Trends in Microbiome and Digital One Health

We live in a microbial world estimated to contain >1 million species with vast genetic diversity arising from 4 billion years of evolution. Microorganisms are adapted to most habitats as complex communities shaped by ecological interactions and yet little is known about how this unseen world is organized. Humanity’s perception of microbes is shaped by a small fraction of pathogenic species leading to an adversarial relationship defined by the pervasive use of antimicrobial agents. Efforts to eradicate microbes have met with limited success. Disinfected environments are rapidly recolonized while antibiotic treatments increasingly select for resistant pathogens.

The global rise in antimicrobial resistance (AMR) rates for common pathogens (e.g. ESKAPE) is recognized as a pre-eminent threat to healthcare systems. As the range of effective antibiotics shrinks we approach a tipping point where no antibiotic works for a pathogen, putting at risk the lives of millions of vulnerable patients in hospitals worldwide. Already >1 million deaths/year are attributed to AMR, surpassing estimates for COVID-19, HIV/AIDS and malaria. By 2050 the UN projects that AMR will be responsible for more deaths every year than all cancers (>10 million deaths/year), with >$3 trillion in economic impact/year by 2030. Parts of Asia are particularly vulnerable as AMR hubs, fueled by several factors including higher infectious disease burden and inappropriate antibiotic usage. 

We need radically new approaches to understand the microbial world we live in and change the rules of interaction. We propose that this involves (i) systematically deconstructing microbial communities by combining genome-resolved metagenomics and high-throughput culturing, (ii) modelling principles of community organization by studying defined complex communities in vitro and in vivo, and (iii) reconstructing ecological functions of natural microbial communities based on predictive models to suppress the burden of pathogenic species. In this talk, I will present some of the tools we have been developing towards these goals including for genome-resolved metagenomics1 and generalized-Lotka-Volterra modelling from metagenomic data2,3. These have served to provide new insights into the impact of antibiotics on the gut microbiome4 and how colonization resistance might emerge5, as well as the spread of multi-drug resistant organisms through hospital environments6. I will highlight some of these applications in my talk and how we envision the development of improved guidelines and new classes of interventions to tackle the global challenge of antimicrobial resistance.