Evidence map›Paper›PMID 30185188›Full record

ArticleMicrobial cell factories2018

Elucidating redox balance shift in Scheffersomyces stipitis' fermentative metabolism using a modified genome-scale metabolic model.

Matthew Hilliard, Andrew Damiani, Q Peter He, Thomas Jeffries, Jin Wang

Open access · goldAbstract read
In one paragraph

Article in Microbial cell factories, 2018. 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
0.9field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
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    Article
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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

5 authors at 2 institutions in 1 country.

Matthew HilliardDepartment of Chemical Engineering, Auburn University, Auburn, AL, 36849, USA.
Andrew DamianiDepartment of Chemical Engineering, Auburn University, Auburn, AL, 36849, USA.
Q Peter HeDepartment of Chemical Engineering, Auburn University, Auburn, AL, 36849, USA.
Thomas JeffriesXylome, Madison, WI, 53719, USA.
Jin WangDepartment of Chemical Engineering, Auburn University, Auburn, AL, 36849, USA. wang@auburn.edu.ORCID http://orcid.org/0000-0002-7638-8537
Auburn University · USUniversity of Wisconsin–Madison · US

Funding

National Science Foundation 1069004National Science Foundation 1264861U. S. Department of Education P200A150074
6 · The paper itself

Abstract

backgroundScheffersomyces stipitis is an important yeast species in the field of biorenewables due to its desired capacity for xylose utilization. It has been recognized that redox balance plays a critical role in S. stipitis due to the different cofactor preferences in xylose assimilation pathway. However, there has not been any systems level understanding on how the shift in redox balance contributes to the overall metabolic shift in S. stipitis to cope with reduced oxygen uptake. Genome-scale metabolic network models (GEMs) offer the opportunity to gain such systems level understanding; however, currently the two published GEMs for S. stipitis cannot be used for this purpose, as neither of them is able to capture the strain's fermentative metabolism reasonably well due to their poor prediction of xylitol production, a key by-product under oxygen limited conditions.

resultsA system identification-based (SID-based) framework that we previously developed for GEM validation is expanded and applied to refine a published GEM for S. stipitis, iBB814. After the modified GEM, named iDH814, was validated using literature data, it is used to obtain genome-scale understanding on how redox cofactor shifts when cells respond to reduced oxygen supply. The SID-based framework for GEM analysis was applied to examine how the environmental perturbation (i.e., reduced oxygen supply) propagates through the metabolic network, and key reactions that contribute to the shifts of redox and metabolic state were identified. Finally, the findings obtained through GEM analysis were validated using transcriptomic data.

conclusionsiDH814, the modified model, was shown to offer significantly improved performance in terms of matching available experimental results and better capturing available knowledge on the organism. More importantly, our analysis based on iDH814 provides the first genome-scale understanding on how redox balance in S. stipitis was shifted as a result of reduced oxygen supply. The systems level analysis identified the key contributors to the overall metabolic state shift, which were validated using transcriptomic data. The analysis confirmed that S. stipitis uses a concerted approach to cope with the stress associated with reduced oxygen supply, and the shift of reducing power from NADPH to NADH seems to be the center theme that directs the overall shift in metabolic states.

Indexed as

Oxidation-ReductionFermentationGenome, FungalPichiaGenome-scale metabolic network model (GEM)Phenotype phase-plane analysisRedox balanceScheffersomyces stipitisSystem identification

Identifiers

PMID30185188
PMCPMC6126012
OpenAlexW2891700000

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.