Overview of Virus Metagenomic Classification Methods and Their Biological Applications

Nooij, Sam; Schmitz, Dennis; Vennema, Harry; Kroneman, Annelies; Koopmans, Marion

doi:10.3389/fmicb.2018.00749

Cited by 113 publications

(94 citation statements)

References 102 publications

(118 reference statements)

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“…In the longer term, a better understanding of the association between farm types and virome composition of farm animals would guide farm management practices for reducing risks from zoonoses. In the meantime, it is important to benchmark metagenomic tools and reference databases [147,148] and assess epidemic potential of pathogens for more accurate zoonoses prediction and detection [149].…”

Section: Discussionmentioning

confidence: 99%

Virus Metagenomics in Farm Animals: A Systematic Review

Kwok

Nieuwenhuijse

Phan

et al. 2020

Viruses

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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.Viruses 2020, 12, 107 2 of 22 flocks and wild birds, suggesting that pre-existing biosecurity measurements could not keep up with the rate of livestock intensification [16]. In 2007-2010, a large-scale Q fever outbreak was reported in the Netherlands, affecting more than 3500 human cases and resulting in a huge economic loss [17,18]. A steep increase in the number of goat farms most likely was the driver for the increased prevalence of Coxiella burnetii infections, with animal abortion waves that had gone unnoticed. The policy of voluntary reporting abortion outbreaks to the Animal Health Service hindered the timely detection of the circulation of Q fever, and therefore early interventions. These examples indicate that zoonotic risks in the livestock industry should be carefully managed and adapted to livestock intensification. The One Health approach has been coined for advocating collaboration between multiple stakeholders including veterinarians, clinicians, epidemiologists, virologists, microbiologists, ecologists, and policy makers to prevent and control EIDs through the human-animal-environment interface [19]. Surveillance of livestock and the surrounding environment is a hallmark of early detection but is currently targeted to known risks.Advances in Next-Generation Sequencing (NGS) technologies and rapid development of bioinformatics and computational tools offer new opportunities for EID surveillance in quality and in scale. Particularly, metagenomic NGS (mNGS) allows unbiased detection of all microbes and viruses in a sample, showing potential for timely detection of rare or novel infectio...

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Section: Discussionmentioning

confidence: 99%

Virus Metagenomics in Farm Animals: A Systematic Review

Kwok

Nieuwenhuijse

Phan

et al. 2020

Viruses

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“…The lack of a viable 'meta-barcoding' sequence means that virus discovery often takes a full metagenomic approach, sequencing total (or virus-enriched) nucleic acid, and subsequently assigning sequences through inferred homology (e.g. Rose et al 2016;Paez-Espino et al 2017;Nooij et al 2018). This is challenging, because high divergence means that only the most conserved sequences are recognisable (e.g.…”

Section: Potential Pitfallsmentioning

confidence: 99%

“…Sensitive surveys therefore benefit from assembled contigs rather than raw reads (so that divergent genes are linked to recognisable ones) and protein rather than nucleic-acid similarity searches (because divergence is high). This can be done using off-the-shelf assemblers and search algorithms such as SPADes (Bankevich et al 2012) or Trinity (Grabherr et al 2011), andDiamond (Buchfink et al 2014), but there is also a growing ecosystem of virusspecific metagenomic packages and pipelines available (Nooij et al 2018).…”

Section: Potential Pitfallsmentioning

confidence: 99%

Expansion of the Metazoan Virosphere: Progress, Pitfalls, and Prospects

Obbard

2018

Preprint

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Metagenomic sequencing has led to a recent and rapid expansion in the animal virome. It has uncovered a multitude of new virus lineages from under-sampled host lineages, including many that break up long branches among previously known clades, and many with genomes that display unexpected sizes and structures. Although there are challenges to inferring the existence of a virus from a viruslike sequence, the analysis of nucleic acid (including small RNAs) and sequence data can give us considerable confidence in the absence of an isolate. As a consequence, this period of 'molecular natural history' is helping to reshape our views of deep virus evolution. Nevertheless, there is a limit to what metagenomic discovery alone can tell us, and some open questions will require experimental isolates.

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“…Ranges of bioinformatics tools facilitate data analysis, e.g., Kraken [75], Kaiju [76], VirusFinder [77]. Different workflows have recently been benchmarked and comprehensively overviewed elsewhere [78][79][80].…”

Section: Problems Of Metagenomic Approachmentioning

confidence: 99%

Current Trends in Diagnostics of Viral Infections of Unknown Etiology

Kiselev

Matsvay

Абрамов

et al. 2020

Viruses

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Viruses are evolving at an alarming rate, spreading and inconspicuously adapting to cutting-edge therapies. Therefore, the search for rapid, informative and reliable diagnostic methods is becoming urgent as ever. Conventional clinical tests (PCR, serology, etc.) are being continually optimized, yet provide very limited data. Could high throughput sequencing (HTS) become the future gold standard in molecular diagnostics of viral infections? Compared to conventional clinical tests, HTS is universal and more precise at profiling pathogens. Nevertheless, it has not yet been widely accepted as a diagnostic tool, owing primarily to its high cost and the complexity of sample preparation and data analysis. Those obstacles must be tackled to integrate HTS into daily clinical practice. For this, three objectives are to be achieved: (1) designing and assessing universal protocols for library preparation, (2) assembling purpose-specific pipelines, and (3) building computational infrastructure to suit the needs and financial abilities of modern healthcare centers. Data harvested with HTS could not only augment diagnostics and help to choose the correct therapy, but also facilitate research in epidemiology, genetics and virology. This information, in turn, could significantly aid clinicians in battling viral infections.

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Overview of Virus Metagenomic Classification Methods and Their Biological Applications

Cited by 113 publications

References 102 publications

Virus Metagenomics in Farm Animals: A Systematic Review

Virus Metagenomics in Farm Animals: A Systematic Review

Expansion of the Metazoan Virosphere: Progress, Pitfalls, and Prospects

Current Trends in Diagnostics of Viral Infections of Unknown Etiology

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