Evidence map›Paper›PMID 31072303›Full record

ArticleBMC bioinformatics2019

System-level analysis of metabolic trade-offs during anaerobic photoheterotrophic growth in Rhodopseudomonas palustris.

Ali Navid, Yongqin Jiao, Sergio Ernesto Wong, Jennifer Pett-Ridge

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
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

13 citing papers in PubMed, 34 citations in OpenAlex.

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  10. Curating COBRA Models of Microbial Metabolism.Methods in molecular biology (Clifton, N.J.) · 2022
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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 at 1 institution in 1 country.

Ali NavidPhysics and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA, 94550, USA. navid1@llnl.gov.ORCID http://orcid.org/0000-0003-2560-6984
Yongqin JiaoPhysics and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA, 94550, USA.
Sergio Ernesto WongPhysics and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA, 94550, USA.
Jennifer Pett-RidgePhysics and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Ave., Livermore, CA, 94550, USA.
Lawrence Livermore National Laboratory · US

Funding

Biological and Environmental Research SCW1039
6 · The paper itself

Abstract

backgroundLiving organisms need to allocate their limited resources in a manner that optimizes their overall fitness by simultaneously achieving several different biological objectives. Examination of these biological trade-offs can provide invaluable information regarding the biophysical and biochemical bases behind observed cellular phenotypes. A quantitative knowledge of a cell system's critical objectives is also needed for engineering of cellular metabolism, where there is interest in mitigating the fitness costs that may result from human manipulation.

resultsTo study metabolism in photoheterotrophs, we developed and validated a genome-scale model of metabolism in Rhodopseudomonas palustris, a metabolically versatile gram-negative purple non-sulfur bacterium capable of growing phototrophically on various carbon sources, including inorganic carbon and aromatic compounds. To quantitatively assess trade-offs among a set of important biological objectives during different metabolic growth modes, we used our new model to conduct an 8-dimensional multi-objective flux analysis of metabolism in R. palustris. Our results revealed that phototrophic metabolism in R. palustris is light-limited under anaerobic conditions, regardless of the available carbon source. Under photoheterotrophic conditions, R. palustris prioritizes the optimization of carbon efficiency, followed by ATP production and biomass production rate, in a Pareto-optimal manner. To achieve maximum carbon fixation, cells appear to divert limited energy resources away from growth and toward CO

conclusionsPhotoheterotrophic metabolism of R. palustris is primarily regulated by the amount of light it can absorb and not the availability of carbon. However, despite carbon's secondary role as a regulating factor, R. palustris' metabolism strives for maximum carbon efficiency, even when this increased efficiency leads to slightly lower growth rates.

Indexed as

Phototrophic ProcessesRhodopseudomonasAutotrophyCarbon efficiencyCarbon storageFlux balance analysisGenome-scale modelLight limitationMetabolic trade-offsMulti-objective analysisPhototrophic metabolismRhodopseudomonas palustris

Identifiers

PMID31072303
PMCPMC6509789
OpenAlexW2892624118

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.