Hepatitis E virus (HEV) is the most common cause of acute viral hepatitis globally. HEV comprises four genotypes with different geographic distributions and host ranges. We utilize this natural case-control study for investigating the evolution of zoonotic viruses compared to single-host viruses, using 244 near-full-length HEV genomes. Genome-wide estimates of the ratio of nonsynonymous to synonymous evolutionary changes (dN/dS ratio) located a region of overlapping reading frames, which is subject to positive selection in genotypes 3 and 4. The open reading frames (ORFs) involved have functions related to host-pathogen interaction, so genotype-specific evolution of these regions may reflect their fitness. Bayesian inference of evolutionary rates shows that genotypes 3 and 4 have significantly higher rates than genotype 1 across all ORFs. Reconstruction of the phylogenies of zoonotic genotypes demonstrates significant intermingling of isolates between hosts. We speculate that the genotype-specific differences may result from cyclical adaptation to different hosts in genotypes 3 and 4.IMPORTANCE Hepatitis E virus (HEV) is increasingly recognized as a pathogen that affects both the developing and the developed world. While most often clinically mild, HEV can be severe or fatal in certain demographics, such as expectant mothers. Like many other viral pathogens, HEV has been classified into several distinct genotypes. We show that most of the HEV genome is evolutionarily constrained. One locus of positive selection is unusual in that it encodes two distinct protein products. We are the first to detect positive selection in this overlap region. Genotype 1, which infects humans only, appears to be evolving differently from genotypes 3 and 4, which infect multiple species, possibly because genotypes 3 and 4 are unable to achieve the same fitness due to repeated host jumps. KEYWORDS evolution, evolutionary biology, genotypic identification, hepatitis E virus, positive selection H epatitis E virus (HEV) is a nonenveloped single-stranded positive-sense RNA virus that infects approximately 20 million people globally each year (1). It causes large propagated epidemics of acute hepatitis in Asia and Africa, as well as low-level, sporadic, food-associated infections in the developed world (2, 3). Its pathogenicity ranges from acute liver failure and mortality rates as high as 20% in some subpopulations (for example, in pregnant women) to apparently asymptomatic infections in others (4). Acquired via the fecal-oral route, HEV is associated with poor hygiene and living conditions. It can also be acquired by eating contaminated food, including infected artiodactyls (swine, deer, and boar) and shellfish (4-6).Mammalian HEV exists in four internationally recognized genotypes (7). Genotyping is based on nucleotide divergence in the capsid open reading frame (ORF) (8) and on whole-genome phylogenetic analysis (9). Genotypes differ at the epidemiological (distribution, hosts) and virological (pathogenicity, translation mecha...
Background Dengue virus (DENV) infects hundreds of thousands of people annually in Indonesia. However, DENV sequence data from the country are limited, as samples from outbreaks must be shipped across long-distances to suitably equipped laboratories to be sequenced. This approach is time-consuming, expensive, and frequently results in failure due to low viral load or degradation of the RNA genome. Methods We evaluated a method designed to address this challenge, using the ‘Primal Scheme’ multiplex PCR tiling approach to rapidly generate short, overlapping amplicons covering the complete DENV coding-region, and sequencing the amplicons on the portable Nanopore MinION device. The resulting sequence data was assessed in terms of genome coverage, consensus sequence accuracy and by phylogenetic analysis. Results The multiplex approach proved capable of producing near complete coding-region coverage from all samples tested ($$ \overline{x} $$x¯ = 99.96%, n = 18), 61% of which could not be fully amplified using the current, long-amplicon PCR, approach. Nanopore-generated consensus sequences were found to be between 99.17–99.92% identical to those produced by high-coverage Illumina sequencing. Consensus accuracy could be improved by masking regions below 20X coverage depth (99.69–99.92%). However, coding-region coverage was reduced at this depth ($$ \overline{x} $$x¯ = 93.48%). Nanopore and Illumina consensus sequences generated from the same samples formed monophyletic clades on phylogenetic analysis, and Indonesian consensus sequences accurately clustered by geographical origin. Conclusion The multiplex, short-amplicon approach proved superior for amplifying DENV genomes from clinical samples, particularly when the virus was present at low concentrations. The accuracy of Nanopore-generated consensus sequences from these amplicons was sufficient for identifying the geographic origin of the samples, demonstrating that the approach can be a useful tool for identifying and monitoring DENV clades circulating in low-resource settings across Indonesia. However, the inaccuracies in Nanopore-generated consensus sequences mean that the approach may not be appropriate for higher resolution transmission studies, particularly when more accurate sequencing technologies are available.
Human immunodeficiency virus type 1 (HIV-1) is the result of cross-species transmission of simian immunodeficiency virus from chimpanzees (SIVcpz). SIVcpz is a chimeric virus which shares common ancestors with viruses infecting red-capped mangabeys and a subset of guenon species. The epidemiology of SIV infection in hominoids is characterized by low prevalences and an uneven geographic distribution. Surveys in Cameroon indicated that two closely related members of the guenon species subset, mustached guenons and greater spot-nosed guenons, infected with SIVmus and SIVgsn, respectively, also have low rates of SIV infections in their populations. Compared to that for other monkeys, including red-capped mangabeys and closely related guenon species, such an epidemiology is unusual. By intensifying sampling of geographically distinct populations of mustached and greater spot-nosed guenons in Gabon and including large sample sets of mona guenons from Cameroon, we add strong support to the hypothesis that the paucity of SIV infections in wild populations is a general feature of this monophyletic group of viruses. Furthermore, comparative phylogenetic analysis reveals that this phenotype is a feature of this group of viruses infecting phylogenetically disparate hosts, suggesting that this epidemiological phenotype results from infection with these HIV-1-related viruses rather than from a common host factor. Thus, these HIV-1-related viruses, i.e., SIVcpz and the guenon viruses which share an ancestor with part of the SIVcpz genome, have an epidemiology distinct from that found for SIVs in other African primate species.IMPORTANCE Stable virus-host relationships are established over multiple generations. The prevalence of viral infections in any given host is determined by various factors. Stable virus-host relationships of viruses that are able to cause persistent infections and exist with high incidences of infection are generally characterized by a lack of morbidity prior to host reproduction. Such is the case for cytomegalovirus (CMV) and Epstein-Barr virus (EBV) infections of humans. SIV infections of most African primate species also satisfy these criteria, with these infections found at a high prevalence and with rare cases of clinical disease. In contrast, SIVcpz, the ancestor of HIV-1, has a different epidemiology, and it has been reported that infected animals suffer from an AIDS-like disease in the wild. Here we conclusively demonstrate that viruses which are closely related to SIVcpz and infect a subset of guenon monkeys show an epidemiology resembling that of SIVcpz.
Syndromic surveillance, the collection of symptom data from individuals prior to or in the absence of diagnosis, is used throughout the developed world to provide rapid indications of outbreaks and unusual patterns of disease. However, the low cost of syndromic surveillance also makes it highly attractive for the developing world. We present a case study of electronic participatory syndromic surveillance, using participant-mobile phones in a rural region of Western Uganda, which has a high infectious disease burden, and frequent local and regional outbreaks. Our platform uses text messages to encode a suite of symptoms, their associated durations, and household disease burden, and we explore the ability of participants to correctly encode their symptoms, with an average of 75.2% of symptom reports correctly formatted between the second and 11th reporting timeslots. Concomitantly we identify divisions between participants able to rapidly adjust to this unusually participatory style of data collection, and those few for whom the study proved more challenging. We then perform analyses of the resulting syndromic time series, examining the clustering of symptoms by time and household to identify patterns such as a tendency towards the within-household sharing of respiratory illness.
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