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Additional file 1 of Bivalent chromatin accommodates survivin and BRG1/SWI complex to activate DNA damage response in CD4+ cells

2024· article· en· W6902162757 on OpenAlexaff

Bibliographic record

VenueFigshare · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChromatin Remodeling and Cancer
Canadian institutionsQueen's University
Fundersnot available
KeywordsChromatinH3K4me3HistoneTranscription (linguistics)NucleosomeLNCaPGeneDNA

Abstract

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Additional file 1: Supporting Figure S1. S1A. The table of clinical characteristics of healthy controls and patient material used in this study. S1B. The table of primers used for qPCR analysis in this study. S2A. Box plots of histone H3 tag deposition within the bivalent chromatin regions (BvCR) dominant by H3K4me3, H3K27me3 and H3K27ac. S2B. Box plots of histone peak scores within BvCR dominant by H3K4me3, H3K27me3 and H3K27ac. Kolmogorov–Smirnov test p-values are shown. S2C. Box plot of percentage tag change for histone peaks within H3K27me3- and H3K27ac-BvCR, after YM155 treatment. Mann–Whitney test p-values are indicated. Supporting Figure S3. S3A. Forest plot of probability of BvCR to be changeable (Ch) in YM155-treated CD4 cells and genes connected to BvCR to be differentially expressed (DEG) in CD4 + cells treated with IFNγ or IFNγ + YM155. S3B. Scatter plot of correlation between change in deposition of H3K4me3 and H3K27me3 tags and change in transcription of DEG after treatment with IFNγ or IFNγ + YM155 in survivin-positive H3K4me3-BvCR. Spearman ρ are indicated. S3C. Radar plot of Spearman’s ρ correlations between tag change in H3K4me3 and H3K27me3 deposition in H3K27me3-BvCR and transcription change of DEG in CD4+ cells treated with IFNγ or IFNγ + YM155. Arrows indicate direction of transcription change. Supporting Figure S4. S4A. Bar plot of frequency of genes connected to BvCR in the enriched pathways. To the right is the Venn diagram of IFNγ- and survivin-sensitive genes connected to H3K4me3-BvCR and annotated to the DNA damage response pathway (GO:0006974). S4B. Heatmap of normalized tag deposition in BvCR connected to DEG treated with IFNγ + YM155. Filled squares indicate colocalization of survivin (S) in the BvCR. Genes connected to multiple BvCR are marked in bold. S4C. Heatmap of transcription change of DEG annotated to DNA Damage Response (DDR) pathway. Asterisks indicate RNAseq nominal p-values—* < 0.05, ** < 0.01, *** < 0.001. S4D. Box plot of quantified tag deposition in survivin-sensitive and IFNγ-sensitive genes annotated to DNA damage response and connected to H3K4me3-BvCR. Mann–Whitney p-values are indicated. Supporting Figure S5. Genomic maps of the DNA repair gene loci MSH6, FANCI, SMC3, PIAS4, and MRE11. Filled black and red boxes indicate cis-RE connected to the gene, as determined by GeneHancer. Distance to TSSs is shown. Black filled peaks underneath cis-RE indicate the positions of survivin-ChIP and histone H3-ChIP peaks. Colored peaks indicate the change in tag deposition for H3K4me3 (green) and H3K27me3 (red) after YM155 treatment, scaled to enable direct comparison between the two modifications. Supporting Figure S6. S6A. Frequency of overlapping BvCR with cBAF and PBAF complex subunits retrieved from ReMap2022 database. Fisher test p-values are indicated. S6B. Coomassie-stained electrophoresis gel depicts replicate nuclear extracts of input (lanes 2 and 3), survivin-IP (lanes 7 and 10) and non-specific IgG IP (lanes 15 and 16). The red-marked bands were excised for interrogation using LC–MS. Molecular weight ladder (MW) is shown on the left side and in lane 14. Experiment 1 is presented in lanes 2, 7 and 15; experiment 2 is presented in lanes 3, 10 and 16. Red numbers indicate the bands analyzed by mass spectrometry. S6C. Distribution of survivin binding probability across the protein sequence of SMARCC2, SMARCD1, and SMARCE1. Mbind(n) value indicate the fraction of mutations compatible with a survivin binding to the residue, defined by the functional composition of atomic group. “1” indicates a region predicted to bind survivin even if the position is mutated to any other amino acid. “0” indicates no mutation can convert the site to survivin binding region. UniProt IDs of the proteins are indicated in brackets. Supporting Figure S7. S7A. Interaction between survivin and the conventional BRG1/SWI complex (PDB ID: 6LTJ) predicted by docking modelling in three independent experiments and in the peptide-binding array. Peptide residues involved in the interaction with survivin are marked bold. S7B. Interaction between survivin and the polybromo BRG1/SWI complex (PDB ID: 7VDV) predicted by docking modelling in three independent experiments and in the peptide-binding array. Peptide residues involved in the interaction with survivin are marked bold. Supporting Figure S8. Gallery of immunohistochemical images depicting colocalization of survivin (red) and BRG1 (yellow) in nucleus (blue) of THP1 cells, visualized by confocal microscopy at resolution 40X. Nuclear area is identified by Hoechst stain. Overlap coefficient was calculated by colocalization of fluorescence pixels using ImageJ JACoP plugin. Supporting Figure S9. DNA Damage Response (DDR) network map of upregulated (red) and downregulated (blue) differentially expressed genes in BRG1hi cells in patients with rheumatoid arthritis. Nodes are colored by fold expression difference (log2FC) between BRG1hi and BRG1lo CD4+ cells of genes within nodes. Size of bubble corresponds to percentage of BRG1hi genes within each node.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.771
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.7720.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.268
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2024
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