Carbohydrate enzyme gene clusters in human gut microbiome
人类肠道微生物组中的碳水化合物酶基因簇
基本信息
- 批准号:10569118
- 负责人:
- 金额:$ 30.21万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-05-01 至 2025-02-28
- 项目状态:未结题
- 来源:
- 关键词:AddressAlgorithmsBacterial GenomeBacteroidetesBioinformaticsCarbohydratesClassificationDataDatabasesDevelopmentDietDietary FiberEnvironmentEnzymesFamilyFirmicutesFoodFoundationsGene ClusterGenesGenomeGenomicsGlucansHealthHealth FoodHumanHuman MicrobiomeLearningLinkLiteratureMachine LearningMannansMapsMedicineMetabolicMetabolic DiseasesMicrobeNebraskaOther GeneticsOutcomePectinsPersonsPhysiologyPolysaccharidesProteinsProteobacteriaPublishingResearchResearch PersonnelSamplingSignaling ProteinStarchSystemTestingTrainingWorkXylansannotation systembioinformatics toolcomputer programcomputerized toolscontigdietaryexperiencegenetic elementgut metagenomegut microbesgut microbiomehost microbiotainnovationinterestmachine learning methodmetagenomemetatranscriptomemicrobialmicrobial communitymicrobial genomemicrobiomemicrobiome sequencingnovelnutritionopen sourceprebioticspredictive toolspreventprogramssugarsupervised learningtherapeutic developmenttooltool developmentuser-friendlyweb server
项目摘要
PROJECT SUMMARY
Carbohydrate enzyme gene clusters in human gut microbiome
Hippocrates said ~2,400 years ago: “Let food be thy medicine and medicine be thy food”. It is now well known
that this is largely due to the “diet-microbiota-host” interactions that happen in the human gut. In particular,
microbial degradation of carbohydrates can produce a variety of metabolites, which have a profound impact on
human health. As a bioinformatics researcher in the Nebraska Food for Health Center, the long-term interests of
the PI include: (i) develop specialized computational tools for better functional annotation of food-digesting
microbial genomes and metagenomes, and (ii) characterize enzymes and other genetic elements that connect
microbes, diets, and human health. The objective of this R01 project is to develop a suite of bioinformatics tools
for functional annotation of carbohydrate active enzyme (CAZyme) and CAZyme gene clusters (CGCs) in human
gut microbiome. The PI has over 10 years of experience in CAZyme bioinformatics tool development, and
maintains a well-recognized CAZyme annotation database and web server called dbCAN
(http://bcb.unl.edu/dbCAN2). This project aims to further dbCAN development to address fundamental
personalized nutrition questions: (i) is a gut microbe able to utilize a specific type of glycan? (ii) can a person
carrying certain gut microbes respond to an individualized diet (e.g., prebiotics: dietary compounds that are
beneficial to human health)? To address these questions, new CAZyme annotation tools must have the ability
to predict the carbohydrate substrates of CAZymes.
Recent research has found that different CAZyme encoding genes are often co-localized with each other and
with other genes (e.g., those encoding sugar transporters, regulators, and signaling proteins) in bacterial
genomes to form CGCs (also known as polysaccharide utilization loci or PULs). Thus, the foundation of the new
tool development is that the gene membership (or functional domain composition) of a CGC can be used to
predict its carbohydrate substrates (e.g., xylans, pectins, glucans, etc.). The innovation is that machine learning
approaches will be used to analyze a large number of experimentally characterized PULs curated from literature,
and the extracted sequence features will be used to build effective classifiers to predict and classify CGCs in
new genomes/metagenomes. The expected outcome will be novel and user-friendly open source computer
programs, databases, and web servers that allow automated CGCs identification and substrate predictions. The
significance is that the new tools will facilitate the experimental characterization of more PULs and their
carbohydrate substrates in human gut microbiome (also in other carbohydrate rich environments). Therefore,
this project will contribute computational solutions to the research of personalized nutrition, e.g., analyze a
person's gut microbiome to predict if this person can respond to diets containing certain prebiotic glycans.
项目总结
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Yanbin Yin其他文献
Yanbin Yin的其他文献
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{{ truncateString('Yanbin Yin', 18)}}的其他基金
Bioinformatics Discovery of Anti-CRISPR Operons in Human Gut Microbiome
人类肠道微生物组中抗 CRISPR 操纵子的生物信息学发现
- 批准号:
10509691 - 财政年份:2022
- 资助金额:
$ 30.21万 - 项目类别:
Bioinformatics Discovery of Anti-CRISPR Operons in Human Gut Microbiome
人类肠道微生物组中抗 CRISPR 操纵子的生物信息学发现
- 批准号:
10636879 - 财政年份:2022
- 资助金额:
$ 30.21万 - 项目类别:
Carbohydrate enzyme gene clusters in human gut microbiome
人类肠道微生物组中的碳水化合物酶基因簇
- 批准号:
10398795 - 财政年份:2021
- 资助金额:
$ 30.21万 - 项目类别:
Exploration of cloud computing for CAZyme research
CAZyme 研究的云计算探索
- 批准号:
10827621 - 财政年份:2021
- 资助金额:
$ 30.21万 - 项目类别:
Carbohydrate enzyme gene clusters in human gut microbiome
人类肠道微生物组中的碳水化合物酶基因簇
- 批准号:
10594096 - 财政年份:2021
- 资助金额:
$ 30.21万 - 项目类别:
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