Spatiotemporal modeling of microbial communities

Monday February, 22, 2021 4:00-5:00 PM Eastern
Zoom link https://mit.zoom.us/j/93674644015
iCal shenhav_2021.ics

Liat Shenhav, PhD
Independent Fellow, The Rockefeller University
Center for Studies in Physics and Biology

Abstract: Complex microbial communities play an important role across many domains of life, from the female reproductive tract, through the oceans, to the plant rhizosphere. The study of these communities offers great opportunities for biological discovery, due to the ease of their measurement, the ability to perturb them, and their rapidly evolving nature. These same properties, however, make it difficult to extract robust and reproducible patterns from these high-dimensional ecosystems. To address this, we developed deconvolution methods which identify lower dimensional, latent states, in microbiome data and highlight differences in host phenotypes. Using these methods we found significant differences between vaginally- and cesarean-delivered infants in terms of initial colonization and succession of their gut microbiome (Shenhav et al., Nature Methods 2019) as well as in the trajectories of these communities in the first years of life (Martino, Shenhav et al., Nature Biotechnology). These models, designed to identify robust spatiotemporal patterns, would help us better understand the nature of the microbiome from the time of its formation and throughout life.