Evidence map›Paper›PMID 38167835›Full record

ReviewMolecular microbiology2024

Experimental measurement and computational prediction of bacterial Hanks-type Ser/Thr signaling system regulatory targets.

Noam Grunfeld, Erel Levine, Elizabeth Libby

Abstract readReview
In one paragraph

Review in Molecular microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Noam GrunfeldDepartment of Bioengineering, Northeastern University, Boston, Massachusetts, USA.
Erel LevineDepartment of Bioengineering, Northeastern University, Boston, Massachusetts, USA.
Elizabeth LibbyDepartment of Bioengineering, Northeastern University, Boston, Massachusetts, USA.ORCID 0000-0003-2374-1015

Funding

Physiological and Developmental Role of Bacterial Ser/Thr KinasesR35GM147429 · NIGMS · NORTHEASTERN UNIVERSITY · PI Elizabeth Libby · 2022 to 2026
$2.0M
National Science Foundation MCB1946944NIGMS NIH HHS R35 GM147429NIH HHS R35GM147429
6 · The paper itself

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.

Indexed as

BacteriaBacterial ProteinsProtein Serine-Threonine KinasesSignal TransductionComputational BiologyGene Expression Regulation, BacterialPhosphorylationProtein Processing, Post-TranslationalBacterial ProteinsProtein Serine-Threonine Kinasescomputational modelsphosphoproteomicsphosphorylationSer/Thr kinaseSer/Thr phosphatase

Identifiers

PMID38167835
PMCPMC11219531

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.