Evidence map›Paper›PMID 36191042›Full record

ArticlePLoS computational biology2022

Density-dependent effects are the main determinants of variation in growth dynamics between closely related bacterial strains.

Sabrin Hilau, Sophia Katz, Tanya Wasserman, Ruth Hershberg, Yonatan Savir

Abstract read
In one paragraph

Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  6. A challenge test onHeliyon · 2024
    Article
  7. Rational Design of Live Biotherapeutic Products for the Prevention ofbioRxiv : the preprint server for biology · 2024
    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

5 authors.

Sabrin HilauDepartment of Physiology, Biophysics and Systems Biology, the Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.ORCID 0000-0001-8573-7703
Sophia KatzRachel & Menachem Mendelovitch Evolutionary Processes of Mutation & Natural Selection Research Laboratory, Department of Genetics and Developmental Biology, the Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.ORCID 0000-0001-9114-2466
Tanya WassermanDepartment of Physiology, Biophysics and Systems Biology, the Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.ORCID 0000-0003-0221-1891
Ruth HershbergRachel & Menachem Mendelovitch Evolutionary Processes of Mutation & Natural Selection Research Laboratory, Department of Genetics and Developmental Biology, the Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.
Yonatan SavirDepartment of Physiology, Biophysics and Systems Biology, the Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel.ORCID 0000-0002-5345-8491

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although closely related, bacterial strains from the same species show significant diversity in their growth and death dynamics. Yet, our understanding of the relationship between the kinetic parameters that dictate these dynamics is still lacking. Here, we measured the growth and death dynamics of 11 strains of Escherichia coli originating from different hosts and show that the growth patterns are clustered into three major classes with typical growth rates, maximal fold change, and death rates. To infer the underlying phenotypic parameters that govern the dynamics, we developed a phenomenological mathematical model that accounts not only for growth rate and its dependence on resource availability, but also for death rates and density-dependent growth inhibition. We show that density-dependent growth is essential for capturing the variability in growth dynamics between the strains. Indeed, the main parameter determining the dynamics is the typical density at which they slow down their growth, rather than the maximal growth rate or death rate. Moreover, we show that the phenotypic landscape resides within a two-dimensional plane spanned by resource utilization efficiency, death rate, and density-dependent growth inhibition. In this phenotypic plane, we identify three clusters that correspond to the growth pattern classes. Overall, our results reveal the tradeoffs between growth parameters that constrain bacterial adaptation.

Indexed as

Adaptation, PhysiologicalEscherichia coli

Identifiers

PMID36191042
PMCPMC9578580

What OpenQuestion holds

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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.