Journal: EMBO Reports

Article Title: The USP12/46 deubiquitinases protect integrins from ESCRT-mediated lysosomal degradation

doi: 10.1038/s44319-024-00300-9

Figure Lengend Snippet: ( A ) Schematic overview of the CRISPR screen for identifying DUBs regulating Itgb1 surface levels. Cas9-expressing HAP1 cells were transduced with pooled lentiviral guide RNA (gRNA) libraries targeting 98 DUBs from the human genome. After 2 weeks in culture, cells with the 5% lowest (Itgb1 Lo ) and the 5% highest (Itgb1 Hi ) Itgb1 surface levels were sorted by flow cytometry, and gRNA-targeted genes were determined. ( B ) Volcano plot of the results from the CRISPR screen. The x-axis represents the log 2 fold change (lfc) in the frequency of genes targeted between the Itgb1 Lo and Itgb1 Hi populations. The y-axis indicates the robust rank aggregation (RRA) score determined by the MAGeCK algorithm (MAGeCK-RRA) (Li et al, ). Dots represent individual targeted genes, and those meeting the criteria of |lfc| >0.33 and −log 10 (RRA) >2 were considered significant. Genes significantly enriched in Itgb1 Lo cells are colored in blue, and those enriched in Itgb1 Hi in red. USP12 is marked in white. ( C ) Volcano plot of the α5β1 integrin proximitome determined by label-free MS analysis in mouse kidney fibroblasts expressing miniTurbo-tagged Itag5 (TurboID) versus Itgb1-KO fibroblasts (Ctrl). P values were determined using a two-sided permuted t -test with 250 randomizations. The black dashed line indicates the significance cutoff (FDR:0.05, S0:0.1) estimated by the Perseus software. n = 3 biological replicates. The red dots indicate the subunits of the α5β1 heterodimer and the components of the USP12/46-WDR48-WDR20 complex. ( D ) Itgb1 surface levels in WT and two independent clones (cl1 and cl2) of USP12-KO, USP46-KO, and USP12/46-dKO fibroblasts determined by flow cytometry. Statistical analysis was carried out by RM one-way ANOVA with Dunnett’s multiple comparison test comparing the WT fibroblasts with USP12-KO cl1 or cl2, USP46-KO cl1 or cl2, USP12/46-KO cl1 or cl2 fibroblasts ( P = 0.9905, 0.9968, 0.2401, 0.8080, 0.0067, and 0.0065, respectively). ** P < 0.01; n.s. not significant. Data were shown as Mean ± SD, n = 3 independent experiments. ( E , F ) WB ( E ) and densitometric quantification ( F ) of Itgb1 and Itga5 protein levels in WT and USP12/46-dKO fibroblasts. Gapdh served as loading control. Statistical analysis was carried out by RM one-way ANOVA with Dunnett’s multiple comparison test comparing the WT fibroblasts with USP12/46-KO cl1 or cl2 fibroblasts (for Itgb1, P = 0.0162 and 0.0189, respectively; for Itga5, P = 0.0180 and 0.0106, respectively). * P < 0.05. Data were shown as Mean ± SD, n = 3 independent experiments. ( G – I ) Itgb1 surface levels were determined by flow cytometry ( G ), Itgb1 protein levels in cell lysates were determined by WB ( H ), and densitometric quantification ( I ) in WT and USP12/46-dKO fibroblasts stably expressing EGFP, EGFP-USP12 WT , or EGFP-USP12 C48S . Gapdh served as a loading control. Statistical analysis was carried out by RM two-way ANOVA with Dunnett’s multiple comparison test. In ( G ), statistical significance was tested comparing the EGFP group with EGFP-USP12 WT or EGFP-USP12 C48S group in WT fibroblasts ( P = 0.3449 and 0.0193, respectively); in USP12/46-dKO cl1 fibroblasts ( P = 0.0335 and 0.6230, respectively); and in USP12/46-dKO cl2 fibroblasts ( P = 0.0184 and 0.9260, respectively). In ( I ), statistical significance was tested comparing the EGFP group with EGFP-USP12 WT or EGFP-USP12 C48S group in WT fibroblasts ( P = 0.6467 and 0.6716, respectively); in USP12/46-dKO cl1 fibroblasts ( P = 0.0266 and 0.3351, respectively); and in USP12/46-dKO cl2 fibroblasts ( P = 0.0332 and 0.1310, respectively). * P < 0.05; n.s. not significant. Data were shown as Mean ± SD, n = 3 independent experiments. ( J ) Volcano plot of the cell surface proteome of USP12/46-dKO fibroblasts stably expressing EGFP-USP12 C48S versus EGFP-USP12 WT identified by label-free MS. P values were determined using two-sided permuted t -test with 250 randomizations. The black dashed line indicates the significance cutoff (FDR:0.05, S0:0.1) estimated by the Perseus software. n = 4 biological replicates. Arbitrarily selected cell surface receptors were highlighted in red. .

Article Snippet: The CRISPR screen for human DUBs was carried out as previously described (Paulmann et al, ) with slight modifications.

Techniques: CRISPR, Expressing, Transduction, Flow Cytometry, Software, Clone Assay, Comparison, Control, Stable Transfection

Journal: bioRxiv

Article Title: Riboflavin drives nucleotide biosynthesis and iron-sulfur metabolism to promote acute myeloid leukemia

doi: 10.1101/2025.06.26.661633

Figure Lengend Snippet: A . Volcano plot of relative fold change (log 2 ) in metabolite abundance in NB4 cells upon RFK deletion versus Rosa control at day 9 ranked by significance. The dotted line denotes P < 0.05. Blue circles, starch/sucrose/nucleotide sugar metabolism; green circles, nucleotide metabolism; yellow circles, phosphatidylethanolamine/phosphatidylcholine metabolism. B . Dot plot of genetic co-dependency of genes with RFK ranked by Pearson correlation. Data from DepMap 24Q2. Blue shading denotes nucleotide metabolism-associated genes. C . Heatmap of nucleotide metabolites in RFK deleted NB4 cells versus Rosa controls cultured in RPMI for 7 days. Relative log 2 of metabolite abundances shown. Data representative of n =4 biological replicates per condition. D . Western immunoblot for DHODH in NB4 and MV4-11 cells upon genetic KO of RFK for 9 days (left) or 4 and 7 days of exogenous riboflavin starvation (right). β-Actin served as the loading control. Blot membrane was stripped and re-probed for other proteins of interest, and data from the same gel, including loading control, are also used in Figure S5A. E . Schema of CRISPR screen using metabolic library in NB4 cells cultured in Plasmax complete or riboflavin depleted medium. F . Dot plot of genes ranked by relative log 2 enrichment or depletion in Plasmax complete versus riboflavin depleted culture medium as measured by sgRNA abundance. Genes whose abundance increased conferred resistance to riboflavin depletion. Red denotes genes associated with purine biosynthesis. G . Cell number of NB4 cells at day 6 post culture in Plasmax complete or lacking riboflavin and treated with vehicle (water), or cocktails of purine (A+G, adenosine + guanosine) or pyrimidine (C+T, cytidine + thymidine) nucleosides. Cell number normalized to Complete + Vehicle. Data representative of n =3 biological replicates. H . Cell number of MV4-11 cells at day 8 post induction of Rosa or RFK sgRNAs, treated with vehicle (water), or cocktails of purine (A+G, adenosine + guanosine) or pyrimidine (C+T, cytidine + thymidine) nucleosides in Plasmax medium for 4 days. Cell number normalized to sgRosa + Vehicle. Data representative of n =3 biological replicates. I . Western immunoblot for γH2A.X in MV4-11 cells at day 8 post induction of Rosa or RFK sgRNAs, treated with vehicle (water), or cocktails of purine (A+G, adenosine + guanosine) or pyrimidine (C+T, cytidine + thymidine) nucleosides in Plasmax medium for 4 days. Short exposure (top) and long exposure (bottom). Vinculin served as the loading control. J . Dot plot of the correlation between RFK dependency and metabolite abundance in the DepMap 24Q2 dataset ranked by significance. Each circle denotes an individual metabolite. Dotted line denotes P < 0.05. Data are presented as the mean ± SD. ** P < 0.01, *** P < 0.001 and **** P < 0.0001 by ordinary two-way ANOVA with Bonferroni’s multiple comparisons test (G, H).

Article Snippet: D.E.R. generated the metabolic CRISPR screen library at the Broad Institute Genomic Perturbation Platform (GPP) and provided critical technical and conceptual expertise.

Techniques: Control, Starch, Cell Culture, Western Blot, Membrane, CRISPR

Journal: bioRxiv

Article Title: Riboflavin drives nucleotide biosynthesis and iron-sulfur metabolism to promote acute myeloid leukemia

doi: 10.1101/2025.06.26.661633

Figure Lengend Snippet: A . Dot plot of differentially altered metabolites upon exogenous depletion of riboflavin compared to complete medium (y-axis) at day 4 (top graph) and day 7 (bottom graph), versus deletion of RFK at day 9 (both graphs, x- axis). Relative log 2 of metabolite abundances shown. Highlighted metabolites belong to the metabolic processes indicated. B . Quantification of riboflavin, FMN and FAD in NB4 cells upon 9 days of RFK knockout versus Rosa control via metabolite profiling (top) and in NB4 cells upon 4 and 7 days of exogenous riboflavin depletion versus complete medium (bottom). Normalized peak area of n =4 biological replicates for each condition shown. C . Bubble plots of gene ontology metabolite sets showing pathways associated with metabolites with decreased abundance (left) and increased abundance (right). P -values are reported. Pathway enrichment performed using MetaboAnalyst 6.0. D . Schema of the Kennedy Pathway (left) and heatmap of key pathway intermediates in NB4 cells after 9 days of RFK depletion versus Rosa control. Scale depicts normalized peak area of each metabolite. E . Dot plot of genetic co-dependency of genes with RFK ranked by Pearson correlation. Data from DepMap 24Q2. Yellow shading denotes choline metabolism-associated genes. F . Cell number of NB4 and MV4-11 cells at day 8 post induction of Rosa or RFK sgRNAs, treated with vehicle (water), or 10 mM or 20 mM aspartate in Plasmax medium for 4 days. Cell number normalized to sgRosa + Vehicle. Data representative of n =3 biological replicates. G . Schema of the design and generation of metabolism-focused CRISPR-Cas9 library. H . Cell number of MV4-11 cells at day 8 post induction of Rosa or RFK sgRNAs, treated with vehicle (water), or cocktails of purine (A+G, adenosine + guanosine) or pyrimidine (C+T, cytidine + thymidine) nucleosides in RPMI medium for 4 days. Cell number normalized to sgRosa + Vehicle. Data representative of n =3 biological replicates. I . Cell number of MV4-11 cells at day 8 post induction of Rosa or RFK sgRNAs, treated with vehicle (water), cytidine or 2’-deoxycytidine nucleosides in Plasmax medium for 4 days. Cell number normalized to sgRosa + Vehicle. Data representative of n =3 biological replicates. Data are presented as the mean ± SD. ** P < 0.01, **** P < 0.0001 by unpaired two-tailed Student’s t -test (B), and ordinary two-way ANOVA with Bonferroni’s multiple comparisons test (B, F, H, I).

Article Snippet: D.E.R. generated the metabolic CRISPR screen library at the Broad Institute Genomic Perturbation Platform (GPP) and provided critical technical and conceptual expertise.

Techniques: Knock-Out, Control, CRISPR, Two Tailed Test

Journal: bioRxiv

Article Title: Riboflavin drives nucleotide biosynthesis and iron-sulfur metabolism to promote acute myeloid leukemia

doi: 10.1101/2025.06.26.661633

Figure Lengend Snippet: A . Dot plot of genes ranked by relative log 2 enrichment or depletion in Plasmax complete versus riboflavin depleted culture medium as measured by sgRNA abundance. Genes whose abundance decreased conferred sensitivity to riboflavin depletion. Colors show indicated gene families. B . Dot plot of genetic co-dependency of genes with RFK ranked by Pearson correlation. Data from DepMap 24Q2. Purple shading indicates iron-sulfur cluster containing genes, and orange iron starvation response-associated genes. C . Simplified schema of the synthesis of [2Fe-2S] iron-sulfur clusters, their trafficking, and involvement in the synthesis of [4Fe-4S] iron-sulfur clusters. The client proteins of [4Fe-4S] clusters are highlighted, and stars indicate CRISPR screen hits that sensitize cells to death upon riboflavin starvation. D . Western immunoblot analysis of indicated proteins in cell lysates isolated from NB4 and MV4-11 cells at day 5 (left blots) and day 9 (right blots) post induction of Rosa or RFK sgRNAs. β-Actin served as the loading control. E . Volcano plot of relative fold change (log 2 ) of differentially regulated genes versus −log 10 ( P -values) in NB4 cells upon RFK deletion in RPMI medium at day 7. F . Aconitase activity (mOD/min/μg of protein) in whole-cell lysates of RFK deleted NB4 cells at day 9. mOD, milli optical density. Data representative of n =3 biological replicates. G . Cell number of NB4 and MV4-11 cells at day 7 post induction of Rosa or RFK sgRNAs, or day 7 post riboflavin starvation, treated with vehicle (DMSO, dimethyl sulfoxide), or the iron chelator deferoxamine (DFO) for 3 days. Cell number normalized to sgRosa + DMSO, or Plasmax Complete medium + DMSO. Data representative of n =3 biological replicates. Data are presented as the mean ± SD. *** P < 0.001, **** P < 0.0001 by unpaired two-tailed Student’s t -test (F) and ordinary two-way ANOVA with uncorrected Fisher’s LSD test (G).

Article Snippet: D.E.R. generated the metabolic CRISPR screen library at the Broad Institute Genomic Perturbation Platform (GPP) and provided critical technical and conceptual expertise.

Techniques: CRISPR, Western Blot, Isolation, Control, Activity Assay, Two Tailed Test