The Evolutionary Pathway to Virulence of an RNA Virus.

Paralytic polio once afflicted almost half a million children each year. The attenuated oral polio vaccine (OPV) has enabled world-wide vaccination efforts, which resulted in nearly complete control of the disease. However, poliovirus eradication is hampered globally by epidemics of vaccine-derived polio. Here, we describe a combined theoretical and experimental strategy that describes the molecular events leading from OPV to virulent strains. We discover that similar evolutionary events occur in most epidemics. The mutations and the evolutionary trajectories driving these epidemics are replicated using a simple cell-based experimental setup where the rate of evolution is intentionally accelerated. Furthermore, mutations accumulating during epidemics increase the replication fitness of the virus in cell culture and increase virulence in an animal model. Our study uncovers the evolutionary strategies by which vaccine strains become pathogenic and provides a powerful framework for rational design of safer vaccine strains and for forecasting virulence of viruses. VIDEO ABSTRACT.

Dual anti-viral treatment for persistent COVID-19 in immunocompromised hemato-oncological patients is associated with a favorable prognosis and minor side effects.

In hemato-oncological patients, COVID-19 can present as a persistent infection with ongoing symptoms and viral replication over a prolonged period of time. Data are scarce on the preferred treatment options for these patients. We describe our experience with a five-day course of dual anti-viral treatment with remdesivir and nirmatrelvir/ritonavir for hemato-oncological immunocompromised patients with persistent COVID-19. Fifteen patients with a history of lymphoma, CLL, and MM were included. Eight were male, median age was 74. All patients had an immediate clinical and virological response. In 73 % of patients, PCR for SARS-CoV-2 became negative at the end of treatment and the rest had an increase in PCR cycle threshold (CT) values, with a median increase of 6 cycles. After a follow-up of three months, 60 % of patients remained in full clinical and virological remission. None required invasive mechanical ventilation or died. The side effects we observed, neutropenia, lactatemia and elevated transaminases, were mild and almost all transient in nature. We conclude that dual anti-viral treatment appears to be a valid treatment option for persistent COVID-19.

Inferring Protein Function in an Emerging Virus: Detection of the Nucleoprotein in Tilapia Lake Virus.

Emerging viruses impose global threats to animal and human populations and may bear novel genes with limited homology to known sequences, necessitating the development of novel approaches to infer and test protein functions. This challenge is dramatically evident in tilapia lake virus (TiLV), an emerging "orthomyxo-like" virus that threatens the global tilapia aquaculture and food security of millions of people. The majority of TiLV proteins have no homology to known sequences, impeding functionality assessments. Using a novel bioinformatics approach, we predicted that TiLV's Protein 4 encodes the nucleoprotein, a factor essential for viral RNA replication. Multiple methodologies revealed the expected properties of orthomyxoviral nucleoproteins. A modified yeast three-hybrid assay detected Protein 4-RNA interactions, which were independent of the RNA sequence, and identified specific positively charged residues involved. Protein 4-RNA interactions were uncovered by R-DeeP and XRNAX methodologies. Immunoelectron microscopy found that multiple Protein 4 copies localized along enriched ribonucleoproteins. TiLV RNA from cells and virions coimmunoprecipitated with Protein 4. Immunofluorescence microscopy detected Protein 4 in the cytoplasm and nuclei, and nuclear Protein 4 increased upon CRM1 inhibition, suggesting CRM1-dependent nuclear export of TiLV RNA. Together, these data reveal TiLV's nucleoprotein and highlight the ability to infer protein functionality, including novel RNA-binding proteins, in emerging pathogens. These are important in light of the expected discovery of many unknown viruses and the zoonotic potential of such pathogens. IMPORTANCE Tilapia is an important source of dietary protein, especially in developing countries. Massive losses of tilapia were identified worldwide, risking the food security of millions of people. Tilapia lake virus (TiLV) is an emerging pathogen responsible for these disease outbreaks. TiLV's genome encodes 10 major proteins, 9 of which show no homology to other known viral or cellular proteins, hindering functionality assessment of these proteins. Here, we describe a novel bioinformatics approach to infer the functionality of TiLV proteins, which predicted Protein 4 as the nucleoprotein, a factor essential for viral RNA replication. We provided experimental support for this prediction by applying multiple molecular, biochemical, and imaging approaches. Overall, we illustrate a strategy for functional analyses in viral discovery. The strategy is important in light of the expected discovery of many unknown viruses and the zoonotic potential of such pathogens.

Biased Mutation and Selection in RNA Viruses.

RNA viruses are responsible for some of the worst pandemics known to mankind, including outbreaks of Influenza, Ebola, and COVID-19. One major challenge in tackling RNA viruses is the fact they are extremely genetically diverse. Nevertheless, they share common features that include their dependence on host cells for replication, and high mutation rates. We set out to search for shared evolutionary characteristics that may aid in gaining a broader understanding of RNA virus evolution, and constructed a phylogeny-based data set spanning thousands of sequences from diverse single-stranded RNA viruses of animals. Strikingly, we found that the vast majority of these viruses have a skewed nucleotide composition, manifested as adenine rich (A-rich) coding sequences. In order to test whether A-richness is driven by selection or by biased mutation processes, we harnessed the effects of incomplete purifying selection at the tips of virus phylogenies. Our results revealed consistent mutational biases toward U rather than A in genomes of all viruses. In +ssRNA viruses, we found that this bias is compensated by selection against U and selection for A, which leads to A-rich genomes. In -ssRNA viruses, the genomic mutational bias toward U on the negative strand manifests as A-rich coding sequences, on the positive strand. We investigated possible reasons for the advantage of A-rich sequences including weakened RNA secondary structures, codon usage bias, and selection for a particular amino acid composition, and conclude that host immune pressures may have led to similar biases in coding sequence composition across very divergent RNA viruses.

Drivers of within-host genetic diversity in acute infections of viruses.

Genetic diversity is the fuel of evolution and facilitates adaptation to novel environments. However, our understanding of what drives differences in the genetic diversity during the early stages of viral infection is somewhat limited. Here, we use ultra-deep sequencing to interrogate 43 clinical samples taken from early infections of the human-infecting viruses HIV, RSV and CMV. Hundreds to thousands of virus templates were sequenced per sample, allowing us to reveal dramatic differences in within-host genetic diversity among virus populations. We found that increased diversity was mostly driven by presence of multiple divergent genotypes in HIV and CMV samples, which we suggest reflect multiple transmitted/founder viruses. Conversely, we detected an abundance of low frequency hyper-edited genomes in RSV samples, presumably reflecting defective virus genomes (DVGs). We suggest that RSV is characterized by higher levels of cellular co-infection, which allow for complementation and hence elevated levels of DVGs.

A Bayesian Framework for Inferring the Influence of Sequence Context on Point Mutations.

The probability of point mutations is expected to be highly influenced by the flanking nucleotides that surround them, known as the sequence context. This phenomenon may be mainly attributed to the enzyme that modifies or mutates the genetic material, because most enzymes tend to have specific sequence contexts that dictate their activity. Here, we develop a statistical model that allows for the detection and evaluation of the effects of different sequence contexts on mutation rates from deep population sequencing data. This task is computationally challenging, as the complexity of the model increases exponentially as the context size increases. We established our novel Bayesian method based on sparse model selection methods, with the leading assumption that the number of actual sequence contexts that directly influence mutation rates is minuscule compared with the number of possible sequence contexts. We show that our method is highly accurate on simulated data using pentanucleotide contexts, even when accounting for noisy data. We next analyze empirical population sequencing data from polioviruses and HIV-1 and detect a significant enrichment in sequence contexts associated with deamination by the cellular deaminases ADAR 1/2 and APOBEC3G, respectively. In the current era, where next-generation sequencing data are highly abundant, our approach can be used on any population sequencing data to reveal context-dependent base alterations and may assist in the discovery of novel mutable sites or editing sites.

Direct sequencing of RNA with MinION Nanopore: detecting mutations based on associations.

One of the key challenges in the field of genetics is the inference of haplotypes from next generation sequencing data. The MinION Oxford Nanopore sequencer allows sequencing long reads, with the potential of sequencing complete genes, and even complete genomes of viruses, in individual reads. However, MinION suffers from high error rates, rendering the detection of true variants difficult. Here, we propose a new statistical approach named AssociVar, which differentiates between true mutations and sequencing errors from direct RNA/DNA sequencing using MinION. Our strategy relies on the assumption that sequencing errors will be dispersed randomly along sequencing reads, and hence will not be associated with each other, whereas real mutations will display a non-random pattern of association with other mutations. We demonstrate our approach using direct RNA sequencing data from evolved populations of the MS2 bacteriophage, whose small genome makes it ideal for MinION sequencing. AssociVar inferred several mutations in the phage genome, which were corroborated using parallel Illumina sequencing. This allowed us to reconstruct full genome viral haplotypes constituting different strains that were present in the sample. Our approach is applicable to long read sequencing data from any organism for accurate detection of bona fide mutations and inter-strain polymorphisms.

Correction: Within-patient mutation frequencies reveal fitness costs of CpG dinucleotides and drastic amino acid changes in HIV.

[This corrects the article DOI: 10.1371/journal.pgen.1007420.].

Within-patient mutation frequencies reveal fitness costs of CpG dinucleotides and drastic amino acid changes in HIV.

HIV has a high mutation rate, which contributes to its ability to evolve quickly. However, we know little about the fitness costs of individual HIV mutations in vivo, their distribution and the different factors shaping the viral fitness landscape. We calculated the mean frequency of transition mutations at 870 sites of the pol gene in 160 patients, allowing us to determine the cost of these mutations. As expected, we found high costs for non-synonymous and nonsense mutations as compared to synonymous mutations. In addition, we found that non-synonymous mutations that lead to drastic amino acid changes are twice as costly as those that do not and mutations that create new CpG dinucleotides are also twice as costly as those that do not. We also found that G→A and C→T mutations are more costly than A→G mutations. We anticipate that our new in vivo frequency-based approach will provide insights into the fitness landscape and evolvability of not only HIV, but a variety of microbes.

Associations between ADHD and emotional problems from childhood to young adulthood: a longitudinal genetically sensitive study.

BACKGROUND: Attention deficit/hyperactivity disorder (ADHD) is associated with emotional problems, and their co-occurrence often leads to worse outcomes. We investigated the developmental associations between ADHD and emotional problems from childhood to early adolescence and examined the genetic and environmental contributions to their developmental link. We further tested whether this developmental association remained across the transition to young adulthood. METHODS: We used data from the Environmental Risk (E-Risk) Longitudinal Twin Study, a cohort of 2,232 British twins. In childhood, ADHD and emotional problems were assessed at ages 5, 7, 10 and 12 with mothers' and teachers' reports. At age 18, we used self-reported symptoms according to DSM-5 criteria for ADHD, and DSM-IV for anxiety and depression. RESULTS: Longitudinal analyses showed that earlier ADHD was associated with later emotional problems consistently across childhood. However, earlier emotional problems were not associated with later ADHD symptoms. The developmental association between ADHD and later emotional problems in childhood was entirely explained by common genetic factors. Consistent with results in childhood, earlier symptoms of ADHD were associated with later emotional problems during the transition to young adulthood. CONCLUSIONS: Our findings demonstrate that ADHD symptoms are predictors of the development of emotional problems, from childhood up to young adulthood, through shared genetic influences. Interventions targeting ADHD symptoms might prevent the development of emotional problems. Clinicians treating youth with ADHD must be aware of their risk for developing emotional problems and ought to assess, monitor and treat emotional problems alongside ADHD symptoms from childhood to adulthood.

MYB107 and MYB9 Homologs Regulate Suberin Deposition in Angiosperms.

Suberin, a polymer composed of both aliphatic and aromatic domains, is deposited as a rough matrix upon plant surface damage and during normal growth in the root endodermis, bark, specialized organs (e.g., potato [Solanum tuberosum] tubers), and seed coats. To identify genes associated with the developmental control of suberin deposition, we investigated the chemical composition and transcriptomes of suberized tomato (Solanum lycopersicum) and russet apple (Malus x domestica) fruit surfaces. Consequently, a gene expression signature for suberin polymer assembly was revealed that is highly conserved in angiosperms. Seed permeability assays of knockout mutants corresponding to signature genes revealed regulatory proteins (i.e., AtMYB9 and AtMYB107) required for suberin assembly in the Arabidopsis thaliana seed coat. Seeds of myb107 and myb9 Arabidopsis mutants displayed a significant reduction in suberin monomers and altered levels of other seed coat-associated metabolites. They also exhibited increased permeability, and lower germination capacities under osmotic and salt stress. AtMYB9 and AtMYB107 appear to synchronize the transcriptional induction of aliphatic and aromatic monomer biosynthesis and transport and suberin polymerization in the seed outer integument layer. Collectively, our findings establish a regulatory system controlling developmentally deposited suberin, which likely differs from the one of stress-induced polymer assembly recognized to date.

CRISPR targeting reveals a reservoir of common phages associated with the human gut microbiome.

The bacterial community in the human gut has crucial health roles both in metabolic functions and in protection against pathogens. Phages, which are known to significantly affect microbial community composition in many ecological niches, have the potential to impact the gut microbiota, yet thorough characterization of this relationship remains elusive. We have reconstructed the content of the CRISPR bacterial immune system in the human gut microbiomes of 124 European individuals and used it to identify a catalog of 991 phages targeted by CRISPR across all individuals. Our results show that 78% of these phages are shared among two or more individuals. Moreover, a significant fraction of phages found in our study are shown to exist in fecal samples previously derived from American and Japanese individuals, identifying a common reservoir of phages frequently associated with the human gut microbiome. We further inferred the bacterial hosts for more than 130 such phages, enabling a detailed analysis of phage-bacteria interactions across the 124 individuals by correlating patterns of phage abundance with bacterial abundance and resistance. A subset of phages demonstrated preferred association with host genomes as lysogenized prophages, with highly increased abundance in specific individuals. Overall, our results imply that phage-bacterial attack-resistance interactions occur within the human gut microbiome, possibly affecting microbiota composition and human health. Our finding of global sharing of gut phages is surprising in light of the extreme genetic diversity of phages found in other ecological niches.

Validating the measurement of executive functions in an occupational context for adults with attention deficit hyperactivity disorder.

OBJECTIVE. The objectives of this study were to better understand the cognitive profile of adults with attention deficit hyperactivity disorder (ADHD), their occupational performance, and their quality of life (QoL) and to examine the validity of a cognitive-functional evaluation (CFE) battery for these adults. METHOD. Eighty-one adults with ADHD and 58 without ADHD completed ADHD symptom ratings, the Behavior Rating Inventory of Executive Function-Adult Version, and the Adult ADHD Quality-of-Life Scale. An occupational performance interview was administered to the ADHD group. RESULTS. A broad range of occupational concerns were reported. We found significant differences between groups on all measures. In the ADHD group, we found medium significant correlations among the measures. CONCLUSION. Adults with ADHD experience cognitive and functional difficulties in their daily lives associated with QoL. The results support the use of a CFE battery that has been shown to be sensitive and specific for these adults.

Using big sequencing data to identify chronic SARS-Coronavirus-2 infections.

The evolution of SARS-Coronavirus-2 (SARS-CoV-2) has been characterized by the periodic emergence of highly divergent variants. One leading hypothesis suggests these variants may have emerged during chronic infections of immunocompromised individuals, but limited data from these cases hinders comprehensive analyses. Here, we harnessed millions of SARS-CoV-2 genomes to identify potential chronic infections and used language models (LM) to infer chronic-associated mutations. First, we mined the SARS-CoV-2 phylogeny and identified chronic-like clades with identical metadata (location, age, and sex) spanning over 21 days, suggesting a prolonged infection. We inferred 271 chronic-like clades, which exhibited characteristics similar to confirmed chronic infections. Chronic-associated mutations were often high-fitness immune-evasive mutations located in the spike receptor-binding domain (RBD), yet a minority were unique to chronic infections and absent in global settings. The probability of observing high-fitness RBD mutations was 10-20 times higher in chronic infections than in global transmission chains. The majority of RBD mutations in BA.1/BA.2 chronic-like clades bore predictive value, i.e., went on to display global success. Finally, we used our LM to infer hundreds of additional chronic-like clades in the absence of metadata. Our approach allows mining extensive sequencing data and providing insights into future evolutionary patterns of SARS-CoV-2.

Synonymous site conservation in the HIV-1 genome.

BACKGROUND: Synonymous or silent mutations are usually thought to evolve neutrally. However, accumulating recent evidence has demonstrated that silent mutations may destabilize RNA structures or disrupt cis regulatory motifs superimposed on coding sequences. Such observations suggest the existence of stretches of codon sites that are evolutionary conserved at both DNA-RNA and protein levels. Such stretches may point to functionally important regions within protein coding sequences not necessarily reflecting functional constraints on the amino-acid sequence. The HIV-1 genome is highly compact, and often harbors overlapping functional elements at the protein, RNA, and DNA levels. This superimposition of functions leads to complex selective forces acting on all levels of the genome and proteome. Considering the constraints on HIV-1 to maintain such a highly compact genome, we hypothesized that stretches of synonymous conservation would be common within its genome. RESULTS: We used a combined computational-experimental approach to detect and characterize regions exhibiting strong purifying selection against synonymous substitutions along the HIV-1 genome. Our methodology is based on advanced probabilistic evolutionary models that explicitly account for synonymous rate variation among sites and rate dependencies among adjacent sites. These models are combined with a randomization procedure to automatically identify the most statistically significant regions of conserved synonymous sites along the genome. Using this procedure we identified 21 conserved regions. Twelve of these are mapped to regions within overlapping genes, seven correlate with known functional elements, while the functions of the remaining four are yet unknown. Among these four regions, we chose the one that deviates most from synonymous rate homogeneity for in-depth computational and experimental characterization. In our assays aiming to quantify viral fitness in both early and late stages of the replication cycle, no differences were observed between the mutated and the wild type virus following the introduction of synonymous mutations. CONCLUSIONS: The contradiction between the inferred purifying selective forces and the lack of effect of these mutations on viral replication may be explained by the fact that the phenotype was measured in single-cycle infection assays in cell culture. Such a system does not account for the complexity of HIV-1 infections in vivo, which involves multiple infection cycles and interaction with the host immune system.

Self-targeting by CRISPR: gene regulation or autoimmunity?

The recently discovered prokaryotic immune system known as CRISPR (clustered regularly interspaced short palindromic repeats) is based on small RNAs ('spacers') that restrict phage and plasmid infection. It has been hypothesized that CRISPRs can also regulate self gene expression by utilizing spacers that target self genes. By analyzing CRISPRs from 330 organisms we found that one in every 250 spacers is self-targeting, and that such self-targeting occurs in 18% of all CRISPR-bearing organisms. However, complete lack of conservation across species, combined with abundance of degraded repeats near self-targeting spacers, suggests that self-targeting is a form of autoimmunity rather than a regulatory mechanism. We propose that accidental incorporation of self nucleic acids by CRISPR can incur an autoimmune fitness cost, and this could explain the abundance of degraded CRISPR systems across prokaryotes.

Holding a grudge: persisting anti-phage CRISPR immunity in multiple human gut microbiomes.

The CRISPR (clustered regularly interspaced short palindromic repeats)/Cas (CRISPR-associated) system of bacteria and archaea constitutes a mechanism of acquired adaptive immunity against phages, which is based on genome-encoded markers of previously infecting phage sequences ("spacers"). As a repository of phage sequences, these spacers make the system particularly suitable for elucidating phage-bacteria interactions in metagenomic studies. Recent metagenomic analyses of CRISPRs associated with the human microbiome intriguingly revealed conserved "memory spacers" shared by bacteria in multiple unrelated, geographically separated individuals. Here, we discuss possible avenues for explaining this phenomenon by integrating insights from CRISPR biology and phage-bacteria ecology, with a special focus on the human gut. We further explore the growing body of evidence for the role of CRISPR/Cas in regulating the interplay between bacteria and lysogenic phages, which may be intimately related to the presence of memory spacers and sheds new light on the multifaceted biological and ecological modes of action of CRISPR/Cas.

The phage-host arms race: shaping the evolution of microbes.

Bacteria, the most abundant organisms on the planet, are outnumbered by a factor of 10 to 1 by phages that infect them. Faced with the rapid evolution and turnover of phage particles, bacteria have evolved various mechanisms to evade phage infection and killing, leading to an evolutionary arms race. The extensive co-evolution of both phage and host has resulted in considerable diversity on the part of both bacterial and phage defensive and offensive strategies. Here, we discuss the unique and common features of phage resistance mechanisms and their role in global biodiversity. The commonalities between defense mechanisms suggest avenues for the discovery of novel forms of these mechanisms based on their evolutionary traits.

Mutation rate, selection, and epistasis inferred from RNA virus haplotypes via neural posterior estimation.

RNA viruses are particularly notorious for their high levels of genetic diversity, which is generated through the forces of mutation and natural selection. However, disentangling these two forces is a considerable challenge, and this may lead to widely divergent estimates of viral mutation rates, as well as difficulties in inferring the fitness effects of mutations. Here, we develop, test, and apply an approach aimed at inferring the mutation rate and key parameters that govern natural selection, from haplotype sequences covering full-length genomes of an evolving virus population. Our approach employs neural posterior estimation, a computational technique that applies simulation-based inference with neural networks to jointly infer multiple model parameters. We first tested our approach on synthetic data simulated using different mutation rates and selection parameters while accounting for sequencing errors. Reassuringly, the inferred parameter estimates were accurate and unbiased. We then applied our approach to haplotype sequencing data from a serial passaging experiment with the MS2 bacteriophage, a virus that parasites Escherichia coli. We estimated that the mutation rate of this phage is around 0.2 mutations per genome per replication cycle (95% highest density interval: 0.051-0.56). We validated this finding with two different approaches based on single-locus models that gave similar estimates but with much broader posterior distributions. Furthermore, we found evidence for reciprocal sign epistasis between four strongly beneficial mutations that all reside in an RNA stem loop that controls the expression of the viral lysis protein, responsible for lysing host cells and viral egress. We surmise that there is a fine balance between over- and underexpression of lysis that leads to this pattern of epistasis. To recap, we have developed an approach for joint inference of the mutation rate and selection parameters from full haplotype data with sequencing errors and used it to reveal features governing MS2 evolution.

Deciphering microbial gene function using natural language processing.

Revealing the function of uncharacterized genes is a fundamental challenge in an era of ever-increasing volumes of sequencing data. Here, we present a concept for tackling this challenge using deep learning methodologies adopted from natural language processing (NLP). We repurpose NLP algorithms to model "gene semantics" based on a biological corpus of more than 360 million microbial genes within their genomic context. We use the language models to predict functional categories for 56,617 genes and find that out of 1369 genes associated with recently discovered defense systems, 98% are inferred correctly. We then systematically evaluate the "discovery potential" of different functional categories, pinpointing those with the most genes yet to be characterized. Finally, we demonstrate our method's ability to discover systems associated with microbial interaction and defense. Our results highlight that combining microbial genomics and language models is a promising avenue for revealing gene functions in microbes.