4.7 Article

Gene coexpression network analysis reveals a novel metabolic mechanism ofClostridium acetobutylicumresponding to phenolic inhibitors from lignocellulosic hydrolysates

Journal

BIOTECHNOLOGY FOR BIOFUELS
Volume 13, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s13068-020-01802-z

Keywords

Phenolic compounds; Clostridium acetobutylicum; Weighted gene co-expression network analysis; RNA sequencing; Acetone-Butanol-Ethanol; Lignocellulosic hydrolysates

Funding

  1. National Natural Science Foundation of China [31800072, 31970084, 31800126]
  2. Open Fund of Ministry of Education Key Laboratory of Molecular Microbiology and Technology, Nankai University

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Background Lignocellulosic biomass is a promising resource of renewable biochemicals and biofuels. However, the presence of inhibitors existing in lignocellulosic hydrolysates (LCH) is a great challenge to acetone-butanol-ethanol (ABE) fermentation byClostridium acetobutylicum. In particular, phenolic compounds (PCs) from LCH severely block ABE production even at low concentrations. Thus, it is urgent to gain insight into the intracellular metabolic disturbances caused by phenolic inhibitors and elucidate the underlying mechanisms to identify key industrial bottlenecks that undermine efficient ABE production. Results In this study, a time-course of ABE fermentation byC. acetobutylicumin the presence of four typical PCs (syringaldehyde, vanillin, ferulic acid, andp-coumaric acid) was characterized, respectively. Addition of PCs caused different irreversible effects on ABE production. Specifically, syringaldehyde showed the greatest inhibition to butanol production, followed by vanillin, ferulic acid, andp-coumaric acid. Subsequently, a weighted gene co-expression network analysis (WGCNA) based on RNA-sequencing data was applied to identify metabolic perturbations caused by four LCH-derived PCs, and extract the gene modules associated with extracellular fermentation traits. The hub genes in each module were subjected to protein-protein interaction analysis and enrichment analysis. The results showed that functional modules were PC-dependent and shared some unique features. Specifically,p-coumaric acid caused the most extensive transcriptomic disturbances, particularly affecting the gene expressions of ribosome proteins and the assembly of flagella, DNA replication, repair, and recombination; the addition of syringaldehyde caused significant metabolic disturbances on the gene expressions of ribosome proteins, starch and sucrose metabolism; vanillin mainly disturbed purine metabolism, sporulation and signal transduction; and ferulic acid caused a metabolic disturbance on glycosyl transferase-related gene expressions. Conclusion This study uncovers novel insights into the inhibitory mechanisms of PCs for the first time and provides guidance for future metabolic engineering efforts, which establishes a powerful foundation for the development of phenol-tolerant strains ofC. acetobutylicumfor economically sustainable ABE production with high productivity from lignocellulosic biomass.

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