Garcia-Vedrenne, A. E. | Search bioRxiv

bioRxiv2022

Characterization of Genomic Diversity In Bacteriophages Infecting Rhodococcus

Bacteriophages are globally ubiquitous viruses that infect bacteria. With nearly 4,000 sequenced genomes of phages infecting the phylum Actinobacteria available, genomic analyses of these actinobacteriophage genomes has been instrumental in uncovering a diverse genomic landscape often characterized by genome mosaicism. Here, we describe the genomic characterization of 57 sequenced phages capable of infecting the genus Rhodococcus. These phages were previously isolated at multiple institutions by students in the SEA-PHAGES program using four different species of Rhodococcus. Most Rhodococcus phages have been grouped into 4 clusters based on their genomic similarities; 13 phages are singletons too genetically distinct for clustering. These clusters and singletons contain Siphoviridae and Myoviridae phages, and most contain integrase and repressor genes indicative of a potential lysogenic life cycle. The genome size of these phages varies from 14,270 bp to 142,586 bp and their G+C% content ranges from 41.2-68.4%, while that of their Rhodococcus hosts typically exceeds 60%. Through comparative genomic analyses, it was revealed that these Rhodococcus phages display high intracluster similarity but low intercluster similarity, despite their shared ability to infect the same host genus. Additionally, these Rhodococcus phages share similarities with phages that infect other Actinobacterial hosts such as Gordonia, Streptomyces and Arthrobacter.

microbiology↗

bioRxiv2020

A Biodiversity Composition Map of California Derived from Environmental DNA Metabarcoding and Earth Observation

Unique ecosystems globally are under threat from ongoing anthropogenic environmental change. Effective conservation management requires more thorough biodiversity surveys that can reveal system-level patterns and that can be applied rapidly across space and time. We offer a way to use environmental DNA, community science and remote sensing together as methods to reduce the discrepancy between the magnitude of change and historical approaches to measure it. Taking advantages of modern ecological models, we integrate environmental DNA and Earth observations to evaluate regional biodiversity patterns for a snapshot of time, and provide critical community-level characterization. We collected 278 samples in Spring 2017 from coastal, shrub and lowland forest sites in California, a large-scale biodiversity hotspot. We applied gradient forest to model 915 family occurrences and community composition together with environmental variables and multi-scalar habitat classifications to produce a statewide biodiversity-based map. 16,118 taxonomic entries recovered were associated with environmental variables to test their predictive strength on alpha, beta, and zeta diversity. Local habitat classification was diagnostic of community composition, illuminating a characteristic of biodiversity hotspots. Using gradient forest models, environmental variables predicted 35% of the variance in eDNA patterns at the family level, with elevation, sand percentage, and greenness (NDVI32) as the top predictors. This predictive power was higher than we found in published literature at global scale. In addition to this indication of substantial environmental filtering, we also found a positive relationship between environmentally predicted families and their numbers of biotic interactions. In aggregate, these analyses showed that strong eDNA community-environment correlation is a general characteristic of temperate ecosystems, and may explain why communities easily destabilize under disturbances. Our study provides the first example of integrating citizen science based eDNA with biodiversity mapping across the tree of life, with promises to produce large scale, high resolution assessments that promote a more comprehensive and predictive understanding of the factors that influence biodiversity and enhance its maintenance.

ecology↗