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Environmental DNA (eDNA) data make it possible to measure and monitor biodiversity at unprecedented resolution and scale. As use‐cases multiply and scientific consensus grows regarding the value of eDNA analysis, public agencies have an opportunity to decide how and where eDNA data fit into their mandates. Within the United States, many federal and state agencies are individually using eDNA data in various applications and developing relevant scientific expertise. A national strategy for eDNA implementation would capitalize on recent scientific developments, providing a common set of next‐generation tools for natural resource management and public health protection. Such a strategy would avoid patchwork and possibly inconsistent guidelines in different agencies, smoothing the way for efficient uptake of eDNA data in management. Because eDNA analysis is already in widespread use in both ocean and freshwater settings, we focus here on applications in these environments. However, we foresee the broad adoption of eDNA analysis to meet many resource management issues across the nation because the same tools have immediate terrestrial and aerial applications.

 

Biomolecular analyses are used to investigate the dynamics of cyanobacterial harmful algal blooms (cyanoHABs), with samples collected during monitoring often analyzed by qPCR and sometimes amplicon and metagenomic sequencing. However, cyanoHAB research and monitoring programs face operational constraints due to the reliance on human resources for sample collections. To address this impediment, a third-generation Environmental Sample Processor (3G ESP) integrated with a long-range autonomous underwater vehicle (LRAUV) was tested during seasonal blooms of Microcystis in western Lake Erie (WLE) in 2018 and 2019. The LRAUV-3G ESP successfully performed flexible, autonomous sampling across a wide range of cyanoHAB conditions, and results indicated equivalency between autonomous and manual methods. No significant differences were found between LRAUV-3G ESP and manual sample collection and handling methods in the 12 parameters tested. Analyzed parameters included concentrations of total cyanobacteria and microcystin toxin gene via qPCR; relative abundances of bacterial amplicon sequence variants (ASVs) from 16S rRNA gene amplicon sequencing; and community diversity measures from both 16S amplicon and metagenomic sequencing. The LRAUV-3G ESP provided additional sampling capacity and revealed differences between field seasons for bacterial taxa and concentrations of total cyanobacteria and microcystin toxin gene. Metagenomic analysis of multiple microcystin toxin genes corroborated the use of the mcyE gene as a proxy for the genomic potential of WLE cyanoHABs to produce microcystin. Overall, this study provides support for the use of autonomous ‘omics capability in WLE to help expand the spatial and temporal coverage of cyanoHAB monitoring operations. 

ABSTRACT Cyanobacterial harmful algal blooms (cyanoHABs) degrade freshwater ecosystems globally. Microcystis aeruginosa often dominates cyanoHABs and produces microcystin (MC), a class of hepatotoxins that poses threats to human and animal health. Microcystin toxicity is influenced by distinct structural elements across a diversity of related molecules encoded by variant mcy operons. However, the composition and distribution of mcy operon variants in natural blooms remain poorly understood. Here, we characterized the variant composition of mcy genes in western Lake Erie Microcystis blooms from 2014 and 2018. Sampling was conducted across several spatial and temporal scales, including different bloom phases within 2014, extensive spatial coverage on the same day (2018), and frequent, autonomous sampling over a 2-week period (2018). Mapping of metagenomic and metatranscriptomic sequences to reference sequences revealed three Microcystis mcy genotypes: complete (all genes present [ mcyA–J ]), partial (truncated mcyA , complete mcyBC , and missing mcyD–J ), and absent (no mcy genes). We also detected two different variants of mcyB that may influence the production of microcystin congeners. The relative abundance of these genotypes was correlated with pH and nitrate concentrations. Metatranscriptomic analysis revealed that partial operons were, at times, the most abundant genotype and expressed in situ , suggesting the potential biosynthesis of truncated products. Quantification of genetic divergence between genotypes suggests that the observed strains are the result of preexisting heterogeneity rather than de novo mutation during the sampling period. Overall, our results show that natural Microcystis populations contain several cooccurring mcy genotypes that dynamically shift in abundance spatiotemporally via strain succession and likely influence the observed diversity of the produced congeners. IMPORTANCE Cyanobacteria are responsible for producing microcystins (MCs), a class of potent and structurally diverse toxins, in freshwater systems around the world. While microcystins have been studied for over 50 years, the diversity of their chemical forms and how this variation is encoded at the genetic level remain poorly understood, especially within natural populations of cyanobacterial harmful algal blooms (cyanoHABs). Here, we leverage community DNA and RNA sequences to track shifts in mcy genes responsible for producing microcystin, uncovering the relative abundance, expression, and variation of these genes. We studied this phenomenon in western Lake Erie, which suffers annually from cyanoHAB events, with impacts on drinking water, recreation, tourism, and commercial fishing. 

The ecological and oceanographic processes that drive the response of pelagic ocean microbiomes to environmental changes remain poorly understood, particularly in coastal upwelling ecosystems. Here we show that seasonal and interannual variability in coastal upwelling predicts pelagic ocean microbiome diversity and community structure in the Southern California Current region. Ribosomal RNA gene sequencing, targeting prokaryotic and eukaryotic microbes, from samples collected seasonally during 2014-2020 indicate that nitracline depth is the most robust predictor of spatial microbial community structure and biodiversity in this region. Striking ecological changes occurred due to the transition from a warm anomaly during 2014-2016, characterized by intense stratification, to cooler conditions in 2017-2018, representative of more typical upwelling conditions, with photosynthetic eukaryotes, especially diatoms, changing most strongly. The regional slope of nitracline depth exerts strong control on the relative proportion of highly diverse offshore communities and low biodiversity, but highly productive nearshore communities.

 

Omic BON is a thematic Biodiversity Observation Network under the Group on Earth Observations Biodiversity Observation Network (GEO BON), focused on coordinating the observation of biomolecules in organisms and the environment. Our founding partners include representatives from national, regional, and global observing systems; standards organizations; and data and sample management infrastructures. By coordinating observing strategies, methods, and data flows, Omic BON will facilitate the co-creation of a global omics meta-observatory to generate actionable knowledge. Here, we present key elements of Omic BON's founding charter and first activities.