title: Adaptation to environmental factors shapes the organization of regulatory regions in microbial communities.
abstract: BACKGROUND
  It has been shown in a number of metagenomic studies that the addition and removal of specific genes have allowed microbiomes to adapt to specific environmental conditions by losing and gaining specific functions. But it is not known whether and how the regulation of gene expression also contributes to adaptation.
  
  
  RESULTS
  We have here characterized and analyzed the metaregulome of three different environments, as well as their impact in the adaptation to particular variable physico-chemical conditions. For this, we have developed a computational protocol to extract regulatory regions and their corresponding transcription factors binding sites directly from metagenomic reads and applied it to three well known environments: Acid Mine, Whale Fall, and Waseca Farm. Taking the density of regulatory sites in promoters as a measure of the potential and complexity of gene regulation, we found it to be quantitatively the same in all three environments, despite their different physico-chemical conditions and species composition. However, we found that each environment distributes their regulatory potential differently across their functional space. Among the functions with highest regulatory potential in each niche, we found significant enrichment of processes related to sensing and buffering external variable factors specific to each environment, like for example, the availability of co-factors in deep sea, of oligosaccharides in soil and the regulation of pH in the acid mine.
  
  
  CONCLUSIONS
  These results highlight the potential impact of gene regulation in the adaptation of bacteria to the different habitats through the distribution of their regulatory potential among specific functions, and point to critical environmental factors that challenge the growth of any microbial community.
authors.forename: Leyden
authors.initials: L
authors.lastname: Fernandez
authors.forename: Josep M
authors.initials: JM
authors.lastname: Mercader
authors.forename: Mercè
authors.initials: M
authors.lastname: Planas-Fèlix
authors.affiliation: Joint IRB-BSC program on Computational Biology, BSC, Jordi Girona, 29, 08034 Barcelona, Spain. david.torrents@bsc.es.
authors.forename: David
authors.initials: D
authors.lastname: Torrents
mesh_terms: D000222:Adaptation, Physiological / Q000235:genetics; D001419:Bacteria / Q000235:genetics*; D001426:Bacterial Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D001665:Binding Sites; D004269:DNA, Bacterial / Q000737:chemistry / Q000378:metabolism; D017753:Ecosystem; D054892:Metagenome; D011401:Promoter Regions, Genetic; D011485:Protein Binding; D012045:Regulatory Sequences, Nucleic Acid / Q000235:genetics; D012988:Soil Microbiology; D014157:Transcription Factors / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D062065:Wastewater / Q000382:microbiology; D014871:Water Microbiology
chemical_list: D001426:Bacterial Proteins; D004269:DNA, Bacterial; D014157:Transcription Factors; D062065:Wastewater