Evaluating accessibility, usability and interoperability of genome-scale metabolic models for diverse yeasts species

Metabolic network reconstructions have become an important tool for probing cellular metabolism in the field of systems biology. They are used as tools for quantitative prediction but also as scaffolds for further knowledge contextualization. The yeast Saccharomyces cerevisiae was one of the first organisms for which a genome-scale metabolic model (GEM) was reconstructed, in 2003, and since then 45 metabolic models have been developed for a wide variety of relevant yeasts species. A systematic evaluation of these models revealed that-despite this long modeling history-the sequential process of tracing model files, setting them up for basic simulation purposes and comparing them across species and even different versions, is still not a generalizable task. These findings call the yeast modeling community to comply to standard practices on model development and sharing in order to make GEMs accessible and useful for a wider public

Systems-level approaches for understanding and engineering of the oleaginous cell factory Yarrowia lipolytica

Concerns about climate change and the search for renewable energy sources together with the goal of attaining sustainable product manufacturing have boosted the use of microbial platforms to produce fuels and high-value chemicals. In this regard, Yarrowia lipolytica has been known as a promising yeast with potentials in diverse array of biotechnological applications such as being a host for different oleochemicals, organic acid, and recombinant protein production. Having a rapidly increasing number of molecular and genetic tools available, Y. lipolytica has been well studied amongst oleaginous yeasts and metabolic engineering has been used to explore its potentials. More recently, with the advancement in systems biotechnology and the implementation of mathematical modeling and high throughput omics data-driven approaches, in-depth understanding of cellular mechanisms of cell factories have been made possible resulting in enhanced rational strain design. In case of Y. lipolytica, these systems-level studies and the related cutting-edge technologies have recently been initiated which is expected to result in enabling the biotechnology sector to rationally engineer Y. lipolytica-based cell factories with favorable production metrics. In this regard, here, we highlight the current status of systems metabolic engineering research and assess the potential of this yeast for future cell factory design development

Synthetic biology tools for engineering Yarrowia lipolytica

The non-conventional oleaginous yeast Yarrowia lipolytica shows great industrial promise. It naturally produces certain compounds of interest but can also artificially generate non-native metabolites, thanks to an engineering process made possible by the significant expansion of a dedicated genetic toolbox. In this review, we present recently developed synthetic biology tools that facilitate the manipulation of Y. lipolytica, including 1) DNA assembly techniques, 2) DNA parts for constructing expression cassettes, 3) genome-editing techniques, and 4) computational tools

Yeast Biotechnology 2.0

Yeasts are truly fascinating microorganisms. Due to their diverse and dynamic activities, they have been used for the production of many interesting products, such as beer, wine, bread, biofuels, and biopharmaceuticals. Saccharomyces cerevisiae (brewers’ or bakers’ yeast) is the yeast species that is surely the most exploited by humans. Saccharomyces is a top-choice organism for industrial applications, although its use for producing beer dates back to at least the 6th millennium BC. Bakers’ yeast has been a cornerstone of modern biotechnology, enabling the development of efficient production processes. Today, diverse yeast species are explored for industrial applications. This Special Issue “Yeast Biotechnology 2.0” is a continuation of the first Special Issue, “Yeast Biotechnology” (https://www.mdpi.com/books/pdfview/book/324). It compiles the current state-of-the-art of research and technology in the area of “yeast biotechnology” and highlights prominent current research directions in the fields of yeast synthetic biology and strain engineering, new developments in efficient biomolecule production, fermented beverages (beer, wine, and honey fermentation), and yeast nanobiotechnology.

Genome-scale modeling of yeast metabolism: retrospectives and perspectives

Yeasts have been widely used for production of bread, beer and wine, as well as for production of bioethanol, but they have also been designed as cell factories to produce various chemicals, advanced biofuels and recombinant proteins. To systematically understand and rationally engineer yeast metabolism, genome-scale metabolic models (GEMs) have been reconstructed for the model yeast Saccharomyces cerevisiae and nonconventional yeasts. Here, we review the historical development of yeast GEMs together with their recent applications, including metabolic flux prediction, cell factory design, culture condition optimization and multi-yeast comparative analysis. Furthermore, we present an emerging effort, namely the integration of proteome constraints into yeast GEMs, resulting in models with improved performance. At last, we discuss challenges and perspectives on the development of yeast GEMs and the integration of proteome constraints

Genome-scale modeling of yeast: chronology, applications and critical perspectives

Over the last 15 years, several genome-scale metabolic models (GSMMs) were developed for different yeast species, aiding both the elucidation of new biological processes and the shift toward a bio-based economy, through the design of in silico inspired cell factories. Here, an historical perspective of the GSMMs built over time for several yeast species is presented and the main inheritance patterns among the metabolic reconstructions are highlighted. We additionally provide a critical perspective on the overall genome-scale modeling procedure, underlining incomplete model validation and evaluation approaches and the quest for the integration of regulatory and kinetic information into yeast GSMMs. A summary of experimentally validated model-based metabolic engineering applications of yeast species is further emphasized, while the main challenges and future perspectives for the field are finally addressedThis work was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of a Ph.D. grant (PD/BD/52336/2013), of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01–0145FEDER-006684) and also in the context of the EU-funded initiative ERA-NET for Industrial Biotechnology (ERA-IB-2/0003/2013), in addition to the BioTecNorte operation (NORTE-01–0145FEDER-000004) funded by European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte.info:eu-repo/semantics/publishedVersio

Expanding the Genetic Toolbox to Improve Metabolic Engineering in the Industrial Oleaginous Yeast, \u3cem\u3eYarrowia lipolytica\u3c/em\u3e

The oleaginous yeast, Yarrowia lipolytica, is becoming a popular host for industrial biotechnology because of its ability to grow on non-conventional feedstocks and naturally accumulate significant amounts of lipids. With new genome editing technologies, engineering novel pathways to produce lipid-derived oleochemicals has become easier. The goal, however, is to expand the genetic toolbox to improve the efficiency of metabolic engineering such that production capacities could expand from proof-of-concept shake flasks to an industrial scale. Building efficient metabolic circuits require controlling strength and timing of several enzymes in a metabolic pathway. One method to do this is through transcription – using suitable promoters to control expression of genes that code for enzymes. Native promoters have limited application because of complex regulation and non-tunable expression. Engineering hybrid promoters alleviates these issues to obtain predictable and tunable gene expression. In Y. lipolytica, how to design these promoters is not fully understood, resulting in only a handful of engineered promoters to date. In this work, we aim to develop tools for gene expression by investigating promoter architecture and designing tunable systems. In addition to Upstream Activating Sequences (UAS), tuning promoter strength can be achieved by varying sequence in the core promoter, TATA motif, and adjacent proximal sequences. UASs can modulate transcription strength and inducibility, enabling controlled timing of expression. A promoter of the acyl-CoA oxidase 2 (POX2) from the β-oxidation pathway was truncated heuristically to identify oleic acid (OA) UAS sequences. By fusing tandem repeats of the OA UAS elements, tunable yet inducible fatty acid hybrid promoters were engineered. The current approaches to identify novel UAS elements in Y. lipolytica are laborious. Therefore, we investigated DNA accessibility through nucleosome positioning to determine if a relationship between POX2 UASs and DNA accessibility can be inferred. The goal is to eventually apply this approach develop newer hybrid promoters efficiently. Finally, the hybrid fatty acid inducible promoter we developed was used to rationally engineering a Y. lipolytica strain capable of producing high amounts of free fatty acids. By localizing the fatty acyl / fatty aldehyde reductase in the peroxisome, we compartmentalized fatty alcohol production. This strategy led to upwards of 500 mg/L of fatty alcohols produced. It is a promising route to eventually make short to medium chain fatty alcohols in Y. lipolytica by utilizing the native β-oxidation machinery

Fine-tuning mitochondrial activity in Yarrowia lipolytica for citrate overproduction

ABSTRACT: Yarrowia lipolytica is a non-conventional yeast with promising industrial potentials for lipids and citrate production. It is also widely used for studying mitochondrial respiration due to a respiratory chain like those of mammalian cells. In this study we used a genome-scale model (GEM) of Y. lipolytica metabolism and performed a dynamic Flux Balance Analysis (dFBA) algorithm to analyze and identify metabolic levers associated with citrate optimization. Analysis of fluxes at stationary growth phase showed that carbon flux derived from glucose is rewired to citric acid production and lipid accumulation, whereas the oxidative phosphorylation (OxPhos) shifted to the alternative respiration mode through alternative oxidase (AOX) protein. Simulations of optimized citrate secretion flux resulted in a pronounced lipid oxidation along with reactive oxygen species (ROS) generation and AOX flux inhibition. Then, we experimentally challenged AOX inhibition by adding n-Propyl Gallate (nPG), a specific AOX inhibitor, on Y. lipolytica batch cultures at stationary phase. Our results showed a twofold overproduction of citrate (20.5 g/L) when nPG is added compared to 10.9 g/L under control condition (no nPG addition). These results suggest that ROS management, especially through AOX activity, has a pivotal role on citrate/lipid flux balance in Y. lipolytica. All taken together, we thus provide for the first time, a key for the understanding of a predominant metabolic mechanism favoring citrate overproduction in Y. lipolytica at the expense of lipids accumulation

In silico identification of metabolic engineering strategies for improved lipid production in Yarrowia lipolytica by genome-scale metabolic modeling

Background Yarrowia lipolytica, an oleaginous yeast, is a promising platform strain for production of biofuels and oleochemicals as it can accumulate a high level of lipids in response to nitrogen limitation. Accordingly, many metabolic engineering efforts have been made to develop engineered strains of Y. lipolytica with higher lipid yields. Genome-scale model of metabolism (GEM) is a powerful tool for identifying novel genetic designs for metabolic engineering. Several GEMs for Y. lipolytica have recently been developed; however, not many applications of the GEMs have been reported for actual metabolic engineering of Y. lipolytica. The major obstacle impeding the application of Y. lipolytica GEMs is the lack of proper methods for predicting phenotypes of the cells in the nitrogen-limited condition, or more specifically in the stationary phase of a batch culture. Results In this study, we showed that environmental version of minimization of metabolic adjustment (eMOMA) can be used for predicting metabolic flux distribution of Y. lipolytica under the nitrogen-limited condition and identifying metabolic engineering strategies to improve lipid production in Y. lipolytica. Several well-characterized overexpression targets, such as diglyceride acyltransferase, acetyl-CoA carboxylase, and stearoyl-CoA desaturase, were successfully rediscovered by our eMOMA-based design method, showing the relevance of prediction results. Interestingly, the eMOMA-based design method also suggested non-intuitive knockout targets, and we experimentally validated the prediction with a mutant lacking YALI0F30745g, one of the predicted targets involved in one-carbon/methionine metabolism. The mutant accumulated 45% more lipids compared to the wild-type. Conclusion This study demonstrated that eMOMA is a powerful computational method for understanding and engineering the metabolism of Y. lipolytica and potentially other oleaginous microorganisms.This research was supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF2017R1E1A1A01073523) and Industrial Strategic technology development program, 20002734 funded by the Ministry of Trade, Industry & Energy (MI, Korea

Structural-functional studies of carboxylic acid transporters : novel tools in production optimization using industrial microbes

Dissertação de mestrado em Molecular GeneticsThe rising global energy demands in last century drive to worrying depletion levels of fossil fuels, leading to a growing interest in microbial biofuel synthesis, particularly in model organisms like Saccharomyces cerevisiae. The microbial conversion of sugars to biofuels is a promising technology, thus envisaging for more efficient metabolic pathways has been attempted. Indeed byproducts of biomass pretreatment processes and the biofuels themselves are often toxic at industrially-relevant levels., therefore efforts to improve production yield by engineering efflux systems to overcome toxicity problems and secret inhibitory chemicals from the cell has been revealed as a crucial alternative. In this scope, the aim of the present work was to screen a wide range of promising membrane transporters for the transport of carboxylic acids, particularly for xylonic acid, mucic acid, saccharic acid, gluconic acid and xylaric acid in the yeast S. cerevisiae. During this study a considerable number of membrane proteins, known as carboxylic acid transporters from different yeasts species were screened and functionally characterized in regard to the transport of mono- and dicarboxylic acids with biotechnological application, such as xylonic and gluconic acids, and saccharic, mucic and xylaric acids, respectively. Among the transporters tested, we have found evidences for the transport of four carboxylic acids, mucic, xylaric, gluconic and saccharic acids with the following specificities: gluconic acid (Ki of 13.2 mM and 40.6 mM), xylaric acid (Ki of 27.6 mM), mucic acid (Ki of 32.9 mM) and saccharic acid (Ki of 24.1 mM and 24.7 mM). These results revealed to be very promising for future work aiming at engineering proper microbial strains with increased ability to export biofuel acids to external medium.A crescente procura de combustíveis fósseis a que se assistiu no último século levou a que se atingissem limites de exploração preocupantes, redirecionando a atenção para a síntese microbiana de biocombustíveis, em particular através organismo modelo Saccharomices cerevisiae. A conversão microbiana de açúcares em biocombustíveis temse revelado uma tecnologia promissora, pelo que novas tentativas de melhorar a eficiência das vias metabólicas envolvidas no processo de síntese têm sido testadas. Tanto os produtos resultantes do processamento de biomassa como os próprios biocombustíveis exercem regularmente um efeito tóxico na produção à escala industrial. Nesse sentido, importantes esforços têm sido levados a cabo para desenvolver novos sistemas de efluxo com o intuito de reduzir problemas de toxicidade e conduzir para o exterior da célula diferentes compostos químicos. Neste contexto, o objetivo do presente trabalho é desvendar o potencial de diferentes transportadores de membrana para o transporte de ácidos carboxílicos em S. cerevisiae. Ao longo deste estudo, várias proteínas de membrana, conhecidas como transportadores de ácidos carboxílicos provenientes de diferentes espécies de leveduras foram testadas e caracterizadas funcionalmente no que respeita ao transporte de ácidos mono e dicarboxílicos com interesse biotecnológico, tais como ácidos xilónico e glucónico, e ácidos sacárico, mucico e xilárico, respetivamente. De entre os transportadores testados foram encontradas evidências para o transporte de quatro ácidos carboxílicos, a saber os ácidos mucico, xilárico, glucónico e sacárico com as respetivas especificidades: ácido glucónico (Ki de 13,2 mM e 40,6 mM), ácido xilárico (Ki de 27,6 mM), ácido mucico (Ki de 32,9 mM) e ácido sacárico (de 24,1 mM e 24,7 mM). Estes resultados revelam-se bastante promissores para futuros estudos que envolvam a obtenção de estirpes microbianas com capacidade desenvolvida para excretar biocombustíveis