EMBO/soda-nel huggingface dataset:
Succinate induces skeletal muscle fiber remodeling via SUNCR1 Signaling Pathway (2019)
Figure 7

FIGURE 7. SUNCR1 global knockout blocks the effect of succinate on muscle fiber switch in vivo.

(A-N) Male C57BL/6J or SUNCR1 KO mice were fed with chow diet supplemented with 0 or 1% SUC for 6 weeks.

(A-G) (A-B) The O2 consumption (VO2), (C-D) RER, (E) muscle grip strength, (F) four-limb handing time, (G) low speed running time.

(H-J) The enzymes activity of (H) HK, (I) LDH, and (J) SDH in gastrocnemius.

(K-L) Immunoblots and quantification of MyHC-I, IIb, NFAT, and PGC-1α protein in gastrocnemius.

(M-N) Representative images and quantification of Laminin (green), or MyHC-I and IIb (red) immunofluorescent staining in gastrocnemius muscle (n=3). Scale bar in (M) represents 100 µm.

Data information: Results are presented as mean ± SEM (n=5-6). *P ≤ 0.05 and **P ≤ 0.01 by non-paired Student's t test.
Succinate induces skeletal muscle fiber remodeling via SUNCR1 Signaling Pathway (2019)
Figure 8

FIGURE 8. Gastrocnemius-specific SUNCR1 knockdown abolishes the effect of succinate on muscle fiber switch in vivo.

(A-J) Male C57BL/6J mice were injected with LV-shScrambled or shSUNCR1 lentivirus specifically into the gastrocnemius at 6 weeks of age. After two weeks of recovery, mice were fed with chow diet supplemented with 0 or 1% SUC for 6 weeks.

(A) Timeline of the experimental protocol.

(B) SUNCR1 protein expression in gastrocnemius from mice transfected with shSUNCR1 lentivirus or LV-shScrambled (n=3).

(C-E) (C) The running time in low speed, (D) four-limb handing time and (E) muscle grip strength of both control and gastrocnemius-specific SUNCR1 knockdown mice.

(F-H) The enzymes activity of (F) HK, (G) LDH, (H) SDH in gastrocnemius.

(I-J) Immunoblots and quantification of MyHC-I, IIb, NFAT, and PGC-1α protein in gastrocnemius (n=3). Data information: Results are presented as mean ± SEM (n=5-8). *P ≤ 0.05 by non-paired Student's t test.

EXPANDED VIEW FIGURE LEGENDS
An optimized quantitative proteomics method establishes the cell type-resolved mouse brain secretome (2020)
Figure 1

Fig 1: Workflow of the hiSPECS method and benchmarking against SPECS.

A) Graphical illustration of the hiSPECS workflow. Cells are metabolically labeled with N-azido-mannosamine (ManNAz), an azido group-bearing sugar, which is metabolized in cells and incorporated as azido-sialic acid into N- and O-linked glycans of newly synthesized glycoproteins, but not into exogenously added serum proteins.

B) Bar chart indicating protein quantification, protein localization (according to UniProt) in the secretome of primary neurons, comparing the previous SPECS (blue) to the new hiSPECS method using DDA (light green) or DIA (dark green). Proteins were counted if quantified in at least 9 of the 11 biological replicates of hiSPECS or 4 of 5 biological replicates of the previous SPECS paper (Kuhn et al., 2012). The category glycoprotein* includes UniProt annotations and proteins annotated as glycoproteins in previous papers(Fang et al., 2016, Joshi et al., 2018, Liu et al., 2017, Zielinska et al., 2010). Proteins can have multiple UniProt annotations, e.g. for APP membrane, TM, cytoplasm and nucleus, because distinct proteolytic fragments are found in different organelles, so that some proteins in categories cytoplasm and nucleus may overlap with the categories secreted and TM+GPI.

C) Venn diagram comparing the number of protein groups quantified (5/6 biological replicates) by DDA versus DIA of the same samples. Left panel: glycoprotein. Right panel: TM and GPI proteins, which are potentially shed proteins.

D) Distribution of quantified proteins with DDA and DIA (at least in 3 of 6 biological replicates). The number of quantified proteins is plotted against the log10 transformed intensity based absolute quantification (iBAQ) values with a bin size of 0.5. The iBAQ values roughly correlate with molar abundance of the proteins. Therefore, a difference of one in log10 scale represents a 10-fold abundance difference. The number of quantified proteins per bin for DDA and DIA are indicated in light and dark green, respectively. Proteins that were only quantified with DDA or DIA are colored in light and dark purple, respectively.

E) All tryptic peptides identified from TM proteins were mapped onto their protein domains. Only 0.1% of the peptides mapped to intracellular domains. Demonstrating that secretome proteins annotated as TM proteins comprise the shed ectodomains, but not the full-length forms of the proteins.

F) Comparison of SPECS and hiSPECS method with regard to cell number, volume of culture media, sample preparation time and mass spectrometer measurement time.

Data information: TM: single-pass transmembrane protein; GPI: Glycosylphosphatidylinositol-anchored membrane protein.
An optimized quantitative proteomics method establishes the cell type-resolved mouse brain secretome (2020)
Figure 4

Fig 4: Protein levels in the brain cell secretome vs. lysate proteome.

A) Bar graph of proteins specifically secreted from the indicated cell types. The solid part of the box indicates which fraction of proteins were predominantly enriched both in the secretome and the lysate of the indicated cell type, suggesting that cell type-specific secretion results from cell type-specific protein synthesis. The light part of the box shows the fraction of proteins that were specifically secreted from the indicated cell type, although this protein had similar levels in the lysate of multiple cell types, indicating cell type-specific mechanisms of secretion or shedding. Lysate protein levels were extracted from (Sharma et al., 2015).

B,C) Comparison of the hiSPECS secretome resource and lysate data by (Sharma et al., 2015). The % enrichment is indicated normalized to the average of the most abundant cell type. B) TREM2 and CD200 are jointly enriched in both secretome and lysate in microglia or neurons, respectively. In C) two examples, of proteins specifically enriched in the secretome, but not in the lysate are shown. ADIPOQ is specifically secreted from oligodendrocytes, but reveals highest expression in astrocytes. CACHD1 is specifically secreted from neurons, but high protein levels can be found in astrocytes, neurons and oligodendrocytes. The black line indicates the mean.
An optimized quantitative proteomics method establishes the cell type-resolved mouse brain secretome (2020)
Figure 7

Fig 7: The secretome of brain slices.

A) hiSPECS DDA and DIA analysis of brain slice cultures in the presence of 25% serum. The bar chart comparing the hiSPECS DDA and DIA method indicates the protein number and their localization according to UniProt identified in the secretome of brain slices. Proteins quantified in at least 5 of 6 biological replicates are considered (N=6).

B) Protein dynamic range plot of the log10 LFQ intensities of secretome proteins of brain slices in descending order. According to their intensity, proteins are grouped into quartiles and the percentage of proteins with the following UniProt keywords is visualized: membrane, secreted, cytoplasm. The percentage of proteins identified in the secretome of astrocytes, microglia, neurons or oligodendrocytes in at least 5 of 6 biological replicates is illustrated. Selected proteins specifically secreted from one cell type are indicated with the color code of the corresponding cell type. The circle of APOE indicates it as a soluble secreted protein.

C) Cell type-specifically secreted proteins according to the hiSPECS secretome resource (5-fold enriched in pairwise comparison to the other cell types or consistently detected only in one cell type; Table EV4) detected in the secretome of brain slices. CTSP are color coded according to their origin: astrocytes (orange), microglia (green), neurons (blue), oligodendrocytes (purple).

D) Volcano plot showing changes in protein levels in the secretome of primary cultured brain slices upon 6 h LPS treatment in a 24 h collection window using the hiSPECS DIA method. The negative log10 p-values (two sample t-test) of all proteins are plotted against their log2 fold changes (LPS vs control) (N=6). The grey hyperbolic curves depict a permutation based false discovery rate estimation (p = 0.05; s0 = 0.1). Significantly regulated proteins (p<0.05) are indicated with a dark blue dot. Proteins highlighted in red indicate proteins known to increase upon LPS treatment, whereas proteins labeled in blue are not upregulated in this study (Meissner et al., 2013), for details see Table EV8.

E,F) Significantly regulated proteins upon LPS treatment (p<0.05, two sample t-test) of brain slices) split according to UniProt keywords membrane, single-pass transmembrane and GPI-anchored, and secreted proteins; F) indicating cell type specificity in the hiSPECS secretome resource.

Expanded View Figure Legends
Genetic regulation of liver lipids in a mouse model of insulin resistance and hepatic steatosis (2020)
Figure 4

Figure 4. Liver Pex16 is a novel regulator of hepatic LPC.

A) Manhattan plot of genome-wide association for the levels of hepatic Pex16 transcript, where the only significant locus appears directly surrounding the genomic location (red arrow). Significant cut-offs are shown for FDR (blue) and Bonferroni (red). The peak SNP (rs27364570) is highlighted with a dark red box. Y-axis shows the -log10(pvalue) vs x-axis showing each SNP measured. P-values for GWAS associations were calculated using FaST-LMM.

B) Allelic distribution comparing GG vs TT (x-axis) for the peak SNP of the Pex16 association (rs27364570), where the abundance of each LPC species (y-axis) showed significantly different levels depending on the allele. P-values for GWAS associations were calculated using FaST-LMM. Boxplots show mean (middle line), 25-75% quantiles (colored box) and 5-95% quantiles (vertical lines)

C) Correlations between expression of hepatic Pex16 with LPC species and phenotypic traits. Box color indicates bicor value, where all relationships are positive and number in each box shows p-value for each correlation. Pvalues were calculated based on significance of regression (students test) and adjusted for multiple comparisons (FDR = 0.05)
Genetic regulation of liver lipids in a mouse model of insulin resistance and hepatic steatosis (2020)
Figure 5

Figure 5. Map2k6 regulates hepatic TAG levels and improves metabolic profile.

A) Manhattan plot of genome-wide association for TAG(48:2). Red line shows Bonferroni-corrected threshold of significance calculated based on FaST-LMM pvalues.

B) Locuszoom plots showing the focused genomic region (x-axis) plotted against the -log10 (p-value) of association for liver mRNA expression of Map2k6. P-values for GWAS associations were calculated using FaST-LMM

(C) Correlations between hepatic expression of Map2k6 and all TAGs identified in the study. Blue represents negative correlations.

D) Experimental design for validation of Map2k6 as a regulator of hepatic TAGs and phenotypic traits, which changed as a result.

E) Western blots of liver homogenate using anti-Map2k6 and anti-β-actin.

F) Comparison of total hepatic TAG between Map2k6-overexpressing mice (black bar) and control mice (empty bar).

G) Differences in total phospholipid (PC), total cholesterol (TC) and unesterified cholesterol (UC) between Map2k6-overexpressing mice (black bars) and control mice (empty bars).

H) Body fat % of both experimental cohorts prior to (week 0) or 8 weeks on a HF/HS diet.

I,J) Plasma concentration of glucose (I) and insulin (J) at the end of the 8 weeks study.

Data information: *p<0.05, **p<0.01, ***p<0.001 calculated for the significance of correlation (C) or a students t-test between groups (F-J). Data represent means ± SEM (n = 10 control mice and 7 Map2k6-overexpressing mice). Pvalues were calculated based on significance of regression (students test) and adjusted for multiple comparisons (FDR = 0.05)
Genetic regulation of liver lipids in a mouse model of insulin resistance and hepatic steatosis (2020)
Figure 6

Figure 6. Ifi203 regulates hepatic PC levels.

A) Manhattan plot of genome-wide association for expression of Ifi203 in liver. Red line shows Bonferroni-corrected threshold and blue shows an FDR =0.01 pvalue of significance calculated based on FaST-LMM pvalues.

B-D) Allelic variation plots showing the peak SNP for Ifi203 expression (rs31614030) at the CC or TT allele (x-axis) plotted against expression of Ifi203 (B), levels of hepatic PC(38:3) (C), and plasma insulin levels (D). Red line shows Bonferroni-corrected threshold and blue shows an FDR =0.01 pvalue of significance calculated based on FaST-LMM pvalues.

E-G) Correlation between the parameters listed above showing significant relationships between hepatic Ifi203 and PC(38:3) (E), hepatic Ifi203 and plasma insulin levels (F) or PC (38:3) and plasma insulin (G). Pvalues were calculated based on significance of regression (students test) and adjusted for multiple comparisons (FDR = 0.05)

H) Experimental design for validation of Ifi203 as a regulator of total hepatic PC levels on a HF/HS diet.

I-M) Mice receiving the control virus (open bars) or shIfi203 (black bars) were analyzed for liver expression of Ifi203 (I), total PC levels in liver (J), expression of Pemt (K), total liver TAG content (L), or plasma insulin levels (M). P-values calculated using a students t-test between groups. Data represent means ± SEM (n =4-5 per group).
An alternatively transcribed TAZ variant negatively regulates JAK-STAT signaling (2019)
Figure 1

Fig 1. Identification of a short TAZ isoform transcribed by an alternative promoter

YAP and/or TAZ antibodies and their target regions.

Expression of YAP/TAZ and a smaller protein (asterisk) in different cell lines, protein expression was determined by immunoblotting (IB).

The shRNA targeting TAZ, but not YAP, knocked down the expression of the smaller protein (asterisk).

Antibodies targeting C-terminus YAP/TAZ, such as TAZ (CST) and YAP/TAZ, effectively pulled down the smaller protein (asterisk, dubbed as cTAZ hereafter) in RKO cells in an immunoprecipitation (IP) assay. cTAZ was not recognized by TAZ (SA), an antibody targeting N-terminus of TAZ.

Exogenous TAZ/YAP was not processed proteolytically to cTAZ. RKO cells were transfected with the indicated plasmids expressing C-terminal HA-tagged TAZ or YAP.

UCSC Genome Browser view of TAZ isoforms. Displayed tracks include a short (cTAZ?) and the full-length (TAZ) transcript of TAZ assembled using RNA-seq data of HCT-116 cells form SRA. The short TAZ isoform was similar to transcript ENST00000472417 annotated in Ensembl database. Below: the H3K9ac, H3K27ac, H3K4me1, H3K4me2 and H3K4me3 histone-modification signal peaks across TAZ gene in HCT-116 cells (data from ENCODE database). The red arrows indicate the primers (F: forward; R: reverse) used in (G). UTR and exons are shown in green blocks.

RKO, but not HEK293A cells, expressed both full-length TAZ and cTAZ transcripts. RT PCR primers targeting different regions are shown in (F).

Alignment of TAZ and cTAZ protein sequences. cTAZ protein sequence was derived from the Sanger sequencing results of the short PCR product (RKO, F2:R1) in (G).

Knock out of cTAZ in RKO cells using CRISPR/Cas9 technology. Monoclones (#3 and #14) were selected.
An alternatively transcribed TAZ variant negatively regulates JAK-STAT signaling (2019)
Figure 2

Fig 2. cTAZ directly represses JAK-STAT signaling

Cluster analysis of RNA expression of WT, cTAZ-/-, and cTAZ-/- /GFP-cTAZ put-back RKO cells. Genes down- and up-regulated more than 2 folds (P < 0.05) in cTAZ KO cells were included in cluster analysis. Green and red indicate down- and up-regulated genes respectively.

Gene ontology (GO) analysis identified differentially regulated pathway by cTAZ.

cTAZ suppressed expression of ISGs. RNA levels of selected ISGs in WT, cTAZ-/-, cTAZ-/-/GFP-cTAZ RKO cells were quantified by qPCR. Error bars indicate SD, n =3. **P<0.01; ***P<0.001; Student's t-test.

cTAZ repressed 5×ISRE-luciferase activity induced by IFN-α. HEK293A cells were transfected with 5×ISRE-luciferase reporter along with the indicated plasmids, treated with or without IFN-α (50 ng/ml) for 12 hours. The expression of ectopic genes was determined by IB. Error bars indicate SD, n =3. ***P<0.001; one-way ANOVA test was used for statistical analysis.

Knockout of cTAZ promoted ISGs expression in the presence of IFN-α. WT and cTAZ-/- RKO cells were treated with or without of IFN-α (50 ng/ml) for indicated time, the expression of selected genes was quantified by qPCR. WT or cTAZ-/- group was normalized by basal level, respectively. Error bars indicate SD, n =3. *P<0.05; **P<0.01; Student's t-test.
An alternatively transcribed TAZ variant negatively regulates JAK-STAT signaling (2019)
Figure 3

Fig 3. cTAZ attenuates dimerization and nuclear translocation of STAT1/2

STAT1 interacted with cTAZ, and the interaction was enhanced by IFN-α. HEK293A cells were transfected with indicated plasmids, treated with or without IFN-α (50 ng/ml) for 1 hour. IP were performed using Flag antibody.

cTAZ attenuated heterodimerization between STAT1 and STAT2 induced by IFN-α. Following transfection, cells were treated with or without IFN-α (50 ng/ml) for 1 hour and subjected to IP assays using Flag antibody.

Depletion of cTAZ enhanced the interaction between STAT1 and STAT2. RKO cell lines (WT and #14) were treated with IFN-α as in (B). IP assays were performed using STAT1 antibody.

cTAZ attenuated interaction between STAT1 and importin α5 (Im-α5). Following transfection, HEK293A cells were stimulated using IFN-α as in Fig 2B. IP assays were performed using Flag antibody.

Deletion of cTAZ promoted nuclear accumulation of STAT1 upon IFN-α stimulation. RKO (WT and cTAZ-/-) cells treated with or without IFN-α (50 ng/ml) for 1 hour, fixed, and subjected to IF using STAT1 antibody (green). DNA was labeled by DAPI (blue). Scale bar, 50 μm. Quantification was performed using ImageJ software (right). N>C: nuclear; N=C: nuclear plus cytoplasmic; N<C: cytoplasmic localization.

Deletion of cTAZ promoted nuclear accumulation of STAT1 upon IFN-α stimulation. Cells were treated as in (E) and subjected to subcellular fractionation.

cTAZ defective in STAT1-binding failed to block nuclear translocation of STAT1. HEK293A stably overexpressing STAT1 were transfected with the indicated plasmids, treated with or without IFN-α (50 ng/ml) for 1 hour, fixed, and subjected to IF as in (E). Scale bar, 25 μm.
An alternatively transcribed TAZ variant negatively regulates JAK-STAT signaling (2019)
Figure 4

Fig 4. cTAZ negatively regulates cellular antiviral response

cTAZ repressed the antiviral activity of ectopic STAT1/2. HEK293A were transfected with indicated plasmids, infected with gVSV (MOI = 0.01) for 12 hours, fixed, and subjected to microscopy (Left). Viral infection and replication were marked by green fluorescence. Scale bar, 100 μm. (Right) Quantification of GFP positive cells. About 300 cells (from 3 different fields) were analyzed. Error bars indicate SD. **P<0.01; ***P<0.001; Student's t-test.

cTAZ and STAT1/2 expression levels of cells used in (A).

cTAZ effectively repressed antiviral activity of IFN-α. Transfection and infection were performed as in (A). Top: GFP intensity of cell lysates was measured by a fluorometer. Bottom: viral GFP and ectopic cTAZ protein levels were detected by IB.

Depletion of cTAZ repressed viral replication. RKO cell lines (WT and two independent cTAZ -/- clones) were infected with gVSV (MOI = 0.1) for 12 hours. Scale bar, 100 μm. The ratio of GFP positive cells were calculated as in (A). About 300 cells (from 3 different fields) were analyzed. Error bars indicate SD. ***P<0.001; Student's t-test.

Depletion of cTAZ repressed viral replication. Cells were treated as in (D), GFP intensity of cell lysates was measured. Error bars indicate SD, n = 3. **P<0.01; ***P<0.001; Student's t-test.

Depletion of cTAZ repressed viral replication. Cells were treated as in (D), the viral genomic RNA was quantified by qPCR (normalized to human GAPDH). Error bars indicate SD, n = 3. ***P<0.001; Student's t-test.

cTAZ deficiency enhanced ISGs expression. Cells were treated as in Fig 4E, the expression of IFIH1 and DDX58 were assessed by qPCR. Error bars indicate SD, n = 3. *P<0.05; **P<0.01; ***P<0.001; Student's t-test.

Overexpression of cTAZ promotes virus infection. DOX-inducible cTAZ-overexpressing RKO cell lines were pre-treated with DOX for 48 hours (1 μg/ml). gVSV infection and GFP Fluorescence intensity quantification were performed as in Fig 4D. Error bars indicate SD, n = 3. **P<0.01; ***P<0.001; Student's t-test.

Overexpression of cTAZ repressed ISGs expression. Cells were treated as in Fig 4H, the expression of IFIH1 and DDX58 were assessed by qPCR. Error bars indicate SD, n = 3. *P<0.05; **P<0.01; Student's t-test.
An alternatively transcribed TAZ variant negatively regulates JAK-STAT signaling (2019)
Figure 5

Fig 5. cTAZ expression was induced by JAK-STAT signaling

gVSV induced expression of cTAZ. RKO cells were infected with gVSV (MOI = 0, 0.001, 0.01, 0.01, 1) for 8 hours. Protein expression was determined by IB (Left) and quantified (Right). Error bars indicate SD, n = 3. ***P<0.001; two-way ANOVA test was used for statistical analysis.

IFN-α induced expression of cTAZ. RKO cells were treated with different doses of IFN-α for 8 hours. Protein expression was determined as in Fig (A). Error bars indicate SD, n = 3. ***P<0.001; two-way ANOVA test was used for statistical analysis.

IFN-α induced mRNA level of cTAZ. RKO cells were treated with different doses of IFN-α for 8 hours. RNA levels were measured by qPCR. Error bars indicate SD, n = 3. ***P<0.001; two-way ANOVA test was used for statistical analysis.

STAT1/2 synergistically activated a cTAZ promoter. HEK293A cells were transfected with cTAZ reporter with or without STAT proteins. Promoter activity was determined using luciferase assay, and protein expression was determined by IB. Error bars indicate SD, n = 3. ***P<0.001; Student's t-test.

STAT1/2 binding sites on cTAZ promoter. HEK293A were transfected with cTAZ promoters (wild type or mutants). Luciferase activity and responses to STAT1/2 expression were measured. Error bars indicate SD, n = 3. **P<0.01; Student's t-test.

STAT1 occupied cTAZ promoter in an IFN-α-sensitive manner. RKO cells were treated with or without IFN-α (50 ng/ml) for 1 hour and subjected to ChIP assays. cTAZ PCR primers were designed to target STAT1/2 binding site. ISG15 promoter was included as a positive control.

A negative feedback mechanism regulating JAK-STAT signaling involving cTAZ. Upon IFN-α stimulation, STAT1/2 are phosphorylated and undergo dimerization. STAT1/2 dimer interacts with importins (such as Im-α5), enters nucleus, and activates transcription of target genes including ISGs. The expression of cTAZ is induced by STAT1/2. Elevated cTAZ blocks the dimerization and nuclear translocation of STAT1/2, which in turn leads to repression of the JAK-STAT signaling. cTAZ represent a critical node of a negative feedback mechanism regulating the JAK-STAT signaling.

Expanded View Figure legends