Whole-genome metabolic model of Trichoderma reesei built by comparative reconstruction

BackgroundTrichoderma reesei is one of the main sources of biomass-hydrolyzing enzymes for the biotechnology industry. There is a need for improving its enzyme production efficiency. The use of metabolic modeling for the simulation and prediction of this organism’s metabolism is potentially a valuable tool for improving its capabilities. An accurate metabolic model is needed to perform metabolic modeling analysis.ResultsA whole-genome metabolic model of T. reesei has been reconstructed together with metabolic models of 55 related species using the metabolic model reconstruction algorithm CoReCo. The previously published CoReCo method has been improved to obtain better quality models. The main improvements are the creation of a unified database of reactions and compounds and the use of reaction directions as constraints in the gap-filling step of the algorithm. In addition, the biomass composition of T. reesei has been measured experimentally to build and include a specific biomass equation in the model.ConclusionsThe improvements presented in this work on the CoReCo pipeline for metabolic model reconstruction resulted in higher-quality metabolic models compared with previous versions. A metabolic model of T. reesei has been created and is publicly available in the BIOMODELS database. The model contains a biomass equation, reaction boundaries and uptake/export reactions which make it ready for simulation. To validate the model, we dem1onstrate that the model is able to predict biomass production accurately and no stoichiometrically infeasible yields are detected. The new T. reesei model is ready to be used for simulations of protein production processes.

[1]  Adam M. Feist,et al.  The biomass objective function. , 2010, Current opinion in microbiology.

[2]  Sarah M. Keating,et al.  BioModels: Content, Features, Functionality, and Use , 2015, CPT: pharmacometrics & systems pharmacology.

[3]  Rick L Stevens,et al.  iBsu1103: a new genome-scale metabolic model of Bacillus subtilis based on SEED annotations , 2009, Genome Biology.

[4]  Chikara Furusawa,et al.  Reconstruction and verification of a genome-scale metabolic model for Synechocystis sp. PCC6803 , 2011, Applied Microbiology and Biotechnology.

[5]  Jens Nielsen,et al.  Impact of systems biology on metabolic engineering of Saccharomyces cerevisiae. , 2008, FEMS yeast research.

[6]  Ronan M. T. Fleming,et al.  Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0 , 2007, Nature Protocols.

[7]  Minoru Kanehisa,et al.  KEGG as a reference resource for gene and protein annotation , 2015, Nucleic Acids Res..

[8]  Ying Zhang,et al.  HMDB: the Human Metabolome Database , 2007, Nucleic Acids Res..

[9]  Juho Rousu,et al.  Computing Atom Mappings for Biochemical Reactions without Subgraph Isomorphism , 2011, J. Comput. Biol..

[10]  Mikko Arvas,et al.  Correlation of gene expression and protein production rate - a system wide study , 2011, BMC Genomics.

[11]  Ram Krishnamurthy,et al.  YMDB: the Yeast Metabolome Database , 2011, Nucleic Acids Res..

[12]  Bernard Henrissat,et al.  Corrigendum: Genome sequencing and analysis of the biomass-degrading fungus Trichoderma reesei (syn. Hypocrea jecorina) , 2008, Nature Biotechnology.

[13]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[14]  Sudhakar Jonnalagadda,et al.  Reconstruction and analysis of a genome-scale metabolic model for Scheffersomyces stipitis , 2012, Microbial Cell Factories.

[15]  Markus Heinonen,et al.  Genome wide analysis of protein production load in Trichoderma reesei , 2016, Biotechnology for Biofuels.

[16]  Gary E. Harman,et al.  Trichoderma And Gliocladium. Volume 1 : Basic Biology, Taxonomy and Genetics , 2002 .

[17]  B. Palsson,et al.  A protocol for generating a high-quality genome-scale metabolic reconstruction , 2010 .

[18]  Jens Nielsen,et al.  A simple and reliable method for the determination of cellular RNA content , 1991 .

[19]  Christoph Steinbeck,et al.  The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013 , 2012, Nucleic Acids Res..

[20]  B. Palsson,et al.  Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. , 2003, Genome research.

[21]  Merja Penttilä,et al.  Dynamic flux balance analysis of the metabolism of Saccharomyces cerevisiae during the shift from fully respirative or respirofermentative metabolic states to anaerobiosis , 2012, The FEBS journal.

[22]  D. Fell,et al.  A Genome-Scale Metabolic Model of Arabidopsis and Some of Its Properties1[C][W] , 2009, Plant Physiology.

[23]  Adam M. Feist,et al.  A comprehensive genome-scale reconstruction of Escherichia coli metabolism—2011 , 2011, Molecular systems biology.

[24]  P. J. Phipps,et al.  Chapter III Chemical Analysis of Microbial Cells , 1971 .

[25]  J. Nielsen,et al.  Analysis of Aspergillus nidulans metabolism at the genome-scale , 2008, BMC Genomics.

[26]  Juho Rousu,et al.  Reconstructing Gapless Ancestral Metabolic Networks , 2011, BIOSTEC.

[27]  Monika Schmoll,et al.  Trichoderma: biology and applications. , 2013 .

[28]  Christoph Steinbeck,et al.  Updates in Rhea—a manually curated resource of biochemical reactions , 2014, Nucleic Acids Res..

[29]  Wanwipa Vongsangnak,et al.  Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae , 2008, BMC Genomics.

[30]  Martin J. Lercher,et al.  sybil – Efficient constraint-based modelling in R , 2013, BMC Systems Biology.

[31]  Bernard Henrissat,et al.  Genome sequencing and analysis of the biomass-degrading fungus Trichoderma reesei (syn. Hypocrea jecorina) , 2008, Nature Biotechnology.

[32]  Ronan M. T. Fleming,et al.  Consistent Estimation of Gibbs Energy Using Component Contributions , 2013, PLoS Comput. Biol..

[33]  Liisa Holm,et al.  BIOINFORMATICS ORIGINAL PAPER doi:10.1093/bioinformatics/btm358 Sequence analysis , 2022 .

[34]  M. Mavrovouniotis Group contributions for estimating standard gibbs energies of formation of biochemical compounds in aqueous solution , 1990, Biotechnology and bioengineering.

[35]  Huaiyu Mi,et al.  The InterPro protein families database: the classification resource after 15 years , 2014, Nucleic Acids Res..

[36]  Yaniv Lubling,et al.  An integrated open framework for thermodynamics of reactions that combines accuracy and coverage , 2012, Bioinform..

[37]  Zhao Xu,et al.  CVTree update: a newly designed phylogenetic study platform using composition vectors and whole genomes , 2009, Nucleic Acids Res..

[38]  Ronan M. T. Fleming,et al.  A community-driven global reconstruction of human metabolism , 2013, Nature Biotechnology.

[39]  Matthew D. Jankowski,et al.  Group contribution method for thermodynamic analysis of complex metabolic networks. , 2008, Biophysical journal.

[40]  Nevena Todorova,et al.  Dimensionality of Carbon Nanomaterials Determines the Binding and Dynamics of Amyloidogenic Peptides: Multiscale Theoretical Simulations , 2013, PLoS Comput. Biol..

[41]  J. Nielsen,et al.  Metabolic model integration of the bibliome, genome, metabolome and reactome of Aspergillus niger , 2008, Molecular systems biology.

[42]  Barbara Illman,et al.  Trichoderma and Gliocladium: Basic Biology, Taxonomy and Genetics. Volume 1. Christian P. Kubicek , Gary E. HarmanTrichoderma and Gliocladium: Enzymes, Biological Control and Commercial Applications. Volume 2. Gary E. Harman , Christian P. Kubicek , 2000 .

[43]  Intawat Nookaew,et al.  The RAVEN Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum , 2013, PLoS Comput. Biol..

[44]  Markus J. Herrgård,et al.  A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology , 2008, Nature Biotechnology.

[45]  Nicholas H. Putnam,et al.  The genome of the choanoflagellate Monosiga brevicollis and the origin of metazoans , 2008, Nature.

[46]  Merja Penttilä,et al.  The effect of specific growth rate on protein synthesis and secretion in the filamentous fungus Trichoderma reesei. , 2005, Microbiology.

[47]  Markus Krummenacker,et al.  The MetaCyc database of metabolic pathways and enzymes , 2017, Nucleic acids research.

[48]  Juho Rousu,et al.  Comparative Genome-Scale Reconstruction of Gapless Metabolic Networks for Present and Ancestral Species , 2014, PLoS Comput. Biol..

[49]  Yves Van de Peer,et al.  Genome sequence of the recombinant protein production host Pichia pastoris , 2009, Nature Biotechnology.

[50]  Rick L. Stevens,et al.  High-throughput generation, optimization and analysis of genome-scale metabolic models , 2010, Nature Biotechnology.

[51]  Bernhard O. Palsson,et al.  Connecting Extracellular Metabolomic Measurements to Intracellular Flux States in Yeast , 2022 .

[52]  L. Boddy,et al.  Cloning of an Aspergillus niger invertase gene by expression in Trichoderma reesei , 1993, Current Genetics.

[53]  Ronan M. T. Fleming,et al.  Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0 , 2007, Nature Protocols.

[54]  S. Henry,et al.  Revising the Representation of Fatty Acid, Glycerolipid, and Glycerophospholipid Metabolism in the Consensus Model of Yeast Metabolism. , 2013, Industrial biotechnology.

[55]  Intawat Nookaew,et al.  Genome-scale metabolic reconstructions of Pichia stipitis and Pichia pastoris and in silico evaluation of their potentials , 2012, BMC Systems Biology.

[56]  Sang Yup Lee,et al.  Model based engineering of Pichia pastoris central metabolism enhances recombinant protein production , 2014, Metabolic engineering.