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Engineering microbial consortia to enhance biomining and bioremediation

Authors: Brune, Karl D.; Bayer, Travis S.;

Engineering microbial consortia to enhance biomining and bioremediation

Abstract

In natural environments microorganisms commonly exist as communities of multiple species that are capable of performing more varied and complicated tasks than clonal populations. Synthetic biologists have engineered clonal populations with characteristics such as differentiation, memory, and pattern formation, which are usually associated with more complex multicellular organisms. The prospect of designing microbial communities has alluring possibilities for environmental, biomedical, and energy applications, and is likely to reveal insight into how natural microbial consortia function. Cell signaling and communication pathways between different species are likely to be key processes for designing novel functions in synthetic and natural consortia. Recent efforts to engineer synthetic microbial interactions will be reviewed here, with particular emphasis given to research with significance for industrial applications in the field of biomining and bioremediation of acid mine drainage.

Related Organizations
Keywords

Microbial Consortia, Microbiology, QR1-502, bioremediation, microbial consortia, synthetic microbial consortia, bioleaching, Synthetic Biology, synthetic biology, acid mine drainage, biomining

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    146
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
146
Top 1%
Top 10%
Top 10%
Green
gold