Understanding the differences in 2G ethanol fermentative scales through omics data integration.

In this work, we evaluated the fermentative performance and metabolism modifications of a second generation (2G) industrial yeast by comparing an industrial condition during laboratory and industrial scale fermentations. Fermentations were done using industrial lignocellulosic hydrolysate and a synthetic medium containing inhibitors and analyses were carried out through transcriptomics and proteomics of these experimental conditions. We found that fermentation profiles were very similar, but there was an increase in xylose consumption rate during fermentations using synthetic medium when compared to lignocellulosic hydrolysate, likely due to the presence of unknown growth inhibitors contained in the hydrolysate. We also evaluated the bacterial community composition of the industrial fermentation setting and found that the presence of homofermentative and heterofermentative bacteria did not significantly change the performance of yeast fermentation. In parallel, temporal differentially expressed genes (tDEG) showed differences in gene expression profiles between compared conditions, including heat shocks and the presence of up-regulated genes from the TCA cycle during anaerobic xylose fermentation. Thus, we indicate HMF as a possible electron acceptor in this rapid respiratory process performed by yeast, in addition to demonstrating the importance of culture medium for the performance of yeast within industrial fermentation processes, highlighting the uniquenesses according to scales.

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

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.

A simple and effective set of PCR-based molecular markers for the monitoring of the Saccharomyces cerevisiae cell population during bioethanol fermentation.

One of the defining features of the fermentation process used in the production of bioethanol from sugarcane feedstock is the dynamic nature of the yeast population. Minisatellite molecular markers are particularly useful for monitoring yeast communities because they produce polymorphic PCR products that typically display wide size variations. We compared the coding sequences derived from the genome of the sugarcane bioethanol strain JAY270/PE-2 to those of the reference Saccharomyces cerevisiae laboratory strain S288c, and searched for genes containing insertion or deletion polymorphisms larger than 24 bp. We then designed oligonucleotide primers flanking nine of these sites, and used them to amplify differentially sized PCR products. We analyzed the banding patterns in the most widely adopted sugarcane bioethanol strains and in several indigenous yeast contaminants, and found that our marker set had very good discriminatory power. Subsequently, these markers were used to successfully monitor the yeast cell populations in six sugarcane bioethanol distilleries. Additionally, we showed that most of the markers described here are also polymorphic among strains unrelated to bioethanol production, suggesting that they may be applied universally in S. cerevisiae. Because the relatively large polymorphisms are detectable in conventional agarose gels, our method is well suited to modestly equipped on-site laboratories at bioethanol distilleries, therefore providing both cost and time savings.