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

Lopes, Helena; Rocha, Isabel

doi:10.1093/femsyr/fox050

Cited by 60 publications

(54 citation statements)

References 157 publications

(166 reference statements)

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“…Despite the methodology for the reconstruction of genome-scale metabolic models being standardized, eukaryotic models remain a challenge, due to their large genomes and complexity [ 79 ]. These models always seek to get as close as possible to reality; however, given the complexity of the networks, they are always subject to some errors, which may cause small deviations in the predictions.…”

Section: Resultsmentioning

confidence: 99%

“…These models always seek to get as close as possible to reality; however, given the complexity of the networks, they are always subject to some errors, which may cause small deviations in the predictions. Some errors may include incorrect assignment of GPR associations, reaction directionality or reversibility, incongruous stoichiometric parameters, missing reactions and inaccurate biomass composition [ 79 ]. Additionally, network properties, that go beyond metabolism, cannot be addressed with currently existing modeling tools at a global scale, thus limiting the predictive power that may be drawn from global stoichiometric models.…”

Section: Resultsmentioning

confidence: 99%

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Genome-Scale Metabolic Model of the Human Pathogen Candida albicans: A Promising Platform for Drug Target Prediction

Viana

Dias

Lagoa

et al. 2020

JoF

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Candida albicans is one of the most impactful fungal pathogens and the most common cause of invasive candidiasis, which is associated with very high mortality rates. With the rise in the frequency of multidrug-resistant clinical isolates, the identification of new drug targets and new drugs is crucial in overcoming the increase in therapeutic failure. In this study, the first validated genome-scale metabolic model for Candida albicans, iRV781, is presented. The model consists of 1221 reactions, 926 metabolites, 781 genes, and four compartments. This model was reconstructed using the open-source software tool merlin 4.0.2. It is provided in the well-established systems biology markup language (SBML) format, thus, being usable in most metabolic engineering platforms, such as OptFlux or COBRA. The model was validated, proving accurate when predicting the capability of utilizing different carbon and nitrogen sources when compared to experimental data. Finally, this genome-scale metabolic reconstruction was tested as a platform for the identification of drug targets, through the comparison between known drug targets and the prediction of gene essentiality in conditions mimicking the human host. Altogether, this model provides a promising platform for global elucidation of the metabolic potential of C. albicans, possibly guiding the identification of new drug targets to tackle human candidiasis.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Genome-Scale Metabolic Model of the Human Pathogen Candida albicans: A Promising Platform for Drug Target Prediction

Viana

Dias

Lagoa

et al. 2020

JoF

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“…Compared to mammalian cells, yeasts have simpler genomes and can be more easily characterized and modified [3]. Combine this with tools such as CRISPR/cas9 and the range of tractable organisms is expanding [4,5]. Komagataella phaffii (one of two species previously known as P. pastoris) stands out for its high-protein secretion capacity, its ability to metabolize methanol as its primary carbon source, and its safety record as a source of biologics [3].…”

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Protein Biogenesis Demands of the Early Secretory Pathway in Komagataella Phaffii

Alva¹,

Riera²,

Chartron³

2020

Preprint

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Background: Eukaryotes use distinct networks of biogenesis factors to synthesize, fold, monitor, traﬃc, and secrete proteins. During heterologous expression, saturation of any of these networks may bottleneck titer and yield. To understand the ﬂux through various routes into the early secretory pathway, we quantiﬁed the global and membrane-associated translatomes of Komagataella phaﬃi. Results: By coupling Ribo-seq with long-read mRNA sequencing, we generated a new annotation of protein-encoding genes. By using Ribo-seq with subcellular fractionation, we quantiﬁed demands on co- and posttranslational translocation pathways. During exponential growth in rich media, protein components of the cell-wall represent the greatest number of nascent chains entering the ER. Transcripts encoding the transmembrane protein PMA1 sequester more ribosomes at the ER membrane than any others. Comparison to Saccharomyces cerevisiae reveals conservation in the resources allocated by gene ontology, but variation in the diversity of gene products entering the secretory pathway. Conclusion: A subset of host proteins, particularly cell-wall components, impose the greatest biosynthetic demands in the early secretory pathway. These proteins are potential targets in strain engineering aimed at alleviating bottlenecks during heterologous protein production.

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“…The original versions of these models typically undergo incremental improvements. In particular, 10 different versions of the Saccharomyces cerevisiae metabolic network have been produced to date, by implementing cellular compartments, curated reactions, standard nomenclature, and even transcriptional regulation, as reviewed in [5]. However, less extensive efforts have been dedicated to other so-called non-conventional or non-Saccharomyces yeast species, despite their relevance for biotechnological applications, as well as for basic and biomedical research.…”

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confidence: 99%

Genome-scale metabolic reconstruction of the stress-tolerant hybrid yeast Zygosaccharomyces parabailii

Filippo

Ortiz‐Merino

Damiani

et al. 2018

Preprint

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Funding informationGenome-scale metabolic models are powerful tools to understand and engineer cellular systems facilitating their use as cell factories. This is especially true for microorganisms with known genome sequences from which nearly complete sets of enzymes and metabolic pathways are determined, or can be inferred. Yeasts are highly diverse eukaryotes whose metabolic traits have long been exploited in industry, and although many of their genome sequences are available, few genome-scale metabolic models have so far been produced. For the first time, we reconstructed the genomescale metabolic model of the hybrid yeast Zygosaccharomyces parabailii, which is a member of the Z. bailii sensu lato clade notorious for stress-tolerance and therefore relevant to industry. The model comprises 3096 reactions, 2091 metabolites, and 2413 genes. Our own laboratory data were then used to establish a biomass synthesis reaction, and constrain the extracellular environment. Through constraint-based modeling, our model reproduces the co-consumption and catabolism of acetate and glucose posing it as a promising platform for understanding and exploiting the metabolic po-1 2 MARZIA DI FILIPPO ET AL tential of Z. parabailii. K E Y W O R D SGenome-scale metabolic model/ constraint-based modeling / hybrid yeast / stress tolerance / Zygosaccharomyces parabailii 1 | INTRODUCTION Current genome sequencing technologies allow a fast and cheap overview into the genetic composition of virtually any organism, but connecting such genotypes to observed phenotypes remains a challenge. The reconstruction of genome-scale metabolic networks provide structured frameworks to represent the biochemical transformations within a target organism as complex genotype-phenotype relationships. Afterwards, different modeling approaches can be used to simulate, understand, predict and eventually control the behavior of such genome-scale metabolic networks.Flux Balance Analysis (FBA) is a widely used constraint-based modeling approach that relies on linear programming and the optimization of a given objective function (e.g., maximization of growth) for the determination of the metabolic model flux distribution [1,2]. This approach is based on the assumption that organisms operate under a series of constraints limiting their possible functions, and leading to the definition of allowable cell phenotypes from defined metabolic networks [3].In the last two decades, genome-wide reconstructions of metabolism have been produced for a plethora of model organisms, spanning from bacteria to higher eukaryotes [4]. The original versions of these models typically undergo incremental improvements. In particular, 10 different versions of the Saccharomyces cerevisiae metabolic network have been produced to date, by implementing cellular compartments, curated reactions, standard nomenclature, and even transcriptional regulation, as reviewed in [5]. However, less extensive efforts have been dedicated to other so-called non-conventional or non-Saccharomyces yeast species, de...

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

Cited by 60 publications

References 157 publications

Genome-Scale Metabolic Model of the Human Pathogen Candida albicans: A Promising Platform for Drug Target Prediction

Genome-Scale Metabolic Model of the Human Pathogen Candida albicans: A Promising Platform for Drug Target Prediction

Protein Biogenesis Demands of the Early Secretory Pathway in Komagataella Phaffii

Genome-scale metabolic reconstruction of the stress-tolerant hybrid yeast Zygosaccharomyces parabailii

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