CRISPRi-induced transcriptional regulation of IAH1 gene and its influence on volatile compounds profile in Kluyveromyces marxianus DU3.

Mezcal is a traditional Mexican distilled beverage, known for its marked organoleptic profile, which is influenced by several factors, such as the fermentation process, where a wide variety of microorganisms are present. Kluyveromyces marxianus is one of the main yeasts isolated from mezcal fermentations and has been associated with ester synthesis, contributing to the flavors and aromas of the beverage. In this study, we employed CRISPR interference (CRISPRi) technology, using dCas9 fused to the Mxi1 repressor factor domain, to down-regulate the expression of the IAH1 gene, encoding for an isoamyl acetate-hydrolyzing esterase, in K. marxianus strain DU3. The constructed CRISPRi plasmid successfully targeted the IAH1 gene, allowing for specific gene expression modulation. Through gene expression analysis, we assessed the impact of IAH1 down-regulation on the metabolic profile of volatile compounds. We also measured the expression of other genes involved in volatile compound biosynthesis, including ATF1, EAT1, ADH1, and ZWF1 by RT-qPCR. Results demonstrated successful down-regulation of IAH1 expression in K. marxianus strain DU3 using the CRISPRi system. The modulation of IAH1 gene expression resulted in alterations in the production of volatile compounds, specifically ethyl acetate, which are important contributors to the beverage's aroma. Changes in the expression levels of other genes involved in ester biosynthesis, suggesting that the knockdown of IAH1 may generate intracellular alterations in the balance of these metabolites, triggering a regulatory response. The application of CRISPRi technology in K. marxianus opens the possibility of targeted modulation of gene expression, metabolic engineering strategies, and synthetic biology in this yeast strain.

Identification of genes related to hydrolysis and assimilation of Agave fructans in Candida apicola NRRL Y-50540 and Torulaspora delbrueckii NRRL Y-50541 by denovo transcriptome analysis.

Fructans are the main sugar in agave pine used by yeasts during mezcal fermentation processes, from which Candida apicola NRRL Y-50540 and Torulaspora delbrueckii NRRL Y-50541 were isolated. De novo transcriptome analysis was carried out to identify genes involved in the hydrolysis and assimilation of Agave fructans (AF). We identified a transcript annotated as SUC2, which is related to ß-fructofuranosidase activity, and several differential expressed genes involved in the transcriptional regulation of SUC2 such as: MIG1, MTH1, SNF1, SNF5, REG1, SSN6, SIP1, SIP2, SIP5, GPR1, RAS2, and PKA. Some of these genes were specifically expressed in some of the yeasts according to their fructans assimilation metabolism. Different hexose transporters that could be related to the assimilation of fructose and glucose were found in both the transcriptomes. Our findings provide a better understanding of AF assimilation in these yeasts and provide resources for further metabolic engineering and biotechnology applications.

Estimation of metabolic fluxes distribution in Saccharomyces cerevisiae during the production of volatile compounds of Tequila.

A stoichiometric model for Saccharomyces cerevisiae is reconstructed to analyze the continuous fermentation process of agave juice in Tequila production. The metabolic model contains 94 metabolites and 117 biochemical reactions. From the above set of reactions, 93 of them are linked to internal biochemical reactions and 24 are related to transport fluxes between the medium and the cell. The central metabolism of S. cerevisiae includes the synthesis for 20 amino-acids, carbohydrates, lipids, DNA and RNA. Using flux balance analysis (FBA), different physiological states of S. cerevisiae are shown during the fermentative process; these states are compared with experimental data under different dilution rates (0.04-0.12 h$ ^{-1} $). Moreover, the model performs anabolic and catabolic biochemical reactions for the production of higher alcohols. The importance of the Saccharomyces cerevisiae genomic model in the area of alcoholic beverage fermentation is due to the fact that it allows to estimate the metabolic fluxes during the beverage fermentation process and a physiology state of the microorganism.

Real-time monitoring of ethanol production during Pichia stipitis NRRL Y-7124 alcoholic fermentation using transflection near infrared spectroscopy.

The application of in situ near-infrared spectroscopy monitoring of xylose metabolizing yeast such as Pichia stipitis for ethanol production with semisynthetic media, applying chemometrics, was investigated. During the process in a bioreactor, biomass, glucose, xylose, ethanol, acetic acid, and glycerol determinations were performed by a transflection probe immersed in the culture broth and connected to a near-infrared process analyzer. Wavelength windows in near-infrared spectra recorded between 800 and 2200 nm were pretreated using Savitzky-Golay smoothing, second derivative and multiplicative scattering correction in order to perform a partial least squares regression and generate the calibration models. These calibration models were tested by external validation (78 samples). Calibration and validation criteria were defined and evaluated in order to generate robust and reliable models for an alcoholic fermentation process matrix. Moreover, regressions coefficients (ß) and variable influence in the projection plots were used to assess the results. A novelty is the use of ß versus VIP dispersion plots to determine which vectors have more influence on the response in order to improve process comprehension and operability. Validated models were used in a real-time monitoring during P. stipitis NRRL Y7124 semisynthetic media fermentations.

In-situ monitoring of Saccharomyces cerevisiae ITV01 bioethanol process using near-infrared spectroscopy NIRS and chemometrics.

The application feasibility of in-situ or in-line monitoring of S. cerevisiae ITV01 alcoholic fermentation process, employing Near-Infrared Spectroscopy (NIRS) and Chemometrics, was investigated. During the process in a bioreactor, in the complex analytical matrix, biomass, glucose, ethanol and glycerol determinations were performed by a transflection fiber optic probe immersed in the culture broth and connected to a Near-Infrared (NIR) process analyzer. The NIR spectra recorded between 800 and 2,200 nm were pretreated using Savitzky-Golay smoothing and second derivative in order to perform a partial least squares regression (PLSR) and generate the calibration models. These calibration models were tested by external validation and then used to predict concentrations in batch alcoholic fermentations. The standard errors of calibration (SEC) for biomass, ethanol, glucose and glycerol were 0.212, 0.287, 0.532, and 0.296 g/L and standard errors of prediction (SEP) were 0.323, 0.369, 0.794, and 0.507 g/L, respectively. Calibration and validation criteria were defined and evaluated in order to generate robust and reliable models for an alcoholic fermentation process matrix. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:510-517, 2016.