Proteogenomic analysis of inflammation and dysbiosis in the infant gut
Proteogenomic analysis of inflammation and dysbiosis in the infant gut
批准号:
8605019
负责人:
Jillian Banfield
金额:
$37.05万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-02-06 至 2017-11-30
关键词:
AdultAerobicAnti-Inflammatory AgentsAnti-inflammatoryAttentionBiochemical ProcessBioinformaticsBiological MarkersBiological ModelsBiologyCarbonCommunitiesCompanionsCrohn&aposs diseaseDataData AnalysesData SetDevelopmentDiseaseEcosystemEpithelialFermentationGenerationsGenesGoalsHealthHumanHuman MicrobiomeHuman bodyHydrogenImmune responseInfantInflammationInflammatoryInflammatory Bowel DiseasesInflammatory ResponseInflammatory disease of the intestineInformaticsIntestinal DiseasesIntestinesInvestigationLifeLinkMaintenanceMass Spectrum AnalysisMeasurementMeasuresMetabolic PathwayMetabolismMetagenomicsMethodsMicrobeModelingMonitorNatural ImmunityNecrotizing EnterocolitisNewborn InfantNitrogenOnset of illnessOrganismOxidation-ReductionPathogenesisPathway interactionsPatternPremature InfantProductionProteinsProteomeProteomicsResearchResolutionRespirationSamplingSeriesStudy modelsSulfur Metabolism PathwaySystemTestingTimeUnited States National Institutes of HealthVirulence FactorsVolatile Fatty AcidsWorkbaseimprovedinterestintestinal homeostasisknowledge baselink proteinmicrobialmicrobial colonizationmicrobial communitymicrobiomenovelprotein expressionpublic health relevancetool
中文摘要
本项目的目标是进行时间序列蛋白质组学分析,可处理和自然-
英文摘要
The goal of this project is to conduct time-series proteomic analyses of a tractable and naturally-
occurring model ecosystem, the newborn intestinal tract, in order to characterize links between dysbiosis and
intestinal inflammation.
At present, we lack a mechanistic understanding of the relationships between the microbiota and
inflammatory disorders such as necrotizing enterocolitis (NEC) and inflammatory bowel disease. We also lack
tools to clarify which microbial biochemical processes are active in the human gut. Over the past decade, our
research group has developed methods to pair community metagenomics with high-throughput mass
spectrometry-based proteomic analyses to accurately identify proteins with strain-level resolution. An
important component of this approach has been the development of bioinformatics tools that enable the
integration and analysis of "omic" data. Recently, we adapted these methods to simultaneously measure
human and microbial proteins in time series infant fecal samples.
Here, we propose to test the hypothesis that inflammation in the premature infant gut is triggered by aberrations
in microbial community metabolism. This project will leverage samples and a large amount of metagenomic data
obtained in a companion NIH study of the microbiota in babies with and without NEC. The specific Aims of
this project are: Aim 1. Characterize gut microbial community function during the first month of life in
healthy infants, by determining which microbial genes and metabolic pathways are most important during
early colonization, with specific attention to the transition from aerobic to anaerobic community metabolism.
Aim 2. Characterize time-dependent signatures of human proteins linked to intestinal inflammation in
fecal samples from newborn infants, by evaluating the abundances of human proteins linked to intestinal
homeostasis, inflammation, and redox biology in the context of changes in the microbial proteome. Aim 3. Test
the hypothesis that babies with NEC developed inflammation as a consequence of a delayed transition to
anaerobic microbial metabolism in the gut, by comparing temporal patterns of human and microbial protein
expression in babies with and without NEC to determine if dysbiosis precedes inflammation This work will
rely on a bioinformatics strategy for analysis of large time series datasets that will deployed in the context of
GGKbase, a novel knowledgebase framework that will facilitate collaborative data analysis and sharing of
"omic" information with the scientific community.
This research uses the developing infant gut as a model system to uncover general features of gut
microbial community function, and to clarify the relationships between aberrant function and inflammation.
Our results and the informatics tools that we develop will contribute to an improved understanding of the
dynamics of the relationship between the human body and the human microbiome.
1
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海外基金