Evidence map›Paper›PMID 42034725›Full record

ArticleApplied microbiology and biotechnology2026

Understanding time-growth rate relationship for slow-growing microbial cells in retentostat culturing systems.

Beatriz Aranda, Juan M Gonzalez

Abstract read
In one paragraph

Article in Applied microbiology and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Beatriz ArandaInstituto de Recursos Naturales y Agrobiologia de Sevilla, Consejo Superior de Investigaciones Cientificas (IRNAS-CSIC), Seville, Spain.
Juan M GonzalezInstituto de Recursos Naturales y Agrobiologia de Sevilla, Consejo Superior de Investigaciones Cientificas (IRNAS-CSIC), Seville, Spain. juan.gonzalez@csic.es.

Funding

Consejería de Economía, Innovación, Ciencia y Empleo, Junta de Andalucía P20_00774Ministerio de Ciencia, Innovación y Universidades PID2020-119373GB-I00Ministerio de Ciencia, Innovación y Universidades PRE2021-100213
6 · The paper itself

Abstract

Generally, microorganisms in nature are severely growth-limited because of nutrient availability, competition, or physico-chemical parameters. To simulate these growing conditions, the use of continuous culturing systems has been proposed. One modification of these systems is the so-called retentostat. It corresponds to a system closed to cells and open to nutrients, and a nutrient is limiting growth. In this system, cells are forced to reduce progressively their growth rate as a result of increasing biomass sharing the same resources. In these systems, near-zero growth rates (corresponding to long doubling times) can be achieved within relatively reasonable time frames. Nevertheless, in these systems, the relationship between growth rate and time remains to be further analyzed. Herein, we evaluate a retentostat culturing system for different prokaryotic species. We established a general relationship between growth rate and incubation time. This allows us to easily estimate either the growth rate reached after a given incubation time or the time required to obtain cells at a specific slow growth rate. The results suggested progressive adaptation of cells at decreasing growth rates. This contribution simplifies estimates for incubation time-dependent growth rates and shows a retentostat as a species-independent culturing system where growth rates depend on time and dilution rate.

Indexed as

BacteriaBacteriological TechniquesBioreactorsBiomassCulture MediaTime FactorsCulture MediaContinuous cultureGrowth limitationGrowth rateNear-zero growthNutrient-limiting growthRetentostat

Identifiers

PMID42034725
PMCPMC13246870

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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.