Who We Are
AOML scientists use Omics as an umbrella term for the study of various fields such as genomics, metagenomics, metatranscriptomics, proteomics, metabolomics, epigenomics, and high-throughput amplicon sequencing. These emerging fields help us answer research questions about DNA, RNA, proteins, and other small molecules from organisms and the environment. With this information, we can identify mechanisms that keep marine systems healthy and productive.
The Five Pillars of AOML’s Omics Activities
The Omics program at AOML works to promote coral resilience, develop and transfer emerging technologies, advance Omics for fisheries and microbiome applications, and foster the bioinformatics and infrastructure capabilities upon which all Omics research and operations rely. This work engages coral, fisheries, and microbiology experts across the agency and through international engagement.
New study highlights major step forward in monitoring ocean health
May 23, 2022
In a major step forward for monitoring the biodiversity of marine systems, a new study published in Environmental DNA details how Monterey Bay Aquarium Research Institute (MBARI) and NOAA’s Atlantic Oceanographic & Meteorological Laboratory (AOML) researchers are using autonomous underwater robots to sample environmental DNA (eDNA). eDNA allows scientists to detect the presence of aquatic species from the tiny bits of genetic material they leave behind. This DNA soup offers clues about biodiversity changes in sensitive areas, the presence of rare or endangered species, and the spread of invasive species—all critical to understanding, promoting, and maintaining a healthy ocean.
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Coral Restoration Omics
Resilience and Resistance
Our research aims to identify what makes certain corals more resilient to stressors like heat, ocean acidification and disease. Understanding the molecular underpinnings of coral resilience and susceptibility by identifying resilient genotypes allows resource managers to be more effective with their restoration plans, especially when out-planting corals on the reef.
To Understand the Microbiome
There is a global need for low-cost indicators that measure the health of marine ecosystems. The microbiome forms the base of the food web and controls things like carbon, nutrients, metals and toxins – that means that we can’t truly understand the state of marine ecosystems until we have a good understanding of its microbiome. This understanding has allowed us to appreciate the role of microbes in all aspects of life, including ocean resiliency and marine resource management as well as and infection and disease.
To Detect Higher Trophic Levels
Because eDNA comes from cells that have been sloughed or excreted from a marine organism, eDNA offers a unique opportunity to detect what marine organisms have been in the area using only seawater samples. This can be especially useful in remote sensitive areas. It also offers the ability to detect multiple trophic levels from a single sample.
We are working on using environmental DNA (eDNA) – DNA from filtered seawater to understand what kinds of higher trophic level animals (like fish or mammals) are found in a particular area. This is done by capture of sloughed or excreted cells. eDNA is collected from seawater or sediment instead of from tissues so that samples can be collected without animal capture, tissue processing, or trawling through sensitive habitats.
Exploring Environmental DNA Video Series
Research involving Environmental DNA or “eDNA” is an exciting and emerging area of science that can help scientists to manage endangered species, invasive species, and monitor the biodiversity of ecosystems. Learn about environmental DNA through the “Exploring Environmental DNA” video series that covers what “eDNA” is, environmental DNA sampling technology developed at NOAA AOML, and a hands-on activity for DNA extraction.
Reducing Ship Time & Labor with Smart Sampling
NOAA AOML and our partners at the Monterey Bay Aquarium Research Institute (MBARI) are testing new underwater autonomous vehicles (AUVs or eAUVs) that can collect, filter, and process water samples so scientists can see what organisms inhabit a particular marine area. These AUVs are deployed from ships and small boats to provide a rapid response to measure environmental changes and increase sampling coverage without the added expense of deploying additional ships and crew.
Check out the Photo Story by our partners at the Great Lakes Environmental Research Laboratory.
AOML has developed inexpensive auto-samplers for the collection and preservation of environmental DNA (eDNA) to advance the application and utility of Omics-based technologies in marine science. These prototypes are intuitive, cost-effective autonomous samplers that automatically filter water and preserve DNA. These samplers will serve as a low-cost solution for sampling eDNA during periods when field collection is not feasible.
Our ability to effectively manage fisheries is limited by our understanding of fishery populations and their dependence on environmental conditions. Including genomic information into fisheries management may improve the decision-making process and thus the sustainability of fisheries.
How genomic information affects decisions will be evaluated using advanced population assessment techniques, and the Management Strategy Evaluation framework adopted by the National Marine Fisheries Service. AOML and the Southeast Fisheries Science Center (SEFSC) have formed a collaborative partnership with a clear path to transition results into fisheries management plans for the following projects:
- Using DNA Single Nucleotide Polymorphisms (DNA SNPs) to differentiate between eastern and western stocks of Atlantic bluefin tuna to inform stock assessments and management strategy evaluation.
- Using Restriction site Associated DNA Sequencing (ddRAD-Seq) to access the population structure of king mackerel to address pressing uncertainties affecting the stock assessment of this species.
- Empirical models are being used to assess whether microbiome data (sometimes termed “eDNA”) improves the ability to predict distributions of fish and to understand trophic interactions and habitat use.
Enhancing Omics Workforce & Infrastructure
Experimental Reef Laboratory
The Experimental Reef Laboratory located on the University of Miami’s Virginia Key campus at the Rosenstiel School of Marine and Atmospheric Sciences was completed in September of 2016. This unique experimental facility was designed to study the combined effect of heat stress and ocean acidification on corals so that scientists can see how coral organisms respond at the molecular level (DNA and RNA) under present and possible future conditions.
Rollover the dots to learn more or visit Experimental Reef Lab’s Page.
By building in-house facilities such as these, we can fulfill critical gaps in in equipment, increase efficiency and integrity of sample processing, and offer a place for partners (such as the Southeast Fisheries Science Center) and others to collaborate on new research projects.
Interpreting Omics Data with Bioinformatics
Genome-based techniques improve our ability to characterize and monitor ecosystems, including characterization environments with potential commercial potential. Examples include genomic signatures that mark natural resources such as oil and gas reserves, enzymes with commercial potential such as pharmaceutical or bioremediation potential, microbiomes that control the health of commercially valuable wild and aquaculture species, and indicators of anthropogenic stress which can forecast degraded environmental productivity.
However, our ability to supply bioinformatics expertise has not kept pace with the generation of sequence data, creating a data backlog and hindering transition of data collected into actionable information. To address this gap, AOML has been working to develop bioinformatics capacity, which is important to the success of all ‘omics projects. AOML has secured servers dedicated to bioinformatic analysis, hired young scientists to help with analysis, and created user groups (local and NOAA-wide) to provide support.
To facilitate analysis of amplicon datasets, a bioinformatics pipeline (“Tourmaline”) was created and added to AOML’s GitHub account. This automated amplicon workflow uses QIIME 2 and Snakemake and can run Deblur (single-end) or DADA2 (single-end and paired-end); steps can be manually adjusted if needed.
Publications & References
Thompson, L.R., M.F. Haroon, A.A. Shibl, M.J. Cahill, D.K. Ngugi, G.J. Williams, J.T. Morton, R. Knight, K.D. Goodwin & U. Stingl. (2019). Red Sea SAR11 and Prochlorococcus single-
cell genomes reflect globally distributed pangenomes. Appl Environ Microbiol, https://doi.org/10.1128/AEM. 00369-19.Franzosa, E.A., L.J. McIver, G. Rahnavard, L.R. Thompson, M. Schirmer, G. Weingart, K. Schwarzberg Lipson, R. Knight, J.G. Caporaso, N. Segata & C. Huttenhower. (2018). Species-level functional profiling of metagenomes and metatranscriptomes. Nat Meth, https://doi.org/10.1038/ s41592-018-0176-y.Thompson, L.R., J.G. Sanders, D. McDonald, A. Amir, J. Ladau, K.J. Locey, R.J. Prill, A. Tripathi, S.M. Gibbons, G.Ackermann, J.A. Navas-Molina, S. Janssen, E. Kopylova, Y. Va ́zquez-Baeza, A. Gonza ́lez, J.T. Morton, S. Mirarab, Z.Z. Xu, L. Jiang, M.F. Haroon, J. Kanbar, Q. Zhu, S. Song, T. Kosciolek, N.A. Bokulich, J. Lefler, C.J. Brislawn, G.C. Humphrey, S.M. Owens, J. Hampton-Marcell, D. Berg-Lyons, V. McKenzie, N. Fierer, J.A. Fuhrman, A. Clauset, R.L. Stevens, A. Shade, K.S. Pollard, K.D. Goodwin, J.K. Jansson, J.A. Gilbert, R. Knight & The Earth Microbiome Project Consortium. (2017). A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551:457–463, https://doi.org/10.1038/ nature24621.Goodwin, K.D., L.R. Thompson, B. Duarte, T. Kahlke, J.C. Marques & I. Cac ̧ador. (2017). DNA sequencing as atool to monitor marine ecological status. Front Mar Sci 4:107, https://doi.org/10. 3389/fmars.2017.00107.Amir, A., D. McDonald, J.A. Navas-Molina, E. Kopylova, J. Morton, Z.Z. Xu, E.P. Kightley, L.R. Thompson, E.R. Hyde, A. Gonzalez & R. Knight. (2017). Deblur rapidly resolves single-nucleotide community sequence patterns. mSystems 2(2): e00191–16, https://doi.org/10. 1128/mSystems.00191-16.
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