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Saccharomyces cerevisiae transcriptional reprograming due to bacterial contamination during industrial scale bioethanol production.

Carvalho-Netto OV, Carazzolle MF, Mofatto LS, Teixeira PJ, Noronha MF, Calderón LA, Mieczkowski PA, Argueso JL, Pereira GA - Microb. Cell Fact. (2015)

Bottom Line: The bioethanol production system used in Brazil is based on the fermentation of sucrose from sugarcane feedstock by highly adapted strains of the yeast Saccharomyces cerevisiae.The formation of such particles is undesirable because it slows the fermentation kinetics and reduces the overall bioethanol yield.In this study, we investigated the molecular physiology of one of the main S. cerevisiae strains used in Brazilian bioethanol production, PE-2, under two contrasting conditions: typical fermentation, when most yeast cells are in suspension, and co-aggregated fermentation.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Genética, Evolução e Bioagentes, Instituto de Biologia, Universidade Estadual de Campinas, Campinas, SP, Brazil. osmar@lge.ibi.unicamp.br.

ABSTRACT

Background: The bioethanol production system used in Brazil is based on the fermentation of sucrose from sugarcane feedstock by highly adapted strains of the yeast Saccharomyces cerevisiae. Bacterial contaminants present in the distillery environment often produce yeast-bacteria cellular co-aggregation particles that resemble yeast-yeast cell adhesion (flocculation). The formation of such particles is undesirable because it slows the fermentation kinetics and reduces the overall bioethanol yield.

Results: In this study, we investigated the molecular physiology of one of the main S. cerevisiae strains used in Brazilian bioethanol production, PE-2, under two contrasting conditions: typical fermentation, when most yeast cells are in suspension, and co-aggregated fermentation. The transcriptional profile of PE-2 was assessed by RNA-seq during industrial scale fed-batch fermentation. Comparative analysis between the two conditions revealed transcriptional profiles that were differentiated primarily by a deep gene repression in the co-aggregated samples. The data also indicated that Lactobacillus fermentum was likely the main bacterial species responsible for cellular co-aggregation and for the high levels of organic acids detected in the samples.

Conclusions: Here, we report the high-resolution gene expression profiling of strain PE-2 during industrial-scale fermentations and the transcriptional reprograming observed under co-aggregation conditions. This dataset constitutes an important resource that can provide support for further development of this key yeast biocatalyst.

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Related in: MedlinePlus

Gene expression comparisons between typical and flocculated fermentations. A- FLO genes and flocculation activators; B- Plasma membrane H+-ATPase (PMA1) and related genes; C- Haa1p target genes; D- Cell wall components; E- Methionine- and glutathione-related genes; F- Thiamine metabolic process genes. Differentially expressed (DE) genes were defined as those with a fold change ≥2 or ≥ -2 and a p-value <0.01. Negative values were obtained for the TF samples, and positive values were obtained for the FL samples. General analysis (TFs vs. FLs) was performed using six time-points for the TF samples and seven time-points for the FL samples. The beginning of fermentation is denoted as TF1 and FL1, and the end of fermentation is denoted as TF6 and FL7. The software Expander6 was used for the gene clustering image drawn using the end of fermentation as a reference.
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Fig4: Gene expression comparisons between typical and flocculated fermentations. A- FLO genes and flocculation activators; B- Plasma membrane H+-ATPase (PMA1) and related genes; C- Haa1p target genes; D- Cell wall components; E- Methionine- and glutathione-related genes; F- Thiamine metabolic process genes. Differentially expressed (DE) genes were defined as those with a fold change ≥2 or ≥ -2 and a p-value <0.01. Negative values were obtained for the TF samples, and positive values were obtained for the FL samples. General analysis (TFs vs. FLs) was performed using six time-points for the TF samples and seven time-points for the FL samples. The beginning of fermentation is denoted as TF1 and FL1, and the end of fermentation is denoted as TF6 and FL7. The software Expander6 was used for the gene clustering image drawn using the end of fermentation as a reference.

Mentions: Genes related to flocculation (MUC1, FLO5, FLO8, FLO9, FLO10 and PHD1) were not found to be up-regulated in the FL samples (Figure 4A). This result confirmed that the observed cellular co-aggregation was not due to yeast genetic control. We observed that the main transcriptional differences between the FL and TF conditions were related to content variations in the concentrations of organic acids present in the medium. The major plasma membrane H+-ATPase, encoded by PMA1 [32], was not differentially expressed between samples at the beginning of fermentation (TF1 vs. FL1). However, we verified a two-fold PMA1 induction in flocculated fermentations at the last time point. Pma1p-related genes, AST1 (targeting factor to plasma membrane), PMP1, PMP2 and HRK1 (regulatory elements), had similar expression patterns (Figure 4B). These data show that the mechanism used to pump out protons to regulate cytoplasmic pH is up-regulated in the FL cells. This stress response, however, consumes excessive ATP and may cause an inhibitory action by energy depletion [31].Figure 4


Saccharomyces cerevisiae transcriptional reprograming due to bacterial contamination during industrial scale bioethanol production.

Carvalho-Netto OV, Carazzolle MF, Mofatto LS, Teixeira PJ, Noronha MF, Calderón LA, Mieczkowski PA, Argueso JL, Pereira GA - Microb. Cell Fact. (2015)

Gene expression comparisons between typical and flocculated fermentations. A- FLO genes and flocculation activators; B- Plasma membrane H+-ATPase (PMA1) and related genes; C- Haa1p target genes; D- Cell wall components; E- Methionine- and glutathione-related genes; F- Thiamine metabolic process genes. Differentially expressed (DE) genes were defined as those with a fold change ≥2 or ≥ -2 and a p-value <0.01. Negative values were obtained for the TF samples, and positive values were obtained for the FL samples. General analysis (TFs vs. FLs) was performed using six time-points for the TF samples and seven time-points for the FL samples. The beginning of fermentation is denoted as TF1 and FL1, and the end of fermentation is denoted as TF6 and FL7. The software Expander6 was used for the gene clustering image drawn using the end of fermentation as a reference.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4318157&req=5

Fig4: Gene expression comparisons between typical and flocculated fermentations. A- FLO genes and flocculation activators; B- Plasma membrane H+-ATPase (PMA1) and related genes; C- Haa1p target genes; D- Cell wall components; E- Methionine- and glutathione-related genes; F- Thiamine metabolic process genes. Differentially expressed (DE) genes were defined as those with a fold change ≥2 or ≥ -2 and a p-value <0.01. Negative values were obtained for the TF samples, and positive values were obtained for the FL samples. General analysis (TFs vs. FLs) was performed using six time-points for the TF samples and seven time-points for the FL samples. The beginning of fermentation is denoted as TF1 and FL1, and the end of fermentation is denoted as TF6 and FL7. The software Expander6 was used for the gene clustering image drawn using the end of fermentation as a reference.
Mentions: Genes related to flocculation (MUC1, FLO5, FLO8, FLO9, FLO10 and PHD1) were not found to be up-regulated in the FL samples (Figure 4A). This result confirmed that the observed cellular co-aggregation was not due to yeast genetic control. We observed that the main transcriptional differences between the FL and TF conditions were related to content variations in the concentrations of organic acids present in the medium. The major plasma membrane H+-ATPase, encoded by PMA1 [32], was not differentially expressed between samples at the beginning of fermentation (TF1 vs. FL1). However, we verified a two-fold PMA1 induction in flocculated fermentations at the last time point. Pma1p-related genes, AST1 (targeting factor to plasma membrane), PMP1, PMP2 and HRK1 (regulatory elements), had similar expression patterns (Figure 4B). These data show that the mechanism used to pump out protons to regulate cytoplasmic pH is up-regulated in the FL cells. This stress response, however, consumes excessive ATP and may cause an inhibitory action by energy depletion [31].Figure 4

Bottom Line: The bioethanol production system used in Brazil is based on the fermentation of sucrose from sugarcane feedstock by highly adapted strains of the yeast Saccharomyces cerevisiae.The formation of such particles is undesirable because it slows the fermentation kinetics and reduces the overall bioethanol yield.In this study, we investigated the molecular physiology of one of the main S. cerevisiae strains used in Brazilian bioethanol production, PE-2, under two contrasting conditions: typical fermentation, when most yeast cells are in suspension, and co-aggregated fermentation.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Genética, Evolução e Bioagentes, Instituto de Biologia, Universidade Estadual de Campinas, Campinas, SP, Brazil. osmar@lge.ibi.unicamp.br.

ABSTRACT

Background: The bioethanol production system used in Brazil is based on the fermentation of sucrose from sugarcane feedstock by highly adapted strains of the yeast Saccharomyces cerevisiae. Bacterial contaminants present in the distillery environment often produce yeast-bacteria cellular co-aggregation particles that resemble yeast-yeast cell adhesion (flocculation). The formation of such particles is undesirable because it slows the fermentation kinetics and reduces the overall bioethanol yield.

Results: In this study, we investigated the molecular physiology of one of the main S. cerevisiae strains used in Brazilian bioethanol production, PE-2, under two contrasting conditions: typical fermentation, when most yeast cells are in suspension, and co-aggregated fermentation. The transcriptional profile of PE-2 was assessed by RNA-seq during industrial scale fed-batch fermentation. Comparative analysis between the two conditions revealed transcriptional profiles that were differentiated primarily by a deep gene repression in the co-aggregated samples. The data also indicated that Lactobacillus fermentum was likely the main bacterial species responsible for cellular co-aggregation and for the high levels of organic acids detected in the samples.

Conclusions: Here, we report the high-resolution gene expression profiling of strain PE-2 during industrial-scale fermentations and the transcriptional reprograming observed under co-aggregation conditions. This dataset constitutes an important resource that can provide support for further development of this key yeast biocatalyst.

Show MeSH
Related in: MedlinePlus