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Elabscience Biotechnology mouse th17 cell flow cytometry staining kit
Mouse Th17 Cell Flow Cytometry Staining Kit, supplied by Elabscience Biotechnology, used in various techniques. Bioz Stars score: 96/100, based on 2 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 96 stars, based on 2 article reviews

mouse th17 cell flow cytometry staining kit - by Bioz Stars, 2026-05

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a) Schematic of project design. Stage 1: Isolate ATAC-seq fragments from in vitro derived Th0, Th1, Th2, Th17 and Treg CD4+ subsets to build ATAC-STARR-seq libraries. Stage 2: Assay all the unified pool of CD4+ OCRs in each CD4+ subset. Stage 3: Endogenous perturbations of Th17 OCRs using CRISPR-based epigenome editing screens. Stage 4: in vitro and in vivo validation of Th17 enhancer function followed by flow cytometry readouts for cell phenotype b) Genome browser track depicting the union ATAC-STARR-seq input library (grey) and STARR-seq activity score (Log2 CPM RNA/DNA; coloured) at the Bach2 locus for each subset. c) Upset plot of OCR intersections between all CD4 T cell subsets, with the proportion of STARR-seq active OCRs for each intersection highlighted in yellow. d) Stacked bar plots indicating the total number of OCRs tested in ATAC-STARR-seq and the proportion of OCRs with significant STARR-seq activity in that subset (dark colour), any subset (light colour) or tested but not significant (grey; fdr < 0.05). e) Total STARR-seq enhancer calls by subset (FDR < 0.05) with the proportion of functional OCRs by chromatin category (Subset shared = purple; multiple subsets = blue; subset unique = red) f) Effect sizes of significant enhancer calls for each cell type (Log2 RNA/DNA) g) Genome annotation of OCRs mapped by ATAC-seq (grey) or functional OCRs determined by STARR-seq (active = red; repressive = blue) for each subset. h) Violin plot showing distribution and median transcript abundance of genes nearest to OCRs categorized by ATAC-STARR-seq enhancer call significance for that subset (sig = STARR FDR < 0.05; n.s = non-significant; all p ∼ 0 for sig vs n.s, Mann-Whitney U Test) i) Radial plot of STARR-seq regulatory activity preference across CD4+ T cell subsets. Each axis represents a tested subset (Th0, Th1, Th2, Th17, Treg), and each point represents an active OCR with significant STARR-seq activity in at least one subset (FDR < 0.01). A weighted activity score (|Log2FC| x -log10(FDR)) of each OCR was calculated for each subset, normalized to sum to one across all subsets, and projected into 2D using angular coordinates. OCRs with STARR-seq activity biased toward a single subset fall near the corresponding spoke, while OCRs with equivalent activity across subsets fall near the center. Points are coloured by the subset in which the OCR exhibits its highest activity score. j) Odds ratio of top enriched motif families at subset-preferred OCRs. For each enhancer-preference group (subset-preferred, r = 0.85; subset-shared, r=0.3), odds ratios were computed for the preferred OCR set against all others. Top motif families are shown.

Journal: bioRxiv

Article Title: Enhancer hubs govern chromatin topology and Th17 identity

doi: 10.64898/2026.04.02.715458

Figure Lengend Snippet: a) Schematic of project design. Stage 1: Isolate ATAC-seq fragments from in vitro derived Th0, Th1, Th2, Th17 and Treg CD4+ subsets to build ATAC-STARR-seq libraries. Stage 2: Assay all the unified pool of CD4+ OCRs in each CD4+ subset. Stage 3: Endogenous perturbations of Th17 OCRs using CRISPR-based epigenome editing screens. Stage 4: in vitro and in vivo validation of Th17 enhancer function followed by flow cytometry readouts for cell phenotype b) Genome browser track depicting the union ATAC-STARR-seq input library (grey) and STARR-seq activity score (Log2 CPM RNA/DNA; coloured) at the Bach2 locus for each subset. c) Upset plot of OCR intersections between all CD4 T cell subsets, with the proportion of STARR-seq active OCRs for each intersection highlighted in yellow. d) Stacked bar plots indicating the total number of OCRs tested in ATAC-STARR-seq and the proportion of OCRs with significant STARR-seq activity in that subset (dark colour), any subset (light colour) or tested but not significant (grey; fdr < 0.05). e) Total STARR-seq enhancer calls by subset (FDR < 0.05) with the proportion of functional OCRs by chromatin category (Subset shared = purple; multiple subsets = blue; subset unique = red) f) Effect sizes of significant enhancer calls for each cell type (Log2 RNA/DNA) g) Genome annotation of OCRs mapped by ATAC-seq (grey) or functional OCRs determined by STARR-seq (active = red; repressive = blue) for each subset. h) Violin plot showing distribution and median transcript abundance of genes nearest to OCRs categorized by ATAC-STARR-seq enhancer call significance for that subset (sig = STARR FDR < 0.05; n.s = non-significant; all p ∼ 0 for sig vs n.s, Mann-Whitney U Test) i) Radial plot of STARR-seq regulatory activity preference across CD4+ T cell subsets. Each axis represents a tested subset (Th0, Th1, Th2, Th17, Treg), and each point represents an active OCR with significant STARR-seq activity in at least one subset (FDR < 0.01). A weighted activity score (|Log2FC| x -log10(FDR)) of each OCR was calculated for each subset, normalized to sum to one across all subsets, and projected into 2D using angular coordinates. OCRs with STARR-seq activity biased toward a single subset fall near the corresponding spoke, while OCRs with equivalent activity across subsets fall near the center. Points are coloured by the subset in which the OCR exhibits its highest activity score. j) Odds ratio of top enriched motif families at subset-preferred OCRs. For each enhancer-preference group (subset-preferred, r = 0.85; subset-shared, r=0.3), odds ratios were computed for the preferred OCR set against all others. Top motif families are shown.

Article Snippet: Specifically, we empirically determined MNase (Worthington Biochemical, Cat #LS004797) chromatin fragmentation conditions for Naïve and Th17 cells to be 2U MNase for 12 minutes at 37C per 1M cells.

Techniques: In Vitro, Derivative Assay, CRISPR, In Vivo, Biomarker Discovery, Flow Cytometry, Activity Assay, Functional Assay, MANN-WHITNEY

a) Genome browser plot of the Il17a / Il17f locus (70kb window) integrating 500bp resolution region capture Micro-C (RCMC; ICE balanced, normalized by observed/expected), with 3D contacts annotated by dashed line and Il17a-5 enhancer contacts indicated by blue triangles; ATAC-STARR-seq pooled input DNA library coverage track containing DNA fragments from Th0 Th1 Th2 Th17 and Treg ATAC-seq (grey); ATAC-STARR-seq activity score (Log2 fold change CPM) from Th0 (blue), Th1 (orange), Th2 (red), Th17 (yellow) and Treg (green) RNA versus Input DNA; Effect sizes for gRNA in CRISPRi for Il17a and Il17f (grey = tested; red = FDR < 0.05). OCRs are labeled with direction (+/-) and distance (in Kbp) relative to nearest gene. b) Scatter plot comparing sgRNA effect sizes (Log2 fold change high vs low bin) for CRISPRi screens using Il17a and Il17f reporters (green = only Il17f, red = only Il17a, blue = both, grey = non-significant; FDR < 0.05). c) Distribution of elementwise sgRNA effect sizes grouped by top functional OCRs in both Il17a (left) and Il17f (right) CRISPRi screens (lines = tested gRNA per element, blue = FDR < 0.05). Density plot (top) shows distribution of effect sizes for all gRNA. d) Flow cytometry analysis summarizing frequency of IL-17a+ cells or e) geometric MFI of Il17f (HCR-FlowFish) expression from in vitro derived Th17 cells following CRISPRi-mediated perturbation with candidate gRNAs. f) Representative stacked histograms to show distribution of in vitro derived Th17 cell Il17a and Il17f signal (red) relative to non-transduced (grey) following CRISPRi-mediated repression with top candidate single gRNA. Statistical analysis was performed using one-way ANOVA with Dunnett’s post-hoc test versus NTC and sandwich standard error ( d ) or one-sample t-tests with Benjamini-Hochberg correction (e) . Data are shown as mean ± s.e.m. for gRNA-transduced (Thy1.1 + ) relative to non-transduced (Thy1.1-) cell signal; *** p<0.001; ** p<0.0001; * p<0.05.

Journal: bioRxiv

Article Title: Enhancer hubs govern chromatin topology and Th17 identity

doi: 10.64898/2026.04.02.715458

Figure Lengend Snippet: a) Genome browser plot of the Il17a / Il17f locus (70kb window) integrating 500bp resolution region capture Micro-C (RCMC; ICE balanced, normalized by observed/expected), with 3D contacts annotated by dashed line and Il17a-5 enhancer contacts indicated by blue triangles; ATAC-STARR-seq pooled input DNA library coverage track containing DNA fragments from Th0 Th1 Th2 Th17 and Treg ATAC-seq (grey); ATAC-STARR-seq activity score (Log2 fold change CPM) from Th0 (blue), Th1 (orange), Th2 (red), Th17 (yellow) and Treg (green) RNA versus Input DNA; Effect sizes for gRNA in CRISPRi for Il17a and Il17f (grey = tested; red = FDR < 0.05). OCRs are labeled with direction (+/-) and distance (in Kbp) relative to nearest gene. b) Scatter plot comparing sgRNA effect sizes (Log2 fold change high vs low bin) for CRISPRi screens using Il17a and Il17f reporters (green = only Il17f, red = only Il17a, blue = both, grey = non-significant; FDR < 0.05). c) Distribution of elementwise sgRNA effect sizes grouped by top functional OCRs in both Il17a (left) and Il17f (right) CRISPRi screens (lines = tested gRNA per element, blue = FDR < 0.05). Density plot (top) shows distribution of effect sizes for all gRNA. d) Flow cytometry analysis summarizing frequency of IL-17a+ cells or e) geometric MFI of Il17f (HCR-FlowFish) expression from in vitro derived Th17 cells following CRISPRi-mediated perturbation with candidate gRNAs. f) Representative stacked histograms to show distribution of in vitro derived Th17 cell Il17a and Il17f signal (red) relative to non-transduced (grey) following CRISPRi-mediated repression with top candidate single gRNA. Statistical analysis was performed using one-way ANOVA with Dunnett’s post-hoc test versus NTC and sandwich standard error ( d ) or one-sample t-tests with Benjamini-Hochberg correction (e) . Data are shown as mean ± s.e.m. for gRNA-transduced (Thy1.1 + ) relative to non-transduced (Thy1.1-) cell signal; *** p<0.001; ** p<0.0001; * p<0.05.

Techniques: Activity Assay, Labeling, Functional Assay, Flow Cytometry, Expressing, In Vitro, Derivative Assay

a) Correlation of differential RNA-seq (All Subsets vs Th0) and nearest differential ATAC-seq (All Subsets vs Th0) peaks, split by promoter-proximal (< 3kbp) and distal (≥ 3kbp) from TSS, activating (Log2 RNA/DNA > 0) and repressive (Log2 RNA/DNA < 0) and coloured by magnitude of STARR-seq activity (Log2 RNA/DNA). b) Correlation of Th17 ATAC-seq signal at peak regions (Log2 CPM) against Th17 ATAC-STARR-seq activity score for all enhancers (Pearson’s r = -0.2). c) Correlation of Th17 ATAC-seq signal at peak regions (Log2 CPM) against ATAC-STARR-seq significance (-log10(padj); Pearson’s r = 0.12) d ) Pairwise correlation of transcript abundance (Log2 TPM) for all known transcription factors and epigenetic modifiers expressed in the CD4 T cell subsets of this study (Pearson’s correlations = 0.45-0.92). e) Expression levels (mean TPM) of transcription factor families shown in , averaged across family members, for each CD4 T cell subset at 72hrs post polarization.

Journal: bioRxiv

Article Title: Enhancer hubs govern chromatin topology and Th17 identity

doi: 10.64898/2026.04.02.715458

Figure Lengend Snippet: a) Correlation of differential RNA-seq (All Subsets vs Th0) and nearest differential ATAC-seq (All Subsets vs Th0) peaks, split by promoter-proximal (< 3kbp) and distal (≥ 3kbp) from TSS, activating (Log2 RNA/DNA > 0) and repressive (Log2 RNA/DNA < 0) and coloured by magnitude of STARR-seq activity (Log2 RNA/DNA). b) Correlation of Th17 ATAC-seq signal at peak regions (Log2 CPM) against Th17 ATAC-STARR-seq activity score for all enhancers (Pearson’s r = -0.2). c) Correlation of Th17 ATAC-seq signal at peak regions (Log2 CPM) against ATAC-STARR-seq significance (-log10(padj); Pearson’s r = 0.12) d ) Pairwise correlation of transcript abundance (Log2 TPM) for all known transcription factors and epigenetic modifiers expressed in the CD4 T cell subsets of this study (Pearson’s correlations = 0.45-0.92). e) Expression levels (mean TPM) of transcription factor families shown in , averaged across family members, for each CD4 T cell subset at 72hrs post polarization.

Techniques: RNA Sequencing, Activity Assay, Expressing

a) Schematic of the CRISPR-based screening workflow for identifying regulatory elements involved in Th17 differentiation. Naive CD4+ T cells were activated in vitro under Th0 conditions for 24h, followed by transduction with gRNAs targeting open chromatin regions. Cells were then polarized under Th17 conditions for 3 days and prepared for FACS using one of three readouts: i) eGFP expression (i.e Il17a), ii) fixed intracellular staining (i.e RORγt, BATF), or iii) hybridized chain reaction fluorescence in situ hybridization (i.e Il17a Il17f). Cells were finally sorted into high or low expression bins where gRNA abundance was compared. b) Scatter plot comparing sgRNA effect sizes (Log2 fold change hi/lo) between Th17 differentiation noncoding CRISPRi screens with Il17a-eGFP and RORγt readouts (blue = sgRNA significant in both; padj < 0.05). c) Distribution of element-wise effect sizes for gRNA (vertical lines) targeting OCRs in the Il17a- and RORγt-CRISPRi screens (lines = element-targeting gRNA, blue = padj < 0.05). d) Volcano plots depicting sgRNA effect sizes (Log2 fold change) comparing high/low bins for Il17a-eGFP (left) and RORγt(right), with top gRNA labelled (red = padj < 0.05). e ) Mean fluorescence intensity (MFI) of Il17a-eGFP (left) or RORyt (right) from in vitro derived Th17 cells following CRISPRi-mediated repression with individual candidate gRNAs, shown relative to non-targeting control (NTC). Box plots summarize n=5 per targeting gRNA, n=3 for Th0, n=3 for NTC. Statistical analysis was performed using one-way ANOVA with Dunnett’s test versus the NTC and sandwich standard error. Data are shown as mean ± s.e.m. relative to the NTC; * p <0.01; ** p < 0.001

Journal: bioRxiv

Article Title: Enhancer hubs govern chromatin topology and Th17 identity

doi: 10.64898/2026.04.02.715458

Figure Lengend Snippet: a) Schematic of the CRISPR-based screening workflow for identifying regulatory elements involved in Th17 differentiation. Naive CD4+ T cells were activated in vitro under Th0 conditions for 24h, followed by transduction with gRNAs targeting open chromatin regions. Cells were then polarized under Th17 conditions for 3 days and prepared for FACS using one of three readouts: i) eGFP expression (i.e Il17a), ii) fixed intracellular staining (i.e RORγt, BATF), or iii) hybridized chain reaction fluorescence in situ hybridization (i.e Il17a Il17f). Cells were finally sorted into high or low expression bins where gRNA abundance was compared. b) Scatter plot comparing sgRNA effect sizes (Log2 fold change hi/lo) between Th17 differentiation noncoding CRISPRi screens with Il17a-eGFP and RORγt readouts (blue = sgRNA significant in both; padj < 0.05). c) Distribution of element-wise effect sizes for gRNA (vertical lines) targeting OCRs in the Il17a- and RORγt-CRISPRi screens (lines = element-targeting gRNA, blue = padj < 0.05). d) Volcano plots depicting sgRNA effect sizes (Log2 fold change) comparing high/low bins for Il17a-eGFP (left) and RORγt(right), with top gRNA labelled (red = padj < 0.05). e ) Mean fluorescence intensity (MFI) of Il17a-eGFP (left) or RORyt (right) from in vitro derived Th17 cells following CRISPRi-mediated repression with individual candidate gRNAs, shown relative to non-targeting control (NTC). Box plots summarize n=5 per targeting gRNA, n=3 for Th0, n=3 for NTC. Statistical analysis was performed using one-way ANOVA with Dunnett’s test versus the NTC and sandwich standard error. Data are shown as mean ± s.e.m. relative to the NTC; * p <0.01; ** p < 0.001

Techniques: CRISPR, In Vitro, Transduction, Expressing, Staining, Fluorescence, In Situ Hybridization, Derivative Assay, Control

Browser track elaborating on chromatin architecture of the a) Il17a b) Rorc(t) c) Batf locus, and d) magnified view of the regulatory core region of Rorc(t). Contact heatmaps show RCMC of Tnaive (top) and Th17 (bottom) cells at 500 bp resolution. Track plots include signal from Th17 ATAC-seq, Th17, Th0, Th1, Th2 and Treg subset-specific STARR-seq (Log2 fold change RNA/DNA), CTCF ChIP-seq (CPM; Ciofani 2012) and CRISPRa/i screening (Log2 FC hi/lo).

Journal: bioRxiv

Article Title: Enhancer hubs govern chromatin topology and Th17 identity

doi: 10.64898/2026.04.02.715458

Figure Lengend Snippet: Browser track elaborating on chromatin architecture of the a) Il17a b) Rorc(t) c) Batf locus, and d) magnified view of the regulatory core region of Rorc(t). Contact heatmaps show RCMC of Tnaive (top) and Th17 (bottom) cells at 500 bp resolution. Track plots include signal from Th17 ATAC-seq, Th17, Th0, Th1, Th2 and Treg subset-specific STARR-seq (Log2 fold change RNA/DNA), CTCF ChIP-seq (CPM; Ciofani 2012) and CRISPRa/i screening (Log2 FC hi/lo).

Techniques: ChIP-sequencing

a) Genome browser view of Rorc and surrounding region (200k bp region) integrating 500bp RCMC contact map (ICE balanced, observed/expected normalization) and 3D interactions annotated by dotted lines; ATAC-STARR pooled Input library (blue), Th17 ATAC-STARR-seq activity score (Log2 CPM (RNA / DNA); yellow); CRISPRi- and CRISPRa-RORγt effect size (red = sgRNA FDR < 0.05; grey = tested); and OCR annotations label the direction (+/-) and distance (in Kbp) from nearest gene. b) Scatter plot comparing sgRNA effect sizes (Log2 fold change RORγt high vs low bins) from CRISPRi and CRISPRa screens (green = CRISPRa only; red = CRISPRi only; blue = both; grey = nonsignificant; FDR < 0.05). c) Element-wise distribution of effect sizes for both CRISPRi (left) and CRISPRa (right) (lines = element-tested gRNA; blue = FDR < 0.05) d) Zoomed in RCMC contact map (500bp resolution) focusing on the proximal RORγt locus (16kb window) with 3D contacts annotated as dotted lines, notable contact enrichments labelled with blue triangles, and corresponding Th17 ATAC-seq coverage track (blue) e) Frequency of IL-17a (blue) or MFI of RORγt (green) relative to non-targeting control (NTC) for in vitro derived Th17 cells following CRISPRi-mediated perturbation with top candidate gRNA from RORγt screening. f) Representative stacked histograms depicting RORγt and IL17a flow cytometry signal for Th17 cells transduced (Thy1+; blue/green) or nontransduced (Thy1-; grey) with candidate gRNAs. Statistical analysis was performed using one-way ANOVA with Dunnett’s test versus the NTC and sandwich standard error. Data are shown as mean ± s.e.m. relative to the NTC; * p <0.001; † p < 0.05.

Journal: bioRxiv

Article Title: Enhancer hubs govern chromatin topology and Th17 identity

doi: 10.64898/2026.04.02.715458

Figure Lengend Snippet: a) Genome browser view of Rorc and surrounding region (200k bp region) integrating 500bp RCMC contact map (ICE balanced, observed/expected normalization) and 3D interactions annotated by dotted lines; ATAC-STARR pooled Input library (blue), Th17 ATAC-STARR-seq activity score (Log2 CPM (RNA / DNA); yellow); CRISPRi- and CRISPRa-RORγt effect size (red = sgRNA FDR < 0.05; grey = tested); and OCR annotations label the direction (+/-) and distance (in Kbp) from nearest gene. b) Scatter plot comparing sgRNA effect sizes (Log2 fold change RORγt high vs low bins) from CRISPRi and CRISPRa screens (green = CRISPRa only; red = CRISPRi only; blue = both; grey = nonsignificant; FDR < 0.05). c) Element-wise distribution of effect sizes for both CRISPRi (left) and CRISPRa (right) (lines = element-tested gRNA; blue = FDR < 0.05) d) Zoomed in RCMC contact map (500bp resolution) focusing on the proximal RORγt locus (16kb window) with 3D contacts annotated as dotted lines, notable contact enrichments labelled with blue triangles, and corresponding Th17 ATAC-seq coverage track (blue) e) Frequency of IL-17a (blue) or MFI of RORγt (green) relative to non-targeting control (NTC) for in vitro derived Th17 cells following CRISPRi-mediated perturbation with top candidate gRNA from RORγt screening. f) Representative stacked histograms depicting RORγt and IL17a flow cytometry signal for Th17 cells transduced (Thy1+; blue/green) or nontransduced (Thy1-; grey) with candidate gRNAs. Statistical analysis was performed using one-way ANOVA with Dunnett’s test versus the NTC and sandwich standard error. Data are shown as mean ± s.e.m. relative to the NTC; * p <0.001; † p < 0.05.

Techniques: Activity Assay, Control, In Vitro, Derivative Assay, Flow Cytometry

STARR-seq signal (Log2 FC) at all ATAC-STARR-seq tested OCRs within Batf , Rorc(t), and Il17a/f loci categorized by CRISPR-screen result (untested = no CRISPR gRNA coverage). b) Waterfall plot of Th17 ATAC-STARR-seq signal (Log2 fold change RNA/DNA) for OCRs with at least 1 significant gRNA in Il17a-CRISPRi (blue circle) or Il17f-CRISPRi (orange circle), c) RORγt-CRISPRi (blue circle) and RORγt-CRISPRa (red circle) or d) Batf-CRISPRi (blue circle) and Batf-CRISPRa (red circle)

Journal: bioRxiv

Article Title: Enhancer hubs govern chromatin topology and Th17 identity

doi: 10.64898/2026.04.02.715458

Figure Lengend Snippet: STARR-seq signal (Log2 FC) at all ATAC-STARR-seq tested OCRs within Batf , Rorc(t), and Il17a/f loci categorized by CRISPR-screen result (untested = no CRISPR gRNA coverage). b) Waterfall plot of Th17 ATAC-STARR-seq signal (Log2 fold change RNA/DNA) for OCRs with at least 1 significant gRNA in Il17a-CRISPRi (blue circle) or Il17f-CRISPRi (orange circle), c) RORγt-CRISPRi (blue circle) and RORγt-CRISPRa (red circle) or d) Batf-CRISPRi (blue circle) and Batf-CRISPRa (red circle)

Techniques: CRISPR

a) Multimodal view of the Batf locus (100k bp window). Top: Region-capture Micro-C (RCMC) contact map (200bp resolution; ICE balanced), with interactions annotated by dotted lines. Tracks display Th17 ATAC-seq coverage by condition (non-targeting control [NTC] = grey; +19kb CRISPRi = red), Th17 ATAC-STARR-seq activity (Log2 CPM RNA / DNA; yellow), and CRISPRi/CRISPRa screen effect sizes (points indicate tested sgRNA, red = FDR < 0.05). Enhancers are annotated by distance (kb) and direction (+/-) relative to the Batf TSS. b) Scatter plot comparing CRISPRi versus CRISPRa effect sizes (Log2 fold change) for all tested sgRNA. Points coloured by significance (FDR < 0.05). c) Distribution of sgRNA effect sizes at selected elements from CRISPRi (left) and CRISPRa (right) screens (blue = significant; grey = tested) d) Comparison of RCMC contact frequency (500bp resolution) at the Batf locus following transduction with Batf +19kb-targeting (top) or NTC (bottom) sgRNAs in dCas9-KRAB Th17 cells. e) Differential contact map showing Log2 fold-change in interaction frequency (Batf +19kb sgRNA / NTC) f) Aggregate Peak Analysis quantifying contact frequency of interactions between the Batf-TSS (P), Batf +19kb (E1) and Batf +43kb (E2) elements in CRISPRi-mediated Batf +19kb perturbed Th17 cells (red) versus NTC (grey). g) Quantitative comparison of transcriptomic changes measured by RNA-seq (Log2 fold-changes relative to control) or h) chromatin accessibility changes by ATAC-seq (Log2 fold-change relative to control) in Batf-/-(BATF-KO) and CRISPRi-mediated Batf +19kb enhancer perturbation (Batf-gRNA) of in vitro derived Th17 cells (RNA Pearson’s r = 0.78; ATAC Pearson’s r = 0.774). i) MFI of BATF (red) or RORyt (green), and frequency of IL-17A+ (blue) from in vitro derived Th17 cells following CRISPRi-mediated repression of candidate OCRs with single gRNA relative to non-targeting control. Box plots summarise n=3 biological replicates j) Representative stacked histograms for BATF (red) IL-17a (blue) and RORγt (green) protein levels in Th17 cells following CRISPRi-mediated repression of Batf +19kb enhancer compared to nontargeting control (grey). Statistical analysis was performed using one-way ANOVA with Dunnett’s test versus the NTC and sandwich standard errors. Data are shown as mean ± s.e.m. relative to the NTC; * p <0.001.

Journal: bioRxiv

Article Title: Enhancer hubs govern chromatin topology and Th17 identity

doi: 10.64898/2026.04.02.715458

Figure Lengend Snippet: a) Multimodal view of the Batf locus (100k bp window). Top: Region-capture Micro-C (RCMC) contact map (200bp resolution; ICE balanced), with interactions annotated by dotted lines. Tracks display Th17 ATAC-seq coverage by condition (non-targeting control [NTC] = grey; +19kb CRISPRi = red), Th17 ATAC-STARR-seq activity (Log2 CPM RNA / DNA; yellow), and CRISPRi/CRISPRa screen effect sizes (points indicate tested sgRNA, red = FDR < 0.05). Enhancers are annotated by distance (kb) and direction (+/-) relative to the Batf TSS. b) Scatter plot comparing CRISPRi versus CRISPRa effect sizes (Log2 fold change) for all tested sgRNA. Points coloured by significance (FDR < 0.05). c) Distribution of sgRNA effect sizes at selected elements from CRISPRi (left) and CRISPRa (right) screens (blue = significant; grey = tested) d) Comparison of RCMC contact frequency (500bp resolution) at the Batf locus following transduction with Batf +19kb-targeting (top) or NTC (bottom) sgRNAs in dCas9-KRAB Th17 cells. e) Differential contact map showing Log2 fold-change in interaction frequency (Batf +19kb sgRNA / NTC) f) Aggregate Peak Analysis quantifying contact frequency of interactions between the Batf-TSS (P), Batf +19kb (E1) and Batf +43kb (E2) elements in CRISPRi-mediated Batf +19kb perturbed Th17 cells (red) versus NTC (grey). g) Quantitative comparison of transcriptomic changes measured by RNA-seq (Log2 fold-changes relative to control) or h) chromatin accessibility changes by ATAC-seq (Log2 fold-change relative to control) in Batf-/-(BATF-KO) and CRISPRi-mediated Batf +19kb enhancer perturbation (Batf-gRNA) of in vitro derived Th17 cells (RNA Pearson’s r = 0.78; ATAC Pearson’s r = 0.774). i) MFI of BATF (red) or RORyt (green), and frequency of IL-17A+ (blue) from in vitro derived Th17 cells following CRISPRi-mediated repression of candidate OCRs with single gRNA relative to non-targeting control. Box plots summarise n=3 biological replicates j) Representative stacked histograms for BATF (red) IL-17a (blue) and RORγt (green) protein levels in Th17 cells following CRISPRi-mediated repression of Batf +19kb enhancer compared to nontargeting control (grey). Statistical analysis was performed using one-way ANOVA with Dunnett’s test versus the NTC and sandwich standard errors. Data are shown as mean ± s.e.m. relative to the NTC; * p <0.001.

Techniques: Control, Activity Assay, Comparison, Transduction, RNA Sequencing, In Vitro, Derivative Assay

Differential motif enrichment comparing ATAC-seq peaks with significantly altered accessibility exclusively in Batf -/- relative to control (KO-specific) versus peaks affected in both Batf -/- and Batf +19kb CRISPRi-perturbed (Shared) in vitro polarized Th17 cells (Fisher’s exact test; * FDR < 0.05, ** FDR < 0.01, *** FDR < 0.001).

Journal: bioRxiv

Article Title: Enhancer hubs govern chromatin topology and Th17 identity

doi: 10.64898/2026.04.02.715458

Figure Lengend Snippet: Differential motif enrichment comparing ATAC-seq peaks with significantly altered accessibility exclusively in Batf -/- relative to control (KO-specific) versus peaks affected in both Batf -/- and Batf +19kb CRISPRi-perturbed (Shared) in vitro polarized Th17 cells (Fisher’s exact test; * FDR < 0.05, ** FDR < 0.01, *** FDR < 0.001).

Techniques: Control, In Vitro

Impact of periodontitis microbiota on inflammatory factors and T cell subsets in CIA mice. (A) Representative flow cytometry dot plot for Treg cells (CD4 + Foxp3 + ) in mouse spleen. (B) Representative flow cytometry dot plot for Th17 cells (CD4 + IL‐17A + ) in mouse spleen. (C) Comparison of Treg cell proportions in spleen (percentage of CD4 + T cells). (D) Comparison of Th17 cell proportions in spleen. (*: Compared to Con_PBS group, p < 0.05; **: p < 0.01; ***: p < 0.001; ****: p < 0.0001.) (E) Serum IL‐6 levels in mice. (F) Serum CRP levels in mice. (*: Compared to Con_PBS group, p < 0.05; **: p < 0.01. #: CIA_P group versus CIA_H group, p < 0.05).

Journal: The FASEB Journal

Article Title: Periodontitis Salivary Microbiota Exacerbates Murine Rheumatoid Arthritis via Gut Dysbiosis and Immune Dysregulation

doi: 10.1096/fj.202502610R

Figure Lengend Snippet: Impact of periodontitis microbiota on inflammatory factors and T cell subsets in CIA mice. (A) Representative flow cytometry dot plot for Treg cells (CD4 + Foxp3 + ) in mouse spleen. (B) Representative flow cytometry dot plot for Th17 cells (CD4 + IL‐17A + ) in mouse spleen. (C) Comparison of Treg cell proportions in spleen (percentage of CD4 + T cells). (D) Comparison of Th17 cell proportions in spleen. (*: Compared to Con_PBS group, p < 0.05; **: p < 0.01; ***: p < 0.001; ****: p < 0.0001.) (E) Serum IL‐6 levels in mice. (F) Serum CRP levels in mice. (*: Compared to Con_PBS group, p < 0.05; **: p < 0.01. #: CIA_P group versus CIA_H group, p < 0.05).

Article Snippet: Mouse Treg Cell Staining Kit and Mouse Th17 Cell Staining Kit (Liankebio, Hangzhou, China) were used.

Techniques: Flow Cytometry, Comparison

Gating strategy for Tregs and Th17 cells analyses in representative samples of peripheral blood mononuclear cells. (A) Schematic diagram of the flow cytometry analyses of CD3+ CD4+ T cells. (B) Q2 gate represents the percentage of Tregs (CD25+FOXP3+) among total CD4+ T cells. (C) The plot showing the gate used to identify the percentage of Th17 cells (CD4+IL-17+) in CD4+ T cells.

Journal: Frontiers in Immunology

Article Title: Significance of the peripheral blood Treg/Th17 ratio as a prognostic immune biomarker in newly diagnosed multiple myeloma and its correlation with 1q21 gain/amplification

doi: 10.3389/fimmu.2025.1595613

Figure Lengend Snippet: Gating strategy for Tregs and Th17 cells analyses in representative samples of peripheral blood mononuclear cells. (A) Schematic diagram of the flow cytometry analyses of CD3+ CD4+ T cells. (B) Q2 gate represents the percentage of Tregs (CD25+FOXP3+) among total CD4+ T cells. (C) The plot showing the gate used to identify the percentage of Th17 cells (CD4+IL-17+) in CD4+ T cells.

Article Snippet: Detection of Treg and Th17 cells was conducted by Sichuan West China Kang Shengda Medical Testing Co., Ltd.

Techniques: Flow Cytometry

Analysis of 1q21 gain/amplification in relation to Tregs and Th17 cells levels. (A, B) Treg/Th17 ratio at remission and at diagnosis in patients with and without 1q21 gain/amplification. (C, D) Percentages of Tregs in CD4+T cells at diagnosis and at remission in patients with and without 1q21 gain/amplification. (E, F) Percentages of Th17 cells in CD4+T cells at diagnosis and at remission in patients with and without 1q21 gain/amplification. “ns”, represent not significant. p < 0.05 was considered statistically significant.

Journal: Frontiers in Immunology

Article Title: Significance of the peripheral blood Treg/Th17 ratio as a prognostic immune biomarker in newly diagnosed multiple myeloma and its correlation with 1q21 gain/amplification

doi: 10.3389/fimmu.2025.1595613

Figure Lengend Snippet: Analysis of 1q21 gain/amplification in relation to Tregs and Th17 cells levels. (A, B) Treg/Th17 ratio at remission and at diagnosis in patients with and without 1q21 gain/amplification. (C, D) Percentages of Tregs in CD4+T cells at diagnosis and at remission in patients with and without 1q21 gain/amplification. (E, F) Percentages of Th17 cells in CD4+T cells at diagnosis and at remission in patients with and without 1q21 gain/amplification. “ns”, represent not significant. p < 0.05 was considered statistically significant.

Article Snippet: Detection of Treg and Th17 cells was conducted by Sichuan West China Kang Shengda Medical Testing Co., Ltd.

Techniques: Amplification, Biomarker Discovery

Association of MYC gene abnormality with 1q21 gain/amplification and Treg/Th17 Ratio. (A) MYC gene sequencing results of MM Patients at initial diagnosis, remission and relapse. The numbers marked on the graph indicate the number of patients. (B) MYC gene expression during remission in patients with or without 1q21 gain/amplification. (C, D) MYC gene expression at diagnosis and remission in high- vs low-Treg/Th17 ratio groups at diagnosis. (E) MYC gene expression at remission in high- vs low-Treg/Th17 ratio groups at remission. Treg, regulatory T cell. Th17, T helper (Th) 17 cell. p < 0.05 was considered statistically significant.

Journal: Frontiers in Immunology

Article Title: Significance of the peripheral blood Treg/Th17 ratio as a prognostic immune biomarker in newly diagnosed multiple myeloma and its correlation with 1q21 gain/amplification

doi: 10.3389/fimmu.2025.1595613

Figure Lengend Snippet: Association of MYC gene abnormality with 1q21 gain/amplification and Treg/Th17 Ratio. (A) MYC gene sequencing results of MM Patients at initial diagnosis, remission and relapse. The numbers marked on the graph indicate the number of patients. (B) MYC gene expression during remission in patients with or without 1q21 gain/amplification. (C, D) MYC gene expression at diagnosis and remission in high- vs low-Treg/Th17 ratio groups at diagnosis. (E) MYC gene expression at remission in high- vs low-Treg/Th17 ratio groups at remission. Treg, regulatory T cell. Th17, T helper (Th) 17 cell. p < 0.05 was considered statistically significant.

Article Snippet: Detection of Treg and Th17 cells was conducted by Sichuan West China Kang Shengda Medical Testing Co., Ltd.

Techniques: Amplification, Sequencing, Biomarker Discovery, Gene Expression

Survival analysis of PFS and OS of Treg/Th17 at Different Stages in MM Patients. (A, B) PFS and OS analysis in patients with Higher (>1.0) and Lower (≤ 1.0) Treg/Th17 ratio at diagnosis. (C) The PFS in patients with Higher (>0.7) and Lower (≤ 0.7) Treg/Th17 ratio at remission. (D) The OS in patients with Higher (>1.0) and Lower (≤ 1.0) Treg/Th17 ratio at relapse. PFS, Progression-Free Survival. OS, Overall Survival. MM, Multiple Myeloma. p < 0.05 was considered statistically significant.

Journal: Frontiers in Immunology

Article Title: Significance of the peripheral blood Treg/Th17 ratio as a prognostic immune biomarker in newly diagnosed multiple myeloma and its correlation with 1q21 gain/amplification

doi: 10.3389/fimmu.2025.1595613

Figure Lengend Snippet: Survival analysis of PFS and OS of Treg/Th17 at Different Stages in MM Patients. (A, B) PFS and OS analysis in patients with Higher (>1.0) and Lower (≤ 1.0) Treg/Th17 ratio at diagnosis. (C) The PFS in patients with Higher (>0.7) and Lower (≤ 0.7) Treg/Th17 ratio at remission. (D) The OS in patients with Higher (>1.0) and Lower (≤ 1.0) Treg/Th17 ratio at relapse. PFS, Progression-Free Survival. OS, Overall Survival. MM, Multiple Myeloma. p < 0.05 was considered statistically significant.

Article Snippet: Detection of Treg and Th17 cells was conducted by Sichuan West China Kang Shengda Medical Testing Co., Ltd.

Techniques: Biomarker Discovery

Prognosis assessment of R2-ISS or combined Treg/Th17 ratio. (A) The difference in PFS between R2-ISS stage I–II and stage III–IV patients. (B) The difference in PFS between R2-ISS stage I–III and stage IV patients. (C) Comparison of PFS based on the risk stratification by the combination of R2-ISS staging and Treg/Th17 Ratio at diagnosis. R2-ISS stages I, II, III and IV were assigned scores of 1, 2, 3, and 4, respectively, while Treg/Th17 ratio > 1.0 at diagnosis was assigned a score of 1. Patients with a total score of 1–3 were classified as low-risk, and those with a score of 4–5 were classified as high-risk. (D) C-index for the prediction of PFS by R-ISS, R2-ISS, mSMART 3.0, and the combination of R2-ISS with the baseline Treg/Th17 ratio. R2-ISS, the second revision of the International Staging System. Treg, regulatory T cell. Th17, T helper (Th) 17 cell. C-index, concordance index. PFS, Progression-Free Survival. p < 0.05 was considered statistically significant.

Journal: Frontiers in Immunology

Article Title: Significance of the peripheral blood Treg/Th17 ratio as a prognostic immune biomarker in newly diagnosed multiple myeloma and its correlation with 1q21 gain/amplification

doi: 10.3389/fimmu.2025.1595613

Figure Lengend Snippet: Prognosis assessment of R2-ISS or combined Treg/Th17 ratio. (A) The difference in PFS between R2-ISS stage I–II and stage III–IV patients. (B) The difference in PFS between R2-ISS stage I–III and stage IV patients. (C) Comparison of PFS based on the risk stratification by the combination of R2-ISS staging and Treg/Th17 Ratio at diagnosis. R2-ISS stages I, II, III and IV were assigned scores of 1, 2, 3, and 4, respectively, while Treg/Th17 ratio > 1.0 at diagnosis was assigned a score of 1. Patients with a total score of 1–3 were classified as low-risk, and those with a score of 4–5 were classified as high-risk. (D) C-index for the prediction of PFS by R-ISS, R2-ISS, mSMART 3.0, and the combination of R2-ISS with the baseline Treg/Th17 ratio. R2-ISS, the second revision of the International Staging System. Treg, regulatory T cell. Th17, T helper (Th) 17 cell. C-index, concordance index. PFS, Progression-Free Survival. p < 0.05 was considered statistically significant.

Article Snippet: Detection of Treg and Th17 cells was conducted by Sichuan West China Kang Shengda Medical Testing Co., Ltd.

Techniques: Comparison, Biomarker Discovery

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