Massively parallel combinatorial microbiology

Abstract

Reductionist biology of the 20th century rooted pure culture methods and antibiotics as pillars of humankind's interaction with microbiology, igniting a revolution in medicine and biotechnology. The revolution was not without cost. By overlooking complex biological interactions, it introduced new problems--from the sharp rise in immune disorders to the antibiotic resistance crisis--that 21st century tools must address. While 'omics methods have fundamentally expanded our understanding of biological complexity, we lack a generalized method for measuring how the parts of a complex system, such as the individual strains of a microbial community, interact with each other. In this thesis, I present kChip, a new platform for constructing massively parallel combinatorial arrays of these parts in order to measure their interactions directly. I describe how kChip has been used to reveal patterns in microbial community assembly, unearth minimal microbial combinations with desirable functions, and screen for compounds that potentiate antibiotic activity. I demonstrate how kChip can advance the development of new technologies like microbial consortia and combinatorial drug therapies.