Tuning the course of evolution on the biophysical fitness landscape of an RNA virus

Abstract

1Predicting viral evolution remains a major challenge with profound implications for public 2 health. Viral evolutionary pathways are determined by the fitness landscape, which maps 3 viral genotype to fitness. However, a quantitative description of the landscape and the 4 evolutionary forces on it remain elusive. Here, we apply a biophysical fitness model based 5 on capsid folding stability and antibody binding affinity to predict the evolutionary 6 pathway of norovirus escaping a neutralizing antibody. The model is validated by 7 experimental evolution in bulk culture and in a drop-based microfluidics device, the 8 "Evolution Chip", which propagates millions of independent viral sub-populations. We 9 demonstrate that along the axis of binding affinity, selection for escape variants and drift 10 due to random mutations have the same direction. However, along folding stability, 11 selection and drift are opposing forces whose balance is tuned by viral population size. Our 12 results demonstrate that predictable epistatic tradeoffs shape viral evolution. 13 14

The Role of Evolutionary Selection in the Dynamics of Protein Structure Evolution

“…Integrating these various molecular properties could yield even better predictions of structure evolution rate than contact density alone. Combining information about protein stability, abundance, catalytic rate, and organism population size has already proved a fruitful method of predicting the strength of selection and fate of arising mutations (78).…”

The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology

“…A number of automated ALE devices have been developed that span the range of culturing methods: large volume batch culture (Sandberg et al, 2014;LaCroix et al, 2014;Wong et al, 2018), microtiter plates (Horinouchi et al, 2014;Radek et al, 2017), chemostats/turbidostats (Blaby et al, 2012;Toprak et al, 2013), or microfluidics (Rotem et al, 2016). Such demonstrations establish the broad scope of technologies which can be part of automated strain construction workflows (Chao et al, 2017).…”

Mapping the Evolutionary Potential of RNA Viruses

“…First, the sequestration and manipulation of individual viral particles for genotypic and phenotypic characterization is a fundamentally new way to perform virology (Guo et al, 2017). Recent studies have quantified such phenotypes as viability (Tao et al, 2015a), replication kinetics (Guo et al, 2017), and antibody binding and neutralization (Rotem et al, 2016). Depending on the platform, deep-sequencing technologies are limited by read length and accuracy and therefore require probabilistic reconstruction of the haplotype diversity of the population which limits resolution (Di Giallonardo et al, 2014).…”

“…The ability to finely control host cells and viruses has also made microfluidics a useful tool for miniaturizing and parallelizing viral experimental evolution to explore the influence of evolutionary parameters on the evolution of viral populations (Fischer et al, 2015; Guo et al, 2017; Rotem et al, 2016; Tao et al, 2015a) (Figure 2C). Microfluidic technologies allow simultaneous observation of the genotypes and phenotypes of host and virus at single-cell and single-virus resolution, providing a holistic view of the infection.…”