Validation of a constraint-based model of Pichia pastoris metabolism under data scarcity

<p>Abstract</p> <p>Background</p> <p>Constraint-based models enable structured cellular representations in which intracellular kinetics are circumvented. These models, combined with experimental data, are useful analytical tools to estimate the state exhibited (the phenotype) by the cells at given pseudo-steady conditions.</p> <p>Results</p> <p>In this contribution, a simplified constraint-based stoichiometric model of the metabolism of the yeast <it>Pichia pastoris</it>, a workhorse for heterologous protein expression, is validated against several experimental available datasets. Firstly, maximum theoretical growth yields are calculated and compared to the experimental ones. Secondly, possibility theory is applied to quantify the consistency between model and measurements. Finally, the biomass growth rate is excluded from the datasets and its prediction used to exemplify the capability of the model to calculate non-measured fluxes.</p> <p>Conclusions</p> <p>This contribution shows how a small-sized network can be assessed following a rational, quantitative procedure even when measurements are scarce and imprecise. This approach is particularly useful in lacking data scenarios.</p

MCR-ALS on metabolic networks: Obtaining more meaningful pathways

[EN] With the aim of understanding the flux distributions across a metabolic network, i.e. within living cells, Principal Component Analysis (PCA) has been proposed to obtain a set of orthogonal components (pathways) capturing most of the variance in the flux data. The problems with this method are (i) that no additional information can be included in the model, and (ii) that orthogonality imposes a hard constraint, not always reasonably. To overcome these drawbacks, here we propose to use a more flexible approach such as Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) to obtain this set of biological pathways through the network. By using this method, different constraints can be included in the model, and the same source of variability can be present in different pathways, which is reasonable from a biological standpoint. This work follows a methodology developed for Pichia pastoris cultures grown on different carbon sources, lately presented in González-Martínez et al. (2014). In this paper a different grey modelling approach, which aims to incorporate a priori knowledge through constraints on the modelling algorithms, is applied to the same case of study. The results of both models are compared to show their strengths and weaknesses.Research in this study was partially supported by the Spanish Ministry of Science and Innovation and FEDER funds from the European Union through grants DPI2011-28112-C04-01 and DPI2011-28112-C04-02. The authors are also grateful to Biopolis SL for supporting this research.Folch-Fortuny, A.; Tortajada Serra, M.; Prats-Montalbán, JM.; Llaneras Estrada, F.; Picó Marco, JA.; Ferrer Riquelme, AJ. (2015). MCR-ALS on metabolic networks: Obtaining more meaningful pathways. Chemometrics and Intelligent Laboratory Systems. 142:293-303. https://doi.org/10.1016/j.chemolab.2014.10.004S29330314

CONTROL OF CONSTRAINED BIOSYSTEMS

Biological systems (biosystems), due to their complexity and multidisplinary character, are becoming one of the challenging research topics in the field of systems and control. In this work, several tools for dealing with control subject to constraints in the area of biosystems have been explored.Revert Tomás, A. (2011). CONTROL OF CONSTRAINED BIOSYSTEMS. http://hdl.handle.net/10251/12873Archivo delegad

Enhancement of Kluyveromyces marxianus biotechnological potential

Elektroniskā versija nesatur pielikumusKluyveromyces marxianus ir netradicionāls pārtikas raugs, kas spēj patērēt plašu substrātu spektru. Šim raugam ir arī citas priekšrocības, tostarp augsts augšanas ātrums, termotolerance un augsta tādu biotehnoloģiski svarīgu fermentu kā β-galaktozidāzes un inulināzes aktivitāte. Šīs K. marxianus priekšrocības padara to par perspektīvu bioloģiski bagātinātu ķīmisko vielu ražošanai no tādiem atjaunojamiem substrātiem, kā lignoceluloze (ksiloze), polifruktāni (inulīns) un piena sūkalas (laktoze). Mēs izstrādājām nestrukturētu kinētisko modeli un ar biomasu saistītu centrālā metabolisma stehiometrisko modeli. Kinētiskais modelis var kalpot kā rīks bioetanola ražošanas procesu izstrādei un optimizācijai no laktozi un inulīnu saturošiem substrātiem, stehiometriskais modelis atklāj K. marxianus biotehnoloģisko potenciālu rūpnieciskiem pielietojumiem un metabolisma inženierijai. Etiķskābe ir vāja skābe, kas veidojas kā šūnu metabolisma blakusprodukts vai kompleksa substrāta hidrolīzes rezultātā, un ir viens no galvenajiem inhibitoriem, kas kavē K. marxianus plašu industriālo izmantošanu. Darbā mēs pētījām acetāta ietekmi uz četriem K. marxianuscelmiem. Iegūtie rezultāti liecina, ka acetāts inhibē augšanu atkarībā no vides pH, un tam ir izteikta ietekme, ja raugs tiek audzēts uz laktozes vai galaktozes barotnes. Ņemot vērā K. marxianus sugas iekšējo daudzveidību un atšķirības dažādu celmu spējā efektīvi asimilēt laktozi, šajā pētījumā mēs noteicām kopējo β-galaktozidāzes aktivitāti četros K. marxianus celmos (DSM 5422, DSM 5418, DSM 4906 un NCYC 2791), kā arī aktivitātes sadalījumu starp periplazmas un citoplazmas β-galaktozidāzi. Tika konstatēta korelācija starp K. marxianus dažādu celmu toleranci pret acetātu un β-galaktozidāzes lokalizāciju, tādējādi apstiprinot laktozes transportiera lomu acetāta inhibīcijas mehānismāKluyveromyces marxianus is non-conventional food grade yeast capable of consuming a wide spectrum of substrates. This yeast also offers other great benefits including a high growth rate, thermotolerance and possesses hight activities of such biotechnologically important enzymes as β-galactosidase and inulinase. These advantages of K. marxianus make it promising for the production of bio-enriched chemicals from renewable substrates such as lignocellulose (xylose), polyfructans (inulin) and dairy whey (lactose). We developed an unstructured kinetic model and a biomass-linked stoichiometric model of central metabolism. The former can serve as tool to develop and optimise processes for producing bioethanol from lactose- and inulin-containing resources, the latter in turn reveals the biotechnological potential of K. marxianus for industrial applications and metabolic engineering. Acetic acid is weak acid formed as a by-product of cellular metabolism or as a result of hydrolysis of a complex substrate, is the one of main inhibitors that hamper a wide industrial usage of K. marxianus. Here, we investigate the effects of acetate in four K. marxianus strains. Our results indicate that acetate inhibits growth in a pH-dependent manner and has pronounced effects if yeast is grown on lactose or galactose. Bearing in mind the intraspecific diversity in K. marxianus and the differences in the ability to efficiently assimilate lactose between the different strains, we determined the total β-galactosidase activity in the four K. marxianus strains (DSM 5422, DSM 5418, DSM 4906 and NCYC 2791) as well as the distribution of activity between periplasmic and cytoplasmic β-galactosidases in this study. The correlation between acetate tolerance of K. marxianus different strains and localization of β-galactosidase was found thus confirming the role of lactose transporter in inhibition mechanism by acetate

PFA toolbox: a MATLAB tool for Metabolic Flux Analysis

Background: Metabolic Flux Analysis (MFA) is a methodology that has been successfully applied to estimate metabolic fluxes in living cells. However, traditional frameworks based on this approach have some limitations, particularly when measurements are scarce and imprecise. This is very common in industrial environments. The PFA Toolbox can be used to face those scenarios. Results: Here we present the PFA (Possibilistic Flux Analysis) Toolbox for MATLAB, which simplifies the use of Interval and Possibilistic Metabolic Flux Analysis. The main features of the PFA Toolbox are the following: (a) It provides reliable MFA estimations in scenarios where only a few fluxes can be measured or those available are imprecise. (b) It provides tools to easily plot the results as interval estimates or flux distributions. (c) It is composed of simple functions that MATLAB users can apply in flexible ways. (d) It includes a Graphical User Interface (GUI), which provides a visual representation of the measurements and their uncertainty. (e) It can use stoichiometric models in COBRA format. In addition, the PFA Toolbox includes a User s Guide with a thorough description of its functions and several examples. Conclusions: The PFA Toolbox for MATLAB is a freely available Toolbox that is able to perform Interval and Possibilistic MFA estimations.This research has been partially supported by the Spanish Government (FEDER-CICYT: DPI 2014-55276-C5-1-R). Yeimy Morales is grateful for the BR Grants of the University of Girona (BR2012/26). Gabriel Bosque Chacon is recipient of a doctoral fellowship from the Spanish Government (BES-2012-053772).Morales, Y.; Bosque Chacón, G.; Vehi, J.; Picó Marco, JA.; Llaneras, F. (2016). PFA toolbox: a MATLAB tool for Metabolic Flux Analysis. 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Interval and possibilistic methods for constraint-based metabolic models, PhD Thesis. Universidad Politécnica de Valencia: Departamento de Ingeniería de Sistemas y Automática; 2011.Llaneras F, Picó J. An interval approach for dealing with flux distributions and elementary modes activity patterns. J Theor Biol. 2007;246(2):290–308.Llaneras F, Sala A, Picó J. A possibilistic framework for constraint-based metabolic flux analysis. BMC Syst Biol. 2009;3(1):79.Tortajada M, Llaneras F, Picó J. Validation of a constraint-based model of Pichia pastoris metabolism under data scarcity. BMC Syst Biol. 2010;4(1):115.Llaneras F, Picó J. A procedure for the estimation over time of metabolic fluxes in scenarios where measurements are uncertain and/or insufficient. BMC Bioinformatics. 2007;8(1):421.Iyer VV, Ovacik MA, Androulakis IP, Roth CM, Ierapetritou MG. Transcriptional and metabolic flux profiling of triadimefon effects on cultured hepatocytes. 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BMC bioinformatics. 2011;12(1):28.González J, Folch-Fortuny A, Llaneras F, Tortajada M, Picó J, Ferrer A. Metabolic flux understanding of Pichia pastoris grown on heterogenous culture media. Chemometr Intell Lab. 2014;134:89–99.Morales Y, Tortajada M, Picó J, Vehí J, Llaneras F. Validation of an FBA model for Pichia pastoris in chemostat cultures. BMC System Biol. 2014;8(1):142.Stephanopoulos GN, Aristidou AA, Nielsen J. Metabolic Engineering: Principles and Methodologies. San Diego, USA: Academic; 1998.Heijden R, Romein B, Heijnen J, Hellinga C, Luyben K. Linear constraint relations in biochemical reaction systems: I & II. Biotech Bioeng. 1994;43(1):3–10.Lofberg J. YALMIP: A toolbox for modeling and optimization in MATLAB. In: IEEE International Symposium on Computer Aided Control Systems Design. 2004. p. 284–9.YALMIP Home Page [ http://users.isy.liu.se/johanl/yalmip/ ]. Accessed 11 May 2016.IBM ILOG CPLEX- High-performance mathematical programming engine. [ http://www-01.ibm.com/software/commerce/optimization/cplex-optimizer/ ]. Accessed 11 May 2016.GLPK (GNU Linear programming kit) [ http://www.gnu.org/software/glpk/ ]. Accessed 11 May 2016.Orth D, Fleming M, Palsson B. Reconstruction and use of microbial metabolic networks: the core Escherichia coli metabolic model as an educational guide. EcoSal Plus. 2010;4:1.Emmerling M, Dauner M, Ponti A, Fiaux J, Hochuli M, Szyperski T, Wüthrich K, Bailey J, Sauer U. Metabolic flux responses to pyruvate kinase knockout in Escherichia coli. Journal of bacteriology. 2002;184(1):152–64.Orth J, Conrad T, Na J, Lerman J, Nam H, Feist A, Palsson B. A comprehensive genome‐scale reconstruction of Escherichia coli metabolism—2011. Molecular systems biology. 2011;7(1):535.Bonarius H, Schmid G, Tramper J. Flux analysis of underdetermined metabolic networks: the quest for the missing constraints. Trends in Biotechnology. 1997;15(8):308–14.Palsson BØ. Systems biology: properties of reconstructed networks. New York: Cambridge University Press; 2006.Schilling C, Covert M, Famili I, Church G, Edwards J, Palsson B. Genome-scale metabolic model of Helicobacter pylori 26695. Journal of Bacteriology. 2002;184(16):4582–93.Solà A, Jouhten P, Maaheimo H, Sánchez-Ferrando F, Szyperski T, Ferrer P. Metabolic flux profiling of Pichia pastoris grown on glycerol/methanol mixtures in chemostat cultures at low and high dilution rates. Microbiol. 2007;153:281–90.Solà A. Estudi del metabolisme central del carboni de Pichia pastoris, PhD Thesis. Universitat Autònoma de Barceloana: Escola Tècnica Superior d’Enginyeria; 2004.Jungo C, Rerat C, Marison IW, von Stockar U. Quantitative characterization of the regulation of the synthesis of alcohol oxidase and of the expression of recombinant avidin in a Pichia pastoris Mut + strain. Enzyme Microb Technol. 2006;39:936–44.Tortajada M. Process development for the obtention and use of recombinant glycosidases: expression, modelling and immobilization, PhD Thesis. 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Process development for the obtention and use of recombinant glycosidases: expression, modelling and immobilisation

El objetivo general de la presente tesis doctoral es el desarrollo de herramientas para la obtencion, produccion y aplicacion de dos enzimas glicosidicas: �¿-L-arabinofuranosidasa proveniente del hongo Aspergillus niger (Abf) y �À-D-glucosidasa (Bgl), proveniente de la levadura Candida molischiana. Estas hidrolasas se emplean en la liberacion de azucares en procesos de conversion de biomasa y en la industria alimentaria, pero tambien en la sintesis de aminoglicosidos, glicoconjugados y oligosacaridos, compuestos de alto valor anadido para la industria quimico-farmaceutica. Las enzimas se han expresado en la levadura metilotrofica Pichia pastoris, y se han purificado para caracterizar sus propiedades bioquimicas. Asimismo, se ha comprobado su capacidad para catalizar reacciones de transglicosilacion con alto rendimiento. En relacion a su produccion, se ha establecido y validado un modelo basado en restricciones del metabolismo de Pichia pastoris, evaluando su consistencia mediante analisis de flujos metabolicos posibilistico. El modelo permite estimar la tasa de crecimiento y la distribucion de flujos intracelulares a partir de unos pocos flujos extracelulares medidos experimentalmente. Adicionalmente, el modelo se ha extendido para estimar la productividad de proteina recombinante, y se ha empleado para analizar diferentes condiciones de cultivo de las cepas transgenicas que sobreproducen las enzimas Abf y Bgl. Finalmente, las enzimas se han inmobilizado en organosilicas bimodales de la familia UVM-7. Los biocatalizadores resultantes se han caracterizado bioquimica y fisico-quimicamente y se han evaluado en diferentes aplicaciones de interes biotecnologico.Tortajada Serra, M. (2012). Process development for the obtention and use of recombinant glycosidases: expression, modelling and immobilisation [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/16800Palanci

Interval and Possibilistic Methods for Constraint-Based Metabolic Models

This thesis is devoted to the study and application of constraint-based metabolic models. The objective was to find simple ways to handle the difficulties that arise in practice due to uncertainty (knowledge is incomplete, there is a lack of measurable variables, and those available are imprecise). With this purpose, tools have been developed to model, analyse, estimate and predict the metabolic behaviour of cells. The document is structured in three parts. First, related literature is revised and summarised. This results in a unified perspective of several methodologies that use constraint-based representations of the cell metabolism. Three outstanding methods are discussed in detail, network-based pathways analysis (NPA), metabolic flux analysis (MFA), and flux balance analysis (FBA). Four types of metabolic pathways are also compared to clarify the subtle differences among them. The second part is devoted to interval methods for constraint-based models. The first contribution is an interval approach to traditional MFA, particularly useful to estimate the metabolic fluxes under data scarcity (FS-MFA). These estimates provide insight on the internal state of cells, which determines the behaviour they exhibit at given conditions. The second contribution is a procedure for monitoring the metabolic fluxes during a cultivation process that uses FS-MFA to handle uncertainty. The third part of the document addresses the use of possibility theory. The main contribution is a possibilistic framework to (a) evaluate model and measurements consistency, and (b) perform flux estimations (Poss-MFA). It combines flexibility on the assumptions and computational efficiency. Poss-MFA is also applied to monitoring fluxes and metabolite concentrations during a cultivation, information of great use for fault-detection and control of industrial processes. Afterwards, the FBA problem is addressed.Llaneras Estrada, F. (2011). Interval and Possibilistic Methods for Constraint-Based Metabolic Models [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10528Palanci