EMBO/soda-nel huggingface dataset:
PICALM modulates autophagy activity and tau accumulation (2014)
f8

(ai) Western blot analysis of tubulin, LC3-I and LC3-II in zebrafish
larvae where ATG7 was
downregulated, as indicated. (ii) Western blot analysis of CALM-HA, actin and LC3-II in
zebrafish larvae where CALM-HA was expressed, as indicated. The larvae were
treated with ammonium
chloride (NH4Cl), as indicated. (SE, short
exposure; LE, longer exposure). Quantification of LC3-II/actin ratio is
shown. Data are representative of three independent experiments and shown as
mean ±s.d. (*P0.05; two-tailed t-test).
(b) Modulation of autophagy alters Dendra-tau clearance dynamics. The
fluorescence intensity of each individual cell was quantified at each
timepoint (n≥ 31 cells, ≥9 larvae per treatment
group) and mean cell intensity values for each drug treatment at each
timepoint were calculated. Images were taken immediately after
photoconversion and at 24, 30 and 48 h intervals thereafter.
Rapamycin treatment
significantly increased the rate of Dendra-tau clearance. Ammonium chloride (NH4Cl) treatment
significantly decreases the rate of Dendra-tau clearance
(**P0.01, ***P0.001, one-way analysis of
variance (ANOVA)). Error bars are ±s.e.m. (c)
Dendra-tau clearance
in the presence of CALM:
representative images of larvae with mosaic expression of
Dendra-tau and
full-length CALM taken
immediately after photoconversion and at 6, 24, 30, 48 and 54 h
after conversion. The fluorescence intensity of individual cells was
quantified and mean fluorescent intensity of cells co-expressing
Dendra-tau and either
full-length CALM or
Δ–ANTH CALM (CALM-ANTH-HA) constructs (n≥ 100
cells, ≥9 larvae per treatment group) at each time point was
calculated. (i) Expression of full-length CALM significantly delayed the
clearance of Dendra-tau
at all time points compared with Δ–ANTH CALM (***P0.001,
one-way ANOVA). One graph, representative of three independent experiments,
is presented. (CALM-ANTH-HA: 132 cells, 20 fishes; CALM-HA: 18 cells, 8 fishes).
Another two experiments are shown in Supplementary Fig. S5C. Error bars are mean ±s.d. (ii)
Treatment with ammonium
chloride alters the dynamics of Dendra-tau clearance. Expression of
full-length CALM
significantly delayed the clearance of Dendra-tau at all time points compared
with Δ–ANTH CALM, as observed in i (P0.001, one-way
ANOVA). However, treatment of Δ–ANTH CALM injected larvae with
ammonium chloride
slows the Dendra-tau
clearance by 70% to a level comparable to that observed in larvae injected
with full-length CALM.
Ammonium chloride
treatment of larvae injected with full-length CALM results in a modest (22%)
decrease in Dendra-tau
clearance, suggesting that CALM overexpression and ammonium chloride treatment have a
cumulative effect (n≥25 cells, n≥9
larvae per treatment group). Error bars are mean ±s.d. Note that i
and ii are distinct experiments.
PICALM modulates autophagy activity and tau accumulation (2014)
f9

(a) rho::GFP-tau
fishes were incubated from 3 to 9 d.p.f. in either dimethyl sulphoxide (DMSO) or rapamycin (i) or from 3 to 7 d.p.f
in EM alone or 10 mM ammonium
chloride or 100 nM Wortmannin (ii). Images through the
central retina at 9 d.p.f. (top panel; (i)) reveal rod degeneration (arrow)
throughout the retina in control (DMSO-treated) larvae, whereas rod photoreceptors are
present throughout the retina, particularly in the central region following
treatment with rapamycin
(arrow). Images taken through the central retina at 7 d.p.f. (bottom panel;
(ii)) show normal photoreceptors in the marginal zones (arrows) and only
limited numbers in the central region. NH4Cl exacerbates
degeneration—photoreceptors are absent from the central retina
and reduced/absent from marginal zones (arrows). Sections were stained with
anti-rhodopsin (1D1) antibody. GFP labels whole rod photoreceptors, whereas
rhodopsin is present in the rod outer segment. GFP co-localizes with the red
rhodopsin label in all experimental conditions. Scale bars,
50 μm. Quantification of rod photoreceptor degeneration
(n=10 larvae per group; ***P0.001;
###P0.001, two-tailed unpaired t-test). Error bars are
mean ±s.d. (b) Full-length CALM electroporation into rho::GFP
larvae did not cause degeneration., while full-length CALM electroporation into
rho::GFP-tau larvae
exacerbated photoreceptor degeneration. Central retina sections in the
region of the optic nerve head are presented. Scale bars,
50 μm. Data represent the ratio (in %) of the intensity
of the GFP signal between CALM-HA electroporated eye versus control eye for five
individuals per transgenic line. ***P0.05; two-tailed
t-test. Error bars are mean ±s.d. (c)
NH4Cl
treatment of rho::GFP-tau
immediately after unilateral CALM electroporation caused photoreceptor degenerationon
the control (non-electroporated) side but did not alter the degeneration
caused by CALM
electroporation. Rapamycin treatment of rho::GFP-tau immediately after unilateral
CALM electroporation
rescued photoreceptors on the control (non-electroporated) side but not on
the CALM-electroporated
side. To demonstrate that loss of GFP corresponds to loss of photoreceptors,
sections were stained with anti-rhodopsin (1D1) antibody. Wilcoxon signed
rank test was used to compare the left eye versus the right eye of the same
fish; Mann–Whitney test was used to compare drug treatment in the
right eye of different fishes. *P0.05. Scale bars,
50 μm. Error bars are mean ±s.e.m.
PICALM modulates autophagy activity and tau accumulation (2014)
f10

(a) Histological section to demonstrate the individual cell layers of
the zebrafish retina. The photoreceptor layer (PR, comprising rod and cone
photoreceptors) lies immediately adjacent to the retinal pigment epithelium
(RPE) at the outermost surface of the eye. Thioflavin-S labelling of retinal
sections was used to identify neurofibrillary tangles in the photoreceptor
layer (marked with yellow dotted lines). No labelling was observed in the
retina of rho::GFP at 8 d.p.f., whereas distinct thioflavin-S-positive
tangles (arrows) were observed in the photoreceptor layer of
rho::GFP-tau fish.
Note, the RPE is highly autofluorescent due to the presence of silver
pigment. High power regions are shown in the top right of each panel.
(b) Unilateral electroporation of CALM into the retina of
rho::GFP-tau
zebrafish resulted in a marked increase in thioflavin-S positive tangles in
the electroporated retina in the photoreceptor layer (PR) compared with the
control side. Top panel are lower magnification images to show the retinal
cell layers. Thioflavin-S labelling is restricted to the PR layer. Note the
RPE is highly autofluorescent due to the presence of silver pigment. Bottom
panel are higher magnification images to show individual thioflavin-S
tangles the largest of which are indicated by arrows.
Optogenetic actuator - ERK biosensor circuits identify MAPK network nodes that shape ERK dynamics (2022)
Figure 4

Figure 4: RNA interference screen reveals that ERK dynamics remain unaffected in response to perturbation of most MAPK signaling nodes.

(A) RNAi perturbation targets referred to by their protein names. Nodes were spatially grouped based on the hierarchy of interactions within the MAPK network and color-coded for their function.

(B) ERK responses to sustained optoFGFR input (D = 18 mJ/cm2) in cells transfected with 10 nM siRNA against ERK1, ERK2 or a 5 nM combination of each (ERK1+2). A non-targeting siRNA (CTRL) was used as control (N = 15 cells from low and high optoFGFR levels).

(C) Western blot analysis of cells transfected with 10 nM siRNA against ERK1, ERK2 or a 5 nM combination of each (ERK1+2).

(D) Z-Score evaluation of the baseline, maxPeak and ERKpostStim of single-cell ERK responses under sustained high optoFGFR input (D = 18 mJ/cm2). The z-score was calculated by comparing each RNAi perturbation to the CTRL KD (Nmin = 126 cells per treatment, from 3 technical replicates). Non-significant (NS) results are in grey (see Figure EV3A for statistical results).

(E) Single-cell ERK trajectories (sustained optoFGFR input, D = 18 mJ/cm2) for the RNAi perturbations classified with the highest accuracy by CODEX. Top lines show single-cell ERK trajectories for which CODEX had the highest classification confidence in the validation set (N = 10). Bottom lines show single-cell ERK trajectories for low and high optoFGFR cells (N = 30 for each condition, randomly selected out of at least 212 cells per perturbation from 3 technical replicates). For easier visualization, the CTRL condition is shown twice.

(F) Proportion of oscillating cells (trajectories with at least 3 peaks) per RNAi perturbation for low and high optoFGFR expression (sustained optoFGFR input, D = 18 mJ/cm2, Nmin = 61 cells for low and 126 for high optoFGFR per perturbation from 3 technical replicates). Perturbations were ordered based on the proportion of oscillating cells with low optoFGFR expression. Statistical analysis was done using a pairwise t-test, comparing each perturbation against the CTRL for each receptor level independently (*<0.05, **<0.005, ***<0.0005, ****<0.00005, FDR p-value correction method).
Structure of a VirD4 coupling protein bound to a VirB type IV secretion machinery (2017)
Figure 1

Figure 1. SDS-PAGE analysis of purified T4SS3-10+D4 complex, comparison with the T4SS3-10 complex, stoichiometry measurement, and purification of T4SS3-10+D4 sub-complexes after deletion of single T4S system components.

A. SDS-PAGE analysis of purified T4SS3-10+D4 complex. Left panel: Coomassie-stained SDS-PAGE gel of the T4SS3-10+D4 complex. Right panel: Sypro Ruby-stained SDS-PAGE gel of the T4SS3-10m and T4SS3-10+D4 complexes. Molecular weights of MW markers are shown on the left. Identification of bands is shown in the middle. "*" indicates TrwK/VirB4 degradation products. "**" indicates minor contaminants OmpA and OmpC.

B. Stoichiometry measurement. Fluorescence scan of an SDS-PAGE gel analysis of the T4SS3-10+D4 complex where cysteine residues were reacted with AlexaFluor 633 C5 maleimide. Signals corresponding to the proteins coupled to AlexaFluor 633 were detected at a wavelength of 633 nm. Fluorescent Trw protein bands are labelled and the derived stoichiometry for TrwB/VirD4 is indicated.

C. SDS-PAGE analysis of complexes purified from cell expressing deletion mutants of the pBADM11_trwN/virB1-trwE/virB10Strep_trwD/virB11_HistrwB/virD4 constructs termed pBADM11_ΔtrwX/ΔvirBY (see main text). The same molecular weights marker has been used on this gel as in the gel presented in Figure 1A. * indicates degradation products of TrwK/VirB4.
Structure of a VirD4 coupling protein bound to a VirB type IV secretion machinery (2017)
Figure 2

Figure 2. Interaction between TrwB/VirD4 and TrwE/VirB10. Left panel: Coomassie-stained SDS-PAGE gel of the T4SS3-10+D4 complex (lane 1), T4SS3-10+D4:TrwEΔN42 complex (lane 2) and T4SS3-10+D4:TrwEΔN64 complex (lane 3). Middle panel: Western Blot analysis using αStrep antibodies to detect the TrwE/VirB10 protein within the T4SS3-10+D4 complex and its variants. Right panel: Western Blot analysis using αHis antibodies to detect the TrwB/VirD4 protein within the T4SS3-10+D4 complex and its variants.
Structure of a VirD4 coupling protein bound to a VirB type IV secretion machinery (2017)
Figure 3

Figure 3. NS-EM of the T4SS3-10+D4 complex.

A. NS-EM micrograph of the T4SS3-10+D4 complex. A few representative particles of the T4SS3-10+D4 complex are circled in yellow. Scale bar 50nm.

B. Representative class averages of T4SS3-10+D4 complex obtained after initial alignment and classification.

C. The upper row represents typical class averages of the T4SS3-10+D4 IMC complex (i.e. with the outer membrane core complex (OMC) masked out). The second row shows projections of the T4SS3-10+D4 IMC complex in the same directions determined for the classes above. The third row displays projections of the T4SS3-10 IMC complex (EMD-2567) in the same directions. The bottom row shows the differences between the projections above (plus or minus TrwB/VirD4) corresponding to positions of the TrwB/VirD4 protein.

D. FSC of the electron density map of the T4SS3-10+D4 complex. The 0.5 line crosses the FSC at a resolution of 28 Å.
Structure of a VirD4 coupling protein bound to a VirB type IV secretion machinery (2017)
Figure 4

Figure 4. NS-EM structure of the T4SS3-10+D4 complex.

A. Side views of the NS-EM structure of the T4SS3-10 (left) and T4SS3-10+D4 (right) complexes. The arches, the TrwK/VirB4 barrels, and the TrwB/VirD4 density are shown in green, yellow, and blue, respectively. The boundaries of the 3-tiers structure of the TrwK/VirB4 barrel are indicated in the middle of the panels and each tier is labelled as lower, middle, and upper, respectively.

B. Side view of the T4SS3-10+D4 structure (upper panel) and derived schematic representation (lower panel). Overall dimensions are indicated

C. Same as in B except that the side-view shown is rotated 90 degrees along a vertical axis compared to the view shown in panel B. Overall dimension is indicated.

D. Bottom view of the NS-EM structure of the T4SS3-10 (upper panel) and the corresponding schematic representation (lower panel). Angle between the axes connecting the TrwK/VirB4 hexamer pair and the TrwB/VirD4 dimer pair is shown.
Structure of a VirD4 coupling protein bound to a VirB type IV secretion machinery (2017)
Figure 5

Figure 5. Validation of the location of TrwB/VirD4 in the T4SS3-10+D4 complex.

A. Location of position 236 of TrwB/VirD4 where a FLAG tag was introduced for immuno-labelling of TrwB/VirD4 within the T4SS3-10+D4 complex. Left: structure of hexameric TrwBΔN70/VirD4ΔN70 (PDB entry code 1GKI). Only two diametrically opposed subunits are shown. The position of residue 236 is shown with a red sphere. Right: region of the T4SS3-10+D4 IMC where the location of the residue 236 of TrwB/VirD4 would be expected (indicated by a red sphere) and schematic representation of an anti-FLAG antibody bound to that location.

B. Class averages of antibody-bound T4SS3-10+D4FLAG. Class averages of the aligned NS-EM images of the T4SS3-10+D4FLAG with 3-4 particles per class. Red circles indicate the position of the antibody.

C. Network of spatial restraints identified by XL-MS mapped onto primary sequences of the TrwB/VirD4 subunit (blue) and the subunits interacting with it, TrwE/VirB10 (grey) and TrwK/VirB4 (yellow). Intermolecular and intramolecular crosslinks are shown in green and orange, respectively. * indicates crosslinks mapped in the structure shown in Figure EV3B.

Expanded View Figure Legends
Translational offsetting as a mode of estrogen receptor α-dependent regulation of gene expression (2019)
Figure 1

Figure 1. ERα-dependent alterations in steady-state mRNA levels are largely offset at the level of mRNA translation.

(A) Expression of ERα in control (shCtrl) and knockdown (shERα) BM67 cells was determined by western blotting (β-actin served as a loading control). Gene expression was determined using polysome-profiling which quantifies both total mRNA and efficiently translated polysome-associated mRNA (n = 3).

(B) Distributions (quantified by kernel density estimation) of p-values for differential expression (shERα vs. shCtrl BM67 cells) using data from polysome-associated mRNA (orange), cytosolic mRNA (purple) or from analysis of changes in translational efficiency (i.e. changes in polysome-associated mRNA not paralleled by changes in cytosolic mRNA) leading to altered protein levels (red; a higher density of low p-values indicates a higher frequency of changes in gene expression).

(C) Scatterplot of polysome-associated mRNA vs. cytosolic mRNA log2 fold-changes (shERα vs. shCtrl). Areas of the plot are colored according to the density of data points (genes; dark blue corresponds to areas with many genes [see methods])

(D) Same plot as in (B) but including a blue density of p-values from the analysis of translational offsetting.

(E) A scatter plot similar to (C) but where genes are colored according to their mode of regulation derived from anota2seq analysis. A relaxed threshold (p<0.05) was used to identify a set of transcripts regulated via translation, which did not pass thresholds used for identification of changes in mRNA abundance or translational offsetting (FDR<0.1). Confidence ellipses (level 0.7) are overlaid for each mode of regulation. A bar graph indicates the number of mRNAs regulated via each mode.
Translational offsetting as a mode of estrogen receptor α-dependent regulation of gene expression (2019)
Figure 2

Figure 2. ERα-dependent translational offsetting opposes changes in protein levels despite alterations in corresponding mRNA abundance.

(A) Targets from each mode of regulation (cf. Fig 1E) were selected for validation by Nanostring. Shown is a scatterplot of Nanostring quantification of polysome-associated mRNA vs. cytosolic mRNA log2 fold-change (shERα vs. shCtrl; n = 3). Genes are colored according to their identified mode of regulation (i.e. from Fig 1E). Confidence ellipses (based on Nanostring data, level 0.7) are overlaid for each mode of regulation. Selected genes from each mode of regulation are indicated.

(B) Levels of indicated proteins from shERα and control BM67 cells were determined by western blotting with their quantifications. β-actin served as loading control. Graphs represent mean ± standard deviation (n = 3-5 as indicated). Protein expression between groups were compared using two-sided paired Student's t tests.

(C) Immunoblotting of BM67 cell lines extract and its quantitation following incubation with 100 µg/mL cycloheximide as indicated. Graphs represent mean ± standard deviation (n = 5).
Translational offsetting as a mode of estrogen receptor α-dependent regulation of gene expression (2019)
Figure 4

Figure 4. Upon ERα depletion, target sites for miRNAs are under-represented among suppressed but offset mRNAs.

(A) Volcano plot of ERα dependent miRNA expression in BM67 cells quantified by small RNAseq. Down- and up-regulated miRNAs (FDR<0.2 and fold-change > 1.25) are colored in blue and red, respectively.

(B-C) Validation of miRNA expression using qPCR. Normalized expression (mean ± standard deviation; n = 3) (B) and expression fold change (shERα vs. shCtrl) obtained from small RNAseq vs. qPCR (C).

(D) Percentage of miRNA among small RNAs in shERα and shCtrl BM67 cells (mean ± standard deviation; n = 3).

(E-J) Assessment of the relationship between presence of miRNA target sites and translational offsetting. (E) For visualization, mRNAs were assigned angles describing their mode of regulation such that mRNAs with congruently modulated total and polysome-associated mRNA obtain an angle of ~45 degrees, whereas offset mRNAs are assigned an angle of ~0 degrees. (F) The distributions (quantified by kernel density estimation) of such angles were then compared between mRNAs whose levels were induced upon ERα depletion, which were also targets of each suppressed miRNAs separately (blue lines); and the set of background transcripts (mRNAs induced upon ERα depletion but not targets of suppressed miRNAs; black). (G) For such subsets of miRNA targets (i.e. from F), the relative number of offset and non-offset mRNAs (as determined by anota2seq analysis) was also compared to the background (same as in F) using Fisher's exact test; and the resulting adjusted p-values (FDRs; across all assessed miRNAs) were visualized as a histogram. (H-I) A similar assessment as in (F-G) but for suppressed mRNAs and induced miRNAs. (J) A similar assessment as in (H) but for randomly selected groups of 10 miRNAs (gray lines) compared to background (black) and targets of all induced miRNA (red; i.e. from H).
Translational offsetting as a mode of estrogen receptor α-dependent regulation of gene expression (2019)
Figure 5

Figure 5. Transcripts induced but translationally offset upon ERα depletion are characterized by distinct codon usage.

(A) For each codon, the average frequency (per thousand) is compared between transcripts induced but offset vs non-offset (i.e. abundance mode of regulation) upon ERα depletion in BM67 cells. Codons for the same amino acid are connected by a gray line.

(B) Heatmap of standardized residuals from a chi-squared contingency table test. Shown in red and blue are cells with counts significantly higher and lower, respectively, than expected counts under the null hypothesis (i.e. independence between mode for regulation of gene expression and codon composition).

(C) A correspondence analysis for average codon frequency among transcripts annotated to each GO term. Each gray dot corresponds to one GO term. The gene expression modes observed upon ERα depletion (Fig 1E) were then projected into the same dimensions based on the average codon frequencies of included transcripts.

(D) A correspondence analysis for codon frequency in each regulated mRNA (from Fig 1E). Each dot represents one mRNA and is colored according to its mode of regulation. Codons identified as over-represented among translationally offset mRNAs are also indicated.

(E) Unsupervised clustering of gene level codon usage normalized by amino acid counts. All regulated mRNAs (from Fig 1E) are shown in rows and all codons in columns. Codons identified as over-represented among mRNAs whose levels were induced but offset or suppressed but offset are indicated in light and dark blue, respectively.
Translational offsetting as a mode of estrogen receptor α-dependent regulation of gene expression (2019)
Figure 6

Figure 6. Translational offsetting of transcripts induced following ERα depletion is mediated by U34 tRNA-modification enzymes.

(A) Immunoblotting of BM67 cell extract for ELP3 after stable shRNA-mediated ERα knockdown in BM67 cells. Graphs represent mean ± standard deviation of n=3.

(B) qPCR analysis and immunoblotting of BM67 cell extract for indicated proteins with its quantitation following deletion of Esr1 gene by CRISPR-Cas9 technology. Graphs represent mean ± standard deviation of n=5.

(C) qPCR analysis and immunoblotting of BM67 cell extract for ELP3 and DEK with its quantitation following deletion of Elp3 gene by CRISPR-Cas9 technology. Graphs represent mean ± standard deviation of n=4.

(D) Immunoblotting and qPCR analysis comparing cell extracts obtained from BM67 cells transduced with pLentiCRISPRV2 empty vector, Elp3-null BM67 cells and Elp3-null BM67 cells overexpressing ELP3 protein containing silent mutations in the sgRNA binding site. Graphs represent mean ± standard deviation of n=3-4.

Data information: Data were analyzed by Student t test.
Translational offsetting as a mode of estrogen receptor α-dependent regulation of gene expression (2019)
Figure 7

Figure 7. ERα regulates mcm5s2-U tRNA modifications by controlling the expression of mcm5s2-U-modifying enzymes in MCF7 cells.

(A) Boxplots (plotted as in Fig 3B) of gene expression of ELP3, ALKBH8 and CTU2 upon treatment with 17β-E2 and/or ICI-182780 in MCF7 cells (extracted from (Wardell et al, 2012; Data Ref: McDonnell et al, 2012)). Wilcoxon-Mann-Whitney tests (two-sided) were used to assess differences between conditions (n = 10) and a global Bonferroni adjustment was applied on p-values.

(B) Immunoblotting of MCF7 cell extracts. MCF-7 cells were grown in phenol red-free RPMI media supplemented with 5% charcoal-stripped serum for 24 hours and then treated with 1 nM E2 and/or 100 nM ICI-182780 for 24 hours. Graphs represent mean ± SD of n=5 experiments. Data were analyzed using two-sided paired Student's t tests.

(C) ChIP-seq reveals ER binding sites proximal to the ELP3 gene. Each track represents a distinct ChIP-seq dataset.

(D) Immunoblotting of MCF-7 cell extract for indicated proteins following deletion of ELP3 gene by CRISPR-Cas9 technology.

(E) Quantification of mcm5S2-U, mcm5U and cm5U levels in ELP3-null MCF-7 cells and in MCF-7 cells treated with 100 nM ICI-182780 for 72 hours versus their respective controls by liquid chromatography-mass spectrometry (LC-MS) analysis. The MCF-7 cells were grown in phenol red-free RPMI media supplemented with 5% charcoal-stripped serum for 24 hours prior to ICI-182780 treatment. Graphs represent mean ± SD of n=4. Data were analyzed using two-sided paired Student's t tests. Vh, Vehicle; ICI, ICI-182780.

EXPANDED VIEW FIGURE LEGENDS