Chromatin accessibility changes induced by the microbial metabolite butyrate reveal possible mechanisms of anti-cancer effects

Butyrate is a four-carbon fatty acid produced in large quantities by bacteria found in the human gut. It is the major source of colonic epithelial cell energy, can bind to and agonize short-chain fatty acid G-protein coupled receptors and functions as a histone deacetylase (HDAC) inhibitor. Anti-cancer effects of butyrate are attributed to a global increase in histone acetylation in colon cancer cells; however, the role that corresponding chromatin remodeling plays in this effect is not fully understood. We used longitudinal paired ATAC-seq and RNA-seq on HCT-116 colon cancer cells to determine how butyrate-related chromatin changes functionally associate with cancer. We detected distinct temporal changes in chromatin accessibility in response to butyrate with less accessible regions enriched in transcription factor binding motifs and distal enhancers. These regions significantly overlapped with regions maintained by the SWI/SNF chromatin remodeler, and were further enriched amongst chromatin regions that are associated with ARID1A/B synthetic lethality. Finally, we found that butyrate-induced chromatin regions were enriched for both colorectal cancer GWAS loci and somatic mutations in cancer. These results demonstrate the convergence of both somatic mutations and GWAS risk variants for colon cancer within butyrate-responsive chromatin regions, providing a molecular map of the mechanisms by which this microbial metabolite might confer anti-cancer properties. Highlights Chromatin accessibility changes longitudinally upon butyrate exposure in colon cancer cells. Chromatin regions that close in response to butyrate are enriched among distal enhancers. There is strong overlap between butyrate-induced peaks and peaks associated with SWI/SNF synthetic lethality. Butyrate-induced peaks are enriched for colorectal cancer GWAS loci and somatic variation in colorectal cancer.

[1]  M. Oren,et al.  The gut microbiome switches mutant p53 from tumour-suppressive to oncogenic , 2020, Nature.

[2]  A. Tenesa,et al.  Functional annotation of the cattle genome through systematic discovery and characterization of chromatin states and butyrate-induced variations , 2019, BMC Biology.

[3]  Manolis Kellis,et al.  Chromatin Accessibility Impacts Transcriptional Reprogramming in Oocytes , 2018, Cell reports.

[4]  Longhuo Wu,et al.  Effects of the intestinal microbial metabolite butyrate on the development of colorectal cancer , 2018, Journal of Cancer.

[5]  A. Andremont Too Early to Recommend Early Fecal Microbiota Transplantation in Patients With Severe Clostridium difficile Infection, or Not Too Early? , 2018, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[6]  N. Bergeron,et al.  The gut microbiome. , 2017, Australian family physician.

[7]  Lars G Fritsche,et al.  Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies , 2017, Nature Genetics.

[8]  Devin K Porter,et al.  Chromatin accessibility underlies synthetic lethality of SWI/SNF subunits in ARID1A-mutant cancers , 2017, eLife.

[9]  Y. Bhutia,et al.  Gut Microbiome and Colon Cancer: Role of Bacterial Metabolites and Their Molecular Targets in the Host , 2017, Current Colorectal Cancer Reports.

[10]  C. Mulder,et al.  Current challenges in the treatment of severe Clostridium difficile infection: early treatment potential of fecal microbiota transplantation , 2017, Therapeutic advances in gastroenterology.

[11]  P. Park,et al.  ARID1A loss impairs enhancer-mediated gene regulation and drives colon cancer in mice , 2016, Nature Genetics.

[12]  Howard Y. Chang,et al.  Lineage-specific and single cell chromatin accessibility charts human hematopoiesis and leukemia evolution , 2016, Nature Genetics.

[13]  S. Olesen,et al.  Designing fecal microbiota transplant trials that account for differences in donor stool efficacy , 2016, bioRxiv.

[14]  Andrew D. Rouillard,et al.  Enrichr: a comprehensive gene set enrichment analysis web server 2016 update , 2016, Nucleic Acids Res..

[15]  R. Gordân,et al.  HDAC inhibitors cause site-specific chromatin remodeling at PU.1-bound enhancers in K562 cells , 2016, Epigenetics & Chromatin.

[16]  Yakir A Reshef,et al.  Partitioning heritability by functional annotation using genome-wide association summary statistics , 2015, Nature Genetics.

[17]  David A. Streett,et al.  Super deduper, fast PCR duplicate detection in fastq files , 2015, BCB.

[18]  Howard Y. Chang,et al.  ATAC‐seq: A Method for Assaying Chromatin Accessibility Genome‐Wide , 2015, Current protocols in molecular biology.

[19]  Paul Theodor Pyl,et al.  HTSeq – A Python framework to work with high-throughput sequencing data , 2014, bioRxiv.

[20]  M. Daly,et al.  LD Score regression distinguishes confounding from polygenicity in genome-wide association studies , 2014, Nature Genetics.

[21]  S. Bultman Molecular Pathways: Gene–Environment Interactions Regulating Dietary Fiber Induction of Proliferation and Apoptosis via Butyrate for Cancer Prevention , 2013, Clinical Cancer Research.

[22]  Howard Y. Chang,et al.  Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position , 2013, Nature Methods.

[23]  G. Crabtree,et al.  Proteomic and bioinformatic analysis of mammalian SWI/SNF complexes identifies extensive roles in human malignancy , 2013, Nature Genetics.

[24]  E. Lander,et al.  Lessons from the Cancer Genome , 2013, Cell.

[25]  Timothy Daley,et al.  Predicting the molecular complexity of sequencing libraries , 2013, Nature Methods.

[26]  Steven L Salzberg,et al.  Fast gapped-read alignment with Bowtie 2 , 2012, Nature Methods.

[27]  Marcel Martin Cutadapt removes adapter sequences from high-throughput sequencing reads , 2011 .

[28]  Pedro M. Valero-Mora,et al.  ggplot2: Elegant Graphics for Data Analysis , 2010 .

[29]  C. Glass,et al.  Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. , 2010, Molecular cell.

[30]  Cory Y. McLean,et al.  GREAT improves functional interpretation of cis-regulatory regions , 2010, Nature Biotechnology.

[31]  Davis J. McCarthy,et al.  edgeR: a Bioconductor package for differential expression analysis of digital gene expression data , 2009, Bioinform..

[32]  Hadley Wickham,et al.  ggplot2 - Elegant Graphics for Data Analysis (2nd Edition) , 2017 .

[33]  Clifford A. Meyer,et al.  Model-based Analysis of ChIP-Seq (MACS) , 2008, Genome Biology.

[34]  M. L. Liu,et al.  Nutrient utilization by cells isolated from rat jejunum, cecum and colon. , 1991, The Journal of nutrition.

[35]  W. Roediger Utilization of nutrients by isolated epithelial cells of the rat colon. , 1982, Gastroenterology.

[36]  Thomas R. Gingeras,et al.  STAR: ultrafast universal RNA-seq aligner , 2013, Bioinform..

[37]  Antonio Calignano,et al.  Potential beneficial effects of butyrate in intestinal and extraintestinal diseases. , 2011, World journal of gastroenterology.

[38]  Ira M. Hall,et al.  BEDTools: a flexible suite of utilities for comparing genomic features , 2010, Bioinform..