THE BAILIS LAB
The University of Pennsylvania & the Children’s Hospital of Philadelphia
All biological processes operate under biochemical constraints. The Bailis lab aims to understand how metabolism controls immune cell state by setting the biochemical potential of cells and tissues.
It has been nearly 20 years since the human genome was sequenced. This heroic effort has resulted in the identification of over 20,000 protein coding genes and over 40,000 non-coding transcripts, yet the majority of human disease and pathological conditions still lack simple genetic explanations and lack curative treatment. Moreover, hundreds of genome-wide association studies have been performed across disease contexts, and while this approach has been highly informative in directing research, we have made little progress in advancing our treatment of some of the most monumental health challenges that face us. We assert that this vast discrepancy in genetic knowledge and clinical outcome stems not from a poor understanding of the genome or genetic regulation, but that we have largely overlooked how a more ancient and fundamental aspect of biology underlies human health: the metabolic regulation of cellular and organismal biochemistry.
We traditionally think of cell state (i.e. whether a cell is a skin cell or a liver cell, a resting or inflammatory immune cell, a living cell or a dying cell) as driven by how cells relay information from their environment to their nucleus to turn genes on or off, a process known as signal transduction. This paradigm for understanding how cells process information is in large part shaped by our appreciation of the “Central Dogma” of biology: that the information necessary for life is maintained in the ordered sequence of nucleotides in an organism’s genome (DNA) that can be used to arrange the sequence of nucleotides in RNA’s, which in turn orders the sequence of amino acids in the proteins that cary out the work of a cell. Within this context, life and cell state are maintained by three classes of molecules: DNA, RNA, and protein. Accordingly, biological research has focused on understanding how the relationship between these three sets of molecules underlies human health and disease.
While the appreciation of the Central Dogma and the study of signal transduction have been the basis of most major advances in biomedical research, we have largely overlooked the fact that DNA, RNA, and protein are all composed of smaller biochemical units (nucleic acids and amino acids, respectively), which by definition must predate life itself. The rules by which these fundamental biomolecules are generated and interact with one another therefore must be incorporated into the framework of every layer of evolution that life has been selected on. We seek to test hypothesize that the metabolic pathways that connect these biochemical molecules form the most ancient and fundamental information processing systems used by life. Though they are less durable than the networks that compose the Central Dogma, these biochemical pathways define the boundaries of what a cell is capable of in real-time and what near-term states it is equipped to adopt.
The goal of our research is to begin understanding the logic of how these biochemical networks are organized – both through the reactions they participate in and the manner they are spatially compartmentalized within and between cells – and how they interact with well appreciated signal transduction pathways. We believe this perspective will open new avenues for designing metabolism-based therapies for treating disease and help illuminate why so many pathologies cannot simply be explained by genetics. Unlike therapies targeting signal transduction, which often entail antibody or peptide/protein-based therapeutics that are expensive to develop and require sophisticated infrastructure to produce, metabolites and their derivatives are less costly to generate and have more modest manufacturing demands, offering the potential to vastly expand both treatment access and affordability. Moreover, metabolic networks have built-in negative and positive feedback systems using metabolites within a pathway, making them readily druggable with a large degree of specificity. Our group aims to actively leverage the therapeutic potential of cellular metabolism and translate our basic mechanistic findings into novel treatments and diagnostics for human disease.