Evidence map›Paper›PMID 38493086›Full record

ArticleMicrobial cell factories2024

Engineering Saccharomyces cerevisiae for targeted hydrolysis and fermentation of glucuronoxylan through CRISPR/Cas9 genome editing.

Jonas L Ravn, João H C Manfrão-Netto, Jana B Schaubeder, Luca Torello Pianale, Stefan Spirk, Iván F Ciklic, Cecilia Geijer

Open access · goldAbstract read
In one paragraph

Article in Microbial cell factories, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 26% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

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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

7 authors at 4 institutions in 4 countries.

Jonas L RavnDepartment of Life Sciences, Chalmers University of Technology, Gothenburg, 412 96, Sweden. ravn@chalmers.se.
João H C Manfrão-NettoDepartment of Life Sciences, Chalmers University of Technology, Gothenburg, 412 96, Sweden.
Jana B SchaubederInstitute of Bioproducts and Paper Technology (BPTI), Graz University of Technology, Inffeldgasse 23, Graz, 8010, Austria.
Luca Torello PianaleDepartment of Life Sciences, Chalmers University of Technology, Gothenburg, 412 96, Sweden.
Stefan SpirkInstitute of Bioproducts and Paper Technology (BPTI), Graz University of Technology, Inffeldgasse 23, Graz, 8010, Austria.
Iván F CiklicDepartment of Life Sciences, Chalmers University of Technology, Gothenburg, 412 96, Sweden.
Cecilia GeijerDepartment of Life Sciences, Chalmers University of Technology, Gothenburg, 412 96, Sweden. cecilia.geijer@chalmers.se.
Chalmers University of Technology · SEGraz University of Technology · ATBrazilian Center for Research in Energy and Materials · BRUniversidad Nacional de Cuyo · AR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe abundance of glucuronoxylan (GX) in agricultural and forestry residual side streams positions it as a promising feedstock for microbial conversion into valuable compounds. By engineering strains of the widely employed cell factory Saccharomyces cerevisiae with the ability to directly hydrolyze and ferment GX polymers, we can avoid the need for harsh chemical pretreatments and costly enzymatic hydrolysis steps prior to fermentation. However, for an economically viable bioproduction process, the engineered strains must efficiently express and secrete enzymes that act in synergy to hydrolyze the targeted polymers.

resultsThe aim of this study was to equip the xylose-fermenting S. cerevisiae strain CEN.PK XXX with xylanolytic enzymes targeting beechwood GX. Using a targeted enzyme approach, we matched hydrolytic enzyme activities to the chemical features of the GX substrate and determined that besides endo-1,4-β-xylanase and β-xylosidase activities, α-methyl-glucuronidase activity was of great importance for GX hydrolysis and yeast growth. We also created a library of strains expressing different combinations of enzymes, and screened for yeast strains that could express and secrete the enzymes and metabolize the GX hydrolysis products efficiently. While strains engineered with BmXyn11A xylanase and XylA β-xylosidase could grow relatively well in beechwood GX, strains further engineered with Agu115 α-methyl-glucuronidase did not display an additional growth benefit, likely due to inefficient expression and secretion of this enzyme. Co-cultures of strains expressing complementary enzymes as well as external enzyme supplementation boosted yeast growth and ethanol fermentation of GX, and ethanol titers reached a maximum of 1.33 g L

conclusionThis work underscored the importance of identifying an optimal enzyme combination for successful engineering of S. cerevisiae strains that can hydrolyze and assimilate GX. The enzymes must exhibit high and balanced activities, be compatible with the yeast's expression and secretion system, and the nature of the hydrolysis products must be such that they can be taken up and metabolized by the yeast. The engineered strains, particularly when co-cultivated, display robust growth and fermentation of GX, and represent a significant step forward towards a sustainable and cost-effective bioprocessing of GX-rich biomass. They also provide valuable insights for future strain and process development targets.

Indexed as

Gene EditingSaccharomyces cerevisiaeXylansCRISPR-Cas SystemsEthanolFermentationGlucuronidaseHydrolysisPolymersXyloseEthanolGlucuronidaseglucuronoxylanPolymersXylansXyloseCo-cultureConsolidated bioprocessingMetabolic engineeringMicrobial cell factoriesXylanXylanaseYeastα-glucuronidase

Identifiers

PMID38493086
PMCPMC10943827
OpenAlexW4392883053

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.