Research
Biodegradation and production microbiomes
This project, in collaboration with the Joint BioEnergy Institute (JBEI), focuses on the editing of lignin-degrading microbiomes. The ability to implement targeted DNA editing in JBEI microbiomes will facilitate improved genetic understanding and control of these microbial communities for biodegradation and production.
Soil microbial editing
This work will build on previously successful editing of soil microbiomes in our lab. Using CRISPR-based editing within bacterial hosts, we hope to investigate the interactions and activities of microbes within rhizosphere communities. In the longer term, this engineering should allow improved plant growth on marginal soils.
Decreasing livestock methane emissions through editing
Editing the DNA of livestock gut microbes has the potential to decrease methane emissions using highly targeted modifications, replacing blunter breeding and feeding strategies. Ongoing work will optimize these tools from their previously validated use on gut microbes in the lab so that they can be efficiently deployed to livestock in the field.
Gut microbiome editing for improved health
We aim to harness new DNA delivery and editing systems, along with those we have previously developed, for efficient modification of microbes within human guts. The development of highly targeted and efficient gene editing tools in the gut microbiome should expand the causal understanding of the role of genes in this fundamentally important community. The work should also help shift the medical intervention standard from the sledgehammer of antibiotics to the scalpel of targeted DNA editing.
Machine learning for next-generation editing tools
This project leverages large language models to discover and engineer new DNA editing systems. By training models on natural mobile genetic elements, we aim to harvest four billion years of evolutionary knowledge to create bespoke editing vectors with user-defined properties. We are also using machine learning to discover highly divergent editing systems that could overcome current limitations in the CRISPR-Cas toolset. Our approach connects massive microbial genomic datasets, cutting-edge ML architectures, and experimental validation in diverse bacterial hosts, creating a feedback loop that continuously refines our ability to engineer microbiomes from soil communities to the human gut.
All illustrations created by Chenyu Zhang!