| Literature DB >> 32337704 |
Julie Bonne Køhler1, Carsten Jers1, Mériem Senissar1, Lei Shi2, Abderahmane Derouiche2, Ivan Mijakovic1,2.
Abstract
Protein phosphorylation regulates a large variety of biological processes in all living cells. In pathogenic bacteria, the study of serine, threonine, and tyrosine (Ser/Thr/Tyr) phosphorylation has shed light on the course of infectious diseases, from adherence to host cells to pathogen virulence, replication, and persistence. Mass spectrometry (MS)-based phosphoproteomics has provided global maps of Ser/Thr/Tyr phosphosites in bacterial pathogens. Despite recent developments, a quantitative and dynamic view of phosphorylation events that occur during bacterial pathogenesis is currently lacking. Temporal, spatial, and subpopulation resolution of phosphorylation data is required to identify key regulatory nodes underlying bacterial pathogenesis. Herein, we discuss how technological improvements in sample handling, MS instrumentation, data processing, and machine learning should improve bacterial phosphoproteomic datasets and the information extracted from them. Such information is expected to significantly extend the current knowledge of Ser/Thr/Tyr phosphorylation in pathogenic bacteria and should ultimately contribute to the design of novel strategies to combat bacterial infections.Entities:
Keywords: BY-kinases; Hanks kinases; Ser/Thr/Tyr phosphorylation; antibiotic kinase inhibitors; antibiotic resistance; host-pathogen interactions; machine learning; omics integration; pathogenic bacteria; phosphoproteomics
Year: 2020 PMID: 32337704 DOI: 10.1002/1873-3468.13797
Source DB: PubMed Journal: FEBS Lett ISSN: 0014-5793 Impact factor: 4.124