Joy Yang

INTRODUCTION: The PCR-based analysis of homologous genes has become one of the most powerful approaches for species detection and identification, particularly with the recent availability of Next Generation Sequencing platforms (NGS) making it possible to identify species composition from a broad range of environmental samples. Identifying species from these samples relies on the ability to match sequences with reference barcodes for taxonomic identification. Unfortunately, most studies of environmental samples have targeted ribosomal markers, despite the fact that the mitochondrial Cytochrome c Oxidase subunit I gene (COI) is by far the most widely available sequence region in public reference libraries. This is largely because the available versatile ("universal") COI primers target the 658 barcoding region, whose size is considered too large for many NGS applications. Moreover, traditional barcoding primers are known to be poorly conserved across some taxonomic groups. RESULTS: We first design a new PCR primer within the highly variable mitochondrial COI region, the "mlCOIintF" primer. We then show that this newly designed forward primer combined with the "jgHCO2198" reverse primer to target a 313 bp fragment performs well across metazoan diversity, with higher success rates than versatile primer sets traditionally used for DNA barcoding (i.e. LCO1490/HCO2198). Finally, we demonstrate how the shorter COI fragment coupled with an efficient bioinformatics pipeline can be used to characterize species diversity from environmental samples by pyrosequencing. We examine the gut contents of three species of planktivorous and benthivorous coral reef fish (family: Apogonidae and Holocentridae). After the removal of dubious COI sequences, we obtained a total of 334 prey Operational Taxonomic Units (OTUs) belonging to 14 phyla from 16 fish guts. Of these, 52.5% matched a reference barcode (>98% sequence similarity) and an additional 32% could be assigned to a higher taxonomic level using Bayesian assignment. CONCLUSIONS: The molecular analysis of gut contents targeting the 313 COI fragment using the newly designed mlCOIintF primer in combination with the jgHCO2198 primer offers enormous promise for metazoan metabarcoding studies. We believe that this primer set will be a valuable asset for a range of applications from large-scale biodiversity assessments to food web studies.

UNLABELLED: Biological sensors can be engineered to measure a wide range of environmental conditions. Here we show that statistical analysis of DNA from natural microbial communities can be used to accurately identify environmental contaminants, including uranium and nitrate at a nuclear waste site. In addition to contamination, sequence data from the 16S rRNA gene alone can quantitatively predict a rich catalogue of 26 geochemical features collected from 93 wells with highly differing geochemistry characteristics. We extend this approach to identify sites contaminated with hydrocarbons from the Deepwater Horizon oil spill, finding that altered bacterial communities encode a memory of prior contamination, even after the contaminants themselves have been fully degraded. We show that the bacterial strains that are most useful for detecting oil and uranium are known to interact with these substrates, indicating that this statistical approach uncovers ecologically meaningful interactions consistent with previous experimental observations. Future efforts should focus on evaluating the geographical generalizability of these associations. Taken as a whole, these results indicate that ubiquitous, natural bacterial communities can be used as in situ environmental sensors that respond to and capture perturbations caused by human impacts. These in situ biosensors rely on environmental selection rather than directed engineering, and so this approach could be rapidly deployed and scaled as sequencing technology continues to become faster, simpler, and less expensive. IMPORTANCE: Here we show that DNA from natural bacterial communities can be used as a quantitative biosensor to accurately distinguish unpolluted sites from those contaminated with uranium, nitrate, or oil. These results indicate that bacterial communities can be used as environmental sensors that respond to and capture perturbations caused by human impacts.

Microbial communities are shaped by viral predators. Yet, resolving which viruses (phages) and bacteria are interacting is a major challenge in the context of natural levels of microbial diversity. Thus, fundamental features of how phage-bacteria interactions are structured and evolve in the wild remain poorly resolved. Here we use large-scale isolation of environmental marine Vibrio bacteria and their phages to obtain estimates of strain-level phage predator loads, and use all-by-all host range assays to discover how phage and host genomic diversity shape interactions. We show that lytic interactions in environmental interaction networks (as observed in agar overlay) are sparse-with phage predator loads being low for most bacterial strains, and phages being host-strain-specific. Paradoxically, we also find that although overlap in killing is generally rare between tailed phages, recombination is common. Together, these results suggest that recombination during cryptic co-infections is an important mode of phage evolution in microbial communities. In the development of phages for bioengineering and therapeutics it is important to consider that nucleic acids of introduced phages may spread into local phage populations through recombination, and that the likelihood of transfer is not predictable based on lytic host range.