Identification of Genes Involved in the Degradation of Lignocellulose Using Comparative Transcriptomics

Abstract

Lignocellulosic biomass represents an abundant, renewable resource that can be used to produce biofuels, low-cost livestock feed, and high-value chemicals. The potential of this resource has led to intensive research efforts to develop cost effective methods to breakdown lignocellulose. The efficiency with which the anaerobic fungi (phylum Neocallimastigomycota) degrade plant biomass is well recognized and in recent years has received renewed interest. Transcriptomics has been used to identify enzymes that are expressed by these fungi and are involved in the degradation of a range of lignocellulose feedstocks. The transcriptome is the entire complement of coding and noncoding RNA transcripts that are expressed by a cell under a particular set of conditions. Monitoring changes in gene expression can provide fundamental information about the biology of an organism. Here we outline a general methodology that will enable researchers to conduct comparative transcriptomic studies with the goal of identifying enzymes involved in the degradation of the plant cell wall. The method described here includes growth of fungal cultures, isolation and sequencing of RNA, and a basic description of data analysis for bioinformatic identification of differentially expressed transcripts.

Evaluation of the lignocellulose degradation potential of Mediterranean forests soil microbial communities through diversity and targeted functional metagenomics

“…Taking into consideration the aforementioned distribution of bacterial communities in the two forests and the AA2 peroxidases sequences recovered, it is likely that interactions among microorganisms may affect the fitness of either fungi or bacteria depending on whether the organisms possess the enzymes required to degrade lignin (mainly white-rot fungi) or hemicelluloses and cellulose (Basidiomycota, Ascomycota, Bacteria). Such effects have been demonstrated by secretome and transcriptomic studies on soil microbiomes (Kellner et al, 2014;Gruninger et al, 2017;Moraes et al, 2018;Peng et al, 2018;Wymelenberg et al, 2020).…”