Evidence map›Paper›PMID 36088344›Full record

ArticleNature communications2022

A multi-state dynamic process confers mechano-adaptation to a biological nanomachine.

Navish Wadhwa, Alberto Sassi, Howard C Berg, Yuhai Tu

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Motility inMicroorganisms · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Article
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

4 authors.

Navish Wadhwa *Department of Physics, Arizona State University, Tempe, AZ, 85287, USA. Navish.Wadhwa@asu.edu.ORCID 0000-0002-3514-5256
Alberto Sassi *IBM T. J. Watson Research Center, Yorktown Heights, NY, 10598, USA.ORCID 0000-0002-1269-4746
Howard C BergDepartment of Molecular and Cellular Biology, Harvard University, Cambridge, MA, 02138, USA.
Yuhai TuIBM T. J. Watson Research Center, Yorktown Heights, NY, 10598, USA. yuhai@us.ibm.com.ORCID 0000-0002-4589-981X

Funding

Molecular Mechanisms and Biochemical Circuits for Adaptation in Biological SystemsR35GM131734 · NIGMS · IBM THOMAS J. WATSON RESEARCH CENTER · PI TU, YUHAI · 2019 to 2024
$1.8M
Identifying the mechanisms of mechanosensing by the bacterial flagellar motor K99GM134124 · NIGMS · HARVARD UNIVERSITY · PI WADHWA, NAVISH · 2020 to 2021
$200k
NIGMS NIH HHS K99 GM134124NIGMS NIH HHS R35 GM131734
6 · The paper itself

Abstract

Adaptation is a defining feature of living systems. The bacterial flagellar motor adapts to changes in the external mechanical load by adding or removing torque-generating (stator) units. But the molecular mechanism behind this mechano-adaptation remains unclear. Here, we combine single motor eletrorotation experiments and theoretical modeling to show that mechano-adaptation of the flagellar motor is enabled by multiple mechanosensitive internal states. Dwell time statistics from experiments suggest the existence of at least two bound states with a high and a low unbinding rate, respectively. A first-passage-time analysis of a four-state model quantitatively explains the experimental data and determines the transition rates among all four states. The torque generated by bound stator units controls their effective unbinding rate by modulating the transition between the bound states, possibly via a catch bond mechanism. Similar force-mediated feedback enabled by multiple internal states may apply to adaptation in other macromolecular complexes.

Indexed as

FlagellaMolecular Motor ProteinsAcclimatizationBacteriaTorqueMolecular Motor Proteins

Identifiers

PMID36088344
PMCPMC9464220

What OpenQuestion holds

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Registered trials

None linked

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.