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ARS Home » Midwest Area » Peoria, Illinois » National Center for Agricultural Utilization Research » Bioenergy Research » Research » Publications at this Location » Publication #298548
Title: ChiNet uncovers rewired rewired transcription subnetworks in tolerant yeast for advanced biofuels conversion

Author
item ZHANG, YANG - New Mexico State University
item Liu, Zonglin
item SONG, MINGZHOU - New Mexico State University

Submitted to: Nucleic Acids Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/12/2015
Publication Date: 4/6/2015
Publication URL: http://nar.oxfordjournals.org/content/43/9/4393.short
Citation: Zhang, Y., Liu, Z.L., Song, M. 2015. ChiNet uncovers rewired transcription subnetworks in tolerant yeast for advanced biofuels conversion. Nucleic Acids Research. 43(9):4393-4407. doi: 10.1093/nar/gkv358.

Interpretive Summary: A tolerant industrial yeast Saccharomyces cerevisiae NRRL Y-50049 was developed to detoxify toxic compounds, including furfural and 5-hydroxymethylfurfural, liberated from biomass pretreatment for low-cost cellulosic ethanol production. Key genes and enzymes have been identified that are involved in detoxification but understanding the totality of events responsible for this adaptation is hampered by the lack of access from available bioinformatic tools. This research developed a computation program (ChiNet) to dissect the genetic events responsible for adaptation of yeast to fermentation toxins. Fundamental differences in the genome of the adapted yeast strain were revealed for the first time allowing the yeast to overcome the toxic chemical stress. New knowledge obtained by this research aids interpretation of stress tolerance mechanisms and future strain development for advanced biofuels production. The computation program developed (ChiNet) has potential applications for genome data analysis in similar biological systems.

Technical Abstract: Conventional differential gene expression analysis is insufficient to dissect altered gene interactions for adapted transcription regulatory networks that impact downstream molecular responses. Here we present comparative chi-square network analysis (ChiNet), a computational method, to uncover rewired network components for an adapted tolerant industrial strain Saccharomyces cerevisiae NRRL Y-50049 in overcoming toxic chemicals furfural and 5-hydroxymethylfurfural involved in lignocellulose-to-ethanol conversion, in comparison with its parental wild type Y-12632. Propagating upstream transcription regulation to downstream metabolic pathway responses, ChiNet measures both heterogeneity and homogeneity between two sets of regulatory networks based on transcriptome data. We found the gene regulatory networks of the adapted strain Y-50049 altered broadly at the genome level and involved at least 44 pathways interweaving with differential and conserved gene interactions. Highly adapted activation of YAP1 signature expression affected 39 downstream pathways under the chemical stress with the greatest impact on oxidative phosphorylation pathway.