The production of fuel ethanol from sugarcane-based raw materials in Brazil is a successful example of a large-scale bioprocess that delivers an advanced biofuel at competitive prices and low environmental impact. Two to three fed-batch fermentations per day, with acid treatment of the yeast cream between consecutive cycles, during 6-8 months of uninterrupted production in a nonaseptic environment are some of the features that make the Brazilian process quite peculiar. Along the past decades, some wild Saccharomyces cerevisiae strains were isolated, identified, characterized, and eventually, reintroduced into the process, enabling us to build up knowledge on these organisms. This information, combined with physiological studies in the laboratory and, more recently, genome sequencing data, has allowed us to start clarifying why and how these strains behave differently from the better known laboratory, wine, beer, and baker's strains. All these issues are covered in this minireview, which also presents a brief discussion on future directions in the field and on the perspectives of introducing genetically modified strains in this industrial process.

Improved biofuels production requires a better understanding of industrial microorganisms. Some wild Saccharomyces cerevisiae strains, isolated from the fuel ethanol industry in Brazil, present exceptional fermentation performance, persistence and prevalence in the harsh industrial environment. Nevertheless, their physiology has not yet been systematically investigated. Here we present a first systematic evaluation of the widely used industrial strains PE-2, CAT-1, BG-1 and JP1, in terms of their tolerance towards process-related stressors. We also analyzed their growth physiology under heat stress. These strains were evaluated in parallel to laboratory and baker's strains. Whereas the industrial strains performed in general better than the laboratory strains under ethanol or acetic acid stresses and on industrial media, high sugar stress was tolerated equally by all strains. Heat and low pH stresses clearly distinguished fuel ethanol strains from the others, indicating that these conditions might be the ones that mostly exert selective pressure on cells in the industrial environment. During shake-flask cultivations using a synthetic medium at 37 °C, industrial strains presented higher ethanol yields on glucose than the laboratory strains, indicating that they could have been selected for this trait-a response to energy-demanding fermentation conditions. These results might be useful to guide future improvements of large-scale fuel ethanol production via engineering of stress tolerance traits in other strains, and eventually also for promoting the use of these fuel ethanol strains in different industrial bioprocesses.

Selected Saccharomyces cerevisiae strains are used in Brazil to produce the hitherto most energetically efficient first-generation fuel ethanol. Although genome and some transcriptome data are available for some of these strains, quantitative physiological data are lacking. This study investigates the physiology of S. cerevisiae strain PE-2, widely used in the Brazilian fuel ethanol industry, in comparison with CEN.PK113-7D, a reference laboratory strain, focusing on tolerance to low pH and acetic acid stress. Both strains were grown in anaerobic bioreactors, operated as batch, chemostat or dynamic continuous cultures. Despite their different backgrounds, biomass and product formation by the two strains were similar under a range of conditions (pH 5 or pH < 3, with or without 105 mM acetic acid added). PE-2 displayed a remarkably higher fitness than CEN.PK113-7D during batch cultivation on complex Yeast extract - Peptone - Dextrose medium at low pH (2.7). Kinetics of viability loss of non-growing cells, incubated at pH 1.5, indicated a superior survival of glucose-depleted PE-2 cells, when compared with either CEN.PK113-7D or a commercial bakers' strain. These results indicate that the sulfuric acid washing step, used in the fuel ethanol industry to decrease bacterial contamination due to non-aseptic operation, might have exerted an important selective pressure on the microbial populations present in such environments.

Cell immobilisation is the physical restriction of cells in a delimited region by means of physical and chemical approaches. It usually comprises a solid support containing cell biomass. In brewing fermentations, yeast cell immobilisation was widely explored during the 1970s to the 90s, with the expectation that immobilised systems would revolutionise the brewing industry. The most studied immobilisation method has been the attachment to a surface and entrapment within a porous solid. Some industrial applications were developed, but the flavour profile of the product rarely matched that produced by batch fermentation. Numerous factors are important in immobilised yeast systems and its successful industrial implementation. Although cell immobilisation results in many advantages, such as high biomass loading and ease of cell reuse, there are drawbacks including physiological changes and mass transfer limitations. Therefore, in order to design a feasible brewing fermentation process using immobilised yeast cells, the solid support, immobilisation method and the bioreactor system require to be properly developed. In this review, yeast cell immobilisation technology in brewing is considered together with methods of immobilisation with the associated advantages and drawbacks. Physiological and metabolic alterations in yeast are also explored and industrial applications are highlighted. It is suggested that immobilisation technology has new opportunities as the market is increasingly open to novel flavours and styles.

There is an ever-increasing demand for reduction of unit operations and a growing interest in the physiology of yeasts used in beer fermentation. In this context, cell immobilization is an interesting alternative, since it reduces steps to separate biomass from fermented broth. Yet, physiological alterations in yeast metabolism caused by immobilization are still to be fully described. Thus, the main objective of this work was to evaluate the physiology of three brewer's S. cerevisiae yeast strains (SY025, SY067 and SY001) immobilized on a porous cellulose-based support. Batch fermentations in malt extract 12 degree P were carried out for all strains both in free and immobilized forms in order to compare kinetic parameters obtained from distinct process conditions. Mathematical modeling was performed following two viewpoints: modeling of fermentation kinetics by parameter estimation from experimental data and application of a reaction-diffusion model for estimation of substrate concentration gradient inside the immobilization support. Moreover, fermentations with different initial substrate and biomass concentrations were carried out using strain SY025, aiming to evaluate their influence over flavor compounds, using statistical models. Compared to free cells, immobilized yeasts showed both higher glycerol yield (SY025, 40%; SY067, 53%; SY001, 19%) and biomass yield in the system (SY025, 67%; SY067, 78%; SY001, 56%). On the other hand, free cells presented higher ethanol yields when compared to immobilized ones (SY025, 9%; SY067, 9%; and SY001, 13%). According to the model developed, a substrate gradient inside the support was predicted, but with low mass transfer limitations.

The maximum specific growth rate of a microbe in a given growth condition is of primary relevance for biological research and bioprocess development. In the case of the unicellular yeast Saccharomyces cerevisiae, this physiological parameter is routinely calculated in (almost) every laboratory, but this procedure conceals several challenges that are often neglected in scientific works, which might lead to misinterpretation of the reported data and of phenomena. We present here several pitfalls involved in µMAX calculation and interpretation, which was achieved through comparative analyses of: 1) the use of different methodologies for determining cell concentration, 2) different calibration procedures to correlate indirect (e.g. absorbance) to direct (e.g. dry cell mass) cell concentration measurements, 3) different statistical methods for determining the significance of µMAX differences, 4) the influence of culture media composition, and 5) the influence of the cultivation system (e.g. microplate, shake-flask or bioreactor). It becomes clear that each of these factors has a great influence on µMAX calculation and interpretation. We also present a case study involving three yeast strains and three different carbon sources, illustrating that opposite conclusions can be drawn in a screening procedure, if proper caution is not taken during data generation and analysis. Last but not least, we conclude this work with a series of recommendations that we believe could make experimental planning, data generation, µMAX calculation and interpretation more meaningful and scientifically sound, contributing to the improvement of yeast research and of microbiology in general.