# Viral MEM: Viral Enrichment and Precise Stochastic Quantification with Microbial Context Preservation for Rigorous Virome Analysis of Challenging Human Samples

> **NIH NIH U01** · CALIFORNIA INSTITUTE OF TECHNOLOGY · 2024 · $594,934

## Abstract

PROJECT SUMMARY
Overview. This U01 proposal is dedicated to advancing the Human Virome Project (HVP) by addressing several
key objectives outlined in RFA-RM-23-018 NOFO. The project's focus is on the development and validation of
innovative technologies that enhance rigor and reproducibility of virome discovery and characterization,
particularly in human tissue samples. By addressing challenges such as low-biomass sample analysis, host and
environmental DNA contamination, and the need for more effective viral quantification and enrichment
techniques, this proposal aims to significantly advance the field of virome research.
Goals and Objectives. The project is structured around three specific aims:
Development of Viral-MEM: An innovative viral enrichment technology that operates independently of viral-like
particles (VLP). Viral-MEM is designed to effectively process high-host load tissue samples by removing host
nucleic acids while preserving and separating viruses and other microbes. This technology, building on our
validated microbial enrichment method, is crucial for deep characterization of viral and bacterial fractions,
improving limits of detection in sequencing, and aiding in the identification of novel viruses.
Development of Viral StochQuant: A novel experimental and computational approach designed to increase
the rigor and reproducibility of viral sequencing. This method uniquely combines sequencing measurements with
absolute anchoring measurements to accurately track the absolute numbers of molecules throughout the
sequencing process. It addresses the challenges of low target abundance and high background signal, and uses
anchoring measurements and stochastic simulations for deriving limits of detection, measurement noise,
differential abundance analyses, and contamination detection.
Validation of Developed Technologies: Validation will address both biological and technical variabilities and
be conducted in three distinct and challenging human tissue sample sets—daily sampled vaginal swabs, saliva
samples paired with small-intestine biopsies, and paired biopsies from four locations in the human lower
gastrointestinal (GI) tract. This approach will facilitate study of intricate phage-bacterial dynamics, connections
between different human viromes, and the quantitative biogeography of the human virome along the GI tract.
Impact. The successful implementation of this proposal will dramatically enhance the accuracy, cost-
effectiveness, and scalability of virome analyses in human tissues. The technologies developed will enable a
more comprehensive integration of virome data with broader human microbiome research and will offer new
insights into virome dynamics and interactions. Importantly, these innovations will diversify the HVP's research
capabilities, provide access to new sample types, and improve data quality, particularly for low-biomass samples.
Overall, this project is designed to provide tools that significantly deepen our unders...

## Key facts

- **NIH application ID:** 10986859
- **Project number:** 1U01DE034199-01
- **Recipient organization:** CALIFORNIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** RUSTEM F ISMAGILOV
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $594,934
- **Award type:** 1
- **Project period:** 2024-09-20 → 2028-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10986859

## Citation

> US National Institutes of Health, RePORTER application 10986859, Viral MEM: Viral Enrichment and Precise Stochastic Quantification with Microbial Context Preservation for Rigorous Virome Analysis of Challenging Human Samples (1U01DE034199-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10986859. Licensed CC0.

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