A study posted on the bioRxiv* preprint server characterized the total virome of game animals from five mammalian orders using the total RNA sequencing technique. Of the 71 mammalian species discovered, the study found 18 had a potential risk to humans.
Study: Total virome characterizations of game animals in China reveals a spectrum of emerging viral pathogens. Image Credit: teekayu/ Shutterstock
Along with finding human viruses in these animals, interestingly, the researchers from the study identified an alphacoronavirus species jump from bats to civets. They also detected the H9N2 influenza virus in a civet and an Asian badger.
These data highlight the importance of game animals as potential drivers of disease emergence. The study reports that many of the species were investigated for the first time using the metagenomic framework.
In the context of the ongoing coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome virus (SARS-CoV-2), and the previous viral epidemics caused by the influenza virus, SARS-CoV, and Middle East Respiratory Coronavirus (MERS-CoV), scientists are researching further into the zoonotic origin of human pathogens and cross-species jumping.
Game animals, wildlife or semi-wild species traded and consumed as exotic food in China and other Asian countries are potential reservoirs for viruses, such as SARS-CoV and SARS-CoV-2. They include rodents (porcupines, bamboo rats, and marmots), carnivores (civets, badgers, and foxes), pangolins, hedgehogs, and rabbits.
Live animal or wet markets where these animals are brought in for trading have expanded in commercial wildlife farming operations and for their species diversity. Because of the poor hygiene conditions and close contact between animals and humans, these markets make an ideal breeding ground for emerging infectious diseases.
Several infectious disease outbreaks are linked to these markets. Cases of both SARS-CoV and SARS-CoV-2 were identified in these markets, and the related species were also found in civets, raccoon dogs, and pangolins.
In this context, it is important to identify existing and potential human pathogens in game animals. This will help trace the origin of epidemics and provide a risk assessment of likely future outbreaks.
Using techniques such as consensus PCR and Sanger sequencing approaches on isolated viruses and metagenomic next-generation sequencing (mNGS), scientists have recently discovered several human infectious pathogens from animals. However, such systematic investigations are few, especially in China, where wet markets are prominent.
Because of the little investigations done on game animals for their virome, the researchers in the present study performed a systematic meta-transcriptomic (i.e., total RNA sequencing) virome investigation of 16 species of game animals representing five mammalian orders sampled across China. The researchers attempt to assess which species have the greatest potential for carrying viruses that could eventually emerge in human populations.
In this study, the researchers collected samples from 1725 game animals from 16 species commonly consumed as exotic food throughout China between 2017 and 2021. They collected most of the animal samples after 2020, which is concurrent with the COVID-19 pandemic.
These species represented five mammalian orders: Rodentia, Pholidota, Carnivora, Eulipotyphla, and Lagomorpha, including civets (P. larvata) that have been implicated in the emergence of SARS-CoV. These animals were obtained from artificial breeding sites that supply animal markets and zoos, and natural habitats.
The researchers collected respiratory and fecal samples from across 19 provinces in China. Subsequently, they organized them into 181 pools according to species, location, health, and feeding (living) conditions for RNA extraction and library construction – the meta-transcriptomic sequencing. They reported that this process yielded 172.36 billion nucleotide bases of sequence reads for virus discovery and characterization.
They preliminarily identified the viruses, specifically vertebrate-specific viruses and vector-borne vertebrate viruses, based on the taxonomic lineage information of the blastx results and then confirmed them by phylogenetic analyses.
The researchers identified a wide diversity of virus species (both previously described and novel). Interestingly, they did not find any SARS-CoV-like or SARS-CoV-2-like sequences, even in Malayan pangolins. This is because, most likely, SARS-positive samples were confiscated by the customs authorities in the provinces.
The study found that Civets (Paguma larvata) carried the highest number of potentially high-risk viruses.
The researchers identified the transmission of Bat coronavirus HKU8 from a bat to a civet. Similarly, they identified avian Influenza A virus H9N2 in civets and Asian badgers. These observations confirmed cross-species jumps from bats to hedgehogs and birds to porcupines, ‘that might seed a disease outbreak.’
Further, the researchers presented the first evidence of human pathogens in various game animals, such as Influenza B virus, Human parainfluenza virus 2, and Norovirus GII.17 in bamboo rats, Malayan pangolins, and civets – indicative of human-to-wildlife transmission.
Importantly, the study showed that these viruses were present in seemingly healthy animals, and there is the ongoing cross-species transmission of the virus among game animals.
Performing a large-scale survey of viral pathogens, this study reveals the diversity and abundance of viruses in game animals using meta-trancriptomic techniques. It confirms that game animals are important hosts for these viruses that pose a health risk to humans and domestic animals.
This is an important study with insights into information on viruses in game animals that might lead to the next pandemic.
bioRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
Wan-Ting He, Xin Hou, Jin Zhao, Jiumeng Sun, Haijian He, Wei Si, Jing Wang, Zhiwen Jiang, Ziqing Yan, Gang Xing, Meng Lu, Marc A. Suchard, Xiang Ji, Wenjie Gong, Biao He, Jun Li, Philippe Lemey, Deyin Guo, Changchun Tu, Edward C. Holmes, Mang Shi, Shuo Su. bioRxiv. 2021. doi: https://doi.org/10.1101/2021.11.10.467646 https://www.biorxiv.org/content/10.1101/2021.11.10.467646v1
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