Phylogenetic proximity drives temporal succession of marine giant viruses in a five-year metagenomic time-series.

Nucleocytoplasmic Large DNA Viruses (NCLDVs, also called giant viruses) are widespread in marine systems and infect a broad range of microbial eukaryotes (protists). Recent biogeographic work has provided global snapshots of NCLDV diversity and community composition across the world's oceans, yet little information exists about the guiding 'rules' underpinning their community dynamics over time. We leveraged a five-year monthly metagenomic time-series to quantify the community composition of NCLDVs off the coast of Southern California and characterize these populations' temporal dynamics.

Local monitoring of SARS-CoV-2 variants in two large California counties in 2021.

Coronavirus Disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), continues to persist due to mutations resulting in newer, more infectious variants of concern. We aimed to leverage an ongoing private SARS-CoV-2 testing laboratory's infrastructure to monitor SARS-CoV-2 variants in two large California counties. Study enrollment was offered to adults aged 18 years or older in Los Angeles County and Riverside County who recently tested positive for SARS-CoV-2 with a polymerase chain reaction (PCR) assay.

Benchmarking microbial growth rate predictions from metagenomes.

Growth rates are central to understanding microbial interactions and community dynamics. Metagenomic growth estimators have been developed, specifically codon usage bias (CUB) for maximum growth rates and "peak-to-trough ratio" (PTR) for in situ rates. Both were originally tested with pure cultures, but natural populations are more heterogeneous, especially in individual cell histories pertinent to PTR.

A network-based integrated framework for predicting virus-prokaryote interactions.

Metagenomic sequencing has greatly enhanced the discovery of viral genomic sequences; however, it remains challenging to identify the host(s) of these new viruses. We developed VirHostMatcher-Net, a flexible, network-based, Markov random field framework for predicting virus-prokaryote interactions using multiple, integrated features: CRISPR sequences and alignment-free similarity measures ([Formula: see text] and WIsH). Evaluation of this method on a benchmark set of 1462 known virus-prokaryote pairs yielded host prediction accuracy of 59% and 86% at the genus and phylum levels, representing 16-27% and 6-10% improvement, respectively, over previous single-feature prediction approaches.

Long-term stability and Red Queen-like strain dynamics in marine viruses.

Viruses that infect microorganisms dominate marine microbial communities numerically, with impacts ranging from host evolution to global biogeochemical cycles. However, virus community dynamics, necessary for conceptual and mechanistic model development, remains difficult to assess. Here, we describe the long-term stability of a viral community by analysing the metagenomes of near-surface 0.