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    Thermo Fisher clariom s mouse microarray
    ( A ) Venn diagram depicting intersection of 51 DELE1-dependent DEGs common to all three MM/CM models (the DELE1 mt-ISR heart signature), identified in <t>microarray</t> data. Data from the C10 G58R; Dele1 KO dataset also appears in Appendix Fig. , Figs. and . ( B ) Heat map depicting fold change for DELE1-dependent DEGs identified in all three models (left). Those annotated as regulating transcription in Lambert et al, are separated from other genes. * Shmt2 is in both the “AA transport/biosynthesis” and the “1C metabolism” categories. Reported FDR was calculated in TAC v4.0.3 software across all genes in dataset, using the default settings, which uses a one-way ANOVA corrected with the Benjamini-Hochberg procedure for multiple procedures. ( C ) DELE1-dependent DEGs common to two of three myopathy/cardiomyopathy models (color coded as in ( A )). ( D ) Venn diagram shows overlap between DELE1 mt-ISR heart signature and previously identified ATF4 targets in mouse cells, using ATF4 ChIP-Seq from (Han et al, ). ( E ) Heat map showing significant DELE1-dependent changes in mitochondrial protein abundance in C10 G58R hearts. N = 4 mice per condition. Statistics for proteomics data (which also appear in Dataset ) were performed as described in the Methods with correction for multiple comparisons across all protein groups in the dataset. ( F ) Heat map showing significant DELE1-dependent changes in mitochondrial protein abundance in Tfam mKO hearts. N = 4 mice per condition, except for C10 S59L group2 which was N = 3 mice. Statistics for proteomics data (which also appear in Dataset ) were performed as described in the Methods with correction for multiple comparisons across all protein groups in the dataset. ( G ) Scatterplots compares RNA log 2 FC for C10 G58 vs. control (in the presence of Dele1 ) and mitochondrial protein log 2 FC for C10 G58R vs. control animals in the presence of Dele1 (left) or the absence of Dele1 (right). .
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    1) Product Images from "DELE1 maintains muscle proteostasis to promote growth and survival in mitochondrial myopathy"

    Article Title: DELE1 maintains muscle proteostasis to promote growth and survival in mitochondrial myopathy

    Journal: The EMBO Journal

    doi: 10.1038/s44318-024-00242-x

    ( A ) Venn diagram depicting intersection of 51 DELE1-dependent DEGs common to all three MM/CM models (the DELE1 mt-ISR heart signature), identified in microarray data. Data from the C10 G58R; Dele1 KO dataset also appears in Appendix Fig. , Figs. and . ( B ) Heat map depicting fold change for DELE1-dependent DEGs identified in all three models (left). Those annotated as regulating transcription in Lambert et al, are separated from other genes. * Shmt2 is in both the “AA transport/biosynthesis” and the “1C metabolism” categories. Reported FDR was calculated in TAC v4.0.3 software across all genes in dataset, using the default settings, which uses a one-way ANOVA corrected with the Benjamini-Hochberg procedure for multiple procedures. ( C ) DELE1-dependent DEGs common to two of three myopathy/cardiomyopathy models (color coded as in ( A )). ( D ) Venn diagram shows overlap between DELE1 mt-ISR heart signature and previously identified ATF4 targets in mouse cells, using ATF4 ChIP-Seq from (Han et al, ). ( E ) Heat map showing significant DELE1-dependent changes in mitochondrial protein abundance in C10 G58R hearts. N = 4 mice per condition. Statistics for proteomics data (which also appear in Dataset ) were performed as described in the Methods with correction for multiple comparisons across all protein groups in the dataset. ( F ) Heat map showing significant DELE1-dependent changes in mitochondrial protein abundance in Tfam mKO hearts. N = 4 mice per condition, except for C10 S59L group2 which was N = 3 mice. Statistics for proteomics data (which also appear in Dataset ) were performed as described in the Methods with correction for multiple comparisons across all protein groups in the dataset. ( G ) Scatterplots compares RNA log 2 FC for C10 G58 vs. control (in the presence of Dele1 ) and mitochondrial protein log 2 FC for C10 G58R vs. control animals in the presence of Dele1 (left) or the absence of Dele1 (right). .
    Figure Legend Snippet: ( A ) Venn diagram depicting intersection of 51 DELE1-dependent DEGs common to all three MM/CM models (the DELE1 mt-ISR heart signature), identified in microarray data. Data from the C10 G58R; Dele1 KO dataset also appears in Appendix Fig. , Figs. and . ( B ) Heat map depicting fold change for DELE1-dependent DEGs identified in all three models (left). Those annotated as regulating transcription in Lambert et al, are separated from other genes. * Shmt2 is in both the “AA transport/biosynthesis” and the “1C metabolism” categories. Reported FDR was calculated in TAC v4.0.3 software across all genes in dataset, using the default settings, which uses a one-way ANOVA corrected with the Benjamini-Hochberg procedure for multiple procedures. ( C ) DELE1-dependent DEGs common to two of three myopathy/cardiomyopathy models (color coded as in ( A )). ( D ) Venn diagram shows overlap between DELE1 mt-ISR heart signature and previously identified ATF4 targets in mouse cells, using ATF4 ChIP-Seq from (Han et al, ). ( E ) Heat map showing significant DELE1-dependent changes in mitochondrial protein abundance in C10 G58R hearts. N = 4 mice per condition. Statistics for proteomics data (which also appear in Dataset ) were performed as described in the Methods with correction for multiple comparisons across all protein groups in the dataset. ( F ) Heat map showing significant DELE1-dependent changes in mitochondrial protein abundance in Tfam mKO hearts. N = 4 mice per condition, except for C10 S59L group2 which was N = 3 mice. Statistics for proteomics data (which also appear in Dataset ) were performed as described in the Methods with correction for multiple comparisons across all protein groups in the dataset. ( G ) Scatterplots compares RNA log 2 FC for C10 G58 vs. control (in the presence of Dele1 ) and mitochondrial protein log 2 FC for C10 G58R vs. control animals in the presence of Dele1 (left) or the absence of Dele1 (right). .

    Techniques Used: Microarray, Software, ChIP-sequencing, Control

    ( A ) Dele1 KO and WT littermates were challenged with cold stress for 9 h and interscapular BAT was analyzed by immunoblotting for OPA1 cleavage by OMA1. OMA1 cleavage generated OPA1 isoforms are in indicated in red as c* and e*. ( B ) Volcano plot of global gene expression changes in cold stressed Dele1 KO vs. WT littermates measured by microarray; significant genes (FDR < 0.05 and |Log 2 FC| > 1) are in black. Statistics were performed as described in Methods for all microarray-based transcriptomics. N = 7 mice per group. ( C ) Heat map shows overlap among DELE1-dependent DEGS in four mitochondrial-rich tissues: heart, gastrocnemius (gastroc) skeletal muscle, and liver from C10 G58R mice, in addition to BAT from mice subjected to cold stress. BAT microarray data from same dataset that also appears in Appendix Fig. . C10 G58R heart microarray data are from the same dataset that also appears in Appendix Fig. , Fig. , and Fig. . Statistics on all microarray data (which also appear in Dataset ) were performed as described in Methods for all microarray-based transcriptomics. FDR values were corrected for multiple comparisons across all transcripts in dataset. N = 4 for all groups except for C10 G58R; Dele1+ liver, which was N = 3. ( D ) Venn diagram shows intersection of C10 G58R DELE1-dependent DEGs from three muscles (gastrocnemius, tibalis anterior, and heart), measured by RNA-Seq at P28 (data also available in Dataset – ). ( E ) Venn diagram shows intersection of skeletal and and heart muscle DELE1-dependent DEGs as in ( D ) with ATF4 target genes, from previously published ATF4 ChIP-Seq dataset (Han et al, ). ( F ) Scatterplot shows correlation between genes that increase in tibalis anterior of P28 C10 G58R mice vs. CTRL and those that decrease in abundance in tibalis anterior from 6-month-old ATF4 skeletal muscle knockout mice vs. CTRL, from a previously published dataset (Miller et al, ). ( G , H ) Individual data is shown for select DELE1-dependent genes detected from skeletal muscle and/or heart from P28 C10 G58R mice, by RNA-Seq (data for all detected genes in Dataset – ). Fgf21 was below detection limit (not detected, “nd”) in all but the C10 G58R; Dele1+ condition. Significance was first tested with a two-way ANCOVA including genotype and sex as variables. For post hoc testing) after ANCOVA (shown in Figure), the general linear hypotheses was used in conjunction with the multiple comparisons of means (“mcp”) function to test for all possible two-way comparisons via “Tukey” method. For ( G ), p -values were 1.98E−08 and 6.98E−07 (for bottom row) and 7.12E−10 and 6.62E−08 (for top row). For ( H , top graph, gastrocnemius) p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 0, 0, 2.58E−09, 1.89E−15, 0, 0, 0, 0, and 1.11E−16, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 0, 0, 1.19E−12, 2.50E−13, 0, 0, 0, 0, and 0. For ( H , middle graph, tibialis anterior) p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 4.37E−07, 0, 4.63E−06, 7.99E−09, 4.97E−11, 0, 0, 2.33E−15, 3.42E−13 and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 8.51E−08, 0, 2.24E−05, 1.37E−08, 1.24E−12, 0, 2.22E−16, 7.77E−16, and 0. For ( H , top graph, heart) p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 1.57E−10, 0, 1.42E−11, 1.63E−12, 0, 2.71E−09, 0, 0, and 0, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 6.21E−10, 1.22E−12, 1.55E−15, 3.22E−15, 1.16E−13, 0.0001011, 0, 0, 0. In all graphs, **** indicates p ≤ 0.0001, respectively, and “ns” not significant. Error bars represent SD. N ≥ 4 mice per group (genotype). ( I ) individual data is shown for select genes significantly elevated in skeletal muscles of only C10 G58R; Dele1 KO and no other genotypes relative to control. Significance was first tested with a two-way ANCOVA including genotype and sex as variables. For post hoc testing) after ANCOVA (shown in Figure), the general linear hypotheses was used in conjunction with the multiple comparisons of means (“mcp”) function to test for all possible two-way comparisons via “Tukey” method. For gastrocnemius (top graph), p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 0.7386, 0.3720, 0.8302, 0.8152, 0.9998, and 0.9999, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 0.0007080, 0.001020, 7.28E−05, 2.80E−05, 0.003794, 0.005845. For tibialis anterior (bottom graph), p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 0.9919, 0.3088, 0.9999, 0.9984, 0.2705, 0.9920, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 3.52E−05, 0.002405, 1.66E−05, 0.001349, 1.16E−07, 1.30E−08. In all graphs, **, ***, **** indicates p ≤ 0.01, 0.001, 0.0001, respectively, and “ns” not significant. Error bars represent SD. N ≥ 4 mice per group (genotype). ( J ) Heat map of 13 mouse genes that are DELE1-dependent in C10 G58R gastrocnemius and tibialis anterior model (as in D ) and have human orthologs that are upregulated by >2-fold (on average) in three previously published datasets from mitochondrial myopathy patients (Hathazi et al, ; Pirinen et al, ; Kalko et al, ). P -values were corrected for multiple comparisons across all transcripts in dataset. .
    Figure Legend Snippet: ( A ) Dele1 KO and WT littermates were challenged with cold stress for 9 h and interscapular BAT was analyzed by immunoblotting for OPA1 cleavage by OMA1. OMA1 cleavage generated OPA1 isoforms are in indicated in red as c* and e*. ( B ) Volcano plot of global gene expression changes in cold stressed Dele1 KO vs. WT littermates measured by microarray; significant genes (FDR < 0.05 and |Log 2 FC| > 1) are in black. Statistics were performed as described in Methods for all microarray-based transcriptomics. N = 7 mice per group. ( C ) Heat map shows overlap among DELE1-dependent DEGS in four mitochondrial-rich tissues: heart, gastrocnemius (gastroc) skeletal muscle, and liver from C10 G58R mice, in addition to BAT from mice subjected to cold stress. BAT microarray data from same dataset that also appears in Appendix Fig. . C10 G58R heart microarray data are from the same dataset that also appears in Appendix Fig. , Fig. , and Fig. . Statistics on all microarray data (which also appear in Dataset ) were performed as described in Methods for all microarray-based transcriptomics. FDR values were corrected for multiple comparisons across all transcripts in dataset. N = 4 for all groups except for C10 G58R; Dele1+ liver, which was N = 3. ( D ) Venn diagram shows intersection of C10 G58R DELE1-dependent DEGs from three muscles (gastrocnemius, tibalis anterior, and heart), measured by RNA-Seq at P28 (data also available in Dataset – ). ( E ) Venn diagram shows intersection of skeletal and and heart muscle DELE1-dependent DEGs as in ( D ) with ATF4 target genes, from previously published ATF4 ChIP-Seq dataset (Han et al, ). ( F ) Scatterplot shows correlation between genes that increase in tibalis anterior of P28 C10 G58R mice vs. CTRL and those that decrease in abundance in tibalis anterior from 6-month-old ATF4 skeletal muscle knockout mice vs. CTRL, from a previously published dataset (Miller et al, ). ( G , H ) Individual data is shown for select DELE1-dependent genes detected from skeletal muscle and/or heart from P28 C10 G58R mice, by RNA-Seq (data for all detected genes in Dataset – ). Fgf21 was below detection limit (not detected, “nd”) in all but the C10 G58R; Dele1+ condition. Significance was first tested with a two-way ANCOVA including genotype and sex as variables. For post hoc testing) after ANCOVA (shown in Figure), the general linear hypotheses was used in conjunction with the multiple comparisons of means (“mcp”) function to test for all possible two-way comparisons via “Tukey” method. For ( G ), p -values were 1.98E−08 and 6.98E−07 (for bottom row) and 7.12E−10 and 6.62E−08 (for top row). For ( H , top graph, gastrocnemius) p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 0, 0, 2.58E−09, 1.89E−15, 0, 0, 0, 0, and 1.11E−16, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 0, 0, 1.19E−12, 2.50E−13, 0, 0, 0, 0, and 0. For ( H , middle graph, tibialis anterior) p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 4.37E−07, 0, 4.63E−06, 7.99E−09, 4.97E−11, 0, 0, 2.33E−15, 3.42E−13 and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 8.51E−08, 0, 2.24E−05, 1.37E−08, 1.24E−12, 0, 2.22E−16, 7.77E−16, and 0. For ( H , top graph, heart) p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 1.57E−10, 0, 1.42E−11, 1.63E−12, 0, 2.71E−09, 0, 0, and 0, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 6.21E−10, 1.22E−12, 1.55E−15, 3.22E−15, 1.16E−13, 0.0001011, 0, 0, 0. In all graphs, **** indicates p ≤ 0.0001, respectively, and “ns” not significant. Error bars represent SD. N ≥ 4 mice per group (genotype). ( I ) individual data is shown for select genes significantly elevated in skeletal muscles of only C10 G58R; Dele1 KO and no other genotypes relative to control. Significance was first tested with a two-way ANCOVA including genotype and sex as variables. For post hoc testing) after ANCOVA (shown in Figure), the general linear hypotheses was used in conjunction with the multiple comparisons of means (“mcp”) function to test for all possible two-way comparisons via “Tukey” method. For gastrocnemius (top graph), p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 0.7386, 0.3720, 0.8302, 0.8152, 0.9998, and 0.9999, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 0.0007080, 0.001020, 7.28E−05, 2.80E−05, 0.003794, 0.005845. For tibialis anterior (bottom graph), p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 0.9919, 0.3088, 0.9999, 0.9984, 0.2705, 0.9920, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 3.52E−05, 0.002405, 1.66E−05, 0.001349, 1.16E−07, 1.30E−08. In all graphs, **, ***, **** indicates p ≤ 0.01, 0.001, 0.0001, respectively, and “ns” not significant. Error bars represent SD. N ≥ 4 mice per group (genotype). ( J ) Heat map of 13 mouse genes that are DELE1-dependent in C10 G58R gastrocnemius and tibialis anterior model (as in D ) and have human orthologs that are upregulated by >2-fold (on average) in three previously published datasets from mitochondrial myopathy patients (Hathazi et al, ; Pirinen et al, ; Kalko et al, ). P -values were corrected for multiple comparisons across all transcripts in dataset. .

    Techniques Used: Western Blot, Generated, Expressing, Microarray, Muscles, RNA Sequencing Assay, ChIP-sequencing, Knock-Out, Control

    Reagents and tools table
    Figure Legend Snippet: Reagents and tools table

    Techniques Used: Recombinant, Control, Sequencing, Electron Microscopy, Saline, Staining, Microarray, Software, Laser-Scanning Microscopy, High Performance Liquid Chromatography, Mass Spectrometry



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    Thermo Fisher clariom-s, mouse microarray
    ( A ) RiboTag Lyve1-Cre schematic depicting experimental protocol. ( B ) Mean Grimace Score for RiboTag mice, confirming initiation of chronic migraine model. n = 3 animals per group. Data not recorded from final injection day (Day 8). Graph shows mean ± SD. ( C ) Heatmap of differentially translated genes. Red, up with NTG; Blue, down with NTG. n = 3 animals per group from 1 cohort. ( D ) IPA analysis of differentially expressed genes from <t>microarray.</t> Top 10 pathways with more than 4 identified transcripts per pathway displayed. ( E ) Volcano plot of significant differentially genes in MLVs. Labeled genes were selected because PubMed searches resulted in over 7 papers with the topic trend of lymphatic biology. Red text, upregulated and investigated. Significance determined by 1-way ANOVA. Significant P values < 0.05 (above dashed line).
    Clariom S, Mouse Microarray, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Thermo Fisher applied clariom s mouse gene expression microarrays
    ( A ) RiboTag Lyve1-Cre schematic depicting experimental protocol. ( B ) Mean Grimace Score for RiboTag mice, confirming initiation of chronic migraine model. n = 3 animals per group. Data not recorded from final injection day (Day 8). Graph shows mean ± SD. ( C ) Heatmap of differentially translated genes. Red, up with NTG; Blue, down with NTG. n = 3 animals per group from 1 cohort. ( D ) IPA analysis of differentially expressed genes from <t>microarray.</t> Top 10 pathways with more than 4 identified transcripts per pathway displayed. ( E ) Volcano plot of significant differentially genes in MLVs. Labeled genes were selected because PubMed searches resulted in over 7 papers with the topic trend of lymphatic biology. Red text, upregulated and investigated. Significance determined by 1-way ANOVA. Significant P values < 0.05 (above dashed line).
    Applied Clariom S Mouse Gene Expression Microarrays, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Average 90 stars, based on 1 article reviews
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    Image Search Results


    ( A ) Venn diagram depicting intersection of 51 DELE1-dependent DEGs common to all three MM/CM models (the DELE1 mt-ISR heart signature), identified in microarray data. Data from the C10 G58R; Dele1 KO dataset also appears in Appendix Fig. , Figs. and . ( B ) Heat map depicting fold change for DELE1-dependent DEGs identified in all three models (left). Those annotated as regulating transcription in Lambert et al, are separated from other genes. * Shmt2 is in both the “AA transport/biosynthesis” and the “1C metabolism” categories. Reported FDR was calculated in TAC v4.0.3 software across all genes in dataset, using the default settings, which uses a one-way ANOVA corrected with the Benjamini-Hochberg procedure for multiple procedures. ( C ) DELE1-dependent DEGs common to two of three myopathy/cardiomyopathy models (color coded as in ( A )). ( D ) Venn diagram shows overlap between DELE1 mt-ISR heart signature and previously identified ATF4 targets in mouse cells, using ATF4 ChIP-Seq from (Han et al, ). ( E ) Heat map showing significant DELE1-dependent changes in mitochondrial protein abundance in C10 G58R hearts. N = 4 mice per condition. Statistics for proteomics data (which also appear in Dataset ) were performed as described in the Methods with correction for multiple comparisons across all protein groups in the dataset. ( F ) Heat map showing significant DELE1-dependent changes in mitochondrial protein abundance in Tfam mKO hearts. N = 4 mice per condition, except for C10 S59L group2 which was N = 3 mice. Statistics for proteomics data (which also appear in Dataset ) were performed as described in the Methods with correction for multiple comparisons across all protein groups in the dataset. ( G ) Scatterplots compares RNA log 2 FC for C10 G58 vs. control (in the presence of Dele1 ) and mitochondrial protein log 2 FC for C10 G58R vs. control animals in the presence of Dele1 (left) or the absence of Dele1 (right). .

    Journal: The EMBO Journal

    Article Title: DELE1 maintains muscle proteostasis to promote growth and survival in mitochondrial myopathy

    doi: 10.1038/s44318-024-00242-x

    Figure Lengend Snippet: ( A ) Venn diagram depicting intersection of 51 DELE1-dependent DEGs common to all three MM/CM models (the DELE1 mt-ISR heart signature), identified in microarray data. Data from the C10 G58R; Dele1 KO dataset also appears in Appendix Fig. , Figs. and . ( B ) Heat map depicting fold change for DELE1-dependent DEGs identified in all three models (left). Those annotated as regulating transcription in Lambert et al, are separated from other genes. * Shmt2 is in both the “AA transport/biosynthesis” and the “1C metabolism” categories. Reported FDR was calculated in TAC v4.0.3 software across all genes in dataset, using the default settings, which uses a one-way ANOVA corrected with the Benjamini-Hochberg procedure for multiple procedures. ( C ) DELE1-dependent DEGs common to two of three myopathy/cardiomyopathy models (color coded as in ( A )). ( D ) Venn diagram shows overlap between DELE1 mt-ISR heart signature and previously identified ATF4 targets in mouse cells, using ATF4 ChIP-Seq from (Han et al, ). ( E ) Heat map showing significant DELE1-dependent changes in mitochondrial protein abundance in C10 G58R hearts. N = 4 mice per condition. Statistics for proteomics data (which also appear in Dataset ) were performed as described in the Methods with correction for multiple comparisons across all protein groups in the dataset. ( F ) Heat map showing significant DELE1-dependent changes in mitochondrial protein abundance in Tfam mKO hearts. N = 4 mice per condition, except for C10 S59L group2 which was N = 3 mice. Statistics for proteomics data (which also appear in Dataset ) were performed as described in the Methods with correction for multiple comparisons across all protein groups in the dataset. ( G ) Scatterplots compares RNA log 2 FC for C10 G58 vs. control (in the presence of Dele1 ) and mitochondrial protein log 2 FC for C10 G58R vs. control animals in the presence of Dele1 (left) or the absence of Dele1 (right). .

    Article Snippet: RNA expression was measured using the Clariom S Mouse microarray (Affymetrix) by the NHGRI Microarray Core.

    Techniques: Microarray, Software, ChIP-sequencing, Control

    ( A ) Dele1 KO and WT littermates were challenged with cold stress for 9 h and interscapular BAT was analyzed by immunoblotting for OPA1 cleavage by OMA1. OMA1 cleavage generated OPA1 isoforms are in indicated in red as c* and e*. ( B ) Volcano plot of global gene expression changes in cold stressed Dele1 KO vs. WT littermates measured by microarray; significant genes (FDR < 0.05 and |Log 2 FC| > 1) are in black. Statistics were performed as described in Methods for all microarray-based transcriptomics. N = 7 mice per group. ( C ) Heat map shows overlap among DELE1-dependent DEGS in four mitochondrial-rich tissues: heart, gastrocnemius (gastroc) skeletal muscle, and liver from C10 G58R mice, in addition to BAT from mice subjected to cold stress. BAT microarray data from same dataset that also appears in Appendix Fig. . C10 G58R heart microarray data are from the same dataset that also appears in Appendix Fig. , Fig. , and Fig. . Statistics on all microarray data (which also appear in Dataset ) were performed as described in Methods for all microarray-based transcriptomics. FDR values were corrected for multiple comparisons across all transcripts in dataset. N = 4 for all groups except for C10 G58R; Dele1+ liver, which was N = 3. ( D ) Venn diagram shows intersection of C10 G58R DELE1-dependent DEGs from three muscles (gastrocnemius, tibalis anterior, and heart), measured by RNA-Seq at P28 (data also available in Dataset – ). ( E ) Venn diagram shows intersection of skeletal and and heart muscle DELE1-dependent DEGs as in ( D ) with ATF4 target genes, from previously published ATF4 ChIP-Seq dataset (Han et al, ). ( F ) Scatterplot shows correlation between genes that increase in tibalis anterior of P28 C10 G58R mice vs. CTRL and those that decrease in abundance in tibalis anterior from 6-month-old ATF4 skeletal muscle knockout mice vs. CTRL, from a previously published dataset (Miller et al, ). ( G , H ) Individual data is shown for select DELE1-dependent genes detected from skeletal muscle and/or heart from P28 C10 G58R mice, by RNA-Seq (data for all detected genes in Dataset – ). Fgf21 was below detection limit (not detected, “nd”) in all but the C10 G58R; Dele1+ condition. Significance was first tested with a two-way ANCOVA including genotype and sex as variables. For post hoc testing) after ANCOVA (shown in Figure), the general linear hypotheses was used in conjunction with the multiple comparisons of means (“mcp”) function to test for all possible two-way comparisons via “Tukey” method. For ( G ), p -values were 1.98E−08 and 6.98E−07 (for bottom row) and 7.12E−10 and 6.62E−08 (for top row). For ( H , top graph, gastrocnemius) p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 0, 0, 2.58E−09, 1.89E−15, 0, 0, 0, 0, and 1.11E−16, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 0, 0, 1.19E−12, 2.50E−13, 0, 0, 0, 0, and 0. For ( H , middle graph, tibialis anterior) p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 4.37E−07, 0, 4.63E−06, 7.99E−09, 4.97E−11, 0, 0, 2.33E−15, 3.42E−13 and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 8.51E−08, 0, 2.24E−05, 1.37E−08, 1.24E−12, 0, 2.22E−16, 7.77E−16, and 0. For ( H , top graph, heart) p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 1.57E−10, 0, 1.42E−11, 1.63E−12, 0, 2.71E−09, 0, 0, and 0, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 6.21E−10, 1.22E−12, 1.55E−15, 3.22E−15, 1.16E−13, 0.0001011, 0, 0, 0. In all graphs, **** indicates p ≤ 0.0001, respectively, and “ns” not significant. Error bars represent SD. N ≥ 4 mice per group (genotype). ( I ) individual data is shown for select genes significantly elevated in skeletal muscles of only C10 G58R; Dele1 KO and no other genotypes relative to control. Significance was first tested with a two-way ANCOVA including genotype and sex as variables. For post hoc testing) after ANCOVA (shown in Figure), the general linear hypotheses was used in conjunction with the multiple comparisons of means (“mcp”) function to test for all possible two-way comparisons via “Tukey” method. For gastrocnemius (top graph), p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 0.7386, 0.3720, 0.8302, 0.8152, 0.9998, and 0.9999, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 0.0007080, 0.001020, 7.28E−05, 2.80E−05, 0.003794, 0.005845. For tibialis anterior (bottom graph), p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 0.9919, 0.3088, 0.9999, 0.9984, 0.2705, 0.9920, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 3.52E−05, 0.002405, 1.66E−05, 0.001349, 1.16E−07, 1.30E−08. In all graphs, **, ***, **** indicates p ≤ 0.01, 0.001, 0.0001, respectively, and “ns” not significant. Error bars represent SD. N ≥ 4 mice per group (genotype). ( J ) Heat map of 13 mouse genes that are DELE1-dependent in C10 G58R gastrocnemius and tibialis anterior model (as in D ) and have human orthologs that are upregulated by >2-fold (on average) in three previously published datasets from mitochondrial myopathy patients (Hathazi et al, ; Pirinen et al, ; Kalko et al, ). P -values were corrected for multiple comparisons across all transcripts in dataset. .

    Journal: The EMBO Journal

    Article Title: DELE1 maintains muscle proteostasis to promote growth and survival in mitochondrial myopathy

    doi: 10.1038/s44318-024-00242-x

    Figure Lengend Snippet: ( A ) Dele1 KO and WT littermates were challenged with cold stress for 9 h and interscapular BAT was analyzed by immunoblotting for OPA1 cleavage by OMA1. OMA1 cleavage generated OPA1 isoforms are in indicated in red as c* and e*. ( B ) Volcano plot of global gene expression changes in cold stressed Dele1 KO vs. WT littermates measured by microarray; significant genes (FDR < 0.05 and |Log 2 FC| > 1) are in black. Statistics were performed as described in Methods for all microarray-based transcriptomics. N = 7 mice per group. ( C ) Heat map shows overlap among DELE1-dependent DEGS in four mitochondrial-rich tissues: heart, gastrocnemius (gastroc) skeletal muscle, and liver from C10 G58R mice, in addition to BAT from mice subjected to cold stress. BAT microarray data from same dataset that also appears in Appendix Fig. . C10 G58R heart microarray data are from the same dataset that also appears in Appendix Fig. , Fig. , and Fig. . Statistics on all microarray data (which also appear in Dataset ) were performed as described in Methods for all microarray-based transcriptomics. FDR values were corrected for multiple comparisons across all transcripts in dataset. N = 4 for all groups except for C10 G58R; Dele1+ liver, which was N = 3. ( D ) Venn diagram shows intersection of C10 G58R DELE1-dependent DEGs from three muscles (gastrocnemius, tibalis anterior, and heart), measured by RNA-Seq at P28 (data also available in Dataset – ). ( E ) Venn diagram shows intersection of skeletal and and heart muscle DELE1-dependent DEGs as in ( D ) with ATF4 target genes, from previously published ATF4 ChIP-Seq dataset (Han et al, ). ( F ) Scatterplot shows correlation between genes that increase in tibalis anterior of P28 C10 G58R mice vs. CTRL and those that decrease in abundance in tibalis anterior from 6-month-old ATF4 skeletal muscle knockout mice vs. CTRL, from a previously published dataset (Miller et al, ). ( G , H ) Individual data is shown for select DELE1-dependent genes detected from skeletal muscle and/or heart from P28 C10 G58R mice, by RNA-Seq (data for all detected genes in Dataset – ). Fgf21 was below detection limit (not detected, “nd”) in all but the C10 G58R; Dele1+ condition. Significance was first tested with a two-way ANCOVA including genotype and sex as variables. For post hoc testing) after ANCOVA (shown in Figure), the general linear hypotheses was used in conjunction with the multiple comparisons of means (“mcp”) function to test for all possible two-way comparisons via “Tukey” method. For ( G ), p -values were 1.98E−08 and 6.98E−07 (for bottom row) and 7.12E−10 and 6.62E−08 (for top row). For ( H , top graph, gastrocnemius) p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 0, 0, 2.58E−09, 1.89E−15, 0, 0, 0, 0, and 1.11E−16, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 0, 0, 1.19E−12, 2.50E−13, 0, 0, 0, 0, and 0. For ( H , middle graph, tibialis anterior) p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 4.37E−07, 0, 4.63E−06, 7.99E−09, 4.97E−11, 0, 0, 2.33E−15, 3.42E−13 and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 8.51E−08, 0, 2.24E−05, 1.37E−08, 1.24E−12, 0, 2.22E−16, 7.77E−16, and 0. For ( H , top graph, heart) p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 1.57E−10, 0, 1.42E−11, 1.63E−12, 0, 2.71E−09, 0, 0, and 0, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 6.21E−10, 1.22E−12, 1.55E−15, 3.22E−15, 1.16E−13, 0.0001011, 0, 0, 0. In all graphs, **** indicates p ≤ 0.0001, respectively, and “ns” not significant. Error bars represent SD. N ≥ 4 mice per group (genotype). ( I ) individual data is shown for select genes significantly elevated in skeletal muscles of only C10 G58R; Dele1 KO and no other genotypes relative to control. Significance was first tested with a two-way ANCOVA including genotype and sex as variables. For post hoc testing) after ANCOVA (shown in Figure), the general linear hypotheses was used in conjunction with the multiple comparisons of means (“mcp”) function to test for all possible two-way comparisons via “Tukey” method. For gastrocnemius (top graph), p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 0.7386, 0.3720, 0.8302, 0.8152, 0.9998, and 0.9999, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 0.0007080, 0.001020, 7.28E−05, 2.80E−05, 0.003794, 0.005845. For tibialis anterior (bottom graph), p -values for C10 WT; Dele1+ vs. C10 G58R; Dele1+ (for genes left to right) were 0.9919, 0.3088, 0.9999, 0.9984, 0.2705, 0.9920, and for C10 G58R; Dele1+ vs. C10 G58R; Dele1 KO (for genes left to right) were 3.52E−05, 0.002405, 1.66E−05, 0.001349, 1.16E−07, 1.30E−08. In all graphs, **, ***, **** indicates p ≤ 0.01, 0.001, 0.0001, respectively, and “ns” not significant. Error bars represent SD. N ≥ 4 mice per group (genotype). ( J ) Heat map of 13 mouse genes that are DELE1-dependent in C10 G58R gastrocnemius and tibialis anterior model (as in D ) and have human orthologs that are upregulated by >2-fold (on average) in three previously published datasets from mitochondrial myopathy patients (Hathazi et al, ; Pirinen et al, ; Kalko et al, ). P -values were corrected for multiple comparisons across all transcripts in dataset. .

    Article Snippet: RNA expression was measured using the Clariom S Mouse microarray (Affymetrix) by the NHGRI Microarray Core.

    Techniques: Western Blot, Generated, Expressing, Microarray, Muscles, RNA Sequencing Assay, ChIP-sequencing, Knock-Out, Control

    Reagents and tools table

    Journal: The EMBO Journal

    Article Title: DELE1 maintains muscle proteostasis to promote growth and survival in mitochondrial myopathy

    doi: 10.1038/s44318-024-00242-x

    Figure Lengend Snippet: Reagents and tools table

    Article Snippet: RNA expression was measured using the Clariom S Mouse microarray (Affymetrix) by the NHGRI Microarray Core.

    Techniques: Recombinant, Control, Sequencing, Electron Microscopy, Saline, Staining, Microarray, Software, Laser-Scanning Microscopy, High Performance Liquid Chromatography, Mass Spectrometry

    Time-dependent gene expression in persistent infection of hRSV versus niMϕ. (A) Heatmap representation of differentially expressed genes in piMϕ versus niMϕ after 6 h of in vitro culture. (B) Number of altered genes in piMϕ at 6 h of in vitro culture. (C) Heatmap representation of differentially expressed genes in piMϕ versus niMϕ after 24 h of in vitro culture. (D) Number of altered genes in piMϕ at 24 h of in vitro culture. (E) Venn diagram of genes expressed only at 6 or 24 h and at both timepoints. Top-up-regulated genes are shown in red, while top-down-regulated genes are shown in blue. Common genes expressed at both timepoints are shown in black. (F) Microarray expression data validation by qRT-PCR at 6 and 24 h. piMϕ , persistently infected macrophages with hRSV; niMϕ , non-infected macrophages; hRSV, human respiratory syncytial virus. p -values were calculated using the Student t -test between microarrays and rt-PCR data for each cytokine: *** = ≤0.001 and **** = ≤0.0001.

    Journal: Frontiers in Microbiology

    Article Title: Transcriptome profiling of macrophages persistently infected with human respiratory syncytial virus and effect of recombinant Taenia solium calreticulin on immune-related genes

    doi: 10.3389/fmicb.2024.1402589

    Figure Lengend Snippet: Time-dependent gene expression in persistent infection of hRSV versus niMϕ. (A) Heatmap representation of differentially expressed genes in piMϕ versus niMϕ after 6 h of in vitro culture. (B) Number of altered genes in piMϕ at 6 h of in vitro culture. (C) Heatmap representation of differentially expressed genes in piMϕ versus niMϕ after 24 h of in vitro culture. (D) Number of altered genes in piMϕ at 24 h of in vitro culture. (E) Venn diagram of genes expressed only at 6 or 24 h and at both timepoints. Top-up-regulated genes are shown in red, while top-down-regulated genes are shown in blue. Common genes expressed at both timepoints are shown in black. (F) Microarray expression data validation by qRT-PCR at 6 and 24 h. piMϕ , persistently infected macrophages with hRSV; niMϕ , non-infected macrophages; hRSV, human respiratory syncytial virus. p -values were calculated using the Student t -test between microarrays and rt-PCR data for each cytokine: *** = ≤0.001 and **** = ≤0.0001.

    Article Snippet: The resulting cDNA was hybridized to GeneChip mouse Clariom S microarrays (Thermo Fisher, Waltham, MA, United States), which analyze gene-level expression of >20,000 well-annotated mouse genes.

    Techniques: Gene Expression, Infection, In Vitro, Microarray, Expressing, Biomarker Discovery, Quantitative RT-PCR, Virus, Reverse Transcription Polymerase Chain Reaction

    Time-dependent gene expression in niMϕ treated with 5 μg of recombinant T. solium calreticulin (rTsCRT + ). (A) Heatmap representation of differentially expressed genes in niMϕ after rTsCRT treatment for 6 h. (B) Number of altered genes in niMϕ after rTsCRT treatment for 6 h. (C) Heatmap representation of differentially expressed genes in niMϕ after rTsCRT treatment for 24 h. (D) Number of altered genes in niMϕ after rTsCRT treatment for 24 h. (E) Venn diagram of the genes expressed only at 6 or 24 h and at both timepoints. Top-up-regulated genes are shown in red, while top-down-regulated genes are shown in blue. Common genes expressed at both timepoints are shown in black. (F) Microarray expression data validation by qRT-PCR at 6 and 24 h. (G) Temporary gene expression of niMϕ treated with rTsCRT. niMϕ , non-infected macrophages. p -values were calculated using the Student t -test between microarrays and rt-PCR data for each cytokine: * = <0.05, ** = <0.01, and *** = ≤0.001.

    Journal: Frontiers in Microbiology

    Article Title: Transcriptome profiling of macrophages persistently infected with human respiratory syncytial virus and effect of recombinant Taenia solium calreticulin on immune-related genes

    doi: 10.3389/fmicb.2024.1402589

    Figure Lengend Snippet: Time-dependent gene expression in niMϕ treated with 5 μg of recombinant T. solium calreticulin (rTsCRT + ). (A) Heatmap representation of differentially expressed genes in niMϕ after rTsCRT treatment for 6 h. (B) Number of altered genes in niMϕ after rTsCRT treatment for 6 h. (C) Heatmap representation of differentially expressed genes in niMϕ after rTsCRT treatment for 24 h. (D) Number of altered genes in niMϕ after rTsCRT treatment for 24 h. (E) Venn diagram of the genes expressed only at 6 or 24 h and at both timepoints. Top-up-regulated genes are shown in red, while top-down-regulated genes are shown in blue. Common genes expressed at both timepoints are shown in black. (F) Microarray expression data validation by qRT-PCR at 6 and 24 h. (G) Temporary gene expression of niMϕ treated with rTsCRT. niMϕ , non-infected macrophages. p -values were calculated using the Student t -test between microarrays and rt-PCR data for each cytokine: * = <0.05, ** = <0.01, and *** = ≤0.001.

    Article Snippet: The resulting cDNA was hybridized to GeneChip mouse Clariom S microarrays (Thermo Fisher, Waltham, MA, United States), which analyze gene-level expression of >20,000 well-annotated mouse genes.

    Techniques: Gene Expression, Recombinant, Microarray, Expressing, Biomarker Discovery, Quantitative RT-PCR, Infection, Reverse Transcription Polymerase Chain Reaction

    Time-dependent gene expression in piMϕ treated with 5 μg of recombinant T. solium calreticulin (rTsCRT + ). (A) Heatmap representation of differentially expressed genes in piMϕ after rTsCRT treatment for 6 h. (B) Number of altered genes in piMϕ after rTsCRT treatment for 6 h. (C) Heatmap representation of differentially expressed genes in piMϕ after rTsCRT treatment for 24 h. (D) Number of altered genes in piMϕ after rTsCRT treatment for 24 h. (E) Venn diagram of the genes expressed only at 6 or 24 h and at both timepoints. Top up-regulated genes are shown in red, while top down-regulated genes are in shown blue. Common genes expressed at both times are in black. (F) Microarray expression data validation by qRT-PCR at 6 and 24 h (G) Temporary gene expression of piMϕ treated with rTsCRT. piMϕ , persistently infected macrophages with hRSV; hRSV, human respiratory syncytial virus. p -values were calculated using the Student t -test between microarrays and rt-PCR data from each cytokine: * = <0.05, ** = <0.01, and *** = ≤0.001.

    Journal: Frontiers in Microbiology

    Article Title: Transcriptome profiling of macrophages persistently infected with human respiratory syncytial virus and effect of recombinant Taenia solium calreticulin on immune-related genes

    doi: 10.3389/fmicb.2024.1402589

    Figure Lengend Snippet: Time-dependent gene expression in piMϕ treated with 5 μg of recombinant T. solium calreticulin (rTsCRT + ). (A) Heatmap representation of differentially expressed genes in piMϕ after rTsCRT treatment for 6 h. (B) Number of altered genes in piMϕ after rTsCRT treatment for 6 h. (C) Heatmap representation of differentially expressed genes in piMϕ after rTsCRT treatment for 24 h. (D) Number of altered genes in piMϕ after rTsCRT treatment for 24 h. (E) Venn diagram of the genes expressed only at 6 or 24 h and at both timepoints. Top up-regulated genes are shown in red, while top down-regulated genes are in shown blue. Common genes expressed at both times are in black. (F) Microarray expression data validation by qRT-PCR at 6 and 24 h (G) Temporary gene expression of piMϕ treated with rTsCRT. piMϕ , persistently infected macrophages with hRSV; hRSV, human respiratory syncytial virus. p -values were calculated using the Student t -test between microarrays and rt-PCR data from each cytokine: * = <0.05, ** = <0.01, and *** = ≤0.001.

    Article Snippet: The resulting cDNA was hybridized to GeneChip mouse Clariom S microarrays (Thermo Fisher, Waltham, MA, United States), which analyze gene-level expression of >20,000 well-annotated mouse genes.

    Techniques: Gene Expression, Recombinant, Microarray, Expressing, Biomarker Discovery, Quantitative RT-PCR, Infection, Virus, Reverse Transcription Polymerase Chain Reaction

    ( A ) RiboTag Lyve1-Cre schematic depicting experimental protocol. ( B ) Mean Grimace Score for RiboTag mice, confirming initiation of chronic migraine model. n = 3 animals per group. Data not recorded from final injection day (Day 8). Graph shows mean ± SD. ( C ) Heatmap of differentially translated genes. Red, up with NTG; Blue, down with NTG. n = 3 animals per group from 1 cohort. ( D ) IPA analysis of differentially expressed genes from microarray. Top 10 pathways with more than 4 identified transcripts per pathway displayed. ( E ) Volcano plot of significant differentially genes in MLVs. Labeled genes were selected because PubMed searches resulted in over 7 papers with the topic trend of lymphatic biology. Red text, upregulated and investigated. Significance determined by 1-way ANOVA. Significant P values < 0.05 (above dashed line).

    Journal: The Journal of Clinical Investigation

    Article Title: Meningeal lymphatic CGRP signaling governs pain via cerebrospinal fluid efflux and neuroinflammation in migraine models

    doi: 10.1172/JCI175616

    Figure Lengend Snippet: ( A ) RiboTag Lyve1-Cre schematic depicting experimental protocol. ( B ) Mean Grimace Score for RiboTag mice, confirming initiation of chronic migraine model. n = 3 animals per group. Data not recorded from final injection day (Day 8). Graph shows mean ± SD. ( C ) Heatmap of differentially translated genes. Red, up with NTG; Blue, down with NTG. n = 3 animals per group from 1 cohort. ( D ) IPA analysis of differentially expressed genes from microarray. Top 10 pathways with more than 4 identified transcripts per pathway displayed. ( E ) Volcano plot of significant differentially genes in MLVs. Labeled genes were selected because PubMed searches resulted in over 7 papers with the topic trend of lymphatic biology. Red text, upregulated and investigated. Significance determined by 1-way ANOVA. Significant P values < 0.05 (above dashed line).

    Article Snippet: Clariom S Pico microarray targeting mouse (902932, Thermo Fisher Scientific) was used in collaboration with the UNC Functional Genomics Core to measure expression changes.

    Techniques: Injection, Microarray, Labeling