In Silico Identification of Microbial Partners to Form Consortia with Anaerobic Fungi

Wilken, St.; Saxena, Mohan; Petzold, Linda; O’Malley, Michelle

doi:10.3390/pr6010007

Title: In Silico Identification of Microbial Partners to Form Consortia with Anaerobic Fungi

Journal Article · Mon Jan 15 00:00:00 EST 2018 · Processes

DOI:https://doi.org/10.3390/pr6010007· OSTI ID:1485152

Wilken, St. ^[1]; Saxena, Mohan ^[1]; Petzold, Linda ^[2]; O’Malley, Michelle ^[1]

Univ. of California, Santa Barbara, CA (United States). Department of Chemical Engineering
Univ. of California, Santa Barbara, CA (United States). Department of Computer Science

Lignocellulose is an abundant and renewable resource that holds great promise for sustainable bioprocessing. However, unpretreated lignocellulose is recalcitrant to direct utilization by most microbes. Current methods to overcome this barrier include expensive pretreatment steps to liberate cellulose and hemicellulose from lignin. Anaerobic gut fungi possess complex cellulolytic machinery specifically evolved to decompose crude lignocellulose, but they are not yet genetically tractable and have not been employed in industrial bioprocesses. Here, we aim to exploit the biomass-degrading abilities of anaerobic fungi by pairing them with another organism that can convert the fermentable sugars generated from hydrolysis into bioproducts. By combining experiments measuring the amount of excess fermentable sugars released by the fungal enzymes acting on crude lignocellulose, and a novel dynamic flux balance analysis algorithm, we screened potential consortia partners by qualitative suitability. Microbial growth simulations reveal that the fungus Anaeromyces robustus is most suited to pair with either the bacterium Clostridia ljungdahlii or the methanogen Methanosarcina barkeri—both organisms also found in the rumen microbiome. By capitalizing on simulations to screen six alternative organisms, valuable experimental time is saved towards identifying stable consortium members. This approach is also readily generalizable to larger systems and allows one to rationally select partner microbes for formation of stable consortia with non-model microbes like anaerobic fungi.

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Research Organization:: Univ. of California, Santa Barbara, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division

Grant/Contract Number:: SC0010352

OSTI ID:: 1485152

Journal Information:: Processes, Vol. 6, Issue 1; ISSN 2227-9717

Publisher:: Multidisciplinary Digital Publishing Institute (MDPI)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 12 works

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