Biology subjects

Tato, C.

Publications and source records attributed to Tato, C..

3 recordsLinked to original sources

bioRxiv2024

Birds affected by a 2021 avian mortality event are strongly associated with supplemental feeding and ground foraging behaviors

In 2021, news outlets and state natural resources agencies reported a large number of avian deaths across several states in the eastern and midwestern USA. This event fomented a rapid and robust response from animal health experts from across the country. Given the clustered pattern of disease and death, an infectious etiology was rigorously investigated. No single causative pathogen was identified, leaving the cause and thus epidemiology of the mortality event unex-plained. In this study, we attempted to hone in on potential causes or contributors to this event by constructing a dataset on affected birds life history, phylogeny, and ecology. After a preliminary analysis of these features, we developed a statistical pipeline to test two hypotheses regarding features of birds associated with the mortality event: (1) that a significant proportion of affected birds in the total sample are members of the Cornell Feederwatch list (i.e., birds that consume supplemental feed, and their predators), and that (2) ground-feeding species would be significantly represented in the sample. While logistic regression models support the plausibility of the two hypotheses, they are statistically indistinguishable. We discuss the implications of these findings, propose future work, and highlight the importance of ecological and behavioral expertise in understanding epidemiological phenomena.

ecology↗

bioRxiv2024

CZ ID: a cloud-based, no-code platform enabling advanced long read metagenomic analysis

Metagenomics has enabled the rapid, unbiased detection of microbes across diverse sample types, leading to exciting discoveries in infectious disease, microbiome, and viral research. However, the analysis of metagenomic data is often complex and computationally resource-intensive. CZ ID is a free, cloud-based genomic analysis platform that enables researchers to detect microbes using metagenomic data, identify antimicrobial resistance genes, and generate viral consensus genomes. With CZ ID, researchers can upload raw sequencing data, find matches in NCBI databases, get per-sample taxon metrics, and perform a variety of analyses and data visualizations. The intuitive interface and interactive visualizations make exploring and interpreting results simple. Here, we describe the expansion of CZ ID with a new long read mNGS pipeline that accepts Oxford Nanopore generated data (czid.org). We report benchmarking of a standard mock microbial community dataset against Kraken2, a widely used tool for metagenomic analysis. We evaluated the ability of this new pipeline to detect divergent viruses using simulated datasets. We also assessed the detection limit of a spiked-in virus to a cell line as a proxy for clinical samples. Lastly, we detected known and novel viruses in previously characterized disease vector (mosquitoes) samples.

bioinformatics↗

bioRxiv2023

Detection, characterization, and phylogenetic analysis of a near-whole genome sequence of a novel astrovirus in an endemic Malagasy fruit bat, Rousettus madagascariensis

Bats (order: Chiroptera) are known to host a diverse range of viruses, some of which present a public health risk. Thorough viral surveillance is therefore essential to predict and potentially mitigate zoonotic spillover. Astroviruses (family: Astroviridae) are an understudied group of viruses with a growing amount of indirect evidence for zoonotic transfer. Astroviruses have been detected in bats with significant prevalence and diversity, suggesting that bats may act as important astrovirus hosts. Most astrovirus surveillance in wild bat hosts has, to date, been restricted to single-gene PCR detection and concomitant Sanger sequencing; additionally, many bat species and many geographic regions have not yet been surveyed for astroviruses at all. Here, we use metagenomic Next Generation Sequencing (mNGS) to detect astroviruses in three species of Madagascar fruit bats, Eidolon dupreanum, Pteropus rufus, and Rousettus madagascariensis. We detect numerous partial sequences from all three species and one near-full length astrovirus sequence from Rousettus madagascariensis, which we use to characterize the evolutionary history of astroviruses both within bats and the broader mammalian clade, Mamastrovirus. Taken together, applications of mNGS implicate bats as important astrovirus hosts and demonstrate novel patterns of bat astrovirus evolutionary history, particularly in the Southwest Indian Ocean region.

evolutionary biology↗