Special Issue "Metagenomics in Biodiscovery from Oceans"

Guest Editor
Dr. Jack A. Gilbert
¹ Argonne National Laboratory, 9700 South Cass Avenue, Argonne, IL 60439, USA
² Department of Ecology and Evolution, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637, USA
E-Mail: gilbertjack@gmail.com

Dear Colleagues,

Metagenomics has a lot to live up to. We as a community have made constant promises for the last ten years that metagenomics will open up the black box of the microbial world to enable the bounty of genetic diversity to be accessed. We made this promise because cultivation-independent processes can only access approximately 99% of microbes in a given ecosystem.  However, opening the black box has not rapidly translated into identifying the pharmaceutical bonanza we may have promised.

Primarily this is because of the drive towards sequencing platforms with higher throughput but shorter reads than traditional long-insert clone libraries (e.g. BACs, cosmids and fosmids), which yielded such great advances in our understanding of the microbial world (e.g. proteorhodopsin and archaeal ammonia oxidizers). A data-hungry community readily adopted the switch to cheaper, faster, but shorter sequences, which comprised our ability to identify functions, and assembly genetic operons that could be used to generate novel products.

However, metagenomics has recently turned over another leaf. Increases in sequencing depth now yield data from which whole genomes of currently uncultivable organisms can be re-assembled. In addition, novel culturing and microfludics approaches are taking advantage of advances in our understanding of the interactions between members of a microbial community to target specific microbial consortia with pertinent functions. It seems that long-standing promises will be fulfilled and metagenomics will be seen as a useful approach for biotechnological advance.

Dr. Jack A. Gilbert
Guest Editor

Submission

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• metagenomics
• metatranscriptomics
• microbial communities
• metabolic interactions
• functional networks
• interactome
• systems biology
• omics