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Journal: Cells
Article Title: MDM2 Drives Proteasome Inhibitor Resistance and Represents a TP53-Independent Therapeutic Vulnerability in Multiple Myeloma
doi: 10.3390/cells15090831
Figure Lengend Snippet: Complementary functional screenings identify MDM2 as a modulator of carfilzomib (CFZ) resistance in multiple myeloma. ( A ) Schematic overview of the complementary screening strategies. A gain-of-function (GOF) CRISPR activation (CRISPRa) screen was performed in PI-sensitive AMO-1 CVPH cells treated with CFZ or DMSO to identify modulators of CFZ resistance. In parallel, a loss-of-function (LOF) pharmacological screen using a 320-compound library was conducted to identify compounds exhibiting synthetic lethality with CFZ. Both approaches converged on MDM2. ( B ) Log 2 -normalized read counts of sgRNAs targeting MDM2 at the end of the CRISPRa screen (T_end). sgRNA enrichment is shown relative to the mean read counts in DMSO- or CFZ-treated conditions at T_end. The most enriched sgRNAs selected for individual validation are indicated by asterisks. ( C – F ) AMO-1 CVPH cells were transduced with two independent sgRNAs targeting MDM2 or a non-targeting control sgRNA (sgCTRL). ( C , D ) MDM2 transactivation was confirmed at the mRNA and protein levels by RT–qPCR and immunoblotting, respectively. Band quantification values are indicated above each band (band intensities were normalized to β-actin and subsequently to the sgCTRL control). ( E ) Cells were subsequently treated with CFZ, and cell viability was assessed 72 h post-treatment by flow cytometry after staining with tetramethylrhodamine methyl ester (TMRM). ( F ) Recovery following treatment with 5 nM CFZ was evaluated after 7 days as above. Data represent mean ± SD of three independent experiments. Immunoblots are representative of three independent experiments. Statistical significance was determined by one-way ANOVA (* p < 0.05; ** p < 0.01; **** p < 0.0001).
Article Snippet: Equal amounts of complementary
Techniques: Functional Assay, CRISPR, Activation Assay, Drug discovery, Biomarker Discovery, Transduction, Control, Quantitative RT-PCR, Western Blot, Flow Cytometry, Staining
Journal: bioRxiv
Article Title: The phenotypic landscape of the model firmicute Bacillus subtilis
doi: 10.64898/2026.05.13.724699
Figure Lengend Snippet: A-B. RFs are reproducible across conditions. RF of all sgRNAs plotted pairwise from each experimental replicate of every condition (done in triplicate): 11,566 sgRNAs x 149 conditions ≈ 1.7 million RF values per replicate. Pearson’s r for all comparisons > 0.95. Condition replicates with severely abnormal median sgRNA behavior and/or outlier correlation values to the other triplicates generally indicate bottlenecking from read depth and were excluded during preprocessing prior to this analysis (Methods). 100,000 randomly chosen data points are displayed (out of approximately 1.7 million). C. RF of sgRNAs shared between our library and previous work are consistent. sgRNAs were selected from ref . Lower minimum RF in ref reflects a higher sequencing depth in that study. Pearson’s r = 0.88. D. RF of fully-complementary sgRNAs targeting genes designated as “nonessential”, “impaired” or “essential” based on their single gene deletion phenotypes in KanR or ErmR libraries from ref . Box bounds: first and third quartile, midline: median, whiskers: most extreme datapoints. sgRNAs targeting nonessential genes with RF < 0.9 may reflect polar knockdown effects on essential operon partners.
Article Snippet:
Techniques: Sequencing, Knockdown
Journal: bioRxiv
Article Title: The phenotypic landscape of the model firmicute Bacillus subtilis
doi: 10.64898/2026.05.13.724699
Figure Lengend Snippet: A. Gene-chemical S-Scores of genes involved in the elongasome or divisome against the cell-wall drug cefaclor and the FAS inhibitors cerulenin and triclosan. As expected, knockdown of genes comprising both the elongasome and divisiome (the PG synthesis machineries) are sensitized to the β-lactam cefaclor. In contrast, inhibition of FAS by triclosan or cerulenin generally had a protective effect on knockdown of elongasome genes, but a sensitizing effect on knockdown of divisome genes. Drug concentrations with strongest S-scores are displayed. For genes targeted by multiple knockdown bins, only the most responsive bin (greatest sum of absolute S-scores across the drug concentrations used) is shown. B. RF values of mntR knockdown and sufD knockdown across all conditions. For sufD , the average RF of the two fully-complementary sgRNAs is plotted. Blue = dipyridyl (iron chelator), Green = excess manganese, Purple = minimal and glucose complete media, Red = mupirocin.
Article Snippet:
Techniques: Knockdown, Inhibition
Journal: bioRxiv
Article Title: The phenotypic landscape of the model firmicute Bacillus subtilis
doi: 10.64898/2026.05.13.724699
Figure Lengend Snippet: A. Growth of B. subtilis mutant strains grown as single colonies of knockouts on minimal media agar plates (x-axis, ) or in pooled liquid minimal media culture growth of this knockdown library (y-axis) (all genes present in both libraries; n = 3774 genes). For single colonies, WT growth is signified as a RF of 1.0. For growth in liquid culture, WT growth is signified as a RF of 1.0. Error bars signify standard deviation of RF values in minimal media of the two targeting sgRNAs in pooled culture. Auxotrophs are highlighted in red (defined in ref ). Cross-feeding behavior of a strain would manifest as a RF of 0 as single colonies and a RF of 1.0 in pooled culture (upper left quadrant). B. Growth of E. coli knockout strains grown as single colonies on minimal media agar plates (x-axis, ) or in pooled liquid minimal media culture growth (y-axis, ) (all genes present in both screens; n = 3410 genes). For single colonies, WT growth is signified as an S-score of 0. For growth in liquid culture, WT growth is signified as a L2FC of 0. Error bars signify standard deviation of two separate measurements of growth in pooled culture. Auxotrophs are highlighted in red (defined in ref ). Cross-feeding behavior of a strain would manifest as a negative S-score (i.e. S-score < -5) as single colonies and a L2FC of 0 in pooled culture (upper left quadrant).
Article Snippet:
Techniques: Mutagenesis, Knockdown, Standard Deviation, Knock-Out
Journal: bioRxiv
Article Title: CPT1A loss promotes lung metastasis in immune-competent mice via a mechanism of mtDNA release and chronic activation of STING pathway
doi: 10.64898/2026.05.01.722261
Figure Lengend Snippet: a , 4T1 cells transduced with metabolism-focused CRISPR KO lentiviral library were implanted into the mammary fat pad (MFP) of BALB/c Rag1 -/- or BALB/c wild type mice. Primary tumors were surgically removed on day 21 after transplantation and whole lung was collected (4-9 weeks). n ≥ 3 mice per group. b , The differential abundance (log 2 FC) of sgRNA corresponding genes in the lungs between Rag1 -/- and wild type (WT) mice. Target gene sgRNAs were normalized to non-targeted control sgRNA (sgNTC). Cpt1a was enriched in WT mice. c , The log 2 -transformed Cpt1a sgRNA reads from the primary tumors (1° tumors) or lung metastases (lung mets.) between Rag1 -/- and WT mice. Welch’s t-test, p=0.688 (1° tumors), p=0.00199 (lung mets.) d , Diagram of in vivo metastasis competition assay in Rag1 -/- or BALB/c WT mice. Primary tumors were resected on day 14 (4T1) or day 18 (EO771) post-implantation, and whole lungs were collected 2 weeks and 4 weeks after 4T1, EO771 tumor resection, respectively. e-f , Normalized Cpt1a sgRNA (fold change) from primary tumors or lung metastases upon MFP injection of sgNTC control, or Cpt1a -KO 4T1 ( e ) or EO771 ( f ) into immune competent hosts (BALB/c) or immune deficient hosts ( Rag1 -/- ). n ≥ 4 mice per group. Proportions of sgNTC vs s sgCpt1a cells at implantation are shown (Input). Welch’s t-test was performed. g , Oxygen consumption rate (pmol/min) in sgNTC control (Ctrl), Cpt1a -KO (KO) 4T1 cells or KO cells re-expressing WT or D454G CPT1A, per 5×10 4 cells. Maximal respiration capacity OCR is shown. One-way ANOVA (p=4.32×10 -6 ) with Tukey’s post hoc. h-j, 4T1 control, Cpt1a -KO, or re-expression WT or D454G CPT1A in Cpt1 a-KO cells were implanted into the mammary fat pad of BALB/c mice (n=9), followed by primary tumor resection and lung metastatic growth. ( h ) Primary tumor volume was tracked over time. Two-way ANOVA (p=0.345). ( i ) Numbers of lung surface metastases at was determined at sacrifice. One-way ANOVA (p=1.17×10 -4 ) with Tukey’s post-hoc. ( j ) Survival of mice inoculated with 4T1 control, Cpt1a -KO, or re-expression WT or D454G CPT1A in Cpt1 a-KO tumors (n=15). *p<0.05, **p<0.01, ***p<0.005, ****p<0.001. ns, not significant.
Article Snippet: A metabolism-focused loss-of-function sgRNA library was utilized, targeting 101 metabolic genes with four sgRNAs per gene as well as ten non-targeting control sgRNAs (Supplemental Table 2).
Techniques: Transduction, CRISPR, Transplantation Assay, Control, Transformation Assay, In Vivo, Competitive Binding Assay, Injection, Expressing
Journal: bioRxiv
Article Title: Reprogramming of neuronal genome function and phenotype by astrocytes
doi: 10.64898/2026.03.07.710282
Figure Lengend Snippet: (A) Volcano plot showing the changes of n=222 ArN TF genes selected for Perturb-seq between N and N+A conditions, average of 4 time points. (B) Table showing statistics of sgRNA library design and data quality metrics for CRISPRi and CRISPRa pRE screens. (C) Scatterplot of showing the numbers of CRISPRi vs CRISPRa pRE targets per ArN TF gene, with genes that are up-regulated by astrocytes at the mRNA level colored in red, and genes down-regulated by astrocytes colored by blue. (D) Barplot showing that the dCas9-p300 cell line activates GRIN2A and MYOD genes by sgRNAs targeted at promoters and a distal regulatory element in differentiated neurons. (E) Histogram showing the distributions of base-pair distance between functional RE and target genes identified in the CRISPRi and CRISPRa pRE screens, respectively. (F) Barplots showing the distribution of # of target genes assigned to a functional RE, and # of functional REs assigned to a target gene, respectively. (G) Barplot showing the effects of CRISPRi on two different functional REs of the TF gene SIX3. The statistical test was done by one-way ANOVA followed by Tukey’s multiple comparisons test. **: adjusted p<0.01; ***: adjusted p<0.001. (H) Schematics showing a high-level overview of the single-cell analysis pipeline of the Perturb-seq screens, highlighting the methods used.
Article Snippet: The
Techniques: Functional Assay, Single-cell Analysis
Journal: bioRxiv
Article Title: Reprogramming of neuronal genome function and phenotype by astrocytes
doi: 10.64898/2026.03.07.710282
Figure Lengend Snippet: (A) Stacked bar plots showing the numbers of targeted annotated primary TSSs, alternative TSSs, and unannotated TSSs based on the RNA-seq data generated in this study, in the CRISPRi/a promoter Perturb-seq experiments, respectively. (B) Table showing statistics of sgRNA library design and data quality metrics for CRISPRi and CRISPRa promoter screens. (C) Violin plot showing the number of cells per target region in the CRISPRa promoter Perturb-seq experiment, highlighting the MYC promoter as an outlier. (D) Violin plot showing the log2FC of the direct target genes in the CRISPRi and CRISPRa promoter Perturb-seq experiments, respectively, separated by positive controls (regardless of significance), TF genes with significant alteration in expression level (Sig. perturb.; p < 0.05), and TF genes with non-significant alteration (N.S. perturb.; p >= 0.05). (E) Jitter plot showing the basal expression levels of CRISPRi promoter target genes that were successfully (‘success’) or unsuccessfully (‘fail’) repressed (F) Bar plot showing the numbers of total global perturbation-gene links discovered by the 4 Perturb-seq experiments. Only those from the positive controls, statistically significant promoters (for the promoter experiments), and fREs (for the pRE experiments) are shown. (G) Jitter plot showing the numbers of global perturbation-gene links per perturbation. Only those from the positive controls, statistically significant promoters (for the promoter experiments), and fREs (for the pRE experiments) are shown. Top perturbations are labeled by its local or direct target gene, for fRE and promoter, respectively. Red bolded are positive controls.
Article Snippet: The
Techniques: RNA Sequencing, Generated, Expressing, Labeling