Unraveling a lignocellulose-decomposing bacterial consortium from soil associated with dry sugarcane straw by genomic-centered metagenomics - Weiss, Bruno [UNESP]; Souza, Anna Carolina Oliveira [UNESP]; Constancio, Milena Tavares Lima [UNESP]; Alvarenga, Danillo Oliveira [UNESP]; Pylro, Victor S.; Alves, Lucia M. Carareto [UNESP]; Varani, Alessandro M. [UNESP] (MDPI, 2021)
Second-generation biofuel production is in high demand, but lignocellulosic biomass’ complexity impairs its use due to the vast diversity of enzymes necessary to execute the complete saccharification. In nature, lignocellulose can be rapidly deconstructed due to the division of biochemical labor effectuated in bacterial communities. Here, we analyzed the lignocellulolytic potential of a bacterial consortium obtained from soil and dry straw leftover from a sugarcane milling plant. This consortium was cultivated for 20 weeks in aerobic conditions using sugarcane bagasse as a sole carbon source. Scanning electron microscopy and chemical analyses registered modification of the sugarcane fiber’s appearance and biochemical composition, indicating that this consortium can deconstruct cellulose and hemicellulose but no lignin. A total of 52 metagenome-assembled genomes from eight bacterial classes (Actinobacteria, Alphaproteobacteria, Bacilli, Bacteroidia, Cytophagia, Gammaproteobacteria, Oligoflexia, and Thermoleophilia) were recovered from the consortium, in which ~46% of species showed no relevant modification in their abundance during the 20 weeks of cultivation, suggesting a mostly stable consortium. Their CAZymes repertoire indicated that many of the most abundant species are known to deconstruct lignin (e.g., Chryseobacterium) and carry sequences related to hemicellulose and cellulose deconstruction (e.g., Chitinophaga, Niastella, Niabella, and Siphonobacter). Taken together, our results unraveled the bacterial diversity, enzymatic potential, and effectiveness of this lignocellulose-decomposing bacterial consortium.
Keywords: Biofuels; Biotechnology; Community dynamics; Lignocellulose; Metabolic modeling