From Bioinformatics Core Wiki

Title Integration of multi-omics data of a genome-reduced bacterium: Prevalence of post-transcriptional regulation and its correlation with protein abundances

Authors Wei-Hua Chen, Vera van Noort, Maria Lluch-Senar, Marco L. Hennrich, Judith A. H. Wodke, Eva Yus, Andreu Alibés, Guglielmo Roma, Daniel R. Mende, Christina Pesavento, Athanasios Typas, Anne-Claude Gavin, Luis Serrano, Peer Bork
Date 2016-02-18

Publisher Nucleic Acids Research
DOI 10.1093/nar/gkw004
Tag Amino Acid Sequence, Bacterial Proteins, Base Sequence, Cluster Analysis, Gene Expression Profiling, Gene Expression Regulation, Genome, Bacterial, Genomics, Molecular Sequence Annotation, Molecular Sequence Data, Mycoplasma pneumoniae, Protein Processing, Post-Translational, Proteome, Proteomics, RNA, Untranslated, Systems Biology

We developed a comprehensive resource for the genome-reduced bacterium Mycoplasma pneumoniae comprising 1748 consistently generated '-omics' data sets, and used it to quantify the power of antisense non-coding RNAs (ncRNAs), lysine acetylation, and protein phosphorylation in predicting protein abundance (11%, 24% and 8%, respectively). These factors taken together are four times more predictive of the proteome abundance than of mRNA abundance. In bacteria, post-translational modifications (PTMs) and ncRNA transcription were both found to increase with decreasing genomic GC-content and genome size. Thus, the evolutionary forces constraining genome size and GC-content modify the relative contributions of the different regulatory layers to proteome homeostasis, and impact more genomic and genetic features than previously appreciated. Indeed, these scaling principles will enable us to develop more informed approaches when engineering minimal synthetic genomes.

Bioinformatics Core Facility @ CRG — 2011-2019