Enhancing biodiversity monitoring efficiency through CRISPR-driven depletion and enrichment of aquatic environmental DNA

Abstract

Characterising biodiversity using environmental DNA (eDNA) represents a paradigm shift in our capacity for biomonitoring complex aquatic environments. However, eDNA biomonitoring is limited by biases towards certain species and low taxonomic resolution of current metabarcoding-based approaches. Shotgun metagenomics of eDNA enables the collection of whole ecosystem data by sequencing all molecules present in a sample, allowing them to be characterised and identified. Ongoing enhancements of whole genome reference databases are improving the resolution of shotgun metagenomics, reducing database related limitations in species and individual identification for metagenomic studies. However, shotgun metagenomics-based insights are constrained by preferential sequencing, favouring more abundant organisms in the water column like bacteria and viruses over less abundant target species like vertebrates. To improve the probability of detecting low abundant target organisms, methods such as target species enrichment or the removal of non-target DNA prior to sequencing can be employed. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and the CRISPR-associated proteins (Cas) have recently emerged as a novel technology that can achieve both enrichment and depletion. CRISPR-Cas-based methods have the potential to improve the efficiency of eDNA metagenomic sequencing and simplify data analysis by reducing non-target data filtration steps, however, they have not been widely implemented due to a lack of interest and support in the past, as well as limited number of studies demonstrating they can be applied in a robust and cost-effective manner. Here, we review current approaches of CRISPR-Cas to study underrepresented aquatic taxa. We advocate that further optimization of depletion and enrichment methods of eDNA using CRISPR-Cas holds great promise for the rapidly evolving field of eDNA biomonitoring through refining monitoring approaches, overcoming PCR bias, and enabling efficient high-throughput applications.