Application of the Cre-loxP system for multiple gene disruption in the yeast kluyveromyces marxianus

The yeast Kluyveromyces marxianus presents several interesting features that make this species a promising industrial yeast for the production of several compounds. In order to take full advantage of this yeast and its particular properties, proper tools for gene disruption and metabolic engineering are needed. The Cre-loxP system is a very versatile tool that allows for gene marker rescue, resulting in mutant strains free of exogenous selective markers, which is a very important aspect for industrial application. As the Cre-loxP system works in some non-conventional yeasts, namely Kluyveromyces lactis, we wished to know whether it also works in K. marxianus. Here, we report the validation of this system in K. marxianus CBS 6556, by disrupting two copies of the LAC4 gene, which encodes a β-galactosidase activity.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - (CAPES), Brazil;Agência de Inovação - projecto UMINHO/POCI-Zimlac/BI/2/0

Towards a genome-scale metabolic model for the Kluyveromyces lactis yeast

The interest in Kluyveromyces lactis (K. lactis) has begun in academia due to its ability to metabolize the betaglycoside (1). Since then, this yeast has been considered a model organism for studies in genetics and physiology (2). This yeast had its genome sequenced back in 2004 (3) and recently we have published a full metabolic re-annotation of its genome (4). This re-annotation can be used, among other applications, to reconstruct genome-scale metabolic models. These models allow anticipating a given organism's phenotype from its genome sequence. The reconstruction of biochemical networks is, currently, a valid alternative to microorganisms modelling as the output provided by the in silico simulations permits focusing on experiments with promising results. Thus, we propose a new fully compartmentalised genome-scale metabolic model for K. lactis, the iOD1759 which comprises 1759 metabolic genes

Reconstructing genome-scale metabolic models with Merlin

The reconstruction of genome-scale metabolic models is based on the well-known stoichiometry of biochemical reactions. Usually the main objective of a reconstruction is the in silico simulation of the phenotypic behaviour of a microorganism, under different environmental and genetic conditions, thus representing an important tool in Metabolic Engineering. The genome of the yeast Kluyveromyces lactis was used as a case study for this method, providing information for the first stage of the reconstruction of this eukaryote. Given and input of 5085 gene sequences, Merlin identified more than 4200 distinct organisms and approximately 394.000 genes with sequence similarities to the K. lactis genome. This information, after user appraisal, will be used to assemble a metabolic model with the reactions catalysed by the enzymes encoded in the genome. Such model, in the SBML format, can be used as a first raw approach to the study of the K. lactis metabolism

Genome-wide metabolic (re-) annotation of Kluyveromyces lactis

Even before having its genome sequence published in 2004, Kluyveromyces lactis had long been considered a model organism for studies in genetics and physiology. Research on Kluyveromyces lactis is quite advanced and this yeast species is one of the few with which it is possible to perform formal genetic analysis. Nevertheless, until now, no complete metabolic functional annotation has been performed to the proteins encoded in the Kluyveromyces lactis genome. Results In this work, a new metabolic genome-wide functional re-annotation of the proteins encoded in the Kluyveromyces lactis genome was performed, resulting in the annotation of 1759 genes with metabolic functions, and the development of a methodology supported by merlin (software developed in-house). The new annotation includes novelties, such as the assignment of transporter superfamily numbers to genes identified as transporter proteins. Thus, the genes annotated with metabolic functions could be exclusively enzymatic (1410 genes), transporter proteins encoding genes (301 genes) or have both metabolic activities (48 genes). The new annotation produced by this work largely surpassed the Kluyveromyces lactis currently available annotations. A comparison with KEGG's annotation revealed a match with 844 (~90%) of the genes annotated by KEGG, while adding 850 new gene annotations. Moreover, there are 32 genes with annotations different from KEGG. Conclusions The methodology developed throughout this work can be used to re-annotate any yeast or, with a little tweak of the reference organism, the proteins encoded in any sequenced genome. The new annotation provided by this study offers basic knowledge which might be useful for the scientific community working on this model yeast, because new functions have been identified for the so-called metabolic genes. Furthermore, it served as the basis for the reconstruction of a compartmentalized, genome-scale metabolic model of Kluyveromyces lactis, which is currently being finished.This work was partially supported by the MIT-Portugal Program in Bioengineering (MIT-Pt/BS-BB/0082/2008) and a PhD grant (SFRH / BD / 47307 / 2008) from Portuguese FCT (Fundacao para a Ciencia e Tecnologia)

iOD962 - the first genome-scale metabolic model of Kluyveromyces lactis

The genome-scale metabolic model of Kluyveromyces lactis was reconstructed from its genome annotation. The result was the partially compartmentalized (5 compartments) iOD962 metabolic model composed of 2038 reactions and 1561 metabolites. Previous chemostate experiments were used to adjust the maintenance ATP parameter, and the model proved valuable when predicting the biomass, oxygen and carbon dioxide yields. Also, the in silico knockouts predicted accurately the in vivo phenotypes, when compared to published experiments. This model allowed determining a minimal medium for cultivating K. lactis and will surely allow elucidating insights on the milk yeast metabolism as well as identifying engineering targets for the improvement of the production of by-products of interest by performing in silico simulations

Anaerobiosis revisited: growth of Saccharomyces cerevisiae under extremely low oxygen availability

The budding yeast Saccharomyces cerevisiae plays an important role in biotechnological applications, ranging from fuel ethanol to recombinant protein production. It is also a model organism for studies on cell physiology and genetic regulation. Its ability to grow under anaerobic conditions is of interest in many industrial applications. Unlike industrial bioreactors with their low surface area relative to volume, ensuring a complete anaerobic atmosphere during microbial cultivations in the laboratory is rather difficult. Tiny amounts of O2 that enter the system can vastly influence product yields and microbial physiology. A common procedure in the laboratory is to sparge the culture vessel with ultrapure N2 gas; together with the use of butyl rubber stoppers and norprene tubing, O2 diffusion into the system can be strongly minimized. With insights from some studies conducted in our laboratory, we explore the question ‘how anaerobic is anaerobiosis?’. We briefly discuss the role of O2 in non-respiratory pathways in S. cerevisiae and provide a systematic survey of the attempts made thus far to cultivate yeast under anaerobic conditions. We conclude that very few data exist on the physiology of S. cerevisiae under anaerobiosis in the absence of the anaerobic growth factors ergosterol and unsaturated fatty acids. Anaerobicity should be treated as a relative condition since complete anaerobiosis is hardly achievable in the laboratory. Ideally, researchers should provide all the details of their anaerobic set-up, to ensure reproducibility of results among different laboratories. A correction to this article is available online at http://eprints.whiterose.ac.uk/131930/ https://doi.org/10.1007/s00253-018-9036-

Metabolic network analysis of Saccharomyces cerevisiae.

Análise de Redes Metabólicas foi aplicada à cepa de Saccharomyces cerevisiae CEN.PK113-7D, e a alguns mutantes interrompidos em genes que codificam para proteínas regulatórias envolvidas no fenômeno de repressão por glicose. Todas as cepas foram cultivadas em aerobiose, em meio mínimo contendo [1-13C]glicose como substrato limitante. As células eram recolhidas em situação de crescimento balanceado e submetidas à hidrólise, seguida de derivação e posterior injeção da amostra resultante num cromatógrafo gasoso acoplado a um espectrômetro de massa, para análise da marcação em alguns fragmentos de metabólitos intracelulares. Estes dados serviram como base para a identificação da atividade de algumas vias metabólicas no metabolismo central de S. cerevisiae. Além disto, utilizando-os juntamente com um modelo estequiométrico, foi possível obter uma estimativa para os fluxos no metabolismo central na cepa referência e nos mutantes estudados. Num primeiro momento, a metodologia foi validada para cultivos contínuos e descontínuos. Calculou-se um desvio padrão para a medida da marcação em cada fragmento de metabólito detectado pela metodologia empregada. Na cepa referência, observou-se que o ciclo de Krebs opera de forma cíclica em células que respiram e de forma não cíclica em células que apresentam metabolismo respiratório-fermentativo. Verificou-se que uma maior parte da glicose consumida é desviada para a via das pentoses fosfato no primeiro caso, em relação ao segundo. Foram encontradas evidências para a biossíntese de glicina através da enzima treonina aldolase e para a atividade da enzima málica. A ausência das proteínas Mig1 e Mig2 não altera os padrões de crescimento, produção de etanol e de marcação em metabólitos intracelulares de S. cerevisiae. Já a ausência de Hxk2, Reg1 ou Grr1 provoca alívio na repressão por glicose, observado pelo aumento das atividades respiratórias.Metabolic Network Analysis was applied to the reference strain CEN.PK113-7D of Saccharomyces cerevisiae, as well as to some mutants disrupted in genes which code for regulatory proteins involved in the glucose repression cascade. All strains were cultivated under aerobic conditions, using minimal medium with [1-13C]glucose as the limiting substrate. Cells were harvested under balanced growth conditions and submitted to hydrolysis, derivatization and injection of the sample into a gas chromatograph coupled to a mass spectrometer for analysis of the labeling pattern in some fragments of intracellular metabolites. These data were used for identifying the activity of some pathways in the central metabolism of S. cerevisiae. Furthermore, using the data together with a stoichiometric model, it was possible to estimate the fluxes in the central metabolism of the reference strain and in the mutant strains. First, the methodology was validated for batch and continuous cultivations. Standard deviations were calculated for the measurement of the fractional labeling in each of the detected fragments. In the reference strain, it was observed that the Krebs cycle operates in a cyclic manner in respiratory cells, whereas it operates in a non cyclic manner under respiro-fermentative metabolism. It was also seen that a greater part of the glucose consumed by the cells enters the pentose phosphate pathway in the former than in the later case. Evidence for the activity of the threonine aldolase and the malic enzyme catalyzed reactions was also found. The absence of the Mig1 and Mig2 proteins does not alter the growth, ethanol formation and labeling pattern of intracellular metabolites in S. cerevisiae. In contrast, the absence of Hxk2, Reg1, or Grr1 provoques a relief in glucose repression, which was observed by an increased respiratory activity