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1. Coronavirus sampling and surveillance in bats from 1996–2019: a systematic review and meta-analysis

   https://doi.org/10.1038/s41564-023-01375-1  

   Cohen, Lily E. ; Fagre, Anna C. ; Chen, Binqi ; Carlson, Colin J. ; Becker, Daniel J. ( May 2023 , Nature Microbiology)

   The emergence of SARS-CoV-2 highlights a need for evidence-based strategies to monitor bat viruses. We performed a systematic review of coronavirus sampling (testing for RNA positivity) in bats globally. We identified 110 studies published between 2005 and 2020 that collectively reported positivity from 89,752 bat samples. We compiled 2,274 records of infection prevalence at the finest methodological, spatiotemporal and phylogenetic level of detail possible from public records into an open, static database named datacov, together with metadata on sampling and diagnostic methods. We found substantial heterogeneity in viral prevalence across studies, reflecting spatiotemporal variation in viral dynamics and methodological differences. Meta-analysis identified sample type and sampling design as the best predictors of prevalence, with virus detection maximized in rectal and faecal samples and by repeat sampling of the same site. Fewer than one in five studies collected and reported longitudinal data, and euthanasia did not improve virus detection. We show that bat sampling before the SARS-CoV-2 pandemic was concentrated in China, with research gaps in South Asia, the Americas and sub-Saharan Africa, and in subfamilies of phyllostomid bats. We propose that surveillance strategies should address these gaps to improve global health security and enable the origins of zoonotic coronavirusesmore »to be identified.

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2. Targeted assemblies of cas1 suggest CRISPR-Cas’s response to soil warming

   https://doi.org/10.1038/s41396-020-0635-1  

   Wu, Ruonan ; Chai, Benli ; Cole, James R. ; Gunturu, Santosh K. ; Guo, Xue ; Tian, Renmao ; Gu, Ji-Dong ; Zhou, Jizhong ; Tiedje, James M. ( March 2020 , The ISME Journal)

   There is an increasing interest in the clustered regularly interspaced short palindromic repeats CRISPR-associated protein (CRISPR-Cas) system to reveal potential virus–host dynamics. The universal and most conserved Cas protein,cas1is an ideal marker to elucidate CRISPR-Cas ecology. We constructed eight Hidden Markov Models (HMMs) and assembledcas1directly from metagenomes by a targeted-gene assembler, Xander, to improve detection capacity and resolve the diverse CRISPR-Cas systems. The eight HMMs were first validated by recovering all 17cas1subtypes from the simulated metagenome generated from 91 prokaryotic genomes across 11 phyla. We challenged the targeted method with 48 metagenomes from a tallgrass prairie in Central Oklahoma recovering 3394cas1. Among those, 88 were near full length, 5 times more than in de-novo assemblies from the Oklahoma metagenomes. To validate the host assignment bycas1, the targeted-assembledcas1was mapped to the de-novo assembled contigs. All the phylum assignments of those mapped contigs were assigned independent of CRISPR-Cas genes on the same contigs and consistent with the host taxonomies predicted by the mappedcas1. We then investigated whether 8 years of soil warming alteredcas1prevalence within the communities. A shift in microbial abundances was observed during the year with the biggest temperature differential (mean 4.16 °C above ambient).cas1prevalence increased and even in the phylamore »with decreased microbial abundances over the next 3 years, suggesting increasing virus–host interactions in response to soil warming. This targeted method provides an alternative means to effectively minecas1from metagenomes and uncover the host communities.

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3. Using machine learning to detect coronaviruses potentially infectious to humans

   https://doi.org/10.1038/s41598-023-35861-7  

   Gonzalez-Isunza, Georgina ; Jawaid, M. Zaki ; Liu, Pengyu ; Cox, Daniel L. ; Vazquez, Mariel ; Arsuaga, Javier ( June 2023 , Scientific Reports)

   Establishing the host range for novel viruses remains a challenge. Here, we address the challenge of identifying non-human animal coronaviruses that may infect humans by creating an artificial neural network model that learns from spike protein sequences of alpha and beta coronaviruses and their binding annotation to their host receptor. The proposed method produces a human-Binding Potential (h-BiP) score that distinguishes, with high accuracy, the binding potential among coronaviruses. Three viruses, previously unknown to bind human receptors, were identified: Bat coronavirus BtCoV/133/2005 and Pipistrellus abramus bat coronavirus HKU5-related (both MERS related viruses), andRhinolophus affiniscoronavirus isolate LYRa3 (a SARS related virus). We further analyze the binding properties of BtCoV/133/2005 and LYRa3 using molecular dynamics. To test whether this model can be used for surveillance of novel coronaviruses, we re-trained the model on a set that excludes SARS-CoV-2 and all viral sequences released after the SARS-CoV-2 was published. The results predict the binding of SARS-CoV-2 with a human receptor, indicating that machine learning methods are an excellent tool for the prediction of host expansion events.
4. Environmental transmission of Pseudogymnoascus destructans to hibernating little brown bats

   https://doi.org/10.1038/s41598-023-31515-w  

   Hicks, Alan C. ; Darling, Scott R. ; Flewelling, Joel E. ; von Linden, Ryan ; Meteyer, Carol U. ; Redell, David N. ; White, J. Paul ; Redell, Jennifer ; Smith, Ryan ; Blehert, David S. ; et al ( March 2023 , Scientific Reports)

   Pathogens with persistent environmental stages can have devastating effects on wildlife communities. White-nose syndrome (WNS), caused by the fungusPseudogymnoascus destructans,has caused widespread declines in bat populations of North America. In 2009, during the early stages of the WNS investigation and before molecular techniques had been developed to readily detectP. destructansin environmental samples, we initiated this study to assess whetherP. destructanscan persist in the hibernaculum environment in the absence of its conclusive bat host and cause infections in naive bats. We transferred little brown bats (Myotis lucifugus) from an unaffected winter colony in northwest Wisconsin to twoP. destructanscontaminated hibernacula in Vermont where native bats had been excluded.Infection withP. destructanswas apparent on some bats within 8 weeks following the introduction of unexposed bats to these environments, and mortality from WNS was confirmed by histopathology at both sites 14 weeks following introduction. These results indicate that environmental exposure toP. destructansis sufficient to cause the infection and mortality associated with WNS in naive bats, which increases the probability of winter colony extirpation and complicates conservation efforts.
5. The Global Virome in One Network (VIRION): an Atlas of Vertebrate-Virus Associations

   https://doi.org/10.1128/mbio.02985-21  

   Carlson, Colin J. ; Gibb, Rory J. ; Albery, Gregory F. ; Brierley, Liam ; Connor, Ryan P. ; Dallas, Tad A. ; Eskew, Evan A. ; Fagre, Anna C. ; Farrell, Maxwell J. ; Frank, Hannah K. ; et al ( April 2022 , mBio)

   Pickett, Brett E. ; Jurado, Kellie (Ed.)

   ABSTRACT Data that catalogue viral diversity on Earth have been fragmented across sources, disciplines, formats, and various degrees of open sharing, posing challenges for research on macroecology, evolution, and public health. Here, we solve this problem by establishing a dynamically maintained database of vertebrate-virus associations, called The Global Virome in One Network (VIRION). The VIRION database has been assembled through both reconciliation of static data sets and integration of dynamically updated databases. These data sources are all harmonized against one taxonomic backbone, including metadata on host and virus taxonomic validity and higher classification; additional metadata on sampling methodology and evidence strength are also available in a harmonized format. In total, the VIRION database is the largest open-source, open-access database of its kind, with roughly half a million unique records that include 9,521 resolved virus “species” (of which 1,661 are ICTV ratified), 3,692 resolved vertebrate host species, and 23,147 unique interactions between taxonomically valid organisms. Together, these data cover roughly a quarter of mammal diversity, a 10th of bird diversity, and ∼6% of the estimated total diversity of vertebrates, and a much larger proportion of their virome than any previous database. We show how these data can be used to testmore »hypotheses about microbiology, ecology, and evolution and make suggestions for best practices that address the unique mix of evidence that coexists in these data. IMPORTANCE Animals and their viruses are connected by a sprawling, tangled network of species interactions. Data on the host-virus network are available from several sources, which use different naming conventions and often report metadata in different levels of detail. VIRION is a new database that combines several of these existing data sources, reconciles taxonomy to a single consistent backbone, and reports metadata in a format designed by and for virologists. Researchers can use VIRION to easily answer questions like “Can any fish viruses infect humans?” or “Which bats host coronaviruses?” or to build more advanced predictive models, making it an unprecedented step toward a full inventory of the global virome.« less