Comparison of metagenomes from fermentation of various agroindustrial residues suggests a common model of community organization

Journal Article · 10 May 2023 · Frontiers in Bioengineering and Biotechnology

DOI: https://doi.org/10.3389/fbioe.2023.1197175 · OSTI ID:1973165

Myers, Kevin S. ^[1]; Ingle, Abel T. ^[1]; Walters, Kevin A. ^[1]; Fortney, Nathaniel W. ^[1]; Scarborough, Matthew J. ^[2]; Donohue, Timothy J. ^[1]; Noguera, Daniel R. ^[1]

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1. Great Lakes Bioenergy Research Center (GLBRC), Madison, WI (United States); University of Wisconsin, Madison, WI (United States)
2. University of Vermont, Burlington, VT (United States)

The liquid residue resulting from various agroindustrial processes is both rich in organic material and an attractive source to produce a variety of chemicals. Using microbial communities to produce chemicals from these liquid residues is an active area of research, but it is unclear how to deploy microbial communities to produce specific products from the different agroindustrial residues. To address this, we fed anaerobic bioreactors one of several agroindustrial residues (carbohydrate-rich lignocellulosic fermentation conversion residue, xylose, dairy manure hydrolysate, ultra-filtered milk permeate, and thin stillage from a starch bioethanol plant) and inoculated them with a microbial community from an acid-phase digester operated at the wastewater treatment plant in Madison, WI, United States. The bioreactors were monitored over a period of months and sampled to assess microbial community composition and extracellular fermentation products. We obtained metagenome assembled genomes (MAGs) from the microbial communities in each bioreactor and performed comparative genomic analyses to identify common microorganisms, as well as any community members that were unique to each reactor. Collectively, we obtained a dataset of 217 non-redundant MAGs from these bioreactors. This metagenome assembled genome dataset was used to evaluate whether a specific microbial ecology model in which medium chain fatty acids (MCFAs) are simultaneously produced from intermediate products (e.g., lactic acid) and carbohydrates could be applicable to all fermentation systems, regardless of the feedstock. MAGs were classified using a multiclass classification machine learning algorithm into three groups, organisms fermenting the carbohydrates to intermediate products, organisms utilizing the intermediate products to produce MCFAs, and organisms producing MCFAs directly from carbohydrates. This analysis revealed common biological functions among the microbial communities in different bioreactors, and although different microorganisms were enriched depending on the agroindustrial residue tested, the results supported the conclusion that the microbial ecology model tested was appropriate to explain the MCFA production potential from all agricultural residues.

• Research Organization: Univ. of Wisconsin, Madison, WI (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER); National Dairy Council; National Science Foundation (NSF)
• Grant/Contract Number: SC0018409; MSN214606; CBET-1803055
• OSTI ID: 1973165
• Alternate ID(s): OSTI ID: 2420791
• Journal Information: Frontiers in Bioengineering and Biotechnology, Vol. 11; ISSN 2296-4185
• Publisher: Frontiers Media S.A.Copyright Statement
• Country of Publication: United States
• Language: English