Speaker: Liat Shenhav, Ph.D., Fellow, Center for Studies in Physics and Biology, Rockefeller University
Title: It’s about time: ecological and eco-evolutionary dynamics across the scales
The explosion of multi-omics longitudinal data holds the potential to unlock complex and dynamic biological processes but analyzing and modeling these dynamics is not simple. To address this challenge, I devise models that combine longitudinal data analysis and statistical learning, and which draw from principles of community ecology and evolution. As building blocks of my approach, I will briefly present methods for decomposition and context-aware dimensionality reduction of microbial dynamics (Shenhav et al., Nature Methods 2019; Martino & Shenhav et al., Nature Biotechnology 2020), and show how incorporating eco-evolutionary considerations allowed us to detect signals of purifying selection across diverse ecosystems (Shenhav & Zeevi, Science 2020). I will further present new results from an ongoing study in which those concepts are combined to build integrative models of the mother-milk-infant triad, which are then used to predict infant respiratory health. I found that the temporal dynamics of microbiota in the first year of life, mediated by milk composition, predict the development of chronic respiratory disease later in childhood. These models, designed to identify robust spatiotemporal patterns, would help us better understand the nature and impact of complex biological systems from the time of formation and throughout life.
