Capturing, quantifying, and understanding combinatorial effects in small molecule signaling

Harvard Medical School, Boston MA

Investigators

Linked publications, trials & patents

Abstract

Project Summary/Abstract Chemical landscapes in biology consist of thousands to millions of different small molecules, such that cells and organisms always experience any single small molecule in the context of other molecules. Indeed, biological processes from cell fate decisions to regulation of central metabolism are driven by combined action of multiple small molecules. Insight into such combinatorial effects, however, is largely based on anecdotal evidence; as yet, there exists no coherent framework to capture and quantify combinatorial effects in small molecule signaling. This gap limits the ability of scientists to study signaling in the complex chemical landscapes found in biology, to predict biological activities of small molecules, and to manipulate small molecule signaling in the context of disease. This work will develop a conceptual, experimental, and analytical framework to capture and quantify combinatorial effects of different molecules, or “chemical epistasis”. As a starting point, this work will focus on signaling in the context of communication between the human microbiome and the human host, which provides an ideal testbed. Working in this context, the first goal is to develop experimental and analytical approaches to capture chemical epistasis and to use these approaches to measure empirically how pervasive chemical epistasis is in pairwise combinations of small molecules from the human microbiome. From there, this work will continue in three broad directions: 1) a broader exploration of the scope and manifestations of chemical epistasis including in combinations of three or more small molecules; 2) a dissection of mechanisms underlying chemical epistasis, using a combination of systematic CRISPR screens and focused approaches; and 3) exploration of the physiological consequences of epistasis, harnessing defined microbiome communities to independently control the concentrations of multiple small molecules in vivo. This work will be transformative for efforts to establish causal links in host-microbiome interactions and to predict and manipulate outcomes of host-microbiome communication, for example to alleviate microbiome-associated diseases. More broadly, complex chemical landscapes are a central feature of biology, and this work will lay the groundwork to understand signaling in these landscapes.