# Programmable benchtop bioreactors for scalable eco-evolutionary dynamics of the human microbiome > **NIH NIH R01** · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · 2022 · $867,648 ## Abstract PROJECT SUMMARY/ABSTRACT Antibiotic-resistant microbial pathogens are a grave and urgent threat to public health. With rising rates of drug- resistant infections and a diminishing arsenal of new antibiotic treatments, there is pressing need for approaches to better understand, predict, and prevent the emergence of antimicrobial resistance (AMR). To this end, experimental evolution approaches, in which microbial organisms are evolved in the laboratory in user-defined conditions, provide a powerful paradigm to define the evolutionary paths toward AMR. This approach has illuminated genetic pathways to evolving resistance, and can define factors that can be exploited to steer toward drug-susceptible states and guide new clinical strategies. However, the potential of this approach for understanding AMR evolution is fundamentally constrained by technological barriers in conducting continuous culture and evolution experiments, which requires the following key capacities: 1) Scale to evolve across a diversity of microbes, experimental conditions, and antibiotics; 2) Automation for frequent perturbations and feedback over long experimental time scales; 3) Control to reproduce key features of the mammalian gut environment, a primary site for the evolution of AMR in vivo. All existing tools fail in one or more of these capacities. And critically, laboratory evolution studies fail to account for how interactions within bacterial communities impact the evolutionary trajectory, dynamics, and outcomes of AMR. We propose to fill this technological and experimental void by developing a first-in-class, benchtop technology for scalable, automated, and controlled microbial evolution studies, and apply it to two pressing problems in AMR. Because the gut environment is depleted of oxygen (anaerobic), and current technology lacks complete oxygen control, we will first develop a system for individual control of atmospheric conditions across mini-bioreactors (atmostat). We will achieve this in the eVOLVER platform, an open-source microbial culture system for automated control of growth conditions that is easily adapted to new control features, and is exceedingly scalable. Preliminary results of eVOLVER-atmostat demonstrate unprecedented scale for continuous culture and evolution of strict anaerobic gut microbes on the benchtop. The first study will determine the effects of oxygen tension on the mutational fitness landscapes of AMR in E. coli strains. We will implement an automated antibiotic selection regime in combination with atmostat control of oxygen gradients, and employ metagenomic sequencing to map the interactions of oxygen, antibiotics, and strains backgrounds in AMR. The second study will determine how AMR emerges in the ecological context of the gut microbiome, by evolving E. coli strains with a gut community across multiple antibiotics. Applying state-of-the-art abundance quantification over time and population genetics approaches, we will define both the eco... ## Key facts - **NIH application ID:** 10503736 - **Project number:** 1R01AI171100-01 - **Recipient organization:** BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) - **Principal Investigator:** Ahmad Samir Khalil - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $867,648 - **Award type:** 1 - **Project period:** 2022-06-10 → 2027-05-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10503736 ## Citation > US National Institutes of Health, RePORTER application 10503736, Programmable benchtop bioreactors for scalable eco-evolutionary dynamics of the human microbiome (1R01AI171100-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10503736. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*