Biodiversity is necessary to maintain ecosystems, supply chains, and the health and persistence of all species, including humans. Engineering biology can help to reduce biodiversity loss through less-invasive and more-sustainable monitoring and by ensuring that we can protect and support the resilience of keystone species and those that are threatened, particularly due to climate change and human activities.
Measurement technologies (i.e., multi-omics techniques) could be leveraged to rapidly catalog existing biodiversity in field environments with regard to genetic expression, metabolomics, and species composition. By documenting microbial species and their strain level diversity and identifying keystone functional guilds within a given ecosystem, we can support foundational microbiomes that are essential, designing and engineering networks, pathways, and heterogeneity to support at-risk ecosystems and keystone guilds. Genome monitoring and editing can also help to conserve biodiversity by tracking at-risk organisms, informing adaptation approaches or genetic rescue, and helping to limit or prevent poaching.1Phelps, M. P., Seeb, L. W., & Seeb, J. E. (2020). Transforming ecology and conservation biology through genome editing. Conservation Biology, 34(1), 54–65. View Publication.
Breakthrough Capabilities & Milestones
Enable monitoring of ecosystem health with bio-sensors and -reporters.
Improve data collection and libraries of mitochondrial DNA for sensitive ecosystem members (i.e., threatened and keystone species).
Increase application of genetic marker surveillance.
Use genetic fingerprinting and marker surveillance to develop species demographic and evolutionary data libraries for conservation management strategies.*
Expand activity-based monitoring (metafunctional genomics, metabolomics, stable tracer analyses) to track critical system function across diverse environments.
Develop integrated, continuous biosensors to track the effects of ecological forces (e.g., dispersal, drift, and selection) on community members in target biomes.
Track sourcing through supply chains by scaling-up biomolecular forensics (DNA, protein, and metabolic profiling) and genetic barcoding.
*Zimmerman, S. J., Aldridge, C. L., & Oyler-McCance, S. J. (2020). An empirical comparison of population genetic analyses using microsatellite and SNP data for a species of conservation concern. BMC Genomics, 21(1), 382. https://doi.org/10.1186/s12864-020-06783-9
Enable strengthening and protection of keystone and threatened species.
Build reference genome libraries for currently threatened species.*
Utilize genetic monitoring to determine best approaches for introducing and optimizing intrapopulation genetic variation.**
Design and build targeted gene-drives for introducing beneficial or adaptive traits into threatened species.
Engineer keystone and threatened species to be more adaptive or robust to climate change and anthropogenic impacts, such as through engineered microbiome robustness.
Enable introduction of genetic diversity into threatened species populations.
*Paez, S., Kraus, R. H. S., Shapiro, B., Gilbert, M. T. P., Jarvis, E. D., & VERTEBRATE GENOMES PROJECT CONSERVATION GROUP. (2022). Reference genomes for conservation. Science, 377(6604), 364–366. https://doi.org/10.1126/science.abm8127
**Kaczmarczyk, D. (2019). Techniques based on the polymorphism of microsatellite DNA as tools for conservation of endangered populations. Applied Ecology and Environmental Research, 17(2), 1599–1615. https://doi.org/10.15666/aeer/1702_15991615
- Phelps, M. P., Seeb, L. W., & Seeb, J. E. (2020). Transforming ecology and conservation biology through genome editing. Conservation Biology, 34(1), 54–65. https://doi.org/10.1111/cobi.13292
- Khan, H. A., Arif, I. A., Bahkali, A. H., Al Farhan, A. H., & Al Homaidan, A. A. (2008). Bayesian, maximum parsimony and UPGMA models for inferring the phylogenies of antelopes using mitochondrial markers. Evolutionary Bioinformatics Online, 4, 263–270. https://doi.org/10.4137/ebo.s934
- Arif, I. A., Khan, H. A., Bahkali, A. H., Al Homaidan, A. A., Al Farhan, A. H., Al Sadoon, M., & Shobrak, M. (2011). DNA marker technology for wildlife conservation. Saudi Journal of Biological Sciences, 18(3), 219–225. https://doi.org/10.1016/j.sjbs.2011.03.002
- Zimmerman, S. J., Aldridge, C. L., & Oyler-McCance, S. J. (2020). An empirical comparison of population genetic analyses using microsatellite and SNP data for a species of conservation concern. BMC Genomics, 21(1), 382. https://doi.org/10.1186/s12864-020-06783-9
- Bier, E. (2022). Gene drives gaining speed. Nature Reviews Genetics, 23(1), 5–22. https://doi.org/10.1038/s41576-021-00386-0
- Conklin, B. R. (2019). On the road to a gene drive in mammals. Nature, 566(7742), 43–45. https://doi.org/10.1038/d41586-019-00185-y