Evolutionary dynamics of viral escape under antibodies stress: A biophysical model

Biophysical principles predict fitness of SARS-CoV-2 variants

SARS-CoV-2 employs its spike protein's receptor binding domain (RBD) to enter host cells. The RBD is constantly subjected to immune responses, while requiring efficient binding to host cell receptors for successful infection. However, our understanding of how RBD's biophysical properties contribute to SARS-CoV-2's epidemiological fitness remains largely incomplete. Through a comprehensive approach, comprising large-scale sequence analysis of SARS-CoV-2 variants and the identification of a fitness function based on binding thermodynamics, we unravel the relationship between the biophysical properties of RBD variants and their contribution to viral fitness. We developed a biophysical model that uses statistical mechanics to map the molecular phenotype space, characterized by dissociation constants of RBD to ACE2, LY-CoV016, LY-CoV555, REGN10987, and S309, onto an epistatic fitness landscape. We validate our findings through experimentally measured and machine learning (ML) estimated binding affinities, coupled with infectivity data derived from population-level sequencing. Our analysis reveals that this model effectively predicts the fitness of novel RBD variants and can account for the epistatic interactions among mutations, including explaining the later reversal of Q493R. Our study sheds light on the impact of specific mutations on viral fitness and delivers a tool for predicting the future epidemiological trajectory of previously unseen or emerging low-frequency variants. These insights offer not only greater understanding of viral evolution but also potentially aid in guiding public health decisions in the battle against COVID-19 and future pandemics.

Biophysical principles predict fitness of SARS-CoV-2 variants

SARS-CoV-2 employs its spike protein's receptor binding domain (RBD) to enter host cells. The RBD is constantly subjected to immune responses, while requiring efficient binding to host cell receptors for successful infection. However, our understanding of how RBD's biophysical properties contribute to SARS-CoV-2's epidemiological fitness remains largely incomplete. Through a comprehensive approach, comprising large-scale sequence analysis of SARS-CoV-2 variants and the discovery of a fitness function based on binding thermodynamics, we unravel the relationship between the biophysical properties of RBD variants and their contribution to viral fitness. We developed a biophysical model that uses statistical mechanics to map the molecular phenotype space, characterized by binding constants of RBD to ACE2, LY-CoV016, LY-CoV555, REGN10987, and S309, onto a epistatic fitness landscape. We validate our findings through experimentally measured and machine learning (ML) estimated binding affinities, coupled with infectivity data derived from population-level sequencing. Our analysis reveals that this model effectively predicts the fitness of novel RBD variants and can account for the epistatic interactions among mutations, including explaining the later reversal of Q493R. Our study sheds light on the impact of specific mutations on viral fitness and delivers a tool for predicting the future epidemiological trajectory of previously unseen or emerging low frequency variants. These insights offer not only greater understanding of viral evolution but also potentially aid in guiding public health decisions in the battle against COVID-19 and future pandemics.

A hijack mechanism of Indian SARS-CoV-2 isolates for relapsing contemporary antiviral therapeutics

Coronavirus disease (COVID-19) rapidly expands to a global pandemic and its impact on public health varies from country to country. It is caused by a new virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It is imperative for relapsing current antiviral therapeutics owing to randomized genetic drift in global SARS-CoV-2 isolates. A molecular mechanism behind the emerging genomic variants is not yet understood for the prioritization of selective antivirals. The present computational study was aimed to repurpose existing antivirals for Indian SARS-CoV-2 isolates by uncovering a hijack mechanism based on structural and functional characteristics of protein variants. Forty-one protein mutations were identified in 12 Indian SARS-CoV-2 isolates by analysis of genome variations across 460 genome sequences obtained from 30 geographic sites in India. Two unique mutations such as W6152R and N5928H found in exonuclease of Surat (GBRC275b) and Gandhinagar (GBRC239) isolates. We report for the first time the impact of folding rate on stabilizing/retaining a sequence-structure-function-virulence link of emerging protein variants leading to accommodate hijack ability from current antivirals. Binding affinity analysis revealed the effect of point mutations on virus infectivity and the drug-escaping efficiency of Indian isolates. Emodin and artinemol suggested herein as repurposable antivirals for the treatment of COVID-19 patients infected with Indian isolates. Our study concludes that a protein folding rate is a key structural and evolutionary determinant to enhance the receptor-binding specificity and ensure hijack ability from the prevalent antiviral therapeutics.

Evolution on the Biophysical Fitness Landscape of an RNA Virus

Viral evolutionary pathways are determined by the fitness landscape, which maps viral genotype to fitness. However, a quantitative description of the landscape and the evolutionary forces on it remain elusive. Here, we apply a biophysical fitness model based on capsid folding stability and antibody binding affinity to predict the evolutionary pathway of norovirus escaping a neutralizing antibody. The model is validated by experimental evolution in bulk culture and in a drop-based microfluidics that propagates millions of independent small viral subpopulations. We demonstrate that along the axis of binding affinity, selection for escape variants and drift due to random mutations have the same direction, an atypical case in evolution. However, along folding stability, selection and drift are opposing forces whose balance is tuned by viral population size. Our results demonstrate that predictable epistatic tradeoffs between molecular traits of viral proteins shape viral evolution.

Survival of the simplest in microbial evolution

The evolution of microbial and viral organisms often generates clonal interference, a mode of competition between genetic clades within a population. Here we show how interference impacts systems biology by constraining genetic and phenotypic complexity. Our analysis uses biophysically grounded evolutionary models for molecular phenotypes, such as fold stability and enzymatic activity of genes. We find a generic mode of phenotypic interference that couples the function of individual genes and the population’s global evolutionary dynamics. Biological implications of phenotypic interference include rapid collateral system degradation in adaptation experiments and long-term selection against genome complexity: each additional gene carries a cost proportional to the total number of genes. Recombination above a threshold rate can eliminate this cost, which establishes a universal, biophysically grounded scenario for the evolution of sex. In a broader context, our analysis suggests that the systems biology of microbes is strongly intertwined with their mode of evolution.

In asexual populations selection at different genomic loci can interfere with each other. Here, using a biophysical model of molecular evolution the authors show that interference results in long-term degradation of molecular function, an effect that strongly depends on genome size.

SodaPop: a forward simulation suite for the evolutionary dynamics of asexual populations on protein fitness landscapes

Motivation

Protein evolution is determined by forces at multiple levels of biological organization. Random mutations have an immediate effect on the biophysical properties, structure and function of proteins. These same mutations also affect the fitness of the organism. However, the evolutionary fate of mutations, whether they succeed to fixation or are purged, also depends on population size and dynamics. There is an emerging interest, both theoretically and experimentally, to integrate these two factors in protein evolution. Although there are several tools available for simulating protein evolution, most of them focus on either the biophysical or the population-level determinants, but not both. Hence, there is a need for a publicly available computational tool to explore both the effects of protein biophysics and population dynamics on protein evolution.

Results

To address this need, we developed SodaPop, a computational suite to simulate protein evolution in the context of the population dynamics of asexual populations. SodaPop accepts as input several fitness landscapes based on protein biochemistry or other user-defined fitness functions. The user can also provide as input experimental fitness landscapes derived from deep mutational scanning approaches or theoretical landscapes derived from physical force field estimates. Here, we demonstrate the broad utility of SodaPop with different applications describing the interplay of selection for protein properties and population dynamics. SodaPop is designed such that population geneticists can explore the influence of protein biochemistry on patterns of genetic variation, and that biochemists and biophysicists can explore the role of population size and demography on protein evolution.

Availability and implementation

Source code and binaries are freely available at https://github.com/louisgt/SodaPop under the GNU GPLv3 license. The software is implemented in C++ and supported on Linux, Mac OS/X and Windows.

Supplementary information

Supplementary data are available at Bioinformatics online.

Using Antibodies and Mutants To Localize the Presumptive gH/gL Binding Site on Herpes Simplex Virus gD

HSV virus-cell and cell-cell fusion requires multiple interactions between four essential virion envelope glycoproteins, gD, gB, gH, and gL, and between gD and a cellular receptor, nectin-1 or herpesvirus entry mediator (HVEM). Current models suggest that binding of gD to receptors induces a conformational change that leads to activation of gH/gL and consequent triggering of the prefusion form of gB to promote membrane fusion. Since protein-protein interactions guide each step of fusion, identifying the sites of interaction may lead to the identification of potential therapeutic targets that block this process. We have previously identified two "faces" on gD: one for receptor binding and the other for its presumed interaction with gH/gL. We previously separated the gD monoclonal antibodies (MAbs) into five competition communities. MAbs from two communities (MC2 and MC5) neutralize virus infection and block cell-cell fusion but do not block receptor binding, suggesting that they block binding of gD to gH/gL. Using a combination of classical epitope mapping of gD mutants with fusion and entry assays, we identified two residues (R67 and P54) on the presumed gH/gL interaction face of gD that allowed for fusion and viral entry but were no longer sensitive to inhibition by MC2 or MC5, yet both were blocked by other MAbs. As neutralizing antibodies interfere with essential steps in the fusion pathway, our studies strongly suggest that these key residues block the interaction of gD with gH/gL.IMPORTANCE Virus entry and cell-cell fusion mediated by HSV require gD, gH/gL, gB, and a gD receptor. Neutralizing antibodies directed against any of these proteins bind to residues within key functional sites and interfere with an essential step in the fusion pathway. Thus, the epitopes of these MAbs identify critical, functional sites on their target proteins. Unlike many anti-gD MAbs, which block binding of gD to a cellular receptor, two, MC2 and MC5, block a separate, downstream step in the fusion pathway which is presumed to be the activation of the modulator of fusion, gH/gL. By combining epitope mapping of a panel of gD mutants with fusion and virus entry assays, we have identified residues that are critical in the binding and function of these two MAbs. This new information helps to define the site of the presumptive interaction of gD with gH/gL, of which we have limited knowledge.

Human dengue virus serotype 2 neutralizing antibodies target two distinct quaternary epitopes

Dengue virus (DENV) infection causes dengue fever, dengue hemorrhagic fever and dengue shock syndrome. It is estimated that a third of the world’s population is at risk for infection, with an estimated 390 million infections annually. Dengue virus serotype 2 (DENV2) causes severe epidemics, and the leading tetravalent dengue vaccine has lower efficacy against DENV2 compared to the other 3 serotypes. In natural DENV2 infections, strongly neutralizing type-specific antibodies provide protection against subsequent DENV2 infection. While the epitopes of some human DENV2 type-specific antibodies have been mapped, it is not known if these are representative of the polyclonal antibody response. Using structure-guided immunogen design and reverse genetics, we generated a panel of recombinant viruses containing amino acid alterations and epitope transplants between different serotypes. Using this panel of recombinant viruses in binding, competition, and neutralization assays, we have finely mapped the epitopes of three human DENV2 type-specific monoclonal antibodies, finding shared and distinct epitope regions. Additionally, we used these recombinant viruses and polyclonal sera to dissect the epitope-specific responses following primary DENV2 natural infection and monovalent vaccination. Our results demonstrate that antibodies raised following DENV2 infection or vaccination circulate as separate populations that neutralize by occupying domain III and domain I quaternary epitopes. The fraction of neutralizing antibodies directed to different epitopes differs between individuals. The identification of these epitopes could potentially be harnessed to evaluate epitope-specific antibody responses as correlates of protective immunity, potentially improving vaccine design.

Dengue viruses (DENV) are flaviviruses transmitted by mosquitos. There are approximately 390 million DENV infections every year, making dengue virus a major global public health concern. While there is a recently licensed DENV vaccine, it has low efficacy against preventing DENV2 infections. Individuals that are naturally infected with DENV2 generate neutralizing antibodies that can be protective against reinfection with DENV2. By studying three of these neutralizing antibodies, we found that they bind to two different locations on the surface of the virus. Additionally we found that most individuals that were naturally infected with DENV2, have antibodies circulating in their blood that target both of these regions. People who were vaccinated against DENV2 also make antibodies targeting both of these sites, suggesting they might also be protected against DENV2 infection. These studies reveal that human antibodies against DENV2 target the same two regions across multiple individuals. Additionally, for a DENV2 vaccine to be protective, it may be important to elicit antibodies directed to these regions as well.

Host proteostasis modulates influenza evolution

Predicting and constraining RNA virus evolution require understanding the molecular factors that define the mutational landscape accessible to these pathogens. RNA viruses typically have high mutation rates, resulting in frequent production of protein variants with compromised biophysical properties. Their evolution is necessarily constrained by the consequent challenge to protein folding and function. We hypothesized that host proteostasis mechanisms may be significant determinants of the fitness of viral protein variants, serving as a critical force shaping viral evolution. Here, we test that hypothesis by propagating influenza in host cells displaying chemically-controlled, divergent proteostasis environments. We find that both the nature of selection on the influenza genome and the accessibility of specific mutational trajectories are significantly impacted by host proteostasis. These findings provide new insights into features of host–pathogen interactions that shape viral evolution, and into the potential design of host proteostasis-targeted antiviral therapeutics that are refractory to resistance.

Influenza viruses, commonly called flu, can evade our immune system and develop resistance to treatments by changing frequently. Specifically, mutations in their genome cause influenza proteins to change in ways that can help the virus evade our defences. However, these mutations come at a cost and can prevent the viral proteins from forming functional and stable three-dimensional shapes – a process known as protein folding – thereby hampering the virus’ ability to replicate.

In human cells, proteins called chaperones can help our other proteins fold properly. Influenza viruses do not have their own chaperones and, instead, hijack those of their host. Host chaperones are therefore crucial to the virus’ ability to replicate. However, until now, it was not known if host chaperones can influence how these viruses evolve.

Here, Phillips et al. used mammalian cells to study how host chaperones affect an evolving influenza population. First, cells were engineered to either have normal chaperone levels, elevated chaperone levels, or inactive chaperones. Next, the H3N2 influenza strain was grown in these different conditions for nearly 200 generations and sequenced to determine how the virus evolved in each distinctive host chaperone environment.

Phillips et al. discovered that host chaperones affect the rate at which mutations accumulate in the influenza population, and also the types of mutations in the influenza genome. For instance, when a chaperone called Hsp90 was inactivated, mutations became prevalent in the viral population more slowly than in cells with normal or elevated chaperone levels. Moreover, some specific mutations fared better in cells with high chaperone levels, whilst others worked better in cells with inactivated chaperones.

These results suggest that influenza evolution is affected by host chaperone levels in complex and important ways. Moreover, whether chaperones will promote or hinder the effects of any single mutation is difficult to predict ahead of time. This discovery is significant, as the chaperones available to influenza can vary in different tissues, organisms and infectious conditions, and may therefore influence the virus' ability to change and evolve in a context-specific manner.

The findings are likely to extend to other viruses such as HIV and Ebola, which also hijack host chaperones for the same purpose. More work is now needed to systematically quantify these effects so that we can better predict how specific chaperones will affect the ability of viruses to adapt, especially in pathologically relevant conditions like fever or viral host-switching. In the future, such insights could help shape the design of treatments to which viruses do not evolve resistance.

Bridging the physical scales in evolutionary biology: from protein sequence space to fitness of organisms and populations

Bridging the gap between the molecular properties of proteins and organismal/population fitness is essential for understanding evolutionary processes. This task requires the integration of the several physical scales of biological organization, each defined by a distinct set of mechanisms and constraints, into a single unifying model. The molecular scale is dominated by the constraints imposed by the physico-chemical properties of proteins and their substrates, which give rise to trade-offs and epistatic (non-additive) effects of mutations. At the systems scale, biological networks modulate protein expression and can either buffer or enhance the fitness effects of mutations. The population scale is influenced by the mutational input, selection regimes, and stochastic changes affecting the size and structure of populations, which eventually determine the evolutionary fate of mutations. Here, we summarize the recent advances in theory, computer simulations, and experiments that advance our understanding of the links between various physical scales in biology.