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      Quantitative proteome and transcriptome analysis of the archaeon Thermoplasma acidophilum cultured under aerobic and anaerobic conditions.

      Journal of Proteome Research
      Aerobiosis, Anaerobiosis, Bacterial Proteins, analysis, classification, metabolism, Chromatography, Liquid, Gene Expression Profiling, methods, Gene Expression Regulation, Bacterial, physiology, Mass Spectrometry, Metabolic Networks and Pathways, Oligonucleotide Array Sequence Analysis, Oxygen, Proteome, chemistry, Proteomics, RNA, Bacterial, RNA, Messenger, Thermoplasma, genetics

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          Abstract

          A comparative proteome and transcriptome analysis of Thermoplasma acidophilum cultured under aerobic and anaerobic conditions has been performed. One-thousand twenty-five proteins were identified covering 88% of the cytosolic proteome. Using a label-free quantitation method, we found that approximately one-quarter of the identified proteome (263 proteins) were significantly induced (>2 fold) under anaerobic conditions. Thirty-nine macromolecular complexes were identified, of which 28 were quantified and 15 were regulated under anaerobiosis. In parallel, a whole genome cDNA microarray analysis was performed showing that the expression levels of 445 genes were influenced by the absence of oxygen. Interestingly, more than 40% of the membrane protein-encoding genes (145 out of 335 ORFs) were up- or down-regulated at the mRNA level. Many of these proteins are functionally associated with extracellular protein or peptide degradation or ion and amino acid transport. Comparison of the transcriptome and proteome showed only a weak positive correlation between mRNA and protein expression changes, which is indicative of extensive post-transcriptional regulatory mechanisms in T. acidophilum. Integration of transcriptomics and proteomics data generated hypotheses for physiological adaptations of the cells to anaerobiosis, and the quantitative proteomics data together with quantitative analysis of protein complexes provide a platform for correlation of MS-based proteomics studies with cryo-electron tomography-based visual proteomics approaches.

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