CRISPR-Cas-Based Biomonitoring for Marine Environments: Toward CRISPR RNA Design Optimization Via Deep Learning.

Almost all of Earth's oceans are now impacted by multiple anthropogenic stressors, including the spread of nonindigenous species, harmful algal blooms, and pathogens. Early detection is critical to manage these stressors effectively and to protect marine systems and the ecosystem services they provide. Molecular tools have emerged as a promising solution for marine biomonitoring. One of the latest advancements involves utilizing CRISPR-Cas technology to build programmable, rapid, ultrasensitive, and specific diagnostics. CRISPR-based diagnostics (CRISPR-Dx) has the potential to allow robust, reliable, and cost-effective biomonitoring in near real time. However, several challenges must be overcome before CRISPR-Dx can be established as a mainstream tool for marine biomonitoring. A critical unmet challenge is the need to design, optimize, and experimentally validate CRISPR-Dx assays. Artificial intelligence has recently been presented as a potential approach to tackle this challenge. This perspective synthesizes recent advances in CRISPR-Dx and machine learning modeling approaches, showcasing CRISPR-Dx potential to progress as a rising molecular tool candidate for marine biomonitoring applications.

Assessing the utility of marine filter feeders for environmental DNA (eDNA) biodiversity monitoring.

Aquatic environmental DNA (eDNA) surveys are transforming how marine ecosystems are monitored. The time-consuming preprocessing step of active filtration, however, remains a bottleneck. Hence, new approaches that eliminate the need for active filtration are required. Filter-feeding invertebrates have been proven to collect eDNA, but side-by-side comparative studies to investigate the similarity between aquatic and filter-feeder eDNA signals are essential. Here, we investigated the differences among four eDNA sources (water; bivalve gill-tissue; sponges; and ethanol in which filter-feeding organisms were stored) along a vertically stratified transect in Doubtful Sound, New Zealand using three metabarcoding primer sets targeting fish and vertebrates. Combined, eDNA sources detected 59 vertebrates, while concurrent diver surveys observed eight fish species. There were no significant differences in alpha and beta diversity between water and sponge eDNA and both sources were highly correlated. Vertebrate eDNA was successfully extracted from the ethanol in which sponges were stored, although a reduced number of species were detected. Bivalve gill-tissue dissections, on the other hand, failed to reliably detect eDNA. Overall, our results show that vertebrate eDNA signals obtained from water samples and marine sponges are highly concordant. The strong similarity in eDNA signals demonstrates the potential of marine sponges as an additional tool for eDNA-based marine biodiversity surveys, by enabling the incorporation of larger sample numbers in eDNA surveys, reducing plastic waste, simplifying sample collection, and as a cost-efficient alternative. However, we note the importance to not detrimentally impact marine communities by, for example, nonlethal subsampling, specimen cloning, or using bycatch specimens.