Environmental biomonitoring infers the health of an ecosystem by examining the organisms that live there. While chemical monitoring provides a snap-shot in time, biomonitoring assesses the long-term cumulative impacts of all contaminants on the ecosystem. Bio-monitoring of aquatic systems is frequently done by studying the composition of the macroinvertebrate communities that live in the system. Current macroinvertebrate bio-monitoring approaches rely on microscope analysis to identify and classify the invertebrates that live in the community. This requires a high degree of taxonomic expertise and can result in high costs/slow turn-around times.
I am interested in looking at ways to develop a molecular approach to evaluating macroinvertebrate communities. We have previously tested two methods for examining the communities. The first was a more traditional amplicon sequencing approach (comparable to 16S sequencing of microbial communities). The second used a gene enrichment approach in which DNA was fragmented and captured by sequence probes.
We could show that the gene enrichment approach worked far better than a traditional amplicon sequencing for evaluating macroinvertebrate communities. The amplicon sequencing struggled with priming bias (despite degenerate primers) and often missed taxa altogether. The gene enrichment approach generated per taxa sequence counts proportional to the taxa biomass estimates generated before DNA extraction. I am very interested in working with end users (iwi and local government) to expand on this work and include recent methodological developments in PCR-free enrichment approaches.
For more details see:
Dowle, E.J., X. Pochon, J. C. Banks, K. Shearer, and S.A. Wood, Targeted gene enrichment and high-throughput sequencing for environmental biomonitoring: a case study using freshwater macroinvertebrates. Molecular Ecology Resources, 2016. 16, 1240–1254
Dowle, E., X. Pochon, N. Keeley, and S.A. Wood, Assessing the effects of salmon farming seabed enrichment using bacterial community diversity and high throughput sequencing. FEMS Microbiology Ecology, 2015.