No Exchange of Picornaviruses in Vietnam Between Humans and Animals in a High-Risk Cohort with Close Contact Despite High Prevalence and Diversity
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viruses Article No Exchange of Picornaviruses in Vietnam between Humans and Animals in a High-Risk Cohort with Close Contact despite High Prevalence and Diversity Lu Lu 1,*,† , Jordan Ashworth 1,† , Dung Nguyen 2, Kejin Li 3, Donald B. Smith 2,3, Mark Woolhouse 1 and on behalf of the VIZIONS Consortium ‡ 1 Usher Institute, University of Edinburgh, Edinburgh EH9 3FL, UK; [email protected] (J.A.); [email protected] (M.W.) 2 Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, UK; [email protected] (D.N.); [email protected] (D.B.S.) 3 Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK; [email protected] * Correspondence: [email protected] † The two authors contributed equally to this work. ‡ Membership of the VIZIONS Consortium is provided in the Acknowledgments. Abstract: Hospital-based and community-based ‘high-risk cohort’ studies investigating humans at risk of zoonotic infection due to occupational or residential exposure to animals were conducted in Vietnam, with diverse viruses identified from faecal samples collected from humans, domestic and wild animals. In this study, we focus on the positive-sense RNA virus family Picornaviridae, investi- gating the prevalence, diversity, and potential for cross-species transmission. Through metagenomic Citation: Lu, L.; Ashworth, J.; sequencing, we found picornavirus contigs in 23% of samples, belonging to 15 picornavirus genera. Nguyen, D.; Li, K.; Smith, D.B.; Prevalence was highest in bats (67%) while diversity was highest in rats (nine genera). In addition, Woolhouse, M.; on behalf of the VIZIONS Consortium. No Exchange 22% of the contigs were derived from novel viruses: Twelve phylogenetically distinct clusters were of Picornaviruses in Vietnam between observed in rats of which seven belong to novel species or types in the genera Hunnivirus, Parechovirus, Humans and Animals in a High-Risk Cardiovirus, Mosavirus and Mupivirus; four distinct clusters were found in bats, belonging to one Cohort with Close Contact despite novel parechovirus species and one related to an unclassified picornavirus. There was no evidence High Prevalence and Diversity. for zoonotic transmission in our data. Our study provides an improved knowledge of the diversity Viruses 2021, 13, 1709. https:// and prevalence of picornaviruses, including a variety of novel picornaviruses in rats and bats. We doi.org/10.3390/v13091709 highlight the importance of monitoring the human–animal interface for possible spill-over events. Academic Editor: Caroline Tapparel Keywords: picornavirus; animal–human interface; metagenomic sequencing; rats; bats Received: 13 July 2021 Accepted: 23 August 2021 Published: 27 August 2021 1. Introduction Publisher’s Note: MDPI stays neutral Viruses of zoonotic origin are a significant public health concern worldwide having with regard to jurisdictional claims in given rise to a number of high-profile health emergencies. Examples of diseases which published maps and institutional affil- are known or presumed to have been transmitted from animals to humans include avian iations. influenza A virus, MERS and SARS-CoV-2 [1,2]. Direct or indirect contact between humans and animals is essential for a successful cross-species transmission [3]. The incidence of zoonotic disease is likely to be higher in regions where there is frequent contact between humans and animals. The multidisciplinary surveillance program Vietnam Initiative on Zoonotic InfectIONS Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. (VIZIONS) project was conducted to explore the zoonotic potential of viruses across This article is an open access article different rural sites in Vietnam [4]. Studies focussed on small-scale farmers who house distributed under the terms and several different animal species within a small area with minimum biosecurity and may conditions of the Creative Commons also eat wild animals or be involved in commercial wildlife farming, processing, or selling. Attribution (CC BY) license (https:// Such activities increase the likelihood of pathogen transfer between wildlife, humans, creativecommons.org/licenses/by/ and domestic animals. Another component of VIZIONS was hospital-based surveillance. 4.0/). Metagenomic sequencing was used to identify viruses in samples collected from 2012 to Viruses 2021, 13, 1709. https://doi.org/10.3390/v13091709 https://www.mdpi.com/journal/viruses Viruses 2021, 13, 1709 2 of 15 2016 from humans who presented with enteric disease and potential zoonotic contacts, these being both domestic and wild animals. Subsequent phylogenetic analysis was used to investigate the viruses identified in these samples, including their spatial and temporal spread through human and animal populations and the inference of any zoonotic transmission events. Picornaviruses are non-enveloped viruses with a positive-sense single-stranded RNA genome of 6.7–10.1 kb containing a single long open reading frame (ORF) [5]. Picor- naviruses are globally distributed and infect vertebrates of all classes [6]. Sixty-eight genera and 158 species are currently recognised by the ICTV [5]. Of these, members of nine genera and 24 species are known to be human-infective [7]. Previous VIZIONS studies have reported a variety of novel picornaviruses in both humans and animals, including diverse members of the species Enterovirus G types in domestic pigs and farmed wild boar [8], and of the genus Kobuvirus in rodents and bats [9]. However, there may still be novel and unknown picornaviruses present in animals, whose existence may increase the scope for further transmission events between humans and animals, where there is close contact. These transmission events have the potential to become the origin of emerging infectious diseases. The aims of this VIZIONS study were to describe the prevalence and genetic diversity of picornaviruses present in wide range of hosts at the animal–human interface; to identify novel picornaviruses circulating in animals and humans and to explore possible animal sources of picornavirus infections in humans. 2. Materials and Methods 2.1. Samples For the study, 2100 faecal samples collected from human and non-humans in Vietnam between year 2012 and 2016 were subjected to a viral diagnostic algorithm and put through a next generation sequencing (NGS) process [4,10]. Of these, 1258 samples were obtained from human subjects: 707 samples were collected from patients admitted to hospital with diarrhoea and 551 samples were obtained from a high-risk cohort in Dong Thap province (farm households, animal health workers, abattoir workers, poultry slaughterers, rat traders). In parallel, 842 samples were obtained from a variety of non-human animals in Dong Thap including: rats which were farmed or traded in the live markets (n = 315) and 93% were from rat species Rattus argentiventer (commonly known as ricefield rat and is a species of rat found throughout Southeast Asia); bats whose faeces were collected from roosting sites for trading (n = 179); domestic pigs (n = 270) and farmed wild boar (n = 15). A smaller number of samples were collected from domestic dogs (n = 45), cats (n = 13), monkeys (n = 3) and goats (n = 2). Information on host species, sampling date, location and other attributes is available for all samples [11]. 2.2. Metagenomic Analysis Reads from 2100 metagenomics samples had adapters and low-quality bases removed using Cutadapt [12]. Reads which mapped, when queried against a custom database consisting of human, pig, rat and several hundred representative bacterial genomes us- ing KRAKEN, were removed [13]. Remaining reads were assembled into contigs using MetaSPAdes [14]. Each of the 2100 samples were assembled individually using the default parameters. Contigs <700 nucleotides were removed. Remaining contigs were queried against a custom viral protein database containing all protein sequences available on Gen- Bank as of 5 May 2021 that had the Picornaviridae taxonomic ID (NCBI: txid12058) using the DIAMOND BLASTX ultra-sensitive algorithm [15]. An e-value cut-off of <=10 × 10−50 and an alignment cut-off of >=500 amino acids were applied for hits to be categorised as positive. Contigs with positive hits were annotated using Geneious Prime 2021.1.1 (https://www.geneious.com, accessed on 2 April 2021). Viruses 2021, 13, 1709 3 of 15 2.3. Genomic and Phylogenetic Analysis Nucleotide sequences of genomes and amino acid sequences of open reading frames (ORFs) were aligned with the reference sequences downloaded from ICTV and NCBI database using MAFFT [16]. The best substitution model was evaluated using the Model Selection package. Maximum-likelihood trees were generated with 1000 bootstrap repli- cates with IQTREE [17]. Time-scaled phylogenies for the VP1 gene were generated using the Bayesian Monte Carlo Markov Chain (MCMC) method implemented in BEAST v.1.10 [18]. The combinations of substitution models, clock models, and population size models were evaluated by stepping-stone methods: a SRD06 nucleotide substitution with uncorrelated lognormal relaxed molecular clocks and a constant-population coalescent process prior. Priors of substitution rate were chosen according to published evolution rates from related genera in the family Picornaviridae [8], using the mean rate of 2 × 10−3 sub/site/year with SD = 1 × 10−3. MCMC chains were run for 100 million steps, sampled every 10,000 states with 10% burn-in. MCMC convergence and effective sample size of parameter estimates were evaluated using Tracer 1.7 (http://beast.bio.ed.ac.uk, accessed on: 24 May 2021). Maximum clade credibility (MCC) trees were summarized using Tree Annotator and visualized using FigTree v1.4.4 (http://tree.bio.ed.ac.uk/software/figtree/, accessed on: 1 June 2021). The overall rates of evolutionary change (ns/s/y, nucleotide substitutions per site per year) and tree root ages were estimated simultaneously. The pairwise amino acid (aa) and nucleotide (nt) identities were calculated using Geneious Prime 2020.1.1.1 (https://www.geneious.com, accessed on 15 June 2021). The genetic scan of complete polyprotein coding sequences was using simplot in R (v.3.6.1).