title: Bacterial adaptation during chronic infection revealed by independent component analysis of transcriptomic data.
abstract: BACKGROUND
  Bacteria employ a variety of adaptation strategies during the course of chronic infections. Understanding bacterial adaptation can facilitate the identification of novel drug targets for better treatment of infectious diseases. Transcriptome profiling is a comprehensive and high-throughput approach for characterization of bacterial clinical isolates from infections. However, exploitation of the complex, noisy and high-dimensional transcriptomic dataset is difficult and often hindered by low statistical power.
  
  
  RESULTS
  In this study, we have applied two kinds of unsupervised analysis methods, principle component analysis (PCA) and independent component analysis (ICA), to extract and characterize the most informative features from transcriptomic dataset generated from cystic fibrosis (CF) Pseudomonas aeruginosa isolates. ICA was shown to be able to efficiently extract biological meaningful features from the transcriptomic dataset and improve clustering patterns of CF isolates. Decomposition of the transcriptomic dataset by ICA also facilitates gene identification and gene ontology enrichment.
  
  
  CONCLUSIONS
  Our results show that P. aeruginosa employs multiple patient-specific adaption strategies during the early stage infections while certain essential adaptations are evolved in parallel during the chronic infections.
authors.affiliation: Department of Systems Biology, Technical University of Denmark, DK-2800, Lyngby, Denmark. ly@bio.dtu.dk
authors.forename: Lei
authors.initials: L
authors.lastname: Yang
authors.forename: Martin Holm
authors.initials: MH
authors.lastname: Rau
authors.forename: Liang
authors.initials: L
authors.lastname: Yang
authors.forename: Niels
authors.initials: N
authors.lastname: Høiby
authors.forename: Søren
authors.initials: S
authors.lastname: Molin
authors.forename: Lars
authors.initials: L
authors.lastname: Jelsbak
mesh_terms: D000222:Adaptation, Physiological; D001426:Bacterial Proteins / Q000235:genetics; D003550:Cystic Fibrosis / Q000382:microbiology*; D015964:Gene Expression Regulation, Bacterial; D006801:Humans; D010802:Phylogeny; D011552:Pseudomonas Infections / Q000382:microbiology*; D011550:Pseudomonas aeruginosa / Q000145:classification / Q000235:genetics* / Q000302:isolation & purification / Q000502:physiology; D059467:Transcriptome
chemical_list: D001426:Bacterial Proteins