Accurate and cost-effective detection of mutagenicity and mutagenic exposure

NIH RePORTER · NIH · R43 · $275,763 · view on reporter.nih.gov ↗

Abstract

ABSTRACT Mutations in the genome of somatic cells in multicellular organisms result from DNA repair or replication errors, causing cancer and other age-related diseases. As DNA mutations are irreversible, they represent the critical molecular endpoint of the interaction between DNA damage and genome integrity maintenance mechanisms. Thus, quantifying diverse mutation types in cells and tissues is essential in genetic toxicology for assessing genetic risk associated with human exposure to environmental and anthropogenic agents. Current techniques face challenges due to low mutation abundance and indistinguishability from sequencing errors. We propose optimizing and validating Single Molecule Mutation Sequencing (SMM-seq), a novel approach for accurate, cost-effective assessment of somatic mutations in normal cells and tissues. SMM-seq detects single-nucleotide variants, small insertions and deletions, and structural variants, providing a comprehensive tool for somatic mutational burden assessment. Our research has two specific aims: 1) optimize and validate an integrated SMM-seq assay for measuring the mutational landscape of normal cells, focusing on protocol consolidation, automation, and precision and recall evaluation; and 2) assess the mutagenicity of known genotoxic agents on human primary cells. In this Phase 1, we will establish the technical merit and feasibility of SMM-seq and develop a prototype platform, and scale up and expand applications in subsequent phases. The resulting diagnostic product will address a market gap by providing a practical analytical tool for integrated genetic toxicity/mutagenicity testing and monitoring human exposure to mutagenic agents, supporting the launch of a successful business venture.

Key facts

NIH application ID
10830629
Project number
1R43ES036101-01
Recipient
MUTAGENTECH, INC.
Principal Investigator
Alexander Y. Maslov
Activity code
R43
Funding institute
NIH
Fiscal year
2024
Award amount
$275,763
Award type
1
Project period
2024-02-06 → 2025-01-31