Unravelling virus community ecology in bats through the integration of metagenomics and community ecology

The spillover of viruses from wildlife into agricultural animals or humans has profound socioeconomic and public health impact. Vampire bats, found throughout South America, feed directly on humans and other animals and are an important reservoir for zoonotic viruses, including rabies virus. This has resulted in considerable effort in understanding both the ecology of bat‐borne viruses and the composition and associated correlates of the structure of entire virus communities in wildlife, particularly in the context of disease control interventions. In a From the Cover article in this issue of Molecular Ecology, Bergner et al. (2019) set out to reveal virus community dynamics in vampire bats by interrogating factors that affect the structure, diversity and richness of these communities. Due to the linkage of metagenomic sequence data with community ecology, this study represents an important advance in the field of virus ecology.     

A total crapshoot? Evaluating bioinformatic decisions in animal diet metabarcoding analyses

Metabarcoding studies provide a powerful approach to estimate the diversity and abundance of organisms in mixed communities in nature. While strategies exist for optimizing sample and sequence library preparation, best practices for bioinformatic processing of amplicon sequence data are lacking in animal diet studies. Here we evaluate how decisions made in core bioinformatic processes, including sequence filtering, database design, and classification, can influence animal metabarcoding results. We show that denoising methods have lower error rates compared to traditional clustering methods, although these differences are largely mitigated by removing low‐abundance sequence variants. We also found that available reference datasets from GenBank and BOLD for the animal marker gene cytochrome oxidase I (COI) can be complementary, and we discuss methods to improve existing databases to include versioned releases. Taxonomic classification methods can dramatically affect results. For example, the commonly used Barcode of Life Database (BOLD) Classification API assigned fewer names to samples from order through species levels using both a mock community and bat guano samples compared to all other classifiers (vsearch‐SINTAX and q2‐feature‐classifier's BLAST + LCA, VSEARCH + LCA, and Naive Bayes classifiers). The lack of consensus on bioinformatics best practices limits comparisons among studies and may introduce biases. Our work suggests that biological mock communities offer a useful standard to evaluate the myriad computational decisions impacting animal metabarcoding accuracy. Further, these comparisons highlight the need for continual evaluations as new tools are adopted to ensure that the inferences drawn reflect meaningful biology instead of digital artifacts.     

Maximizing antibody production in a targeted integration host by optimization of subunit gene dosage and position

Historically, therapeutic protein production in Chinese hamster ovary (CHO) cells has been accomplished by random integration (RI) of expression plasmids into the host cell genome. More recently, the development of targeted integration (TI) host cells has allowed for recombination of plasmid DNA into a predetermined genomic locus, eliminating one contributor to clone-to-clone variability. In this study, a TI host capable of simultaneously integrating two plasmids at the same genomic site was used to assess the effect of antibody heavy chain and light chain gene dosage on antibody productivity. Our results showed that increasing antibody gene copy number can increase specific productivity, but with diminishing returns as more antibody genes are added to the same TI locus. Random integration of additional antibody DNA copies in to a targeted integration cell line showed a further increase in specific productivity, suggesting that targeting additional genomic sites for gene integration may be beneficial. Additionally, the position of antibody genes in the two plasmids was observed to have a strong effect on antibody expression level. These findings shed light on vector design to maximize production of conventional antibodies or tune expression for proper assembly of complex or bispecific antibodies in a TI system.     

Population and genetic structure of a male-dispersing strepsirrhine,Galago moholi (Primates,Galagidae), from northern South Africa,inferred from mitochondrial DNA

Primates - The habitats of Galago moholi are suspected to be largely fragmented, while the species is thought to be expanding further into the southernmost fringe of its range, as well as into...     

Population-level impacts of natural and anthropogenic causes-of-death for Hawaiian monk seals in the main Hawaiian Islands

Identifying, assessing, and ranking the impact of individual threats is fundamental to the conservation and recovery of rare and endangered species. In this analysis, we quantify not only the frequency of specific causes-of-death (CODs) among Main Hawaiian Island (MHI) monk seals, but also assess the impact of individual CODs on the intrinsic growth rate, λ, of the MHI population. We used gross necropsy results, histopathology, and other evidence to assign probabilities of 11 COD types to each mortality and then used Monte Carlo sampling to evaluate the influence of each COD on λ. By right censoring realizations involving specific CODs, we were able to estimate λ (and its associated uncertainty) when CODs were selectively removed from influencing survival. Applying the analysis to all known and inferred deaths believed to have occurred 2004–2019, the CODs with the largest influence on λ were anthropogenic trauma, anthropogenic drowning, and protozoal disease. In aggregate, anthropogenic CODs had a larger effect on the growth rate than either natural or disease CODs. Possible bias associated with differential carcass detection, recovery, and COD classification are discussed.