Virus genomics

Mosquito- and tick-borne viruses, such as Zika, West Nile, and Powassan, continue to emerge into new areas, and sometimes, they surprise us by causing large outbreaks and severe disease. We use genomics to investigate how they spread (genomic epidemiology), cause disease (functional evolution), and adapt to new environments (experimental evolution). Together, these studies can help us better understand and respond to outbreaks.

Genomic epidemiology

By sequencing viruses and reconstructing phylogenetic trees, we can track key events during outbreaks (Grubaugh et al., 2019). We recently teamed up with a large group of international collaborators to investigate the Zika virus epidemic in the Americas by sequencing directly from clinical samples and field-collected mosquitoes. Our team determined that Zika virus was introduced into Brazil more than a year before it was first detected, and by that time, it had already spread to most of the Americas (Metsky et al., 2017; Faria et al., 2017). In Florida, we determined that the Zika outbreak was fueled by many introductions coming from the Caribbean Islands (Grubaugh et al., 2017). Furthermore, we investigated the risk factors leading to Zika virus spread (Gardner et al., 2018) and compiled our genetic findings to reveal insights into its emergence (Grubaugh et al., 2018). We will continue to incorporate genomic epidemiology as we seek to understand virus emergence. For example, we will investigate virus spillover from sylvatic to urban transmission cycles in South America and how West Nile virus is being maintained in North America ~20 years since it first arrived (WestNile 4K). To rapidly share our analyses with our collaborators and the public, we are creating Nexstrain webpages. To do these projects, we will collaborate with many awesome labs from around the world (see a list of our collaborators at the bottom of the “team” page).

Functional evolution

What caused the sudden onset of severe congenital disease associated with Zika virus infections? Has the virus always been able to do this or is the virus now suddenly different? This topic has been hotly debated since the epidemic began (Grubaugh & Andersen, 2016). We recently cataloged many Zika virus mutations through our sequencing studies and will extensively test their fitness using in vitro and in vivo experiments. Combined with epidemiological information, we will use this data to help determine the role of Zika virus genetic factors associated with the epidemic. In a similar study, we found that a mutation in the ebola virus glycoprotein (A82V) arose early during the recent West Africa epidemic and enhanced infection in human cells, suggesting adaptation to human infection and/or transmission (Diehl et al., 2016). From the host’s side, we identified a novel human allele present in 1/3 of people with African ancestry that provides resistence to Plasmodium infection (Ma et al., 2018). We will continue to use this pipeline of field sequencing, identifying mutations of interest, and experimental fitness evaluation (i.e., functional evolution) to understand how other emerging mosquito-borne viruses, like Mayaro and Oropouche, may be changing in response to their environments.

Experimental evolution

A central aspect of RNA virus biology is that they exist as genetically diverse populations within hosts, primarily stemming from their high mutation rates, rapid replication, and large population sizes. The composition of genetic diversity within hosts provides the foundation for adaptation and can alter the outcome of infection. We previously used experimental evolution to describe the factors influencing West Nile virus evolution within mosquito vectors and vertebrate hosts (Grubaugh et al., 2017; Grubaugh et al., 2016a; Grubaugh et al., 2015). In general, we found that mosquito-borne viruses go through cycles of genetic drift and strong purifying selection (Grubaugh & Ebel, 2016), which may be why they have slower evolutionary rates compared to many single host viruses. Tick-borne virus evolution is driven by many of the same forces, such as tick RNAi-driven diversification and genetic drift, but they also have unique features because of their vector ecology (Grubaugh et al., 2016b). We plan to expand these studies to understand the conditions that promote virus emergence (Grubaugh & Andersen, 2017), such as adaptation to new hosts and escape from immune or therapeutic pressures. These data will help us to define evolutionary pathways that a virus may take and to develop novel countermeasures to thwart them.

Methods development

Each project comes with their own set of challenges – e.g., harsh field conditions, sample degradation, mosquito manipulation, etc – and we are constantly searching for new approaches to overcome them. For example, we developed a method called “xenosurveillance” to detect human and animal pathogens in resource poor settings by collecting blood from recently fed mosquitoes, avoiding the need for direct blood draws by trained clinicians (Grubaugh et al., 2015). For laboratory studies, we developed a method to sequentially collect mosquito saliva from individual mosquitoes by exploiting their sugar feeding needs (see figure, Grubaugh et al., 2017), allowing us to track viral populations and more precisely measure the extrinsic incubation period. On a different front, due to the very low titers in clinical samples, many researchers were finding it difficult to sequence Zika virus, resulting in very limited data being released. We solved this issue by developing a highly multiplexed PCR approach to amplify the virus genome in many small pieces (i.e., “RNA jackhammering”), greatly enhancing our sequencing sensitivity (Quick et al., 2017). We are now using it as a cost-effective solution to sequence other viruses, such as West Nile and chikungunya, and have validated for use in measuring intrahost virus diversity (Grubaugh et al., 2019). We try not to be limited by what can be done with current technology and are always open to new approaches.