EMBO/soda-nel huggingface dataset:
Mechanism and functions of membrane binding by the Atg5–Atg12/Atg16 complex during autophagosome formation (2012)
Figure 3

Atg3 recruitment to membranes is dependent on Atg16 and Atg12. (A) Coomassie‐stained gels showing co‐sedimentation assays using Folch liposomes and the indicated proteins. Atg5–Atg12/Atg16 was most efficient in recruiting Atg3 to the pellet fraction. (B) Quantification of Atg3 in the pellet fraction in the presence of the indicated proteins. The quantification is based on three independent experiments. (C) Coomassie‐stained gels showing the results of Atg8–PE conjugation assays using the indicated proteins and E. coli lipids derived liposomes. Atg8–PE conjugation was detected as characteristic band shift as the conjugated form runs faster on urea‐SDS gels. The numbers above the gels indicate the time in minutes. Note that at least under these conditions almost no Atg8–PE conjugation was detected in the absence of the Atg5–Atg12 conjugate or the Atg5–Atg12/Atg16 complex. The numbers next to the gels indicate the molecular weight in kDa. The averages and the error bars representing the standard deviations are shown. P‐values were calculated using Student's t‐test. NS, non‐significant; P, pellet; S, supernatant. Figure source data can be found with the Supplementary data.
Mechanism and functions of membrane binding by the Atg5–Atg12/Atg16 complex during autophagosome formation (2012)
Figure 4

Reconstitution of Atg5–Atg12/Atg16 and Atg8 on GUVs. (A) Confocal images showing eGFP–Atg8 recruitment to GUVs is dependent on the Atg5–Atg12/Atg16 complex and PE. The membrane was labelled by incorporation of rhodamine‐PE. (B) Single confocal section showing colocalization of Atg5–Atg12/Atg16–eGFP and mCherry–Atg8 on GUVs. (C) Quantification of GUV‐associated eGFP–Atg8 in the presence of the Atg5–Atg12/Atg16 complex and the Atg5–Atg12 conjugate. The first graph shows the percentage of GUVs associated with eGFP–Atg8 fluorescence. The second graph shows the intensity of eGFP–Atg8 on the GUVs. The quantification is based on four independent experiments. Inset: anti‐Atg12 western blot using the rabbit anti‐Atg12 antiserum showing the amounts of Atg5–Atg12/Atg16 complex and Atg5–Atg12 conjugate in one of the assays used for the quantification shown in (C). (D) Quantification of membrane recruitment of Atg3–mCherry by the Atg5–Atg12/Atg16 complex, the Atg5–Atg12 conjugate and a buffer control. The graph is based on two independent experiments. (E) Widefield images showing individual frames of a time series of GUVs incubated with Atg3, Atg7, Atg8 and the Atg5–Atg12/Atg16 complex (see Materials and methods for details). The membrane was labelled by incorporation of rhodamine‐PE. The time is indicated in minutes. (F) Widefield images of GUVs incubated with Atg3, Atg7, eGFP–Atg8 and the Atg5–Atg12/Atg16 complex for 35 min (left) or 70 min (right). The membrane was labelled by incorporation of rhodamine‐PE. Note the massive accumulation of eGFP–Atg8 at the interface between individual GUVs. The arrows point to some of these interfaces. For the quantifications, the averages and standard deviations are shown. P‐values were calculated using Student's t‐test. Scale bars: 10 μm. Figure source data can be found with the Supplementary data.
Mechanism and functions of membrane binding by the Atg5–Atg12/Atg16 complex during autophagosome formation (2012)
Figure 5

Membrane tethering by the Atg5–Atg12/Atg16 complex. (A) Frames of widefield images taken from a time series of rhodamine‐PE labelled GUVs in the presence of the Atg5–Atg12/Atg16 complex. For the control condition buffer but no protein was added. Note the increase in clustered GUVs over time. The numbers indicate the time in minutes. (B) Confocal images of rhodamine‐PE labelled GUVs incubated with Atg5–Atg12/Atg16–eGFP complex. Note the accumulation of the complex at the interface between GUVs (arrows). (C) Individual confocal frames of a time series of rhodamine‐PE labelled GUVs incubated with Atg5–Atg12/Atg16–eGFP. The arrows point to the GUV–GUV interface where the protein initially accumulated. (D) Confocal images of rhodamine‐PE labelled GUVs incubated with Atg5–Atg12/Atg16–eGFP. The arrows point to the concentrations of Atg5–Atg12/Atg16 on the GUV membrane. Scale bars: 10 μm (A–C) and 3 μm (D).
Mechanism and functions of membrane binding by the Atg5–Atg12/Atg16 complex during autophagosome formation (2012)
Figure 6

Membrane tethering is Atg16 dependent. (A) Widefield images of rhodamine‐PE labelled GUVs 30 min after incubation with the indicated proteins. Note that GUVs cluster only in the presence of the Atg5–Atg12/Atg16 and Atg5/Atg16 complexes. (B) SUV aggregation assay using Folch liposomes and the indicated proteins. The proteins were added after a short delay. The symbols above, below the images or next to the curves represent Atg5 (blue oval), Atg12 (red circle) and Atg16 (green Y). The overall shape of the Atg5–Atg12/Atg16 complex is according to the structural model of the complex as proposed in Fujioka et al (2010). Scale bars: 10 μm.
Mechanism and functions of membrane binding by the Atg5–Atg12/Atg16 complex during autophagosome formation (2012)
Figure 7

Membrane binding by Atg5 is essential for autophagy and the Cvt pathway in vivo. (A) Liposome co‐sedimentation assay using Folch liposomes and the indicated Atg5 proteins stabilized with an N‐terminal fragment of Atg16 (amino acids 1–46). (B) Quantification based on three co‐sedimentation assays as shown in (A). The amount of protein pelleted in the absence of liposomes was subtracted. The averages and the standard deviations are shown. (C) Yeast cells were transformed with the indicated expression constructs and Atg5–2 × Myc was immunoprecipitated with an anti‐Myc antibody. The precipitated protein was subjected to anti‐Atg5 and anti‐Atg12 western blotting. The substitution of R171 and K160 to glutamate caused the mutant protein to run higher. The same phenomenon was observed for the recombinant protein (Supplementary Figure 3). (D) Anti‐Atg12 western blot of cell fractions prepared from rapamycin‐treated yeast cells. The anti‐Pgk1 and anti‐Pex30 served as control for the cytosolic and membrane fractions, respectively. (E) Anti‐Myc and anti‐Pex30 western blots of yeast cell fractions from cells of the indicated genotype and expressing Atg16–9 × Myc and Atg5 or Atg5 K160E, R171E. (F) Starvation assay with the indicated yeast strains and the indicated rescue constructs. GFP was detected by western blotting. Pgk1 served as loading control. (G) Same assay as shown in (F) but using an anti‐Ape1 antiserum for western blotting. (H) Western blots of yeast cell lysates using an anti‐Atg8 antiserum. (I) Ape1 protease protection assay with the indicated yeast strains. The percentages below the blots indicate the percent of protected ApeI in the +protease K, −Triton X‐100 lanes and are the average of three independent experiments±the standard deviation. The numbers next to the blots indicate the molecular weight in kDa. Figure source data can be found with the Supplementary data.
Mechanism and functions of membrane binding by the Atg5–Atg12/Atg16 complex during autophagosome formation (2012)
Figure 8

Localization of wild‐type Atg5 and Atg5 K160E, R171E to the PAS. (A) Yeast cells of the indicated genotype expressing Atg5–3 × mCherry or Atg5 K160E, R171E–3 × mCherry were treated with rapamycin and imaged using a Deltavision microscope. Maximum projections of z‐stacks are shown. (B) Graph showing the percentage of mCherry‐positive cells that display Atg5–3 × mCherry dots. In total, 3 independent experiments were conducted and >400 cells were counted. (C) Graph showing the percentage of cells that display Atg16–3 × mCherry dots. In total, 3 independent experiments were conducted and >750 cells were counted. The graphs show the averages and the error bars representing the standard deviations. P‐values were calculated using Student's t‐test. Scale bars: 5 μm.
Suppression of Ca2+ Signals by EGR4 controls Th1 differentiation and anti-cancer immunity in vivo (2020)
Figure 1

Fig 1. Characterization of EGR4 knockout T cells.

T cells were collected from age- and gender-matched WT, EGR1KO and EGR4KO mice.

(A) CD4+ T cells were isolated from the spleen by negative selection before incubating with anti-CD3/CD28 antibodies for the indicated time periods. Levels of expression of EGR1, EGR2, EGR3 and EGR4 were measured by qPCR.

(B) WBC were collected from WT, EGR1KO and EGR4KO mice before staining and FACS analysis to determine composition (gating strategies in Appendix Fig S1). Subclasses of CD8+, CD4+ and Treg populations were determined as shown.

Data information: Data in panel A (mean±SEM; a minimum of 3 biological replicates were examined; each biological replicate includes 2 technical replicates) were analyzed by two way ANOVA with post-hoc tests. Changes in the expression of each gene over time were EGR-dependent. EGR1 (p=0.0017); EGR2 (p<0.0001); EGR3 (p=0.0031); EGR4 (p=0.0309). Differences from WT at specific time points due to EGR deletion are marked with * p < 0.05; **** p < 0.0001. Differences between WT, EGR1KO and EGR4KO WBC in panel B (mean±SEM; a minimum of 3 biological replicates were examined; each biological replicate includes 2 technical replicates) were determined by one way ANOVA. Statistically distinct groups were determined by post-hoc analysis and marked as a,b and c.
Suppression of Ca2+ Signals by EGR4 controls Th1 differentiation and anti-cancer immunity in vivo (2020)
Figure 2

Fig 2. Constitutive hyper-proliferation in EGR4KO T cells.

WT and EGR4-/- CD4+ and CD8+ T cells were isolated from the spleen by cell sorting and stained with CFSE.

A Cells were incubated under unstimulated conditions or stimulated with either anti-TCRβ or anti-CD3/CD28 antibodies for 0 to 5 days (mean±SEM; a minimum of 3 biological replicates were examined; each biological replicate includes 2 technical replicates).

B Dose dependence of EGR4-dependent differences in proliferation were also determined in both CD4+ and CD8+ cells aft er treatment with anti-TCRβ (E,F) or anti-CD3/CD28 (G,H) at the indicated concentrations before FACS analysis (Appendix Fig S2) (mean±SEM; a minimum of 3 biological replicates were examined; each biological replicate includes 2 technical replicates).

C,D Generation analysis was then assessed in WT, EGR1-/- and EGR4-/- CD4+ (C) or CD8+ (D) T cells after a 4 day incubation, under unstimulated conditions, or stimulated with either anti-TCRβ or anti-CD3/CD28 antibodies. Generation analysis was determined using FlowJo as depicted in Appendix figure S3 (mean±SEM; a minimum of 3 biological replicates were examined; each biological replicate includes 2 technical replicates).. EGR4 deletion significantly shifted the number of generations as determined by two-way ANOVA; loss of either EGR1 or EGR4 significantly changed the number of generations under resting or stimulated conditions (p < 0.0001).
Suppression of Ca2+ Signals by EGR4 controls Th1 differentiation and anti-cancer immunity in vivo (2020)
Figure 3

Fig 3. EGR4KO cells exhibit Th1 bias and a capacity to differentiate into CTLs.

CD4+ and CD8+ T cells were isolated from the spleens of WT, EGR1KO and EGR4KO mice by cell sorting.

(A-F) Cytokine secretion was measured by ELISA after incubating CD4+ (A,C,E) and CD8+ (B,D,F) T cells for 48 hrs in resting conditions (A,B) or stimulated with either anti-TCRβ (C,D) or anti-CD3/CD28 antibodies (E,F).

(G) Representative FACS plots depicting IFNγ levels after intracellular staining in WT and EGR4KO CD4+ and CD8+ T cells. (H) Comparison of IFNγ levels in WT vs. EGR4-/- T cells.

(I) Representative FACS plots of CD4+ T cells incubated for 24 hrs under Th1 polarizing conditions before intracellular staining with IFNγ and IL-17 antibodies. (J) Comparison of the number of Th1 polarized cells between WT, EGR1-/- and EGR4-/- CD4+ T cells.

(K) CD4+ T cells were incubated for 5 days under polarizing conditions before analysis of cytokine production by ELISA.

Data information: Differences between cytokine levels in WT, EGR1-/- and EGR4-/- cells in panels A-F (mean±SEM; a minimum of 3 biological replicates were examined; each biological replicate includes 2 technical replicates) were determined by one-way ANOVA, with significant differences (p < 0.05) marked by a, b or c. Differences in IFNγ production in Panel H (mean±SEM; n = 4) were determined by two-way ANOVA. The dependence of the percentage of CD4+ IFNγ-Lo cells on TCR signal strength was dependent upon EGR4 expression (p = 0.0003). The percentage of CD4+ IFNγ-Hi cells was dependent on both TCR signal strength (p = 0.0014) and EGR4 expression (p = 0.0009). The dependence of the percentage of CD8+ IFNγ-Lo cells on TCR signal strength was dependent upon EGR4 expression (p < 0.0001). The dependence of the percentage of CD8+ IFNγ-hi cells on TCR signal strength was dependent upon EGR4 expression (p = 0.0079). Panel J (mean±SEM; a minimum of 3 biological replicates were examined; each biological replicate includes 2 technical replicates) were determined by one-way ANOVA, revealing that the number of Th1 polarized cells was dependent upon EGR4 expression (p = 0.0042). Panel K (mean±SEM; a minimum of 3 biological replicates were examined; each biological replicate includes 2 technical replicates) were determined by two-way ANOVA, revealing that IFNγ production was dependent upon EGR4 expression (p < 0.0001). Post-hoc analysis revealed EGR-dependent differences under specific conditions * p < 0.05; *** p < 0.001; **** p < 0.0001.
Suppression of Ca2+ Signals by EGR4 controls Th1 differentiation and anti-cancer immunity in vivo (2020)
Figure 4

Fig 4. Activation of CD4+ cells causes sustained Ca2+ elevation and NFAT upregulation.

(A) NFAT nuclear localization was measured was measured by immunocytochemistry in CD4+ and CD8+ T cells isolated by negative selection from WT, EGR1KO and EGR4KO mice. Cells were stimulated with anti-CD3/CD28 antibodies for the indicated time periods before fixation and staining. Nuclear localization of NFATc1 in CD4+ and CD8+ T cells was determined based on colocalization of NFATc1 and DAPI measured by Pearson analysis (mean±SEM; data are based upon 13 to 20 cells/data point from one experiment; experiment was repeated 3 times). EGR4-mediated differences in NFATc1 localization were determined by two-way ANOVA. NFAT localization was dependent upon EGR4 expression in both CD4+ (p=0.025) and CD8+ (p=0.039) T cells. Post-hoc analysis revealed EGR4-dependent differences at specific timepoints * p < 0.05; *** p < 0.001.

(B) WT, EGR1KO and EGR4KO CD4+ T cells were isolated from the spleen by negative selection before plating on poly-lysine (control) or CD3/CD28 and loading with fura2. Ca2+ levels shown are from representative single cells measured from multiple experiments. (C) Scatter plots showing area under the curve (AUC) and variance for each cell measured under all conditions.
Suppression of Ca2+ Signals by EGR4 controls Th1 differentiation and anti-cancer immunity in vivo (2020)
Figure 5

Fig 5. Ca2+ signal elevation in EGR4KO T cells is required for IFNγ and IL2 production.

CD4+ and CD8+ T cells were isolated by negative selection from WT or EGR4-/-mice.

(A) CD4+ and CD8+ T cells were loaded with Fura-2AM and plated on poly-D-lysine (2 hrs) before treating with biotinylated anti-CD3ε, followed by streptavidin where indicated. (C) The average response of the majority of CD4+ (WT 74.2±3.2%; EGR4-/- 77.8±2.9%) and CD8+ (WT 79.4±3.5%; EGR4-/- 78.2±2.5%) cells that responded to streptavidin crosslinking of CD3 (mean±SEM; 40-60 cells/coverslip; 7 to 8 separate experiments).

(B) Cells were plated on anti-CD3/CD28 antibodies for 2 hrs; BTP2 (10 μM) was added where marked by the arrow.

(C) CD4+ T cells were incubated with anti-CD3/CD28 antibodies for 6 hrs before measuring expression of IFNγ, IL-2, IL-17 and IL-4 by FACS analysis. Data are mean±SEM; a minimum of 3 biological replicates were examined; each biological replicate includes 2 technical replicates.
Suppression of Ca2+ Signals by EGR4 controls Th1 differentiation and anti-cancer immunity in vivo (2020)
Figure 6

Fig 6. Potassium channel activity is required for Ca2+ responses and IFNγ production, but not hyperproliferation in EGR4KO T cells.

CD4+ T cells were isolated by negative selection from WT, EGR1-/- or EGR4-/- mice.

(A) WT or EGR4-/- cells were loaded with Fura-2AM and plated on anti-CD3/CD28 antibodies for 2 hrs. Senicapoc (4 μM) or Tram-34 (5 μM) were added where marked by the arrow.

(B) CD4+ T cells were isolated by negative selection from WT or EGR4-/- mice and incubated with anti-CD3/CD28 antibodies for 6 hrs in the presence or absence of either senicapoc, TRAM-34 or Shk-Dap22 before measuring expression of IFNγ levels by FACS analysis. Data are mean±SEM; 3 biological replicates were examined; each biological replicate includes 2 technical replicates. *** p < 0.001; **** p < 0.0001.

(C) To measure the effect of KCa3.1 inhibition of cell proliferation, WT and EGR4-/- CD4+ T cells were isolated from the spleen by cell sorting and stained with CFSE. Cells were incubated with anti-TCRβ antibodies in the presence of vehicle, Senicapoc (5 µM) or TRAM-34 (5 µM) for 4 days and then collected for FACS analysis. (D) Generation analysis was completed for all data using FlowJo software. Data are mean±SEM; 3 biological replicates were examined; each biological replicate includes 2 technical replicates.
Suppression of Ca2+ Signals by EGR4 controls Th1 differentiation and anti-cancer immunity in vivo (2020)
Figure 7

Fig 7. Attenuated melanoma lung colonization and metastasis in EGR4-/- mice.

B16N melanoma cells stably expressing GFP-luciferase were injected into syngeneic WT and EGR4-/- mice by tail vein injection.

(A) Luciferase expression was monitored by IVIS imaging at the indicated timepoints after luciferin injections.

(B-D) Mice were sacrificed on day 20 and tumors were counted. Data is presented as total/mouse (B), lung tumors (C) and metastatic tumors (all tumors found outside of the lungs; D). N=9 for each gender and genotype. Differences in luciferase activity measured by IVIS in Panel A were determined by two-way ANOVA. Changes in luciferase activity were significantly altered in EGR4 knockout mice (P < 0.0112).

(E-G) All lung tumors were isolated from both WT and EGR4KO mice along with spleens and analysed for CD45+ cells. WT lung tumors were 5.407 ± 1.843% CD45+, while EGR4KO mice were 12.445 ± 2.239% CD45+. WT spleens were 83.92 ± 3.344% CD45+, while EGR4KO mice were 95.13 ± 1.856% CD45+. Relative distributions of T and myeloid cells within the CD45+ populations were determined by flow cytometric analysis. (E,F) Distributions of T and myeloid cells found within lung tumors (E) vs. the spleen (F). (G) Representative FACS plots depicting gating strategies for defining Treg cell populations in Panels E and F; Staining controls are in appendix figure S7.

Data information: Data in panels E-G are mean±SEM; Tumor infiltrates from 10 WT and 4 EGR4-/- mice were examined. EGR4-mediated differences were determined by paired two-tailed T tests, with significant differences marked by asterisks. * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001.
Suppression of Ca2+ Signals by EGR4 controls Th1 differentiation and anti-cancer immunity in vivo (2020)
Figure 8

Fig 8. Th1 bias and decreased anergy/exhaustion in EGR4-/- mice exhibiting melanoma.

Tumors collected and analysed for exhaustion/anergy. Cells were collected and enriched for the immune cell population by Ficoll-Hypaque. WT cells were 36.9 ± 4.68% Thy1.2+, EGR4KO cells were 48.0 ± 0.58% Thy1.2+.

(A) CD4+ and CD8+ T cells were stimulated in vitro with ionomycin/PMA before intracellular staining for IFNγ, IL-17 and IL-9 and FACS analysis.

(B,C) Representative FACS plots depicting gating strategies for defining cytokine expression in panels A to D; staining controls are in appendix figure S8.

(D-I) CD4+ and CD8+ T cells were stained with CD44, CD73, FR4 and PD1 to monitor the formation of anergic/exhausted T cells. (D) Percentages of each population. (E) Gating strategies. (F) FR4 and PD1 levels in WT vs. EGR4-/- T cells.

Data information: Data in panels A, D and F are mean±SEM; tumor infiltrates from 10 WT and 4 EGR4-/- mice were examined. EGR4-mediated differences were determined by paired two-tailed T tests, with significant differences marked by asterisks. * p < 0.05; ** p < 0.01; **** p < 0.0001.

Expanded View Figure Legends
CA10 Regulates Neurexin Heparan Sulfate Addition via a Direct Binding in the Secretory Pathway (2021)
Figure 1

Figure 1. Analysis of Nrxn1 sequence determinants required for HS addition.

(A) Sequences of secreted Fc-tagged Nrxn1β variants analyzed. Mutated residues are shown in red, the HS modified serine in green, and cysteines forming the Cys-loop in blue. Right column ('HS?') summarizes the results from (B-C). Asterisks, colons, and periods indicate fully, strongly, or weakly conserved residues, respectively.

(B) Representative immunoblot of Nrxn1β-Fc variants harvested from HEK293 cell media and subjected to heparinase treatment ('Heps'). Samples were analyzed by reducing SDS/PAGE and immunoblotting with antibodies against the Fc-tag and the 3G10 epitope (to detect the HS stub which reveal HS after heparinase digestion).

(C) Quantification of 3G10 (reflecting HS) signal normalized to that of Fc (Nrxn1). Bar graph shows means ±SEM of 3 independent experiments.