Ethanol production process driving changes on industrial strains
ABSTRACT Ethanol production has key differences between the two largest producing countries of this biofuel, Brazil and the USA, such as feedstock source, sugar concentration and ethanol titers in industrial fermentation. Therefore, it is highly probable that these specificities have led to genome a...
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Published in: | FEMS yeast research Vol. 21; no. 1; pp. 1 - 10 |
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01-02-2021
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Abstract | ABSTRACT
Ethanol production has key differences between the two largest producing countries of this biofuel, Brazil and the USA, such as feedstock source, sugar concentration and ethanol titers in industrial fermentation. Therefore, it is highly probable that these specificities have led to genome adaptation of the Saccharomyces cerevisiae strains employed in each process to tolerate different environments. In order to identify particular adaptations, in this work, we have compared the genomes of industrial yeast strains widely used to produce ethanol from sugarcane, corn and sweet sorghum, and also two laboratory strains as reference. The genes were predicted and then 4524 single-copy orthologous were selected to build the phylogenetic tree. We found that the geographic location and industrial process were shown as the main evolutionary drivers: for sugarcane fermentation, positive selection was identified for metal homeostasis and stress response genes, whereas genes involved in membrane modeling have been connected with corn fermentation. In addition, the corn specialized strain Ethanol Red showed an increased number of copies of MAL31, a gene encoding a maltose transporter. In summary, our work can help to guide new strain chassis selection for engineering strategies, to produce more robust strains for biofuel production and other industrial applications.
Understanding how the environment can drive changes in industrial yeasts is important for detecting genes that are under selection and may impact the adaptive process. |
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AbstractList | Ethanol production has key differences between the two largest producing countries of this bibful, Brazil and the USA, such as feedstock source, sugar concentration and ethanol titers in industrial fermentation. Therefore, it is highly probable that these specificities have led to genome adaptation of the Saccharomyces cerevisiae strains employed in each process to tolerate different environments. In order to identify particular adaptations, in this work, we have compared the genomes of industrial yeast strains widely used to produce ethanol from sugarcane, corn and sweet sorghum, and also two laboratory strains as reference. The genes were predicted and then 4524 single-copy orthologous were selected to build the phylogenetic tree. We found that the geographic location and industrial process were shown as the main evolutionary drivers: for sugarcane fermentation, positive selection was identified for metal homeostasis and stress response genes, whereas genes involved in membrane modeling have been connected with corn fermentation. In addition, the corn specialized strain Ethanol Red showed an increased number of copies of MAL31, a gene encoding a maltose transporter. In summary, our work can help to guide new strain chassis selection for engineering strategies, to produce more robust strains for biofuel production and other industrial applications. ABSTRACT Ethanol production has key differences between the two largest producing countries of this biofuel, Brazil and the USA, such as feedstock source, sugar concentration and ethanol titers in industrial fermentation. Therefore, it is highly probable that these specificities have led to genome adaptation of the Saccharomyces cerevisiae strains employed in each process to tolerate different environments. In order to identify particular adaptations, in this work, we have compared the genomes of industrial yeast strains widely used to produce ethanol from sugarcane, corn and sweet sorghum, and also two laboratory strains as reference. The genes were predicted and then 4524 single-copy orthologous were selected to build the phylogenetic tree. We found that the geographic location and industrial process were shown as the main evolutionary drivers: for sugarcane fermentation, positive selection was identified for metal homeostasis and stress response genes, whereas genes involved in membrane modeling have been connected with corn fermentation. In addition, the corn specialized strain Ethanol Red showed an increased number of copies of MAL31, a gene encoding a maltose transporter. In summary, our work can help to guide new strain chassis selection for engineering strategies, to produce more robust strains for biofuel production and other industrial applications. Understanding how the environment can drive changes in industrial yeasts is important for detecting genes that are under selection and may impact the adaptive process. Ethanol production has key differences between the two largest producing countries of this biofuel, Brazil and the USA, such as feedstock source, sugar concentration and ethanol titers in industrial fermentation. Therefore, it is highly probable that these specificities have led to genome adaptation of the Saccharomyces cerevisiae strains employed in each process to tolerate different environments. In order to identify particular adaptations, in this work, we have compared the genomes of industrial yeast strains widely used to produce ethanol from sugarcane, corn and sweet sorghum, and also two laboratory strains as reference. The genes were predicted and then 4524 single-copy orthologous were selected to build the phylogenetic tree. We found that the geographic location and industrial process were shown as the main evolutionary drivers: for sugarcane fermentation, positive selection was identified for metal homeostasis and stress response genes, whereas genes involved in membrane modeling have been connected with corn fermentation. In addition, the corn specialized strain Ethanol Red showed an increased number of copies of MAL31, a gene encoding a maltose transporter. In summary, our work can help to guide new strain chassis selection for engineering strategies, to produce more robust strains for biofuel production and other industrial applications. Ethanol production has key differences between the two largest producing countries of this bibful, Brazil and the USA, such as feedstock source, sugar concentration and ethanol titers in industrial fermentation. Therefore, it is highly probable that these specificities have led to genome adaptation of the Saccharomyces cerevisiae strains employed in each process to tolerate different environments. In order to identify particular adaptations, in this work, we have compared the genomes of industrial yeast strains widely used to produce ethanol from sugarcane, corn and sweet sorghum, and also two laboratory strains as reference. The genes were predicted and then 4524 single-copy orthologous were selected to build the phylogenetic tree. We found that the geographic location and industrial process were shown as the main evolutionary drivers: for sugarcane fermentation, positive selection was identified for metal homeostasis and stress response genes, whereas genes involved in membrane modeling have been connected with corn fermentation. In addition, the corn specialized strain Ethanol Red showed an increased number of copies of MAL31, a gene encoding a maltose transporter. In summary, our work can help to guide new strain chassis selection for engineering strategies, to produce more robust strains for biofuel production and other industrial applications. Keywords: industrial strain; first-generation ethanol production; sugarcane; corn; comparative genomics; Saccharomyces cerevisiae |
Audience | Academic |
Author | Nagamatsu, Sheila Tiemi Oliveira, Juliana Velasco de Castro Pereira, Gonçalo Amarante Guimarães José, Juliana Fiamenghi, Mateus Bernabe Coutouné, Natalia Carazzolle, Marcelo Falsarella |
Author_xml | – sequence: 1 givenname: Sheila Tiemi orcidid: 0000-0002-4986-5094 surname: Nagamatsu fullname: Nagamatsu, Sheila Tiemi – sequence: 2 givenname: Natalia surname: Coutouné fullname: Coutouné, Natalia – sequence: 3 givenname: Juliana orcidid: 0000-0002-8259-6519 surname: José fullname: José, Juliana – sequence: 4 givenname: Mateus Bernabe surname: Fiamenghi fullname: Fiamenghi, Mateus Bernabe – sequence: 5 givenname: Gonçalo Amarante Guimarães orcidid: 0000-0003-4140-3482 surname: Pereira fullname: Pereira, Gonçalo Amarante Guimarães email: goncalo@unicamp.br – sequence: 6 givenname: Juliana Velasco de Castro surname: Oliveira fullname: Oliveira, Juliana Velasco de Castro – sequence: 7 givenname: Marcelo Falsarella surname: Carazzolle fullname: Carazzolle, Marcelo Falsarella |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33417685$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_3389_fmicb_2021_644089 crossref_primary_10_3389_fmicb_2021_768562 crossref_primary_10_1016_j_ijbiomac_2023_123800 crossref_primary_10_3390_fermentation8100470 crossref_primary_10_1016_j_biortech_2024_130594 crossref_primary_10_1016_j_jbiotec_2022_10_005 crossref_primary_10_1042_EBC20200160 crossref_primary_10_1186_s40643_022_00580_w crossref_primary_10_2139_ssrn_4181174 |
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Keywords | first-generation ethanol production industrial strain corn comparative genomics sugarcane Saccharomyces cerevisiae |
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Ethanol production has key differences between the two largest producing countries of this biofuel, Brazil and the USA, such as feedstock source,... Ethanol production has key differences between the two largest producing countries of this biofuel, Brazil and the USA, such as feedstock source, sugar... Ethanol production has key differences between the two largest producing countries of this bibful, Brazil and the USA, such as feedstock source, sugar... |
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SubjectTerms | Acetaldehyde Adaptation Alcohol Alcohol, Denatured Biodiesel fuels Biofuels Ethanol Fermentation Genetic aspects Genomes Genomics Homeostasis Industrial applications Industrial strains Maltose Phylogeny Positive selection Production data Production processes Sugarcane |
Title | Ethanol production process driving changes on industrial strains |
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