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Open Access Research

Global transcriptome analysis of Clostridium thermocellum ATCC 27405 during growth on dilute acid pretreated Populus and switchgrass

Charlotte M Wilson12, Miguel Rodriguez12, Courtney M Johnson12, Stanton L Martin3, Tzu Ming Chu3, Russ D Wolfinger3, Loren J Hauser12, Miriam L Land12, Dawn M Klingeman12, Mustafa H Syed12, Arthur J Ragauskas24, Timothy J Tschaplinski12, Jonathan R Mielenz12 and Steven D Brown12*

Author Affiliations

1 Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA

2 BioEnergy Science Center, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA

3 SAS Institute, Cary, NC 27513, USA

4 School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA 30332, USA

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Biotechnology for Biofuels 2013, 6:179  doi:10.1186/1754-6834-6-179

Published: 2 December 2013

Abstract

Background

The thermophilic anaerobe Clostridium thermocellum is a candidate consolidated bioprocessing (CBP) biocatalyst for cellulosic ethanol production. The aim of this study was to investigate C. thermocellum genes required to ferment biomass substrates and to conduct a robust comparison of DNA microarray and RNA sequencing (RNA-seq) analytical platforms.

Results

C. thermocellum ATCC 27405 fermentations were conducted with a 5 g/L solid substrate loading of either pretreated switchgrass or Populus. Quantitative saccharification and inductively coupled plasma emission spectroscopy (ICP-ES) for elemental analysis revealed composition differences between biomass substrates, which may have influenced growth and transcriptomic profiles. High quality RNA was prepared for C. thermocellum grown on solid substrates and transcriptome profiles were obtained for two time points during active growth (12 hours and 37 hours postinoculation). A comparison of two transcriptomic analytical techniques, microarray and RNA-seq, was performed and the data analyzed for statistical significance. Large expression differences for cellulosomal genes were not observed. We updated gene predictions for the strain and a small novel gene, Cthe_3383, with a putative AgrD peptide quorum sensing function was among the most highly expressed genes. RNA-seq data also supported different small regulatory RNA predictions over others. The DNA microarray gave a greater number (2,351) of significant genes relative to RNA-seq (280 genes when normalized by the kernel density mean of M component (KDMM) method) in an analysis of variance (ANOVA) testing method with a 5% false discovery rate (FDR). When a 2-fold difference in expression threshold was applied, 73 genes were significantly differentially expressed in common between the two techniques. Sulfate and phosphate uptake/utilization genes, along with genes for a putative efflux pump system were some of the most differentially regulated transcripts when profiles for C. thermocellum grown on either pretreated switchgrass or Populus were compared.

Conclusions

Our results suggest that a high degree of agreement in differential gene expression measurements between transcriptomic platforms is possible, but choosing an appropriate normalization regime is essential.

Keywords:
Genome; Reannotation; Biomass; Elemental composition; RNA-seq; Microarray; Phosphate; Normalization; Transcriptomics