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A strategy to estimate unknown viral diversity in mammals.

ABSTRACT: UNLABELLED:The majority of emerging zoonoses originate in wildlife, and many are caused by viruses. However, there are no rigorous estimates of total viral diversity (here termed "virodiversity") for any wildlife species, despite the utility of this to future surveillance and control of emerging zoonoses. In this case study, we repeatedly sampled a mammalian wildlife host known to harbor emerging zoonotic pathogens (the Indian Flying Fox, Pteropus giganteus) and used PCR with degenerate viral family-level primers to discover and analyze the occurrence patterns of 55 viruses from nine viral families. We then adapted statistical techniques used to estimate biodiversity in vertebrates and plants and estimated the total viral richness of these nine families in P. giganteus to be 58 viruses. Our analyses demonstrate proof-of-concept of a strategy for estimating viral richness and provide the first statistically supported estimate of the number of undiscovered viruses in a mammalian host. We used a simple extrapolation to estimate that there are a minimum of 320,000 mammalian viruses awaiting discovery within these nine families, assuming all species harbor a similar number of viruses, with minimal turnover between host species. We estimate the cost of discovering these viruses to be ~$6.3 billion (or ~$1.4 billion for 85% of the total diversity), which if annualized over a 10-year study time frame would represent a small fraction of the cost of many pandemic zoonoses. IMPORTANCE:Recent years have seen a dramatic increase in viral discovery efforts. However, most lack rigorous systematic design, which limits our ability to understand viral diversity and its ecological drivers and reduces their value to public health intervention. Here, we present a new framework for the discovery of novel viruses in wildlife and use it to make the first-ever estimate of the number of viruses that exist in a mammalian host. As pathogens continue to emerge from wildlife, this estimate allows us to put preliminary bounds around the potential size of the total zoonotic pool and facilitates a better understanding of where best to allocate resources for the subsequent discovery of global viral diversity.

SUBMITTER: Anthony SJ

PROVIDER: S-EPMC3760253 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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A strategy to estimate unknown viral diversity in mammals.

Anthony Simon J SJ Epstein Jonathan H JH Murray Kris A KA Navarrete-Macias Isamara I Zambrana-Torrelio Carlos M CM Solovyov Alexander A Ojeda-Flores Rafael R Arrigo Nicole C NC Islam Ariful A Ali Khan Shahneaz S Hosseini Parviez P Bogich Tiffany L TL Olival Kevin J KJ Sanchez-Leon Maria D MD Karesh William B WB Goldstein Tracey T Luby Stephen P SP Morse Stephen S SS Mazet Jonna A K JA Daszak Peter P Lipkin W Ian WI

mBio 20130903 5

<h4>Unlabelled</h4>The majority of emerging zoonoses originate in wildlife, and many are caused by viruses. However, there are no rigorous estimates of total viral diversity (here termed "virodiversity") for any wildlife species, despite the utility of this to future surveillance and control of emerging zoonoses. In this case study, we repeatedly sampled a mammalian wildlife host known to harbor emerging zoonotic pathogens (the Indian Flying Fox, Pteropus giganteus) and used PCR with degenerate ...[more]

PMID: 24003179

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Project description:Robust policy decisions regarding the protection and management of terrestrial mammals require knowledge of where species are and in what numbers. The last comprehensive review, presenting absolute estimates at a national scale, was published nearly 20 years ago and was largely based on expert opinion. We investigated and propose a systematic data driven approach combing publically available occurrence data with published density estimates to predict species distribution maps and derive total abundance figures for all terrestrial mammals inhabiting Britain. Our findings suggest that the methodology has potential; generally producing plausible predictions consistent with existing information. However, inconsistencies in the availability and recording of data impact the certainty of this output limiting its current application for policy. Restrictions on access and use of occurrence data at a local level produces "data deserts" for which models cannot compensate. This leads to gaps in spatial distribution of species and consequently underestimates abundance. For many species the limited number of geo-referenced densities hampered the extrapolation from habitat suitability to absolute abundance. Even for well-studied species, further density estimates are required. Many density estimates used were pre-1995 and therefore the derived abundance should not be considered a current estimate. To maximise a systematic approach in the future we make the following recommendations: To mitigate the attitudes of a minority of local data providers occurrence records must be submitted to national surveys such as the Mammal Society's Mammal Tracker.Studies are required to estimate density for common species and in areas of low or no abundance.To ensure such studies can be collated and used efficiently we propose a standardised approach reporting density estimates based on the 1km resolution British National Grid, or habitat representative of the 1km square, with digital maps to accompany publications.

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A strategy to estimate unknown viral diversity in mammals.

Publications

A strategy to estimate unknown viral diversity in mammals.

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