Journal: bioRxiv

Article Title: Rhodococcus parequi sp. nov., a new species isolated from equine farm soil closely related to the pathogen Rhodococcus equi

doi: 10.1101/2024.12.09.627583

Figure Lengend Snippet: Heat map of Phenotype MicroArray TM (PM) results for carbon and nitrogen source utilization by PAM 2766 T , R. equi DSM 20307 T and R. equi 103S (PAM 1126). Bacterial inocula were grown at 30°C in TSB until the stationary phase and then suspended in mReMM mineral medium and transferred to the PM plates. Incubabion was performed at 30°C with OD 590 monitored every 15 min for 48 hours in an OmniLog reader. Strains were tested in duplicate and results were analysed using OmniLog software. Maximum growth is represented in graded colours from lowest (black) to highest (yellow). Red arrows indicate differential utilization of a substrate between PAM 2766 T and R. equi. Black arrows in the PM1 and PM2A plates indicate a carbon source utilized by the three tested bacteria (see Table S2 for detailed results). Asterisks indicate false positive reactions in the PM2A plate previously reported in ref. .

Article Snippet: Phenotype MicroArray TM (Biolog Inc.) screens for carbon (PM1 and PM2A plates) and nitrogen (PM3B plates) sources were used to identify additional differential phenotypic markers.

Techniques: Microarray, Software, Bacteria

Journal: Nature biotechnology

Article Title: Generation of pancreatic β cells from CD177 + anterior definitive endoderm.

doi: 10.1038/s41587-020-0492-5

Figure Lengend Snippet: Fig. 1 | Identification of CD177+ and CD275+ ADE subpopulations. a, Schematic representation of hESC differentiation toward DE. b,c, Representative FACS plots of apparently homogeneous FOXA2+/SOX17+ DE (b) showing a heterogenous population marked by CXCR4+/CD117+ cells (c) (n = 3 (b), n = 6 (c) biologically independent experiments). d–g, Gene expression profiles of CXCR4+/CD117−, CXCR4high/CD117high, CXCR4mid/CD117mid and CXCR4low/CD117low cells for FOXA2 (d), SOX17 (e), CER1 (f) and HHEX (g) (ANOVA, n = 3 biologically independent experiments). Data are represented as mean ± s.e.m.; P < 0.05 and P < 0.01. Statistically nonsignificant results are not indicated in the figure. h, Summary of the antibody screen identifying and isolating CD177 and CD275 as markers of ADE subpopulations. CXCR4 and FOXA2 are used as controls to identify the whole DE. i, hPSCs and hPSC-derived DE stained for CXCR4, CD177 and CD275 as shown by live-cell FACS (n = 10 biologically independent experiments). AA, activin A; D, day.

Article Snippet: Materials & experimental systems n/a Involved in the study Antibodies Eukaryotic cell lines Palaeontology Animals and other organisms Human research participants Clinical data Methods n/a Involved in the study ChIP-seq Flow cytometry MRI-based neuroimaging Antibodies Antibodies used Human CXCR4-PE,Miltenyi Biotech,130-098-354, dilution 1:40; Human CXCR4-APC,Miltenyi Biotech, 120-010-802, dilution 1:40; Human CD117-APC, Miltenyi Biotech, 130-091-733, dilution 1:40; Human CD117-PE, Miltenyi Biotech, 130-091-734, dilution 1:40; FOXA2-Alexa Fluor® 488, R and D, IC2400G; dilution 1:10 SOX17-APC, R and D, IC1924A; dilution 1:10 Human CD177-APC, Miltenyi Biotech, 120-017-498; dilution 1:20 Human CD275-APC, Miltenyi Biotech, 120-012-112; dilution 1:20 PE Mouse anti-PDX1, BD PharmingenTM, 562161; dilution 1:40 4 nature research | reporting sum m ary O ctober 2018 Alexa Fluor® 647 Mouse anti-Nkx6.1, BD PharmingenTM, 563338; dilution 1:40 Alexa Fluor® 647 Mouse IgG1 κ Isotype Control, BD PharmingenTM, 563023; dilution 1:40 Rabbit FOXA2, Cell signalling, 8186; dilution 1:1000 Goat SOX17 Acris/Novus GT15094, dilution 1:1000 Goat CER1 R&D Systems AF1075, dilution 1:1000 Mouse β-catenin BD 610154, dilution 1:1000 Guinea pig INSULIN Thermo Schientific PA1-26938, dilution 1:100 Guinea pig C-Peptide Abcam ab30477, dilution 1:300 Rabbit MAFA Betalogics LP9872, dilution 1:100 Rabbit MAFA ,Novus Biologicals, NB400-137, dilution 1:100 Rabbit GLUT1 Thermo Fisher PA1-37782, dilution 1:100 Goat GATA6 R&D Systems AF1700, dilution 1:1000 Mouse SOX2 Abgent / Bio Cat AM2048, dilution 1:1000 Rabbit CDX2 Santa Cruz sc-134468, dilution 1:1000 Mouse GCG Sigma G2654-.2ML, dilution 1:300 Goat PDX1 R&D Systems AF2419, dilution 1:500 Rabbit NKX6.1Novus biologicalsNBP1-49672, dilution 1:500 Goat NKX6.1R&D systemsAF5857, dilution 1:300 Rabbit p-JNK Cell signalling 4668, dilution 1:1000 Rabbit DVL2 Cell signalling 3216, dilution 1:1000 Mouse GAPDH Merck Biosciences CB1001, dilution 1:6000 Validation All primary antibodies were validated for their expression on undifferentiated cells and/or pancreatic human sections/islets.

Techniques: Gene Expression, Derivative Assay, Staining

Journal: Nature biotechnology

Article Title: Generation of pancreatic β cells from CD177 + anterior definitive endoderm.

doi: 10.1038/s41587-020-0492-5

Figure Lengend Snippet: Fig. 2 | Molecular profiling of CD177+, CD275+ and CXCR4+ DE subpopulations reveals distinct signatures. a, Summary of differentiation protocol toward DE/ADE followed by MACS to enrich for CD177, CD275 and CXCR4 populations. b, Principal component analysis showing that mRNA-derived transcriptome profiles are characteristic of different DE/ADE subpopulations (n = 3 biologically independent experiments). c–e, Bar graphs of selected and significantly enriched gene ontology terms in CD275+ versus CXCR4+ (c), CD177+ versus CD275+ (d) and CD177+ versus CXCR4+ (e) DE populations (n = 3 biologically independent experiments). Enrichment P values are calculated by HOMER findGO.pl based on the cumulative hypergeometric distribution. f,g, Validation of the microarray analysis by qPCR for noncanonical WNT/PCP components and ligands (f) and canonical WNT components and ligands (g). Data were normalized to 18S (ANOVA, n = 3 biologically independent experiments). Data are represented as mean ± s.e.m.; P < 0.05 and P < 0.01. Statistically nonsignificant results are not indicated in the figure. h,i, Western blot analysis (h) and quantification (i) of WNT/PCP components such as p-JNK and DVL2 in ADE subpopulations (n = 3 biologically independent experiments). GAPDH is used as a loading control. Data are represented as mean ± s.e.m. j, Immunofluorescence analysis validated the exclusive localization of β-catenin in the membrane in CD177+ ADE cells and in the cytoplasm and nucleus in CD275+ ADE and CXCR4+ DE cells (n = 3 biologically independent experiments). FOXA2 is used as a nuclear marker. Scale bars, 20 µm and 10 µm in inset. PC1/2, principal component 1/2.

Article Snippet: Materials & experimental systems n/a Involved in the study Antibodies Eukaryotic cell lines Palaeontology Animals and other organisms Human research participants Clinical data Methods n/a Involved in the study ChIP-seq Flow cytometry MRI-based neuroimaging Antibodies Antibodies used Human CXCR4-PE,Miltenyi Biotech,130-098-354, dilution 1:40; Human CXCR4-APC,Miltenyi Biotech, 120-010-802, dilution 1:40; Human CD117-APC, Miltenyi Biotech, 130-091-733, dilution 1:40; Human CD117-PE, Miltenyi Biotech, 130-091-734, dilution 1:40; FOXA2-Alexa Fluor® 488, R and D, IC2400G; dilution 1:10 SOX17-APC, R and D, IC1924A; dilution 1:10 Human CD177-APC, Miltenyi Biotech, 120-017-498; dilution 1:20 Human CD275-APC, Miltenyi Biotech, 120-012-112; dilution 1:20 PE Mouse anti-PDX1, BD PharmingenTM, 562161; dilution 1:40 4 nature research | reporting sum m ary O ctober 2018 Alexa Fluor® 647 Mouse anti-Nkx6.1, BD PharmingenTM, 563338; dilution 1:40 Alexa Fluor® 647 Mouse IgG1 κ Isotype Control, BD PharmingenTM, 563023; dilution 1:40 Rabbit FOXA2, Cell signalling, 8186; dilution 1:1000 Goat SOX17 Acris/Novus GT15094, dilution 1:1000 Goat CER1 R&D Systems AF1075, dilution 1:1000 Mouse β-catenin BD 610154, dilution 1:1000 Guinea pig INSULIN Thermo Schientific PA1-26938, dilution 1:100 Guinea pig C-Peptide Abcam ab30477, dilution 1:300 Rabbit MAFA Betalogics LP9872, dilution 1:100 Rabbit MAFA ,Novus Biologicals, NB400-137, dilution 1:100 Rabbit GLUT1 Thermo Fisher PA1-37782, dilution 1:100 Goat GATA6 R&D Systems AF1700, dilution 1:1000 Mouse SOX2 Abgent / Bio Cat AM2048, dilution 1:1000 Rabbit CDX2 Santa Cruz sc-134468, dilution 1:1000 Mouse GCG Sigma G2654-.2ML, dilution 1:300 Goat PDX1 R&D Systems AF2419, dilution 1:500 Rabbit NKX6.1Novus biologicalsNBP1-49672, dilution 1:500 Goat NKX6.1R&D systemsAF5857, dilution 1:300 Rabbit p-JNK Cell signalling 4668, dilution 1:1000 Rabbit DVL2 Cell signalling 3216, dilution 1:1000 Mouse GAPDH Merck Biosciences CB1001, dilution 1:6000 Validation All primary antibodies were validated for their expression on undifferentiated cells and/or pancreatic human sections/islets.

Techniques: Derivative Assay, Biomarker Discovery, Microarray, Western Blot, Control, Immunofluorescence, Membrane, Marker

Journal: Molecular Cancer

Article Title: Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia

doi: 10.1186/1476-4598-13-28

Figure Lengend Snippet: Hypoxia regulated microRNAs in MCF-7 cells. microRNA sequencing data generated from a hypoxia time course in MCF-7 (16, 32 and 48 h at 1% Oxygen) was analysed and the overlap between the microRNAs found significantly up- or down-regulated at each time point compared to normoxia control (adj.p-val <0.05) has been represented in Venn diagrams (A) . The levels of HIF-1α and HIF-2α were measured by immunoblotting across the hypoxia time course (H16h, H32h, H48h) and normoxia (N), with beta-actin used as a control (B) . The down-regulation of miR-4521, miR-145-3p and miR-222-5p in hypoxia was validated by qPCR (C) . Fold-changes (in linear scale) obtained for each microRNA at each time point relative to normoxia control are represented in boxplots (*significant fold-change compared to normoxia after ANOVA followed by pairwise t-test, adj.p-val ≤ 0.05). The expression of miR-145-5p and miR-222-3p was also assessed by qPCR, confirming a different pattern of expression as compared to their counterpart strands.

Article Snippet: Agilent microRNA microarrays (3 biological replicates per condition) were also used to complement and validate the sequencing data in a broad manner, as the two technologies have their own strengths and weaknesses in microRNA profiling [ ].

Techniques: Sequencing, Generated, Western Blot, Expressing

Journal: Molecular Cancer

Article Title: Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia

doi: 10.1186/1476-4598-13-28

Figure Lengend Snippet: MicroRNAs found significantly down-regulated in MCF7 cells exposed to hypoxia by analysis of microRNA-seq data

Article Snippet: Agilent microRNA microarrays (3 biological replicates per condition) were also used to complement and validate the sequencing data in a broad manner, as the two technologies have their own strengths and weaknesses in microRNA profiling [ ].

Techniques:

Journal: Molecular Cancer

Article Title: Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia

doi: 10.1186/1476-4598-13-28

Figure Lengend Snippet: MicroRNAs found significantly up-regulated in MCF7 cells exposed to hypoxia by analysis of microRNA-seq data

Article Snippet: Agilent microRNA microarrays (3 biological replicates per condition) were also used to complement and validate the sequencing data in a broad manner, as the two technologies have their own strengths and weaknesses in microRNA profiling [ ].

Techniques: Real-time Polymerase Chain Reaction

Journal: Molecular Cancer

Article Title: Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia

doi: 10.1186/1476-4598-13-28

Figure Lengend Snippet: Hypoxically induced microRNAs are transcriptionally regulated by HIF. microRNAs within 50 kb of a HIF-binding site were analysed by GSEA using the pan-genomic microRNA datasets of fold change in expression at (A) 16 hours, (B) 32 hours and (C) 48 hours. (D) Heat map showing fold change after differing periods of hypoxia for all HIF-binding microRNAs. (E & F) RNA-seq and ChIP-seq tracks showing HIF binding and transcriptional up-regulation of previously un-annotated transcripts hosting the loci MIR27A and MIR30D . Red tracks show strand-specific ribo- RNA-seq in normoxia and hypoxia. RNA-seq reads are split between ones mapping in the plus and minus strand under normoxia or hypoxia. Purple tracks show ChIP-seq using antibodies against the indicated HIF subunit.

Article Snippet: Agilent microRNA microarrays (3 biological replicates per condition) were also used to complement and validate the sequencing data in a broad manner, as the two technologies have their own strengths and weaknesses in microRNA profiling [ ].

Techniques: Binding Assay, Expressing, RNA Sequencing Assay, ChIP-sequencing

Journal: Molecular Cancer

Article Title: Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia

doi: 10.1186/1476-4598-13-28

Figure Lengend Snippet: Hypoxic regulation of microRNAs clustered to MIR27A and MIR30D . QPCR was used to assess the expression of both 5p and 3p arms of two microRNA clusters that are within 50 kb of a HIF-binding site: hsa-miR-27a, hsa-miR-23a and hsa-miR-24-2 (A) and hsa-miR-30d and hsa-miR-30b (B) . Fold-changes (in linear scale) obtained for each microRNA at each time point relative to normoxia control are represented in boxplots (*significant fold-change compared to normoxia after ANOVA followed by pairwise t-test, adj.p-val ≤ 0.05).

Article Snippet: Agilent microRNA microarrays (3 biological replicates per condition) were also used to complement and validate the sequencing data in a broad manner, as the two technologies have their own strengths and weaknesses in microRNA profiling [ ].

Techniques: Expressing, Binding Assay

Journal: Molecular Cancer

Article Title: Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia

doi: 10.1186/1476-4598-13-28

Figure Lengend Snippet: Low correlation between microRNA and corresponding host gene expression. Expression of genes hosting microRNAs was obtained from microarray data and expression of corresponding microRNAs was obtained from microRNA-seq data. The hypoxic regulation at 32 h and 48 h for both groups was then compared from two different perspectives. First, hosting genes were sorted in 3 groups at each time point: significantly down-regulated (down), not significantly regulated (unv) and significantly up-regulated (up). The fold-change distribution for each group of genes at 32 h and 48 h of hypoxia compared to normoxia is shown in boxplots (A) . For each group of genes, the fold-change distribution of corresponding microRNAs at 32 h and 48 h compared to normoxia is also shown in boxplots for comparison (B) . Second, microRNAs hosted within genes were sorted in 3 groups according to their hypoxic regulation at 32 h and 48 h: significantly down-regulated (down), not significantly regulated (unv) and significantly up-regulated (up). The fold-change distribution for each group of microRNAs at 32 h and 48 h of hypoxia compared to normoxia is shown in boxplots (C) . For each group of microRNAs, the fold-change distribution of corresponding host genes at 32 h and 48 h compared to normoxia is also shown in boxplots for comparison (D) . All fold-change distributions are shown in linear scale.

Article Snippet: Agilent microRNA microarrays (3 biological replicates per condition) were also used to complement and validate the sequencing data in a broad manner, as the two technologies have their own strengths and weaknesses in microRNA profiling [ ].

Techniques: Expressing, Microarray

Journal: Molecular Cancer

Article Title: Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia

doi: 10.1186/1476-4598-13-28

Figure Lengend Snippet: Examples of lack of correlation between microRNA and host gene expression. QPCR was used to assess the expression of two genes hosting microRNAs: FBXW7 (A) and MCM7 (B) . Primers able to anneal to different isoforms were used in order to monitor isoform-specific expression. Fold-changes (in linear scale) obtained for each transcript at each hypoxia time point relative to normoxia control are represented in boxplots (*significant fold-change compared to normoxia after ANOVA followed by pairwise t-test, adj.p-val ≤ 0.05). For FBXW7 and MCM7 , diagrams showing the different isoforms and the location of microRNAs and pairs of primers designed for detecting each isoform are included in (A) and (B) , respectively (forward and reverse primers are designed as F and R, respectively).

Article Snippet: Agilent microRNA microarrays (3 biological replicates per condition) were also used to complement and validate the sequencing data in a broad manner, as the two technologies have their own strengths and weaknesses in microRNA profiling [ ].

Techniques: Expressing

Journal: Molecular Cancer

Article Title: Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia

doi: 10.1186/1476-4598-13-28

Figure Lengend Snippet: Hypoxia regulates genes involved in microRNA processing pathway in a HIF-dependent manner. QPCR was performed to monitor the expression of genes involved in the microRNA processing pathway. Hypoxia MCF-7 time course and 2 sets of HIF-1α and HIF-2α siRNA in MCF-7 were analysed. Fold-changes (in linear scale) obtained for each gene at each time point relative to corresponding control are represented in boxplots (*significant fold-change compared to normoxia after ANOVA followed by pairwise t-test, adj.p-val ≤ 0.05; † adj.p-val ≤0.08).

Article Snippet: Agilent microRNA microarrays (3 biological replicates per condition) were also used to complement and validate the sequencing data in a broad manner, as the two technologies have their own strengths and weaknesses in microRNA profiling [ ].

Techniques: Expressing

Journal: Cell

Article Title: A white-box machine learning approach for revealing antibiotic mechanisms of action

doi: 10.1016/j.cell.2019.04.016

Figure Lengend Snippet: (A) Overall experimental design for measuring metabolite effects on antibiotic lethality. Overnight cultures of E. coli MG1655 were inoculated into MOPS minimal medium, grown to early exponential phase, and back-diluted to OD600 = 0.1. Cells were dispensed into Biolog phenotype microarray plates (PMs) 1–4 (Bochner, 2009) with different concentrations of ampicillin (AMP), ciprofloxacin (CIP) or gentamicin (GENT) added. OD600 was measured after 4 hours of incubation at 37°C and 900 rpm shaking. Antibiotic IC50s were estimated for each antibiotic-metabolite combination.

Article Snippet: Cells were dispensed into Biolog phenotype microarray plates (PMs) 1–4 ( Bochner, 2009 ) with different concentrations of ampicillin (AMP), ciprofloxacin (CIP) or gentamicin (GENT) added.

Techniques: Microarray, Incubation

Journal: Cell

Article Title: A white-box machine learning approach for revealing antibiotic mechanisms of action

doi: 10.1016/j.cell.2019.04.016

Figure Lengend Snippet: Key Resources Table

Article Snippet: Cells were dispensed into Biolog phenotype microarray plates (PMs) 1–4 ( Bochner, 2009 ) with different concentrations of ampicillin (AMP), ciprofloxacin (CIP) or gentamicin (GENT) added.

Techniques: Virus, Recombinant, Microarray, Software, Combined Bisulfite Restriction Analysis Assay