Research

Identifying heterogeneity in clinical samples

Complicated bacterial infections are often difficult to treat and frequently recur, as in urinary tract infections. One reason is the presence of bacterial subpopulations that survive therapy by occupying distinct physiological states. We aim to identify and characterize these co-existing bacterial states directly in clinical samples by combining Microcolony-seq with experimental and computational tools.

Study mechanisms that lead to bacterial memory

We observed that bacteria can “remember” past conditions, maintaining distinct functional states across generations. We aim to uncover the mechanisms that create this cellular memory and those that reset it. By understanding how bacterial states are stabilized, inherited, and eventually lost, we aim to explain how phenotypic diversity emerges during infection and how it dynamically adapts to changing environments.

Identifying new virulence genes

Traditional approaches to identify virulence genes often rely on comparing bacteria grown under different conditions, making it difficult to separate true virulence programs from general growth effects. By comparing bacterial subpopulations grown under identical conditions using Microcolony-seq, we aim to uncover previously hidden virulence factors that drive host interaction and disease.