Official websites use .gov

A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS

A lock ( 🔒 ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Need Help

Hiding in plain sight: integrating AI with targeted bench methods to discover and characterize viruses in the human body

Award Number: U01DE035632
ORGANIZATION: NATIONAL INSTITUTE OF DENTAL AND CRANIOFACIAL RESEARCH
OPDIV: NIH
AWARD CLASS: COOPERATIVE AGREEMENT
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 03/13/2026
PERIOD OF PERFORMANCE END DATE: 01/31/2030

Group Awards By:

View Award Description

Hiding in plain sight: integrating AI with targeted bench methods to discover and characterize viruses in the human body - PROJECT SUMMARY/ABSTRACT The broad goal of the proposed work is to provide innovative computational tools and laboratory protocols to identify and characterize viruses that are currently unaccounted for in human virome studies. Viruses are abundant in the human body and impact the health and function of human cells and commensal microbial communities, yet understanding of the structure and function of human viromes remains limited. Human viromes appear to be dominated by tailed viruses (phages), yet imperfect computational and experimental approaches limit the ability to broadly recover and recognize all viruses present in an environment. Thus, statements about the human virome and its impacts are currently based only on the fraction of viruses most similar to existing references. The central hypothesis of the proposed work is that the phylogenetic heterogeneity of viruses in the human virome is greater than currently recognized, and that viruses are being missed in two major ways: first, when they are present in sequence datasets and go unrecognized, as “dark matter”; and second, when they are underrepresented in sequence datasets because they are operationally excluded. This hypothesis is addressed through two complementary aims, which develop innovative computational tools and laboratory protocols, and apply these to new and existing sequence datasets in light of metaproteomics, to facilitate and achieve systematic discovery and annotation of the human virome. In Aim 1, computational protein language model (PLM)-based approaches are used to address the technological challenge of identifying and meaningfully characterizing viral sequences in metagenomic data. Novel tools based on PLMs are built to enable viral discovery by the scientific community in any microbiome of interest, and novel conceptual frameworks for genome sequence topology-based classification of uncharacterized viral sequences are developed. In Aim 2, laboratory methods are developed that leverage the distinctive buoyant density features of tailed viruses to systematically deplete these from viromes, thereby allowing detection of viruses otherwise missed. To enable identification of even the most divergent “dark matter” viruses, fractionated viromes are complemented with metaproteomics to reveal as viral those contigs physically co-occurring with the proteins their genes encode (a diagnostic feature of a virion). In both aims, newly developed approaches are applied to stool samples from donors with colorectal cancer (CRC), a disease that is currently increasing in prevalence and in which microbes and viruses have been implicated. Completion of these aims will provide a uniquely broad view of the phylogenetic heterogeneity of the human virome, and new bioinformatic tools and laboratory protocols that will allow the research community to overcome obstacles to viral discovery and characterization currently limiting the translational potential of virome studies.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $423,366 )
2026	2026	THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK	520 LEE ENTRANCE STE 211	AMHERST	NY	14228	ERIE	USA	Trans-NIH Research Support	000	1	3/13/2026	NEW	$423,366
														Subtotal = $423,366

Grand Total All Awards = $423,366

Top

All Categories

About

Search

Reports

Data Submission

Award Information

Hiding in plain sight: integrating AI with targeted bench methods to discover and characterize viruses in the human body

Award Number: U01DE035632

ORGANIZATION: NATIONAL INSTITUTE OF DENTAL AND CRANIOFACIAL RESEARCH

OPDIV: NIH

AWARD CLASS: COOPERATIVE AGREEMENT

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 03/13/2026

PERIOD OF PERFORMANCE END DATE: 01/31/2030

Federal Websites

Department of Health & Human Services

HHS Operating Divisions

HHS Staff Divisions

Download A Document Viewer