Evidence map›Paper›PMID 32926401›Full record

ArticleBiotechnology and bioengineering2021

Dynamic co-culture metabolic models reveal the fermentation dynamics, metabolic capacities and interplays of cheese starter cultures.

Emrah Özcan, Merve Seven, Burcu Şirin, Tunahan Çakır, Emrah Nikerel, Bas Teusink, Ebru Toksoy Öner

Abstract read
In one paragraph

Article in Biotechnology and bioengineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Eco-Evolutionary Dynamics in Microbial Communities from Spontaneous Fermented Foods.International journal of environmental research and public health · 2021
    Article
  10. Review
  11. Article
  12. 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

7 authors.

Emrah ÖzcanSystems Biology, Amsterdam Institute of Molecular and Life Sciences (AIMMS), VU Amsterdam, Amsterdam, The Netherlands.ORCID 0000-0001-9036-9909
Merve SevenGenetics and Bioengineering Department, Yeditepe University, Istanbul, Turkey.
Burcu ŞirinGenetics and Bioengineering Department, Yeditepe University, Istanbul, Turkey.
Tunahan ÇakırDepartment of Bioengineering, Gebze Technical University, Gebze, Kocaeli, Turkey.ORCID 0000-0001-8262-4420
Emrah NikerelGenetics and Bioengineering Department, Yeditepe University, Istanbul, Turkey.
Bas TeusinkSystems Biology, Amsterdam Institute of Molecular and Life Sciences (AIMMS), VU Amsterdam, Amsterdam, The Netherlands.ORCID 0000-0003-3929-0423
Ebru Toksoy ÖnerDepartment of Bioengineering, IBSB, Marmara University, Istanbul, Turkey.ORCID 0000-0001-6054-8842

Funding

Marmara University Scientific Research Project Fund FEN-C-DRP-091116-0498Scientific and Technological Research Council of Turkey (TUBITAK) TUBITAK 2211-C and 2214-A programs
6 · The paper itself

Abstract

In this study, we have investigated the cheese starter culture as a microbial community through a question: can the metabolic behaviour of a co-culture be explained by the characterized individual organism that constituted the co-culture? To address this question, the dairy-origin lactic acid bacteria Lactococcus lactis subsp. cremoris, Lactococcus lactis subsp. lactis, Streptococcus thermophilus and Leuconostoc mesenteroides, commonly used in cheese starter cultures, were grown in pure and four different co-cultures. We used a dynamic metabolic modelling approach based on the integration of the genome-scale metabolic networks of the involved organisms to simulate the co-cultures. The strain-specific kinetic parameters of dynamic models were estimated using the pure culture experiments and they were subsequently applied to co-culture models. Biomass, carbon source, lactic acid and most of the amino acid concentration profiles simulated by the co-culture models fit closely to the experimental results and the co-culture models explained the mechanisms behind the dynamic microbial abundance. We then applied the co-culture models to estimate further information on the co-cultures that could not be obtained by the experimental method used. This includes estimation of the profile of various metabolites in the co-culture medium such as flavour compounds produced and the individual organism level metabolic exchange flux profiles, which revealed the potential metabolic interactions between organisms in the co-cultures.

Indexed as

Models, BiologicalCheeseCoculture TechniquesLactobacillalesco-culture metabolic modellinggenome-scale metabolic networklactic acid bacteriastarter cultures

Identifiers

PMID32926401
PMCPMC7971941

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