BMC Genomics (Jan 2018)

RNAseq analysis of α-proteobacterium Gluconobacter oxydans 621H

  • Angela Kranz,
  • Tobias Busche,
  • Alexander Vogel,
  • Björn Usadel,
  • Jörn Kalinowski,
  • Michael Bott,
  • Tino Polen

DOI
https://doi.org/10.1186/s12864-017-4415-x
Journal volume & issue
Vol. 19, no. 1
pp. 1 – 17

Abstract

Read online

Abstract Background The acetic acid bacterium Gluconobacter oxydans 621H is characterized by its exceptional ability to incompletely oxidize a great variety of carbohydrates in the periplasm. The metabolism of this α-proteobacterium has been characterized to some extent, yet little is known about its transcriptomes and related data. In this study, we applied two different RNAseq approaches. Primary transcriptomes enriched for 5′-ends of transcripts were sequenced to detect transcription start sites, which allow subsequent analysis of promoter motifs, ribosome binding sites, and 5´-UTRs. Whole transcriptomes were sequenced to identify expressed genes and operon structures. Results Sequencing of primary transcriptomes of G. oxydans revealed 2449 TSSs, which were classified according to their genomic context followed by identification of promoter and ribosome binding site motifs, analysis of 5´-UTRs including validation of predicted cis-regulatory elements and correction of start codons. 1144 (41%) of all genes were found to be expressed monocistronically, whereas 1634 genes were organized in 571 operons. Together, TSSs and whole transcriptome data were also used to identify novel intergenic (18), intragenic (328), and antisense transcripts (313). Conclusions This study provides deep insights into the transcriptional landscapes of G. oxydans. The comprehensive transcriptome data, which we made publicly available, facilitate further analysis of promoters and other regulatory elements. This will support future approaches for rational strain development and targeted gene expression in G. oxydans. The corrections of start codons further improve the high quality genome reference and support future proteome analysis.

Keywords