Phylogenomics and genetic analysis of solvent-producing Clostridium species

Rasmus O. Jensen, Frederik Schulz, Simon Roux, Dawn M. Klingeman, Wayne P. Mitchell, Daniel Udwary, Sarah Moraïs, Vinicio Reynoso, James Winkler, Shilpa Nagaraju, Sashini De Tissera, Nicole Shapiro, Natalia Ivanova, T. B.K. Reddy, Itzhak Mizrahi, Sagar M. Utturkar, Edward A. Bayer, Tanja Woyke, Nigel J. Mouncey, Michael C. JewettSéan D. Simpson, Michael Köpke, David T. Jones, Steven D. Brown

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The genus Clostridium is a large and diverse group within the Bacillota (formerly Firmicutes), whose members can encode useful complex traits such as solvent production, gas-fermentation, and lignocellulose breakdown. We describe 270 genome sequences of solventogenic clostridia from a comprehensive industrial strain collection assembled by Professor David Jones that includes 194 C. beijerinckii, 57 C. saccharobutylicum, 4 C. saccharoperbutylacetonicum, 5 C. butyricum, 7 C. acetobutylicum, and 3 C. tetanomorphum genomes. We report methods, analyses and characterization for phylogeny, key attributes, core biosynthetic genes, secondary metabolites, plasmids, prophage/CRISPR diversity, cellulosomes and quorum sensing for the 6 species. The expanded genomic data described here will facilitate engineering of solvent-producing clostridia as well as non-model microorganisms with innately desirable traits. Sequences could be applied in conventional platform biocatalysts such as yeast or Escherichia coli for enhanced chemical production. Recently, gene sequences from this collection were used to engineer Clostridium autoethanogenum, a gas-fermenting autotrophic acetogen, for continuous acetone or isopropanol production, as well as butanol, butanoic acid, hexanol and hexanoic acid production.

Original languageEnglish
Article number432
JournalScientific data
Issue number1
StatePublished - 1 Dec 2024

ASJC Scopus subject areas

  • Information Systems
  • Education
  • Library and Information Sciences
  • Statistics and Probability
  • Computer Science Applications
  • Statistics, Probability and Uncertainty


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