Article ; Online: Experimental measurement and computational prediction of bacterial Hanks-type Ser/Thr signaling system regulatory targets.
2024
Abstract: Bacteria possess diverse classes of signaling systems that they use to sense and respond to their environments and execute properly timed developmental transitions. One widespread and evolutionarily ancient class of signaling systems are the Hanks-type ... ...
| Abstract | Bacteria possess diverse classes of signaling systems that they use to sense and respond to their environments and execute properly timed developmental transitions. One widespread and evolutionarily ancient class of signaling systems are the Hanks-type Ser/Thr kinases, also sometimes termed "eukaryotic-like" due to their homology with eukaryotic kinases. In diverse bacterial species, these signaling systems function as critical regulators of general cellular processes such as metabolism, growth and division, developmental transitions such as sporulation, biofilm formation, and virulence, as well as antibiotic tolerance. This multifaceted regulation is due to the ability of a single Hanks-type Ser/Thr kinase to post-translationally modify the activity of multiple proteins, resulting in the coordinated regulation of diverse cellular pathways. However, in part due to their deep integration with cellular physiology, to date, we have a relatively limited understanding of the timing, regulatory hierarchy, the complete list of targets of a given kinase, as well as the potential regulatory overlap between the often multiple kinases present in a single organism. In this review, we discuss experimental methods and curated datasets aimed at elucidating the targets of these signaling pathways and approaches for using these datasets to develop computational models for quantitative predictions of target motifs. We emphasize novel approaches and opportunities for collecting data suitable for the creation of new predictive computational models applicable to diverse species. |
|---|---|
| Language | English |
| Publishing date | 2024-01-03 |
| Publishing country | England |
| Document type | Journal Article ; Review |
| ZDB-ID | 619315-8 |
| ISSN | 1365-2958 ; 0950-382X |
| ISSN (online) | 1365-2958 |
| ISSN | 0950-382X |
| DOI | 10.1111/mmi.15220 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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