BioEnergy Research

, Volume 7, Issue 4, pp 1481–1492 | Cite as

New Insights into Clostridia Through Comparative Analyses of Their 40 Genomes

  • Chuan Zhou
  • Qin Ma
  • Xizeng Mao
  • Bingqiang Liu
  • Yanbin YinEmail author
  • Ying XuEmail author


The Clostridium genus of bacteria contains the most widely studied biofuel-producing organisms such as Clostridium thermocellum and also some human pathogens, plus a few less characterized strains. Here, we present a comparative genomic analysis of 40 fully sequenced clostridial genomes, paying a particular attention to the biomass degradation ones. Our analysis indicates that some of the Clostridium botulinum strains may have been incorrectly classified in the current taxonomy and hence should be renamed according to the 16S ribosomal RNA (rRNA) phylogeny. A core-genome analysis suggests that only 169 orthologous gene groups are shared by all the strains, and the strain-specific gene pool consists of 22,668 genes, which is consistent with the fact that these bacteria live in very diverse environments and have evolved a very large number of strain-specific genes to adapt to different environments. Across the 40 genomes, 1.4–5.8 % of genes fall into the carbohydrate active enzyme (CAZyme) families, and 20 out of the 40 genomes may encode cellulosomes with each genome having 1 to 76 genes bearing the cellulosome-related modules such as dockerins and cohesins. A phylogenetic footprinting analysis identified cis-regulatory motifs that are enriched in the promoters of the CAZyme genes, giving rise to 32 statistically significant motif candidates.


Clostridium Comparative genomics Pan-genome Phylogeny CAZyme Motif 



This research was supported in part by the National Science Foundation (#NSF DEB-0830024 and NSF MCB-0958172), the US Department of Energy’s BioEnergy Science Center (BESC) grant through the Office of Biological and Environmental Research, and National Science Foundation of China (NSFC 61272016 and 61303084). The BioEnergy Science Center is a US Department of Energy Bioenergy Research Center supported by the Office of Biological and Environmental Research in the DOE Office of Science. Funding for open access charge was provided by the US Department of Energy’s BioEnergy Science Center (BESC).

Author Contribution

Y.Y. and Y.X. conceived the basic idea and planned the project. Q.M. and C.Z. carried out the experiments and analyzed the data. X.M. did the pathway enrichment analysis and proposed good suggestions to interpret the data in the view of biology. All authors edited the manuscript and approved the final manuscript. Q.M., C.Z., and X.M. contributed equally to this paper.

Supplementary material

12155_2014_9486_MOESM1_ESM.pdf (2 mb)
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12155_2014_9486_MOESM2_ESM.xlsx (163 kb)
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12155_2014_9486_MOESM3_ESM.xlsx (591 kb)
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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.School of MathematicsShandong UniversityJinanChina
  2. 2.Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology and Institute of BioinformaticsUniversity of GeorgiaAthensUSA
  3. 3.BioEnergy Science CenterOak RidgeUSA
  4. 4.Department of Biological SciencesNorthern Illinois UniversityDeKalbUSA
  5. 5.College of Computer Science and TechnologyJilin UniversityChangchunChina

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