grant

COMPUTATIONAL FRAMEWORKS FOR PHAGE DISCOVERY, ECOLOGY, AND DYNAMICS FROM METAGENOMES

Organization UNIVERSITY OF WISCONSIN-MADISONLocation MADISON, UNITED STATESPosted 6 Aug 2021Deadline 30 Jun 2027
NIHUS FederalResearch GrantFY2025AlgorithmsBacteriophagesBioinformaticsBionomicsCollaborationsCommunitiesComputer softwareDataData BasesData SetDatabasesDevelopmentEcologic SystemsEcological SystemsEcologyEcosystemEukaryotaEukaryoteFunctional MetagenomicsGeneral TaxonomyGenomicsHealthHumanHuman MicrobiomeIntermediary MetabolismInvestigationLaboratoriesMetabolic ProcessesMetabolismMetagenomicsMethodsMicrobiomicsModern ManPathogenicityPhagesPopulationProkaryotaeProkaryotic CellsRNA BacteriophagesRNA PhagesSoftwareSourceTaxonomyVirusbacterial virusbio-informatics toolbioinformatics toolclinical relevanceclinically relevantcomputational frameworkcomputer frameworkdata basedesigndesigningdevelopmentalhuman-associated microbiomeimprovedinteroperabilitymetagenomemetagenome sequencingmetagenomic sequencingmetatranscriptomicsmicrobiome researchmicrobiome sciencemicrobiome studiesmicroorganismnovelprokaryotepublic health relevancetoolvirology
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Full Description

Project Summary/Abstract
Metagenomics sequencing is increasingly becoming important for human microbiome

research. Human microbiomes comprise a rich ecosystem of beneficial and pathogenic

microorganisms and bacteriophages that can influence human health. Yet,

bacteriophages remain poorly studied because most bacteriophages cannot be isolated

in a laboratory. As a result, cultivation-independent omics approaches such as

metagenomics are emerging as important tools for studying bacteriophages directly

from mixed communities. However, a significant challenge in virology is the relative

absence of high-quality bioinformatics tools to enable the study of bacteriophages from

metagenomics data compared to the abundance of such tools available for prokaryotes.

We will develop several novel algorithms to enable the study of bacteriophages and

their ecology from metagenomics data, including for the discovery of novel uncultivated

phages, phage population genomics, phage taxonomy, phage:host and

phage:metabolism interactions, and the dynamics of integrated phages. Our

approaches will be formalized through the development and release of open access

databases and software based on FAIR (Fair, Accessible, Interoperable, Reusable)

data principles, which will enable investigation of fundamental questions in

bacteriophage ecology governing human health. To demonstrate the utility and wide

applicability of our methods to study bacteriophages, we will apply them on a diverse

group of metagenome data sets from human microbiomes sourced from publicly

available data and several existing collaborations. While our approaches are designed

for the study of bacteriophages from metagenome data, they can also be applied

broadly towards the study of all viruses including RNA phages from metatranscriptomic

data and viruses infecting eukaryotes. Successfully accomplishing this project will

provide scalable bioinformatics approaches that can be widely applied to the study of

bacteriophages from metagenomics data.

Grant Number: 5R35GM143024-05
NIH Institute/Center: NIH

Principal Investigator: Karthik Anantharaman

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