Journal: Microbiology Spectrum

Article Title: Virtual Screening and In Vitro Experimental Verification of LuxS Inhibitors for Escherichia coli O157:H7

doi: 10.1128/spectrum.03502-22

Figure Lengend Snippet: Structure of LuxS protein of E. coli . (A) The pocket (red) of LuxS protein binds to a small-molecule pocket. The length, width, and depth of the pocket are 21.33, 26.50, and 18.67 Å, respectively. (B) The amino acids in the small-molecule binding pocket of the sequence are labeled red. (C) In the pocket attribute, the red part is the metal-binding site, and the green part was the methionine-binding site.

Article Snippet: The ChemDiv database, a commercially available small-molecule database from Shanghai TopScience Biotechnology Co. with more than 1 million compounds, was used as the screening library.

Techniques: Binding Assay, Sequencing, Labeling

Journal: Scientific Data

Article Title: Comprehensive genome-scale CRISPR knockout screening of CHO cells

doi: 10.1038/s41597-025-04438-6

Figure Lengend Snippet: Schematic illustration of a non-viral, genome-scale CRISPR screening platform in Chinese hamster ovary (CHO) cells. ( a ) Plasmid library construction. CHO genome-wide CRISPR guide RNA (gRNA) oligonucleotides were designed and synthesized. Recombinase mediated cassette exchange (RMCE) donor plasmid library was then constructed by cloning gRNA oligos into a backbone plasmid that contained a promoter-less puromycin resistance (PuroR) gene and gRNA scaffold, flanked by attB and mutant attB recombination sites. The plasmid library was verified using next-generation sequencing (NGS) analysis. ( b ) Workflow of cell library and knockout (KO) library development. The CHO-K1 host and recombinant cell-based master cell lines (MCLs) were established through CRISPR/Cas9-mediated site-specific integration (SSI) of the landing pad (LP) plasmid donor, which contained mCherry and hygromycin resistance (HygR) gene flanked by attP and mutant attP recombination sites. The host and recombinant cell libraries were generated through the Bxb1-att recombination system and puromycin selection. Promoter-trapping ensures the expression of a single gRNA per cell. The host and recombinant KO libraries were then generated through transient Cas9 expression and blasticidin semi-selection. The distribution of gRNAs in the pooled cell libraries and KO libraries was confirmed using NGS analysis. The KO libraries were also analyzed after long-term cultivation. ( c ) Functional genomic screens. Phenotypes of interest in the KO library can be enriched through reporter-based fluorescence-activated cell sorting (FACS) or pool selection under selective pressure. Highly productive recombinant cell populations were sorted in this study. The distribution of gRNAs was confirmed using NGS analysis. The screening hits are candidate targets for KO cell engineering.

Article Snippet: CRISPR screening data analysis is available at https://sourceforge.net/p/mageck/wiki/Home/#usage and http://pinapl-py.ucsd.edu .

Techniques: CRISPR, Plasmid Preparation, Genome Wide, Synthesized, Construct, Cloning, Mutagenesis, Next-Generation Sequencing, Knock-Out, Recombinant, Generated, Selection, Expressing, Functional Assay, Fluorescence, FACS

Journal: Scientific Data

Article Title: Comprehensive genome-scale CRISPR knockout screening of CHO cells

doi: 10.1038/s41597-025-04438-6

Figure Lengend Snippet: The development process of the cell and KO libraries using a non-viral genome-scale CRISPR screening platform. Entire profiles of ( a ) viability and ( b ) cell growth (VCD; viable cell density) during the generation of the cell (red solid lines) and KO (blue solid lines) libraries in both CHO-K1 host and recombinant cells. Arrows indicate the transfection of RMCE (red) and Cas9 (blue). Shaded areas denote periods of chemical treatment for cell library enrichment (red, puromycin) and KO library enrichment (blue, blasticidin). The pEGFP-c1 expression vector was used as the transfection control (green lines), while chemically untreated cells served as non-enriched controls (dotted lines). ( c ) The percentage of mCherry-negative populations in the CHO-K1 host (blue line) and recombinant cells (red line) during cell library development with and without puromycin selection. Dotted line indicates the threshold required to maintain 500 × gRNA coverage. The mCherry negativity in enriched populations indicated successful implementation of the genome-scale plasmid library into cells. ( d ) Bar plot showing the transfection efficiency of Cas9 in CHO-K1 host cells and recombinant cells as measured through 2 A peptide-linked reporter expression.

Article Snippet: CRISPR screening data analysis is available at https://sourceforge.net/p/mageck/wiki/Home/#usage and http://pinapl-py.ucsd.edu .

Techniques: CRISPR, Recombinant, Transfection, Expressing, Plasmid Preparation, Control, Selection

Journal: Cancers

Article Title: MiRNA Deregulation Distinguishes Anaplastic Thyroid Carcinoma (ATC) and Supports Upregulation of Oncogene Expression

doi: 10.3390/cancers13235913

Figure Lengend Snippet: Unsupervised analyses of small RNA expression data from 10 ATCs, 6 PTCs, 6 FTCs, and 6 nonmalignant human thyroid (NT, normal thyroid) samples of 85 miRNAs with significantly deregulated expression (DE) in ATC. ( A ) Principal component analysis (PCA) shows that DE miRNAs distinguish ATC from all other samples analyzed, except for ATC#10. ( B ) Hierarchical clustering of the 85 significantly deregulated miRNAs supports the PCA analyses and sharply distinguishes all ATC samples, except ATC#10. Rows are ordered by average log2 fold change of miRNA expression in ATC samples compared to all other samples analyzed. Normalized log2 CPM (counts per million mapped reads) expression values of identified miRNAs were used for both analyses.

Article Snippet: To integrate essentiality information of the determined miRNA target genes in ATC, pancancer loss-of-function CRISPR screens of nine ATC-derived cell lines (8305C, 8505C, MB1, ASH3, BHT101, CAL62, HOTHC, HTCC3, KMHDASH2) were utilized for a dependency analysis, using the Broad Institute Cancer Dependency Map (DepMap) portal (v 21Q1, [ ]).

Techniques: RNA Expression, Expressing

Journal: Cancers

Article Title: MiRNA Deregulation Distinguishes Anaplastic Thyroid Carcinoma (ATC) and Supports Upregulation of Oncogene Expression

doi: 10.3390/cancers13235913

Figure Lengend Snippet: The established analysis pipeline showing the rational for selection of prime miRNA–mRNA interactions in ATC. In brief, the miRNA and mRNA expression were determined by RNA-seq in indicated samples. Differential miRNA expression identified 85 differentially expressed (DE) miRNAs at the threshold of FDR < 0.01 and an average expression > 100 CPM. To identify key effector mRNAs of DE miRNAs, miRNA targeting was analyzed by in silico prediction using indicated databases. Candidate miRNA–mRNA interactions were further ranked by the fold change (FC) of target mRNA expression, average essentially scores (ES) were determined in ATC derived cells for target genes, and hazard ratios (HR) were determined by target mRNA expression in the TCGA thyroid cancer cohort (THCA). This led to an interaction score (IS) for each miRNA-mRNA interaction scaled as indicated. Finally, prime candidate oncogenic and tumor-suppressive target mRNAs were determined for the top scoring (IS = 1) target mRNA of each DE miRNA by the indicated parameters. This allowed a ranking of miRNA-controlled candidate oncogenic and tumor-suppressive factors via a scaled OncoScore (OS), as indicated. Bars indicate a scale of 100 µm.

Article Snippet: To integrate essentiality information of the determined miRNA target genes in ATC, pancancer loss-of-function CRISPR screens of nine ATC-derived cell lines (8305C, 8505C, MB1, ASH3, BHT101, CAL62, HOTHC, HTCC3, KMHDASH2) were utilized for a dependency analysis, using the Broad Institute Cancer Dependency Map (DepMap) portal (v 21Q1, [ ]).

Techniques: Selection, Expressing, RNA Sequencing, In Silico, Derivative Assay

Journal: Cancers

Article Title: MiRNA Deregulation Distinguishes Anaplastic Thyroid Carcinoma (ATC) and Supports Upregulation of Oncogene Expression

doi: 10.3390/cancers13235913

Figure Lengend Snippet: Gene Set Enrichment Analysis (GSEA) of total and miRNA-dependent differential mRNA expression in ATC. Columns indicate GSEA results using distinct mRNA selection: FC mRNA, all expressed mRNAs were ranked by their log fold change of expression in ATC compared to all other samples; DN miRNA, candidate target mRNAs with positive interaction scores (IS) determined for DN-miRNAs were ranked by their log fold change of expression in ATC compared to all other samples; UP miRNA candidate target mRNAs with positive interaction scores (IS) determined for UP-miRNAs also ranked by their log fold change of expression in ATC. Color coding indicates scaled normalized enrichment scores (NES) determined for indicated hallmark gene sets. NES scale bar is indicated.

Article Snippet: To integrate essentiality information of the determined miRNA target genes in ATC, pancancer loss-of-function CRISPR screens of nine ATC-derived cell lines (8305C, 8505C, MB1, ASH3, BHT101, CAL62, HOTHC, HTCC3, KMHDASH2) were utilized for a dependency analysis, using the Broad Institute Cancer Dependency Map (DepMap) portal (v 21Q1, [ ]).

Techniques: Expressing, Selection

Journal: Cancers

Article Title: MiRNA Deregulation Distinguishes Anaplastic Thyroid Carcinoma (ATC) and Supports Upregulation of Oncogene Expression

doi: 10.3390/cancers13235913

Figure Lengend Snippet: High ranking miRNA–mRNA interactions identify miRNA-dependent regulation of oncogenic and tumor-suppressive factors in ATC. ( A ) Hierarchical clustering of the top scoring (IS = 1) target mRNAs of the 85 DE miRNAs sharply distinguish all ATC samples. Samples were ordered by the scaled OncoScore (OS), indicating the oncogenic (top score 1) vs. tumor-suppressive (top score −1) potential of the respective genes. Gene symbols are indicated in the left panel. Log2 transformed FPKM expression values of indicated mRNAs scaled to low and high expression range [−1, 1] are depicted by a heatmap in the middle panel. Prime targeting miRNAs of indicated mRNAs are indicated in the right panel along with the scaled [−1, 1] fold change of miRNA expression in ATC vs. others. ( B , C ) Expression and miRNA targeting of the prime oncogene upregulated by miRNA downregulation (BIRC5, ( B )) and the prime tumor-suppressor candidate decreased by miRNA upregulation (FRMD3, ( C )). Boxplots (left panels) show BIRC5 and FRMD3 mRNA (log2 FPKM) expression in ATC and others; **** p < 0.0001. Schemes (middle panels) depict the meta 3′-UTR of selected genes with predicted binding sites for targeting miRNAs with average expression >100 CPM. Fold change of miRNA expression is indicated by up/down bars scaled by fold change of expression. Color coding indicates significant deregulation (FDR < 0.01). Nonsignificant in grey. The sum CPM of targeting miRNAs sorted by significant (color coded) or insignificant change of expression (grey) is indicated in the right panels.

Article Snippet: To integrate essentiality information of the determined miRNA target genes in ATC, pancancer loss-of-function CRISPR screens of nine ATC-derived cell lines (8305C, 8505C, MB1, ASH3, BHT101, CAL62, HOTHC, HTCC3, KMHDASH2) were utilized for a dependency analysis, using the Broad Institute Cancer Dependency Map (DepMap) portal (v 21Q1, [ ]).

Techniques: Transformation Assay, Expressing, Binding Assay

Journal: Cancers

Article Title: MiRNA Deregulation Distinguishes Anaplastic Thyroid Carcinoma (ATC) and Supports Upregulation of Oncogene Expression

doi: 10.3390/cancers13235913

Figure Lengend Snippet: Expression of miRNA-dependent oncogenic factors DTL and TFRC distinguishes ATC. ( A ) Expression of DTL and TFRC analyzed by immunohistochemistry (IHC) in representative samples derived from a tissue microarray (TMA). H&E, hematoxylin eosin staining; magnification 1:40; bars indicate a scale of 50 µm. ( B , C ) Evaluation of IHC samples by histoscore (H-score). Violin plots show the H-score distributions determined for DTL ( B ) and TFRC ( C ) in indicated samples. ANOVA testing confirms significantly distinct expression. Gene specific OncoScores (OS) are depicted in top panels.

Article Snippet: To integrate essentiality information of the determined miRNA target genes in ATC, pancancer loss-of-function CRISPR screens of nine ATC-derived cell lines (8305C, 8505C, MB1, ASH3, BHT101, CAL62, HOTHC, HTCC3, KMHDASH2) were utilized for a dependency analysis, using the Broad Institute Cancer Dependency Map (DepMap) portal (v 21Q1, [ ]).

Techniques: Expressing, Immunohistochemistry, Derivative Assay, Microarray, Staining