Evidence map›Paper›PMID 38192220›Full record

ReviewEnvironmental microbiology reports2024

Genome-scale metabolic modelling of extremophiles and its applications in astrobiological environments.

Nuttapol Noirungsee, Sakunthip Changkhong, Kittiya Phinyo, Chutipong Suwannajak, Nahathai Tanakul, Sahutchai Inwongwan

Abstract readReview
In one paragraph

Review in Environmental microbiology reports, 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. JACS Au · 2025
    Article
  2. Article
  3. Review
  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

6 authors.

Nuttapol NoirungseeDepartment of Biology, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand.
Sakunthip ChangkhongDepartment of Biology, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand.
Kittiya PhinyoDepartment of Biology, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand.
Chutipong SuwannajakNational Astronomical Research Institute of Thailand, Chiang Mai, Thailand.
Nahathai TanakulNational Astronomical Research Institute of Thailand, Chiang Mai, Thailand.
Sahutchai InwongwanDepartment of Biology, Faculty of Science, Chiang Mai University, Chiang Mai, Thailand.ORCID 0009-0000-1386-6725

Funding

Chiang Mai University and National Astronomical Research Institute of Thailand
6 · The paper itself

Abstract

Metabolic modelling approaches have become the powerful tools in modern biology. These mathematical models are widely used to predict metabolic phenotypes of the organisms or communities of interest, and to identify metabolic targets in metabolic engineering. Apart from a broad range of industrial applications, the possibility of using metabolic modelling in the contexts of astrobiology are poorly explored. In this mini-review, we consolidated the concepts and related applications of applying metabolic modelling in studying organisms in space-related environments, specifically the extremophilic microbes. We recapitulated the current state of the art in metabolic modelling approaches and their advantages in the astrobiological context. Our review encompassed the applications of metabolic modelling in the theoretical investigation of the origin of life within prebiotic environments, as well as the compilation of existing uses of genome-scale metabolic models of extremophiles. Furthermore, we emphasize the current challenges associated with applying this technique in extreme environments, and conclude this review by discussing the potential implementation of metabolic models to explore theoretically optimal metabolic networks under various space conditions. Through this mini-review, our aim is to highlight the potential of metabolic modelling in advancing the study of astrobiology.

Indexed as

ExtremophilesExobiologyExtreme EnvironmentsMetabolic Networks and Pathways

Identifiers

PMID38192220
PMCPMC10866088

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.