Demonstrating the microfluidic-based, mini-metagenomics approach on samples from hot springs shows how scientists can delve into microbes that can’t be cultivated in a laboratory.
At Stanford University, researchers have used a new microfluidic analysis system to extract 29 novel microbial genomes (the complete set of genetic material) from samples from two Yellowstone National Park hot springs. They extracted the genomes while still preserving single-cell resolution, meaning they knew which cells the genetic material came from. This work was made possible by a new technology that divides the sample to enable accurate analysis of a microbe’s genetic material. Specifically, it offers details on genome function and abundance. The work was enabled by the Emerging Technology Opportunity Program, a part of the U.S. Department of Energy Joint Genome Institute (DOE JGI), a DOE Office of Science user facility.
This new technology illuminates microbial “dark matter,” genetic information from the majority of the planet’s microbial diversity that has not been grown in a lab. These microbes live in locations as diverse as hot springs and deserts, underneath Antarctic ice and in acid mine drainage from Superfund sites. Tools that can determine microbes’ genetics and metabolism will have applications in fields ranging from bioenergy to biotechnology to environmental research.
There are more than 50,000 microbial genome sequences in the DOE JGI’s Integrated Microbial Genomes publicly accessible database, and many of them have been uncovered through the use of metagenomic sequencing and single-cell genomics. Despite their utility, these sequencing and genomics techniques have limits: single-cell genome amplifications are time-consuming, often incomplete, and metagenomic sequencing generally works best if the environmental sample is not too complex. In eLife, a team of researchers from Stanford University reports the development of a microfluidics-based, mini-metagenomics approach to mitigate these challenges. The technique starts with reducing the environmental sample’s complexity by separating it, using microfluidics, into 96 subsamples each with 5 to 10 cells. Then, the genomes in the cells in each subsample are amplified and libraries are created for sequencing these mini-metagenomes. The smaller subsamples can be held to single-cell resolution for statistical analyses. Co-occurrence patterns from many subsamples can also be used to perform sequence-independent genome binning. The technology was developed through resources provided by the DOE JGI’s Emerging Technologies Opportunity Program, which was launched in 2013. The aim of this program is to use these new technologies to tackle energy and environment applications, adding value to the high-throughput sequencing and analysis being done for DOE JGI users. The team validated the technique using a synthetic microbial community, and then applied it to samples from the Bijah and Mound hot springs at Yellowstone National Park. Among their findings was that the microbes at Mound Spring had higher potential to produce methane than the microbes from Bijah Spring. They also identified a microbial genome from Bijah Spring that could reduce nitrite to nitrogen. Applying this new technology to additional sample sites will add to the range of hitherto uncharacterized microbial capabilities with potential DOE mission applicability.
Daniel Drell, Ph.D.
Biological Systems Sciences Division
Office of Biological and Environmental Research
Office of Science
U.S. Department of Energy
Microbial Program Head
DOE Joint Genome Institute
Department of Bioengineering
Work was conducted by the U.S. Department of Energy (DOE) Joint Genome Institute, a DOE Office of Science user facility (contract DE-AC02-05CH11231). This work was also supported by the John Templeton Foundation, Stanford University, National Science Foundation, and the Burroughs Wellcome Fund.
F.B. Yu, P.C. Blainey, F. Schulz, T. Woyke, M.A. Horowitz, and S.R. Quake, “Microfluidic-based mini-metagenomics enables discovery of novel microbial lineages from complex environmental samples.” eLife 2017, e26580 (2017). [DOI: 10.7554/eLife.26580] (Reference link)
DOE Joint Genome Institute (JGI) news release: The DOE Joint Genome Institute Expands Capabilities via New Partnerships (JGI Emerging Technologies Opportunity Program)
DOE JGI webpage: Phylogenetic Diversity (a mission of the microbial program)
DOE JGI news release: Boldly Illuminating Biology’s “Dark Matter”
DOE JGI science highlight: Confirming Microbial Lineages Through Cultivation-Independent Means
DOE JGI science highlight: Elucidating Extremophilic “Microbial Dark Matter”
DOE JGI science highlight: Solving Microbial “Dark Matter” With Single-Cell Genomics
DOE JGI video: Why Mine Microbial Dark Matter?
DOE JGI video: Slava Epstein, Northeastern University, on the importance of studying microbial dark matter
DOE JGI video: Steve Quake at the 2014 DOE JGI Genomics of Energy & Environment Meeting
SC-23.2 Biological Systems Science Division, BER
BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER
Aug 24, 2019
New Approach for Studying How Microbes Influence Their Environment
A diverse group of scientists suggests a common framework and targeting of known microbial processes [more...]
Aug 08, 2019
Nutrient-Hungry Peatland Microbes Reduce Carbon Loss Under Warmer Conditions
Enzyme production in peatlands reduces carbon lost to respiration under future high temperatures. [more...]
Aug 05, 2019
Amazon Forest Response to CO2 Fertilization Dependent on Plant Phosphorus Acquisition
AmazonFACE Model Intercomparison. The Science Plant growth is dependent on the availabi [more...]
Jul 29, 2019
A Slippery Slope: Soil Carbon Destabilization
Carbon gain or loss depends on the balance between competing biological, chemical, and physical reac [more...]
Jul 15, 2019
Field Evaluation of Gas Analyzers for Measuring Ecosystem Fluxes
How gas analyzer type and correction method impact measured fluxes. The Science A side- [more...]
List all highlights (possible long download time)