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PubMed Central
Other literature type . 2014
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Engineering microbial surfaces to degrade lignocellulosic biomass

Authors: Huang, Grace L; Anderson, Timothy D; Clubb, Robert T;

Engineering microbial surfaces to degrade lignocellulosic biomass

Abstract

Renewable lignocellulosic plant biomass is a promising feedstock from which to produce biofuels, chemicals, and materials. One approach to cost-effectively exploit this resource is to use consolidating bioprocessing (CBP) microbes that directly convert lignocellulose into valuable end products. Because many promising CBP-enabling microbes are non-cellulolytic, recent work has sought to engineer them to display multi-cellulase containing minicellulosomes that hydrolyze biomass more efficiently than isolated enzymes. In this review, we discuss progress in engineering the surfaces of the model microorganisms: Bacillus subtilis, Escherichia coli, and Saccharomyces cerevisiae. We compare the distinct approaches used to display cellulases and minicellulosomes, as well as their surface enzyme densities and cellulolytic activities. Thus far, minicellulosomes have only been grafted onto the surfaces of B. subtilis and S. cerevisiae, suggesting that the absence of an outer membrane in fungi and Gram-positive bacteria may make their surfaces better suited for displaying the elaborate multi-enzyme complexes needed to efficiently degrade lignocellulose.

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Keywords

Conservation of Natural Resources, Cell Membrane, Bioengineering, Review, Bacterial Physiological Phenomena, Protein Engineering, Lignin, Cellulosomes, Genetic Enhancement, Biofuels, Cellulases

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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).
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    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 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    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!
27
Top 10%
Average
Top 10%
Green
gold