Skip to main navigation Skip to search Skip to main content

SBIR Phase I: Enhanced Rock Weathering through Gene Editing of Soil Microorganisms

Project: Research

Abstract & Details

Description

Award ID: 2507231

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is to develop a new biological input for agriculture that offers farmers improved economics through improved soil fertility, reduced reliance on chemical inputs, and enhanced crop resilience. By generating additional revenue through carbon credits, this technology also enables a viable financial pathway for large-scale adoption and increased competitiveness of U.S. agriculture. The problem to be studied is how soil microbes can be optimized to accelerate the process of mineral rock weathering to naturally build healthier and more nutrient rich soils, while reducing unwanted acidity and capturing atmospheric CO2. The net commercial impact of this project will be the development of ameliorated mineral rock dust as an efficient agricultural input, additional revenue and cost savings for American farmers, mining and distribution jobs across Americas farmlands, and the expansion of US biotechnology in the agricultural industry. This scientific innovation will deliver nutrients to crops, put money in farmers pockets, and increase national food security. The net effect will be to help American farmers thrive economically and to produce our food more efficiently. This SBIR Phase I project will deploy cutting-edge microbial strain engineering methods to strengthen the native capacity of selected beneficial soil microbes for breaking down silicate mineral rock in the process of soil formation. The aim is to support the creation of a product that doubles the native rate of mineral rock breakdown in target soils for one season. Strain engineering represents a broad set of techniques that have been highly successful when applied to domesticated industrial strains but has never been used to improve the mineral rock weathering behavior of wild bacterial isolates. This project will characterize a unique library of candidate microbial soil isolates according to their capacity for mineral rock weathering and their engineerability. A selected bacterial isolate will serve as a host for a series of novel gene edits, each of which has the potential to enhance one or more biological mechanisms that lead to rock weathering. These gene edits will be built into the host using the techniques of DNA synthesis, bacterial transformation, and single crossover genomic integration. Additionally, this project will use traditional random mutagenesis methods to create variants of the isolated host. Engineered strains will then be assayed for improved ability to weather silicate rock rapidly and efficiently, establishing their eventual utility. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Rajesh Mehta
StatusClosed
Effective start/end date05/15/2504/30/26

Funding

  • SBIR Phase I: $304,748.00

Active Fiscal Year

  • FY2026
  • FY2025

Start Fiscal Year

  • FY2025

TIP Programs

  • SBIR Phase I

Small Business

  • Yes

Key Technology Areas

  • Biotechnology
  • (confidence score: 100%)
  • Advanced Energy and Industrial Efficiency Technologies
  • (confidence score: 95%)

Technology Foci

  • Synthetic Biology
  • (confidence score: 99%)
  • Carbon management technologies
  • (confidence score: 93%)
  • Biotechnology - Other than SynBio
  • (confidence score: 100%)
  • Genomics and bioinformatics
  • (confidence score: 100%)

Congressional District at Award

  • District n. 08 of California

Current Congressional District

  • District n. 08 of California

United States

  • California

Core Based Statistical Area (CBSA)

  • San Francisco-Oakland-Fremont, CA

County

  • County: Contra Costa, CA

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint. Learn more about Elsevier's Fingerprint Engine here: https://beta.elsevier.com/products/elsevier-fingerprint-engine