Favipiravir induces HuNoV viral mutagenesis and infectivity loss with clinical improvement in immunocompromised patients

Chronic human norovirus (HuNoV) infections in immunocompromised patients result in severe disease, yet approved antivirals are lacking. RNA-dependent RNA polymerase (RdRp) inhibitors inducing viral mutagenesis display broad-spectrum in vitro antiviral activity, but clinical efficacy in HuNoV infections is anecdotal and the potential emergence of drug-resistant variants is concerning. Upon favipiravir (and nitazoxanide) treatment of four immunocompromised patients with life-threatening HuNoV infections, viral whole-genome sequencing showed accumulation of favipiravir-induced mutations which coincided with clinical improvement although treatment failed to clear HuNoV. Infection of zebrafish larvae demonstrated drug-associated loss of viral infectivity and favipiravir treatment showed efficacy despite occurrence of RdRp variants potentially causing favipiravir resistance. This indicates that within-host resistance evolution did not reverse loss of viral fitness caused by genome-wide accumulation of sequence changes. This off-label approach supports the use of mutagenic antivirals for treating prolonged RNA viral infections and further informs the debate surrounding their impact on virus evolution.

Within-host diversity improves phylogenetic and transmission reconstruction of SARS-CoV-2 outbreaks

Accurate inference of who infected whom in an infectious disease outbreak is critical for the delivery of effective infection prevention and control. The increased resolution of pathogen whole-genome sequencing has significantly improved our ability to infer transmission events. Despite this, transmission inference often remains limited by the lack of genomic variation between the source case and infected contacts. Although within-host genetic diversity is common among a wide variety of pathogens, conventional whole-genome sequencing phylogenetic approaches exclusively use consensus sequences, which consider only the most prevalent nucleotide at each position and therefore fail to capture low-frequency variation within samples. We hypothesized that including within-sample variation in a phylogenetic model would help to identify who infected whom in instances in which this was previously impossible. Using whole-genome sequences from SARS-CoV-2 multi-institutional outbreaks as an example, we show how within-sample diversity is partially maintained among repeated serial samples from the same host, it can transmitted between those cases with known epidemiological links, and how this improves phylogenetic inference and our understanding of who infected whom. Our technique is applicable to other infectious diseases and has immediate clinical utility in infection prevention and control.

Genomic and geographical structure of human cytomegalovirus

Human cytomegalovirus (CMV) has infected humans since the origin of our species and currently infects most of the world's population. Variability between CMV genomes is the highest of any human herpesvirus, yet large portions of the genome are conserved. Here, we show that the genome encodes 74 regions of relatively high variability each with 2 to 8 alleles. We then identified two patterns in the CMV genome. Conserved parts of the genome and a minority (32) of variable regions show geographic population structure with evidence for African or European clustering, although hybrid strains are present. We find no evidence that geographic segregation has been driven by host immune pressure affecting known antigenic sites. Forty-two variable regions show no geographical structure, with similar allele distributions across different continental populations. These "nongeographical" regions are significantly enriched for genes encoding immunomodulatory functions suggesting a core functional importance. We hypothesize that at least two CMV founder populations account for the geographical differences that are largely seen in the conserved portions of the genome, although the timing of separation and direction of spread between the two are not clear. In contrast, the similar allele frequencies among 42 variable regions of the genome, irrespective of geographical origin, are indicative of a second evolutionary process, namely balancing selection that may preserve properties critical to CMV biological function. Given that genetic differences between CMVs are postulated to alter immunogenicity and potentially function, understanding these two evolutionary processes could contribute important information for the development of globally effective vaccines and the identification of novel drug targets.

Haplotype assignment of longitudinal viral deep sequencing data using covariation of variant frequencies

Longitudinal deep sequencing of viruses can provide detailed information about intra-host evolutionary dynamics including how viruses interact with and transmit between hosts. Many analyses require haplotype reconstruction, identifying which variants are co-located on the same genomic element. Most current methods to perform this reconstruction are based on a high density of variants and cannot perform this reconstruction for slowly evolving viruses. We present a new approach, HaROLD (HAplotype Reconstruction Of Longitudinal Deep sequencing data), which performs this reconstruction based on identifying co-varying variant frequencies using a probabilistic framework. We illustrate HaROLD on both RNA and DNA viruses with synthetic Illumina paired read data created from mixed human cytomegalovirus (HCMV) and norovirus genomes, and clinical datasets of HCMV and norovirus samples, demonstrating high accuracy, especially when longitudinal samples are available.

HIV-1 Evolutionary Dynamics under Nonsuppressive Antiretroviral Therapy

Prolonged virologic failure on 2nd-line protease inhibitor (PI)-based antiretroviral therapy (ART) without emergence of major protease mutations is well recognized and provides an opportunity to study within-host evolution in long-term viremic individuals. Using next-generation sequencing and in silico haplotype reconstruction, we analyzed whole-genome sequences from longitudinal plasma samples of eight chronically infected HIV-1-positive individuals failing 2nd-line regimens from the French National Agency for AIDS and Viral Hepatitis Research (ANRS) 12249 Treatment as Prevention (TasP) trial. On nonsuppressive ART, there were large fluctuations in synonymous and nonsynonymous variant frequencies despite stable viremia. Reconstructed haplotypes provided evidence for selective sweeps during periods of partial adherence, and viral haplotype competition, during periods of low drug exposure. Drug resistance mutations in reverse transcriptase (RT) were used as markers of viral haplotypes in the reservoir, and their distribution over time indicated recombination. We independently observed linkage disequilibrium decay, indicative of recombination. These data highlight dramatic changes in virus population structure that occur during stable viremia under nonsuppressive ART. IMPORTANCE HIV-1 infections are most commonly initiated with a single founder virus and are characterized by extensive inter- and intraparticipant genetic diversity. However, existing literature on HIV-1 intrahost population dynamics is largely limited to untreated infections, predominantly in subtype B-infected individuals. The manuscript characterizes viral population dynamics in long-term viremic treatment-experienced individuals, which has not been previously characterized. These data are particularly relevant for understanding HIV dynamics but can also be applied to other RNA viruses. With this unique data set we propose that the virus is highly unstable, and we have found compelling evidence of HIV-1 within-host viral diversification, recombination, and haplotype competition during nonsuppressive ART.

Within-host diversity improves phylogenetic and transmission reconstruction of SARS-CoV-2 outbreaks

Accurate inference of who infected whom in an infectious disease outbreak is critical for the delivery of effective infection prevention and control. The increased resolution of pathogen whole-genome sequencing has significantly improved our ability to infer transmission events. Despite this, transmission inference often remains limited by the lack of genomic variation between the source case and infected contacts. Although within-host genetic diversity is common among a wide variety of pathogens, conventional whole-genome sequencing phylogenetic approaches to reconstruct outbreaks exclusively use consensus sequences, which consider only the most prevalent nucleotide at each position and therefore fail to capture low frequency variation within samples. We hypothesized that including within-sample variation in a phylogenetic model would help to identify who infected whom in instances in which this was previously impossible. Using whole-genome sequences from SARS-CoV-2 multi-institutional outbreaks as an example, we show how within-sample diversity is stable among repeated serial samples from the same host, is transmitted between those cases with known epidemiological links, and how this improves phylogenetic inference and our understanding of who infected whom. Our technique is applicable to other infectious diseases and has immediate clinical utility in infection prevention and control.

Evolution of viral variants in remdesivir-treated and untreated SARS-CoV-2-infected pediatrics patients

Detailed information on intrahost viral evolution in SARS-CoV-2 with and without treatment is limited. Sequential viral loads and deep sequencing of SARS-CoV-2 from the upper respiratory tract of nine hospitalized children, three of whom were treated with remdesivir, revealed that remdesivir treatment suppressed viral load in one patient but not in a second infected with an identical strain without any evidence of drug resistance found. Reduced levels of subgenomic RNA during treatment of the second patient, suggest an additional effect of remdesivir on viral replication. Haplotype reconstruction uncovered persistent SARS-CoV-2 variant genotypes in four patients. These likely arose from within-host evolution, although superinfection cannot be excluded in one case. Although our dataset is small, observed sample-to-sample heterogeneity in variant frequencies across four of nine patients suggests the presence of discrete viral populations in the lung with incomplete population sampling in diagnostic swabs. Such compartmentalization could compromise the penetration of remdesivir into the lung, limiting the drugs in vivo efficacy, as has been observed in other lung infections.

Predicted norovirus resurgence in 2021-2022 due to the relaxation of nonpharmaceutical interventions associated with COVID-19 restrictions in England: a mathematical modeling study

BACKGROUND

To reduce the coronavirus disease burden in England, along with many other countries, the government implemented a package of non-pharmaceutical interventions (NPIs) that have also impacted other transmissible infectious diseases such as norovirus. It is unclear what future norovirus disease incidence is likely to look like upon lifting these restrictions.

METHODS

Here we use a mathematical model of norovirus fitted to community incidence data in England to project forward expected incidence based on contact surveys that have been collected throughout 2020-2021.

RESULTS

We report that susceptibility to norovirus infection has likely increased between March 2020 and mid-2021. Depending upon assumptions of future contact patterns incidence of norovirus that is similar to pre-pandemic levels or an increase beyond what has been previously reported is likely to occur once restrictions are lifted. Should adult contact patterns return to 80% of pre-pandemic levels, the incidence of norovirus will be similar to previous years. If contact patterns return to pre-pandemic levels, there is a potential for the expected annual incidence to be up to 2-fold larger than in a typical year. The age-specific incidence is similar across all ages.

CONCLUSIONS

Continued national surveillance for endemic diseases such as norovirus will be essential after NPIs are lifted to allow healthcare services to adequately prepare for a potential increase in cases and hospital pressures beyond what is typically experienced.

Predicted Norovirus Resurgence in 2021-2022 Due to the Relaxation of Nonpharmaceutical Interventions Associated with COVID-19 Restrictions in England: A Mathematical Modelling Study

BACKGROUND

To reduce the coronavirus disease burden in England, along with many other countries, the Government implemented a package of non-pharmaceutical interventions (NPIs) that have also impacted other transmissible infectious diseases such as norovirus. It is unclear what future norovirus disease incidence is likely to look like upon lifting these restrictions.

METHODS

Here we use a mathematical model of norovirus fitted to community incidence data in England to project forward expected incidence based on contact surveys that have been collected throughout 2020-2021.

RESULTS

We report that susceptibility to norovirus infection has likely increased between March 2020 to mid-2021. Depending upon assumptions of future contact patterns incidence of norovirus that is similar to pre-pandemic levels or an increase beyond what has been previously reported is likely to occur once restrictions are lifted. Should adult contact patterns return to 80% of pre-pandemic levels the incidence of norovirus will be similar to previous years. If contact patterns return to pre-pandemic levels there is a potential for the expected annual incidence to be up to 2-fold larger than in a typical year. The age-specific incidence is similar across all ages.

CONCLUSIONS

Continued national surveillance for endemic diseases such as norovirus will be essential after NPIs are lifted to allow healthcare services to adequately prepare for a potential increase in cases and hospital pressures beyond what is typically experienced.

SARS-CoV-2 evolution during treatment of chronic infection

The spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical for virus infection through the engagement of the human ACE2 protein¹ and is a major antibody target. Here we show that chronic infection with SARS-CoV-2 leads to viral evolution and reduced sensitivity to neutralizing antibodies in an immunosuppressed individual treated with convalescent plasma, by generating whole-genome ultra-deep sequences for 23 time points that span 101 days and using in vitro techniques to characterize the mutations revealed by sequencing. There was little change in the overall structure of the viral population after two courses of remdesivir during the first 57 days. However, after convalescent plasma therapy, we observed large, dynamic shifts in the viral population, with the emergence of a dominant viral strain that contained a substitution (D796H) in the S2 subunit and a deletion (ΔH69/ΔV70) in the S1 N-terminal domain of the spike protein. As passively transferred serum antibodies diminished, viruses with the escape genotype were reduced in frequency, before returning during a final, unsuccessful course of convalescent plasma treatment. In vitro, the spike double mutant bearing both ΔH69/ΔV70 and D796H conferred modestly decreased sensitivity to convalescent plasma, while maintaining infectivity levels that were similar to the wild-type virus.The spike substitution mutant D796H appeared to be the main contributor to the decreased susceptibility to neutralizing antibodies, but this mutation resulted in an infectivity defect. The spike deletion mutant ΔH69/ΔV70 had a twofold higher level of infectivity than wild-type SARS-CoV-2, possibly compensating for the reduced infectivity of the D796H mutation. These data reveal strong selection on SARS-CoV-2 during convalescent plasma therapy, which is associated with the emergence of viral variants that show evidence of reduced susceptibility to neutralizing antibodies in immunosuppressed individuals.

SARS-CoV-2 evolution during treatment of chronic infection

The spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical for virus infection through the engagement of the human ACE2 protein1 and is a major antibody target. Here we show that chronic infection with SARS-CoV-2 leads to viral evolution and reduced sensitivity to neutralizing antibodies in an immunosuppressed individual treated with convalescent plasma, by generating whole-genome ultra-deep sequences for 23 time points that span 101 days and using in vitro techniques to characterize the mutations revealed by sequencing. There was little change in the overall structure of the viral population after two courses of remdesivir during the first 57 days. However, after convalescent plasma therapy, we observed large, dynamic shifts in the viral population, with the emergence of a dominant viral strain that contained a substitution (D796H) in the S2 subunit and a deletion (ΔH69/ΔV70) in the S1 N-terminal domain of the spike protein. As passively transferred serum antibodies diminished, viruses with the escape genotype were reduced in frequency, before returning during a final, unsuccessful course of convalescent plasma treatment. In vitro, the spike double mutant bearing both ΔH69/ΔV70 and D796H conferred modestly decreased sensitivity to convalescent plasma, while maintaining infectivity levels that were similar to the wild-type virus.The spike substitution mutant D796H appeared to be the main contributor to the decreased susceptibility to neutralizing antibodies, but this mutation resulted in an infectivity defect. The spike deletion mutant ΔH69/ΔV70 had a twofold higher level of infectivity than wild-type SARS-CoV-2, possibly compensating for the reduced infectivity of the D796H mutation. These data reveal strong selection on SARS-CoV-2 during convalescent plasma therapy, which is associated with the emergence of viral variants that show evidence of reduced susceptibility to neutralizing antibodies in immunosuppressed individuals.

Mixed cytomegalovirus genotypes in HIV-positive mothers show compartmentalization and distinct patterns of transmission to infants

Cytomegalovirus (CMV) is the commonest cause of congenital infection and particularly so among infants born to HIV-infected women. Studies of congenital CMV infection (cCMVi) pathogenesis are complicated by the presence of multiple infecting maternal CMV strains, especially in HIV-positive women, and the large, recombinant CMV genome. Using newly developed tools to reconstruct CMV haplotypes, we demonstrate anatomic CMV compartmentalization in five HIV-infected mothers and identify the possibility of congenitally transmitted genotypes in three of their infants. A single CMV strain was transmitted in each congenitally infected case, and all were closely related to those that predominate in the cognate maternal cervix. Compared to non-transmitted strains, these congenitally transmitted CMV strains showed statistically significant similarities in 19 genes associated with tissue tropism and immunomodulation. In all infants, incident superinfections with distinct strains from breast milk were captured during follow-up. The results represent potentially important new insights into the virologic determinants of early CMV infection.

Neutralising antibodies in Spike mediated SARS-CoV-2 adaptation

SARS-CoV-2 Spike protein is critical for virus infection via engagement of ACE2, and amino acid variation in Spike is increasingly appreciated. Given both vaccines and therapeutics are designed around Wuhan-1 Spike, this raises the theoretical possibility of virus escape, particularly in immunocompromised individuals where prolonged viral replication occurs. Here we report chronic SARS-CoV-2 with reduced sensitivity to neutralising antibodies in an immune suppressed individual treated with convalescent plasma, generating whole genome ultradeep sequences by both short and long read technologies over 23 time points spanning 101 days. Although little change was observed in the overall viral population structure following two courses of remdesivir over the first 57 days, N501Y in Spike was transiently detected at day 55 and V157L in RdRp emerged. However, following convalescent plasma we observed large, dynamic virus population shifts, with the emergence of a dominant viral strain bearing D796H in S2 and ΔH69/ΔV70 in the S1 N-terminal domain NTD of the Spike protein. As passively transferred serum antibodies diminished, viruses with the escape genotype diminished in frequency, before returning during a final, unsuccessful course of convalescent plasma. In vitro, the Spike escape double mutant bearing ΔH69/ΔV70 and D796H conferred decreased sensitivity to convalescent plasma, whilst maintaining infectivity similar to wild type. D796H appeared to be the main contributor to decreased susceptibility, but incurred an infectivity defect. The ΔH69/ΔV70 single mutant had two-fold higher infectivity compared to wild type and appeared to compensate for the reduced infectivity of D796H. Consistent with the observed mutations being outside the RBD, monoclonal antibodies targeting the RBD were not impacted by either or both mutations, but a non RBD binding monoclonal antibody was less potent against ΔH69/ΔV70 and the double mutant. These data reveal strong selection on SARS-CoV-2 during convalescent plasma therapy associated with emergence of viral variants with reduced susceptibility to neutralising antibodies.

Preadaptation of pandemic GII.4 noroviruses in unsampled virus reservoirs years before emergence

The control of re-occurring pandemic pathogens requires understanding the origins of new pandemic variants and the factors that drive their global spread. This is especially important for GII.4 norovirus, where vaccines under development offer promise to prevent hundreds of millions of annual gastroenteritis cases. Previous studies have hypothesized that new GII.4 pandemic viruses arise when previously circulating pandemic or pre-pandemic variants undergo substitutions in antigenic regions that enable evasion of host population immunity, as described by conventional models of antigenic drift. In contrast, we show here that the acquisition of new genetic and antigenic characteristics cannot be the proximal driver of new pandemics. Pandemic GII.4 viruses diversify and spread over wide geographical areas over several years prior to simultaneous pandemic emergence of multiple lineages, indicating that the necessary sequence changes must have occurred before diversification, years prior to pandemic emergence. We confirm this result through serological assays of reconstructed ancestral virus capsids, demonstrating that by 2003, the ancestral 2012 pandemic strain had already acquired the antigenic characteristics that allowed it to evade prevailing population immunity against the previous 2009 pandemic variant. These results provide strong evidence that viral genetic changes are necessary but not sufficient for GII.4 pandemic spread. Instead, we suggest that it is changes in host population immunity that enable pandemic spread of an antigenically preadapted GII.4 variant. These results indicate that predicting future GII.4 pandemic variants will require surveillance of currently unsampled reservoir populations. Furthermore, a broadly acting GII.4 vaccine will be critical to prevent future pandemics.

Viral CpG Deficiency Provides No Evidence That Dogs Were Intermediate Hosts for SARS-CoV-2

Due to the scope and impact of the COVID-19 pandemic there exists a strong desire to understand where the SARS-CoV-2 virus came from and how it jumped species boundaries to humans. Molecular evolutionary analyses can trace viral origins by establishing relatedness and divergence times of viruses and identifying past selective pressures. However, we must uphold rigorous standards of inference and interpretation on this topic because of the ramifications of being wrong. Here, we dispute the conclusions of Xia (2020. Extreme genomic CpG deficiency in SARS-CoV-2 and evasion of host antiviral defense. Mol Biol Evol. doi:10.1093/molbev/masa095) that dogs are a likely intermediate host of a SARS-CoV-2 ancestor. We highlight major flaws in Xia's inference process and his analysis of CpG deficiencies, and conclude that there is no direct evidence for the role of dogs as intermediate hosts. Bats and pangolins currently have the greatest support as ancestral hosts of SARS-CoV-2, with the strong caveat that sampling of wildlife species for coronaviruses has been limited.

ChromaClade: combined visualisation of phylogenetic and sequence data

BACKGROUND

Studying site-specific amino acid frequencies by eye can reveal biologically significant variability and lineage-specific adaptation. This so-called 'sequence gazing' often informs bioinformatics and experimental research. But it is important to also account for the underlying phylogeny, since similarities may be due to common descent rather than selection pressure, and because it is important to distinguish between founder effects and convergent evolution. We set out to combine phylogenetic and sequence data to produce evolutionarily insightful visualisations.

RESULTS

We present ChromaClade, a convenient tool with a graphical user-interface that works in concert with popular tree viewers to produce colour-annotated phylogenies highlighting residues found in each taxon and at each site in a sequence alignment. Colouring branches according to residues found at descendent tips also quickly identifies lineage-specific residues and those internal branches where key substitutions have occurred. We demonstrate applications of ChromaClade to human immunodeficiency virus and influenza A virus datasets, illustrating cases of conservative, adaptive and convergent evolution.

CONCLUSIONS

We find this to be a powerful approach for visualising site-wise residue distributions and detecting evolutionary patterns, especially in large datasets. ChromaClade is available for Windows, macOS and Unix or Linux; program executables and source code are available at github.com/chrismonit/chroma_clade .

Positive selection in dNTPase SAMHD1 throughout mammalian evolution

The vertebrate protein SAMHD1 is highly unusual in having roles in cellular metabolic regulation, antiviral restriction, and regulation of innate immunity. Its deoxynucleoside triphosphohydrolase activity regulates cellular dNTP concentration, reducing levels below those required by lentiviruses and other viruses to replicate. To counter this threat, some primate lentiviruses encode accessory proteins that bind SAMHD1 and induce its degradation; in turn, positive diversifying selection has been observed in regions bound by these lentiviral proteins, suggesting that primate SAMHD1 has coevolved to evade these countermeasures. Moreover, deleterious polymorphisms in human SAMHD1 are associated with autoimmune disease linked to uncontrolled DNA synthesis of endogenous retroelements. Little is known about how evolutionary pressures affect these different SAMHD1 functions. Here, we examine the deeper history of these interactions by testing whether evolutionary signatures in SAMHD1 extend to other mammalian groups and exploring the molecular basis of this coevolution. Using codon-based likelihood models, we find positive selection in SAMHD1 within each mammal lineage for which sequence data are available. We observe positive selection at sites clustered around T592, a residue that is phosphorylated to regulate SAMHD1 activity. We verify experimentally that mutations within this cluster affect catalytic rate and lentiviral restriction, suggesting that virus-host coevolution has required adaptations of enzymatic function. Thus, persistent positive selection may have involved the adaptation of SAMHD1 regulation to balance antiviral, metabolic, and innate immunity functions.

Biophysics and population size constrains speciation in an evolutionary model of developmental system drift

Developmental system drift is a likely mechanism for the origin of hybrid incompatibilities between closely related species. We examine here the detailed mechanistic basis of hybrid incompatibilities between two allopatric lineages, for a genotype-phenotype map of developmental system drift under stabilising selection, where an organismal phenotype is conserved, but the underlying molecular phenotypes and genotype can drift. This leads to number of emergent phenomenon not obtainable by modelling genotype or phenotype alone. Our results show that: 1) speciation is more rapid at smaller population sizes with a characteristic, Orr-like, power law, but at large population sizes slow, characterised by a sub-diffusive growth law; 2) the molecular phenotypes under weakest selection contribute to the earliest incompatibilities; and 3) pair-wise incompatibilities dominate over higher order, contrary to previous predictions that the latter should dominate. The population size effect we find is consistent with previous results on allopatric divergence of transcription factor-DNA binding, where smaller populations have common ancestors with a larger drift load because genetic drift favours phenotypes which have a larger number of genotypes (higher sequence entropy) over more fit phenotypes which have far fewer genotypes; this means less substitutions are required in either lineage before incompatibilities arise. Overall, our results indicate that biophysics and population size provide a much stronger constraint to speciation than suggested by previous models, and point to a general mechanistic principle of how incompatibilities arise the under stabilising selection for an organismal phenotype.

The process of speciation is of fundamental importance to the field of evolution as it is intimately connected to understanding the immense bio-diversity of life. There is still relatively little understanding of the underlying genetic mechanisms that give rise to hybrid incompatibilities with results suggesting that divergence in transcription factor DNA binding and gene expression play an important role. A key finding from the field of evo-devo is that organismal phenotypes show developmental system drift, where species maintain the same phenotype, but diverge in developmental pathways; this is an important potential source of hybrid incompatibilities. Here, we explore a theoretical framework to understand how incompatibilities arise due to developmental system drift, using a tractable biophysically inspired genotype-phenotype for spatial gene expression. Modelling the evolution of phenotypes in this way has the key advantage that it mirrors how selection works in nature, i.e. that selection acts on phenotypes, but variation (mutation) arise at the level of genotypes. This results, as we demonstrate, in a number of non-trivial and testable predictions concerning speciation due to developmental system drift, which would not be obtainable by modelling evolution of genotypes or phenotypes alone.

Skeletal Muscle Injury Biomarkers: Assay Qualification Efforts and Translation to the Clinic

Skeletal muscle (SKM) injury or myopathy results in structural or functional defects in SKMs that can be caused by variety of factors such as (1) genetic, (2) drug-induced, (3) disease progression (cachexia), or (4) aging (sarcopenia). Creatine kinase (CK) and aspartate transaminase (AST) activity assays have been routinely used as SKM injury biomarkers, but they lack sensitivity and tissue specificity. In collaboration with the Predictive Safety Testing Consortium, we evaluated the diagnostic performance of a muscle injury biomarker panel (MIP) compared to CK and AST and their correlation with the histology scores across 34 different rat studies. The MIP panel included the analytes skeletal troponin I, myosin light chain 3, fatty acid binding protein 3, and a CK mass (versus activity) assay. The area under the receiver operator characteristic curve for MIP panel ranged from 0.82 to 0.91 as compared to 0.71 and 0.82 for CK and AST activity assays, respectively. Because the MIP biomarkers outperformed the routine biomarkers, the European Medicines Agency and U.S. Food and Drug Administration posted Letters of Support encouraging further study of these analytes and acknowledged the utility of the MIP panel. Ongoing efforts are directed toward the application of the MIP panel biomarkers in clinical studies and regulatory qualification.

SubRecon: ancestral reconstruction of amino acid substitutions along a branch in a phylogeny

Summary

Existing ancestral sequence reconstruction techniques are ill-suited to investigating substitutions on a single branch of interest. We present SubRecon, an implementation of a hybrid technique integrating joint and marginal reconstruction for protein sequence data. SubRecon calculates the joint probability of states at adjacent internal nodes in a phylogeny, i.e. how the state has changed along a branch. This does not condition on states at other internal nodes and includes site rate variation. Simulation experiments show the technique to be accurate and powerful. SubRecon has a user-friendly command line interface and produces concise output that is intuitive yet suitable for subsequent parsing in an automated pipeline.

Availability and implementation

SubRecon is platform independent, requiring Java v1.8 or above. Source code, installation instructions and an example dataset are freely available under the Apache 2.0 license at https://github.com/chrismonit/SubRecon.

Molecular Signatures of Regression of the Canine Transmissible Venereal Tumor

The canine transmissible venereal tumor (CTVT) is a clonally transmissible cancer that regresses spontaneously or after treatment with vincristine, but we know little about the regression mechanisms. We performed global transcriptional, methylation, and functional pathway analyses on serial biopsies of vincristine-treated CTVTs and found that regression occurs in sequential steps; activation of the innate immune system and host epithelial tissue remodeling followed by immune infiltration of the tumor, arrest in the cell cycle, and repair of tissue damage. We identified CCL5 as a possible driver of CTVT regression. Changes in gene expression are associated with methylation changes at specific intragenic sites. Our results underscore the critical role of host innate immunity in triggering cancer regression.

Functionality and the Evolution of Marginal Stability in Proteins: Inferences from Lattice Simulations

It has been known for some time that many proteins are marginally stable. This has inspired several explanations. Having noted that the functionality of many enzymes is correlated with subunit motion, flexibility, or general disorder, some have suggested that marginally stable proteins should have an evolutionary advantage over proteins of differing stability. Others have suggested that stability and functionality are contradictory qualities, and that selection for both criteria results in marginally stable proteins, optimised to satisfy the competing design pressures. While these explanations are plausible, recent research simulating the evolution of model proteins has shown that selection for stability, ignoring any aspects of functionality, can result in marginally stable proteins because of the underlying makeup of protein sequence-space. We extend this research by simulating the evolution of proteins, using a computational protein model that equates functionality with binding and catalysis. In the model, marginal stability is not required for ligand-binding functionality and we observe no competing design pressures. The resulting proteins are marginally stable, again demonstrating that neutral evolution is sufficient for explaining marginal stability in observed proteins.

Sequence entropy of folding and the absolute rate of amino acid substitutions

Adequate representations of protein evolution should consider how the acceptance of mutations depends on the sequence context in which they arise. However, epistatic interactions among sites in a protein result in time and spatial substitution rate heterogeneity beyond the capabilities of current models. Here, we exploit parallels between amino acid substitutions and chemical reaction kinetics to develop an improved theory of protein evolution. We constructed a mechanistic framework for modelling amino acid substitution rates that employs the formalisms of statistical mechanics, with population genetics principles underlying the analysis. Theoretical analyses and computer simulations of proteins under purifying selection for thermodynamic stability show that substitution rates and the stabilisation of resident amino acids (the ‘evolutionary Stokes shift’) can be predicted from biophysics and the effect of sequence entropy alone. Furthermore, we demonstrate that substitutions predominantly occur when epistatic interactions result in near neutrality; substitution rates are determined by how often epistasis results in such nearly neutral conditions. This theory provides a general framework for modelling protein sequence change under purifying selection, potentially explains patterns of convergence and mutation rates in real proteins that are incompatible with previous models, and provides a better null model for the detection of adaptive changes.

The emerging GII.P16-GII.4 Sydney 2012 norovirus lineage is circulating worldwide, arose by late-2014 and contains polymerase changes that may increase virus transmission

Noroviruses are a leading cause of human gastroenteritis worldwide. The norovirus genotype GII.4 is the most prevalent genotype in the human population and has caused six pandemics since 1995. A novel norovirus lineage containing the GII.P16 polymerase and pandemic GII.4 Sydney 2012 capsid was recently detected in Asia and Germany. We demonstrate that this lineage is also circulating within the UK and USA and has been circulating since October 2014 or earlier. While the lineage does not contain unique substitutions in the capsid, it does contain polymerase substitutions close to positions known to influence polymerase function and virus transmission. These polymerase substitutions are shared with a GII.P16-GII.2 virus that dominated outbreaks in Germany in Winter 2016. We suggest that the substitutions in the polymerase may have resulted in a more transmissible virus and the combination of this polymerase and the pandemic GII.4 capsid may result in a highly transmissible virus. Further surveillance efforts will be required to determine whether the GII.P16-GII.4 Sydney 2012 lineage increases in frequency over the coming months.

Optimal chemotactic responses in stochastic environments

Although the “adaptive” strategy used by Escherichia coli has dominated our understanding of bacterial chemotaxis, the environmental conditions under which this strategy emerged is still poorly understood. In this work, we study the performance of various chemotactic strategies under a range of stochastic time- and space-varying attractant distributions in silico. We describe a novel “speculator” response in which the bacterium compare the current attractant concentration to the long-term average; if it is higher then they tumble persistently, while if it is lower than the average, bacteria swim away in search of more favorable conditions. We demonstrate how this response explains the experimental behavior of aerobically-grown Rhodobacter sphaeroides and that under spatially complex but slowly-changing nutrient conditions the speculator response is as effective as the adaptive strategy of E. coli.

Finding Direction in the Search for Selection

Tests for positive selection have mostly been developed to look for diversifying selection where change away from the current amino acid is often favorable. However, in many cases we are interested in directional selection where there is a shift toward specific amino acids, resulting in increased fitness in the species. Recently, a few methods have been developed to detect and characterize directional selection on a molecular level. Using the results of evolutionary simulations as well as HIV drug resistance data as models of directional selection, we compare two such methods with each other, as well as against a standard method for detecting diversifying selection. We find that the method to detect diversifying selection also detects directional selection under certain conditions. One method developed for detecting directional selection is powerful and accurate for a wide range of conditions, while the other can generate an excessive number of false positives.

Wide variation in susceptibility of transmitted/founder HIV-1 subtype C Isolates to protease inhibitors and association with in vitro replication efficiency

The gag gene is highly polymorphic across HIV-1 subtypes and contributes to susceptibility to protease inhibitors (PI), a critical class of antiretrovirals that will be used in up to 2 million individuals as second-line therapy in sub Saharan Africa by 2020. Given subtype C represents around half of all HIV-1 infections globally, we examined PI susceptibility in subtype C viruses from treatment-naïve individuals. PI susceptibility was measured in a single round infection assay of full-length, replication competent MJ4/gag chimeric viruses, encoding the gag gene and 142 nucleotides of pro derived from viruses in 20 patients in the Zambia-Emory HIV Research Project acute infection cohort. Ten-fold variation in susceptibility to PIs atazanavir and lopinavir was observed across 20 viruses, with EC50s ranging 0.71-6.95 nM for atazanvir and 0.64-8.54 nM for lopinavir. Ten amino acid residues in Gag correlated with lopinavir EC50 (p < 0.01), of which 380 K and 389I showed modest impacts on in vitro drug susceptibility. Finally a significant relationship between drug susceptibility and replication capacity was observed for atazanavir and lopinavir but not darunavir. Our findings demonstrate large variation in susceptibility of PI-naïve subtype C viruses that appears to correlate with replication efficiency and could impact clinical outcomes.

The tangled bank of amino acids

The use of amino acid substitution matrices to model protein evolution has yielded important insights into both the evolutionary process and the properties of specific protein families. In order to make these models tractable, standard substitution matrices represent the average results of the evolutionary process rather than the underlying molecular biophysics and population genetics, treating proteins as a set of independently evolving sites rather than as an integrated biomolecular entity. With advances in computing and the increasing availability of sequence data, we now have an opportunity to move beyond current substitution matrices to more interpretable mechanistic models with greater fidelity to the evolutionary process of mutation and selection and the holistic nature of the selective constraints. As part of this endeavour, we consider how epistatic interactions induce spatial and temporal rate heterogeneity, and demonstrate how these generally ignored factors can reconcile standard substitution rate matrices and the underlying biology, allowing us to better understand the meaning of these substitution rates. Using computational simulations of protein evolution, we can demonstrate the importance of both spatial and temporal heterogeneity in modelling protein evolution.

A coarse-grained biophysical model of sequence evolution and the population size dependence of the speciation rate

Speciation is fundamental to understanding the huge diversity of life on Earth. Although still controversial, empirical evidence suggests that the rate of speciation is larger for smaller populations. Here, we explore a biophysical model of speciation by developing a simple coarse-grained theory of transcription factor-DNA binding and how their co-evolution in two geographically isolated lineages leads to incompatibilities. To develop a tractable analytical theory, we derive a Smoluchowski equation for the dynamics of binding energy evolution that accounts for the fact that natural selection acts on phenotypes, but variation arises from mutations in sequences; the Smoluchowski equation includes selection due to both gradients in fitness and gradients in sequence entropy, which is the logarithm of the number of sequences that correspond to a particular binding energy. This simple consideration predicts that smaller populations develop incompatibilities more quickly in the weak mutation regime; this trend arises as sequence entropy poises smaller populations closer to incompatible regions of phenotype space. These results suggest a generic coarse-grained approach to evolutionary stochastic dynamics, allowing realistic modelling at the phenotypic level.

Nonadaptive Amino Acid Convergence Rates Decrease over Time

Convergence is a central concept in evolutionary studies because it provides strong evidence for adaptation. It also provides information about the nature of the fitness landscape and the repeatability of evolution, and can mislead phylogenetic inference. To understand the role of adaptive convergence, we need to understand the patterns of nonadaptive convergence. Here, we consider the relationship between nonadaptive convergence and divergence in mitochondrial and model proteins. Surprisingly, nonadaptive convergence is much more common than expected in closely related organisms, falling off as organisms diverge. The extent of the convergent drop-off in mitochondrial proteins is well predicted by epistatic or coevolutionary effects in our "evolutionary Stokes shift" models and poorly predicted by conventional evolutionary models. Convergence probabilities decrease dramatically if the ancestral amino acids of branches being compared have diverged, but also drop slowly over evolutionary time even if the ancestral amino acids have not substituted. Convergence probabilities drop-off rapidly for quickly evolving sites, but much more slowly for slowly evolving sites. Furthermore, once sites have diverged their convergence probabilities are extremely low and indistinguishable from convergence levels at randomized sites. These results indicate that we cannot assume that excessive convergence early on is necessarily adaptive. This new understanding should help us to better discriminate adaptive from nonadaptive convergence and develop more relevant evolutionary models with improved validity for phylogenetic inference.

Population size dependence of fitness effect distribution and substitution rate probed by biophysical model of protein thermostability

The predicted effect of effective population size on the distribution of fitness effects and substitution rate is critically dependent on the relationship between sequence and fitness. This highlights the importance of using models that are informed by the molecular biology, biochemistry, and biophysics of the evolving systems. We describe a computational model based on fundamental aspects of biophysics, the requirement for (most) proteins to be thermodynamically stable. Using this model, we find that differences in population size have minimal impact on the distribution of population-scaled fitness effects, as well as on the rate of molecular evolution. This is because larger populations result in selection for more stable proteins that are less affected by mutations. This reduction in the magnitude of the fitness effects almost exactly cancels the greater selective pressure resulting from the larger population size. Conversely, changes in the population size in either direction cause transient increases in the substitution rate. As differences in population size often correspond to changes in population size, this makes comparisons of substitution rates in different lineages difficult to interpret.

Summary of the HESI consortium studies exploring circulating inhibin B as a potential biomarker of testis damage in the rat

The Developmental and Reproductive Toxicity Technical Committee of the Health and Environmental Sciences Institute hosted a working consortium of companies to evaluate a new commercially available analytic assay for Inhibin B in rat serum or plasma. After demonstrating that the kit was stable and robust, the group performed a series of independent pathogenesis studies (23 different compound/investigator combinations) designed to examine the correlation between the appearance of lesions in the testis and changes in circulating levels of Inhibin B. These studies were reported individually in the previous articles in this series (this issue), and are discussed in this paper. For roughly half of these exposures, lesions appeared well before Inhibin B changed. A few of the studies showed a good correlation between seminiferous tubule damage and reduced circulating Inhibin B levels, while for seven exposures, circulating Inhibin B was reduced with no detectable alteration in testis histology. Whether this indicates a prodromal response or a false-positive signal will require further investigation. These exceptions could plausibly suggest some value of circulating Inhibin B as a useful biomarker in some circumstances. However, for roughly half of these exposures, Inhibin B appeared to be a lagging biomarker, requiring significant damage to the seminiferous tubules before a consistent and credible reduction in circulating levels of Inhibin B was observed.

The inhibin B response in male rats treated with two drug candidates

BACKGROUND

Serum Inhibin B was measured in two studies of known testis-toxic drug candidates.

METHODS AND RESULTS

Study 1 was for a compound for Hepatitis C, and utilized a 10-week dosing period, followed by mating and necropsy of half of each group, and then a 12-week recovery period for the remaining animals. At the postmating necropsy, 6 of 15 high-dose males had testis lesions; Inhibin B was significantly reduced in all animals in that group. The mid-dose group had no lesions but significantly reduced serum Inhibin B. At recovery, 9 of 15 high-dose males showed damage in testes; serum Inhibin B levels were not different from controls. Inhibin B appeared to both overreport and underreport testis damage in Study 1. Study 2 was an acute pathogenesis study for an antibacterial compound, using control and two dose levels and multiple time points (days 5, 8, 15, 22, and then untreated until day 71). At each time point blood was sampled from all remaining rats and five/group were killed for histologic evaluation. The low-dose group had minimal to moderate lesions, while serum Inhibin B was never changed. The high-dose animals progressed quickly from minimal lesions to being broadly and moderately affected; serum Inhibin B levels were reduced at days 8 and 15 only. In Study 2, Inhibin B appeared less sensitive than histology, except at the extremes of testis damage, when Inhibin B was routinely low.

CONCLUSION

We conclude that in these two studies there was a poor correlation between changes in serum levels of Inhibin B and testis histopathology.

Assessing predictors of changes in protein stability upon mutation using self-consistency

The ability to predict the effect of mutations on protein stability is important for a wide range of tasks, from protein engineering to assessing the impact of SNPs to understanding basic protein biophysics. A number of methods have been developed that make these predictions, but assessing the accuracy of these tools is difficult given the limitations and inconsistencies of the experimental data. We evaluate four different methods based on the ability of these methods to generate consistent results for forward and back mutations, and examine how this ability varies with the nature and location of the mutation. We find that, while one method seems to outperform the others, the ability of these methods to make accurate predictions is limited.

The interface of protein structure, protein biophysics, and molecular evolution

Abstract The interface of protein structural biology, protein biophysics, molecular evolution, and molecular population genetics forms the foundations for a mechanistic understanding of many aspects of protein biochemistry. Current efforts in interdisciplinary protein modeling are in their infancy and the state-of-the art of such models is described. Beyond the relationship between amino acid substitution and static protein structure, protein function, and corresponding organismal fitness, other considerations are also discussed. More complex mutational processes such as insertion and deletion and domain rearrangements and even circular permutations should be evaluated. The role of intrinsically disordered proteins is still controversial, but may be increasingly important to consider. Protein geometry and protein dynamics as a deviation from static considerations of protein structure are also important. Protein expression level is known to be a major determinant of evolutionary rate and several considerations including selection at the mRNA level and the role of interaction specificity are discussed. Lastly, the relationship between modeling and needed high-throughput experimental data as well as experimental examination of protein evolution using ancestral sequence resurrection and in vitro biochemistry are presented, towards an aim of ultimately generating better models for biological inference and prediction.

Evolution of response dynamics underlying bacterial chemotaxis

Background

The ability to predict the function and structure of complex molecular mechanisms underlying cellular behaviour is one of the main aims of systems biology. To achieve it, we need to understand the evolutionary routes leading to a specific response dynamics that can underlie a given function and how biophysical and environmental factors affect which route is taken. Here, we apply such an evolutionary approach to the bacterial chemotaxis pathway, which is documented to display considerable complexity and diversity.

Results

We construct evolutionarily accessible response dynamics starting from a linear response to absolute levels of attractant, to those observed in current-day Escherichia coli. We explicitly consider bacterial movement as a two-state process composed of non-instantaneous tumbling and swimming modes. We find that a linear response to attractant results in significant chemotaxis when sensitivity to attractant is low and when time spent tumbling is large. More importantly, such linear response is optimal in a regime where signalling has low sensitivity. As sensitivity increases, an adaptive response as seen in Escherichia coli becomes optimal and leads to 'perfect' chemotaxis with a low tumbling time. We find that as tumbling time decreases and sensitivity increases, there exist a parameter regime where the chemotaxis performance of the linear and adaptive responses overlap, suggesting that evolution of chemotaxis responses might provide an example for the principle of functional change in structural continuity.

Conclusions

Our findings explain several results from diverse bacteria and lead to testable predictions regarding chemotaxis responses evolved in bacteria living under different biophysical constraints and with specific motility machinery. Further, they shed light on the potential evolutionary paths for the evolution of complex behaviours from simpler ones in incremental fashion.

A model of the mechanisms of language extinction and revitalization strategies to save endangered languages

Why and how have languages died out? We have devised a mathematical model to help us understand how languages go extinct. We use the model to ask whether language extinction can be prevented in the future and why it may have occurred in the past. A growing number of mathematical models of language dynamics have been developed to study the conditions for language coexistence and death, yet their phenomenological approach compromises their ability to influence language revitalization policy. In contrast, here we model the mechanisms underlying language competition and look at how these mechanisms are influenced by specific language revitalization interventions, namely, private interventions to raise the status of the language and thus promote language learning at home, public interventions to increase the use of the minority language, and explicit teaching of the minority language in schools. Our model reveals that it is possible to preserve a minority language but that continued long-term interventions will likely be necessary. We identify the parameters that determine which interventions work best under certain linguistic and societal circumstances. In this way the efficacy of interventions of various types can be identified and predicted. Although there are qualitative arguments for these parameter values (e.g., the responsiveness of children to learning a language as a function of the proportion of conversations heard in that language, the relative importance of conversations heard in the family and elsewhere, and the amplification of spoken to heard conversations of the high-status language because of the media), extensive quantitative data are lacking in this field. We propose a way to measure these parameters, allowing our model, as well as others models in the field, to be validated.

Charting the host adaptation of influenza viruses

Four influenza pandemics have struck the human population during the last 100 years causing substantial morbidity and mortality. The pandemics were caused by the introduction of a new virus into the human population from an avian or swine host or through the mixing of virus segments from an animal host with a human virus to create a new reassortant subtype virus. Understanding which changes have contributed to the adaptation of the virus to the human host is essential in assessing the pandemic potential of current and future animal viruses. Here, we develop a measure of the level of adaptation of a given virus strain to a particular host. We show that adaptation to the human host has been gradual with a timescale of decades and that none of the virus proteins have yet achieved full adaptation to the selective constraints. When the measure is applied to historical data, our results indicate that the 1918 influenza virus had undergone a period of preadaptation prior to the 1918 pandemic. Yet, ancestral reconstruction of the avian virus that founded the classical swine and 1918 human influenza lineages shows no evidence that this virus was exceptionally preadapted to humans. These results indicate that adaptation to humans occurred following the initial host shift from birds to mammals, including a significant amount prior to 1918. The 2009 pandemic virus seems to have undergone preadaptation to human-like selective constraints during its period of circulation in swine. Ancestral reconstruction along the human virus tree indicates that mutations that have increased the adaptation of the virus have occurred preferentially along the trunk of the tree. The method should be helpful in assessing the potential of current viruses to found future epidemics or pandemics.

Effect of magnetic fields on the triplet state lifetime in photosynthetic reaction centers: Evidence for thermal repopulation of the initial radical pair

The lifetime of the molecular triplet state formed by recombination of the radical ion pair in quinonedepleted bacterial photosynthetic reaction centers is found to depend on applied magnetic field strength. It is suggested that this magnetic field effect results from thermally activated repopulation of the same radical ion pair that generates the triplet. Consistent with this hypothesis, the magnetic field effect on the triplet lifetime disappears at low temperature where the triplet state decays exclusively by ordinary intersystem crossing. This activated pathway for the decay of the triplet state can explain the strong temperature dependence of the triplet decay rate. A detailed theoretical treatment of the problem within a set of physically reasonable assumptions relates the observed temperature dependence of the triplet decay rate to the energy gap between the radical ion pair intermediate and the triplet state. This energy gap is estimated to be about 950 cm(-1) (0.12 eV). Combined with an estimate of the energy of the donor excited state, we obtain an energy gap between the excited singlet state of the donor and the radical ion pair of 2,250 cm(-1) (0.28 eV).

Effects of nuclear spin polarization on reaction dynamics in photosynthetic bacterial reaction centers

Singlet-triplet mixing in the initial radical-pair state, P[unk]I[unk], of photosynthetic bacterial reaction centers is due to the hyperfine mechanism at low magnetic fields and both the hyperfine and Deltag mechanisms at high magnetic fields (>1 kG). Since the hyperfine field felt by the electron spins in P[unk]I[unk] is dependent upon the nuclear spin state in each radical, the relative probabilities of charge recombination to the triplet state of the primary electron donor, (3)PI, or the ground state, PI, will depend on the nuclear spin configuration. As a result these recombination products will have non-equilibrium distributions of nuclear spin states (nuclear spin polarization). This polarization will persist until the (3)PI state decays. In addition, due to unequal nuclear spin relaxation rates in the diamagnetic PI and paramagnetic (3)PI states, net polarization of the nuclear spins can result, especially in experiments that involve recycling of the system through the radical-pair state. This net polarization can persist for very long times, especially at low temperatures. Nuclear spin polarization can have consequences on any subsequent process that involves re-formation of the radical-pair state.Numerical calculations of the nuclear polarization caused by both of these mechanics are presented, including the effect of such polarization on subsequent yields of (3)PI, (3)PI decay rates, the decay rate of the radical pair, and saturation behavior. The effect of this polarization under certain circumstances can be very dramatic and can explain previously noted discrepancies between experiments and theories that do not include nuclear spin polarization effects. Our analysis suggests new classes of experiments and indicates the need to reinterpret some past experimental results.

Analysis of host-parasite incongruence in papillomavirus evolution using importance sampling

The papillomaviruses (PVs) are a family of viruses infecting several mammalian and nonmammalian species that cause cervical cancer in humans. The evolutionary history of the PVs as it associated with a wide range of host species is not well understood. Incongruities between the phylogenetic trees of various viral genes as well as between these genes and the host phylogenies suggest historical viral recombination as well as violations of strict virus–host cospeciation. The extent of recombination events among PVs is uncertain, however, and there is little evidence to support a theory of PV spread via recent host transfers. We have investigated incongruence between PV genes and hence, the possibility of recombination, using Bayesian phylogenetic methods. We find significant evidence for phylogenetic incongruence among the six PV genes E1, E2, E6, E7, L1, and L2, indicating substantial recombination. Analysis of E1 and L1 phylogenies suggests ancestral recombination events. We also describe a new method for examining alternative host–parasite association mechanisms by applying importance sampling to Bayesian divergence time estimation. This new approach is not restricted by a fixed viral tree topology or knowledge of viral divergence times, multiple parasite taxa per host may be included, and it can distinguish between prior divergence of the virus before host speciation and host transfer of the virus following speciation. Using this method, we find prior divergence of PV lineages associated with the ancestral mammalian host resulting in at least 6 PV lineages prior to speciation of this host. These PV lineages have then followed paths of prior divergence and cospeciation to eventually become associated with the extant host species. Only one significant instance of host transfer is supported, the transfer of the ancestral L1 gene between a Primate and Hystricognathi host based on the divergence times between the υ human type 41 and porcupine PVs.

In silico biology

Rather than studying existent living systems, we can increasingly produce computer models that capture the salient aspects of life. This provides us with unprecedented opportunities to examine, manipulate, and explore biological phenomena, allowing us to investigate some of the deepest issues in biology.

Identifying changes in selective constraints: host shifts in influenza

The natural reservoir of Influenza A is waterfowl. Normally, waterfowl viruses are not adapted to infect and spread in the human population. Sometimes, through reassortment or through whole host shift events, genetic material from waterfowl viruses is introduced into the human population causing worldwide pandemics. Identifying which mutations allow viruses from avian origin to spread successfully in the human population is of great importance in predicting and controlling influenza pandemics. Here we describe a novel approach to identify such mutations. We use a sitewise non-homogeneous phylogenetic model that explicitly takes into account differences in the equilibrium frequencies of amino acids in different hosts and locations. We identify 172 amino acid sites with strong support and 518 sites with moderate support of different selection constraints in human and avian viruses. The sites that we identify provide an invaluable resource to experimental virologists studying adaptation of avian flu viruses to the human host. Identification of the sequence changes necessary for host shifts would help us predict the pandemic potential of various strains. The method is of broad applicability to investigating changes in selective constraints when the timing of the changes is known.

Influenza A's natural reservoir is waterfowl. Sometimes avian virus genomic segments are able to shift to a human host, either in toto or by combining with those that underwent a previous host shift event. Such host shift events can cause worldwide pandemics in their immunologically naive hosts. In order for these host shifts to establish a stable lineage, the virus has to adapt to the new host. Identifying the changes that have occurred in the past can provide important clues about how this process happens, and how surveillance for new influenza threats should be targeted. Unfortunately, it is difficult to determine whether an amino acid has changed due to adaptation to the new host or whether the change occurred through random drift. Here we describe a novel phylogenetic approach to identifying locations where the nature of the selective pressure exerted on the location has changed corresponding to the host shift event. We identify a set of locations on a number of the genomic segments. The approach we describe is of wide applicability when the timing of the change of selective constraints is known in advance.

Evolution of taxis responses in virtual bacteria: non-adaptive dynamics

Bacteria are able to sense and respond to a variety of external stimuli, with responses that vary from stimuli to stimuli and from species to species. The best-understood is chemotaxis in the model organism Escherichia coli, where the dynamics and the structure of the underlying pathway are well characterised. It is not clear, however, how well this detailed knowledge applies to mechanisms mediating responses to other stimuli or to pathways in other species. Furthermore, there is increasing experimental evidence that bacteria integrate responses from different stimuli to generate a coherent taxis response. We currently lack a full understanding of the different pathway structures and dynamics and how this integration is achieved. In order to explore different pathway structures and dynamics that can underlie taxis responses in bacteria, we perform a computational simulation of the evolution of taxis. This approach starts with a population of virtual bacteria that move in a virtual environment based on the dynamics of the simple biochemical pathways they harbour. As mutations lead to changes in pathway structure and dynamics, bacteria better able to localise with favourable conditions gain a selective advantage. We find that a certain dynamics evolves consistently under different model assumptions and environments. These dynamics, which we call non-adaptive dynamics, directly couple tumbling probability of the cell to increasing stimuli. Dynamics that are adaptive under a wide range of conditions, as seen in the chemotaxis pathway of E. coli, do not evolve in these evolutionary simulations. However, we find that stimulus scarcity and fluctuations during evolution results in complex pathway dynamics that result both in adaptive and non-adaptive dynamics depending on basal stimuli levels. Further analyses of evolved pathway structures show that effective taxis dynamics can be mediated with as few as two components. The non-adaptive dynamics mediating taxis responses provide an explanation for experimental observations made in mutant strains of E. coli and in wild-type Rhodobacter sphaeroides that could not be explained with standard models. We speculate that such dynamics exist in other bacteria as well and play a role linking the metabolic state of the cell and the taxis response. The simplicity of mechanisms mediating such dynamics makes them a candidate precursor of more complex taxis responses involving adaptation. This study suggests a strong link between stimulus conditions during evolution and evolved pathway dynamics. When evolution was simulated under conditions of scarce and fluctuating stimulus conditions, the evolved pathway contained features of both adaptive and non-adaptive dynamics, suggesting that these two types of dynamics can have different advantages under distinct environmental circumstances.

Here, we study how signalling networks mediating chemotaxis could have evolved. We simulated the evolution of virtual bacteria, which can explore their environment by alternating between swimming and tumbling. The tumbling frequency is dictated by the output of a signalling network that senses extracellular nutrient levels, while the bacteria's reproductive success is determined by their ability to find nutrients. Under conditions of abundant food, we find that bacteria quickly evolve signalling networks that enable effective chemotaxis, where increasing nutrient levels increase tumbling frequency. Our findings provide explanation for network dynamics underlying similar behaviour as observed in certain mutant strains of Escherichia coli and in other bacterial species. Conversely, wild-type E. coli respond to increasing nutrient levels by decreasing their tumbling frequency and adapting to constant attractant levels. We observe such adaptive network dynamics when we repeat evolutionary simulations under conditions of scarce food. These findings suggest that (i) adaptation is not necessary for effective chemotaxis, (ii) an ancestral minimal chemotaxis system could have used a simple coupling between the signalling network and the metabolic state, and (iii) environmental conditions are one of the determining factors for the evolution of adaptive responses.

Changing selective pressure during antigenic changes in human influenza H3

The rapid evolution of influenza viruses presents difficulties in maintaining the optimal efficiency of vaccines. Amino acid substitutions result in antigenic drift, a process whereby antisera raised in response to one virus have reduced effectiveness against future viruses. Interestingly, while amino acid substitutions occur at a relatively constant rate, the antigenic properties of H3 move in a discontinuous, step-wise manner. It is not clear why this punctuated evolution occurs, whether this represents simply the fact that some substitutions affect these properties more than others, or if this is indicative of a changing relationship between the virus and the host. In addition, the role of changing glycosylation of the haemagglutinin in these shifts in antigenic properties is unknown. We analysed the antigenic drift of HA1 from human influenza H3 using a model of sequence change that allows for variation in selective pressure at different locations in the sequence, as well as at different parts of the phylogenetic tree. We detect significant changes in selective pressure that occur preferentially during major changes in antigenic properties. Despite the large increase in glycosylation during the past 40 years, changes in glycosylation did not correlate either with changes in antigenic properties or with significantly more rapid changes in selective pressure. The locations that undergo changes in selective pressure are largely in places undergoing adaptive evolution, in antigenic locations, and in locations or near locations undergoing substitutions that characterise the change in antigenicity of the virus. Our results suggest that the relationship of the virus to the host changes with time, with the shifts in antigenic properties representing changes in this relationship. This suggests that the virus and host immune system are evolving different methods to counter each other. While we are able to characterise the rapid increase in glycosylation of the haemagglutinin during time in human influenza H3, an increase not present in influenza in birds, this increase seems unrelated to the observed changes in antigenic properties.

The organization of two rRNA (rrn) operons of the slow-growing pathogen Mycobacterium celatum provides key insights into mycobacterial evolution

The slow-growing Mycobacterium celatum is known to have two different 16S rRNA gene sequences. This study confirms the presence of two rrn operons and describes their organization. One operon (rrnA) was found to be located downstream from murA and the other (rrnB) was found downstream from tyrS. The promoter regions were sequenced, and also the intergenic transcribed spacer (ITS1 and ITS2) regions separating the 16S rRNA, 23S rRNA and 5S rRNA gene coding regions. Analysis of the RNA fraction revealed that rrnA is regulated by two (P1 and PCL1) promoters and rrnB is regulated by one (P1). These data show that the two rrn operons of M. celatum are organized in the same way as the two rrn operons of classical fast-growing mycobacteria. This information was incorporated into a phylogenetic analysis of the genus based on both 16S rRNA gene sequences and (where possible) the number of rrn operons per genome. The results suggest that the ancestral Mycobacterium possessed two (rrnA and rrnB) operons per genome and that subsequently, on two separate occasions, an operon (rrnB) was lost, leading to two clusters of species having a single operon (rrnA); one cluster includes the classical pathogens and the other includes Mycobacterium abscessus and Mycobacterium chelonae.