U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


Metagenomics Leads to New CRISPR-Cas Systems
Published: December 22, 2016
Posted: February 07, 2017

An artistic representation of the Tree of Life, with the many groups of bacteria and archaea at the upper left and eukaryotes, which include humans, at the lower right. Department of Energy Joint Genome Institute scientists are using gene-editing tools to explore microbial “dark matter.” [Artistic representation of Fig. 1 from Hug et al., “A new view of the tree of life.” Nature Microbiology 1 (2016). DOI: 10.1038/nmicrobiol.2016.48. Courtesy of Jill Banfield, University of California, Berkeley]

Researchers discover the first CRISPR-Cas9 system in archaea.

The Science
Using large amounts of metagenomic data generated by the Department of Energy’s Joint Genome Institute (DOE JGI), researchers analyzed 155 million protein coding genes from uncultivated microbial communities. This work led to the discovery of the first CRISPR- (clustered regularly interspaced short palindromic repeats) Cas9 protein in the archaeal domain, as well as two previously unknown simple bacterial CRISPR-Cas systems.

The Impact
Microbes play key roles in the planet’s cycles, and characterizing them helps researchers work toward solutions for energy and environmental challenges. Examining environmental microbial communities has enabled access to an unprecedented diversity of genomes and CRISPR-Cas systems that have many applications, including biological research. The combined computational-experimental approach that was successful in this study can be used to investigate nearly all environments where life exists.

Summary
Microbes heavily influence the planet’s cycles, but only a fraction have been identified. Characterizing the abundant but largely unknown extent of microbial diversity can help researchers develop solutions to energy and environmental challenges. In microbes, CRISPR-Cas systems provide a form of adaptive immunity, and these gene-editing tools are the foundation of versatile technologies revolutionizing research. Thus far, CRISPR-Cas technology has been based only on systems from isolated bacteria. In a study led by longtime DOE JGI collaborator Jill Banfield of the University of California, Berkeley, researchers discovered, for the first time, a CRISPR-Cas9 system in archaea, as well as simple CRISPR-Cas systems in uncultivable bacteria. To identify these new CRISPR-Cas systems, the team harnessed more than a decade’s worth of metagenomic data from samples sequenced and analyzed by DOE JGI, a DOE Office of Science user facility. The CasX and CasY proteins were found in bacteria from groundwater and sediment samples. The archaeal Cas9 was identified in samples taken from the Iron Mountain Superfund site as part of Banfield’s pioneering metagenomics work with DOE JGI. Both CasX and CasY are among some of the most compact systems ever identified. This application of metagenomics validates studies of CRISPR-Cas proteins using living organisms.

Contacts
Daniel Drell, Ph.D.
Program Manager
Biological Systems Science Division
Office of Biological and Environmental Research
Office of Science
U.S. Department of Energy
daniel.drell@science.doe.gov

David Lesmes, Ph.D.
Program Manager
Climate and Environmental Sciences Division
Office of Biological and Environmental Research
Office of Science
U.S. Department of Energy
david.lesmes@science.doe.gov

Jill Banfield
University of California, Berkeley
jbanfield@berkeley.edu

Funding
DOE Office of Science, National Science Foundation, EMBO, German Science Foundation, Paul Allen Institute, and Howard Hughes Medical Institute 

Publication
Burstein, D., et al., “New CRISPR-Cas systems from uncultivated microbes.” Nature (2016). [DOI: 10.1038/nature21059] (Reference link)

Related Links

Topic Areas:

  • Research Area: Subsurface Biogeochemical Research
  • Research Area: Genomic Analysis and Systems Biology
  • Research Area: Microbes and Communities
  • Research Area: DOE Joint Genome Institute (JGI)
  • Research Area: Computational Biology, Bioinformatics, Modeling

Division: SC-23.1 Climate and Environmental Sciences Division, BER,SC-23.2 Biological Systems Science Division, BER

 

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