High-Resolution Mapping of Bacterial Transcriptional Responses in Human-Associated Microbiota

人类相关微生物群中细菌转录反应的高分辨率图谱

基本信息

批准号：
10710183
负责人：
Ilana Lauren Brito
金额：
$ 32.05万
依托单位：
CORNELL UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-26 至 2026-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10710183
关键词：
Activities of Daily Living Acute Address Adopted Antibiotic Resistance Antibiotics Antibodies Bacteria Bacterial Genome Base Pairing Benchmarking Cells Chemistry Clinical Clustered Regularly Interspaced Short Palindromic Repeats Colorectal Cancer Communities Complex Cytolysis DNA Damage DNA sequencing DNA-Directed RNA Polymerase Data Data Set Development Diet Disease Environment Escherichia coli Eukaryota Excision Exercise Fusobacterium nucleatum Gene Expression Profile Genetic Transcription Genus Vanilla Goals Growth Health Heat-Shock Response Homeostasis Human Human Microbiome Immunoprecipitation Inflammatory Inflammatory Bowel Diseases Laboratories Laboratory culture Libraries Maps Metabolic Metagenomics Methods Microbe Modification Noise Operon Organism Output Oxygen Pathway interactions Periodontal Diseases Polymers Positioning Attribute Prokaryotic Cells Protocols documentation Proxy RNA RNA Decay RNA Stability Reaction Regulation Research Personnel Resolution Ribosomal RNA Role Running Sampling Shotgun Sequencing Signal Transduction Site Stimulus Stress Structure Taxonomy Technology Testing Time Transcript Transcription Elongation Transcription Initiation Transcription Initiation Site Transcriptional Regulation Untranslated RNA Virulence Factors Xenobiotics bacterial community biological adaptation to stress clinically relevant computational suite computerized tools cost cost effective diverse data environmental stressor experimental study feasibility testing genetic manipulation human microbiota improved insight metagenomic sequencing microbial microbial community microbiome microbiome sequencing pathogen polymerization posttranscriptional quorum sensing resilience resistance gene response stressor success tool transcriptome sequencing transcriptomics tripolyphosphate

项目摘要

Project Summary Functional profiling of microbial communities is critical to understanding their overall effects on host health. Most often, metagenomic shotgun sequencing of microbiome samples is used to assess total functional capacity. Yet, transcriptional responses may vary dramatically between organisms depending on the context, with potentially large effects. Many metabolic functions are only expressed after the organism acutely senses the presence of particular substrates in their environment. Pathogens may only express virulence factors after obtaining a critical quorum of pathogens. Overall, stress responses are critical for survival under changing abiotic and biotic conditions. Being able to comprehensively map out these pathways, which determine the resilience, plasticity, and patho-functions of the microbiome, requires sensitive, robust transcriptional –omics tools. Performing traditional RNAseq analyses on bacterial communities has been the predominant method to gain transcriptional information, but it is hampered by the need for technical workarounds and it provides incomplete information about the transcriptional landscape. Ribosomal RNA needs to be depleted prior to sequencing, it has a poor signal-to-noise ratio arising from varying RNA decay rates, and it is insensitive to the transcription of non-coding RNA that has secondary structure or post-transcriptional modifications. Alternatively, the position of RNA polymerase (RNAP) can be assessed, which provides a real-time readout of transcription. Although so-called nascent transcript sequencing has been performed in E. coli, revealing transcriptional pause sites and other phenomenon elusive when using RNAseq alone, these protocols rely on immunoprecipitation of RNAP and are therefore unsuitable for complex microbial communities where RNAP may be quite diverse and require species-specific antibodies. As a solution, Precision Run-On and SEQuencing (PRO-seq), a method originally created for examining transcription in eukaryotes, may provide an unbiased method to examine transcriptional dynamics on cultured bacteria or in complex microbial communities, such as the human microbiome. Our goal is to test the feasibility of PRO-seq when applied to prokaryotes and to evaluate its ability to capture transcriptional dynamics associated with canonical stress response pathways (heat-shock, oxygen exposure and DNA damage), using a set of quantitative metrics. We aim to validate, and if necessary, modify the protocol so it can be used robustly across species. We plan to develop a computational approach to test the full breadth of transcriptional phenomena that can be observed using this method, such as transcriptional pausing, bidirectional transcription, differences in RNAP function apparent across species, and RNA decay rates, among other aspects. If successful, we expect that PRO-seq will be adopted to study the responses of human-associated microbiota to host diet, inflammatory signals, xenobiotics and to human transcriptional circuitry, more directly.