. Mice were killed on day 33 and tissue samples harvested. ( a , b ) miR-34a −/− mice had a reduced incidence ( a ) and severity ( b ) of arthritis; P

    Techniques Used: Mouse Assay

    MiR-34a expression is regulated by GM-CSF and TLR ligands. ( a ) A representative FACS-gating strategy for sorting healthy donor human blood monocyte subsets. ( b ) Each monocyte subset expressed low copy numbers of miR-34a relative to let-7a housekeeping control ( c ), which increased following differentiation with GM-CSF (50 ng ml −1 ) for 3 and 7 days. Data in b are presented as a dot plot with dotted lines joining the cells from the same donor for clarity. ( d ) Monocyte-derived DCs ( n =3) were stimulated with TLR agonists CL097 (TLR7/8; 1 μg ml −1 ) or LPS (TLR4; 1 ng ml −1 ) or left un-stimulated (control, C), which decreased miR-34a expression between 2 and 24 h. * P
    Figure Legend Snippet: MiR-34a expression is regulated by GM-CSF and TLR ligands. ( a ) A representative FACS-gating strategy for sorting healthy donor human blood monocyte subsets. ( b ) Each monocyte subset expressed low copy numbers of miR-34a relative to let-7a housekeeping control ( c ), which increased following differentiation with GM-CSF (50 ng ml −1 ) for 3 and 7 days. Data in b are presented as a dot plot with dotted lines joining the cells from the same donor for clarity. ( d ) Monocyte-derived DCs ( n =3) were stimulated with TLR agonists CL097 (TLR7/8; 1 μg ml −1 ) or LPS (TLR4; 1 ng ml −1 ) or left un-stimulated (control, C), which decreased miR-34a expression between 2 and 24 h. * P

    Techniques Used: Expressing, FACS, Derivative Assay

    MiR-34a controls DC activation by regulating AXL. ( a ) Epigenetic miR-34a mRNA targets relevant to myeloid cell biology were identified by integrating the conserved miR-34a targets generated by the prediction algorithm TargetScan (Probability of conserved targeting value > 0.4) in a Venn diagram along with the mRNA transcriptomic signature of RA SF myeloid cells 68 . ( b , c ) AXL is targeted by miR-34a. ( b ) Luciferase reporter assay for AXL shows a reduction in luciferase activity when cells were transfected with miR-34a mimic (details in Methods). Data are presented as mean±s.e.m of three technical replicates and is representative of two independent experiments. * P
    Figure Legend Snippet: MiR-34a controls DC activation by regulating AXL. ( a ) Epigenetic miR-34a mRNA targets relevant to myeloid cell biology were identified by integrating the conserved miR-34a targets generated by the prediction algorithm TargetScan (Probability of conserved targeting value > 0.4) in a Venn diagram along with the mRNA transcriptomic signature of RA SF myeloid cells 68 . ( b , c ) AXL is targeted by miR-34a. ( b ) Luciferase reporter assay for AXL shows a reduction in luciferase activity when cells were transfected with miR-34a mimic (details in Methods). Data are presented as mean±s.e.m of three technical replicates and is representative of two independent experiments. * P

    Techniques Used: Activation Assay, Generated, Luciferase, Reporter Assay, Activity Assay, Transfection

    MiR-34a drives DC activation. ( a ) miR-34a −/− DCs show reduced production of pro-inflammatory cytokines. Bone marrow DCs from WT and miR-34a −/− mice ( n =6 pooled) were stimulated with LPS or CL097 for 24 h. ( b , c ) miR-34a −/− DCs show reduced expression of MHC class II. WT and miR-34a −/− DCs were stimulated as in a for 24 h and the expression of co-stimulatory molecules was evaluated as median fluorescent index (MFI) by flow cytometry. Representative MFI expression of MHC class II ( b ), and quantitative expression of MHC class II, co-stimulatory (CD40 and CD86), and inhibitory (PD-L1) molecules is shown ( c ). * P
    Figure Legend Snippet: MiR-34a drives DC activation. ( a ) miR-34a −/− DCs show reduced production of pro-inflammatory cytokines. Bone marrow DCs from WT and miR-34a −/− mice ( n =6 pooled) were stimulated with LPS or CL097 for 24 h. ( b , c ) miR-34a −/− DCs show reduced expression of MHC class II. WT and miR-34a −/− DCs were stimulated as in a for 24 h and the expression of co-stimulatory molecules was evaluated as median fluorescent index (MFI) by flow cytometry. Representative MFI expression of MHC class II ( b ), and quantitative expression of MHC class II, co-stimulatory (CD40 and CD86), and inhibitory (PD-L1) molecules is shown ( c ). * P

    Techniques Used: Activation Assay, Mouse Assay, Expressing, Flow Cytometry, Cytometry

    AXL expression is constitutively reduced in RA CD1c + DCs. ( a , b ) The miR-34a-dependent production of TNF by DCs is mediated by AXL. Healthy donor ( n =7) monocyte-derived DCs were transfected with a combination of miR-34a inhibitor or AXL siRNA or control inhibitor or siRNA for 16 h, and then stimulated with CL097 (1 μg ml −1 ) for 24 h. ( a ) Representative experimental data for TNF production; mean±s.d. of 3 biological replicates from one donor. ( b ) Summary of the relative production of TNF from all 7 donors tested; each normalised to the TNF production by DCs transfected with Control inhibitor (Ci) plus Control siRNA (C siRNA). P
    Figure Legend Snippet: AXL expression is constitutively reduced in RA CD1c + DCs. ( a , b ) The miR-34a-dependent production of TNF by DCs is mediated by AXL. Healthy donor ( n =7) monocyte-derived DCs were transfected with a combination of miR-34a inhibitor or AXL siRNA or control inhibitor or siRNA for 16 h, and then stimulated with CL097 (1 μg ml −1 ) for 24 h. ( a ) Representative experimental data for TNF production; mean±s.d. of 3 biological replicates from one donor. ( b ) Summary of the relative production of TNF from all 7 donors tested; each normalised to the TNF production by DCs transfected with Control inhibitor (Ci) plus Control siRNA (C siRNA). P

    Techniques Used: Expressing, Derivative Assay, Transfection

    MiR-34a expression is upregulated in DCs from patients with RA. ( a ) CD1c + DCs were FACS-sorted from PB of healthy donors (HD, n =6), and from PB ( n =6) and SF ( n =6) of RA patients with established RA of > 2 years duration. Compared to HD, miR-34a expression was upregulated in PB CD1c + in RA patients (* P
    Figure Legend Snippet: MiR-34a expression is upregulated in DCs from patients with RA. ( a ) CD1c + DCs were FACS-sorted from PB of healthy donors (HD, n =6), and from PB ( n =6) and SF ( n =6) of RA patients with established RA of > 2 years duration. Compared to HD, miR-34a expression was upregulated in PB CD1c + in RA patients (* P

    Techniques Used: Expressing, FACS

    A model describing miR-34/AXL function in DCs. The expression of miR-34a increases during CD1c + DC differentiation (1) and epigenetically down-regulates AXL expression (2). DC maturation, by TLR ligation, induces DC activation, for example, MHC class II upregulation and cytokine production. This maturation signal also down-regulates miR-34a (3), which then de-represses AXL, which in turn induces SOCSs and terminates DC activation (4), thus providing homeostatic feedback control of DC activation. In RA patients, sustained expression of high levels of miR-34a in CD1c + DCs inhibits AXL expression and may render DCs more sensitive to maturation signals, which can cause DCs to support sustained auto-reactive T-cell activation.
    Figure Legend Snippet: A model describing miR-34/AXL function in DCs. The expression of miR-34a increases during CD1c + DC differentiation (1) and epigenetically down-regulates AXL expression (2). DC maturation, by TLR ligation, induces DC activation, for example, MHC class II upregulation and cytokine production. This maturation signal also down-regulates miR-34a (3), which then de-represses AXL, which in turn induces SOCSs and terminates DC activation (4), thus providing homeostatic feedback control of DC activation. In RA patients, sustained expression of high levels of miR-34a in CD1c + DCs inhibits AXL expression and may render DCs more sensitive to maturation signals, which can cause DCs to support sustained auto-reactive T-cell activation.

    Techniques Used: Expressing, Ligation, Activation Assay

    12) Product Images from "Smooth muscle cells differentiated from mesenchymal stem cells are regulated by microRNAs and suitable for vascular tissue grafts"

    Article Title: Smooth muscle cells differentiated from mesenchymal stem cells are regulated by microRNAs and suitable for vascular tissue grafts

    Journal: The Journal of Biological Chemistry

    doi: 10.1074/jbc.RA118.001739

    miR-503 is transcriptionally up-regulated through SMAD4-dependent pathway. A, SMAD4 mRNA was detected with Q-PCR after treatment with siRNA for 1 day in αMEM with 1% FBS and 5 ng/ml TGFβ1. B, Q-PCR of SMC markers after siRNA transfection for 2 days in αMEM with 1% FBS and 5 ng/ml TGFβ1. C, level of miR-503 detected with TaqMan microRNA assay after cells were treated with siRNA with or without TGFβ1 for 2 days. D, MSCs were starved and then treated with or without TGFβ1 for 4 h and then harvested for ChIP experiments. Cells cultured without TGFβ1 were used as a control. Three primers (primer 1, primer 2, and primer 3) specific to the miR-503 promoter region were used to detect the enrichment of SMAD4. A primer specific to the GAPDH promoter region was used as a negative control. Fold enrichment was calculated against input and the control without TGFβ1 treatment. Data were obtained from at least three independent experiments and shown as mean ± S.D. Statistics were obtained with t test ( A and B ) or one-way ANOVA ( C and D ), followed by Bonferroni post hoc analysis. *, p
    Figure Legend Snippet: miR-503 is transcriptionally up-regulated through SMAD4-dependent pathway. A, SMAD4 mRNA was detected with Q-PCR after treatment with siRNA for 1 day in αMEM with 1% FBS and 5 ng/ml TGFβ1. B, Q-PCR of SMC markers after siRNA transfection for 2 days in αMEM with 1% FBS and 5 ng/ml TGFβ1. C, level of miR-503 detected with TaqMan microRNA assay after cells were treated with siRNA with or without TGFβ1 for 2 days. D, MSCs were starved and then treated with or without TGFβ1 for 4 h and then harvested for ChIP experiments. Cells cultured without TGFβ1 were used as a control. Three primers (primer 1, primer 2, and primer 3) specific to the miR-503 promoter region were used to detect the enrichment of SMAD4. A primer specific to the GAPDH promoter region was used as a negative control. Fold enrichment was calculated against input and the control without TGFβ1 treatment. Data were obtained from at least three independent experiments and shown as mean ± S.D. Statistics were obtained with t test ( A and B ) or one-way ANOVA ( C and D ), followed by Bonferroni post hoc analysis. *, p

    Techniques Used: Polymerase Chain Reaction, Transfection, TaqMan microRNA Assay, Chromatin Immunoprecipitation, Cell Culture, Negative Control

    miR-503 promotes SMC differentiation from MSCs. A, level of miRNAs was detected with TaqMan microRNA assay at early time points in SMC differentiation in 1% FBS and 5 ng/ml TGFβ1. B, level of miRNA with or without TGFβ1 treatment after 2 days was detected with TaqMan microRNA assay. C, TaqMan microRNA assay showed significant up-regulation of miR-503 after mimic treatment for 1 day in αMEM with 1% FBS. D, Q-PCR showed the mRNA level up-regulation of SMC-specific markers after miR-503 mimic treatment for 3 days in αMEM with 1% FBS. E, protein expression and quantification after miR-503 mimic treatment for 3 days in αMEM with 1% FBS were analyzed. F, TaqMan microRNA assay showed significant down-regulation of miR-503 after inhibitor treatment for 1 day. G, level of SMC-specific markers was detected with Q-PCR after miR-503 inhibitor treatment for 3 days in αMEM with 1% FBS and 5 ng/ml TGFβ1. H, protein expression and quantification after miR-503 inhibitor treatment for 3 days in αMEM with 1% FBS and 5 ng/ml TGFβ1 were analyzed. Data are presented as the mean ± S.D. from three independent experiments. *, p
    Figure Legend Snippet: miR-503 promotes SMC differentiation from MSCs. A, level of miRNAs was detected with TaqMan microRNA assay at early time points in SMC differentiation in 1% FBS and 5 ng/ml TGFβ1. B, level of miRNA with or without TGFβ1 treatment after 2 days was detected with TaqMan microRNA assay. C, TaqMan microRNA assay showed significant up-regulation of miR-503 after mimic treatment for 1 day in αMEM with 1% FBS. D, Q-PCR showed the mRNA level up-regulation of SMC-specific markers after miR-503 mimic treatment for 3 days in αMEM with 1% FBS. E, protein expression and quantification after miR-503 mimic treatment for 3 days in αMEM with 1% FBS were analyzed. F, TaqMan microRNA assay showed significant down-regulation of miR-503 after inhibitor treatment for 1 day. G, level of SMC-specific markers was detected with Q-PCR after miR-503 inhibitor treatment for 3 days in αMEM with 1% FBS and 5 ng/ml TGFβ1. H, protein expression and quantification after miR-503 inhibitor treatment for 3 days in αMEM with 1% FBS and 5 ng/ml TGFβ1 were analyzed. Data are presented as the mean ± S.D. from three independent experiments. *, p

    Techniques Used: TaqMan microRNA Assay, Polymerase Chain Reaction, Expressing

    3′-UTRs of ROCK2 and αSMA were direct targets of miR-222-5p. A, alignment of miR-222-5p and ROCK2 3′-UTR showed the postulated target-binding sites ( red ) and induced mutations ( blue ). ROCK2 3′-UTR contains two target-binding sites ( site 1 and site 2 ) of miR-222-5p, which were mutated alone ( m1, m2 ) or together ( m1 + m2 ). B, alignment of miR-222-5p and the 3′-UTR of αSMA showed the postulated target-binding sites ( red ) and induced mutations ( blue ). C, co-transfection of miR-222-5p mimics and reporter plasmid with WT ROCK2 3′-UTR showed reduced relative luciferase activity as compared with vector with empty plasmid, whereas mutation of both target-binding sites ( m1 + m2 ) recovered the reduction. D, dual transfection of plasmids and miR-222-5p into HEK293 cells demonstrated the inhibition of miR-222-5p on the 3′-UTR of αSMA, and mutation of the predicted target site recovered the inhibition. Relative luciferase activity was calculated with firefly luciferase activity/ Renilla luciferase activity. Data are presented as the mean ± S.D. from three independent experiments. Statistics ( C and D ) were obtained from two-way ANOVA test followed by Bonferroni post hoc analysis. E, level of miR-503 was inhibited by miR-222-5p mimic treatment after 1 day as shown with TaqMan microRNA assay. F, TaqMan microRNA assay of miR-222-5p did not reveal any change after miR-503 mimic treatment. Data are presented as the mean ± S.D. from three independent experiments. *, p
    Figure Legend Snippet: 3′-UTRs of ROCK2 and αSMA were direct targets of miR-222-5p. A, alignment of miR-222-5p and ROCK2 3′-UTR showed the postulated target-binding sites ( red ) and induced mutations ( blue ). ROCK2 3′-UTR contains two target-binding sites ( site 1 and site 2 ) of miR-222-5p, which were mutated alone ( m1, m2 ) or together ( m1 + m2 ). B, alignment of miR-222-5p and the 3′-UTR of αSMA showed the postulated target-binding sites ( red ) and induced mutations ( blue ). C, co-transfection of miR-222-5p mimics and reporter plasmid with WT ROCK2 3′-UTR showed reduced relative luciferase activity as compared with vector with empty plasmid, whereas mutation of both target-binding sites ( m1 + m2 ) recovered the reduction. D, dual transfection of plasmids and miR-222-5p into HEK293 cells demonstrated the inhibition of miR-222-5p on the 3′-UTR of αSMA, and mutation of the predicted target site recovered the inhibition. Relative luciferase activity was calculated with firefly luciferase activity/ Renilla luciferase activity. Data are presented as the mean ± S.D. from three independent experiments. Statistics ( C and D ) were obtained from two-way ANOVA test followed by Bonferroni post hoc analysis. E, level of miR-503 was inhibited by miR-222-5p mimic treatment after 1 day as shown with TaqMan microRNA assay. F, TaqMan microRNA assay of miR-222-5p did not reveal any change after miR-503 mimic treatment. Data are presented as the mean ± S.D. from three independent experiments. *, p

    Techniques Used: Binding Assay, Cotransfection, Plasmid Preparation, Luciferase, Activity Assay, Mutagenesis, Transfection, Inhibition, TaqMan microRNA Assay

    miR-222-5p inhibits SMC differentiation from MSCs. A, level of miR-222-5p was detected with TaqMan microRNA assay. B, Q-PCR showed the gene expression of SMC markers (calponin and αSMA) after cells were treated with miRNA mimics in αMEM with 1% FBS and 5 ng/ml TGFβ1 for 2 days. C, representative Western blotting image and analysis after cells were treated with miRNA mimics in αMEM with 1% FBS and 5 ng/ml TGFβ1 for 2 days were obtained from three independent experiments. D, immunofluorescent staining showed the intensity of SMC markers (calponin and αSMA) after miR-222-5p treatment for 2 days. Cell nucleus was stained with DAPI ( blue ). Representative images were obtained from three independent experiments. Data were obtained from at least three independent experiments and shown as mean ± S.D. *, p
    Figure Legend Snippet: miR-222-5p inhibits SMC differentiation from MSCs. A, level of miR-222-5p was detected with TaqMan microRNA assay. B, Q-PCR showed the gene expression of SMC markers (calponin and αSMA) after cells were treated with miRNA mimics in αMEM with 1% FBS and 5 ng/ml TGFβ1 for 2 days. C, representative Western blotting image and analysis after cells were treated with miRNA mimics in αMEM with 1% FBS and 5 ng/ml TGFβ1 for 2 days were obtained from three independent experiments. D, immunofluorescent staining showed the intensity of SMC markers (calponin and αSMA) after miR-222-5p treatment for 2 days. Cell nucleus was stained with DAPI ( blue ). Representative images were obtained from three independent experiments. Data were obtained from at least three independent experiments and shown as mean ± S.D. *, p

    Techniques Used: TaqMan microRNA Assay, Polymerase Chain Reaction, Expressing, Western Blot, Staining

    13) Product Images from "Antiproliferative and proapoptotic effects of a pyrrole containing arylthioindole in human Jurkat leukemia cell line and multidrug-resistant Jurkat/A4 cells"

    Article Title: Antiproliferative and proapoptotic effects of a pyrrole containing arylthioindole in human Jurkat leukemia cell line and multidrug-resistant Jurkat/A4 cells

    Journal: Cancer Biology & Therapy

    doi: 10.1080/15384047.2015.1078026

    Effect of ATI5 on the induction of apoptosis in the Jurkat and Jurkat/A4 cells. Representative flow cytometry histograms showing the percentage of hypodiploid cells in the Jurkat ( A ) and Jurkat/A4 cells ( B ). Effect of pan-caspase inhibitor z-VAD-fmk on ATI5-induced apoptosis in the Jurkat ( C ) and Jurkat/A4 cells ( D ). Effect of caspase-8 z-LEHD-fmk inhibitor ( E ) or caspase-9 inhibitor Ac-IETD-cho ( F ) on ATI5-induced apoptosis in the Jurkat cells. Effect of caspase-8 z-LEHD-fmk inhibitor on agonistic anti-human Fas (CD95) mAbs-induced apoptotic cell death in the Jurkat cells ( G ). The percentage of hypodiploid cells was assessed by flow cytometry after the staining with propidium iodide. The results are presented as means ± SD (n = 3 ). * - Significantly different (p
    Figure Legend Snippet: Effect of ATI5 on the induction of apoptosis in the Jurkat and Jurkat/A4 cells. Representative flow cytometry histograms showing the percentage of hypodiploid cells in the Jurkat ( A ) and Jurkat/A4 cells ( B ). Effect of pan-caspase inhibitor z-VAD-fmk on ATI5-induced apoptosis in the Jurkat ( C ) and Jurkat/A4 cells ( D ). Effect of caspase-8 z-LEHD-fmk inhibitor ( E ) or caspase-9 inhibitor Ac-IETD-cho ( F ) on ATI5-induced apoptosis in the Jurkat cells. Effect of caspase-8 z-LEHD-fmk inhibitor on agonistic anti-human Fas (CD95) mAbs-induced apoptotic cell death in the Jurkat cells ( G ). The percentage of hypodiploid cells was assessed by flow cytometry after the staining with propidium iodide. The results are presented as means ± SD (n = 3 ). * - Significantly different (p

    Techniques Used: Flow Cytometry, Cytometry, Staining

    Effect of ATI5 on caspase-3 activation in the Jurkat ( A ) or Jurkat/A4 ( B ) cells. The percentage of cells with active form of caspase-3 in Jurkat and Jurkat/A4 cells treated with ATI5 for 48 hrs was assessed by flow cytometry as described in the “Materials and Methods.” ( C ) Analysis of PARP-1 cleavage in the Jurkat and Jurkat/A4 cells treated with ATI5. Representative Western blot PARP-1 and β-actin images are shown.
    Figure Legend Snippet: Effect of ATI5 on caspase-3 activation in the Jurkat ( A ) or Jurkat/A4 ( B ) cells. The percentage of cells with active form of caspase-3 in Jurkat and Jurkat/A4 cells treated with ATI5 for 48 hrs was assessed by flow cytometry as described in the “Materials and Methods.” ( C ) Analysis of PARP-1 cleavage in the Jurkat and Jurkat/A4 cells treated with ATI5. Representative Western blot PARP-1 and β-actin images are shown.

    Techniques Used: Activation Assay, Flow Cytometry, Cytometry, Western Blot

    Effect of ATI5 on morphology of the Jurkat ( A ) and ( B ) and Jurkat/A4 ( C ) and ( D ) cells. Untreated cells ( A ) and ( C ) were used as control. Cells were stained using May–Grünwald–Giemsa technique. Representative images are shown (magnification 100x).
    Figure Legend Snippet: Effect of ATI5 on morphology of the Jurkat ( A ) and ( B ) and Jurkat/A4 ( C ) and ( D ) cells. Untreated cells ( A ) and ( C ) were used as control. Cells were stained using May–Grünwald–Giemsa technique. Representative images are shown (magnification 100x).

    Techniques Used: Staining

    14) Product Images from "A putative role of micro RNA in regulation of cholesterol 7?-hydroxylase expression in human hepatocytes [S]"

    Article Title: A putative role of micro RNA in regulation of cholesterol 7?-hydroxylase expression in human hepatocytes [S]

    Journal: Journal of Lipid Research

    doi: 10.1194/jlr.M004531

    CDCA, GW4064, and FGF19 induce miR-122a and miR-422a mRNA levels in PHHs. PHHs were treated with CDCA (25 µM), GW4064 (1 µM), or FGF19 (40 ng/ml) for 24 h. Total RNA was isolated for quantitative real-time PCR analysis of miR-122a (A)
    Figure Legend Snippet: CDCA, GW4064, and FGF19 induce miR-122a and miR-422a mRNA levels in PHHs. PHHs were treated with CDCA (25 µM), GW4064 (1 µM), or FGF19 (40 ng/ml) for 24 h. Total RNA was isolated for quantitative real-time PCR analysis of miR-122a (A)

    Techniques Used: Isolation, Real-time Polymerase Chain Reaction

    15) Product Images from "A putative role of micro RNA in regulation of cholesterol 7?-hydroxylase expression in human hepatocytes [S]"

    Article Title: A putative role of micro RNA in regulation of cholesterol 7?-hydroxylase expression in human hepatocytes [S]

    Journal: Journal of Lipid Research

    doi: 10.1194/jlr.M004531

    CDCA, GW4064, and FGF19 induce miR-122a and miR-422a mRNA levels in PHHs. PHHs were treated with CDCA (25 µM), GW4064 (1 µM), or FGF19 (40 ng/ml) for 24 h. Total RNA was isolated for quantitative real-time PCR analysis of miR-122a (A)
    Figure Legend Snippet: CDCA, GW4064, and FGF19 induce miR-122a and miR-422a mRNA levels in PHHs. PHHs were treated with CDCA (25 µM), GW4064 (1 µM), or FGF19 (40 ng/ml) for 24 h. Total RNA was isolated for quantitative real-time PCR analysis of miR-122a (A)

    Techniques Used: Isolation, Real-time Polymerase Chain Reaction

    16) Product Images from "Modeling the neuropsychiatric manifestations of Lowe syndrome using induced pluripotent stem cells: defective F-actin polymerization and WAVE-1 expression in neuronal cells"

    Article Title: Modeling the neuropsychiatric manifestations of Lowe syndrome using induced pluripotent stem cells: defective F-actin polymerization and WAVE-1 expression in neuronal cells

    Journal: Molecular Autism

    doi: 10.1186/s13229-018-0227-3

    DNA and cDNA sequencing. a Genomic DNA sequences showing mutations in the CRISPR-engineered knockout line (690KO) and the LS samples (LS100, LS300, and LS500) along with controls. The arrows point to the mutations. b The LS100 splice acceptor mutation predicts the loss of the natural splice site at the intron 23/exon 24 border, as well as a cryptic splice site 16 bases into exon 24. c cDNA sequencing showing normal exon 22/23 and exon 23/24 combinations in controls, and aberrant splicing in LS300, which leads to the exclusion of exon 23, thereby connecting exon 22 to 24; and the cryptic splice in LS100, as predicted in panel b
    Figure Legend Snippet: DNA and cDNA sequencing. a Genomic DNA sequences showing mutations in the CRISPR-engineered knockout line (690KO) and the LS samples (LS100, LS300, and LS500) along with controls. The arrows point to the mutations. b The LS100 splice acceptor mutation predicts the loss of the natural splice site at the intron 23/exon 24 border, as well as a cryptic splice site 16 bases into exon 24. c cDNA sequencing showing normal exon 22/23 and exon 23/24 combinations in controls, and aberrant splicing in LS300, which leads to the exclusion of exon 23, thereby connecting exon 22 to 24; and the cryptic splice in LS100, as predicted in panel b

    Techniques Used: Sequencing, CRISPR, Knock-Out, Mutagenesis

    17) Product Images from "Coronary Serum Exosomes Derived from Patients with Myocardial Ischemia Regulate Angiogenesis through the miR-939-mediated Nitric Oxide Signaling Pathway"

    Article Title: Coronary Serum Exosomes Derived from Patients with Myocardial Ischemia Regulate Angiogenesis through the miR-939-mediated Nitric Oxide Signaling Pathway

    Journal: Theranostics

    doi: 10.7150/thno.21895

    The microarray analysis of isc-Exo and con-Exo. (A) volcano plot and heat map (B) of isc-Exo and con-Exo (the red dots indicate up-regulated miRNAs and the green dots indicate the down-regulated miRNAs). For the regulated miRNAs, the GO analysis of biological processes involved in endothelial (C) and cardiomyocytes (D). The columns indicate the related GO terms depending on the enrichment factor and the numbers in the parentheses indicate the number of genes. (E) qPCR verification of the regulated miRNAs and the results are shown as fold changes. (F) Overexpression analysis of selected miRNAs (miR-939-5p, miR-1246, miR-4787-3p) for their proliferative effect on endothelial cells. miR-939-5p and miR-4787-3p repressed endothelial cell proliferation. * indicates P
    Figure Legend Snippet: The microarray analysis of isc-Exo and con-Exo. (A) volcano plot and heat map (B) of isc-Exo and con-Exo (the red dots indicate up-regulated miRNAs and the green dots indicate the down-regulated miRNAs). For the regulated miRNAs, the GO analysis of biological processes involved in endothelial (C) and cardiomyocytes (D). The columns indicate the related GO terms depending on the enrichment factor and the numbers in the parentheses indicate the number of genes. (E) qPCR verification of the regulated miRNAs and the results are shown as fold changes. (F) Overexpression analysis of selected miRNAs (miR-939-5p, miR-1246, miR-4787-3p) for their proliferative effect on endothelial cells. miR-939-5p and miR-4787-3p repressed endothelial cell proliferation. * indicates P

    Techniques Used: Microarray, Real-time Polymerase Chain Reaction, Over Expression

    Effects of isc-Exo and con-Exo on in vitro angiogenesis. (A, B) The isc-Exo group showed greater proliferative effects than con-Exo at both 200 μg/mL and 400 μg/mL doses in EdU-positive cells measured by CCK8 absorbance (C) and manual cell count (D). (E) The isc-Exo group showed better vascular formation ability than con-Exo in tube formation analysis measured by number of nodes (F) and tube length (G). isc-Exo promoted endothelial cell migration, as evaluated by scratch wound assay (H) and analyzed by the ratio of non-migrated area divided by the baseline wound area (I). (J) The Transwell assay also revealed the same trend as the wound assay and was analyzed by the number of migrated cells (K). Bars indicate 200 μm in all pictures. * indicates P
    Figure Legend Snippet: Effects of isc-Exo and con-Exo on in vitro angiogenesis. (A, B) The isc-Exo group showed greater proliferative effects than con-Exo at both 200 μg/mL and 400 μg/mL doses in EdU-positive cells measured by CCK8 absorbance (C) and manual cell count (D). (E) The isc-Exo group showed better vascular formation ability than con-Exo in tube formation analysis measured by number of nodes (F) and tube length (G). isc-Exo promoted endothelial cell migration, as evaluated by scratch wound assay (H) and analyzed by the ratio of non-migrated area divided by the baseline wound area (I). (J) The Transwell assay also revealed the same trend as the wound assay and was analyzed by the number of migrated cells (K). Bars indicate 200 μm in all pictures. * indicates P

    Techniques Used: In Vitro, Cell Counting, Migration, Scratch Wound Assay Assay, Transwell Assay

    miR-939 and iNOS levels after isc-Exo and con-Exo treatment. (A) After treatment by isc-Exo and con-Exo, the miR-939 expression of con-Exo-treated cells was 3-fold higher than that of isc-Exo-treated cells. (B) Meanwhile, the iNOS mRNA level was 5-fold higher in the isc-Exo group. (C, D) The iNOS protein level in the isc-Exo-treated cells was also higher than that of con-Exo-treated cells. * indicates P
    Figure Legend Snippet: miR-939 and iNOS levels after isc-Exo and con-Exo treatment. (A) After treatment by isc-Exo and con-Exo, the miR-939 expression of con-Exo-treated cells was 3-fold higher than that of isc-Exo-treated cells. (B) Meanwhile, the iNOS mRNA level was 5-fold higher in the isc-Exo group. (C, D) The iNOS protein level in the isc-Exo-treated cells was also higher than that of con-Exo-treated cells. * indicates P

    Techniques Used: Expressing

    Healing effects of isc-Exo and con-Exo on mouse ischemic injury after hind-limb ischemia. (A) Blood flow recovery evaluated by Laser-Doppler perfusion imaging 0, 7, 14, 21 days after surgery. The left side was the ischemia limb and the right side was the normal control limb. Bars indicate 1 cm. (B) The healing effect of blood perfusion recovery was analyzed by the perfusion ratio of the ischemia side divided by that of the normal control side. The isc-Exo group showed better blood perfusion recovery effects compared to the con-Exo group 21 days after surgery. (C) The ischemic limb skin appearance 21 days after surgery. The PBS group showed scarring on the left ischemia limb and the con-Exo group showed swelling in the whole ischemia limb. Meanwhile, the isc-Exo group showed a better recovery. Muscle sections stained by hematoxylin and eosin (D), CD31 immunohistochemistry (E) and CD31 and α-SMA immunofluorescence (F). The arrows indicate the microvessels in the muscle and the bars indicate 100 μm in the pictures. red: α-SMA, green: CD31, blue: DAPI. (G) The capillary density in the ischemia muscles was analyzed by the number of microvessels per cm 2 . The isc-Exo group showed higher capillary density than the con-Exo group. * indicates P
    Figure Legend Snippet: Healing effects of isc-Exo and con-Exo on mouse ischemic injury after hind-limb ischemia. (A) Blood flow recovery evaluated by Laser-Doppler perfusion imaging 0, 7, 14, 21 days after surgery. The left side was the ischemia limb and the right side was the normal control limb. Bars indicate 1 cm. (B) The healing effect of blood perfusion recovery was analyzed by the perfusion ratio of the ischemia side divided by that of the normal control side. The isc-Exo group showed better blood perfusion recovery effects compared to the con-Exo group 21 days after surgery. (C) The ischemic limb skin appearance 21 days after surgery. The PBS group showed scarring on the left ischemia limb and the con-Exo group showed swelling in the whole ischemia limb. Meanwhile, the isc-Exo group showed a better recovery. Muscle sections stained by hematoxylin and eosin (D), CD31 immunohistochemistry (E) and CD31 and α-SMA immunofluorescence (F). The arrows indicate the microvessels in the muscle and the bars indicate 100 μm in the pictures. red: α-SMA, green: CD31, blue: DAPI. (G) The capillary density in the ischemia muscles was analyzed by the number of microvessels per cm 2 . The isc-Exo group showed higher capillary density than the con-Exo group. * indicates P

    Techniques Used: Flow Cytometry, Imaging, Staining, Immunohistochemistry, Immunofluorescence

    18) Product Images from "TLR4/NF-κB axis signaling pathway-dependent up-regulation of miR-625-5p contributes to human intervertebral disc degeneration by targeting COL1A1"

    Article Title: TLR4/NF-κB axis signaling pathway-dependent up-regulation of miR-625-5p contributes to human intervertebral disc degeneration by targeting COL1A1

    Journal: American Journal of Translational Research

    doi:

    Activation of the TLR4/NF-κB signaling pathway in vivo and in vitro . (A) The protein levels of members of the TLR4/NF-κB signaling pathway in IDD tissues. The protein levels of TLR4, MyD88, TRAF6, p65 and p50 were examined in a healthy control (HC), and three IDD tissues, including IDD-1, -2 and -3. GAPDH was used as the loading control. (B) Protein levels of p65 and p50 in the cytoplasm and nucleus. The cytoplasmic and nuclear portions of the IDD tissues were prepared, and immunoblots were performed to examine the p65 and p50 levels in these two portions. β-Actin and LSD1 were used as controls to determine the levels of cytoplasmic and nuclear proteins, respectively. (C and D) The protein levels of members of the TLR4/NF-κB signaling pathway in (C) hNPC and (D) hAFC cells treated with LPS. The hNPC and hAFC cells were treated with different concentrations of LPS (0, 50, 100 or 200 ng/mL) for 2 hr, followed by detecting the protein levels of TLR4, MyD88, TRAF6, p65 and p50. GAPDH was used as the loading control. (E and F) Protein levels of p65 and p50 in the cytoplasm and nucleus of (E) hNPC and (F) hAFC cells. The cytoplasmic and nuclear portions of cells used in (C) and (D) were prepared, and immunoblots were performed to examine the p65 and p50 levels in these two portions. β-Actin and LSD1 were used as controls to determine the levels of cytoplasmic and nuclear proteins, respectively. (G and H) The relative mRNA levels of IL1B and IL6 in (G) hNPC and (H) hAFC cells treated with LPS. Cells used in (C) and (D) were subjected to RNA isolation, followed by measuring the expression levels of IL1B and IL6 by qRT-PCR. *** P
    Figure Legend Snippet: Activation of the TLR4/NF-κB signaling pathway in vivo and in vitro . (A) The protein levels of members of the TLR4/NF-κB signaling pathway in IDD tissues. The protein levels of TLR4, MyD88, TRAF6, p65 and p50 were examined in a healthy control (HC), and three IDD tissues, including IDD-1, -2 and -3. GAPDH was used as the loading control. (B) Protein levels of p65 and p50 in the cytoplasm and nucleus. The cytoplasmic and nuclear portions of the IDD tissues were prepared, and immunoblots were performed to examine the p65 and p50 levels in these two portions. β-Actin and LSD1 were used as controls to determine the levels of cytoplasmic and nuclear proteins, respectively. (C and D) The protein levels of members of the TLR4/NF-κB signaling pathway in (C) hNPC and (D) hAFC cells treated with LPS. The hNPC and hAFC cells were treated with different concentrations of LPS (0, 50, 100 or 200 ng/mL) for 2 hr, followed by detecting the protein levels of TLR4, MyD88, TRAF6, p65 and p50. GAPDH was used as the loading control. (E and F) Protein levels of p65 and p50 in the cytoplasm and nucleus of (E) hNPC and (F) hAFC cells. The cytoplasmic and nuclear portions of cells used in (C) and (D) were prepared, and immunoblots were performed to examine the p65 and p50 levels in these two portions. β-Actin and LSD1 were used as controls to determine the levels of cytoplasmic and nuclear proteins, respectively. (G and H) The relative mRNA levels of IL1B and IL6 in (G) hNPC and (H) hAFC cells treated with LPS. Cells used in (C) and (D) were subjected to RNA isolation, followed by measuring the expression levels of IL1B and IL6 by qRT-PCR. *** P

    Techniques Used: Activation Assay, In Vivo, In Vitro, Western Blot, Isolation, Expressing, Quantitative RT-PCR

    19) Product Images from "Epigenetic regulation of the X-chromosomal macrosatellite repeat encoding for the cancer/testis gene CT47"

    Article Title: Epigenetic regulation of the X-chromosomal macrosatellite repeat encoding for the cancer/testis gene CT47

    Journal: European Journal of Human Genetics

    doi: 10.1038/ejhg.2011.150

    ( a ) Expression levels of CT47 mRNA in different SCLC cell lines relative to the expression in human testis. Commercially available human total testis RNA and RNA isolated from SCLC lines were used for cDNA synthesis under identical conditions. CT47 expression levels are normalized to the expression levels measured in the testis. Different SCLC lines have different, but low levels of CT47 expression compared to the testis. Relative abundance of histone modifications and EZH2 at the CT47 promoter ( b ), exon 3 ( c ) and the distal region in SCLC cell lines ( d ). SCLC cell lines show individual variation in the abundance of different histone modifications. Generally, a loss of the repressive chromatin mark H3K9me3 can be observed in SCLCs. H3K27me3 levels are higher in SCLCs at the promoter and exon 3 region than in LCLs, but lower at the distal region. The relative abundance of the PRC2 component EZH2 responsible for generating H2K27me3 is dramatically reduced in SCLCs compared to LCLs at all region studied. ( e ) DNA methylation levels at CpGs located in the CT47 promoter region in LCL and SCLC samples. The methylation level of seven different CpGs, next to the transcriptional start site of CT47 , was determined by bisulfite sequencing and quantified by ESME program. There is a significant difference between the methylation level of LCLs and SCLCs at every CpG tested ( P
    Figure Legend Snippet: ( a ) Expression levels of CT47 mRNA in different SCLC cell lines relative to the expression in human testis. Commercially available human total testis RNA and RNA isolated from SCLC lines were used for cDNA synthesis under identical conditions. CT47 expression levels are normalized to the expression levels measured in the testis. Different SCLC lines have different, but low levels of CT47 expression compared to the testis. Relative abundance of histone modifications and EZH2 at the CT47 promoter ( b ), exon 3 ( c ) and the distal region in SCLC cell lines ( d ). SCLC cell lines show individual variation in the abundance of different histone modifications. Generally, a loss of the repressive chromatin mark H3K9me3 can be observed in SCLCs. H3K27me3 levels are higher in SCLCs at the promoter and exon 3 region than in LCLs, but lower at the distal region. The relative abundance of the PRC2 component EZH2 responsible for generating H2K27me3 is dramatically reduced in SCLCs compared to LCLs at all region studied. ( e ) DNA methylation levels at CpGs located in the CT47 promoter region in LCL and SCLC samples. The methylation level of seven different CpGs, next to the transcriptional start site of CT47 , was determined by bisulfite sequencing and quantified by ESME program. There is a significant difference between the methylation level of LCLs and SCLCs at every CpG tested ( P

    Techniques Used: Expressing, Isolation, DNA Methylation Assay, Methylation, Methylation Sequencing

    20) Product Images from "Transmission of microRNA antimiRs to mouse offspring via the maternal–placental–fetal unit"

    Article Title: Transmission of microRNA antimiRs to mouse offspring via the maternal–placental–fetal unit

    Journal: RNA

    doi: 10.1261/rna.063206.117

    Validation of Eln and Adamts7 mRNA as targets of miR-29a-3p in NIH/3T3 cells in vitro. The NIH/3T3 cells were mock-transfected, or were transfected with either a scrambled microRNA mimic, a miR-29a-3p mimic, or an antimiR-29a-3p for 48 h (all at 80 nM). Total RNA pools from NIH/3T3 cells were screened by real-time RT-PCR for steady-state levels of free miR-29a-3p, after ( A ) transfection of a miR-29a-3p mimic, or ( B ) an antimiR-29a-3p. In silico analyses revealed both the ( C ) Eln mRNA and ( D ) the Adamts7 mRNA to be candidate targets of miR-29a-3p; where the Eln mRNA 3′-untranslated region (UTR) contained three (8mer 34–44 , 8mer 285–291 , and 7mer-m8 298–304 ) predicted miR-29a-3p binding-sites, and the Adamts7 mRNA 3′-UTR contained a single (7mer-A1 93–99 ) predicted miR-29a-3p binding-site. Therefore, total RNA pools from miR-29a-3p mimic-treated NIH/3T3 cells were also screened by real-time RT-PCR for steady-state expression levels of ( E ) Eln and ( F ) Adamts7 . Total protein extracts from NIH/3T3 cells were screened by immunoblot for steady-state protein expression levels of ( G ) elastin (ELN) and ( H ) ADAM metallopeptidase with thrombospondin type 1 motif 7 (ADAMTS7), where β-ACTIN served as a loading control. Total RNA pools from antimiR-29a-3p-treated NIH/3T3 cells were also screened by real-time RT-PCR for steady-state expression levels of ( I ) Eln and ( J ) Adamts7 . For RT-PCR studies, steady-state free miR or mRNA expression levels are described by the mean ΔCT ± SD. ( n = 3–6 separate transfection experiments, per group; each symbol represents an independent transfection experiment, where some symbols may coalesce). For microRNA analyses, ΔCT = CT ( Rnu6 ) – CT (miR-29a-3p) , while for mRNA analyses, ΔCT = CT ( Polr2a ) − CT (gene of interest) . Mean values were compared between treatment conditions by one-way ANOVA with Tukey's post hoc modification, and P -values are provided for scrambled versus miR/antimiR treatments.
    Figure Legend Snippet: Validation of Eln and Adamts7 mRNA as targets of miR-29a-3p in NIH/3T3 cells in vitro. The NIH/3T3 cells were mock-transfected, or were transfected with either a scrambled microRNA mimic, a miR-29a-3p mimic, or an antimiR-29a-3p for 48 h (all at 80 nM). Total RNA pools from NIH/3T3 cells were screened by real-time RT-PCR for steady-state levels of free miR-29a-3p, after ( A ) transfection of a miR-29a-3p mimic, or ( B ) an antimiR-29a-3p. In silico analyses revealed both the ( C ) Eln mRNA and ( D ) the Adamts7 mRNA to be candidate targets of miR-29a-3p; where the Eln mRNA 3′-untranslated region (UTR) contained three (8mer 34–44 , 8mer 285–291 , and 7mer-m8 298–304 ) predicted miR-29a-3p binding-sites, and the Adamts7 mRNA 3′-UTR contained a single (7mer-A1 93–99 ) predicted miR-29a-3p binding-site. Therefore, total RNA pools from miR-29a-3p mimic-treated NIH/3T3 cells were also screened by real-time RT-PCR for steady-state expression levels of ( E ) Eln and ( F ) Adamts7 . Total protein extracts from NIH/3T3 cells were screened by immunoblot for steady-state protein expression levels of ( G ) elastin (ELN) and ( H ) ADAM metallopeptidase with thrombospondin type 1 motif 7 (ADAMTS7), where β-ACTIN served as a loading control. Total RNA pools from antimiR-29a-3p-treated NIH/3T3 cells were also screened by real-time RT-PCR for steady-state expression levels of ( I ) Eln and ( J ) Adamts7 . For RT-PCR studies, steady-state free miR or mRNA expression levels are described by the mean ΔCT ± SD. ( n = 3–6 separate transfection experiments, per group; each symbol represents an independent transfection experiment, where some symbols may coalesce). For microRNA analyses, ΔCT = CT ( Rnu6 ) – CT (miR-29a-3p) , while for mRNA analyses, ΔCT = CT ( Polr2a ) − CT (gene of interest) . Mean values were compared between treatment conditions by one-way ANOVA with Tukey's post hoc modification, and P -values are provided for scrambled versus miR/antimiR treatments.

    Techniques Used: In Vitro, Transfection, Quantitative RT-PCR, In Silico, Binding Assay, Expressing, Reverse Transcription Polymerase Chain Reaction, Modification

    21) Product Images from "The genomic landscape of undifferentiated embryonal sarcoma of the liver is typified by C19MC structural rearrangement and overexpression combined with TP53 mutation or loss"

    Article Title: The genomic landscape of undifferentiated embryonal sarcoma of the liver is typified by C19MC structural rearrangement and overexpression combined with TP53 mutation or loss

    Journal: PLoS Genetics

    doi: 10.1371/journal.pgen.1008642

    UESL display frequent TP53 mutations and exhibit negative correlation of C19MC miRNAs to TP53 and KRAS-regulatory miRNAs. A, Small RNA-seq of UESL samples were subjected to C19MC miRNA correlation analysis with miRNA transcriptome of 1342 miRNAs (that had a cumulative reads of 100 or more) that were selected from a total of 2404 miRNAs (counting 5p and 3p separately). C19MC miRNAs fall into two clusters (top left heatmap): a large cluster which is negatively correlated to many TP53 regulatory miRNAs (top right heatmap) and a smaller cluster which is negatively correlated to both TP53 and KRAS regulatory miRNAs (bottom left heatmap). B, UESL harbor an assortment of TP53 mutations as evaluated by whole exome sequencing. Notably, almost all mutations are truncation or known oncogenic missense mutations.
    Figure Legend Snippet: UESL display frequent TP53 mutations and exhibit negative correlation of C19MC miRNAs to TP53 and KRAS-regulatory miRNAs. A, Small RNA-seq of UESL samples were subjected to C19MC miRNA correlation analysis with miRNA transcriptome of 1342 miRNAs (that had a cumulative reads of 100 or more) that were selected from a total of 2404 miRNAs (counting 5p and 3p separately). C19MC miRNAs fall into two clusters (top left heatmap): a large cluster which is negatively correlated to many TP53 regulatory miRNAs (top right heatmap) and a smaller cluster which is negatively correlated to both TP53 and KRAS regulatory miRNAs (bottom left heatmap). B, UESL harbor an assortment of TP53 mutations as evaluated by whole exome sequencing. Notably, almost all mutations are truncation or known oncogenic missense mutations.

    Techniques Used: RNA Sequencing Assay, Sequencing

    UESL tumors hyperexpress C19MC miRNAs with selective upregulation of 5p or 3p mature miRNAs. A, Small RNA-seq showing overexpression of C19MC miRNAs in UESL tumors compared to normal liver sample or Hep3B cell line. The bar graphs represent the cumulative expression of all 46 C19MC miRNAs (5p and 3p). B, 24 C19MC miRNAs that have 5p and 3p mature miRNA information in UESL tumors display miRNA-specific selective 5p vs. 3p expressional patterns.
    Figure Legend Snippet: UESL tumors hyperexpress C19MC miRNAs with selective upregulation of 5p or 3p mature miRNAs. A, Small RNA-seq showing overexpression of C19MC miRNAs in UESL tumors compared to normal liver sample or Hep3B cell line. The bar graphs represent the cumulative expression of all 46 C19MC miRNAs (5p and 3p). B, 24 C19MC miRNAs that have 5p and 3p mature miRNA information in UESL tumors display miRNA-specific selective 5p vs. 3p expressional patterns.

    Techniques Used: RNA Sequencing Assay, Over Expression, Expressing

    UESL display aberrant transcriptional activity of the C19MC region. A novel PEG3/ZIM2 -C19MC fusion is identified. A, Read counts of mapped whole transcriptome show high levels of aberrant transcriptional activity in the C19MC region. Note that the abrupt starting location of transcriptional mapping is in different co-ordinates in different UESL samples, suggestive of sample specific fusional events. The genomic position of the experimentally verified fusion in PATWXD is indicated by the red arrow in panel-A and notably corresponds to the start (5’ end) of transcriptional activity in this sample. Hep3B cell line (hepatocellular carcinoma) and normal liver samples are shown at the bottom for comparison and as expected show negligible amounts of RNA mapping to this non-coding region. B, Targeted DNA sequencing of PATWXD UESL tumor showing abrupt end of read mapping near the C19MC start site (left) as well as in the PEG2/ZIM2 gene locus (right, shared gene region). The reads also mark the position of primers designed for gDNA PCR (one primer at 5’ end of reads and another at 3’end of reads for each locus (therefore one set of primers will form a nested primer set). C, Nested multiplex PCR of PATWXD genomic DNA showing amplicon (~550 bp) including the nested product (~450 bp). D, Paired end Sanger sequencing of ~550 bp product from panel-B showing the PEG3/ZIM2 locus fused to C19MC aberrant transcriptional start site.
    Figure Legend Snippet: UESL display aberrant transcriptional activity of the C19MC region. A novel PEG3/ZIM2 -C19MC fusion is identified. A, Read counts of mapped whole transcriptome show high levels of aberrant transcriptional activity in the C19MC region. Note that the abrupt starting location of transcriptional mapping is in different co-ordinates in different UESL samples, suggestive of sample specific fusional events. The genomic position of the experimentally verified fusion in PATWXD is indicated by the red arrow in panel-A and notably corresponds to the start (5’ end) of transcriptional activity in this sample. Hep3B cell line (hepatocellular carcinoma) and normal liver samples are shown at the bottom for comparison and as expected show negligible amounts of RNA mapping to this non-coding region. B, Targeted DNA sequencing of PATWXD UESL tumor showing abrupt end of read mapping near the C19MC start site (left) as well as in the PEG2/ZIM2 gene locus (right, shared gene region). The reads also mark the position of primers designed for gDNA PCR (one primer at 5’ end of reads and another at 3’end of reads for each locus (therefore one set of primers will form a nested primer set). C, Nested multiplex PCR of PATWXD genomic DNA showing amplicon (~550 bp) including the nested product (~450 bp). D, Paired end Sanger sequencing of ~550 bp product from panel-B showing the PEG3/ZIM2 locus fused to C19MC aberrant transcriptional start site.

    Techniques Used: Activity Assay, DNA Sequencing, Polymerase Chain Reaction, Multiplex Assay, Amplification, Sequencing

    22) Product Images from "Inflammation-dependent downregulation of miR-532-3p mediates apoptotic signaling in human sarcopenia through targeting BAK1"

    Article Title: Inflammation-dependent downregulation of miR-532-3p mediates apoptotic signaling in human sarcopenia through targeting BAK1

    Journal: International Journal of Biological Sciences

    doi: 10.7150/ijbs.41641

    p50 specifically bond to the promoter of miR-532-3p to repress its expression. (A) The occupancy of p50 on the promoter of miR-532-3p. The HSMM-1, HSMM1-NFKB1-KD and HSMM1-NFKB1-OE cells were subjected to ChIP assays using anti-p50, anti-STAT1 and IgG antibodies, followed by qRT-PCR analyses to measure the enrichment of p50 on the promoter of miR-532-3p. *** P
    Figure Legend Snippet: p50 specifically bond to the promoter of miR-532-3p to repress its expression. (A) The occupancy of p50 on the promoter of miR-532-3p. The HSMM-1, HSMM1-NFKB1-KD and HSMM1-NFKB1-OE cells were subjected to ChIP assays using anti-p50, anti-STAT1 and IgG antibodies, followed by qRT-PCR analyses to measure the enrichment of p50 on the promoter of miR-532-3p. *** P

    Techniques Used: Expressing, Chromatin Immunoprecipitation, Quantitative RT-PCR

    The expression of miR-532-3p was significantly decreased in sarcopenia patients. (A) The heat map of 20 miRNAs that were differentially expressed in sarcopenia patient samples. Three-paired muscle tissues from healthy controls and sarcopenia patients were subjected to RNA isolation and subsequent microarray assays. The top 20 miRNAs that were aberrantly expressed were shown. (B-G) Verification of three upregulated and three downregulated miRNA levels by qRT-PCR. Twenty-four-paired muscle tissues from healthy controls and sarcopenia patients were used for qRT-PCR analyses to measure the relative expression levels of miR-17-3p (B) , miR-192-3p (C) , miR-107 (D) , miR-532-3p (E) , miR-126-5p (F) , and miR-34a-3p (G) . The expression of individual miRNAs in one healthy control sample was defined as one-fold. ** P
    Figure Legend Snippet: The expression of miR-532-3p was significantly decreased in sarcopenia patients. (A) The heat map of 20 miRNAs that were differentially expressed in sarcopenia patient samples. Three-paired muscle tissues from healthy controls and sarcopenia patients were subjected to RNA isolation and subsequent microarray assays. The top 20 miRNAs that were aberrantly expressed were shown. (B-G) Verification of three upregulated and three downregulated miRNA levels by qRT-PCR. Twenty-four-paired muscle tissues from healthy controls and sarcopenia patients were used for qRT-PCR analyses to measure the relative expression levels of miR-17-3p (B) , miR-192-3p (C) , miR-107 (D) , miR-532-3p (E) , miR-126-5p (F) , and miR-34a-3p (G) . The expression of individual miRNAs in one healthy control sample was defined as one-fold. ** P

    Techniques Used: Expressing, Isolation, Microarray, Quantitative RT-PCR

    BAK1 was significantly increased in sarcopenia patients. (A) The heat map of 20 genes that were differentially expressed in sarcopenia patient samples. Three-paired muscle tissues from healthy controls and sarcopenia patients were subjected to RNA isolation and subsequent microarray assays. The top 20 genes that were aberrantly expressed were shown. (B-G) Verification of three upregulated and three downregulated gene levels by qRT-PCR. Twenty-four-paired muscle tissues from healthy controls and sarcopenia patients were used for qRT-PCR analyses to measure the relative expression levels of IL1B (B) , BAK1 (C) , SOD1 (D) , CDH1 (E) , GNG11 (F) , and ZAP70 (G) . The expression of individual genes in one healthy control sample was defined as one-fold. ** P
    Figure Legend Snippet: BAK1 was significantly increased in sarcopenia patients. (A) The heat map of 20 genes that were differentially expressed in sarcopenia patient samples. Three-paired muscle tissues from healthy controls and sarcopenia patients were subjected to RNA isolation and subsequent microarray assays. The top 20 genes that were aberrantly expressed were shown. (B-G) Verification of three upregulated and three downregulated gene levels by qRT-PCR. Twenty-four-paired muscle tissues from healthy controls and sarcopenia patients were used for qRT-PCR analyses to measure the relative expression levels of IL1B (B) , BAK1 (C) , SOD1 (D) , CDH1 (E) , GNG11 (F) , and ZAP70 (G) . The expression of individual genes in one healthy control sample was defined as one-fold. ** P

    Techniques Used: Isolation, Microarray, Quantitative RT-PCR, Expressing

    NFKB1/p50 specifically repressed the expression of miR-532-3p. (A) The transcription factor binding sites in the promoter of miR-532-3p. A 2000 bp-length promoter fragment was used to predict the transcription factor binding sites. The binding positions of NFKB1 (p50), STAT1 and AP-1 were indicated. (B-I) The effects of overexpressing or downregulating different transcription factors on miR-532-3p level. HSMM-1 and HSMM-2 cells were transfected with individual transcription factor-specific siRNAs and the corresponding overexpression vectors to generate the knockdown (KD) and overexpression (OE) cells. The resulting cells were subjected to RNA isolation, followed by the measurement of miR-532-3p level using qRT-PCR analyses. (B and C) The expression levels of NFKB1 (B) and miR-532-3p (C) in NFKB1-KD and NFKB1-OE cells. *** P
    Figure Legend Snippet: NFKB1/p50 specifically repressed the expression of miR-532-3p. (A) The transcription factor binding sites in the promoter of miR-532-3p. A 2000 bp-length promoter fragment was used to predict the transcription factor binding sites. The binding positions of NFKB1 (p50), STAT1 and AP-1 were indicated. (B-I) The effects of overexpressing or downregulating different transcription factors on miR-532-3p level. HSMM-1 and HSMM-2 cells were transfected with individual transcription factor-specific siRNAs and the corresponding overexpression vectors to generate the knockdown (KD) and overexpression (OE) cells. The resulting cells were subjected to RNA isolation, followed by the measurement of miR-532-3p level using qRT-PCR analyses. (B and C) The expression levels of NFKB1 (B) and miR-532-3p (C) in NFKB1-KD and NFKB1-OE cells. *** P

    Techniques Used: Expressing, Binding Assay, Transfection, Over Expression, Isolation, Quantitative RT-PCR

    23) Product Images from "LncRNA-MEG3 inhibits activation of hepatic stellate cells through SMO protein and miR-212"

    Article Title: LncRNA-MEG3 inhibits activation of hepatic stellate cells through SMO protein and miR-212

    Journal: Cell Death & Disease

    doi: 10.1038/s41419-018-1068-x

    MEG3 physically interacts with SMO protein. a The overall interaction propensity of MEG3 and SMO protein was predicted by catRAPID. b Predicted interaction between MEG3 (nucleotide positions 0–1200 nt) and SMO protein (amino acid residues 0–720). c RIP experiments were performed using SMO antibody in primary HSCs at Day 0. qRT-PCR was performed to detect pulled-down MEG3. hnRNP-K antibody and IgG were used as positive and negative controls, respectively. d SMO asscociated MEG3 was detected by regular RT-PCR. e Mapping the SMO interaction region of MEG3. Biotinylated RNAs corresponding to different fragments of MEG3 or its antisense sequences (red line) were co-incubated with cell lysates and associated SMO proteins were detected by immunoblotting
    Figure Legend Snippet: MEG3 physically interacts with SMO protein. a The overall interaction propensity of MEG3 and SMO protein was predicted by catRAPID. b Predicted interaction between MEG3 (nucleotide positions 0–1200 nt) and SMO protein (amino acid residues 0–720). c RIP experiments were performed using SMO antibody in primary HSCs at Day 0. qRT-PCR was performed to detect pulled-down MEG3. hnRNP-K antibody and IgG were used as positive and negative controls, respectively. d SMO asscociated MEG3 was detected by regular RT-PCR. e Mapping the SMO interaction region of MEG3. Biotinylated RNAs corresponding to different fragments of MEG3 or its antisense sequences (red line) were co-incubated with cell lysates and associated SMO proteins were detected by immunoblotting

    Techniques Used: Quantitative RT-PCR, Reverse Transcription Polymerase Chain Reaction, Incubation

    Downregulation of MEG3 in liver fibrosis. a Collagen and α-SMA were analyzed in CCl 4 mice by Masson staining and immunohistochemistry, respectively. Scale bar, 100 μm. b MEG3-1, MEG3-2, and MEG3-3 expressions were detected by qRT-PCR in CCl 4 mice. c Expressions of MEG3-1, MEG3-2, and MEG3-3 were analyzed in primary HSCs at Day 0 and Day 4. Primary HSCs were isolated from the livers of healthy mice. d MEG3 was analyzed in primary HSCs isolated from oil- or CCl 4 -treated mice. e MEG3 was analyzed in primary HSCs and primary hepatocytes from the livers of healthy mice. * P
    Figure Legend Snippet: Downregulation of MEG3 in liver fibrosis. a Collagen and α-SMA were analyzed in CCl 4 mice by Masson staining and immunohistochemistry, respectively. Scale bar, 100 μm. b MEG3-1, MEG3-2, and MEG3-3 expressions were detected by qRT-PCR in CCl 4 mice. c Expressions of MEG3-1, MEG3-2, and MEG3-3 were analyzed in primary HSCs at Day 0 and Day 4. Primary HSCs were isolated from the livers of healthy mice. d MEG3 was analyzed in primary HSCs isolated from oil- or CCl 4 -treated mice. e MEG3 was analyzed in primary HSCs and primary hepatocytes from the livers of healthy mice. * P

    Techniques Used: Mouse Assay, Staining, Immunohistochemistry, Quantitative RT-PCR, Isolation

    24) Product Images from "miR-146a suppresses cellular immune response during Japanese encephalitis virus JaOArS982 strain infection in human microglial cells"

    Article Title: miR-146a suppresses cellular immune response during Japanese encephalitis virus JaOArS982 strain infection in human microglial cells

    Journal: Journal of Neuroinflammation

    doi: 10.1186/s12974-015-0249-0

    JEV upregulates miR-146a, and miR-146a enhances viral replication. JEV infection upregulates miR-146a in CHME3 cells. (A) Human brain microglial cell line CHME3 was infected with JEV (MOI-5), and cells were harvested at 12, 24, and 48 h post infection. qRT-PCR with Taqman probes were used to determine miR-146a levels. RNU24 was used to normalize the fold change in miR-146a levels as compared to uninfected control. (B,C) CHME3 cells were transfected with scramble sequence or miR-146a mimic sequence (B) , Cy3-labeled scrambled anti-miR or anti-miR-146a (C) and infected by JEV 24 h post transfection. The cells were harvested at 12, 24, and 48 h post infection for RNA isolation. Viral RNA level was determined by RT-PCR using JEV NS3 specific primers. The fold change was normalized by GAPDH RNA levels. Fold change was determined by 2 −∆∆C T method. For statistical analysis, scrambled miR and Cy3-labeled scrambled anti-miR group was used as control. (D) Western blots showing upregulation of viral NS1 protein in miR-146a overexpressing cells. A 100 pmol of scrambled sequence and miR-146a mimic was used. Scramble + JEV group was used as control for comparison. The cells were infected by JEV (MOI-5) and harvested 24 and 48 h post infection. All the experiments were done three times independently. The data are shown as mean ± SE from three independent experiments. The fold change is statistically significant. The fold change is significant where *denotes P
    Figure Legend Snippet: JEV upregulates miR-146a, and miR-146a enhances viral replication. JEV infection upregulates miR-146a in CHME3 cells. (A) Human brain microglial cell line CHME3 was infected with JEV (MOI-5), and cells were harvested at 12, 24, and 48 h post infection. qRT-PCR with Taqman probes were used to determine miR-146a levels. RNU24 was used to normalize the fold change in miR-146a levels as compared to uninfected control. (B,C) CHME3 cells were transfected with scramble sequence or miR-146a mimic sequence (B) , Cy3-labeled scrambled anti-miR or anti-miR-146a (C) and infected by JEV 24 h post transfection. The cells were harvested at 12, 24, and 48 h post infection for RNA isolation. Viral RNA level was determined by RT-PCR using JEV NS3 specific primers. The fold change was normalized by GAPDH RNA levels. Fold change was determined by 2 −∆∆C T method. For statistical analysis, scrambled miR and Cy3-labeled scrambled anti-miR group was used as control. (D) Western blots showing upregulation of viral NS1 protein in miR-146a overexpressing cells. A 100 pmol of scrambled sequence and miR-146a mimic was used. Scramble + JEV group was used as control for comparison. The cells were infected by JEV (MOI-5) and harvested 24 and 48 h post infection. All the experiments were done three times independently. The data are shown as mean ± SE from three independent experiments. The fold change is statistically significant. The fold change is significant where *denotes P

    Techniques Used: Infection, Quantitative RT-PCR, Transfection, Sequencing, Labeling, Isolation, Reverse Transcription Polymerase Chain Reaction, Western Blot

    25) Product Images from "Comparison of different extraction techniques to profile microRNAs from human sera and peripheral blood mononuclear cells"

    Article Title: Comparison of different extraction techniques to profile microRNAs from human sera and peripheral blood mononuclear cells

    Journal: BMC Genomics

    doi: 10.1186/1471-2164-15-395

    Comparison of miRNAs expression profiles from human PBMCs and serum. Human PBMCs (1×10 6 cells) and serum (300 μL) samples were extracted by Macherey-Nagel (MN) and Qiagen (Q) kits. A - Number of miRNAs detected from PBMCs RNA samples using TLDA cards. B - Correlation analysis from PBMCs samples. C - Bland-Altman analysis MN versus Q from PBMCs. D - Number of miRNAs detected from serum RNA samples using TLDA cards. E - Correlation analysis from serum samples. F - Bland-Altman analysis MN versus Q from serum. TLDA data were obtained from biological triplicate for each extraction kits. Analysis using mean Ct values of triplicate. Only miRNAs with Ct
    Figure Legend Snippet: Comparison of miRNAs expression profiles from human PBMCs and serum. Human PBMCs (1×10 6 cells) and serum (300 μL) samples were extracted by Macherey-Nagel (MN) and Qiagen (Q) kits. A - Number of miRNAs detected from PBMCs RNA samples using TLDA cards. B - Correlation analysis from PBMCs samples. C - Bland-Altman analysis MN versus Q from PBMCs. D - Number of miRNAs detected from serum RNA samples using TLDA cards. E - Correlation analysis from serum samples. F - Bland-Altman analysis MN versus Q from serum. TLDA data were obtained from biological triplicate for each extraction kits. Analysis using mean Ct values of triplicate. Only miRNAs with Ct

    Techniques Used: Expressing, TLDA Assay

    Assessment of bias in RNA isolation from PBMCs. Assessment of bias in RNA isolation from PBMCs using the Macherey-Nagel (MN) kit, comparison of extraction from 3×10 6 and 1×10 6 cells with a same amount of RNA for RT (130 ng). A - Bland-Altman analysis 3×10 6 versus 1x10 6 cells. B - Plot of the difference in Ct values of the two conditions (x-axis) and the GC content of miRNAs detected in these two settings (y-axis). C - Plot of the difference in Ct values of the conditions 300 vs 100 ng (x-axis) and the GC content of the miRNAs detected in these two settings (y-axis). The Pearson correlation coefficient is indicated. TLDA datas from biological duplicate. Analysis using mean CT values of common miRNAs. Only miRNAs with Ct
    Figure Legend Snippet: Assessment of bias in RNA isolation from PBMCs. Assessment of bias in RNA isolation from PBMCs using the Macherey-Nagel (MN) kit, comparison of extraction from 3×10 6 and 1×10 6 cells with a same amount of RNA for RT (130 ng). A - Bland-Altman analysis 3×10 6 versus 1x10 6 cells. B - Plot of the difference in Ct values of the two conditions (x-axis) and the GC content of miRNAs detected in these two settings (y-axis). C - Plot of the difference in Ct values of the conditions 300 vs 100 ng (x-axis) and the GC content of the miRNAs detected in these two settings (y-axis). The Pearson correlation coefficient is indicated. TLDA datas from biological duplicate. Analysis using mean CT values of common miRNAs. Only miRNAs with Ct

    Techniques Used: Isolation, TLDA Assay

    Impact of the RNA quantity on miRNA TLDA profiles. miRNA TLDA profiles were compared using three different RNA quantities for RT (10, 100 and 300 ng), of the same RNA sample extracted from 3×10 6 PBMCs by Macherey-Nagel. A - Bland-Altman analysis: condition 100 ng of RNA for RT versus 10 ng. B - Bland-Altman analysis: condition 300 ng of RNA for RT versus 100 ng. C - Venn diagram with the detectable miRNAs. Only miRNAs with Ct
    Figure Legend Snippet: Impact of the RNA quantity on miRNA TLDA profiles. miRNA TLDA profiles were compared using three different RNA quantities for RT (10, 100 and 300 ng), of the same RNA sample extracted from 3×10 6 PBMCs by Macherey-Nagel. A - Bland-Altman analysis: condition 100 ng of RNA for RT versus 10 ng. B - Bland-Altman analysis: condition 300 ng of RNA for RT versus 100 ng. C - Venn diagram with the detectable miRNAs. Only miRNAs with Ct

    Techniques Used: TLDA Assay

    26) Product Images from "Vascular Plant One-Zinc-Finger (VOZ) Transcription Factors Are Positive Regulators of Salt Tolerance in Arabidopsis"

    Article Title: Vascular Plant One-Zinc-Finger (VOZ) Transcription Factors Are Positive Regulators of Salt Tolerance in Arabidopsis

    Journal: International Journal of Molecular Sciences

    doi: 10.3390/ijms19123731

    Validation of up- and down-regulated genes in DKO . ( a ) RT-qPCR validation of randomly selected up-regulated genes. ( b ) RT-qPCR of randomly selected down-regulated genes. Left panels in ( a , b ) show relative sequence read abundance (Integrated Genome Browser view) as histograms in WT, DKO (voz1-1 voz2-1) and COMP2-4 lines. The Y-axis indicates read depth with the same scale for all three lines. The gene structure is shown below the read depth profile. The lines represent introns and the boxes represent exons. The thinner boxes represent 5′ and 3′ UTRs. Right panels in ( a , b ) show fold change in expression level relative to WT. WT values were considered as 1. Student’s t -test was performed and significant differences ( p
    Figure Legend Snippet: Validation of up- and down-regulated genes in DKO . ( a ) RT-qPCR validation of randomly selected up-regulated genes. ( b ) RT-qPCR of randomly selected down-regulated genes. Left panels in ( a , b ) show relative sequence read abundance (Integrated Genome Browser view) as histograms in WT, DKO (voz1-1 voz2-1) and COMP2-4 lines. The Y-axis indicates read depth with the same scale for all three lines. The gene structure is shown below the read depth profile. The lines represent introns and the boxes represent exons. The thinner boxes represent 5′ and 3′ UTRs. Right panels in ( a , b ) show fold change in expression level relative to WT. WT values were considered as 1. Student’s t -test was performed and significant differences ( p

    Techniques Used: Quantitative RT-PCR, Sequencing, Expressing

    Validation of genotypes used for RNA-Seq. ( a ) Top panel: Phenotype of 30-day-old plants of wild-type (WT), double knockout ( DKO) mutant ( voz1-1 voz2-1 ) and DKO complemented line (COMP2-4) grown at 21 °C under day neutral conditions at 60% humidity. ( b ) Genomic PCR of three genotypes used for RNA-Seq. Top panel (PCR with VOZ2 -specific primers); second panel (PCR with VOZ1 -specific primers); third panel (PCR with T-DNA specific Lba1 and VOZ2 -specific reverse primer); fourth panel (PCR with Tn insertion specific primer P745 and VOZ1-specific forward primer); bottom panel (PCR with CYCLOPHILIN -specific primers). In all cases expected size PCR product was obtained. ( c ) Analysis of expression of VOZ1 (top panel), VOZ2 (middle panel) and CYCLOPHILIN (bottom panel) using sqRT-PCR in 30-day-old seedlings of WT, DKO mutant ( voz1-1 voz2-1 ) and DKO complemented line (COMP2-4).
    Figure Legend Snippet: Validation of genotypes used for RNA-Seq. ( a ) Top panel: Phenotype of 30-day-old plants of wild-type (WT), double knockout ( DKO) mutant ( voz1-1 voz2-1 ) and DKO complemented line (COMP2-4) grown at 21 °C under day neutral conditions at 60% humidity. ( b ) Genomic PCR of three genotypes used for RNA-Seq. Top panel (PCR with VOZ2 -specific primers); second panel (PCR with VOZ1 -specific primers); third panel (PCR with T-DNA specific Lba1 and VOZ2 -specific reverse primer); fourth panel (PCR with Tn insertion specific primer P745 and VOZ1-specific forward primer); bottom panel (PCR with CYCLOPHILIN -specific primers). In all cases expected size PCR product was obtained. ( c ) Analysis of expression of VOZ1 (top panel), VOZ2 (middle panel) and CYCLOPHILIN (bottom panel) using sqRT-PCR in 30-day-old seedlings of WT, DKO mutant ( voz1-1 voz2-1 ) and DKO complemented line (COMP2-4).

    Techniques Used: RNA Sequencing Assay, Double Knockout, Mutagenesis, Polymerase Chain Reaction, Expressing

    Analysis of differentially expressed genes. ( a ) Heatmap representation of differentially expressed genes in WT , DKO and COMP2-4 (COMP) plants. Expression values were used to generate the heatmap using the Heatmapper. Columns represent samples and rows represent genes. Color scale indicates the gene expression level. Green indicates high expression and red Indicates low expression. ( b ) Box-and-whisker plots showing expression of differentially expressed (DE) genes in different genotypes. ( c ) Gene counts of total, up and down-regulated DE genes that are either fully or partially complemented in COMP2-4 line.
    Figure Legend Snippet: Analysis of differentially expressed genes. ( a ) Heatmap representation of differentially expressed genes in WT , DKO and COMP2-4 (COMP) plants. Expression values were used to generate the heatmap using the Heatmapper. Columns represent samples and rows represent genes. Color scale indicates the gene expression level. Green indicates high expression and red Indicates low expression. ( b ) Box-and-whisker plots showing expression of differentially expressed (DE) genes in different genotypes. ( c ) Gene counts of total, up and down-regulated DE genes that are either fully or partially complemented in COMP2-4 line.

    Techniques Used: Expressing, Whisker Assay

    Germination and seedling growth of WT, mutants and complemented line in the presence of NaCl. ( a ) VOZ Double mutant (DKO) exhibits delayed germination under salt stress. The time course of seed germination of WT, DKO, COMP2-4 (left panels), voz1-1 , voz2-1 and voz2-2 (right panels) in the presence of 0, 50, 100 and 150 mM NaCl. Each value shown here is mean of three biological replicates with n = 10. The error bars represent SD. ( b ) VOZ Double mutant (DKO) is hypersensitive to salt stress. Left panel: Growth of seedlings of WT, DKO and COMP2-4 on MS (Murashige and Skoog medium) plates containing different concentrations of NaCl. Seeds were plated on 1/2 strength MS medium supplemented with 0, 50, 100 and 150 mM of NaCl and were allowed to germinate and grow for two weeks. The photographs were taken after two weeks. Right panel, top: Seedling fresh weight. Right panel, bottom: Seedling root length at different concentrations of NaCl was measured for all genotypes and plotted as % relative to growth on normal (0 mM) MS medium. Three biological replicates were used. Eight to ten seedlings for each genotype per treatment for each biological replicate were included. Student’s t -test was performed and significant differences ( p ≤ 0.05) among samples are labeled with different letters. The error bars represent SD. ( c ) Single mutants of VOZs are not hypersensitive to salt stress. Top: Growth of seedlings of WT, COMP2-4, voz1-1 , voz2-1 and voz2-2 on MS plates containing different concentrations of salt. Seeds were plated on half-strength MS medium supplemented with 0, 50, 100 or 150 mM of NaCl and were allowed to germinate and grow for two weeks. The photographs were taken after two weeks. Bottom: Seedling root length at different concentrations of NaCl was measured for all genotypes and plotted as % relative to growth on normal (0 mM) MS medium. Three biological replicates were used. For each genotype, eight to ten seedlings per treatment and for each biological replicate were used. Student’s t -test was performed and significant differences ( p ≤ 0.05) among samples are labeled with different letters. The error bars represent SD.
    Figure Legend Snippet: Germination and seedling growth of WT, mutants and complemented line in the presence of NaCl. ( a ) VOZ Double mutant (DKO) exhibits delayed germination under salt stress. The time course of seed germination of WT, DKO, COMP2-4 (left panels), voz1-1 , voz2-1 and voz2-2 (right panels) in the presence of 0, 50, 100 and 150 mM NaCl. Each value shown here is mean of three biological replicates with n = 10. The error bars represent SD. ( b ) VOZ Double mutant (DKO) is hypersensitive to salt stress. Left panel: Growth of seedlings of WT, DKO and COMP2-4 on MS (Murashige and Skoog medium) plates containing different concentrations of NaCl. Seeds were plated on 1/2 strength MS medium supplemented with 0, 50, 100 and 150 mM of NaCl and were allowed to germinate and grow for two weeks. The photographs were taken after two weeks. Right panel, top: Seedling fresh weight. Right panel, bottom: Seedling root length at different concentrations of NaCl was measured for all genotypes and plotted as % relative to growth on normal (0 mM) MS medium. Three biological replicates were used. Eight to ten seedlings for each genotype per treatment for each biological replicate were included. Student’s t -test was performed and significant differences ( p ≤ 0.05) among samples are labeled with different letters. The error bars represent SD. ( c ) Single mutants of VOZs are not hypersensitive to salt stress. Top: Growth of seedlings of WT, COMP2-4, voz1-1 , voz2-1 and voz2-2 on MS plates containing different concentrations of salt. Seeds were plated on half-strength MS medium supplemented with 0, 50, 100 or 150 mM of NaCl and were allowed to germinate and grow for two weeks. The photographs were taken after two weeks. Bottom: Seedling root length at different concentrations of NaCl was measured for all genotypes and plotted as % relative to growth on normal (0 mM) MS medium. Three biological replicates were used. For each genotype, eight to ten seedlings per treatment and for each biological replicate were used. Student’s t -test was performed and significant differences ( p ≤ 0.05) among samples are labeled with different letters. The error bars represent SD.

    Techniques Used: Mutagenesis, Mass Spectrometry, Labeling

    27) Product Images from "Identification of the X-linked germ cell specific miRNAs (XmiRs) and their functions"

    Article Title: Identification of the X-linked germ cell specific miRNAs (XmiRs) and their functions

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0211739

    Relationship between target mRNAs of XmiRs and generation of ΔXmiRs mice. (A) A dendrogram of hierarchical clustering analysis of target mRNAs of XmiRs and their neighboring miRNAs. (B) Venn diagram showing the relationship among putative target mRNAs of miR-741-3p, miR-871-3p, and miR-880-3p. Corresponding gene lists are shown in S3 Table . (C) A schematic presentation of the WT and ΔXmiRs locus. gR-741 and gR-871 represent positions of guide RNAs used for genome editing. (D) Representative PCR for genotyping of WT and ΔXmiRs (OT84) mice. Arrows in the right panel represent primers used for PCR. (E) Expression of XmiRs in WT and a ΔXmiRs testes (F2 of OT84) determined with semi-quantitative RT-PCR analysis. U6 snRNA was used as an internal control. (F) HE-stained sections of seminiferous tubules in WT (left) and ΔXmiR (F2 of OT100) (right) testes at 8, 12, 16, and 30 weeks of age. The second and fourth panels for 30 weeks show higher magnification views corresponding to the rectangular area in the first and third panels. Lower two panels show mildly affected seminiferous tubules. Arrowheads show abnormal seminiferous tubules. Scale bar = 50 μm (8, 12, 16 weeks), 200 μm (30 weeks, lower magnification), 100 μm (30 weeks, higher magnification).
    Figure Legend Snippet: Relationship between target mRNAs of XmiRs and generation of ΔXmiRs mice. (A) A dendrogram of hierarchical clustering analysis of target mRNAs of XmiRs and their neighboring miRNAs. (B) Venn diagram showing the relationship among putative target mRNAs of miR-741-3p, miR-871-3p, and miR-880-3p. Corresponding gene lists are shown in S3 Table . (C) A schematic presentation of the WT and ΔXmiRs locus. gR-741 and gR-871 represent positions of guide RNAs used for genome editing. (D) Representative PCR for genotyping of WT and ΔXmiRs (OT84) mice. Arrows in the right panel represent primers used for PCR. (E) Expression of XmiRs in WT and a ΔXmiRs testes (F2 of OT84) determined with semi-quantitative RT-PCR analysis. U6 snRNA was used as an internal control. (F) HE-stained sections of seminiferous tubules in WT (left) and ΔXmiR (F2 of OT100) (right) testes at 8, 12, 16, and 30 weeks of age. The second and fourth panels for 30 weeks show higher magnification views corresponding to the rectangular area in the first and third panels. Lower two panels show mildly affected seminiferous tubules. Arrowheads show abnormal seminiferous tubules. Scale bar = 50 μm (8, 12, 16 weeks), 200 μm (30 weeks, lower magnification), 100 μm (30 weeks, higher magnification).

    Techniques Used: Mouse Assay, Polymerase Chain Reaction, Expressing, Quantitative RT-PCR, Staining

    28) Product Images from "Synergistic Action of 1,2-Epoxy-3 (3- (3,4-dimethoxyphenyl)- 4H-1-benzopiyran-4-on) Propane with Doxorubicin and Cisplatin through Increasing of p53, TIMP-3, and MicroRNA-34a in Cervical Cancer Cell Line (HeLa)"

    Article Title: Synergistic Action of 1,2-Epoxy-3 (3- (3,4-dimethoxyphenyl)- 4H-1-benzopiyran-4-on) Propane with Doxorubicin and Cisplatin through Increasing of p53, TIMP-3, and MicroRNA-34a in Cervical Cancer Cell Line (HeLa)

    Journal: Asian Pacific Journal of Cancer Prevention : APJCP

    doi: 10.22034/APJCP.2018.19.10.2955

    Effect of EPI, DOX, CIS, and Their Combination on p53 of HeLa Cells (A). TIMP-3 of HeLa cells (B). MiR-34a of HeLa cells (C). a, Significantly different from Group 1; b, Significantly different from Group 5; c, Significantly different from Group 7 (p
    Figure Legend Snippet: Effect of EPI, DOX, CIS, and Their Combination on p53 of HeLa Cells (A). TIMP-3 of HeLa cells (B). MiR-34a of HeLa cells (C). a, Significantly different from Group 1; b, Significantly different from Group 5; c, Significantly different from Group 7 (p

    Techniques Used:

    29) Product Images from "lncRNA-ES3/miR-34c-5p/BMF axis is involved in regulating high-glucose-induced calcification/senescence of VSMCs"

    Article Title: lncRNA-ES3/miR-34c-5p/BMF axis is involved in regulating high-glucose-induced calcification/senescence of VSMCs

    Journal: Aging (Albany NY)

    doi: 10.18632/aging.101758

    miR-34c-5p inhibiting the calcification/senescence of HA-VSMCs. ( A ) HA-VSMCs was transfected with miRNA NC, miR-34c-5p mimics, and miR-34c-5p inhibitor, and subjected to qRT–PCR analysis of miR-34c-5p. ( B–D ) HA-VSMCs were transfected with miRNA NC, miR-34c-5p mimics, and miR-34c-5p inhibitor, respectively. Then, ALP activity, OC secretion, and Runx2, p16, and p21 protein levels were measured. The data are expressed as mean ± SD, n=3, * p
    Figure Legend Snippet: miR-34c-5p inhibiting the calcification/senescence of HA-VSMCs. ( A ) HA-VSMCs was transfected with miRNA NC, miR-34c-5p mimics, and miR-34c-5p inhibitor, and subjected to qRT–PCR analysis of miR-34c-5p. ( B–D ) HA-VSMCs were transfected with miRNA NC, miR-34c-5p mimics, and miR-34c-5p inhibitor, respectively. Then, ALP activity, OC secretion, and Runx2, p16, and p21 protein levels were measured. The data are expressed as mean ± SD, n=3, * p

    Techniques Used: Transfection, Quantitative RT-PCR, ALP Assay, Activity Assay

    miR-34c-5p inhibited whereas lncRNA-ES3 and BMF promoted the calcification/senescence of HA-VSMCs. ( A and B ) The ALP activity and OC secretion were detected in HA-VSMCs with different treatment, respectively. ( C ) Representative images of Western blot analyses of p16, p21, Runx2, and BMF in HA-VSMCs with different treatment are shown. ( D and E ) Alizarin Red S staining showed the mineralized nodules in HA-VSMCs, and the calcium content was extracted with cetylpyridinium chloride and quantified by spectrophotometry. Representative pictures are shown and the scale bar is 100 μm. ( F and G ) SA-β-gal staining showed the senescent cells of HA-VSMCs with different treatment, and the quantification of SA-β-gal-stained positive cells is shown. Representative pictures are shown and the scale bar is 100 μm. ( H ) The model proposed to explain the mechanism of miR-34c-5p in inhibiting VSMC calcification/senescence is shown. Herein, lncRNA-ES3 inhibits miR-34c-5p expression, enhances the expression of BMF, and finally promotes calcification/senescence of VSMCs. The data are expressed as mean ± SD, n=3, * p
    Figure Legend Snippet: miR-34c-5p inhibited whereas lncRNA-ES3 and BMF promoted the calcification/senescence of HA-VSMCs. ( A and B ) The ALP activity and OC secretion were detected in HA-VSMCs with different treatment, respectively. ( C ) Representative images of Western blot analyses of p16, p21, Runx2, and BMF in HA-VSMCs with different treatment are shown. ( D and E ) Alizarin Red S staining showed the mineralized nodules in HA-VSMCs, and the calcium content was extracted with cetylpyridinium chloride and quantified by spectrophotometry. Representative pictures are shown and the scale bar is 100 μm. ( F and G ) SA-β-gal staining showed the senescent cells of HA-VSMCs with different treatment, and the quantification of SA-β-gal-stained positive cells is shown. Representative pictures are shown and the scale bar is 100 μm. ( H ) The model proposed to explain the mechanism of miR-34c-5p in inhibiting VSMC calcification/senescence is shown. Herein, lncRNA-ES3 inhibits miR-34c-5p expression, enhances the expression of BMF, and finally promotes calcification/senescence of VSMCs. The data are expressed as mean ± SD, n=3, * p

    Techniques Used: ALP Assay, Activity Assay, Western Blot, Staining, Spectrophotometry, Expressing

    The expression of miR-34c-5p in HG-induced HA-VSMCs. ( A ) HA-VSMCs were treated with NG, OC, or HG for 14 days and then subjected to Alizarin Red S staining. The calcium content was extracted with cetylpyridinium chloride and quantified by spectrophotometry. Representative pictures are shown and the scale bar is 100 μm. ( B ) HA-VSMCs were treated with NG, OC, or HG for 72 hours and then subjected to SA-β-gal staining. Semi-quantitative analysis of SA-β-gal positive cells were performed using Image J. ( C and D ) qRT-PCR showing the expression of miR-3c-5p and miR-34c-3p in the above three groups. The data are expressed as mean ± SD, n=3, ** p
    Figure Legend Snippet: The expression of miR-34c-5p in HG-induced HA-VSMCs. ( A ) HA-VSMCs were treated with NG, OC, or HG for 14 days and then subjected to Alizarin Red S staining. The calcium content was extracted with cetylpyridinium chloride and quantified by spectrophotometry. Representative pictures are shown and the scale bar is 100 μm. ( B ) HA-VSMCs were treated with NG, OC, or HG for 72 hours and then subjected to SA-β-gal staining. Semi-quantitative analysis of SA-β-gal positive cells were performed using Image J. ( C and D ) qRT-PCR showing the expression of miR-3c-5p and miR-34c-3p in the above three groups. The data are expressed as mean ± SD, n=3, ** p

    Techniques Used: Expressing, Staining, Spectrophotometry, Quantitative RT-PCR

    lncRNA-ES3 suppressed miR-34c-5p expression by direct interaction. ( A ) Schematic representation of the putative binding sites between lncRNA-ES3 and miR-34c-5p, and the mutant sites in Mut-lncRNA-ES3 reporter were underlined. ( B ) qRT-PCR showed the expression of lncRNA-ES3 in HA-VSMCs cultured with NG, OC, and HG. ( C ) HA-VSMCs was transfected with miRNA NC and miR-34c-5p mimics and harvested for the examination of lncRNA-ES3 by qRT-PCR. ( D ) The inhibitory efficiency of shRNAs targeting lncRNA-ES3 was verified by qRT-PCR. ( E ) HA-VSMCs were transfected with shRNA NC and shRNA-ES3-2, and the expression of miR-34c-5p was detected by qRT-PCR. ( F ) The WT-lncRNA-ES3 3’UTR and the Mut-lncRNA-ES3 3’UTR reporters were co-transfected with miR-34c-5p mimics or control oligos into HA-VSMCs. Forty-eight hours after transfection, luciferase activities were measured. ( G ) The expression of lncRNA-ES3 was detected by qRT-PCR after biotin-labeled miR-34c-5p pull-down assay. ( H ) RIP and qRT-PCR assays were performed to explore the binding efficiency of miR-34c-5p and lncRNA-ES3 to Ago2 protein in HA-VSMCs. The data are expressed as mean ± SD, n=3, * p
    Figure Legend Snippet: lncRNA-ES3 suppressed miR-34c-5p expression by direct interaction. ( A ) Schematic representation of the putative binding sites between lncRNA-ES3 and miR-34c-5p, and the mutant sites in Mut-lncRNA-ES3 reporter were underlined. ( B ) qRT-PCR showed the expression of lncRNA-ES3 in HA-VSMCs cultured with NG, OC, and HG. ( C ) HA-VSMCs was transfected with miRNA NC and miR-34c-5p mimics and harvested for the examination of lncRNA-ES3 by qRT-PCR. ( D ) The inhibitory efficiency of shRNAs targeting lncRNA-ES3 was verified by qRT-PCR. ( E ) HA-VSMCs were transfected with shRNA NC and shRNA-ES3-2, and the expression of miR-34c-5p was detected by qRT-PCR. ( F ) The WT-lncRNA-ES3 3’UTR and the Mut-lncRNA-ES3 3’UTR reporters were co-transfected with miR-34c-5p mimics or control oligos into HA-VSMCs. Forty-eight hours after transfection, luciferase activities were measured. ( G ) The expression of lncRNA-ES3 was detected by qRT-PCR after biotin-labeled miR-34c-5p pull-down assay. ( H ) RIP and qRT-PCR assays were performed to explore the binding efficiency of miR-34c-5p and lncRNA-ES3 to Ago2 protein in HA-VSMCs. The data are expressed as mean ± SD, n=3, * p

    Techniques Used: Expressing, Binding Assay, Mutagenesis, Quantitative RT-PCR, Cell Culture, Transfection, shRNA, Luciferase, Labeling, Pull Down Assay

    BMF was the target of miR-34c-5p. ( A ) Schematic representation of the miR-34c-5p putative target sites in BMF 3’UTR and alignment of miR-34c-5p with WT and Mut BMF 3’UTR showing pairing. The mutated nucleotides were underlined. ( B and C ) HA-VSMCs were transfected with miRNA NC, miR-34c-5p mimics, and miR-34c-5p inhibitors, and harvested for the examination of BMF mRNA and protein. ( D ) The WT-BMF 3’UTR and Mut-BMF 3’UTR were co-transfected with miR-34c-5p mimics or control oligos into HA-VSMCs. Forty-eight hours after transfection, luciferase activities were measured. ( E and F ) qRT-PCR and Western blot analysis showed the expression level of BMF in HA-VSMCs cultured with NG, OC, and HG. ( G ) HA-VSMCs were transfected with shRNAs NC and shlncRNA-ES3-2, and the protein level of BMF was detected by Western blot. The data are expressed as mean ± SD, n=3, * p
    Figure Legend Snippet: BMF was the target of miR-34c-5p. ( A ) Schematic representation of the miR-34c-5p putative target sites in BMF 3’UTR and alignment of miR-34c-5p with WT and Mut BMF 3’UTR showing pairing. The mutated nucleotides were underlined. ( B and C ) HA-VSMCs were transfected with miRNA NC, miR-34c-5p mimics, and miR-34c-5p inhibitors, and harvested for the examination of BMF mRNA and protein. ( D ) The WT-BMF 3’UTR and Mut-BMF 3’UTR were co-transfected with miR-34c-5p mimics or control oligos into HA-VSMCs. Forty-eight hours after transfection, luciferase activities were measured. ( E and F ) qRT-PCR and Western blot analysis showed the expression level of BMF in HA-VSMCs cultured with NG, OC, and HG. ( G ) HA-VSMCs were transfected with shRNAs NC and shlncRNA-ES3-2, and the protein level of BMF was detected by Western blot. The data are expressed as mean ± SD, n=3, * p

    Techniques Used: Transfection, Luciferase, Quantitative RT-PCR, Western Blot, Expressing, Cell Culture

    30) Product Images from "Nexilin/NEXN controls actin polymerization in smooth muscle and is regulated by myocardin family coactivators and YAP"

    Article Title: Nexilin/NEXN controls actin polymerization in smooth muscle and is regulated by myocardin family coactivators and YAP

    Journal: Scientific Reports

    doi: 10.1038/s41598-018-31328-2

    Knockdown of Nexilin/ NEXN reduces actin polymerization and SMC marker expression. NEXN was silenced using a short hairpin adenoviral construct (sh-NEXN) and the contents of NEXN and a number of SMC differentiation markers were examined at the mRNA (panel A, N = 6–9) and protein levels (panels B and C, N = 12). Panel D shows that depolymerization of actin using LatB reduces SRF expression in both human bladder and coronary artery SMCs (HBSMCs, N = 8; HCASMCs, N = 9). Panel E shows phalloidin staining of actin filaments in control cell (Null) and after NEXN silencing (sh-NEXN). The scale bar represents 50 μm. Panel F shows a sedimentation assay to determine filamentous (F-) and globular (G-) actin in control cells (null) and after silencing of NEXN . Panel G shows the normalized F- to G-actin ratio in bladder and coronary artery SMCs (HBSMCs, N = 12; HCASMCs, N = 6). Panel H shows that polymerization of actin using jasplakinolide (Jasp) increases MYH11 in HBSMCs in control conditions and after NEXN silencing (N = 6). Panel I shows cell density at different times following the creation of a cell-free area in the culture dish (N = 9–10). Panel J shows the speed of cell movement within the cell-free area (N = 19 and 22 motile cells in Null and sh- NEXN , respectively). Panel K shows a cell viability assay comparing control and NEXN -silenced cells (N = 12 throughout). The effect of NEXN silencing on cell migration was confirmed using an independent siRNA in L (N = 9). The associated repression of the NEXN protein is shown in ( M ) (N = 6). The schematic illustration in panel N summarizes our findings regarding the transcriptional control of NEXN and its impact on actin polymerization and cell motility. Several aspects of this model, including the involvement of a ( G ) protein-coupled receptor in the S1P effect, were not directly tested here, and they are thus drawn in grey.
    Figure Legend Snippet: Knockdown of Nexilin/ NEXN reduces actin polymerization and SMC marker expression. NEXN was silenced using a short hairpin adenoviral construct (sh-NEXN) and the contents of NEXN and a number of SMC differentiation markers were examined at the mRNA (panel A, N = 6–9) and protein levels (panels B and C, N = 12). Panel D shows that depolymerization of actin using LatB reduces SRF expression in both human bladder and coronary artery SMCs (HBSMCs, N = 8; HCASMCs, N = 9). Panel E shows phalloidin staining of actin filaments in control cell (Null) and after NEXN silencing (sh-NEXN). The scale bar represents 50 μm. Panel F shows a sedimentation assay to determine filamentous (F-) and globular (G-) actin in control cells (null) and after silencing of NEXN . Panel G shows the normalized F- to G-actin ratio in bladder and coronary artery SMCs (HBSMCs, N = 12; HCASMCs, N = 6). Panel H shows that polymerization of actin using jasplakinolide (Jasp) increases MYH11 in HBSMCs in control conditions and after NEXN silencing (N = 6). Panel I shows cell density at different times following the creation of a cell-free area in the culture dish (N = 9–10). Panel J shows the speed of cell movement within the cell-free area (N = 19 and 22 motile cells in Null and sh- NEXN , respectively). Panel K shows a cell viability assay comparing control and NEXN -silenced cells (N = 12 throughout). The effect of NEXN silencing on cell migration was confirmed using an independent siRNA in L (N = 9). The associated repression of the NEXN protein is shown in ( M ) (N = 6). The schematic illustration in panel N summarizes our findings regarding the transcriptional control of NEXN and its impact on actin polymerization and cell motility. Several aspects of this model, including the involvement of a ( G ) protein-coupled receptor in the S1P effect, were not directly tested here, and they are thus drawn in grey.

    Techniques Used: Marker, Expressing, Construct, Staining, Sedimentation, Viability Assay, Migration

    NEXN correlates with gene products that control and respond to changes in actin polymerization and Nexilin is reduced by depolymerization of actin. Correlations of NEXN versus all other RNAs in the top-ten NEXN expressing tissues were examined (data from GTExPortal). The sum of correlation coefficients for individual RNAs across tissues was calculated (R sum ) and the positive extreme of this distribution was plotted ( A ). Actin controlling and responding gene products represented in the extreme are highlighted in blue colors. Examples of NEXN correlations in the human coronary artery (N = 133) are shown in panels B through ( D ). P-values and Spearman Rho values are given in the respective panels. Panels E and F show mRNA data for NEXN in cultured human bladder (HBSMCs, N = 8) and coronary artery (HCASMCs, N = 9) SMCs after treatment with Latrunculin B (LatB). Panels H and I show protein data for Nexilin/ NEXN in the presence and absence of LatB (HBSMCs, 300 nM, N = 12; HCASMCs, 100 nM, N = 10). The top micrographs in panel J shows confocal imaging of YAP (red) on the left, and YAP (green) and CAV1 (red) on the right. The bottom row shows YAP (red) and Nexilin (green). The high magnification overlay at the bottom right shows partial colocalization of YAP and Nexilin at the cell membrane in yellow. All micrographs are from cross-sectioned HBSMCs and white scale bars represent 5 μm throughout.
    Figure Legend Snippet: NEXN correlates with gene products that control and respond to changes in actin polymerization and Nexilin is reduced by depolymerization of actin. Correlations of NEXN versus all other RNAs in the top-ten NEXN expressing tissues were examined (data from GTExPortal). The sum of correlation coefficients for individual RNAs across tissues was calculated (R sum ) and the positive extreme of this distribution was plotted ( A ). Actin controlling and responding gene products represented in the extreme are highlighted in blue colors. Examples of NEXN correlations in the human coronary artery (N = 133) are shown in panels B through ( D ). P-values and Spearman Rho values are given in the respective panels. Panels E and F show mRNA data for NEXN in cultured human bladder (HBSMCs, N = 8) and coronary artery (HCASMCs, N = 9) SMCs after treatment with Latrunculin B (LatB). Panels H and I show protein data for Nexilin/ NEXN in the presence and absence of LatB (HBSMCs, 300 nM, N = 12; HCASMCs, 100 nM, N = 10). The top micrographs in panel J shows confocal imaging of YAP (red) on the left, and YAP (green) and CAV1 (red) on the right. The bottom row shows YAP (red) and Nexilin (green). The high magnification overlay at the bottom right shows partial colocalization of YAP and Nexilin at the cell membrane in yellow. All micrographs are from cross-sectioned HBSMCs and white scale bars represent 5 μm throughout.

    Techniques Used: Expressing, Cell Culture, Imaging

    31) Product Images from "Induced PTF1a expression in pancreatic ductal adenocarcinoma cells activates acinar gene networks, reduces tumorigenic properties, and sensitizes cells to gemcitabine treatment"

    Article Title: Induced PTF1a expression in pancreatic ductal adenocarcinoma cells activates acinar gene networks, reduces tumorigenic properties, and sensitizes cells to gemcitabine treatment

    Journal: Molecular Oncology

    doi: 10.1002/1878-0261.12314

    PTF 1a expression decreases soft agar colony and orthotopic pancreatic cancer tumor growth. (A,B) Soft agar colony formation assay of Tet‐One and Tet‐ PTF 1a cells ± Dox. (C) Immunoblot analysis of CD 44 and EPCAM from soft agar colonies of Tet‐ PTF 1a cells ± Dox. CD 44 and EPCAM show marked reductions in the PTF 1a expressing colonies. (D) Orthotopic xenograft assays testing Panc‐1 Tet‐ PTF 1a tumor growth in mice subjected to ± Dox chow. * P ≤ 0.05.
    Figure Legend Snippet: PTF 1a expression decreases soft agar colony and orthotopic pancreatic cancer tumor growth. (A,B) Soft agar colony formation assay of Tet‐One and Tet‐ PTF 1a cells ± Dox. (C) Immunoblot analysis of CD 44 and EPCAM from soft agar colonies of Tet‐ PTF 1a cells ± Dox. CD 44 and EPCAM show marked reductions in the PTF 1a expressing colonies. (D) Orthotopic xenograft assays testing Panc‐1 Tet‐ PTF 1a tumor growth in mice subjected to ± Dox chow. * P ≤ 0.05.

    Techniques Used: Expressing, Soft Agar Assay, Mouse Assay

    RNA sequencing of Tet‐ MIST 1 and Tet‐ PTF 1a. (A) Experimental strategy and timeline for cells subjected to RNA ‐Seq. (B) Representative heatmaps of four control samples compared to four doxycycline‐treated samples for the Tet‐ MIST 1 and Tet‐ PTF 1a cells. Heatmaps depict the comparison of log2‐transformed read counts for each gene. (C) A total of 874 genes are differentially expressed in the Tet‐ MIST 1 cell line, while 6688 genes were differentially expressed in Tet‐ PTF 1a cells. (D) Venn diagrams comparing induced and repressed genes in Tet‐ MIST 1 vs. Tet‐ PTF 1a samples. (E) Summary heatmap displaying −Log ( FWER P ‐value) for biological and molecular pathways identified by GSEA.
    Figure Legend Snippet: RNA sequencing of Tet‐ MIST 1 and Tet‐ PTF 1a. (A) Experimental strategy and timeline for cells subjected to RNA ‐Seq. (B) Representative heatmaps of four control samples compared to four doxycycline‐treated samples for the Tet‐ MIST 1 and Tet‐ PTF 1a cells. Heatmaps depict the comparison of log2‐transformed read counts for each gene. (C) A total of 874 genes are differentially expressed in the Tet‐ MIST 1 cell line, while 6688 genes were differentially expressed in Tet‐ PTF 1a cells. (D) Venn diagrams comparing induced and repressed genes in Tet‐ MIST 1 vs. Tet‐ PTF 1a samples. (E) Summary heatmap displaying −Log ( FWER P ‐value) for biological and molecular pathways identified by GSEA.

    Techniques Used: RNA Sequencing Assay, Transformation Assay

    MIST 1 and PTF 1a activate known target genes in PDAC cells. (A) Phase contrast images of Panc‐1 Tet‐ MIST 1 and Tet‐ PTF 1a cells ± Dox (scale bar = 50 μ m ). (B) RT ‐ qPCR analysis of Panc‐1 Tet‐ MIST 1 and Tet‐ PTF 1a cells. Data are normalized to the same cell lines without doxycycline treatment and displayed as fold induction. MIST 1 vesicle trafficking target genes RAB 3D and RAB 26 and ER chaperones SEC 61b, SEC 62, SEC 63, PERK , and DNAJ c1 are induced upon MIST 1 expression. (C) Expression of acinar transcription factors NR 5a2, MIST 1, GATA 6, and PDX 1 is induced in PDAC cells upon PTF 1a induction. (D) Pancreas digestive enzymes PRSS 1, PRSS 2, CPA 1, CPA 2, CELA 3b, and AMY 2a transcripts accumulate upon PTF 1a expression. (E) Trypsinogen ( PRSS 2) staining of Panc‐1 Tet‐One, Tet‐ MIST 1, and Tet‐ PTF 1a cells 72 h post‐doxycycline treatment (scale bar = 50 μ m ). (F) Percentage of Tet‐ PTF 1a cells expressing PRSS 2 or carboxypeptidase ( CPA 1) upon doxycycline treatment. * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001.
    Figure Legend Snippet: MIST 1 and PTF 1a activate known target genes in PDAC cells. (A) Phase contrast images of Panc‐1 Tet‐ MIST 1 and Tet‐ PTF 1a cells ± Dox (scale bar = 50 μ m ). (B) RT ‐ qPCR analysis of Panc‐1 Tet‐ MIST 1 and Tet‐ PTF 1a cells. Data are normalized to the same cell lines without doxycycline treatment and displayed as fold induction. MIST 1 vesicle trafficking target genes RAB 3D and RAB 26 and ER chaperones SEC 61b, SEC 62, SEC 63, PERK , and DNAJ c1 are induced upon MIST 1 expression. (C) Expression of acinar transcription factors NR 5a2, MIST 1, GATA 6, and PDX 1 is induced in PDAC cells upon PTF 1a induction. (D) Pancreas digestive enzymes PRSS 1, PRSS 2, CPA 1, CPA 2, CELA 3b, and AMY 2a transcripts accumulate upon PTF 1a expression. (E) Trypsinogen ( PRSS 2) staining of Panc‐1 Tet‐One, Tet‐ MIST 1, and Tet‐ PTF 1a cells 72 h post‐doxycycline treatment (scale bar = 50 μ m ). (F) Percentage of Tet‐ PTF 1a cells expressing PRSS 2 or carboxypeptidase ( CPA 1) upon doxycycline treatment. * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001.

    Techniques Used: Quantitative RT-PCR, Size-exclusion Chromatography, Expressing, Staining

    PTF 1a sensitizes PDAC cells to gemcitabine in vivo . (A) Experimental timeline. (B) Immunoblot of PTF 1a expression from excised tumors in mice treated ± Dox and ± Gem. (C) RT ‐ qPCR of tumor samples from the indicated groups for the Tet‐induced PTF 1a transgene ( Tg PTF 1a ) as well as for endogenous NR 5a2 , PRSS 1 , and CPA 1 genes. (D) Hematoxylin and eosin (H E) staining, PRSS 2 immunofluorescence (green), and whole‐mount images of tumors isolated from mice treated ± Dox and ± Gem (scale bars = 50 μ m for sections; 2.5 mm for whole‐mount images). (E) Tumor weights obtained from Panc‐1 Tet‐ PTF 1a cells ± Dox and ± Gem ( n = 12–14 mice per experimental group). * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001, N.S., not significant.
    Figure Legend Snippet: PTF 1a sensitizes PDAC cells to gemcitabine in vivo . (A) Experimental timeline. (B) Immunoblot of PTF 1a expression from excised tumors in mice treated ± Dox and ± Gem. (C) RT ‐ qPCR of tumor samples from the indicated groups for the Tet‐induced PTF 1a transgene ( Tg PTF 1a ) as well as for endogenous NR 5a2 , PRSS 1 , and CPA 1 genes. (D) Hematoxylin and eosin (H E) staining, PRSS 2 immunofluorescence (green), and whole‐mount images of tumors isolated from mice treated ± Dox and ± Gem (scale bars = 50 μ m for sections; 2.5 mm for whole‐mount images). (E) Tumor weights obtained from Panc‐1 Tet‐ PTF 1a cells ± Dox and ± Gem ( n = 12–14 mice per experimental group). * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001, N.S., not significant.

    Techniques Used: In Vivo, Expressing, Mouse Assay, Quantitative RT-PCR, Staining, Immunofluorescence, Isolation

    PTF 1a sensitizes Panc‐1 cells to gemcitabine treatment. (A) RT ‐ qPCR of gemcitabine efflux transporters for Tet‐ PTF 1a cells ± Dox. (B) RT ‐ qPCR of gemcitabine influx transporters ENT 1 and CNT 1 . (C) IC 50 kill curve of Tet‐inducible cell lines using a gemcitabine gradient for 72 h. (D,E) Log 10 fold change of IC 50 when cells are treated with doxycycline to induce PTF 1a. (F) Immunoblot analysis of Tet‐inducible cells using 10 μ m gemcitabine for 72 h. Cleaved caspase‐3 is elevated upon PTF 1a induction, while Tet‐One cells display no change. * P ≤ 0.05, ** P ≤ 0.01. ND , not detected.
    Figure Legend Snippet: PTF 1a sensitizes Panc‐1 cells to gemcitabine treatment. (A) RT ‐ qPCR of gemcitabine efflux transporters for Tet‐ PTF 1a cells ± Dox. (B) RT ‐ qPCR of gemcitabine influx transporters ENT 1 and CNT 1 . (C) IC 50 kill curve of Tet‐inducible cell lines using a gemcitabine gradient for 72 h. (D,E) Log 10 fold change of IC 50 when cells are treated with doxycycline to induce PTF 1a. (F) Immunoblot analysis of Tet‐inducible cells using 10 μ m gemcitabine for 72 h. Cleaved caspase‐3 is elevated upon PTF 1a induction, while Tet‐One cells display no change. * P ≤ 0.05, ** P ≤ 0.01. ND , not detected.

    Techniques Used: Quantitative RT-PCR

    32) Product Images from "miR-214 promotes periodontal ligament stem cell osteoblastic differentiation by modulating Wnt/β-catenin signaling"

    Article Title: miR-214 promotes periodontal ligament stem cell osteoblastic differentiation by modulating Wnt/β-catenin signaling

    Journal: Molecular Medicine Reports

    doi: 10.3892/mmr.2017.7821

    miRNA expression in differentiated and non-differentiated PDLSCs. (A) Heat map of miRNA profiles represents the differentially expressed miRNAs between differentiated and non-differentiated PDLSCs. Green indicates low expression levels; red indicates high expression levels. (B) RT-qPCR was performed to determine the expression of miRNAs in differentiated and undifferentiated PDLSCs. (C) RT-qPCR was used to assess the expression levels of miR-214 at the indicated time points in differentiated and non-differentiated PDLSCs. miR-214 expression was normalized to U6 small nuclear RNA. **P
    Figure Legend Snippet: miRNA expression in differentiated and non-differentiated PDLSCs. (A) Heat map of miRNA profiles represents the differentially expressed miRNAs between differentiated and non-differentiated PDLSCs. Green indicates low expression levels; red indicates high expression levels. (B) RT-qPCR was performed to determine the expression of miRNAs in differentiated and undifferentiated PDLSCs. (C) RT-qPCR was used to assess the expression levels of miR-214 at the indicated time points in differentiated and non-differentiated PDLSCs. miR-214 expression was normalized to U6 small nuclear RNA. **P

    Techniques Used: Expressing, Quantitative RT-PCR

    33) Product Images from "RNA sequencing reveals upregulation of a transcriptomic program associated with stemness in metastatic prostate cancer cells selected for taxane resistance"

    Article Title: RNA sequencing reveals upregulation of a transcriptomic program associated with stemness in metastatic prostate cancer cells selected for taxane resistance

    Journal: Oncotarget

    doi: 10.18632/oncotarget.25744

    Tumorsphere formation capacity is higher in DTX-resistant DU145 cells compared to sensitive cells (A) Phase contrast microscopy images of DU145 and DU145-DR tumorspheres (3D) with (B) quantification of tumorsphere percentage using Image J software. (C) Tumorsphere morphology visualized using Hoffman modulation contrast microscopy (scale bar set at 40 μm). (D) Percent of live cells positive for the cell surface markers E-cadherin and N-cadherin, and CSC markers CD44+/CD24-, CD44+/CD24-, with (E) representative flow cytometry plots. (F) Representative flow cytometry plots showing increased ALDH activity (Aldefluor+) in DU145-DR tumorspheres as determined by aldefluor assay with bar graphs. All flow measurements were acquired from at least 3 independent experiments conducted separately. * P
    Figure Legend Snippet: Tumorsphere formation capacity is higher in DTX-resistant DU145 cells compared to sensitive cells (A) Phase contrast microscopy images of DU145 and DU145-DR tumorspheres (3D) with (B) quantification of tumorsphere percentage using Image J software. (C) Tumorsphere morphology visualized using Hoffman modulation contrast microscopy (scale bar set at 40 μm). (D) Percent of live cells positive for the cell surface markers E-cadherin and N-cadherin, and CSC markers CD44+/CD24-, CD44+/CD24-, with (E) representative flow cytometry plots. (F) Representative flow cytometry plots showing increased ALDH activity (Aldefluor+) in DU145-DR tumorspheres as determined by aldefluor assay with bar graphs. All flow measurements were acquired from at least 3 independent experiments conducted separately. * P

    Techniques Used: Microscopy, Software, Flow Cytometry, Cytometry, Activity Assay

    DTX-resistant mCRPC cells upregulate markers associated with CSC-like characteristics compared to DTX-sensitive cells (A) Percent of CD44+ and CD44+/CD24- cells for PC3 vs PC3-DR and DU145 vs DU145-DR, with (B) representative flow cytometry plots showing compensation windows used in the FMO analysis for each marker. Flow data is represented as frequency of live cells determined by annexin-V staining. (C) PC3-DR and (D) DU145-DR cells have significantly greater ALDH activity (Aldefluor+) compared with sensitive PC3 and DU145 cells as determined by aldefluor assay (+DEAB control used for gating). Representative flow plots are shown together with bar graphs. All flow measurements were acquired from at least 3 independent experiments conducted separately. ** P
    Figure Legend Snippet: DTX-resistant mCRPC cells upregulate markers associated with CSC-like characteristics compared to DTX-sensitive cells (A) Percent of CD44+ and CD44+/CD24- cells for PC3 vs PC3-DR and DU145 vs DU145-DR, with (B) representative flow cytometry plots showing compensation windows used in the FMO analysis for each marker. Flow data is represented as frequency of live cells determined by annexin-V staining. (C) PC3-DR and (D) DU145-DR cells have significantly greater ALDH activity (Aldefluor+) compared with sensitive PC3 and DU145 cells as determined by aldefluor assay (+DEAB control used for gating). Representative flow plots are shown together with bar graphs. All flow measurements were acquired from at least 3 independent experiments conducted separately. ** P

    Techniques Used: Flow Cytometry, Cytometry, Marker, Staining, Activity Assay

    DU145-DR derived tumorspheres show increased resistance to DTX compared to DU145-DR adherent cells (A) DU145-DR adherent and tumorsphere cells treated with increasing concentrations of DTX (nM range) and % PI positive cells were measured via flow cytometry. (B) DU145-DR 3D tumorspheres were more resistant to 10 nM DTX than the adherent DU145-DR 2D cells as measured by % PI positive cells. All samples were normalized to untreated controls and to DU145-DR 3D percent viability. All measurements were acquired from at least 3 independent experiments with 3 biological replicates each. * P
    Figure Legend Snippet: DU145-DR derived tumorspheres show increased resistance to DTX compared to DU145-DR adherent cells (A) DU145-DR adherent and tumorsphere cells treated with increasing concentrations of DTX (nM range) and % PI positive cells were measured via flow cytometry. (B) DU145-DR 3D tumorspheres were more resistant to 10 nM DTX than the adherent DU145-DR 2D cells as measured by % PI positive cells. All samples were normalized to untreated controls and to DU145-DR 3D percent viability. All measurements were acquired from at least 3 independent experiments with 3 biological replicates each. * P

    Techniques Used: Derivative Assay, Flow Cytometry, Cytometry

    Gene expression profiling analysis reveals upregulation of CSC-associated genes (A) Principal component Analysis (PCA) mapping demonstrates clustering of DTX-resistant cell lines based on gene expression profiles. (B) Diagram showing the distribution of statistically significant differentially regulated genes in each cell line, comparing DTX-resistant (DR) to sensitive (S). (C) Diagram demonstrating the overlap or shared genes common to both PC3 and DU145 cells, comparing DR to S. (D) Heatmap of the top ranked genes generated using GSEA analysis on the common overlap genes between both sensitive PC3 and DU145 cells compared to PC3-DR and DU145-DR. Red represents fold upregulation and blue represents fold downregulation. (E) GSEA gene set pathway analysis revealed one pathway to be significantly enriched in the DTX-resistant PC3-DR and DU145-DR cells compared to sensitive PC3 and DU145 cells ( P = 0.032) involving precursor metabolites and energy. A positive value indicates correlation with the sensitive phenotype and negative value indicates correlation with the resistant phenotype.
    Figure Legend Snippet: Gene expression profiling analysis reveals upregulation of CSC-associated genes (A) Principal component Analysis (PCA) mapping demonstrates clustering of DTX-resistant cell lines based on gene expression profiles. (B) Diagram showing the distribution of statistically significant differentially regulated genes in each cell line, comparing DTX-resistant (DR) to sensitive (S). (C) Diagram demonstrating the overlap or shared genes common to both PC3 and DU145 cells, comparing DR to S. (D) Heatmap of the top ranked genes generated using GSEA analysis on the common overlap genes between both sensitive PC3 and DU145 cells compared to PC3-DR and DU145-DR. Red represents fold upregulation and blue represents fold downregulation. (E) GSEA gene set pathway analysis revealed one pathway to be significantly enriched in the DTX-resistant PC3-DR and DU145-DR cells compared to sensitive PC3 and DU145 cells ( P = 0.032) involving precursor metabolites and energy. A positive value indicates correlation with the sensitive phenotype and negative value indicates correlation with the resistant phenotype.

    Techniques Used: Expressing, Generated

    In-house qPCR validation of the expression of selected top-ranked genes from RNA-seq results in DTX-sensitive and DTX–resistant mCRPC cells qPCR validation for selected genes in (A) PC3 vs. PC3-DR and (B) DU145 vs. DU145-DR cells. White bars represent parental PC3 or DU145 and colored bars represent PC3-DR or DU145-DR. * P
    Figure Legend Snippet: In-house qPCR validation of the expression of selected top-ranked genes from RNA-seq results in DTX-sensitive and DTX–resistant mCRPC cells qPCR validation for selected genes in (A) PC3 vs. PC3-DR and (B) DU145 vs. DU145-DR cells. White bars represent parental PC3 or DU145 and colored bars represent PC3-DR or DU145-DR. * P

    Techniques Used: Real-time Polymerase Chain Reaction, Expressing, RNA Sequencing Assay

    Protein expression validation of RNA-seq results in DTX-sensitive and DTX-resistant mCRPC cells Representative Western blot images and protein fold change quantification are shown for (A) DPP4 (n= 3), (B) TSPAN8 (n= 4), (C) NES (n= 6), (D) DNAJC12 (n= 4), (E) FABP5 (n= 7), (F) BOP1 (n=4), and (G) TGM2 (n=4). * P
    Figure Legend Snippet: Protein expression validation of RNA-seq results in DTX-sensitive and DTX-resistant mCRPC cells Representative Western blot images and protein fold change quantification are shown for (A) DPP4 (n= 3), (B) TSPAN8 (n= 4), (C) NES (n= 6), (D) DNAJC12 (n= 4), (E) FABP5 (n= 7), (F) BOP1 (n=4), and (G) TGM2 (n=4). * P

    Techniques Used: Expressing, RNA Sequencing Assay, Western Blot

    DTX-resistant mCRPC cells exhibit a mesenchymal-like phenotype compared to DTX-sensitive cells (A) Differences in morphology between DTX-sensitive and DTX-resistant PC3 and DU145 cells visualized by Hoffman modulation contrast microscopy (scale bar set at 40 μm). (B) Percent of live PC3 and DU145 cells (DTX sensitive and -resistant) that stained positive for E-cadherin and N-cadherin as determined by flow cytometry (n=3 biological replicates) * P
    Figure Legend Snippet: DTX-resistant mCRPC cells exhibit a mesenchymal-like phenotype compared to DTX-sensitive cells (A) Differences in morphology between DTX-sensitive and DTX-resistant PC3 and DU145 cells visualized by Hoffman modulation contrast microscopy (scale bar set at 40 μm). (B) Percent of live PC3 and DU145 cells (DTX sensitive and -resistant) that stained positive for E-cadherin and N-cadherin as determined by flow cytometry (n=3 biological replicates) * P

    Techniques Used: Microscopy, Staining, Flow Cytometry, Cytometry

    DTX-resistant PC3 and DU145 cell lines upregulate known markers of DTX resistance Upper panel: Western blots of (A) LEDGF/p75, (B) CLU, and (C) ABCB1 showing upregulation of these proteins in DTX-resistant PC3 and DU145 mCRPC cells, compared to the parental, sensitive cells. Bottom panel: quantification of fold change in protein expression (A) n=8; (B) n=5; (C) n=4 independent experiments. * P
    Figure Legend Snippet: DTX-resistant PC3 and DU145 cell lines upregulate known markers of DTX resistance Upper panel: Western blots of (A) LEDGF/p75, (B) CLU, and (C) ABCB1 showing upregulation of these proteins in DTX-resistant PC3 and DU145 mCRPC cells, compared to the parental, sensitive cells. Bottom panel: quantification of fold change in protein expression (A) n=8; (B) n=5; (C) n=4 independent experiments. * P

    Techniques Used: Western Blot, Expressing

    34) Product Images from "CD63, MHC class 1, and CD47 identify subsets of extracellular vesicles containing distinct populations of noncoding RNAs"

    Article Title: CD63, MHC class 1, and CD47 identify subsets of extracellular vesicles containing distinct populations of noncoding RNAs

    Journal: Scientific Reports

    doi: 10.1038/s41598-018-20936-7

    RNAs enriched in CD47 + EVs. Analysis of specific classes of RNAs in the 272 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in CD47 + EVs versus CD47 − EVs from the scatter graph in Fig. 3a . A table was generated for each type of enriched RNA in CD47 + EV samples. (a) log 2 total RPM values are plotted for the indicated snoRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (c) Log 2 RPM values are plotted for the indicated lncRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (d) Log 2 total RPM values are plotted for the indicated mitochondrial and other RNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. Blue stars indicate RNAs that are also enriched in CD63 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.
    Figure Legend Snippet: RNAs enriched in CD47 + EVs. Analysis of specific classes of RNAs in the 272 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in CD47 + EVs versus CD47 − EVs from the scatter graph in Fig. 3a . A table was generated for each type of enriched RNA in CD47 + EV samples. (a) log 2 total RPM values are plotted for the indicated snoRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (c) Log 2 RPM values are plotted for the indicated lncRNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (d) Log 2 total RPM values are plotted for the indicated mitochondrial and other RNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from CD47 + EVs (blue bars) and uncaptured CD47 − EVs. Blue stars indicate RNAs that are also enriched in CD63 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.

    Techniques Used: Generated

    Noncoding RNA content of CD47 + , CD63 + and MHC1 + captured EVs versus the respective uncaptured EVs. ( a–c ) Individual classes of noncoding RNAs were extracted from linear total RPKM Gene Table by name and a table was generated for each type of RNA. The cutoff threshold 0.02 log2 total RPKM was used to filter RNAs isolated from CD47 + , CD63 + and MHC1 + EVs, and the numbers of mapped genes in each class are shown in pie charts. (d–f) Similarly, the number and type of non-coding RNAs identified in CD47 − , CD63 − and MHC1 − EVs and are shown as pie charts. Abbreviations: PIWI RNA, piwi-interacting RNA; Y-RNA, small non-coding RNA components of the Ro ribonucleoprotein particle; MT-RNA, mitochondrial RNA; SRP RNA, signal recognition particle RNA; Vault RNA RNA family of the vault ribonucleoprotein complex; SCA RNA, small Cajal body-specific RNA; SnRNA, small nuclear RNA; lncRNA, long non-coding RNA; SnoRNA, small nucleolar RNAs; RPRNA, ribosomal protein RNA; tRNA, transfer RNA; LOCRNA, nonannotated gene transcripts.
    Figure Legend Snippet: Noncoding RNA content of CD47 + , CD63 + and MHC1 + captured EVs versus the respective uncaptured EVs. ( a–c ) Individual classes of noncoding RNAs were extracted from linear total RPKM Gene Table by name and a table was generated for each type of RNA. The cutoff threshold 0.02 log2 total RPKM was used to filter RNAs isolated from CD47 + , CD63 + and MHC1 + EVs, and the numbers of mapped genes in each class are shown in pie charts. (d–f) Similarly, the number and type of non-coding RNAs identified in CD47 − , CD63 − and MHC1 − EVs and are shown as pie charts. Abbreviations: PIWI RNA, piwi-interacting RNA; Y-RNA, small non-coding RNA components of the Ro ribonucleoprotein particle; MT-RNA, mitochondrial RNA; SRP RNA, signal recognition particle RNA; Vault RNA RNA family of the vault ribonucleoprotein complex; SCA RNA, small Cajal body-specific RNA; SnRNA, small nuclear RNA; lncRNA, long non-coding RNA; SnoRNA, small nucleolar RNAs; RPRNA, ribosomal protein RNA; tRNA, transfer RNA; LOCRNA, nonannotated gene transcripts.

    Techniques Used: Generated, Isolation

    Validation of small RNA enrichment in CD47 + , CD63 + and MHC1 + captured EVs. ( a,b ) Validation of tRNAs using rtStar™ Pre-designed Human tRNA primer sets for TRE-CTC, TRR-CCG and internal spike control using total RNA from captured and uncaptured CD63 and MHC1 EVs. ( c ) The table presents RPM of SnoRNAs in CD47 + , CD63 + , and MHC1 + EVs. ( d ) Expression of SNHG5, SNHG10 and SNORDA116@ snoRNAs using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via TaqMan real-time PCR. (e) U6 using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via real-time PCR. ( f ) snRNA expression of RNU6ATAC using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via TaqMan assay. ( g,h ) miRNA expression of mir-320a and mir-320b using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs determined using real-time PCR.
    Figure Legend Snippet: Validation of small RNA enrichment in CD47 + , CD63 + and MHC1 + captured EVs. ( a,b ) Validation of tRNAs using rtStar™ Pre-designed Human tRNA primer sets for TRE-CTC, TRR-CCG and internal spike control using total RNA from captured and uncaptured CD63 and MHC1 EVs. ( c ) The table presents RPM of SnoRNAs in CD47 + , CD63 + , and MHC1 + EVs. ( d ) Expression of SNHG5, SNHG10 and SNORDA116@ snoRNAs using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via TaqMan real-time PCR. (e) U6 using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via real-time PCR. ( f ) snRNA expression of RNU6ATAC using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs via TaqMan assay. ( g,h ) miRNA expression of mir-320a and mir-320b using total RNA from captured and uncaptured CD47, CD63 and MHC1 EVs determined using real-time PCR.

    Techniques Used: Expressing, Real-time Polymerase Chain Reaction, TaqMan Assay

    Micro-RNA enrichment in captured EVs determined by microarray analysis. (a) Preparation of CD47 + and CD63 + EVs for miRNA microarray analysis. (b) Hierarchical clustering of human miRNAs identifies differential expression between CD47 +b and CD47 −b EVs (Student-t test). (c) Heat map of hierarchical clustering Human miRNA differentially expressed between CD63 +b /CD63 −b EVs. (d) The table presents enriched hsa-miRNAs in CD47 + EVs. (e) The table presents enriched hsa-miRNAs in CD63 + EVs.
    Figure Legend Snippet: Micro-RNA enrichment in captured EVs determined by microarray analysis. (a) Preparation of CD47 + and CD63 + EVs for miRNA microarray analysis. (b) Hierarchical clustering of human miRNAs identifies differential expression between CD47 +b and CD47 −b EVs (Student-t test). (c) Heat map of hierarchical clustering Human miRNA differentially expressed between CD63 +b /CD63 −b EVs. (d) The table presents enriched hsa-miRNAs in CD47 + EVs. (e) The table presents enriched hsa-miRNAs in CD63 + EVs.

    Techniques Used: Microarray, Expressing

    Micro-RNA enrichment in captured EVs determined by RNAseq. (a) Heat map of hierarchical clustering of 109 miRNAs (All species) differentially enriched in CD47 + versus CD47 − EVs at p
    Figure Legend Snippet: Micro-RNA enrichment in captured EVs determined by RNAseq. (a) Heat map of hierarchical clustering of 109 miRNAs (All species) differentially enriched in CD47 + versus CD47 − EVs at p

    Techniques Used:

    Differential enrichment of miRNAs in CD47 + , CD63 + and MHC1 + EVs. (a) Hierarchical clustering of 208 miRNAs (p
    Figure Legend Snippet: Differential enrichment of miRNAs in CD47 + , CD63 + and MHC1 + EVs. (a) Hierarchical clustering of 208 miRNAs (p

    Techniques Used:

    Enrichment of small RNAs in antibody captured EVs. (a) Scatter graph of data from 3 biological replicates comparing RNA abundance in CD47 + and CD47 − EVs. A total of 680 transcripts were significantly enriched or depleted in captured EVs (CD47_CAP) versus uncaptured EVs (CD47_UnCap, p
    Figure Legend Snippet: Enrichment of small RNAs in antibody captured EVs. (a) Scatter graph of data from 3 biological replicates comparing RNA abundance in CD47 + and CD47 − EVs. A total of 680 transcripts were significantly enriched or depleted in captured EVs (CD47_CAP) versus uncaptured EVs (CD47_UnCap, p

    Techniques Used:

    RNAs enriched in CD63 + EVs. Analysis of specific classes of RNAs in the 271 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in CD63 + EVs versus CD63 - EVs were extracted from the scatter graph in Fig. 3b . A table was generated for each type of upregulated RNAs of captured CD63 + EVs. (a) Log 2 total RPM values are plotted for the indicated snoRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (c) Log 2 total RPM values are plotted for the indicated lncRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (d) Log 2 total RPM values are plotted for the indicated small nuclear RNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. Blue stars indicate RNAs that are also enriched in CD47 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.
    Figure Legend Snippet: RNAs enriched in CD63 + EVs. Analysis of specific classes of RNAs in the 271 differentially expressed non-coding RNAs that were enriched ≥ 2-fold in CD63 + EVs versus CD63 - EVs were extracted from the scatter graph in Fig. 3b . A table was generated for each type of upregulated RNAs of captured CD63 + EVs. (a) Log 2 total RPM values are plotted for the indicated snoRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (b) Log 2 total RPM values are plotted for the indicated tRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (c) Log 2 total RPM values are plotted for the indicated lncRNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (d) Log 2 total RPM values are plotted for the indicated small nuclear RNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. (e) Log 2 total RPM values are plotted for the indicated ribosomal protein RNAs from CD63 + EVs (blue bars) and uncaptured CD63 - EVs. Blue stars indicate RNAs that are also enriched in CD47 + or MHC1 + EVs. Red stars indicate RNAs enriched in all three types of captured EVs.

    Techniques Used: Generated

    Characterization of Jurkat T cell EV fractions and CD47 expression. (a,b) EVs were extracted from wild type ( a ) and CD47-deficient Jurkat T cells ( b ) using the Exo-Quick kit, and vesicle size and concentration were quantified by Nanosight analysis. ( c) EVs released by Jurkat cells were labeled using Bodipy-FL and captured with anti-CD63-MNPs (upper panel) or with anti-MHC I-MNPs (lower panel) and stained with PE-conjugated anti-CD47 or isotype control antibodies. Representative experiment out of 3. ( d) EVs released by CD47-deficient JinB8 cells were captured with anti-CD63-MNPs (upper panel) or with anti-MHC I-MNPs (lower panel) and stained with anti-CD47 or with isotype control antibodies. Representative experiment of out of 3. ( e ) Size distribution of CD47 + EVs captured with anti-CD63-MNPs (red bars) or with anti-MHC1-MNPs (black bars). Representative experiment out of 3. (f) EVs released by Jurkat cells were captured with anti-CD47-MNPs and stained for CD63 antigen. Volumetric control was used to estimate concentration of CD47 + CD63 + EVs. One representative experiment is presented out of 2 performed.
    Figure Legend Snippet: Characterization of Jurkat T cell EV fractions and CD47 expression. (a,b) EVs were extracted from wild type ( a ) and CD47-deficient Jurkat T cells ( b ) using the Exo-Quick kit, and vesicle size and concentration were quantified by Nanosight analysis. ( c) EVs released by Jurkat cells were labeled using Bodipy-FL and captured with anti-CD63-MNPs (upper panel) or with anti-MHC I-MNPs (lower panel) and stained with PE-conjugated anti-CD47 or isotype control antibodies. Representative experiment out of 3. ( d) EVs released by CD47-deficient JinB8 cells were captured with anti-CD63-MNPs (upper panel) or with anti-MHC I-MNPs (lower panel) and stained with anti-CD47 or with isotype control antibodies. Representative experiment of out of 3. ( e ) Size distribution of CD47 + EVs captured with anti-CD63-MNPs (red bars) or with anti-MHC1-MNPs (black bars). Representative experiment out of 3. (f) EVs released by Jurkat cells were captured with anti-CD47-MNPs and stained for CD63 antigen. Volumetric control was used to estimate concentration of CD47 + CD63 + EVs. One representative experiment is presented out of 2 performed.

    Techniques Used: Expressing, Concentration Assay, Labeling, Staining

    35) Product Images from "A Fine-Tune Role of Mir-125a-5p on Foxn1 During Age-Associated Changes in the Thymus"

    Article Title: A Fine-Tune Role of Mir-125a-5p on Foxn1 During Age-Associated Changes in the Thymus

    Journal: Aging and Disease

    doi: 10.14336/AD.2016.1109

    Microarray results of miRNAs expression from enriched TECs of young and old mice (A) A dot plot shows the positions of signals detectable miRNAs in TECs of both young and aged groups. Among these miRNAs there are 341 miRNAs (Red dots represent these miRNAs) with signal intensity over 500. (B) Heatmap shows 12 miRNAs which have signaling strength ≥ 500, decreased (≤ 2 folds) or increased (≥ 2 folds) in aged TECs compared to young TECs. (C) Detailed information about these 12 miRNAs.
    Figure Legend Snippet: Microarray results of miRNAs expression from enriched TECs of young and old mice (A) A dot plot shows the positions of signals detectable miRNAs in TECs of both young and aged groups. Among these miRNAs there are 341 miRNAs (Red dots represent these miRNAs) with signal intensity over 500. (B) Heatmap shows 12 miRNAs which have signaling strength ≥ 500, decreased (≤ 2 folds) or increased (≥ 2 folds) in aged TECs compared to young TECs. (C) Detailed information about these 12 miRNAs.

    Techniques Used: Microarray, Expressing, Mouse Assay

    Validating 12 microRNA expression with Real-time RT-PCR The microRNA expression levels of miR-18a-5p, miR-466f, miR342-3p, miR-6931-5p, miR-125a-5p and miR-320-5p were consistent with the miRNA microarray results. The microRNA expression levels of miR-18a-5p and miR-466f were down-regulated in the aged thymus, while the microRNA expression levels of miR342-3p, miR-6931-5p, miR-125a-5p and miR-320-5p were up-regulated in the aged thymus. Data are presented as mean ± SEM (n = 9, i.e. Animal numbers in each group are 9 in three independent experiments). * p
    Figure Legend Snippet: Validating 12 microRNA expression with Real-time RT-PCR The microRNA expression levels of miR-18a-5p, miR-466f, miR342-3p, miR-6931-5p, miR-125a-5p and miR-320-5p were consistent with the miRNA microarray results. The microRNA expression levels of miR-18a-5p and miR-466f were down-regulated in the aged thymus, while the microRNA expression levels of miR342-3p, miR-6931-5p, miR-125a-5p and miR-320-5p were up-regulated in the aged thymus. Data are presented as mean ± SEM (n = 9, i.e. Animal numbers in each group are 9 in three independent experiments). * p

    Techniques Used: Expressing, Quantitative RT-PCR, Microarray

    36) Product Images from "Co-Inflammatory Roles of TGFβ1 in the Presence of TNFα Drive a Pro-inflammatory Fate in Mesenchymal Stem Cells"

    Article Title: Co-Inflammatory Roles of TGFβ1 in the Presence of TNFα Drive a Pro-inflammatory Fate in Mesenchymal Stem Cells

    Journal: Frontiers in Immunology

    doi: 10.3389/fimmu.2017.00479

    Factors released by TNFα + TGFβ1-stimulated MSCs induce cellular elongation and formation of cellular protrusions in human breast cancer cells . Human BM-derived MSCs were stimulated with vehicle (“Control-MSCs”) or TNFα (50 ng/ml) + TGFβ1 (10 ng/ml), in 0.5% FBS-containing medium; Tα + Tβ = TNFα + TGFβ1. In parallel, samples of “Control medium” (not exposed to MSCs), with or without the stimulating cytokines, were kept in identical conditions. Twenty-four hours later, all different media were filtered (0.45 µm pores) and applied to mCherry-expressing MDA-MB-231 cells for 48–72 h, in different experiments (A) or to mCherry-expressing MCF-7 cells for 48 h (B) . Cancer cells were then washed and photographed. CM = conditioned media. Scale bar: 200 µm in MDA-MB-231 cells and 50 µm in MCF-7 cells. The pictures are representatives of n ≥ 3 independent experiments, performed with MSCs of two to three different donors, which have shown similar results. For MDA-MB-231 cells, enlarged pictures of cells, obtained in MSCs from another experiment, are demonstrated in Figure S8 in Supplementary Material.
    Figure Legend Snippet: Factors released by TNFα + TGFβ1-stimulated MSCs induce cellular elongation and formation of cellular protrusions in human breast cancer cells . Human BM-derived MSCs were stimulated with vehicle (“Control-MSCs”) or TNFα (50 ng/ml) + TGFβ1 (10 ng/ml), in 0.5% FBS-containing medium; Tα + Tβ = TNFα + TGFβ1. In parallel, samples of “Control medium” (not exposed to MSCs), with or without the stimulating cytokines, were kept in identical conditions. Twenty-four hours later, all different media were filtered (0.45 µm pores) and applied to mCherry-expressing MDA-MB-231 cells for 48–72 h, in different experiments (A) or to mCherry-expressing MCF-7 cells for 48 h (B) . Cancer cells were then washed and photographed. CM = conditioned media. Scale bar: 200 µm in MDA-MB-231 cells and 50 µm in MCF-7 cells. The pictures are representatives of n ≥ 3 independent experiments, performed with MSCs of two to three different donors, which have shown similar results. For MDA-MB-231 cells, enlarged pictures of cells, obtained in MSCs from another experiment, are demonstrated in Figure S8 in Supplementary Material.

    Techniques Used: Derivative Assay, Expressing, Multiple Displacement Amplification

    Factors released by TNFα + TGFβ1-stimulated MSCs induce elevated migration and scattering of MCF-7 breast cancer cells . Human BM-derived MSCs were stimulated with vehicle (“Control-MSCs”) or TNFα (50 ng/ml) + TGFβ1 (10 ng/ml) [0.5% FBS-containing medium in panel (A) and FBS-free medium in panel (B) ]; Tα + Tβ = TNFα + TGFβ1. In parallel, samples of “Control medium” (not exposed to MSCs), with or without the stimulating cytokines, were kept in identical conditions. Twenty-four hours later, all different media were filtered (0.45 µm pores) and applied to mCherry-expressing MCF-7 cells for 48 h (A) or 96 h (B) . Then, functional assays were performed. CM = conditioned media. (A) Migration of MCF-7 cells toward 10% FBS-containing medium. (A1) Representative pictures of part of the high-resolution fields, ×40 magnification, of one of three independent experiments performed with MSCs of two different donors. (A2) Bar graph demonstrating the average number of cells migrating in each cell group, obtained in three independent experiments (total of five pictures/insert in each experiment); colored dots represent the number of migrating cells in each of these same three experiments, with corresponding color-coded p -values indicated. (B) Scattering of MCF-7 cells out of tumor spheroids. Scale bar = 200 µm. The pictures are representatives of n > 3 independent experiments, performed with MSCs of three different donors that have shown similar results.
    Figure Legend Snippet: Factors released by TNFα + TGFβ1-stimulated MSCs induce elevated migration and scattering of MCF-7 breast cancer cells . Human BM-derived MSCs were stimulated with vehicle (“Control-MSCs”) or TNFα (50 ng/ml) + TGFβ1 (10 ng/ml) [0.5% FBS-containing medium in panel (A) and FBS-free medium in panel (B) ]; Tα + Tβ = TNFα + TGFβ1. In parallel, samples of “Control medium” (not exposed to MSCs), with or without the stimulating cytokines, were kept in identical conditions. Twenty-four hours later, all different media were filtered (0.45 µm pores) and applied to mCherry-expressing MCF-7 cells for 48 h (A) or 96 h (B) . Then, functional assays were performed. CM = conditioned media. (A) Migration of MCF-7 cells toward 10% FBS-containing medium. (A1) Representative pictures of part of the high-resolution fields, ×40 magnification, of one of three independent experiments performed with MSCs of two different donors. (A2) Bar graph demonstrating the average number of cells migrating in each cell group, obtained in three independent experiments (total of five pictures/insert in each experiment); colored dots represent the number of migrating cells in each of these same three experiments, with corresponding color-coded p -values indicated. (B) Scattering of MCF-7 cells out of tumor spheroids. Scale bar = 200 µm. The pictures are representatives of n > 3 independent experiments, performed with MSCs of three different donors that have shown similar results.

    Techniques Used: Migration, Derivative Assay, Expressing, Functional Assay

    TNFα and TGFβ1 modify private and shared transcriptional programs in MSCs . Human BM-derived MSCs of Donor #1 were stimulated by TNFα (50 ng/ml) or TGFβ1 (10 ng/ml) or treated by a vehicle control, as illustrated in the experimental design of Figure S1A in Supplementary Material (cytokine concentrations were selected as described in Section “ Materials and Methods ”; experiment performed in FBS-free medium). RNA was subjected to Illumina Beadchip array analyses, and the complete dataset was deposited at ArrayExpress [( 51 , 52 ); accession numbers E-MTAB-5421 and E-MTAB-5420]. (A) The figure presents the transcriptional programs modified in MSCs at different time points following their stimulation by TNFα or TGFβ1. Data are presented by p -value scaling ( p ≤ 0.001 after Benjamini–Yekutieli correction for multiple testing). All the transcriptional programs that are demonstrated include ≥10 genes. (B) Venn diagram showing the number of transcriptional programs significantly affected only by TNFα, only by TGFβ1, or by both cytokines.
    Figure Legend Snippet: TNFα and TGFβ1 modify private and shared transcriptional programs in MSCs . Human BM-derived MSCs of Donor #1 were stimulated by TNFα (50 ng/ml) or TGFβ1 (10 ng/ml) or treated by a vehicle control, as illustrated in the experimental design of Figure S1A in Supplementary Material (cytokine concentrations were selected as described in Section “ Materials and Methods ”; experiment performed in FBS-free medium). RNA was subjected to Illumina Beadchip array analyses, and the complete dataset was deposited at ArrayExpress [( 51 , 52 ); accession numbers E-MTAB-5421 and E-MTAB-5420]. (A) The figure presents the transcriptional programs modified in MSCs at different time points following their stimulation by TNFα or TGFβ1. Data are presented by p -value scaling ( p ≤ 0.001 after Benjamini–Yekutieli correction for multiple testing). All the transcriptional programs that are demonstrated include ≥10 genes. (B) Venn diagram showing the number of transcriptional programs significantly affected only by TNFα, only by TGFβ1, or by both cytokines.

    Techniques Used: Derivative Assay, Modification

    37) Product Images from "MicroRNA-1 down-regulates proliferation and migration of breast cancer stem cells by inhibiting the Wnt/β-catenin pathway"

    Article Title: MicroRNA-1 down-regulates proliferation and migration of breast cancer stem cells by inhibiting the Wnt/β-catenin pathway

    Journal: Oncotarget

    doi:

    Altered miR-1 expression changes the percentages of breast CSC in breast cancer cell lines MCF-7 and SKBR3 cells were transfected with, or without, miR-1 NC, miR-1 inhibitor, or miR-1 mimic for 24 or 48 h. The relative levels of miR-1 expression in different groups of cells were determined by quantitative RT-PCR A. The frequency of CD44+CD24− CSCs was determined by flow cytometry B–C. Data are representative FACS charts and expressed as the mean ± SD of each group of cells from three separate experiments. * p
    Figure Legend Snippet: Altered miR-1 expression changes the percentages of breast CSC in breast cancer cell lines MCF-7 and SKBR3 cells were transfected with, or without, miR-1 NC, miR-1 inhibitor, or miR-1 mimic for 24 or 48 h. The relative levels of miR-1 expression in different groups of cells were determined by quantitative RT-PCR A. The frequency of CD44+CD24− CSCs was determined by flow cytometry B–C. Data are representative FACS charts and expressed as the mean ± SD of each group of cells from three separate experiments. * p

    Techniques Used: Expressing, Transfection, Quantitative RT-PCR, Flow Cytometry, Cytometry, FACS

    miR-1 inhibits the growth of implanted breast tumors in vivo The relative levels of miR-1 expression in the MCF-7/miR-1mimic, MCF-7/miR-1inhibitor or control MCF-7/miR-1NC CSCs were determined by quantitative RT-PCR A. The development and growth of implanted CSC-related tumors were monitored at the indicated time points post inoculation B. At the end of this experiment (on day 26 post inoculation), the relative levels of miR-1 expression in the different groups of dissected tumors were determined C. Data are expressed as the mean ± SD of each group of mice ( n = 8 per group). * p
    Figure Legend Snippet: miR-1 inhibits the growth of implanted breast tumors in vivo The relative levels of miR-1 expression in the MCF-7/miR-1mimic, MCF-7/miR-1inhibitor or control MCF-7/miR-1NC CSCs were determined by quantitative RT-PCR A. The development and growth of implanted CSC-related tumors were monitored at the indicated time points post inoculation B. At the end of this experiment (on day 26 post inoculation), the relative levels of miR-1 expression in the different groups of dissected tumors were determined C. Data are expressed as the mean ± SD of each group of mice ( n = 8 per group). * p

    Techniques Used: In Vivo, Expressing, Quantitative RT-PCR, Mouse Assay

    The expression of miRNAs in breast cancer A. The miRNA expression profile in six paired of breast CSC and non-CSC samples was characterized by miRNA microarray. The relative levels of miR-1 expression in different types of breast cancer tissue B. and serum samples C. were determined by quantitative RT-PCR. D. The relative levels of serum miRNA in patients ( n = 18) with or without lymph node metastasis ( n = 27). E. The levels of miR-1 expression in different types of breast cancer cell lines. Data are representative profile of clustered miRNA in individual samples and expressed as the mean ± SD of each group of samples from at least three separate experiments. N = 20 for luminal A; 10 for luminal B; 5 for Her2+; 10 for basal-like. * p
    Figure Legend Snippet: The expression of miRNAs in breast cancer A. The miRNA expression profile in six paired of breast CSC and non-CSC samples was characterized by miRNA microarray. The relative levels of miR-1 expression in different types of breast cancer tissue B. and serum samples C. were determined by quantitative RT-PCR. D. The relative levels of serum miRNA in patients ( n = 18) with or without lymph node metastasis ( n = 27). E. The levels of miR-1 expression in different types of breast cancer cell lines. Data are representative profile of clustered miRNA in individual samples and expressed as the mean ± SD of each group of samples from at least three separate experiments. N = 20 for luminal A; 10 for luminal B; 5 for Her2+; 10 for basal-like. * p

    Techniques Used: Expressing, Microarray, Quantitative RT-PCR

    38) Product Images from "MicroRNAs Circulate in the Hemolymph of Drosophila and Accumulate Relative to Tissue microRNAs in an Age-Dependent Manner"

    Article Title: MicroRNAs Circulate in the Hemolymph of Drosophila and Accumulate Relative to Tissue microRNAs in an Age-Dependent Manner

    Journal: Genomics Insights

    doi: 10.4137/GEI.S38147

    Presence of stable miRNAs in Drosophila melanogaster hemolymph. ( A , B ) Clear HL droplets extruded from fly head and thorax. ( C – F ) Real-time qPCR amplification of selected HL miRNAs and mRNAs. Total RNA including small RNA was extracted from HL samples and analyzed with qPCR to measure the levels of miRNAs and mRNAs. The y -axis represents the relative fluorescence units (RFU) in a semi-log scale. The x -axis represents the cycle at which fluorescence was detected above an automatically determined threshold. ( C ) Amplification plots for miR-14, miR-8, and miR-184 measured in a representative HL sample. ( D ) Amplification plots for miR-14, let-7, bantam, and spiked-in synthetic C. elegans cel-miR-39 RNA in representative HL sample. ( E ) The amplification plots for tubulin, actin, and gapdh mRNAs determined by qPCR using total RNA from HL and S2 cells. Sample from S2 cells are used as a positive control for detecting Drosophila mRNAs by qPCR. The amplification curves of all three mRNAs are superimposed on one another, reflecting the presence of similar amounts of these mRNA in S2 cells. Amplification curves from HL samples show that fluorescent products appear after about 30 cycles, reflecting the significantly lower abundance of these mRNAs in HL relative to S2 cells. ( F ) The cycle threshold (Ct) fold-change of selected miRNA amplified in the absence or presence of RNase A and DNase I. Total RNA was extracted from HL samples spiked with 10 fmoles of cel-miR-39 RNA. The x -axis represents the ratio of raw Ct values from control samples divided by raw Ct values from samples incubated with RNase A and DNase I. The significantly higher magnitude of the Ct fold change of the spiked-in synthetic miRNA relative to those of the miRNA indicates that the HL-miRNA are present in nuclease-resistant, stable form.
    Figure Legend Snippet: Presence of stable miRNAs in Drosophila melanogaster hemolymph. ( A , B ) Clear HL droplets extruded from fly head and thorax. ( C – F ) Real-time qPCR amplification of selected HL miRNAs and mRNAs. Total RNA including small RNA was extracted from HL samples and analyzed with qPCR to measure the levels of miRNAs and mRNAs. The y -axis represents the relative fluorescence units (RFU) in a semi-log scale. The x -axis represents the cycle at which fluorescence was detected above an automatically determined threshold. ( C ) Amplification plots for miR-14, miR-8, and miR-184 measured in a representative HL sample. ( D ) Amplification plots for miR-14, let-7, bantam, and spiked-in synthetic C. elegans cel-miR-39 RNA in representative HL sample. ( E ) The amplification plots for tubulin, actin, and gapdh mRNAs determined by qPCR using total RNA from HL and S2 cells. Sample from S2 cells are used as a positive control for detecting Drosophila mRNAs by qPCR. The amplification curves of all three mRNAs are superimposed on one another, reflecting the presence of similar amounts of these mRNA in S2 cells. Amplification curves from HL samples show that fluorescent products appear after about 30 cycles, reflecting the significantly lower abundance of these mRNAs in HL relative to S2 cells. ( F ) The cycle threshold (Ct) fold-change of selected miRNA amplified in the absence or presence of RNase A and DNase I. Total RNA was extracted from HL samples spiked with 10 fmoles of cel-miR-39 RNA. The x -axis represents the ratio of raw Ct values from control samples divided by raw Ct values from samples incubated with RNase A and DNase I. The significantly higher magnitude of the Ct fold change of the spiked-in synthetic miRNA relative to those of the miRNA indicates that the HL-miRNA are present in nuclease-resistant, stable form.

    Techniques Used: Real-time Polymerase Chain Reaction, Amplification, Fluorescence, Positive Control, Incubation

    Outline of the experimental design and workflow for the integrated analysis of the miRNA-Seq and mRNA-Seq data. Genes that are potentially regulated by the HL-miRNAs were determined by integrating miRNA-Seq and mRNA-Seq data using the following three steps: Step 1 (depicted in green): After identifying the HL-miRNAs enriched relative to BT in either young or old, or both young and old ( Tables 1 and 2 ), we retrieved their computationally predicted target genes from the m 3 RNA database ( http://m3rna.cnb.csic.es ). Step 2 (depicted in blue): mRNA-Seq was utilized to identify three groups of genes that were differentially expressed with age, either upregulated, downregulated, or unchanged in BT. Step 3 (depicted in red): The three groups of genes predicted in step1 as targets of HL-miRNAs were intersected with the three groups of genes identified in step 2. In the figure, ( A ) depicts the derivation of genes that are predicted to be targets of HL-miRNAs enriched in young which are also upregulated with age in BT. These genes (Supplementary Table 1 ) are likely upregulated in BT of old flies because their expression is no longer repressed by HL-miRNAs that are enriched only in young flies. ( B ) Depicts the derivation of genes which are the predicted to be targets of HL-miRNAs enriched in old which are also downregulated with age in BT. These genes (Supplementary Table 2 ) are likely downregulated in BT of old flies because their expression is repressed by HL-miRNAs which are enriched only in old flies. ( C ) Depicts the derivation of genes which are predicted to be targets of HL-miRNAs enriched in both young and old which also do not change expression with age in BT. These genes (Supplementary Table 3) do not change expression with age because the concentration of their regulatory miRNAs in HL does not change with age.
    Figure Legend Snippet: Outline of the experimental design and workflow for the integrated analysis of the miRNA-Seq and mRNA-Seq data. Genes that are potentially regulated by the HL-miRNAs were determined by integrating miRNA-Seq and mRNA-Seq data using the following three steps: Step 1 (depicted in green): After identifying the HL-miRNAs enriched relative to BT in either young or old, or both young and old ( Tables 1 and 2 ), we retrieved their computationally predicted target genes from the m 3 RNA database ( http://m3rna.cnb.csic.es ). Step 2 (depicted in blue): mRNA-Seq was utilized to identify three groups of genes that were differentially expressed with age, either upregulated, downregulated, or unchanged in BT. Step 3 (depicted in red): The three groups of genes predicted in step1 as targets of HL-miRNAs were intersected with the three groups of genes identified in step 2. In the figure, ( A ) depicts the derivation of genes that are predicted to be targets of HL-miRNAs enriched in young which are also upregulated with age in BT. These genes (Supplementary Table 1 ) are likely upregulated in BT of old flies because their expression is no longer repressed by HL-miRNAs that are enriched only in young flies. ( B ) Depicts the derivation of genes which are the predicted to be targets of HL-miRNAs enriched in old which are also downregulated with age in BT. These genes (Supplementary Table 2 ) are likely downregulated in BT of old flies because their expression is repressed by HL-miRNAs which are enriched only in old flies. ( C ) Depicts the derivation of genes which are predicted to be targets of HL-miRNAs enriched in both young and old which also do not change expression with age in BT. These genes (Supplementary Table 3) do not change expression with age because the concentration of their regulatory miRNAs in HL does not change with age.

    Techniques Used: Expressing, Concentration Assay

    39) Product Images from "Increased DUX4 expression during muscle differentiation correlates with decreased SMCHD1 protein levels at D4Z4 "

    Article Title: Increased DUX4 expression during muscle differentiation correlates with decreased SMCHD1 protein levels at D4Z4

    Journal: Epigenetics

    doi: 10.1080/15592294.2015.1113798

    DUX4 activation during myogenic differentiation coincides with SMCHD1 reduction. ( A) Immunofluorescence microscopy analysis confirmed the typical DUX4 protein expression pattern in myosin positive, multinucleated myotubes derived from FSHD1 and FSHD2 individuals. Images were taken using a 200x magnification, scale bars are displayed. ( B ) Quantitative mRNA analysis in control ( C ), FSHD1 (F1), and FSHD2 (F2) primary myoblasts (B) and myotubes (T) showing increased levels of DUX4 expression upon differentiation. GAPDH and GUSB were used as reference genes, n indicates number of samples, error bars display SD, and significance was calculated using a 2-tailed Student t-test. ( C ) Quantitative mRNA analysis showed robust ZSCAN4 activation upon myogenic differentiation in FSHD myotubes. GAPDH and GUSB were used as reference genes, n indicates number of samples, error bars display SD, and significance was calculated using a 2-tailed Student t-test. ( D ) Western blot analysis showing reduced levels of SMCHD1 upon muscle cell differentiation in a primary muscle cell culture derived from a control individual. Myoblasts (B) were differentiated into myotubes (T) for 48 h. H3 serves as a control for equal protein loading, α-ACTIN serves as a control for the induction of myogenic differentiation. ( E ) Western blot analysis of a control derived primary fibroblast undergoing forced myogenesis by ectopic MyoD expression for 48, 72, or 94 h showed a decrease in SMCHD1 protein expression. TUBULIN serves as a loading control. ( F ) Duplicate RT-PCR analysis of DUX4 expression upon ectopic MyoD expression in a Control 1, FSHD1 1 or FSHD2 1 fibroblast (Table S2) revealed DUX4 activation in patient cells exclusively. Ectopic GFP expression was used as a control and GUSB serves as an internal PCR control. ( G , H ) Normalized ChIP qPCR analysis of SMCHD1 binding at D4Z4 in isogenic fibroblasts (F), myoblasts (B), and myotubes (T) derived from the same control individual (panel G) and 3 independent control derived myoblast – myotube pairs showed the highest SMCHD1 abundance in myoblasts with a further decrease during myogenesis. Error bars display SD in panel G and H and significance was calculated using a 2-tailed Student's test. NS = not significant; * = P
    Figure Legend Snippet: DUX4 activation during myogenic differentiation coincides with SMCHD1 reduction. ( A) Immunofluorescence microscopy analysis confirmed the typical DUX4 protein expression pattern in myosin positive, multinucleated myotubes derived from FSHD1 and FSHD2 individuals. Images were taken using a 200x magnification, scale bars are displayed. ( B ) Quantitative mRNA analysis in control ( C ), FSHD1 (F1), and FSHD2 (F2) primary myoblasts (B) and myotubes (T) showing increased levels of DUX4 expression upon differentiation. GAPDH and GUSB were used as reference genes, n indicates number of samples, error bars display SD, and significance was calculated using a 2-tailed Student t-test. ( C ) Quantitative mRNA analysis showed robust ZSCAN4 activation upon myogenic differentiation in FSHD myotubes. GAPDH and GUSB were used as reference genes, n indicates number of samples, error bars display SD, and significance was calculated using a 2-tailed Student t-test. ( D ) Western blot analysis showing reduced levels of SMCHD1 upon muscle cell differentiation in a primary muscle cell culture derived from a control individual. Myoblasts (B) were differentiated into myotubes (T) for 48 h. H3 serves as a control for equal protein loading, α-ACTIN serves as a control for the induction of myogenic differentiation. ( E ) Western blot analysis of a control derived primary fibroblast undergoing forced myogenesis by ectopic MyoD expression for 48, 72, or 94 h showed a decrease in SMCHD1 protein expression. TUBULIN serves as a loading control. ( F ) Duplicate RT-PCR analysis of DUX4 expression upon ectopic MyoD expression in a Control 1, FSHD1 1 or FSHD2 1 fibroblast (Table S2) revealed DUX4 activation in patient cells exclusively. Ectopic GFP expression was used as a control and GUSB serves as an internal PCR control. ( G , H ) Normalized ChIP qPCR analysis of SMCHD1 binding at D4Z4 in isogenic fibroblasts (F), myoblasts (B), and myotubes (T) derived from the same control individual (panel G) and 3 independent control derived myoblast – myotube pairs showed the highest SMCHD1 abundance in myoblasts with a further decrease during myogenesis. Error bars display SD in panel G and H and significance was calculated using a 2-tailed Student's test. NS = not significant; * = P

    Techniques Used: Polyacrylamide Gel Electrophoresis, Activation Assay, Immunofluorescence, Microscopy, Expressing, Derivative Assay, Western Blot, Cell Differentiation, Cell Culture, Reverse Transcription Polymerase Chain Reaction, Polymerase Chain Reaction, Chromatin Immunoprecipitation, Real-time Polymerase Chain Reaction, Binding Assay

    SMCHD1 depletion at D4Z4 leads to increased H3K27me3 and PRC2 binding. ( A ) ChIP-qPCR analysis showed a statistically significant reduction of SMCHD1 at qD4Z4 upon its lentiviral knockdown in control myotubes with 2 independent shRNA constructs in 2 independent control myotube cultures. ( B ) ChIP-qPCR analysis of H3K27me3 at qD4Z4 upon SMCHD1 depletion showed a significant increase at qD4Z4. Enrichment values were normalized to H3 enrichment values. ( C ) Normalized ChIP-qPCR analysis of SUZ12 upon SMCHD1 depletion showed a statistically significant increase at qD4Z4 in 2 independent experiments performed on 2 control myoblast cultures. n indicates sample size , error bars indicate SD, and significance was tested with Student t-test. ( D ) ChIP-qPCR analysis of H3K27me3 at qD4Z4 showed a significant increase in FSHD2 myotubes compared to controls. Enrichment values were normalized to H3 enrichment values. ( E ) ChIP-qPCR analysis of SUZ12abundance showed a significant increase in FSHD2 myotubes at qD4Z4. On panel A, B, D, and E, n indicates sample size, error bars display SD, and significance was tested using a one way-ANOVA followed by Bonferroni multiple comparison test. *= P
    Figure Legend Snippet: SMCHD1 depletion at D4Z4 leads to increased H3K27me3 and PRC2 binding. ( A ) ChIP-qPCR analysis showed a statistically significant reduction of SMCHD1 at qD4Z4 upon its lentiviral knockdown in control myotubes with 2 independent shRNA constructs in 2 independent control myotube cultures. ( B ) ChIP-qPCR analysis of H3K27me3 at qD4Z4 upon SMCHD1 depletion showed a significant increase at qD4Z4. Enrichment values were normalized to H3 enrichment values. ( C ) Normalized ChIP-qPCR analysis of SUZ12 upon SMCHD1 depletion showed a statistically significant increase at qD4Z4 in 2 independent experiments performed on 2 control myoblast cultures. n indicates sample size , error bars indicate SD, and significance was tested with Student t-test. ( D ) ChIP-qPCR analysis of H3K27me3 at qD4Z4 showed a significant increase in FSHD2 myotubes compared to controls. Enrichment values were normalized to H3 enrichment values. ( E ) ChIP-qPCR analysis of SUZ12abundance showed a significant increase in FSHD2 myotubes at qD4Z4. On panel A, B, D, and E, n indicates sample size, error bars display SD, and significance was tested using a one way-ANOVA followed by Bonferroni multiple comparison test. *= P

    Techniques Used: Binding Assay, Chromatin Immunoprecipitation, Real-time Polymerase Chain Reaction, shRNA, Construct

    Treatment of FSHD2 myotube cultures with EZH2 inhibitor GSK126 increases DUX4 levels. ( A ) Western blot analysis of control, FSHD1, and FSHD2 myotube samples after treatment with 0, 1, 2, and 4 μM GSK126. Blots were probed with H3K27me3 antibody and H3 antibody as loading control. Shown are the reduced ratios of H3K27me3:H3 signal intensities in samples treated with GSK126 compared to the untreated sample as a result of EZH2 inhibition. ( B ) qRT-PCR analysis of DUX4 expression in FSHD1 and FSHD2 myotubes after GSK126 treatment shows that relative DUX4 transcript levels are significantly increased in FSHD2 samples treated with 2 μM GSK126 but not in FSHD1 myotubes. Graph shows the results of 4 FSHD1 and 4 FSHD2 cell lines. Results of control cell lines are not shown, DUX4 transcript was not detectable. Error bars show SD, n indicates number of independent cell lines, and significance was tested by 2-way ANOVA followed by Bonferroni multiple comparison test. *= P
    Figure Legend Snippet: Treatment of FSHD2 myotube cultures with EZH2 inhibitor GSK126 increases DUX4 levels. ( A ) Western blot analysis of control, FSHD1, and FSHD2 myotube samples after treatment with 0, 1, 2, and 4 μM GSK126. Blots were probed with H3K27me3 antibody and H3 antibody as loading control. Shown are the reduced ratios of H3K27me3:H3 signal intensities in samples treated with GSK126 compared to the untreated sample as a result of EZH2 inhibition. ( B ) qRT-PCR analysis of DUX4 expression in FSHD1 and FSHD2 myotubes after GSK126 treatment shows that relative DUX4 transcript levels are significantly increased in FSHD2 samples treated with 2 μM GSK126 but not in FSHD1 myotubes. Graph shows the results of 4 FSHD1 and 4 FSHD2 cell lines. Results of control cell lines are not shown, DUX4 transcript was not detectable. Error bars show SD, n indicates number of independent cell lines, and significance was tested by 2-way ANOVA followed by Bonferroni multiple comparison test. *= P

    Techniques Used: Western Blot, Inhibition, Quantitative RT-PCR, Expressing

    SMCHD1, but not SUV39H1 and Cohesin, regulates DUX4 expression. Western blot confirmation of ( A ) SMCHD1, ( B ) SUV39H1, ( D ) RAD21, and E ) SMC3 knockdown in control myotubes expressing the indicated lentiviral transduced shRNAs. Tubulin was used as a loading control. Representative blots of at least duplicate experiments are shown. ( C , F ) Standard gel electrophoresis analysis of DUX4 expression upon lentiviral knockdown of SMCHD1, SUV39H1, RAD21 and SMC3 in control myotubes. Only depletion of SMCHD1 resulted in reproducible activation of DUX4 transcription. Representative gel photos are shown of at least duplicate experiments. The PCR fragment visible in one RAD21 knockdown was sequenced and shown to be the product of an a-specific amplification. ( G ) Western blot analysis confirms a 2-3 fold increase of SMCHD1 expression upon its lentiviral transduction in 2 FSHD1 and 1 FSHD2 myotube cultures. GFP transduced myotubes served as a negative control. Numbers indicate normalized relative expression levels of SMCHD1 using Tubulin as a loading control followed by setting normalized SMCHD1 levels of GFP transduced samples (only expressing endogenous SMCHD1) to 1. ( H ) Expression levels of DUX4 were significantly reduced upon ectopic expression of SMCHD1 in 2 FSHD1 and 2 FSHD2 myotube cultures. Relative DUX4 expression was calculated for each sample by normalization to GUSB and GAPDH housekeeping genes. Bars show values of each samples adjusted to the expression value of GFP transduced sample as 1. ( I ) Expression levels of the DUX4 target genes RFPL2, ZSCAN4, and TRIM43 showed a significant reduction upon ectopic expression of SMCHD1 in 2 FSHD1 and 2 FSHD2 myotubes, concordant with decreased DUX4 protein expression. Expression levels were normalized as described for panel Figure 1A . For panel H, I: Error bars display SD and significance was calculated using a 2-tailed Student's t-test. All P
    Figure Legend Snippet: SMCHD1, but not SUV39H1 and Cohesin, regulates DUX4 expression. Western blot confirmation of ( A ) SMCHD1, ( B ) SUV39H1, ( D ) RAD21, and E ) SMC3 knockdown in control myotubes expressing the indicated lentiviral transduced shRNAs. Tubulin was used as a loading control. Representative blots of at least duplicate experiments are shown. ( C , F ) Standard gel electrophoresis analysis of DUX4 expression upon lentiviral knockdown of SMCHD1, SUV39H1, RAD21 and SMC3 in control myotubes. Only depletion of SMCHD1 resulted in reproducible activation of DUX4 transcription. Representative gel photos are shown of at least duplicate experiments. The PCR fragment visible in one RAD21 knockdown was sequenced and shown to be the product of an a-specific amplification. ( G ) Western blot analysis confirms a 2-3 fold increase of SMCHD1 expression upon its lentiviral transduction in 2 FSHD1 and 1 FSHD2 myotube cultures. GFP transduced myotubes served as a negative control. Numbers indicate normalized relative expression levels of SMCHD1 using Tubulin as a loading control followed by setting normalized SMCHD1 levels of GFP transduced samples (only expressing endogenous SMCHD1) to 1. ( H ) Expression levels of DUX4 were significantly reduced upon ectopic expression of SMCHD1 in 2 FSHD1 and 2 FSHD2 myotube cultures. Relative DUX4 expression was calculated for each sample by normalization to GUSB and GAPDH housekeeping genes. Bars show values of each samples adjusted to the expression value of GFP transduced sample as 1. ( I ) Expression levels of the DUX4 target genes RFPL2, ZSCAN4, and TRIM43 showed a significant reduction upon ectopic expression of SMCHD1 in 2 FSHD1 and 2 FSHD2 myotubes, concordant with decreased DUX4 protein expression. Expression levels were normalized as described for panel Figure 1A . For panel H, I: Error bars display SD and significance was calculated using a 2-tailed Student's t-test. All P

    Techniques Used: Polyacrylamide Gel Electrophoresis, Expressing, Western Blot, Nucleic Acid Electrophoresis, Activation Assay, Polymerase Chain Reaction, Amplification, Transduction, Negative Control

    40) Product Images from "Scutellarin regulates microglia-mediated TNC1 astrocytic reaction and astrogliosis in cerebral ischemia in the adult rats"

    Article Title: Scutellarin regulates microglia-mediated TNC1 astrocytic reaction and astrogliosis in cerebral ischemia in the adult rats

    Journal: BMC Neuroscience

    doi: 10.1186/s12868-015-0219-6

    Cell viability assay of TNC1 astrocytes ( a ): scutellarin (in the range of 0.2–2.0 mM) incubated for different duration did not result in any significant cell death. Treatment of TNC1 with scutellarin ( b ): scutellarin at 0.54 mM did not elicit a noticeable reaction in TNC1 whose GFAP/TNF-α ( B1 – 3 ) expression remained comparable to cells in the control in basic medium (BM) ( A1 – 3 ). BM + S, basic medium + scutellarin. Microglia mediate TNC1 astrocyte reaction ( c ): TNF-α mRNA expression in TNC1 astrocytes remained relatively unchanged at all time-points following treatment with BM, BM + L and BV-2 conditioned medium (CM). However, in TNC1 incubated CM + L for various time points, TNC1 showed a remarkable increase in TNF-α peaking at 24 h. Confocal images in d showing GFAP ( C1 – 3 ), and TNF-α ( D1 – 3 ) expression in TNC1 astrocytes incubated with different medium for 24 h. Compared with cells incubated in BM and BM + LPS (BM + L), TNC1 astrocytes incubated with LPS-stimulated BV-2 cell conditioned medium (CM + L) ( C3 , D3 ) are hypertrophic and exhibit a marked increase in GFAP and TNF-α immunofluorescence. Scale bars 20 μm
    Figure Legend Snippet: Cell viability assay of TNC1 astrocytes ( a ): scutellarin (in the range of 0.2–2.0 mM) incubated for different duration did not result in any significant cell death. Treatment of TNC1 with scutellarin ( b ): scutellarin at 0.54 mM did not elicit a noticeable reaction in TNC1 whose GFAP/TNF-α ( B1 – 3 ) expression remained comparable to cells in the control in basic medium (BM) ( A1 – 3 ). BM + S, basic medium + scutellarin. Microglia mediate TNC1 astrocyte reaction ( c ): TNF-α mRNA expression in TNC1 astrocytes remained relatively unchanged at all time-points following treatment with BM, BM + L and BV-2 conditioned medium (CM). However, in TNC1 incubated CM + L for various time points, TNC1 showed a remarkable increase in TNF-α peaking at 24 h. Confocal images in d showing GFAP ( C1 – 3 ), and TNF-α ( D1 – 3 ) expression in TNC1 astrocytes incubated with different medium for 24 h. Compared with cells incubated in BM and BM + LPS (BM + L), TNC1 astrocytes incubated with LPS-stimulated BV-2 cell conditioned medium (CM + L) ( C3 , D3 ) are hypertrophic and exhibit a marked increase in GFAP and TNF-α immunofluorescence. Scale bars 20 μm

    Techniques Used: Viability Assay, Incubation, Expressing, Immunofluorescence

    Scutellarin enhanced GFAP ( A1 – A3 ), Notch-1 ( B1 – B3 ), NICD ( C1 – C3 ), HES-1 ( D1 – D3 ), nestin ( E1 – E3 ) and TNF-α ( A1 – 3 ) expression in TNC1 via BV-2-conditioned medium. Moderate GFAP expression was detected in TNC1 incubated in CM; also, Notch-1, NICD, HES-1, nestin and TNF-α ( B1 , C1 , D1 , E1 , F1 ) was weakly expressed. The expression however was enhanced in CM + L ( B2 , C2 , D2 , E2 , F2 ). Upon treatment with CM + SL for 24 h, expression of all markers was drastically increased being more pronounced for NICD ( C3 ) and nestin ( E3 ). Note TNC1 astrocytes project long cytoplasmic processes with expansions ( A3 , D3 , F3 ). Scale bars 20 μm
    Figure Legend Snippet: Scutellarin enhanced GFAP ( A1 – A3 ), Notch-1 ( B1 – B3 ), NICD ( C1 – C3 ), HES-1 ( D1 – D3 ), nestin ( E1 – E3 ) and TNF-α ( A1 – 3 ) expression in TNC1 via BV-2-conditioned medium. Moderate GFAP expression was detected in TNC1 incubated in CM; also, Notch-1, NICD, HES-1, nestin and TNF-α ( B1 , C1 , D1 , E1 , F1 ) was weakly expressed. The expression however was enhanced in CM + L ( B2 , C2 , D2 , E2 , F2 ). Upon treatment with CM + SL for 24 h, expression of all markers was drastically increased being more pronounced for NICD ( C3 ) and nestin ( E3 ). Note TNC1 astrocytes project long cytoplasmic processes with expansions ( A3 , D3 , F3 ). Scale bars 20 μm

    Techniques Used: Expressing, Incubation

    Scanning electron microscopy of TNC1 astrocytes in CM ( A1–2 ), CM + SL ( B1–2 ) and CM + SL ( C1–2 ) groups. Note the drastic transformation of TNC1 from oblong outline (CM, A1–2 ) to “squamous” appearance in the CM + SL ( C1–2 ) whose cell surface exhibit a large number of filamentous processes ( arrows ). By transmission electron microscopy ( D1–3 ), TNC1 astrocytes in CM + SL are evidently enlarged ( D3 ) as compared with CM ( D1 ) and CM + L ( D2 ) groups; moreover, the cells contain a larger amount of cytoplasm rich in polyribosomes and usual organelles
    Figure Legend Snippet: Scanning electron microscopy of TNC1 astrocytes in CM ( A1–2 ), CM + SL ( B1–2 ) and CM + SL ( C1–2 ) groups. Note the drastic transformation of TNC1 from oblong outline (CM, A1–2 ) to “squamous” appearance in the CM + SL ( C1–2 ) whose cell surface exhibit a large number of filamentous processes ( arrows ). By transmission electron microscopy ( D1–3 ), TNC1 astrocytes in CM + SL are evidently enlarged ( D3 ) as compared with CM ( D1 ) and CM + L ( D2 ) groups; moreover, the cells contain a larger amount of cytoplasm rich in polyribosomes and usual organelles

    Techniques Used: Electron Microscopy, Transformation Assay, Transmission Assay

    Protein expression of GFAP, Notch-1, NICD, HES-1, TNF-α, IL-1β and iNOS in TNC1 following different treatments. a Expression levels of GFAP, Notch-1, NICD, and HES-1 were significantly increased after treatment with CM + L when compared with the control in CM; likewise, the expression of TNF-α, IL-1β and iNOS was significantly increased. b In CM + SL treated TNC1, the expression levels of the above markers were further elevated as compared with that of CM + L treated cells. Bar graphs represent expression changes of the respective markers. Significant differences in protein levels are expressed as * # P
    Figure Legend Snippet: Protein expression of GFAP, Notch-1, NICD, HES-1, TNF-α, IL-1β and iNOS in TNC1 following different treatments. a Expression levels of GFAP, Notch-1, NICD, and HES-1 were significantly increased after treatment with CM + L when compared with the control in CM; likewise, the expression of TNF-α, IL-1β and iNOS was significantly increased. b In CM + SL treated TNC1, the expression levels of the above markers were further elevated as compared with that of CM + L treated cells. Bar graphs represent expression changes of the respective markers. Significant differences in protein levels are expressed as * # P

    Techniques Used: Expressing

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    Western Blot:

    Article Title: Controlled ovarian hyperstimulation induced changes in the expression of circulatory miRNA in bovine follicular fluid and blood plasma
    Article Snippet: .. Western blot analysis Exosomal and Ago2 immunoprecipitate proteins were isolated from organic phenol part during total RNA isolation using miRNeasy mini kit (Qiagen, Hilden, Germany) and resuspended in 8 M Urea. .. Approximately 20 μg of protein from each sample were resolved in 12 % SDS-PAGE polyacrylamide gel (Bio-Rad, Corp., Hercules, CA, USA) and immune reactive proteins were visualized with a Chemidoc XRS (Bio-Rad) instrument.

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    Qiagen qrt pcr mirneasy mini kit
    MEG3 physically interacts with SMO protein. a The overall interaction propensity of MEG3 and SMO protein was predicted by catRAPID. b Predicted interaction between MEG3 (nucleotide positions 0–1200 nt) and SMO protein (amino acid residues 0–720). c RIP experiments were performed using SMO antibody in primary HSCs at Day 0. <t>qRT-PCR</t> was performed to detect pulled-down MEG3. hnRNP-K antibody and IgG were used as positive and negative controls, respectively. d SMO asscociated MEG3 was detected by regular RT-PCR. e Mapping the SMO interaction region of MEG3. Biotinylated RNAs corresponding to different fragments of MEG3 or its antisense sequences (red line) were co-incubated with cell lysates and associated SMO proteins were detected by immunoblotting
    Qrt Pcr Mirneasy Mini Kit, supplied by Qiagen, used in various techniques. Bioz Stars score: 99/100, based on 3914 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/qrt pcr mirneasy mini kit/product/Qiagen
    Average 99 stars, based on 3914 article reviews
    Price from $9.99 to $1999.99
    qrt pcr mirneasy mini kit - by Bioz Stars, 2020-08
    99/100 stars
      Buy from Supplier

    99
    Qiagen mirneasy micro kit
    Capillary electrophoresis analysis of pig LV biopsy RNA. ( A) Bioanalyzer nano chip traces of all tested samples. Inspection of electropherograms provides additional information to assess RNA quality and protocol performance. (B) Representative traces from each protocol with respective RIN values. Numbers 1–4 correspond to numbered boxes in A. Note that trace 3 has a high RIN despite a large smear in the gel. (C) Summary of RIN values of all the samples tested (mean±SEM). The RNAqueous protocol had undetectable RINs. The mir Vana and miRCURY tissue protocols gave consistently high RIN values, while despite high average RIN, the samples from the <t>miRNeasy</t> micro protocol are more variable. Numbers in brackets indicate the number of samples in each group. (D) Bioanalyzer small RNA chip traces for each kit. Although the RIN of samples marked * were similar (8.6–8.7), the spectrum of small RNAs recovered is highly heterogeneous.
    Mirneasy Micro Kit, supplied by Qiagen, used in various techniques. Bioz Stars score: 99/100, based on 143 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/mirneasy micro kit/product/Qiagen
    Average 99 stars, based on 143 article reviews
    Price from $9.99 to $1999.99
    mirneasy micro kit - by Bioz Stars, 2020-08
    99/100 stars
      Buy from Supplier

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    MEG3 physically interacts with SMO protein. a The overall interaction propensity of MEG3 and SMO protein was predicted by catRAPID. b Predicted interaction between MEG3 (nucleotide positions 0–1200 nt) and SMO protein (amino acid residues 0–720). c RIP experiments were performed using SMO antibody in primary HSCs at Day 0. qRT-PCR was performed to detect pulled-down MEG3. hnRNP-K antibody and IgG were used as positive and negative controls, respectively. d SMO asscociated MEG3 was detected by regular RT-PCR. e Mapping the SMO interaction region of MEG3. Biotinylated RNAs corresponding to different fragments of MEG3 or its antisense sequences (red line) were co-incubated with cell lysates and associated SMO proteins were detected by immunoblotting

    Journal: Cell Death & Disease

    Article Title: LncRNA-MEG3 inhibits activation of hepatic stellate cells through SMO protein and miR-212

    doi: 10.1038/s41419-018-1068-x

    Figure Lengend Snippet: MEG3 physically interacts with SMO protein. a The overall interaction propensity of MEG3 and SMO protein was predicted by catRAPID. b Predicted interaction between MEG3 (nucleotide positions 0–1200 nt) and SMO protein (amino acid residues 0–720). c RIP experiments were performed using SMO antibody in primary HSCs at Day 0. qRT-PCR was performed to detect pulled-down MEG3. hnRNP-K antibody and IgG were used as positive and negative controls, respectively. d SMO asscociated MEG3 was detected by regular RT-PCR. e Mapping the SMO interaction region of MEG3. Biotinylated RNAs corresponding to different fragments of MEG3 or its antisense sequences (red line) were co-incubated with cell lysates and associated SMO proteins were detected by immunoblotting

    Article Snippet: qRT-PCR miRNeasy Mini Kit (Qiagen, Valencia, CA, USA) was used to extract the total RNA from primary cells as well as liver tissues.

    Techniques: Quantitative RT-PCR, Reverse Transcription Polymerase Chain Reaction, Incubation

    Downregulation of MEG3 in liver fibrosis. a Collagen and α-SMA were analyzed in CCl 4 mice by Masson staining and immunohistochemistry, respectively. Scale bar, 100 μm. b MEG3-1, MEG3-2, and MEG3-3 expressions were detected by qRT-PCR in CCl 4 mice. c Expressions of MEG3-1, MEG3-2, and MEG3-3 were analyzed in primary HSCs at Day 0 and Day 4. Primary HSCs were isolated from the livers of healthy mice. d MEG3 was analyzed in primary HSCs isolated from oil- or CCl 4 -treated mice. e MEG3 was analyzed in primary HSCs and primary hepatocytes from the livers of healthy mice. * P

    Journal: Cell Death & Disease

    Article Title: LncRNA-MEG3 inhibits activation of hepatic stellate cells through SMO protein and miR-212

    doi: 10.1038/s41419-018-1068-x

    Figure Lengend Snippet: Downregulation of MEG3 in liver fibrosis. a Collagen and α-SMA were analyzed in CCl 4 mice by Masson staining and immunohistochemistry, respectively. Scale bar, 100 μm. b MEG3-1, MEG3-2, and MEG3-3 expressions were detected by qRT-PCR in CCl 4 mice. c Expressions of MEG3-1, MEG3-2, and MEG3-3 were analyzed in primary HSCs at Day 0 and Day 4. Primary HSCs were isolated from the livers of healthy mice. d MEG3 was analyzed in primary HSCs isolated from oil- or CCl 4 -treated mice. e MEG3 was analyzed in primary HSCs and primary hepatocytes from the livers of healthy mice. * P

    Article Snippet: qRT-PCR miRNeasy Mini Kit (Qiagen, Valencia, CA, USA) was used to extract the total RNA from primary cells as well as liver tissues.

    Techniques: Mouse Assay, Staining, Immunohistochemistry, Quantitative RT-PCR, Isolation

    Specificity of isolation of exosomes and Ago2 protein complex from follicular fluid and blood plasma. Exosome and Ago2 proteins were isolated from organic-phenol fraction during total RNA isolation using miRNeasy kit and resolved in 8M urea. Protein concentrations were quantified using Bradford assay and total of twenty microgram protein from each group were separated in 12 % SDS-PAGE, transferred nitrocellulose membrane and incubated with specific antibody (CD63 and Ago2). Followed by HRP-conjugated secondary antibody and detected using chemiluminescent substrate. Western-blot results indicate the specificity of exosome and Ago2 protein isolation from follicular fluid (FF) and blood plasma (BP) as indicated in the corresponding figures

    Journal: Journal of Ovarian Research

    Article Title: Controlled ovarian hyperstimulation induced changes in the expression of circulatory miRNA in bovine follicular fluid and blood plasma

    doi: 10.1186/s13048-015-0208-5

    Figure Lengend Snippet: Specificity of isolation of exosomes and Ago2 protein complex from follicular fluid and blood plasma. Exosome and Ago2 proteins were isolated from organic-phenol fraction during total RNA isolation using miRNeasy kit and resolved in 8M urea. Protein concentrations were quantified using Bradford assay and total of twenty microgram protein from each group were separated in 12 % SDS-PAGE, transferred nitrocellulose membrane and incubated with specific antibody (CD63 and Ago2). Followed by HRP-conjugated secondary antibody and detected using chemiluminescent substrate. Western-blot results indicate the specificity of exosome and Ago2 protein isolation from follicular fluid (FF) and blood plasma (BP) as indicated in the corresponding figures

    Article Snippet: Western blot analysis Exosomal and Ago2 immunoprecipitate proteins were isolated from organic phenol part during total RNA isolation using miRNeasy mini kit (Qiagen, Hilden, Germany) and resuspended in 8 M Urea.

    Techniques: Isolation, Bradford Assay, SDS Page, Incubation, Western Blot

    Detection of miR-375 stored in LDCVs. ( a ) Schematic of test for miR-375 stored in LDCVs (top); 1% (vol/vol) TX-100 was incubated with LDCVs to disrupt the vesicle membrane. RNase A was then applied to degrade miR-375. Relative levels of miR-375 with or without 1% (vol/vol) TX-100 were determined by qRT-PCR (bottom). ( b ) LDCVs were treated with Proteinase K in the presence of TX-100, followed by RNase A treatment. ( c ) RNase A was applied after RNA extraction using the miRNeasy Mini Kit. Proteins are removed from RNA samples. Values represent a percentage of control and data are mean ± SD from three to four independent replicates.

    Journal: Scientific Reports

    Article Title: Isolation of large dense-core vesicles from bovine adrenal medulla for functional studies

    doi: 10.1038/s41598-020-64486-3

    Figure Lengend Snippet: Detection of miR-375 stored in LDCVs. ( a ) Schematic of test for miR-375 stored in LDCVs (top); 1% (vol/vol) TX-100 was incubated with LDCVs to disrupt the vesicle membrane. RNase A was then applied to degrade miR-375. Relative levels of miR-375 with or without 1% (vol/vol) TX-100 were determined by qRT-PCR (bottom). ( b ) LDCVs were treated with Proteinase K in the presence of TX-100, followed by RNase A treatment. ( c ) RNase A was applied after RNA extraction using the miRNeasy Mini Kit. Proteins are removed from RNA samples. Values represent a percentage of control and data are mean ± SD from three to four independent replicates.

    Article Snippet: RNA isolation kit, miRNeasy Mini Kit (Qiagen, cat. no. 217004). cDNA synthesis kit, miScript RT II kit (Qiagen, cat. no. 218161).

    Techniques: Incubation, Quantitative RT-PCR, RNA Extraction

    Capillary electrophoresis analysis of pig LV biopsy RNA. ( A) Bioanalyzer nano chip traces of all tested samples. Inspection of electropherograms provides additional information to assess RNA quality and protocol performance. (B) Representative traces from each protocol with respective RIN values. Numbers 1–4 correspond to numbered boxes in A. Note that trace 3 has a high RIN despite a large smear in the gel. (C) Summary of RIN values of all the samples tested (mean±SEM). The RNAqueous protocol had undetectable RINs. The mir Vana and miRCURY tissue protocols gave consistently high RIN values, while despite high average RIN, the samples from the miRNeasy micro protocol are more variable. Numbers in brackets indicate the number of samples in each group. (D) Bioanalyzer small RNA chip traces for each kit. Although the RIN of samples marked * were similar (8.6–8.7), the spectrum of small RNAs recovered is highly heterogeneous.

    Journal: PLoS ONE

    Article Title: Optimisation of laboratory methods for whole transcriptomic RNA analyses in human left ventricular biopsies and blood samples of clinical relevance

    doi: 10.1371/journal.pone.0213685

    Figure Lengend Snippet: Capillary electrophoresis analysis of pig LV biopsy RNA. ( A) Bioanalyzer nano chip traces of all tested samples. Inspection of electropherograms provides additional information to assess RNA quality and protocol performance. (B) Representative traces from each protocol with respective RIN values. Numbers 1–4 correspond to numbered boxes in A. Note that trace 3 has a high RIN despite a large smear in the gel. (C) Summary of RIN values of all the samples tested (mean±SEM). The RNAqueous protocol had undetectable RINs. The mir Vana and miRCURY tissue protocols gave consistently high RIN values, while despite high average RIN, the samples from the miRNeasy micro protocol are more variable. Numbers in brackets indicate the number of samples in each group. (D) Bioanalyzer small RNA chip traces for each kit. Although the RIN of samples marked * were similar (8.6–8.7), the spectrum of small RNAs recovered is highly heterogeneous.

    Article Snippet: RNA isolation from human plasma Recovery of miRNAs from pig plasma was consistently highest using the Qiagen miRNeasy micro kit with additional glycogen co-precipitation, therefore this protocol was used for further biofluids RNA extractions from human clinical samples.

    Techniques: Electrophoresis, Chromatin Immunoprecipitation

    Evaluating plasma RNA yield using RT-qPCR for miRNAs. As biofluid RNA is below the detection limit of standard quantification tools, all RT-qPCRs were performed using 1.5 μL RNA extracted from 200 μL plasma. Lines indicate paired samples i.e. aliquots of plasma from the same blood draw. (A) RT-qPCR for the spike-in cel-miR-39-3p using the four kits with and without glycogen. (B-D) RT-qPCR for three endogenous miRNAs isolated using the four kits with and without glycogen. (E) The miRNeasy serum/plasma protocol recommends elution in 14 μL, compared with 100 μL for the mir Vana protocol. To control for effects of this, RNA extractions were performed with both protocols, eluting in 30 μL or 50 μL. RT-qPCR for cel-miR-39-3p, hsa-miR-16-5p and hsa-miR-21-5p were performed to evaluate the different elution volumes.

    Journal: PLoS ONE

    Article Title: Optimisation of laboratory methods for whole transcriptomic RNA analyses in human left ventricular biopsies and blood samples of clinical relevance

    doi: 10.1371/journal.pone.0213685

    Figure Lengend Snippet: Evaluating plasma RNA yield using RT-qPCR for miRNAs. As biofluid RNA is below the detection limit of standard quantification tools, all RT-qPCRs were performed using 1.5 μL RNA extracted from 200 μL plasma. Lines indicate paired samples i.e. aliquots of plasma from the same blood draw. (A) RT-qPCR for the spike-in cel-miR-39-3p using the four kits with and without glycogen. (B-D) RT-qPCR for three endogenous miRNAs isolated using the four kits with and without glycogen. (E) The miRNeasy serum/plasma protocol recommends elution in 14 μL, compared with 100 μL for the mir Vana protocol. To control for effects of this, RNA extractions were performed with both protocols, eluting in 30 μL or 50 μL. RT-qPCR for cel-miR-39-3p, hsa-miR-16-5p and hsa-miR-21-5p were performed to evaluate the different elution volumes.

    Article Snippet: RNA isolation from human plasma Recovery of miRNAs from pig plasma was consistently highest using the Qiagen miRNeasy micro kit with additional glycogen co-precipitation, therefore this protocol was used for further biofluids RNA extractions from human clinical samples.

    Techniques: Quantitative RT-PCR, Isolation

    Spectrophotometry analysis of pig LV biopsy RNA. RNA extracted according to each manufacturer’s protocol, with the addition of a proteinase K digestion in half the samples. n = 3 biopsies/experimental condition, mean±SEM. N . B . Exiqon miRCURY tissue protocol requires proteinase K, therefore no–proteinase K condition was done with this kit. (A) RNA yield, assessed as ng RNA recovered per mg input tissue, was not significantly different between the protocols (Kruskal-Wallis test with Dunn correction), and additional proteinase K digestion in the RNAqueous micro, mir Vana and miRNeasy micro protocols did not significantly improve RNA yield (Kruskal-Wallis test with Dunn correction). (B) 260/280 and 260/230 ratios provide an assessment of the purity of the RNA. Ratio

    Journal: PLoS ONE

    Article Title: Optimisation of laboratory methods for whole transcriptomic RNA analyses in human left ventricular biopsies and blood samples of clinical relevance

    doi: 10.1371/journal.pone.0213685

    Figure Lengend Snippet: Spectrophotometry analysis of pig LV biopsy RNA. RNA extracted according to each manufacturer’s protocol, with the addition of a proteinase K digestion in half the samples. n = 3 biopsies/experimental condition, mean±SEM. N . B . Exiqon miRCURY tissue protocol requires proteinase K, therefore no–proteinase K condition was done with this kit. (A) RNA yield, assessed as ng RNA recovered per mg input tissue, was not significantly different between the protocols (Kruskal-Wallis test with Dunn correction), and additional proteinase K digestion in the RNAqueous micro, mir Vana and miRNeasy micro protocols did not significantly improve RNA yield (Kruskal-Wallis test with Dunn correction). (B) 260/280 and 260/230 ratios provide an assessment of the purity of the RNA. Ratio

    Article Snippet: RNA isolation from human plasma Recovery of miRNAs from pig plasma was consistently highest using the Qiagen miRNeasy micro kit with additional glycogen co-precipitation, therefore this protocol was used for further biofluids RNA extractions from human clinical samples.

    Techniques: Spectrophotometry

    Summary of experimental design for Figs 2 , 3 and 4 . (A) Left ventricular biopsies were taken from three pigs undergoing cardio-pulmonary bypass (CPB). 7 biopsies were taken per pig. RNA was isolated from the biopsies using four commercially available kits; RNAqueous micro, mir Vana, miRCURY tissue, miRNeasy micro. Three kits (RNAqueous micro, mir Vana, miRNeasy micro) were tested with and without an additional proteinase K digestion step, giving 7 protocols in total. The miRCURY tissue protocol includes a proteinase K digestion, therefore this kit was not tested without this. RNA samples were characterised by spectrophotometry and capillary electrophoresis. (B) Blood samples were taken from three pigs undergoing CPB and processed to plasma. RNA was isolated from the plasma using four commercially-available kits; miRNeasy serum/plasma, mir Vana, miRCURY biofluids, Norgen Biotek plasma/serum. Each kit was tested with and without glycogen as a co-precipitant, giving 8 protocols in total. RNA samples were evaluated by RT-qPCR for the exogenous spike-in cel-miR-39-3p, and endogenous miRNAs miR-16-5p, miR-21-5p, miR-92a-3p.

    Journal: PLoS ONE

    Article Title: Optimisation of laboratory methods for whole transcriptomic RNA analyses in human left ventricular biopsies and blood samples of clinical relevance

    doi: 10.1371/journal.pone.0213685

    Figure Lengend Snippet: Summary of experimental design for Figs 2 , 3 and 4 . (A) Left ventricular biopsies were taken from three pigs undergoing cardio-pulmonary bypass (CPB). 7 biopsies were taken per pig. RNA was isolated from the biopsies using four commercially available kits; RNAqueous micro, mir Vana, miRCURY tissue, miRNeasy micro. Three kits (RNAqueous micro, mir Vana, miRNeasy micro) were tested with and without an additional proteinase K digestion step, giving 7 protocols in total. The miRCURY tissue protocol includes a proteinase K digestion, therefore this kit was not tested without this. RNA samples were characterised by spectrophotometry and capillary electrophoresis. (B) Blood samples were taken from three pigs undergoing CPB and processed to plasma. RNA was isolated from the plasma using four commercially-available kits; miRNeasy serum/plasma, mir Vana, miRCURY biofluids, Norgen Biotek plasma/serum. Each kit was tested with and without glycogen as a co-precipitant, giving 8 protocols in total. RNA samples were evaluated by RT-qPCR for the exogenous spike-in cel-miR-39-3p, and endogenous miRNAs miR-16-5p, miR-21-5p, miR-92a-3p.

    Article Snippet: RNA isolation from human plasma Recovery of miRNAs from pig plasma was consistently highest using the Qiagen miRNeasy micro kit with additional glycogen co-precipitation, therefore this protocol was used for further biofluids RNA extractions from human clinical samples.

    Techniques: Isolation, Spectrophotometry, Electrophoresis, Quantitative RT-PCR