Adaptation to fluctuating temperatures in an RNA virus is driven by the most stringent selective pressure

Evolutionary Adaptation of an RNA Bacteriophage to Repeated Freezing and Thawing Cycles

Bacteriophage fitness is determined by factors influencing both their replication within bacteria and their ability to maintain infectivity between infections. The latter becomes particularly crucial under adverse environmental conditions or when host density is low. In such scenarios, the damage experienced by viral particles could lead to the loss of infectivity, which might be mitigated if the virus undergoes evolutionary optimization through replication. In this study, we conducted an evolution experiment involving bacteriophage Qβ, wherein it underwent 30 serial transfers, each involving a cycle of freezing and thawing followed by replication of the surviving viruses. Our findings show that Qβ was capable of enhancing its resistance to this selective pressure through various adaptive pathways that did not impair the virus replicative capacity. Notably, these adaptations predominantly involved mutations located within genes encoding capsid proteins. The adapted populations exhibited higher resistance levels than individual viruses isolated from them, and the latter surpassed those observed in single mutants generated via site-directed mutagenesis. This suggests potential interactions among mutants and mutations. In conclusion, our study highlights the significant role of extracellular selective pressures in driving the evolution of phages, influencing both the genetic composition of their populations and their phenotypic properties.

The balance between fitness advantages and costs drives adaptation of bacteriophage Qβ to changes in host density at different temperatures

Introduction

Host density is one of the main factors affecting the infective capacity of viruses. When host density is low, it is more difficult for the virus to find a susceptible cell, which increases its probability of being damaged by the physicochemical agents of the environment. Nevertheless, viruses can adapt to variations in host density through different strategies that depend on the particular characteristics of the life cycle of each virus. In a previous work, using the bacteriophage Qβ as an experimental model, we found that when bacterial density was lower than optimal the virus increased its capacity to penetrate into the bacteria through a mutation in the minor capsid protein (A1) that is not described to interact with the cell receptor.

Results

Here we show that the adaptive pathway followed by Qβ in the face of similar variations in host density depends on environmental temperature. When the value for this parameter is lower than optimal (30°C), the mutation selected is the same as at the optimal temperature (37°C). However, when temperature increases to 43°C, the mutation selected is located in a different protein (A2), which is involved both in the interaction with the cell receptor and in the process of viral progeny release. The new mutation increases the entry of the phage into the bacteria at the three temperatures assayed. However, it also considerably increases the latent period at 30 and 37°C, which is probably the reason why it is not selected at these temperatures.

Conclusion

The conclusion is that the adaptive strategies followed by bacteriophage Qβ, and probably other viruses, in the face of variations in host density depend not only on their advantages at this selective pressure, but also on the fitness costs that particular mutations may present in function of the rest of environmental parameters that influence viral replication and stability.

Evolution of thermal performance curves: A meta-analysis of selection experiments

Temperatures are increasing due to global changes, putting biodiversity at risk. Organisms are faced with a limited set of options to cope with this situation: adapt, disperse or die. We here focus on the first possibility, more specifically, on evolutionary adaptations to temperature. Ectotherms are usually characterized by a hump-shaped relationship between fitness and temperature, a non-linear reaction norm that is referred to as thermal performance curve (TPC). To understand and predict impacts of global change, we need to know whether and how such TPCs evolve. Therefore, we performed a systematic literature search and a statistical meta-analysis focusing on experimental evolution and artificial selection studies. This focus allows us to directly quantify relative fitness responses to temperature selection by calculating fitness differences between TPCs from ancestral and derived populations after thermal selection. Out of 7561 publications screened, we found 47 studies corresponding to our search criteria representing taxa across the tree of life, from bacteria, to plants and vertebrates. We show that, independently of species identity, the studies we found report a positive response to temperature selection. Considering entire TPC shapes, adaptation to higher temperatures traded off with fitness at lower temperatures, leading to niche shifts. Effects were generally stronger in unicellular organisms. By contrast, we do not find statistical support for the often discussed "Hotter is better" hypothesis. While our meta-analysis provides evidence for adaptive potential of TPCs across organisms, it also highlights that more experimental work is needed, especially for under-represented taxa, such as plants and non-model systems.

Standing Genetic Diversity and Transmission Bottleneck Size Drive Adaptation in Bacteriophage Qβ

A critical issue to understanding how populations adapt to new selective pressures is the relative contribution of the initial standing genetic diversity versus that generated de novo. RNA viruses are an excellent model to study this question, as they form highly heterogeneous populations whose genetic diversity can be modulated by factors such as the number of generations, the size of population bottlenecks, or exposure to new environment conditions. In this work, we propagated at nonoptimal temperature (43 °C) two bacteriophage Qβ populations differing in their degree of heterogeneity. Deep sequencing analysis showed that, prior to the temperature change, the most heterogeneous population contained some low-frequency mutations that had previously been detected in the consensus sequences of other Qβ populations adapted to 43 °C. Evolved populations with origin in this ancestor reached similar growth rates, but the adaptive pathways depended on the frequency of these standing mutations and the transmission bottleneck size. In contrast, the growth rate achieved by populations with origin in the less heterogeneous ancestor did depend on the transmission bottleneck size. The conclusion is that viral diversification in a particular environment may lead to the emergence of mutants capable of accelerating adaptation when the environment changes.

Intra-Population Competition during Adaptation to Increased Temperature in an RNA Bacteriophage

Evolution of RNA bacteriophages of the family Leviviridae is governed by the high error rates of their RNA-dependent RNA polymerases. This fact, together with their large population sizes, leads to the generation of highly heterogeneous populations that adapt rapidly to most changes in the environment. Throughout adaptation, the different mutants that make up a viral population compete with each other in a non-trivial process in which their selective values change over time due to the generation of new mutations. In this work we have characterised the intra-population dynamics of a well-studied levivirus, Qβ, when it is propagated at a higher-than-optimal temperature. Our results show that adapting populations experienced rapid changes that involved the ascent of particular genotypes and the loss of some beneficial mutations of early generation. Artificially reconstructed populations, containing a fraction of the diversity present in actual populations, fixed mutations more rapidly, illustrating how population bottlenecks may guide the adaptive pathways. The conclusion is that, when the availability of beneficial mutations under a particular selective condition is elevated, the final outcome of adaptation depends more on the occasional occurrence of population bottlenecks and how mutations combine in genomes than on the selective value of particular mutations.

The Adaptive Potential of the Middle Domain of Yeast Hsp90

The distribution of fitness effects (DFEs) of new mutations across different environments quantifies the potential for adaptation in a given environment and its cost in others. So far, results regarding the cost of adaptation across environments have been mixed, and most studies have sampled random mutations across different genes. Here, we quantify systematically how costs of adaptation vary along a large stretch of protein sequence by studying the distribution of fitness effects of the same ≈2,300 amino-acid changing mutations obtained from deep mutational scanning of 119 amino acids in the middle domain of the heat shock protein Hsp90 in five environments. This region is known to be important for client binding, stabilization of the Hsp90 dimer, stabilization of the N-terminal-Middle and Middle-C-terminal interdomains, and regulation of ATPase–chaperone activity. Interestingly, we find that fitness correlates well across diverse stressful environments, with the exception of one environment, diamide. Consistent with this result, we find little cost of adaptation; on average only one in seven beneficial mutations is deleterious in another environment. We identify a hotspot of beneficial mutations in a region of the protein that is located within an allosteric center. The identified protein regions that are enriched in beneficial, deleterious, and costly mutations coincide with residues that are involved in the stabilization of Hsp90 interdomains and stabilization of client-binding interfaces, or residues that are involved in ATPase–chaperone activity of Hsp90. Thus, our study yields information regarding the role and adaptive potential of a protein sequence that complements and extends known structural information.

Potentially adaptive SARS-CoV-2 mutations discovered with novel spatiotemporal and explainable AI models

BACKGROUND

A mechanistic understanding of the spread of SARS-CoV-2 and diligent tracking of ongoing mutagenesis are of key importance to plan robust strategies for confining its transmission. Large numbers of available sequences and their dates of transmission provide an unprecedented opportunity to analyze evolutionary adaptation in novel ways. Addition of high-resolution structural information can reveal the functional basis of these processes at the molecular level. Integrated systems biology-directed analyses of these data layers afford valuable insights to build a global understanding of the COVID-19 pandemic.

RESULTS

Here we identify globally distributed haplotypes from 15,789 SARS-CoV-2 genomes and model their success based on their duration, dispersal, and frequency in the host population. Our models identify mutations that are likely compensatory adaptive changes that allowed for rapid expansion of the virus. Functional predictions from structural analyses indicate that, contrary to previous reports, the Asp614Gly mutation in the spike glycoprotein (S) likely reduced transmission and the subsequent Pro323Leu mutation in the RNA-dependent RNA polymerase led to the precipitous spread of the virus. Our model also suggests that two mutations in the nsp13 helicase allowed for the adaptation of the virus to the Pacific Northwest of the USA. Finally, our explainable artificial intelligence algorithm identified a mutational hotspot in the sequence of S that also displays a signature of positive selection and may have implications for tissue or cell-specific expression of the virus.

CONCLUSIONS

These results provide valuable insights for the development of drugs and surveillance strategies to combat the current and future pandemics.

Evolutionary Dynamics in the RNA Bacteriophage Qβ Depends on the Pattern of Change in Selective Pressures

The rate of change in selective pressures is one of the main factors that determines the likelihood that populations can adapt to stress conditions. Generally, the reduction in the population size that accompanies abrupt environmental changes makes it difficult to generate and select adaptive mutations. However, in systems with high genetic diversity, as happens in RNA viruses, mutations with beneficial effects under new conditions can already be present in the population, facilitating adaptation. In this work, we have propagated an RNA bacteriophage (Qβ) at temperatures higher than the optimum, following different patterns of change. We have determined the fitness values and the consensus sequences of all lineages throughout the evolutionary process in order to establish correspondences between fitness variations and adaptive pathways. Our results show that populations subjected to a sudden temperature change gain fitness and fix mutations faster than those subjected to gradual changes, differing also in the particular selected mutations. The life-history of populations prior to the environmental change has great importance in the dynamics of adaptation. The conclusion is that in the bacteriophage Qβ, the standing genetic diversity together with the rate of temperature change determine both the rapidity of adaptation and the followed evolutionary pathways.

Influence of adaptive mutations, from thermal adaptation experiments, on the infection cycle of RNA bacteriophage Qβ

A population's growth rate is determined by multiple 'life history traits'. To quantitatively determine which life history traits should be improved to allow a living organism to adapt to an inhibitory environment is an important issue. Previously, we conducted thermal adaptation experiments on the RNA bacteriophage Qβ using three independent replicates and reported that all three end-point populations could grow at a temperature (43.6°C) that inhibited the growth of the ancestral strain. Even though the fitness values of the endpoint populations were almost the same, their genome sequence was not, indicating that the three thermally adapted populations may have different life history traits. In this study, we introduced each mutation observed in these three end-point populations into the cDNA of the Qβ genome and prepared three different mutants. Quantitative analysis showed that they tended to increase their fitness by increasing the adsorption rate to their host, shortening their latent period (i.e., the duration between phage infection and progeny release), and increasing the burst size (i.e., the number of progeny phages per infected cell), but all three mutants decreased their thermal stability. However, the degree to which these traits changed differed. The mutant with the least mutations showed a smaller decrease in thermal stability, the largest adsorption rate to the host, and the shortest latent period. These results indicated that several different adaptive routes exist by which Qβ can adapt to higher temperatures, even though Qβ is a simple RNA bacteriophage with a small genome size, encoding only four genes.

Evolutionary adaptation of an RNA bacteriophage to the simultaneous increase in the within-host and extracellular temperatures

Bacteriophages are the most numerous biological entities on Earth. They are on the basis of most ecosystems, regulating the diversity and abundance of bacterial populations and contributing to the nutrient and energy cycles. Bacteriophages have two well differentiated phases in their life cycle, one extracellular, in which they behave as inert particles, and other one inside their hosts, where they replicate to give rise to a progeny. In both phases they are exposed to environmental conditions that often act as selective pressures that limit both their survival in the environment and their ability to replicate, two fitness traits that frequently cannot be optimised simultaneously. In this study we have analysed the evolutionary ability of an RNA bacteriophage, the bacteriophage Qβ, when it is confronted with a temperature increase that affects both the extracellular and the intracellular media. Our results show that Qβ can optimise its survivability when exposed to short-term high temperature extracellular heat shocks, as well as its replicative ability at higher-than-optimal temperature. Mutations responsible for simultaneous adaptation were the same as those selected when adaptation to each condition proceeded separately, showing the absence of important trade-offs between survival and reproduction in this virus.

Differences in adaptive dynamics determine the success of virus variants that propagate together

Virus fitness is a complex parameter that results from the interaction of virus-specific characters (e.g. intracellular growth rate, adsorption rate, virion extracellular stability, and tolerance to mutations) with others that depend on the underlying fitness landscape and the internal structure of the whole population. Individual mutants usually have lower fitness values than the complex population from which they come from. When they are propagated and allowed to attain large population sizes for a sufficiently long time, they approach mutation-selection equilibrium with the concomitant fitness gains. The optimization process follows dynamics that vary among viruses, likely due to differences in any of the parameters that determine fitness values. As a consequence, when different mutants spread together, the number of generations experienced by each of them prior to co-propagation may determine its particular fate. In this work we attempt a clarification of the effect of different levels of population diversity in the outcome of competition dynamics. To this end, we analyze the behavior of two mutants of the RNA bacteriophage Qβ that co-propagate with the wild-type virus. When both competitor viruses are clonal, the mutants rapidly outcompete the wild type. However, the outcome in competitions performed with partially optimized virus populations depends on the distance of the competitors to their clonal origin. We also implement a theoretical population dynamics model that describes the evolution of a heterogeneous population of individuals, each characterized by a fitness value, subjected to subsequent cycles of replication and mutation. The experimental results are explained in the framework of our theoretical model under two non-excluding, likely complementary assumptions: (1) The relative advantage of both competitors changes as populations approach mutation-selection equilibrium, as a consequence of differences in their growth rates and (2) one of the competitors is more robust to mutations than the other. The main conclusion is that the nearness of an RNA virus population to mutation-selection equilibrium is a key factor determining the fate of particular mutants arising during replication.

Adaptations of an RNA virus to increasing thermal stress

Environments can change in incremental fashions, where a shift from one state to another occurs over multiple organismal generations. The rate of the environmental change is expected to influence how and how well populations adapt to the final environmental state. We used a model system, the lytic RNA bacteriophage Φ6, to investigate this question empirically. We evolved viruses for thermostability by exposing them to heat shocks that increased to a maximum temperature at different rates. We observed increases in the ability of many heat-shocked populations to survive high temperature heat shocks. On their first exposure to the highest temperature, populations that experienced a gradual increase in temperature had higher average survival than populations that experienced a rapid temperature increase. However, at the end of the experiment, neither the survival of populations at the highest temperature nor the number of mutations per population varied significantly according to the rate of thermal change. We also evaluated mutations from the endpoint populations for their effects on viral thermostability and growth. As expected, some mutations did increase viral thermostability. However, other mutations decreased thermostability but increased growth rate, suggesting that benefits of an increased replication rate may have sometimes outweighed the benefits of enhanced thermostability. Our study highlights the importance of considering the effects of multiple selective pressures, even in environments where a single factor changes.

Impact of increased mutagenesis on adaptation to high temperature in bacteriophage Qβ

RNA viruses replicate with very high error rates, which makes them more sensitive to additional increases in this parameter. This fact has inspired an antiviral strategy named lethal mutagenesis, which is based on the artificial increase of the error rate above a threshold incompatible with virus infectivity. A relevant issue concerning lethal mutagenesis is whether incomplete treatments might enhance the adaptive possibilities of viruses. We have addressed this question by subjecting an RNA virus, the bacteriophage Qβ, to different transmission regimes in the presence or the absence of sublethal concentrations of the mutagenic nucleoside analogue 5-azacytidine (AZC). Populations obtained were subsequently exposed to a non-optimal temperature and analyzed to determine their consensus sequences. Our results show that previously mutagenized populations rapidly fixed a specific set of mutations upon propagation at the new temperature, suggesting that the expansion of the mutant spectrum caused by AZC has an influence on later evolutionary behavior.