The science of the host–virus network

Albery, Gregory F.; Becker, Daniel J.; Brierley, Liam; Brook, Cara E.; Christofferson, Rebecca C.; Cohen, Lily E; Dallas, Tad; Eskew, Evan A.; Fagre, Anna C.; Farrell, Maxwell J.; Glennon, Emma E.; Guth, Sarah; Joseph, Maxwell B.; Mollentze, Nardus; Neely, Benjamin A.; Poisot, Timothée; Rasmussen, Angela L.; Ryan, Sadie J.; Seifert, Stephanie; Sjödin, Anna; Sorrell, Erin M.; Carlson, Colin J.

doi:10.1038/s41564-021-00999-5

Cited by 72 publications

(80 citation statements)

References 120 publications

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“…This is likely an underestimate as our criteria for zoonotic alien hosts were highly conservative (Supplementary Data 2 ). Given taxonomic and geographic biases in zoonosis sampling, there might be many unknown zoonotic hosts that have not yet been reported or studied 27 , 28 . Despite this, we tried to account for potential sampling biases in disease surveillance efforts and which species and geographic locations were studied to increase the robustness of our findings.…”

Section: Discussionmentioning

confidence: 99%

Biological invasions facilitate zoonotic disease emergences

et al. 2022

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Outbreaks of zoonotic diseases are accelerating at an unprecedented rate in the current era of globalization, with substantial impacts on the global economy, public health, and sustainability. Alien species invasions have been hypothesized to be important to zoonotic diseases by introducing both existing and novel pathogens to invaded ranges. However, few studies have evaluated the generality of alien species facilitating zoonoses across multiple host and parasite taxa worldwide. Here, we simultaneously quantify the role of 795 established alien hosts on the 10,473 zoonosis events across the globe since the 14th century. We observe an average of ~5.9 zoonoses per alien zoonotic host. After accounting for species-, disease-, and geographic-level sampling biases, spatial autocorrelation, and the lack of independence of zoonosis events, we find that the number of zoonosis events increase with the richness of alien zoonotic hosts, both across space and through time. We also detect positive associations between the number of zoonosis events per unit space and climate change, land-use change, biodiversity loss, human population density, and PubMed citations. These findings suggest that alien host introductions have likely contributed to zoonosis emergences throughout recent history and that minimizing future zoonotic host species introductions could have global health benefits.

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Section: Discussionmentioning

confidence: 99%

Biological invasions facilitate zoonotic disease emergences

et al. 2022

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“…The SARS-CoV-2 pandemic highlighted the need to investigate previously unknown viruses from wild animals in an unbiased manner (Albery et al, 2021;Grange et al, 2021;Hu et al, 2021). Information on viral diversity in animals, especially in birds and small mammals from the Qinghai-Tibet Plateau (average altitude >4000 m), is still limited.…”

Section: Discussionmentioning

confidence: 99%

RNA Virus Diversity in Birds and Small Mammals From Qinghai–Tibet Plateau of China

Zhu

Yang

et al. 2022

Front. Microbiol.

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Most emerging and re-emerging viruses causing infectious diseases in humans and domestic animals have originated from wildlife. However, current knowledge of the spectrum of RNA viruses in the Qinghai-Tibet Plateau in China is still limited. Here, we performed metatranscriptomic sequencing on fecal samples from 56 birds and 91 small mammals in Tibet and Qinghai Provinces, China, to delineate their viromes and focused on vertebrate RNA viruses. A total of 184 nearly complete genome RNA viruses belonging to 28 families were identified. Among these, 173 new viruses shared <90% amino acid identity with previously known viral sequences. Several of these viruses, such as those belonging to genera Orthonairovirus and Hepatovirus, could be zoonotic viruses. In addition, host taxonomy and geographical location of these viruses showed new hosts and distribution of several previously discovered viruses. Moreover, 12 invertebrate RNA viruses were identified with <40% amino acid identity to known viruses, indicating that they belong to potentially new taxa. The detection and characterization of RNA viruses from wildlife will broaden our knowledge of virus biodiversity and possible viral diseases in the Qinghai–Tibet Plateau.

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“…While sharing networks can identify host profiles for particular parasite groups or host species that promote parasite sharing across hosts, the ability to predict individual host–parasite interactions is limited (Becker et al, 2022). An alternative is to treat hosts and parasites as two separate interacting classes that can be represented in a bipartite network (Albery et al, 2021). Bipartite network models can predict new links based solely on the structure of the observed network, or incorporate node‐level covariates, such as species traits (Becker et al, 2022; Dallas et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Predicting missing links in global host–parasite networks

Farrell

Elmasri

Stephens

et al. 2022

Journal of Animal Ecology

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1. Parasites that infect multiple species cause major health burdens globally, but for many, the full suite of susceptible hosts is unknown. Predicting undocumented host–parasite associations will help expand knowledge of parasite host specificities, promote the development of theory in disease ecology and evolution, and support surveillance of multi‐host infectious diseases. The analysis of global species interaction networks allows for leveraging of information across taxa, but link prediction at this scale is often limited by extreme network sparsity and lack of comparable trait data across species. 2. Here we use recently developed methods to predict missing links in global mammal‐parasite networks using readily available data: network properties and evolutionary relationships among hosts. We demonstrate how these link predictions can efficiently guide the collection of species interaction data and increase the completeness of global species interaction networks. 3. We amalgamate a global mammal host–parasite interaction network (>29,000 interactions) and apply a hierarchical Bayesian approach for link prediction that leverages information on network structure and scaled phylogenetic distances among hosts. We use these predictions to guide targeted literature searches of the most likely yet undocumented interactions, and identify empirical evidence supporting many of the top ‘missing’ links. 4. We find that link prediction in global host–parasite networks can successfully predict parasites of humans, domesticated animals and endangered wildlife, representing a combination of published interactions missing from existing global databases, and potential but currently undocumented associations. 5. Our study provides further insight into the use of phylogenies for predicting host–parasite interactions, and highlights the utility of iterated prediction and targeted search to efficiently guide the collection of information on host–parasite interactions. These data are critical for understanding the evolution of host specificity, and may be used to support disease surveillance through a process of predicting missing links, and targeting research towards the most likely undocumented interactions.

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The science of the host–virus network

Cited by 72 publications

References 120 publications

Biological invasions facilitate zoonotic disease emergences

Biological invasions facilitate zoonotic disease emergences

RNA Virus Diversity in Birds and Small Mammals From Qinghai–Tibet Plateau of China

Predicting missing links in global host–parasite networks

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