Genomic epidemiological models describe pathogen evolution across fitness valleys.
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ABSTRACT:
SUBMITTER: Cardenas P
PROVIDER: S-EPMC9278859 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Mutational escape from vaccine-induced immune responses has thwarted the development of a successful vaccine against AIDS, whose causative agent is HIV, a highly mutable virus. Knowing the virus' fitness as a function of its proteomic sequence can enable rational design of potent vaccines, as this information can focus vaccine-induced immune responses to target mutational vulnerabilities of the virus. Spin models have been proposed as a means to infer intrinsic fitness landscapes of HIV proteins from patient-derived viral protein sequences. These sequences are the product of nonequilibrium viral evolution driven by patient-specific immune responses and are subject to phylogenetic constraints. How can such sequence data allow inference of intrinsic fitness landscapes? We combined computer simulations and variational theory á la Feynman to show that, in most circumstances, spin models inferred from patient-derived viral sequences reflect the correct rank order of the fitness of mutant viral strains. Our findings are relevant for diverse viruses.
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Project description:BackgroundSingle nucleotide substitutions in protein-coding genes can be divided into synonymous (S), with little fitness effect, and non-synonymous (N) ones that alter amino acids and thus generally have a greater effect. Most of the N substitutions are affected by purifying selection that eliminates them from evolving populations. However, additional mutations of nearby bases potentially could alleviate the deleterious effect of single substitutions, making them subject to positive selection. To elucidate the effects of selection on double substitutions in all codons, it is critical to differentiate selection from mutational biases.ResultsWe addressed the evolutionary regimes of within-codon double substitutions in 37 groups of closely related prokaryotic genomes from diverse phyla by comparing the fractions of double substitutions within codons to those of the equivalent double S substitutions in adjacent codons. Under the assumption that substitutions occur one at a time, all within-codon double substitutions can be represented as "ancestral-intermediate-final" sequences (where "intermediate" refers to the first single substitution and "final" refers to the second substitution) and can be partitioned into four classes: (1) SS, S intermediate-S final; (2) SN, S intermediate-N final; (3) NS, N intermediate-S final; and (4) NN, N intermediate-N final. We found that the selective pressure on the second substitution markedly differs among these classes of double substitutions. Analogous to single S (synonymous) substitutions, SS double substitutions evolve neutrally, whereas analogous to single N (non-synonymous) substitutions, SN double substitutions are subject to purifying selection. In contrast, NS show positive selection on the second step because the original amino acid is recovered. The NN double substitutions are heterogeneous and can be subject to either purifying or positive selection, or evolve neutrally, depending on the amino acid similarity between the final or intermediate and the ancestral states.ConclusionsThe results of the present, comprehensive analysis of the evolutionary landscape of within-codon double substitutions reaffirm the largely conservative regime of protein evolution. However, the second step of a double substitution can be subject to positive selection when the first step is deleterious. Such positive selection can result in frequent crossing of valleys on the fitness landscape.
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Project description:Characterizing fitness landscapes associated with polymorphic adaptive traits enables investigation of mechanisms allowing transitions between fitness peaks. Here, we explore how natural selection can promote genetic mechanisms preventing heterozygous phenotypes from falling into non-adaptive valleys. Polymorphic mimicry is an ideal system to investigate such fitness landscapes, because the direction of selection acting on complex mimetic colour patterns can be predicted by the local mimetic community composition. Using more than 5000 artificial butterflies displaying colour patterns exhibited by the polymorphic Müllerian mimic Heliconius numata, we directly tested the role of wild predators in shaping fitness landscapes. We compared predation rates on mimetic phenotypes (homozygotes at the supergene controlling colour pattern), intermediate phenotypes (heterozygotes), exotic morphs (absent from the local community) and palatable cryptic phenotypes. Exotic morphs were significantly more attacked than local morphs, highlighting predators' discriminatory capacities. Overall, intermediates were attacked twice as much as local homozygotes, suggesting the existence of deep fitness valleys promoting strict dominance and reduced recombination between supergene alleles. By including information on predators' colour perception, we also showed that protection on intermediates strongly depends on their phenotypic similarity to homozygous phenotypes and that ridges exist between similar phenotypes, which may facilitate divergence in colour patterns.
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Project description:Changes in dengue virus (DENV) genome affect viral fitness both clinically and epidemiologically. Even in the 3' untranslated region (3' UTR), mutations could affect subgenomic flaviviral RNA (sfRNA) production and its affinity for host proteins, which are necessary for successful viral replication. Indeed, we recently showed that mutations in DENV2 3' UTR of epidemic strains increased sfRNA ability to bind host proteins and reduce interferon expression. However, whether 3' UTR differences shape the overall DENV evolution remains incompletely understood. Herein, we combined RNA phylogeny with phylogenetics to gain insights on sfRNA evolution. We found that sfRNA structures are under purifying selection and highly conserved despite sequence divergence. Only the second flaviviral nuclease-resistant RNA (fNR2) structure of DENV2 sfRNA has undergone strong positive selection. Epidemiological reports suggest that substitutions in fNR2 may drive DENV2 epidemiological fitness, possibly through sfRNA-protein interactions. Collectively, our findings indicate that 3' UTRs are important determinants of DENV fitness in human-mosquito cycles.
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Project description:To escape from local fitness peaks, a population must navigate across valleys of low fitness. How these transitions occur, and what role they play in adaptation, have been subjects of active interest in evolutionary genetics for almost a century. However, to our knowledge, this problem has never been addressed directly by considering the evolution of a gene, or group of genes, as a whole, including the complex effects of fitness interactions among multiple loci. Here, we use a precise model of protein fitness to compute the probability P ( s , Δ t ) that an allele, randomly sampled from a population at time t, has crossed a fitness valley of depth s during an interval t - Δ t , t in the immediate past. We study populations of model genes evolving under equilibrium conditions consistent with those in mammalian mitochondria. From this data, we estimate that genes encoding small protein motifs navigate fitness valleys of depth 2 N s ≳ 30 with probability P ≳ 0 . 1 on a time scale of human evolution, where N is the (mitochondrial) effective population size. The results are consistent with recent findings for Watson⁻Crick switching in mammalian mitochondrial tRNA molecules.
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Project description:Adaptation, where a population evolves increasing fitness in a fixed environment, is typically thought of as a hill-climbing process on a fitness landscape. With a finite genome, such a process eventually leads the population to a fitness peak, at which point fitness can no longer increase through individual beneficial mutations. Instead, the ruggedness of typical landscapes due to epistasis between genes or DNA sites suggests that the accumulation of multiple mutations (via a process known as stochastic tunneling) can allow a population to continue increasing in fitness. However, it is not clear how such a phenomenon would affect long-term fitness evolution. By using a spin-glass type model for the fitness function that takes into account microscopic epistasis, we find that hopping between metastable states can mechanistically and robustly give rise to a slow, logarithmic average fitness trajectory.
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Project description:Individuals in a population often have different fitnesses even when they have identical genotypes, but the effect of this variation on the evolution of a population through complicated fitness landscapes is unknown. Here, we investigate how populations with non-genetic fitness variation cross fitness valleys, common barriers to adaptation in rugged fitness landscapes in which a population must pass through a deleterious intermediate to arrive at a final advantageous stage. We develop a stochastic computational model describing the dynamics of an asexually reproducing population crossing a fitness valley, in which individuals of the same evolutionary stage can have variable fitnesses. We find that fitness variation that persists over multiple generations increases the rate of valley crossing through a novel evolutionary mechanism different from previously characterized mechanisms such as stochastic tunneling. By reducing the strength of selection against deleterious intermediates, persistent fitness variation allows for faster adaptation through rugged fitness landscapes.
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Project description:Phylodynamics requires an interdisciplinary understanding of phylogenetics, epidemiology, and statistical inference. It has also experienced more intense application than ever before amid the SARS-CoV-2 pandemic. In light of this, we present a review of phylodynamic models beginning with foundational models and assumptions. Our target audience is public health researchers, epidemiologists, and biologists seeking a working knowledge of the links between epidemiology, evolutionary models, and resulting epidemiological inference. We discuss the assumptions linking evolutionary models of pathogen population size to epidemiological models of the infected population size. We then describe statistical inference for phylodynamic models and list how output parameters can be rearranged for epidemiological interpretation. We go on to cover more sophisticated models and finish by highlighting future directions.
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Project description:Periodontitis is a microbial infection that destroys the structures that support the teeth. Although it is typically a chronic condition, rapidly progressing, aggressive forms are associated with the oral pathogen Aggregatibacter actinomycetemcomitans One of this bacterium's key virulence traits is its ability to attach to surfaces and form robust biofilms that resist killing by the host and antibiotics. Though much has been learned about A. actinomycetemcomitans since its initial discovery, we lack insight into a fundamental aspect of its basic biology, as we do not know the full set of genes that it requires for viability (the essential genome). Furthermore, research on A. actinomycetemcomitans is hampered by the field's lack of a mutant collection. To address these gaps, we used rapid transposon mutant sequencing (Tn-seq) to define the essential genomes of two strains of A. actinomycetemcomitans, revealing a core set of 319 genes. We then generated an arrayed mutant library comprising >1,500 unique insertions and used a sequencing-based approach to define each mutant's position (well and plate) in the library. To demonstrate its utility, we screened the library for mutants with weakened resistance to subinhibitory erythromycin, revealing the multidrug efflux pump AcrAB as a critical resistance factor. During the screen, we discovered that erythromycin induces A. actinomycetemcomitans to form biofilms. We therefore devised a novel Tn-seq-based screen to identify specific factors that mediate this phenotype and in follow-up experiments confirmed 4 mutants. Together, these studies present new insights and resources for investigating the basic biology and disease mechanisms of a human pathogen.IMPORTANCE Millions suffer from gum disease, which often is caused by Aggregatibacter actinomycetemcomitans, a bacterium that forms antibiotic-resistant biofilms. To fully understand any organism, we should be able to answer: what genes does it require for life? Here, we address this question for A. actinomycetemcomitans by determining the genes in its genome that cannot be mutated. As for the genes that can be mutated, we archived these mutants into a library, which we used to find genes that contribute to antibiotic resistance, leading us to discover that antibiotics cause A. actinomycetemcomitans to form biofilms. We then devised an approach to find genes that mediate this process and confirmed 4 genes. These results illuminate new fundamental traits of a human pathogen.
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Project description:Protein sequences contain rich information about protein evolution, fitness landscapes, and stability. Here we investigate how latent space models trained using variational auto-encoders can infer these properties from sequences. Using both simulated and real sequences, we show that the low dimensional latent space representation of sequences, calculated using the encoder model, captures both evolutionary and ancestral relationships between sequences. Together with experimental fitness data and Gaussian process regression, the latent space representation also enables learning the protein fitness landscape in a continuous low dimensional space. Moreover, the model is also useful in predicting protein mutational stability landscapes and quantifying the importance of stability in shaping protein evolution. Overall, we illustrate that the latent space models learned using variational auto-encoders provide a mechanism for exploration of the rich data contained in protein sequences regarding evolution, fitness and stability and hence are well-suited to help guide protein engineering efforts.
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