Correlation of proteomic and transcriptomic profiles of Staphylococcus aureus during the post-exponential phase of growth

  • Scherl A
  • François P
  • Bento M
 et al. 
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A combined proteomic and transcriptomic analysis of Staphylococcus aureus strain N315 was performed to study a sequenced strain at the system level. Total protein and membrane protein extracts were prepared and analyzed using various proteomic workflows including: 2-DE, SDS-PAGE combined with microcapillary LC-MALDI-MS/MS, and multidimensional liquid chromatography. The presence of a protein was then correlated with its respective transcript level from S. aureus cells grown under the same conditions. Gene-expression data revealed that 97% of the 2′596 ORFs were detected during the post-exponential phase. At the protein level, 23% of these ORFs (591 proteins) were identified. Correlation of the two datasets revealed that 42% of the identified proteins (248 proteins) were amongst the top 25% of genes with highest mRNA signal intensities, and 69% of the identified proteins (406 proteins) were amongst the top 50% with the highest mRNA signal intensities. The fact that the remaining 31% of proteins were not strongly expressed at the RNA level indicates either that some low-abundance proteins were identified or that some transcripts or proteins showed extended half-lives. The most abundant classes identified with the combined proteomic and transcriptomic approach involved energy production, translational activities and nucleotide transport, reflecting an active metabolism. The simultaneous large-scale analysis of transcriptomes and proteomes enables a global and holistic view of the S. aureus biology, allowing the parallel study of multiple active events in an organism. © 2004 Elsevier B.V. All rights reserved.

Author-supplied keywords

  • Microarray
  • Proteins
  • Proteome
  • Staphylococcus aureus
  • Transcriptome

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  • Alexander Scherl

  • Patrice François

  • Manuela Bento

  • Jacques M. Deshusses

  • Yvan Charbonnier

  • Véronique Converset

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