Virus Metagenomics in Farm Animals: A Systematic Review

A majority of emerging infectious diseases are of zoonotic origin. Metagenomic Next-Generation Sequencing (mNGS) has been employed to identify uncommon and novel infectious etiologies and characterize virus diversity in human, animal, and environmental samples. Here, we systematically reviewed studies that performed viral mNGS in common livestock (cattle, small ruminants, poultry, and pigs). We identified 2481 records and 120 records were ultimately included after a first and second screening. Pigs were the most frequently studied livestock and the virus diversity found in samples from poultry was the highest. Known animal viruses, zoonotic viruses, and novel viruses were reported in available literature, demonstrating the capacity of mNGS to identify both known and novel viruses. However, the coverage of metagenomic studies was patchy, with few data on the virome of small ruminants and respiratory virome of studied livestock. Essential metadata such as age of livestock and farm types were rarely mentioned in available literature, and only 10.8% of the datasets were publicly available. Developing a deeper understanding of livestock virome is crucial for detection of potential zoonotic and animal pathogens and One Health preparedness. Metagenomic studies can provide this background but only when combined with essential metadata and following the "FAIR" (Findable, Accessible, Interoperable, and Reusable) data principles

The Utility of Data Transformation for Alignment, De Novo Assembly and Classification of Short Read Virus Sequences.

Advances in DNA sequencing technology are facilitating genomic analyses of unprecedented scope and scale, widening the gap between our abilities to generate and fully exploit biological sequence data. Comparable analytical challenges are encountered in other data-intensive fields involving sequential data, such as signal processing, in which dimensionality reduction (i.e., compression) methods are routinely used to lessen the computational burden of analyses. In this work, we explored the application of dimensionality reduction methods to numerically represent high-throughput sequence data for three important biological applications of virus sequence data: reference-based mapping, short sequence classification and de novo assembly. Leveraging highly compressed sequence transformations to accelerate sequence comparison, our approach yielded comparable accuracy to existing approaches, further demonstrating its suitability for sequences originating from diverse virus populations. We assessed the application of our methodology using both synthetic and real viral pathogen sequences. Our results show that the use of highly compressed sequence approximations can provide accurate results, with analytical performance retained and even enhanced through appropriate dimensionality reduction of sequence data

Genome sequence of a Minacovirus strain from a farmed mink in The Netherlands

We report the genome sequence of a Minacovirus strain identified from a fecal sample from a farmed mink (Neovison vison) in The Netherlands that was tested negative for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using real-time PCR (RT-PCR). The viral genome sequence was obtained using agnostic deep sequencing

Near-Complete Genome Sequences of Eight Human Astroviruses Recovered from Diarrheal Stool Samples of Hospitalized Children in Coastal Kenya in 2019.

Here, using a sequence-independent sequencing approach (M. V. Phan, P. Hong Anh, N. Van Cuong, B. Oude Munnink, et al., Virus Evol 2:vew027, 2016, https://doi.org/10.1093/ve/vew027), we determined human astrovirus (HAstV) genome sequences from eight diarrheal stool samples collected in coastal Kenya in 2019. Phylogenetic analysis identified the following 4 genotypes: HAstV-1 (n = 4), HAstV-2 (n = 1), HAstV-3 (n = 1), and HAstV-5 (n = 2)

Complete genome sequences of dengue virus type 2 strains from Kilifi, Kenya

Dengue infection remains poorly characterized in Africa and little is known regarding its associated viral genetic diversity. Here, we report dengue virus type 2 (DENV-2) sequence data from 10 clinical samples, including 5 complete genome sequences of the cosmopolitan genotype, obtained from febrile adults seeking outpatient care in coastal Kenya

Identification of missed respiratory viruses by metagenomic sequencing of clinical respiratory samples from Kenya

Pneumonia remains a major cause of mortality and morbidity. Most molecular diagnoses of viruses rely on polymerase chain reaction (PCR) assays that however can fail due to primer mismatch. We investigated the performance of routine virus diagnostics in Kilifi, Kenya, using random-primed viral next generation sequencing (viral NGS) on respiratory samples which tested negative for the common viral respiratory pathogens by a local standard diagnostic panel. Among 95 hospitalised pneumonia patients and 95 household-cohort individuals, analysis of viral NGS identified at least one respiratory-associated virus in 35 (37%) and 23 (24%) samples, respectively. The majority (66%; 42/64) belonged to the Picornaviridae family. The NGS data analysis identified a number of viruses that were missed by the diagnostic panel (rhinovirus, human metapneumovirus, respiratory syncytial virus and parainfluenza virus), and these failures could be attributed to PCR primer/probe binding site mismatches. Unexpected viruses identified included parvovirus B19, enterovirus D68, coxsackievirus A16 and A24 and rubella virus. The regular application of such viral NGS could help evaluate assay performance, identify molecular causes of missed diagnoses and reveal gaps in the respiratory virus set used for local screening assays. The results can provide actionable information to improve the local pneumonia diagnostics and reveal locally important viral pathogens

Mapping for engagement: setting up a community based participatory research project to reach underserved communities at risk for Hepatitis C in Ho Chi Minh City, Vietnam

Background: Approximately 1. 07 million people in Vietnam are infected with hepatitis C virus (HCV). To address this epidemic, the South East Asian Research Collaborative in Hepatitis (SEARCH) launched a 600-patient cohort study and two clinical trials, both investigating shortened treatment strategies for chronic HCV infection with direct-acting antiviral drugs. We conducted ethnographic research with a subset of trial participants and found that the majority were aware of HCV infection and its implications and were motivated to seek treatment. However, people who inject drugs (PWID), and other groups at risk for HCV were under-represented, although injecting drug use is associated with high rates of HCV. Material and Methods: We designed a community-based participatory research (CBPR) study to engage in dialogues surrounding HCV and other community-prioritized health issues with underserved groups at risk for HCV in Ho Chi Minh City. The project consists of three phases: situation analysis, CBPR implementation, and dissemination. In this paper, we describe the results of the first phase (i.e., the situation analysis) in which we conducted desk research and organized stakeholder mapping meetings with representatives from local non-government and community-based organizations where we used participatory research methods to identify and analyze key stakeholders working with underserved populations. Results: Twenty six institutions or groups working with the key underserved populations were identified. Insights about the challenges and dynamics of underserved communities were also gathered. Two working groups made up of representatives from the NGO and CBO level were formed. Discussion: Using the information provided by local key stakeholders to shape the project has helped us to build solid relationships, give the groups a sense of ownership from the early stages, and made the project more context specific. These steps are not only important preliminary steps for participatory studies but also for other research that takes place within the communities

Establishing farm dust as a useful viral metagenomic surveillance matrix

Farm animals may harbor viral pathogens, some with zoonotic potential which can possibly cause severe clinical outcomes in animals and humans. Documenting the viral content of dust may provide information on the potential sources and movement of viruses. Here, we describe a dust sequencing strategy that provides detailed viral sequence characterization from farm dust samples and use this method to document the virus communities from chicken farm dust samples and paired feces collected from the same broiler farms in the Netherlands. From the sequencing data, Parvoviridae and Picornaviridae were the most frequently found virus families, detected in 85-100% of all fecal and dust samples with a large genomic diversity identified from the Picornaviridae. Sequences from the Caliciviridae and Astroviridae familes were also obtained. This study provides a unique characterization of virus communities in farmed chickens and paired farm dust samples and our sequencing methodology enabled the recovery of viral genome sequences from farm dust, providing important tracking details for virus movement between livestock animals and their farm environment. This study serves as a proof of concept supporting dust sampling to be used in viral metagenomic surveillance

Norovirus outbreak in a natural playground: A One Health approach

Norovirus constitutes the most frequently identified infectious cause of disease outbreaks associated with untreated recreational water. When investigating outbreaks related to surface water, a One Health approach is insightful. Historically, there has been a focus on potential contamination of recreational water by bird droppings and a recent publication demonstrating human noroviruses in bird faeces suggested this should be investigated in future water-related norovirus outbreaks. Here, we describe a One Health approach investigating a norovirus outbreak in a natural playground. On social media, a large amount of waterfowl were reported to defecate near these playground premises leading to speculations about their potential involvement. Surface water, as well as human and bird faecal specimens, was tested for human noroviruses. Norovirus was found to be the most likely cause of the outbreak but there was no evidence for transmission via waterfowl. Cases had become known on social media prior to notification to the public health service underscoring the potential of online media as an early warning system. In view of known risk factors, advice was given for future outbreak investigations and natural playgroun