Evidence map›Paper›PMID 32385605›Full record

ArticleJournal of industrial microbiology & biotechnology2020

Evolution of mutualistic behaviour between Chlorella sorokiniana and Saccharomyces cerevisiae within a synthetic environment.

J R Oosthuizen, R K Naidoo, D Rossouw, F F Bauer

Abstract read
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In one paragraph

Article in Journal of industrial microbiology & biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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.

J R OosthuizenDepartment of Viticulture and Oenology, Institute for Wine Biotechnology, Stellenbosch University, Stellenbosch, South Africa.
R K NaidooDepartment of Viticulture and Oenology, Institute for Wine Biotechnology, Stellenbosch University, Stellenbosch, South Africa.
D RossouwDepartment of Viticulture and Oenology, Institute for Wine Biotechnology, Stellenbosch University, Stellenbosch, South Africa.
F F BauerDepartment of Viticulture and Oenology, Institute for Wine Biotechnology, Stellenbosch University, Stellenbosch, South Africa. fb2@sun.ac.za.ORCID http://orcid.org/0000-0001-5764-4542

Funding

National Research Foundation South Africs 83471The Royal Society FLAIR Fellowship
6 · The paper itself

Abstract

Yeast and microalgae are microorganisms with widely diverging physiological and biotechnological properties. Accordingly, their fields of applications diverge: yeasts are primarily applied in processes related to fermentation, while microalgae are used for the production of high-value metabolites and green technologies such as carbon capture. Heterotrophic-autotrophic systems and synthetic ecology approaches have been proposed as tools to achieve stable combinations of such evolutionarily unrelated species. We describe an entirely novel synthetic ecology-based approach to evolve co-operative behaviour between winery wastewater isolates of the yeast Saccharomyces cerevisiae and microalga Chlorella sorokiniana. The data show that biomass production and mutualistic growth improved when co-evolved yeast and microalgae strains were paired together. Combinations of co-evolved strains displayed a range of phenotypes, including differences in amino acid profiles. Taken together, the results demonstrate that biotic selection pressures can lead to improved mutualistic growth phenotypes over relatively short time periods.

Indexed as

SymbiosisAutotrophic ProcessesBiomassChlorellaFermentationHeterotrophic ProcessesMicroalgaeSaccharomyces cerevisiaeCo-evolutionMicroalgaeMutualismSyntheticYeast

Identifiers

What OpenQuestion holds

Textmetadata
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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.