Microbial Systems Group

Group within the Metagenomics Program.

Research in the Tringe group focuses on sequence-based approaches to studying microbial community assembly, function and dynamics.  Members of the group aid in communicating and interpreting sequencing results to collaborators in addition to performing collaborative and independent research in microbial community genomics.  Major foci of these research efforts are the roles of microbial communities in wetland carbon cycling and the interactions of plants with their associated microbiomes.

Microbiology of produced water recycling

Hydrocarbon extraction through methods such as hydraulic fracturing produces large volumes of chemically contaminated produced water that must be managed and disposed of appropriately.  There is interest in exploiting produced water for crop irrigation, especially in drought-prone areas, but treatment is necessary to remove the diverse chemical components, many of which are potentially toxic to plants, animals and humans. Biological treatment methods are effective at removing many contaminants found in produced water, but the microbial communities inhabiting the treatment reactors have been minimally characterized and thus exhibit variable performance that is challenging to optimize.

We aim to characterize the microbial communities found in bioreactors treating produced water and assign key activities to specific organisms, using metagenome sequencing, genome binning and metabolic reconstruction. Additionally, we would also cultivate and study individual members of these communities based on their predicted metabolisms, in order to construct stable defined consortia for produced water treatment.

Wetland greenhouse gas cycling

Wetlands occupy less than 10% of the Earth’s land surface but harbor up to a third of soil organic carbon.  Wetland preservation and restoration has the potential to sequester significant amounts of terrestrial carbon, but they can also produce the potent greenhouse gas methane, meaning different types of wetlands may serve as either greenhouse gas sources or sinks.  This uncertainty leads to considerable variability in predictions from climate models, both in the overall carbon budget and in how wetlands are expected to respond to climate change.

More accurate prediction of wetland carbon dynamics requires better understanding of the belowground microbial communities that are key to recycling or storing biomass carbon and producing greenhouse gases.  To gain insight into these systems we are applying microbial community genomics to wetland microbial communities in coastal wetlands across the San Francisco Bay / Delta region, including in-depth metagenome and metatranscriptome sequencing of natural and restored wetlands. (Watch the video here.) These studies are revealing organisms and genes involved in promoting or repressing greenhouse gas emissions, enabling a mechanistic understanding of belowground carbon cycling. Ultimately these findings are expected to aid in planning wetland restoration projects to maximize carbon storage. Download a copy of the JGI wetlands handout.

Plant-microbe interactions

The interactions of plants with microbial communities found in the endosphere and rhizosphere (within plant tissues and adjacent to the roots) have been shown to be critical to plant growth, health and disease resistance and manipulation of these organisms could potentially improve yields of both bioenergy and food crops.  Yet how these communities form and to what extent plants exert active control over the organisms involved is largely unknown, and genomic investigation of endophytic and rhizosphere microbes has been largely confined to culture-based methods due to both the challenges associated with soil metagenomics described above, and the close association with plant cells which harbor large and complex genomes.  In close collaboration with Jeff Dangl at the University of North Carolina, we are addressing these obstacles with high-throughput 16S profiling of rhizosphere and endophyte communities combined with single cell genomics, metagenomics and metatranscriptomics to characterize key plant-associated microbes, using Arabidopsis thaliana as a plant model system.  These investigations have revealed reproducible rhizosphere and endophyte community assemblage and plant genotype-specific associations with rhizosphere organisms. Ultimately, this work will allow us to identify genes, proteins and molecules involved in plant-microbe and microbe-microbe interactions in the plant root environment.

Group Members

Susannah Green Tringe, PI	Jinglie Zhou, Postdoc	Shwetha Acharya, Postdoc	Kyle Hartman, Postdoc
More about Susannah.	Jinglie received his Ph.D. degree in biological science from Auburn University. His research interests include metagenomic analysis, viral genome analysis, carbon cycling in wetlands and arbuscular mycorrhizal fungi associating with sorghum roots. He also has a background in bioinformatics, machine learning, data engineering and statistics.	Shwetha holds a Ph.D. in Urban Engineering from The University of Tokyo and specializes in water and wastewater microbiology. She is investigating microbial communities involved in biological treatment of produced water.	Kyle completed his Ph.D. at the University of Zürich and Agroscope, a Swiss federal research institute. His current research uses DNA sequence-based methods to investigate how nutrient and water stress influence host-microbe and microbe-microbe interactions in sorghum-associated microbial communities.

Mo Kaze, Affiliate	Xiaohui Li, Affiliate
Mo Kaze is finishing up her PhD at the University of California, Merced in Quantitative Systems Biology. Her DOE SCGSR Fellowship project at JGI examines carbon flux and microbial community structure in engineered interfaces between aquatic and terrestrial systems.	Xiaohui is a visiting scholar from Ningbo University, China. He is interested in mechanisms of interaction between plants and microorganisms. At JGI, he is investigating the rhizosphere microbiome of sorghum in order to clarify their roles in plant abiotic stress.

Group Alumni

• Dawn Chiniquy is a Project Scientist in the Deutschbauer lab at Lawrence Berkeley National Laboratory
• Devin Coleman-Derr is Principal Investigator at the Plant Gene Expression Center ([email protected])
• Filipa Godoy-Vitorino is currently Assistant Professor at the Inter American University of Puerto Rico ([email protected])
• Wyatt Hartman is a Soil Microbiome Data Scientist at Trace Genomics.
• Susanna Theroux is an Ecologist at the Southern California Coastal Water Research Project.
• Julien Tremblay is Bioinformatician at National Research Council Canada ([email protected])
• Qingpeng Zhang is a Staff Data Scientist at Illumina.

Publications

1. Sieber, CMK., AJ  Probst, A Sharrar, BC Thomas, M Hess, SG Tringe, JF Banfield.  Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy. Nature Microbiology, 3: 836-843, 2018. doi: 10.1038/s41564-018-0171-1. (Co-corresponding author)
2. Hartman, WH, R Ye, WR Horwath, SG Tringe. A genomic perspective on stoichiometric regulation of soil carbon cycling. ISME Journal 11: 2652-2665, 2017. doi:10.1038/ismej.2017.115
3. Singer, E, D Coleman-Derr, B Bowman, B Bushnell, E Gies, JF Cheng, A Copeland, S Hallam, SG Tringe, T Woyke (2016) High-resolution phylogenetic microbial community profiling. ISME Journal. doi: 10.1038/ismej.2015.249.
4. Tremblay, J, K Singh, A Fern, ES Kirton, S He, J Lee, T Woyke, F Chen, JL Dangl, SG Tringe (2015) Primer and platform effects on 16S rRNA tag sequencing. Frontiers in Microbiology 6: 771. doi: 10.3389/fmicb.2015.00771.
5. Nobu, MK, T Narihiro, C Rinke, Y Kamagata, SG Tringe, T Woyke, WT Liu (2015) Microbial dark matter ecogenomics reveals complex synergistic networks in a methanogenic bioreactor. ISME Journal 9: 1710-1722. doi: 10.1038/ismej.2014.256.
6. He, S, SA Malfatti, JW McFarland, FE Anderson, A Pati, M Huntemann, J Tremblay, T Glavina del Rio, M Waldrop, L Windham-Myers, SG Tringe (2015) Patterns in wetland microbial community composition and functional gene repertoire associated with methane emissions. Mbio 6: e00066-15. doi: 10.1128/mBio.00066-15.

   ORCiD link – https://orcid.org/0000-0001-6479-8427