Nicholas DiBenedetto

The paper introduces MDSINE2, a Bayesian method for inferring microbial dynamics from time-series data, and shows it outperforms existing methods in identifying ecosystem-scale interactions.

This study identifies distinct growth and chaining properties in Clade 5 Clostridioides difficile strains using time-lapse microscopy, linked to the cmr switch sequence orientation.

This study develops a method to visualize single-cell phenotypic heterogeneity in gut microbial communities using spectrally compatible reporters, revealing subpopulation behavior in Clostridioides difficile during infection.

The paper develops regulatory, metabolic, and integrated models for C. difficile to understand its colonization mechanisms and interactions with the gut microbiota.

The paper engineers inter-species amino acid cross-feeding in bacterial consortia to increase population evenness in synthetic microbial communities.