Stress response and adaptation mechanisms in Kluyveromyces marxianus

Kluyveromyces marxianus is a non-Saccharomyces yeast that has gained importance due to its great potential to be used in the food and biotechnology industries. In general, K. marxianus is a known yeast for its ability to assimilate hexoses and pentoses; even this yeast can grow in disaccharides such as sucrose and lactose and polysaccharides such as agave fructans. Otherwise, K. marxianus is an excellent microorganism to produce metabolites of biotechnological interest, such as enzymes, ethanol, aroma compounds, organic acids, and single-cell proteins. However, several studies highlighted the metabolic trait variations among the K. marxianus strains, suggesting genetic diversity within the species that determines its metabolic functions; this diversity can be attributed to its high adaptation capacity against stressful environments. The outstanding metabolic characteristics of K. marxianus have motivated this yeast to be a study model to evaluate its easy adaptability to several environments. This chapter will discuss overview characteristics and applications of K. marxianus and recent insights into the stress response and adaptation mechanisms used by this non-Saccharomyces yeast.

Effect of Hanseniaspora uvarum-Saccharomyces cerevisiae Mixed Fermentation on Aroma Characteristics of Rosa roxburghii Tratt, Blueberry, and Plum Wines

Hanseniaspora uvarum, a non-Saccharomyces cerevisiae species, has a crucial effect on the aroma characteristics of fruit wines, thus, attracting significant research interest in recent years. In this study, H. uvarum-Saccharomyces cerevisiae mixed fermentation was used to ferment Rosa roxburghii Tratt, blueberry fruit wine, and plum fruit wines using either a co-inoculated or a sequentially inoculated approach. The three fruit wines' volatile aroma characteristics were analyzed by headspace-solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). The results showed that the mixed inoculation of H. uvarum and S. cerevisiae reduced the alcoholic content of Kongxinli fruit wine. Moreover, H. uvarum-S. cerevisiae fermented Rosa roxburghii Tratt, blueberry, and plum fruit wines and further enriched their flavor compounds. The overall flavor characteristics of sequentially inoculated fruit wines differed significantly from those fermented with S. cerevisiae alone, although several similarities were also observed. Sequential inoculation of H. uvarum and S. cerevisiae positively affected the mellowness of the wine and achieved a better harmony of the overall wine flavors. Therefore, H. uvarum-Saccharomyces cerevisiae mixed fermentation can improve the complexity of the wines' aromatic composition and empower them with a unique identity. In particular, H. uvarum-Saccharomyces cerevisiae blueberry wine produced by mixed fermentation had the widest variety and content of aroma compounds among the fermented wines. Therefore, H. uvarum-Saccharomyces cerevisiae mixed-fermentation inoculation in the three fermented fruit wines significantly increased the aroma compound variety and content, thus, enriching their aroma richness and complexity. This study is the first comparative evaluation of the aroma characteristics of different fruit wines fermented with a mixed inoculation of H. uvarum and S. cerevisiae and provides a preliminary guide for these fruit wines produced with non-Saccharomyces yeast.

Effect of Metschnikowia pulcherrima on Saccharomyces cerevisiae PDH By-Pass in MixedFermentation with Varied Sugar Concentrations of Synthetic Grape Juice and Inoculation Ratios

The effects of Metschnikowia pulcherrima and high glucose osmolality on S. cerevisiae pyruvate dehydrogenase pathway (PDH) by-pass were examined by varying the starting sugar concentration of synthetic grape juice and the inoculation ratio of S. cerevisiae to M. pulcherrima. The findings revealed that M. pulcherrima and osmolarity impacted S. cerevisiae’s PDH by-pass. The inoculation concentration of M. pulcherrima significantly affected pyruvate decarboxylase (PDC) activity and acs2 expression when the initial sugar concentration was 200 g L−1 and 290 g L−1. The osmolarity caused by the initial sugar (380 g L−1) significantly influenced the enzymatic activity of S. cerevisiae, which decreased PDC and acetaldehyde dehydrogenase (ALD) activities while increasing Acetyl-CoA synthetase (ACS) activity. The reduction in acetic acid in the wine was caused by M. pulcherrima altering the initial sugar concentration faced by S. cerevisiae, which in turn affected enzymatic activity. The alteration of enzyme activity and accumulation of primary metabolites revealed why mixed fermentation could reduce the acetic acid content in wine by altering the enzymatic activity and affecting the expression of several key genes. The M. pulcherrima inoculation levels had no significant effect on the acetic acid and glycerol concentration in the same fermentation medium.

Modeling and Use of Inter-Criteria Decision Analysis for Selecting Growth Rate Models for Batch Cultivation of Yeast Kluyveromyces marxianus var. lactis MC 5

Ten unstructured models of Monod, Mink, Tessier, Moser, Aiba, Andrews, Haldane, Luong, Edward, and Han-Levenspiel are considered in this paper to explain the kinetics of cell growth for batch cultivation of the yeast Kluyweromyces marxianus var. lactis MC 5. For the first time, two independent kinetic models are used to model the process for the two basic substrates—lactose and oxygen. The selection of the most appropriate growth rate models has been made through a new multi-criteria decision-making approach called the Inter-Criteria Decision Analysis (ICDA) method. The application of ICDA to the growth rate of lactose and oxygen alone has shown that there have been many correlations between the studied models. Thus, the models for the growth rate, depending only on lactose, are reduced to one—Monod model and there are two models—Monod and Mink—depending on oxygen only. Separate kinetic process models have been developed for the combination of Monod–Monod and Monod–Mink models. For the first time, in addition to the multiplicative form, the additive form of a specific growth rate has been studied. The comparison of the obtained results has shown that the additive form has shown better results than the multiplicative one. For this reason, the additive form of the Monod–Monod model will be used to model the process.