Advancing the central role of non-model biorepositories in predictive modeling of emerging pathogens

How many mammal species are there now? Updates and trends in taxonomic, nomenclatural, and geographic knowledge

The Mammal Diversity Database (MDD) is an open-access resource providing up-to-date taxonomic, nomenclatural, and geographic data for global mammal species. Since its launch in 2018, the MDD has transformed the traditionally static process of updating mammalian taxonomy into regular online releases reflecting the latest published research. To build on this foundation, we here present version 2.0 of the MDD (MDD2), which catalogues 6,759 living and recently extinct mammal species, representing net increases of 4.1% and 24.8% over MDD version 1.0 and Mammal Species of the World, 3rd edition (MSW3), respectively. Additionally, we identify a net increase of 68.8% (+2,754; 3,149 splits + de novo, 395 lumps) species since 1980 at a rate of ~65 species/year based on past totals from 14 mammalian compendia, leading to projections of ~7,084 species by 2030 and ~8,382 by 2050 if these trends continue. Key updates in MDD2 include: (i) codings of US state, country, continent, and biogeographic realm geographic categories for each species; (ii) a comprehensive nomenclatural dataset for 50,230 valid and synonymous species-rank names, curated with type locality and specimen information for the first time; and (iii) integration between the MDD and the databases Hesperomys and Batnames for greater data accuracy and completeness. These updates bridge critical gaps in the taxonomic and nomenclatural information needed for ongoing revisions and assessments of mammalian species diversity. Using these data, we evaluate temporal and geographic trends over the past 267 years, identifying four major time periods of change in mammalian taxonomy and nomenclature: (i) the initial monographic description of traditionally charismatic species (1758-1880); (ii) the peak of descriptive taxonomy, describing subspecies, and publishing in journals (1881-1939); (iii) the shift toward revisionary taxonomy and polytypic species (1940-1999); and (iv) the current technology-driven period of integrative revisionary taxonomy (2000-present). Geographically, new species recognition since MSW3 has been concentrated in equatorial, mountainous, and island regions, highlighting areas of high mammal endemism (e.g., Madagascar, Philippines, Andes, East Africa, Himalayas, Atlantic Forests). However, gaps in 21st century taxonomic activity are identified in West and Central Africa, India, and some parts of Indonesia. Currently lagging conservation assessments are alarming, with 25% of the MDD2-recognized mammal species allocated to the 'understudied' conservation threat categories of Data Deficient (11%) or Not Evaluated (14%), underscoring the need for greater taxonomic integration with conservation organizations. Governance advancements in MDD2 include the establishment of external taxonomic subcommittees to guide data collection and curation, a rewritten website that improves access and scalability, a cross-platform application that provides offline access, and new partnerships to continue linking MDD data to global biodiversity infrastructure. By providing up-to-date mammalian taxonomic and nomenclatural data-including links to the text of original name descriptions, type localities, and type specimen collections-the MDD provides an integrative resource for mammalogists and conservationists to more easily track the status of their study organisms.

Choclo virus (CHOV) recovered from deep metatranscriptomics of archived frozen tissues in natural history biorepositories

BACKGROUND

Hantaviruses are negative-stranded RNA viruses that can sometimes cause severe disease in humans; however, they are maintained in mammalian host populations without causing harm. In Panama, sigmodontine rodents serve as hosts to transmissible hantaviruses. Due to natural and anthropogenic forces, these rodent populations are having increased contact with humans.

METHODS

We extracted RNA and performed Illumina deep metatranscriptomic sequencing on Orthohantavirus seropositive museum tissues from rodents. We acquired sequence reads mapping to Choclo virus (CHOV, Orthohantavirus chocloense) from heart and kidney tissue of a two-decade old frozen museum sample from a Costa Rican pygmy rice rat (Oligoryzomys costaricensis) collected in Panama. Reads mapped to the CHOV reference were assembled and then validated by visualization of the mapped reads against the assembly.

RESULTS

We recovered a 91% complete consensus sequence from a reference-guided assembly to CHOV with an average of 16X coverage. The S and M segments used in our phylogenetic analyses were nearly complete (98% and 99%, respectively). There were 1,199 ambiguous base calls of which 93% were present in the L segment. Our assembled genome varied 1.1% from the CHOV reference sequence resulting in eight nonsynonymous mutations. Further analysis of all publicly available partial S segment sequences support a clear relationship between CHOV clinical cases and O. costaricensis acquired strains.

CONCLUSIONS

Viruses occurring at extremely low abundances can be recovered from deep metatranscriptomics of archival tissues housed in research natural history museum biorepositories. Our efforts resulted in the second CHOV genome publicly available. This genomic data is important for future surveillance and diagnostic tools as well as understanding the evolution and pathogenicity of CHOV.

Integrating databases for spatial analysis of parasite-host associations and the novel Brazilian dataset

Incomplete information on parasites, their associated hosts, and their precise geographical location hampers the ability to predict disease emergence in Brazil, a continental-sized country characterised by significant regional disparities. Here, we demonstrate how the NCBI Nucleotide and GBIF databases can be used as complementary databases to study spatially georeferenced parasite-host associations. We also provide a comprehensive dataset of parasites associated with mammal species that occur in Brazil, the Brazilian Mammal Parasite Occurrence Data (BMPO). This dataset integrates wild mammal species' morphological and life-history traits, zoonotic parasite status, and zoonotic microparasite transmission modes. Through meta-networks, comprising interconnected host species linked by shared zoonotic microparasites, we elucidate patterns of zoonotic microparasite dissemination. This approach contributes to wild animal and zoonoses surveillance, identifying and targeting host species accountable for disproportionate levels of parasite sharing within distinct biomes. Moreover, our novel dataset contributes to the refinement of models concerning disease emergence and parasite distribution among host species.