EMBO/soda-nel huggingface dataset:
Loss of Nat4 and its associated histone H4 N-terminal acetylation mediates calorie restriction-induced longevity (2016)
Figure 3

Figure 3. nat4∆ mimics transcriptome effects of calorie restriction.

(A) Clustering analysis for upregulated and downregulated genes in BY4741 nat4Δ (NCR, 2% glucose) and wild-type (CR, 0.1% glucose) strains. Gene ontology was calculated by DAVID software (version 6). GO categories with enrichment scores of p < 0.05 are shown. (B) Venn diagram showing statistically significant overlap (83 genes) between upregulated genes in nat4∆ cells (138) and wild-type cells grown in CR conditions (914). Significance of overlap between the two sets is shown (p = 4.19 x10-13; calculated using hypergeometric test [phyper]). The most relevant GO categories from the overlapping genes are indicated in the table on the right. (C) Gene expression analysis of selected upregulated stress-response genes (according to results in 3A) in BY4741 wild-type and nat4∆ strains grown under NCR and CR conditions. Expression levels were normalized to TAF10, whose expression remains unchanged. Error bars, SEM of 3 independent experiments. p-values were obtained comparing results to wild-type under NCR conditions, and calculated by unpaired two-tailed Student’s t-test: * p ≤ 0.05; ** p ≤ 0.01. (D) Gene expression analysis showing fold induction levels (Log2) of selected genes comparing BY4741 wild-type and STE5p-NAT4 strains under NCR (2% glucose) and CR (0.1% glucose) conditions. Expression levels were normalized to TAF10, whose expression remains unchanged. Error bars, SEM of 3 independent experiments. p-values were calculated by unpaired two-tailed Student’s t-test: * p ≤ 0.05; ** p ≤ 0.01
Loss of Nat4 and its associated histone H4 N-terminal acetylation mediates calorie restriction-induced longevity (2016)
Figure 4

Figure 4. nat4∆-induced longevity is mediated through loss of H4 N-terminal acetylation.

(A) RLS analysis for BY4741 wild-type and nat4-E186A strains. Values in parenthesis (here and hereafter) indicate mean lifespan. Statistical significance (here and hereafter) was determined by one-way ANOVA test: *** p ≤ 0.001; **** p ≤ 0.0001. (B) Mean RLS for YSC5106 wild-type, nat4∆ and H4S1D strains. (C) Gene expression analysis of the indicated stress-induced genes in YSC5106 wild-type, nat4∆ and H4S1D strains. Expression levels were normalized to RPP0 whose expression remains unchanged. Error bars, SEM of 3 independent experiments. p-values were obtained by comparing nat4∆ and H4S1D to wild-type values and calculated by unpaired two-tailed Student’s t test: * p ≤ 0.05; ** p ≤ 0.01. (D) Gene expression analysis of the indicated stress-induced genes in BY4742 wild-type, nat4∆ and nat4∆[hNAA40] strains. Expression levels were normalized to ACT1, whose expression remains unchanged. Error bars, SEM of 3 independent experiments. Statistical significance was determined by unpaired two-tailed Student’s t test: * p ≤ 0.05 and ** p ≤ 0.01 compared to corresponding wild-type values.
Loss of Nat4 and its associated histone H4 N-terminal acetylation mediates calorie restriction-induced longevity (2016)
Figure 5

Figure 5. H4R3 is required for nat4∆-induced longevity and activation of stress-response genes.

(A) RLS analysis for YSC5106 wild-type, nat4∆, H4R3K and double mutant strains. Values in parenthesis indicate mean lifespan. Statistical significance was determined by one-way ANOVA test: **** p ≤ 0.0001. (B) Gene expression analysis of the indicated stress-induced genes in YSC5106 WT, nat4∆, H4R3K and double mutant strains. Expression levels were normalized to RPP0, whose expression remains unchanged. Error bars, SEM of 3 independent experiments. Statistical significance was determined by unpaired two-tailed Student’s t test: * p ≤ 0.05 and ** p ≤ 0.01 compared to corresponding wild-type values.
Loss of Nat4 and its associated histone H4 N-terminal acetylation mediates calorie restriction-induced longevity (2016)
Figure 6

Figure 6. PNC1 is required for lifespan extension by nat4∆.

(A) Gene expression analysis of the indicated stress-induced genes in young and old cells isolated from YSC5106 WT, nat4∆ and H4R3K nat4∆ strains. Expression levels were normalized to ACT1, whose expression remains unchanged. Error bars, SEM of 3 independent experiments. P-values were calculated by unpaired two-tailed Student’s t test: * p ≤ 0.05 compared to young wild-type; arrowhead p ≤ 0.05 compared to old wild-type. (B) RLS analysis for WT, nat4∆, pnc1∆ and double mutant strains in BY4741 genetic background. Values in parenthesis (here and hereafter) indicate mean lifespan. Statistical significance (here and hereafter) was determined by one-way ANOVA test: * p ≤ 0.05; ** p ≤ 0.01; *** p ≤ 0.001; **** p ≤ 0.0001. ns = non-significant. (C) Mean RLS in BY4741 wild-type, msn2∆ msn4∆ double and msn2∆ msn4∆ nat4∆ triple mutant strains. (D) Mean RLS in BY4741 wild-type, nat4∆, fob1∆ sir2∆ double and fob1∆ sir2∆ nat4∆ triple mutant strains. (E) ChIP analysis performed in BY4741 wild-type, nat4Δ and Pste5-NAT4 strains grown under NCR and CR conditions. Chromatin was immunoprecipitated using antibodies against N-acH4 and Histone H4, and analyzed by qRT-PCR with the indicated primers. PNC1-P (Promoter), PNC1-S (Transcriptional Start), PNC1-E (End of gene). The enrichment from the antibody was normalized to Histone H4. Error bars, SEM of 3 independent experiments. Statistical significance was determined by unpaired two-tailed Student’s t test: * p ≤ 0.05 and ** p ≤ 0.01 compared values to wild-type NCR conditions; arrowhead p ≤ 0.05 and double arrowhead p ≤ 0.01 compared values to wild-type CR conditions.
Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets (2021)
Figure 4

Figure 4. Validation of the predicted anti-SARS-CoV-2 targets with an immunofluorescence-based in vitro siRNA assay.

(A) A schematic illustration of the siRNA assay in Caco-2 cells infected with SARS-CoV-2 to validate the antiviral efficacies of the consensus predicted metabolic targets. Caco-2 cells were transfected with siRNAs for 48 h prior to infection with SARS-CoV-2 (MOI=0.1). Four replicates were performed for each target. At 48 h post-infection, cells were subjected to staining with SARS-CoV-2 nucleoprotein (N) antibody and DAPI, and then imaged to determine the percentage of infected cells after each target knockdown (Methods).

(B) Quantification of SARS-CoV-2 infection. After the siRNA knockdown of each target, viral infection was quantified as mean log2 fold-change (log2FC) of the percentage of SARS-CoV-2+ cells relative to the mean of scrambled non-targeting siRNAs ("SCRAMBLED", green dots; accordingly the mean log2FC value of scrambled non-targeting siRNAs was normalized to zero). Predicted positive targets ("TARGETING", grey dots), predicted negative targets ("NEG", blue dots) and positive controls ("POS", red dots, including ACE2 and TMPRSS2) are all shown. Wilcoxon rank-sum test P value comparing the predicted positive targets to scrambled non-targeting siRNAs is given.

(C) Quantification of cell number after each target knockdown, calculated as the mean fraction of DAPI+ cells relative to the scrambled non-targeting siRNAs (i.e. the latter was normalized to 1). Colors of dots and P value are interpreted in the same way as in (B).

(D) Representative fluorescence images from the siRNA assay showing SARS-CoV-2 infection (green channel, top row), cell number (blue channel, middle row) and merged (bottom row). Results for scrambled non-targeting siRNA as negative control (left column), knockdown of three predicted top metabolic targets (PIKFYVE, SLC16A10, and PIP5K1C, middle columns), and knockdown of positive control (ACE2, right column) are shown. Scale bar=10 μm.
Altered metabolic landscape in IDH mutant gliomas affects phospholipid, energy and oxidative stress pathways (2017)
Figure 1

Figure 1: MALDI imaging for in situ metabolic profiling of gliomas reveals aberrant phospholipid metabolism in IDH mutant glioma

A) MALDI imaging was performed on tumor-containing brain sections at a lateral resolution of 100µm and (M-H) ions were analysed in negative mode with a FTICR Mass Spectrometer (analytical range 100-1000Da). Hematoxylin-eosin (HE) staining of the same sections was performed after MALDI analysis. Patient-derived glioma xenografts (PDXs) with IDH wildtype (IDHwt), IDH mutant (IDHm), and control brain tissue (CB) were analyzed in a non-targeted and targeted approach using regions of interest (ROI) of different sizes to compare tumor (T, yellow line) and contralateral control brain (CB, blue line). The non-targeted approach was used for statistical pair-wise comparisons between samples, while the targeted approach on a selected set of metabolites allowed distribution and quantification analyses. B) Histological sections of 3 IDHwt PDXs (P3, T434, P8) and 3 IDHm PDXs ((T394, E478, T186) showing a large ROI (boxed rectangle, >500 pixels) within the tumor area applied for targeted quantification of selected metabolites. Left rectangle in P3 PDX was used as control contralateral brain (CB) for quantifications. Middle panel shows tissue distribution of D-2-hydroxyglutarate (D2HG) by MSI, which is exclusively detected in IDHm PDXs (D2HG in IDHwt tumours is below detection limit). Right panel shows tissue distribution of a key metabolite (m/z 778.51) presenting strong accumulation in IDHm lower grade gliomas (LGG) versus glioblastomas (GBM) independent of IDH status. An intensity-dependent color code indicates the relative amount of a specific compound (defined by m/z value) throughout the tissue section. C) Quantification of several high mass metabolites differentially present in IDHm PDXs (IDHwt glioblastomas (GBM) in blue, IDHm GBM in orange, IDHm lower grade gliomas (LGG) in red, contralateral control brain (CB) in grey). Box plots represent log values of metabolite intensities measured within a large ROI (>500 pixels). Many metabolites in this mass range (m/z 700-900) have been putatively assigned to phospholipids (Tables EV2-3). m/z represents the mass over charge ratio of ionized metabolites, as measured by the mass spectrometer. Except where otherwise indicated, statistical significance was calculated for IDHm (n=3) versus IDHwt (n=3) PDXs using T test. pv: p-values.
Altered metabolic landscape in IDH mutant gliomas affects phospholipid, energy and oxidative stress pathways (2017)
Figure 2

Figure 2: IDH mutant gliomas display a low energy potential

A) MALDI imaging of indicated metabolites in IDHwt PDX (P3), IDHm PDX (E478) and control brain (CB). Hex-P: hexose-phosphate; AMP, ADP, ATP: adenosine mono-, di- and triphosphate respectively. B) LC-MS quantification of indicated metabolites in 6 PDXs. Relative quantities of metabolites are expressed in log scale and normalized to tissue quantity used for extract preparation. IDHwt glioblastomas (GBM) in blue, IDHm GBM in orange, IDHm lower grade gliomas (LGG) in red, contralateral control brain (CB) in grey. Sdh7-P: sedoheptulose-7-phosphate. C) Energetic charge defined as the ratio of (ATP+1/2ADP)/(ATP+ADP+AMP) was calculated at each pixel to present its distribution throughout the tumor. (D) The energetic charge ratio was confirmed by the LC-MS data performed on separate tumor extracts (n=3/ sample/ group). Indicated statistical significant group differences are based on T test, pv: p-values.
Altered metabolic landscape in IDH mutant gliomas affects phospholipid, energy and oxidative stress pathways (2017)
Figure 3

Figure 3: In vivo metabolic flux analysis indicates a reduced glucose turnover in IDH mutant glioma

A) LC-MS quantification of steady-state level of glycolysis and TCA cycle metabolites in three IDH1wt and three IDH1m PDXs and contralateral control brain (CB) (n=3/ sample/ group). Metabolites showing statistically significant group differences between IDH1wt and IDH1m are indicated (pvalue: * <0.05). Color code as in Fig. 1-2. B) Schematic of 13C6 glucose-derived carbon flux to pyruvate and TCA metabolites, highlighting expected 13C2 and 13C3 labels (in red) in intermediate metabolites. C) In vivo flux analysis of 13C-labelled glucose injected 20 minutes prior to sacrifice in one IDH1wt PDX (P3) and one IDH1m PDX (E478) (n=3/ sample). The percentage of glucose-derived 13C label is shown in selected metabolites containing 0 to 6 13C atoms (13C0 - 13C6 as indicated by color code). Note the absence of 13C2 label of αKG and D2HG in IDHm tumours, while the label was detectable in IDHwt PDX and in contralateral brain of both tumors (lower panel). D) Quantities of 13C3 and 13C2 labeled metabolites from glucose tracer experiment in (C). D2HG in IDH1m PDX shows a detectable 13C2 signature here, but represents a minor fraction of the total cellular D2HG pool in this tumor. Hex-P: hexose phosphate, PEP: phosphoenolpyruvate, Pyr: pyruvate, Cit: citrate, Mal: malate, Asp: aspartate, Glu: glutamate, Gln: glutamine, α-KG: α-Ketoglutarate, D2HG: D2-Hydroxyglutarate. Indicated statistical significant group differences are based on T test, pv: p-values.
Altered metabolic landscape in IDH mutant gliomas affects phospholipid, energy and oxidative stress pathways (2017)
Figure 4

Figure 4: Distribution of selected amino acids in gliomas

A) MALDI imaging of key metabolites in IDHwt (P3) and IDHm (E478) glioma PDX, compared to control brain (CB) sections. B) Quantification of metabolite distribution by MSI in 6 PDX with IDH1wt and IDH1m status (n=3 / group) and in contralateral control brain (CB). No significant differences between IDH groups were detected, although significant differences are found between tumors and control brain (glutamate, apsartate). Color code as in Fig. 1, NAA: N-acetylaspartic acid; NAAG: N-acetylaspartylglutamic acid.
Altered metabolic landscape in IDH mutant gliomas affects phospholipid, energy and oxidative stress pathways (2017)
Figure 5

Figure 5 : Oxidative stress response in IDH wildtype and IDH mutant glioma

A) NADPH levels are reduced in IDHm compared to wildtype tumors, resulting in a reduced NADPH/NAD+ ratio (n=3/ sample). p-value from T test: *<0.05. NADPH, NADP: reduced, oxydized nicotinamide adenine dinucleotide phosphate, NADH, NAD: reduced, oxydized nicotinamide adenine dinucleotide. B) MALDI images for glutathione (GSH) and cystathionine on IDHwt (P3) and IDHm (E478) PDXs. C) Quantification of MSI signals for GSH and cystathionine from 6 PDXs (n=3 / group). D) LC-MS quantification of independent samples for GSH, GSSG (oxidized GSH), GSSG/GSH ratio and cystathionine from 6 PDXs (n=3/ sample / group). Statistical significance between IDH groups calculated by T test, pv: p-value. E) Schematic of GSH synthesis, cysteine supply and its degradation pathways. GSH: reduced glutathione; GSSG: oxydized glutathione; SAM: S-adenosylmethionine, SAH: S-adenosylhomocysteine, CSA: cysteine sulfinic acid. Key enzymes in red: CBS: cystathionine-beta-synthase, GCL: glutamate-cystine ligase, xCT: cysteine-glutamate antiporter.
Altered metabolic landscape in IDH mutant gliomas affects phospholipid, energy and oxidative stress pathways (2017)
Figure 6

Figure 6 : CBS is a prognostic biomarker for patients with IDH mutant 1p19q co-deleted gliomas

A) Comparative gene expression analysis of key enzymes involved in GSH and cysteine synthesis and supply in IDHwt (n=220), IDHm with 1p/19q co-deletion (n=151) or IDHm without 1p/19q co-deletion (n=226) patients based on TCGA RNA-seq data from a cohort of 597 patients. CBS: Cystathionine beta synthase, key enzyme of the transsulfuration pathway. GCLC: catalytic subunit of glutamate-cysteine ligase. SLC7A11: gene encoding xCT, the cystine-glutamate antiporter. B) Kaplan-Meier curves of CBS gene expression versus overall survival in patients with IDHwt, IDHm with or without 1p/19q co-deletion. Statistical significance for the survival analysis is shown as: pv: p-value, ns= non significant.

Extended view: Figure Legends EV1 - EV4
HACE1-dependent protein degradation
            provides cardiac protection in response to haemodynamic stress (2014)
f1

(a) HACE1
mRNA expression is markedly increased in ischaemic and dilated
cardiomyopathy (ICM and DCM) heart failure (HF) patient heart tissue
compared with non-failing hearts (NF). Expression levels were normalized to
HPRT and
GAPDH mRNAs. n=15 per group. Control, non-failing heart.
(b) Elevated Hace1 mRNA expression in sTAC mouse hearts
compared with sham controls, expression levels were normalized to
Hprt and
Gapdh mRNAs. n=6–9 per group, P=0.004
(unpaired two-tailed Student’s t-tests).
(c–j) Hace1−/−
and WT mice were subjected to sTAC or sham surgery and analysed 4 days after
the operation. (c–e) Echocardiographic measurement
of (c) LV fractional shortening (FS=(LVEDD−LVESD)/LVEDD
× 100%); (d) LV end-diastolic dimension (LVEDD) (mm) and
(e) LV end-systolic dimension (LVESD) (mm) are shown.
n=6–8 for each group. (f) Mortality rate of WT and
Hace1−/−
mice after sTAC is shown by Kaplan–Meier plots as the survival
proportion of each cohort of mice. Survival incidence in mice over the
indicated follow-up period is shown as the ratio of the number of mice
survived/total mice analysed for each group. This represents 60% (12/20) for
Hace1−/−
sTAC mice, 84% (16/19) for Hace1+/+ sTAC mice and
100% (12/12) for both Hace1−/−
and Hace1+/+ sham mice on day
4; P value as indicated (log-rank
χ2-test). (g) Heart weight/body
weight ratios (HW/BW) and (h) lung weight/body weight ratio (LW/BW)
of WT and Hace1−/−
mice 4 days after sTAC or sham surgery. n=15–21 for each
group. (i) Representative haematoxylin and eosin staining transverse
heart cross-sections showing myocyte cross-sectional area (scale bars,
20 μm). (j) Real-time RT–PCR analyses
reveal a significant increase in the expression of the atrial natriuretic
peptide gene (Nppa), a clinical biomarker for heart hypertrophy, in
Hace1−/−
sTAC heart; expression levels were normalized to Hprt and Gapdh
mRNAs. n=6–9 per group. In all panels, error bars
represent s.e.m., one-way analysis of variance were used to calculate
P-values.
HACE1-dependent protein degradation
            provides cardiac protection in response to haemodynamic stress (2014)
f2

Representative immunohistochemical staining for (a) ubiquitinated
protein (brown); (b) p62 (brown) and (c) GFP-LC3 (brown) in paraffin sections of
heart revealing increased accumulation of p62, ubiquitinated protein and
LC3 in
Hace1−/−
sTAC hearts. Hearts from three mice in each group were analysed (scale bars,
10 μm). Representative immunoblot and quantification
for (d,e) Ub-conjugated proteins, (d,f)
p62 and
(g,h) LC3 in heart extracts (n=3 per group), Gapdh were
used as a loading control. (i) Increased Ub proteasome activity in
Hace1−/−
sTAC hearts as measured by 20S proteasome activity assay
(n=4–6 per group). In all panels, error bars represent
s.e.m., P value between KO and WT sTAC as indicated (one-way analysis
of variance).
HACE1-dependent protein degradation
            provides cardiac protection in response to haemodynamic stress (2014)
f3

(a) Representative confocal microscopy images showing HACE1 (green) localizing to the
Ub+ protein aggregates (red) induced by puromycin treatment in
HA-HACE1 MEF. Arrows
indicate co-localized puncta. Scale bar, 10 μm.
(b) Representative confocal micrographs of Hace1−/− and
Hace1+/+ NCM treated with puromycin for 4 h
(puromycin),
puromycin followed by
8 h recover (puromycin+recover). Vehicle (PBS)-treated cells were
used as control. Hace1
deficiency in cardiomyocytes (Hace1−/− NCM)
blocks ubiquitinated protein aggregate degradation. Scale bars,
10 μm. (c,d) WT and Hace1−/− MEF as
well as Hace1−/− MEF stably
transfected with WT HACE1
and C876S-mutant HACE1were subjected to protein aggregates clearance assay by
pulsing with puromycin
for 4 h to induce protein aggregate formation followed by an 8-h
chase to monitor for aggregate clearance. Cells were fixed and stained for
ubiquitinated proteins to visualize aggregates. Vehicle (PBS)-treated MEFs
were used as control. (c) Representative confocal micrographs of
images used for quantification of the efficiency of aggregates clearance in
d (percentage of cells that cleared all aggregates by
8 h after puromycin removal). At least 10 images from each group
were used for the calculation, error bars represent s.e.m.,
P0.001 (one-way analysis of variance). Scale bars,
10 μm.
HACE1-dependent protein degradation
            provides cardiac protection in response to haemodynamic stress (2014)
f4

(a) Diagrams representing GFP-tagged WT HACE1 and mutant HACE1 (HACE1Δ HECT and
HACE1Δ ANK)
constructs transiently transfected into Hace1−/−
MEF for protein aggregate clearance assay. (b–d)
Representative confocal micrographs of (b) WT, (c)
ΔHECT and (d) ΔANK MEF subjected to protein
aggregate clearance assay by pulsing with puromycin for 4 h to
induce protein aggregate formation followed by an 8-h chase to monitor for
aggregate clearance. Vehicle-treated MEFs were used as control. Scale bars,
10 μm.
HACE1-dependent protein degradation
            provides cardiac protection in response to haemodynamic stress (2014)
f5

(a) Fluorescence microscopy images showing HACE1 (green) co-aggregating with
p62 (red) in the
perinuclear space on puromycin treatment (8 h) in Hace1−/−
NCM transiently expressing HACE1-GFP. p62 was visualized by immunofluorescent staining. Arrows
indicate co-localized puncta. (b) Representative confocal images
showing HACE1 (red)
localizes to LC3+ puncta (green) induced by
MG132 treatment
(8 h) in Hace1−/−GFP-Lc3Tg
NCM cells transiently expressing HACE1-RFP. Arrows indicate co-localized puncta.
(c) Primary NCMs from Hace1+/+Lc3Tg and
Hace1−/−Lc3Tg
newborn pups were treated with or without MG132 for 8 h and the
cell lysates were subjected to western blot with anti-GFP antibodies. Gapdh
was used as a loading control. (d) Fluorescence microscopy images
showing co-localization of HACE1 (green) with Lamp1 (red) on MG132 treatment (8 h) in Hace1−/−NCM
cells transiently expressing HACE1-GFP. Lamp1 was visualized by immunofluorescent staining.
Scale bar, 10 μm in all images.
HACE1-dependent protein degradation
            provides cardiac protection in response to haemodynamic stress (2014)
f6

(a,b) Primary NCMs from WT and Hace1−/−
newborn pups and (c,d) WT and Hace1−/−
MEF, as well as Hace1−/−
MEF stably transfected with WT HACE1 and C876S-mutant HACE1, were transiently transfected
with a tandem tagged mRFP-GFP-LC3 reporter (tfLC3) plasmid, followed by 8 h
treatment with MG132 or
MG132 plus
Baf in the last
4 h, and were subjected to confocal microscopy. DMSO treatment only was used in the
control group. (a,c) Representative confocal micrographs of
images used for quantification of the percentage of yellow dots in b
and d. At least 10 images from each group were used for the
calculation; error bars represent s.e.m., P-value as indicated
(one-way ANAVO). Scale bars, 10 μm. Autophagosomes show
both GFP and mRFP-LC3
signals (yellow) while autolysosomes exhibit mRFP-L3 signals only (red).