ORNL platform accelerates bacterial gene mapping for biotech engineering

Scientists at Oak Ridge National Laboratory have developed a platform that rapidly identifies genetic triggers for desirable traits in bacteria, supporting the engineering of microbial strains for industrial biotechnology. The approach integrates synthetic biology, artificial intelligence, and statistical mapping to assess bacterial traits and pinpoint candidate genes, which are then validated using CRISPR gene editing. The work was published in Nature Communications.

The platform builds on quantitative trait locus (QTL) mapping, a technique common in plant genetics but historically difficult to apply to bacteria because they reproduce asexually with limited genetic variation. ORNL researchers overcame this by adapting protoplast fusion, a method from the 1970s, to cross Bacillus strains and generate large populations of genetically diverse recombinant offspring. The technique was also demonstrated in other bacteria, including Clostridium thermocellum, Novosphingobium aromaticivorans, and Stutzerimonas stutzeri.

Researchers measured traits across the diverse progeny and identified DNA variants linked to differences in those traits. Automation and computer vision accelerated phenotyping tenfold, using a robotic system to standardize high-resolution imaging for consistent data extraction. Mathematical algorithms and a computer vision model processed the images to quantify traits across thousands of recombinants.

"Unlike past approaches that study the effect of gaining or losing whole genes, the new approach lets us determine how small differences in the nucleotide sequence affect bacterial function," said Josh Michener, co-lead for the project and Biological Systems Design group leader at ORNL. He noted that nucleotide-level variations have a large impact on phenotype, especially when engineering microbes with specific mutations.

Co-lead Dan Jacobson, a computational systems biologist at ORNL, emphasized the multidisciplinary collaboration required, spanning robotics, imaging, statistical mapping, genome assembly, DNA sequencing, and phenotype assays. The platform is available for licensing and is being deployed through the DOE Center for Bioenergy Innovation at ORNL, the Secure Ecosystem Engineering and Design Science Focus Area, and a program at Colorado State University studying airborne microbes.

Applications include designing microbes to break down plant lignin into valuable chemicals, convert cellulose, recover critical minerals, and support soil health. The integrated workflow — from generating genetic diversity to automated phenotyping and gene validation — represents the first time these components have been combined into a single platform for rapid gene-to-trait linkage discovery in bacteria.