The interaction between a pathogen and its host is an evolutionary arms race of ever-changing components. Vast arrays of receptors are produced by B- and T-cells of the host adaptive immune system to detect and clear the pathogen. In response, mutations arise within parts of the pathogen’s genome recognized by these receptors. These mutations are positively selected and accumulate at a rapid rate, often leading to immune escape. What are the mechanisms governing the interaction between these partners? Why is a pathogen successful in some hosts, but not in others? What does these signatures tell us about outbreak dynamics? How can we use this knowledge to develop new therapeutics? Advances in metagenomic next-generation sequencing (mNGS) have revolutionized our ability to survey genetic variation in hosts and microbes allowing us to address these fundamental questions.
We are taking advantage of these tools, in combination with a well established network of collaborators and collection sites across West Africa and South America, to uncover the mechanisms that underpin this arms race. We employ mNGS, experimentation and evolutionary theory to conduct research on Zika virus (ZIKV), Ebola virus (EBOV) and Lassa virus (LASV) infections. Based on our large-scale datasets, we perform system-level analyses to understand how the viruses emerge and spread during outbreaks, and how they interact and co-evolve with the host adaptive immune system. A quantitative understanding of the underlying co-evolutionary mechanisms will contribute to the prevention and treatment of human pathogens, and will provide insights into how genetic diversity leads to pathogen emergence.
We have previously shown how EBOV evolves over the course of an outbreak (Gire et. al, Science 2014; Park et. al, Cell 2015; Diehl et. al, Cell 2016; Holmes et. al, Nature 2016). We have also described how LASV evolves within individuals and how that interferes with its transmission between hosts (Andersen et. al, Cell 2015). We are now also using these methods to study ZIKV. Many of the mutations that we observe in the virus genomes appear to be under positive selection from both B- and T-cell mediated pressures. We found that these selection pressures appear to be similar in both infected patients, as well as in virus reservoirs. This is surprising, as human patients are believed to carry the virus only for a short period of time, whereas reservoirs are known to be infected asymptomatically for life. These observations suggest that each infected host is driving positive selection in the virus population, and that individual mutations may confer fitness advantages by enabling viral immune escape.
Using mNGS, we investigate how and when these mutations originate in ZIKV, EBOV, and LASV genomes, and how they might confer fitness advantages. Using virus genomic signatures allows us to gain unprecedented insights into the beginnings and dynamics of infectious disease outbreaks. In addition, using mNGS, we follow the host dynamics of B- and T-cells, to get a complete picture of the co-evolution between host and pathogen over an extended period of time. Using a combination of field work, experimentation, and computational biology, we investigate samples obtained from human patients and natural reservoirs with ZIKV, LASV and EBOV.
By obtaining a complete understanding of intrahost viral dynamics and the architecture of effective immune networks, it is our hope that we will be able to help transform outbreak response and inform the future development of effective vaccines and novel therapeutics.