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

> **NIH NIH R35** · UNIVERSITY OF WISCONSIN-MADISON · 2021 · $349,756

## Abstract

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.

## Key facts

- **NIH application ID:** 10276730
- **Project number:** 1R35GM143024-01
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** Karthik Anantharaman
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $349,756
- **Award type:** 1
- **Project period:** 2021-08-06 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10276730

## Citation

> US National Institutes of Health, RePORTER application 10276730, COMPUTATIONAL FRAMEWORKS FOR PHAGE DISCOVERY, ECOLOGY, AND DYNAMICS FROM METAGENOMES (1R35GM143024-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10276730. Licensed CC0.

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