Evidence map›Paper›PMID 28000736›Full record

ArticleScientific reports2016

Unraveling the genetic basis of xylose consumption in engineered Saccharomyces cerevisiae strains.

Leandro Vieira Dos Santos, Marcelo Falsarella Carazzolle, Sheila Tiemi Nagamatsu, Nádia Maria Vieira Sampaio, Ludimila Dias Almeida, Renan Augusto Siqueira Pirolla, Guilherme Borelli, Thamy Lívia Ribeiro Corrêa, Juan Lucas Argueso, Gonçalo Amarante Guimarães Pereira

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
5.1field-weighted citation impact, top 4% 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

37 citing papers in PubMed, 97 citations in OpenAlex.

  1. Review
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  8. FromJournal of fungi (Basel, Switzerland) · 2023
    Review
  9. Article
  10. Advances inJournal of fungi (Basel, Switzerland) · 2023
    Review
  11. Article
  12. Review
  13. Review
  14. Article
  15. Xylo-Oligosaccharide Utilization by EngineeredFrontiers in bioengineering and biotechnology · 2022
    Review
  16. D-Xylose Sensing inInternational journal of molecular sciences · 2021
    Review
  17. Article
  18. Article
  19. 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

10 authors at 2 institutions in 2 countries.

Leandro Vieira Dos SantosLaboratório de Genômica e Expressão, Departamento de Genética e Evolução, UNICAMP, Campinas, São Paulo 13083-970, Brazil.
Marcelo Falsarella CarazzolleLaboratório de Genômica e Expressão, Departamento de Genética e Evolução, UNICAMP, Campinas, São Paulo 13083-970, Brazil.
Sheila Tiemi NagamatsuLaboratório de Genômica e Expressão, Departamento de Genética e Evolução, UNICAMP, Campinas, São Paulo 13083-970, Brazil.
Nádia Maria Vieira SampaioDepartment of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins-CO, 80523-1618, USA.
Ludimila Dias AlmeidaGranBio/BioCelere, Campinas, Brazil.
Renan Augusto Siqueira PirollaGranBio/BioCelere, Campinas, Brazil.
Guilherme BorelliLaboratório de Genômica e Expressão, Departamento de Genética e Evolução, UNICAMP, Campinas, São Paulo 13083-970, Brazil.
Thamy Lívia Ribeiro CorrêaLaboratório de Genômica e Expressão, Departamento de Genética e Evolução, UNICAMP, Campinas, São Paulo 13083-970, Brazil.
Juan Lucas ArguesoDepartment of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins-CO, 80523-1618, USA.
Gonçalo Amarante Guimarães PereiraLaboratório de Genômica e Expressão, Departamento de Genética e Evolução, UNICAMP, Campinas, São Paulo 13083-970, Brazil.
Universidade Estadual de Campinas (UNICAMP) · BRColorado State University · US

Funding

MinION long-read DNA sequencer system for the analysis of structural genomic variation in yeastR35GM119788 · NIGMS · COLORADO STATE UNIVERSITY · PI ARGUESO, JUAN LUCAS · 2016 to 2025
$3.7M
NIGMS NIH HHS R35 GM119788
6 · The paper itself

Abstract

The development of biocatalysts capable of fermenting xylose, a five-carbon sugar abundant in lignocellulosic biomass, is a key step to achieve a viable production of second-generation ethanol. In this work, a robust industrial strain of Saccharomyces cerevisiae was modified by the addition of essential genes for pentose metabolism. Subsequently, taken through cycles of adaptive evolution with selection for optimal xylose utilization, strains could efficiently convert xylose to ethanol with a yield of about 0.46 g ethanol/g xylose. Though evolved independently, two strains carried shared mutations: amplification of the xylose isomerase gene and inactivation of ISU1, a gene encoding a scaffold protein involved in the assembly of iron-sulfur clusters. In addition, one of evolved strains carried a mutation in SSK2, a member of MAPKKK signaling pathway. In validation experiments, mutating ISU1 or SSK2 improved the ability to metabolize xylose of yeast cells without adaptive evolution, suggesting that these genes are key players in a regulatory network for xylose fermentation. Furthermore, addition of iron ion to the growth media improved xylose fermentation even by non-evolved cells. Our results provide promising new targets for metabolic engineering of C5-yeasts and point to iron as a potential new additive for improvement of second-generation ethanol production.

Indexed as

Base SequenceDiploidyEvolution, MolecularFermentationGenetic EngineeringGenome, FungalHeterozygoteHomozygoteIronKaryotypeMetabolic EngineeringNucleotidesPoint MutationPolymorphism, Single NucleotideSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsIronNucleotidesSaccharomyces cerevisiae ProteinsXylose

Identifiers

PMID28000736
PMCPMC5175268
OpenAlexW2565996229

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.