Metabolic engineering最新文献

{"title":"Genome-wide host-pathway interactions affecting cis-cis-muconic acid production in yeast","authors":"Paul Cachera ,&nbsp;Nikolaj Can Kurt ,&nbsp;Andreas Røpke ,&nbsp;Tomas Strucko ,&nbsp;Uffe H. Mortensen ,&nbsp;Michael K. Jensen","doi":"10.1016/j.ymben.2024.02.015","DOIUrl":"10.1016/j.ymben.2024.02.015","url":null,"abstract":"<div><p>The success of forward metabolic engineering depends on a thorough understanding of the behaviour of a heterologous metabolic pathway within its host. We have recently described CRI-SPA, a high-throughput gene editing method enabling the delivery of a metabolic pathway to all strains of the <em>Saccharomyces cerevisiae</em> knock-out library. CRI-SPA systematically quantifies the effect of each modified gene present in the library on product synthesis, providing a complete map of host:pathway interactions. In its first version, CRI-SPA relied on the colour of the product betaxanthins to quantify strains synthesis ability. However, only a few compounds produce a visible or fluorescent phenotype limiting the scope of our approach. Here, we adapt CRI-SPA to onboard a biosensor reporting the interactions between host genes and the synthesis of the colourless product <em>cis-cis</em>-muconic acid (CCM). We phenotype &gt;9,000 genotypes, including both gene knock-out and overexpression, by quantifying the fluorescence of yeast colonies growing in high-density agar arrays. We identify novel metabolic targets belonging to a broad range of cellular functions and confirm their positive impact on CCM biosynthesis. In particular, our data suggests a new interplay between CCM biosynthesis and cytosolic redox through their common interaction with the oxidative pentose phosphate pathway. Our genome-wide exploration of host:pathway interaction opens novel strategies for improved production of CCM in yeast cell factories.</p></div>","PeriodicalId":18483,"journal":{"name":"Metabolic engineering","volume":null,"pages":null},"PeriodicalIF":8.4,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1096717624000314/pdfft?md5=000dae8c0e47818ab85462dc691b57cd&pid=1-s2.0-S1096717624000314-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140012848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning predicts system-wide metabolic flux control in cyanobacteria","authors":"Amit Kugler,&nbsp;Karin Stensjö","doi":"10.1016/j.ymben.2024.02.013","DOIUrl":"10.1016/j.ymben.2024.02.013","url":null,"abstract":"<div><p>Metabolic fluxes and their control mechanisms are fundamental in cellular metabolism, offering insights for the study of biological systems and biotechnological applications. However, quantitative and predictive understanding of controlling biochemical reactions in microbial cell factories, especially at the system level, is limited. In this work, we present ARCTICA, a computational framework that integrates constraint-based modelling with machine learning tools to address this challenge. Using the model cyanobacterium <em>Synechocystis</em> sp. PCC 6803 as chassis, we demonstrate that ARCTICA effectively simulates global-scale metabolic flux control. Key findings are that (i) the photosynthetic bioproduction is mainly governed by enzymes within the Calvin–Benson–Bassham (CBB) cycle, rather than by those involve in the biosynthesis of the end-product, (ii) the catalytic capacity of the CBB cycle limits the photosynthetic activity and downstream pathways and (iii) ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) is a major, but not the most, limiting step within the CBB cycle. Predicted metabolic reactions qualitatively align with prior experimental observations, validating our modelling approach. ARCTICA serves as a valuable pipeline for understanding cellular physiology and predicting rate-limiting steps in genome-scale metabolic networks, and thus provides guidance for bioengineering of cyanobacteria.</p></div>","PeriodicalId":18483,"journal":{"name":"Metabolic engineering","volume":null,"pages":null},"PeriodicalIF":8.4,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1096717624000296/pdfft?md5=4548b4178e927ad79f1cb9e05adfe171&pid=1-s2.0-S1096717624000296-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139916924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combinatorial biosynthesis in yeast leads to over 200 diterpenoids","authors":"Maximilian Frey ,&nbsp;Ulschan Bathe ,&nbsp;Luca Meink ,&nbsp;Gerd U. Balcke ,&nbsp;Jürgen Schmidt ,&nbsp;Andrej Frolov ,&nbsp;Alena Soboleva ,&nbsp;Ahmed Hassanin ,&nbsp;Mehdi D. Davari ,&nbsp;Oliver Frank ,&nbsp;Verena Schlagbauer ,&nbsp;Corinna Dawid ,&nbsp;Alain Tissier","doi":"10.1016/j.ymben.2024.02.006","DOIUrl":"10.1016/j.ymben.2024.02.006","url":null,"abstract":"<div><p>Diterpenoids form a diverse group of natural products, many of which are or could become pharmaceuticals or industrial chemicals. The modular character of diterpene biosynthesis and the promiscuity of the enzymes involved make combinatorial biosynthesis a promising approach to generate libraries of diverse diterpenoids. Here, we report on the combinatorial assembly in yeast of ten diterpene synthases producing (+)-copalyl diphosphate-derived backbones and four cytochrome P450 oxygenases (CYPs) in diverse combinations. This resulted in the production of over 200 diterpenoids. Based on literature and chemical database searches, 162 of these compounds can be considered new-to-Nature. The CYPs accepted most substrates they were given but remained regioselective with few exceptions. Our results provide the basis for the systematic exploration of the diterpenoid chemical space in yeast using sequence databases.</p></div>","PeriodicalId":18483,"journal":{"name":"Metabolic engineering","volume":null,"pages":null},"PeriodicalIF":8.4,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1096717624000223/pdfft?md5=3b15c057941fe4f76834f1cf3baef433&pid=1-s2.0-S1096717624000223-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139916918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cyclo-diphenylalanine production in Aspergillus nidulans through stepwise metabolic engineering","authors":"Xiaolin Liu ,&nbsp;Kang Li ,&nbsp;Jing Yu ,&nbsp;Chuanteng Ma ,&nbsp;Qian Che ,&nbsp;Tianjiao Zhu ,&nbsp;Dehai Li ,&nbsp;Blaine A. Pfeifer ,&nbsp;Guojian Zhang","doi":"10.1016/j.ymben.2024.02.009","DOIUrl":"10.1016/j.ymben.2024.02.009","url":null,"abstract":"<div><p>Cyclo-diphenylalanine (cFF) is a symmetrical aromatic diketopiperazine (DKP) found wide-spread in microbes, plants, and resulting food products. As different bioactivities continue being discovered and relevant food and pharmaceutical applications gradually emerge for cFF, there is a growing need for establishing convenient and efficient methods to access this type of compound. Here, we present a robust cFF production system which entailed stepwise engineering of the filamentous fungal strain <em>Aspergillus nidulans</em> A1145 as a heterologous expression host. We first established a preliminary cFF producing strain by introducing the heterologous nonribosomal peptide synthetase (NRPS) gene <em>penP1</em> to <em>A. nidulans</em> A1145. Key metabolic pathways involving shikimate and aromatic amino acid biosynthetic support were then engineered through a combination of gene deletions of competitive pathway steps, over-expressing feedback-insensitive enzymes in phenylalanine biosynthesis, and introducing a phosphoketolase-based pathway, which diverted glycolytic flux toward the formation of erythrose 4-phosphate (E4P). Through the stepwise engineering of <em>A. nidulans</em> A1145 outlined above, involving both heterologous pathway addition and native pathway metabolic engineering, we were able to produce cFF with titers reaching 611 mg/L in shake flask culture and 2.5 g/L in bench-scale fed-batch bioreactor culture. Our study establishes a production platform for cFF biosynthesis and successfully demonstrates engineering of phenylalanine derived diketopiperazines in a filamentous fungal host.</p></div>","PeriodicalId":18483,"journal":{"name":"Metabolic engineering","volume":null,"pages":null},"PeriodicalIF":8.4,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139931773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"COSMIC-dFBA: A novel multi-scale hybrid framework for bioprocess modeling","authors":"Saratram Gopalakrishnan ,&nbsp;William Johnson ,&nbsp;Miguel A. Valderrama-Gomez ,&nbsp;Elcin Icten ,&nbsp;Jasmine Tat ,&nbsp;Michael Ingram ,&nbsp;Coral Fung Shek ,&nbsp;Pik K. Chan ,&nbsp;Fabrice Schlegel ,&nbsp;Pablo Rolandi ,&nbsp;Cleo Kontoravdi ,&nbsp;Nathan E. Lewis","doi":"10.1016/j.ymben.2024.02.012","DOIUrl":"10.1016/j.ymben.2024.02.012","url":null,"abstract":"<div><p>Metabolism governs cell performance in biomanufacturing, as it fuels growth and productivity. However, even in well-controlled culture systems, metabolism is dynamic, with shifting objectives and resources, thus limiting the predictive capability of mechanistic models for process design and optimization. Here, we present Cellular Objectives and State Modulation In bioreaCtors (COSMIC)-dFBA, a hybrid multi-scale modeling paradigm that accurately predicts cell density, antibody titer, and bioreactor metabolite concentration profiles. Using machine-learning, COSMIC-dFBA decomposes the instantaneous metabolite uptake and secretion rates in a bioreactor into weighted contributions from each cell state (growth or antibody-producing state) and integrates these with a genome-scale metabolic model. A major strength of COSMIC-dFBA is that it can be parameterized with only metabolite concentrations from spent media, although constraining the metabolic model with other omics data can further improve its capabilities. Using COSMIC-dFBA, we can predict the final cell density and antibody titer to within 10% of the measured data, and compared to a standard dFBA model, we found the framework showed a 90% and 72% improvement in cell density and antibody titer prediction, respectively. Thus, we demonstrate our hybrid modeling framework effectively captures cellular metabolism and expands the applicability of dFBA to model the dynamic conditions in a bioreactor.</p></div>","PeriodicalId":18483,"journal":{"name":"Metabolic engineering","volume":null,"pages":null},"PeriodicalIF":8.4,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139916960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient production of protocatechuic acid using systems engineering of Escherichia coli","authors":"Ming Wang ,&nbsp;Haomiao Wang ,&nbsp;Cong Gao ,&nbsp;Wanqing Wei ,&nbsp;Jia Liu ,&nbsp;Xiulai Chen ,&nbsp;Guipeng Hu ,&nbsp;Wei Song ,&nbsp;Jing Wu ,&nbsp;Fan Zhang ,&nbsp;Liming Liu","doi":"10.1016/j.ymben.2024.02.003","DOIUrl":"10.1016/j.ymben.2024.02.003","url":null,"abstract":"<div><p>Protocatechuic acid (3, 4-dihydroxybenzoic acid, PCA) is widely used in the pharmaceuticals, health food, and cosmetics industries owing to its diverse biological activities. However, the inhibition of 3-dehydroshikimate dehydratase (AroZ) by PCA and its toxicity to cells limit the efficient production of PCA in <em>Escherichia coli</em>. In this study, a high-level strain of 3-dehydroshikimate, <em>E. coli</em> DHS01, was developed by blocking the carbon flow from the shikimate-overproducing strain <em>E. coli</em> SA09. Additionally, the PCA biosynthetic pathway was established in DHS01 by introducing the high-activity <em>Ap</em>AroZ. Subsequently, the protein structure and catalytic mechanism of 3-dehydroshikimate dehydratase from <em>Acinetobacter pittii</em> PHEA-2 (<em>Ap</em>AroZ) were clarified. The variant <em>Ap</em>AroZ^R363A, achieved by modulating the conformational dynamics of <em>Ap</em>AroZ, effectively relieved product inhibition. Additionally, the tolerance of the strain <em>E. coli</em> PCA04 to PCA was enhanced by adaptive laboratory evolution, and a biosensor-assisted high-throughput screening method was designed and implemented to expedite the identification of high-performance PCA-producing strains. Finally, in a 5 L bioreactor, the final strain PCA05 achieved the highest PCA titer of 46.65 g/L, a yield of 0.23 g/g, and a productivity of 1.46 g/L/h for PCA synthesis from glucose using normal fed-batch fermentation. The strategies described herein serve as valuable guidelines for the production of other high-value and toxic products.</p></div>","PeriodicalId":18483,"journal":{"name":"Metabolic engineering","volume":null,"pages":null},"PeriodicalIF":8.4,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139900210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome-scale and pathway engineering for the sustainable aviation fuel precursor isoprenol production in Pseudomonas putida","authors":"Deepanwita Banerjee ,&nbsp;Ian S. Yunus ,&nbsp;Xi Wang ,&nbsp;Jinho Kim ,&nbsp;Aparajitha Srinivasan ,&nbsp;Russel Menchavez ,&nbsp;Yan Chen ,&nbsp;Jennifer W. Gin ,&nbsp;Christopher J. Petzold ,&nbsp;Hector Garcia Martin ,&nbsp;Jon K. Magnuson ,&nbsp;Paul D. Adams ,&nbsp;Blake A. Simmons ,&nbsp;Aindrila Mukhopadhyay ,&nbsp;Joonhoon Kim ,&nbsp;Taek Soon Lee","doi":"10.1016/j.ymben.2024.02.004","DOIUrl":"10.1016/j.ymben.2024.02.004","url":null,"abstract":"<div><p>Sustainable aviation fuel (SAF) will significantly impact global warming in the aviation sector, and important SAF targets are emerging. Isoprenol is a precursor for a promising SAF compound DMCO (1,4-dimethylcyclooctane) and has been produced in several engineered microorganisms. Recently, <em>Pseudomonas putida</em> has gained interest as a future host for isoprenol bioproduction as it can utilize carbon sources from inexpensive plant biomass. Here, we engineer metabolically versatile host <em>P. putida</em> for isoprenol production. We employ two computational modeling approaches (Bilevel optimization and Constrained Minimal Cut Sets) to predict gene knockout targets and optimize the “IPP-bypass” pathway in <em>P. putida</em> to maximize isoprenol production. Altogether, the highest isoprenol production titer from <em>P. putida</em> was achieved at 3.5 g/L under fed-batch conditions. This combination of computational modeling and strain engineering on <em>P. putida</em> for an advanced biofuels production has vital significance in enabling a bioproduction process that can use renewable carbon streams.</p></div>","PeriodicalId":18483,"journal":{"name":"Metabolic engineering","volume":null,"pages":null},"PeriodicalIF":8.4,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S109671762400020X/pdfft?md5=ccf3c9a3453e592888a4831af6d1fee9&pid=1-s2.0-S109671762400020X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139900211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction and integration of metabolite-protein interactions with genome-scale metabolic models","authors":"Mahdis Habibpour ,&nbsp;Zahra Razaghi-Moghadam ,&nbsp;Zoran Nikoloski","doi":"10.1016/j.ymben.2024.02.008","DOIUrl":"10.1016/j.ymben.2024.02.008","url":null,"abstract":"<div><p>Metabolites, as small molecules, can act not only as substrates to enzymes, but also as effectors of activity of proteins with different functions, thereby affecting various cellular processes. While several experimental techniques have started to catalogue the metabolite-protein interactions (MPIs) present in different cellular contexts, characterizing the functional relevance of MPIs remains a challenging problem. Computational approaches from the constrained-based modeling framework allow for predicting MPIs and integrating their effects in the <em>in silico</em> analysis of metabolic and physiological phenotypes, like cell growth. Here, we provide a classification of all existing constraint-based approaches that predict and integrate MPIs using genome-scale metabolic networks as input. In addition, we benchmark the performance of the approaches to predict MPIs in a comparative study using different features extracted from the model structure and predicted metabolic phenotypes with the state-of-the-art metabolic networks of <em>Escherichia coli</em> and <em>Saccharomyces cerevisiae.</em> Lastly, we provide an outlook for future, feasible directions to expand the consideration of MPIs in constraint-based modeling approaches with wide biotechnological applications.</p></div>","PeriodicalId":18483,"journal":{"name":"Metabolic engineering","volume":null,"pages":null},"PeriodicalIF":8.4,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1096717624000247/pdfft?md5=8eb3485e91061c2df98c8ad0db4171c8&pid=1-s2.0-S1096717624000247-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139881274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Engineering Saccharomyces cerevisiae for fast vitamin-independent aerobic growth","authors":"Anja K. Ehrmann ,&nbsp;Anna K. Wronska ,&nbsp;Thomas Perli ,&nbsp;Erik A.F. de Hulster ,&nbsp;Marijke A.H. Luttik ,&nbsp;Marcel van den Broek ,&nbsp;Clara Carqueija Cardoso ,&nbsp;Jack T. Pronk ,&nbsp;Jean-Marc Daran","doi":"10.1016/j.ymben.2024.01.010","DOIUrl":"10.1016/j.ymben.2024.01.010","url":null,"abstract":"<div><p>Chemically defined media for cultivation of <em>Saccharomyces cerevisiae</em> strains are commonly supplemented with a mixture of multiple Class-B vitamins, whose omission leads to strongly reduced growth rates. Fast growth without vitamin supplementation is interesting for industrial applications, as it reduces costs and complexity of medium preparation and may decrease susceptibility to contamination by auxotrophic microbes. In this study, suboptimal growth rates of <em>S. cerevisiae</em> CEN.PK113-7D in the absence of pantothenic acid, <em>para</em>-aminobenzoic acid (<em>p</em>ABA), pyridoxine, inositol and/or biotin were corrected by single or combined overexpression of <em>ScFMS1</em>, <em>ScABZ1</em>/<em>ScABZ2</em>, <em>ScSNZ1</em>/<em>ScSNO1</em>, S<em>cINO1</em> and <em>Cyberlindnera fabianii BIO1</em>, respectively. Several strategies were explored to improve growth of <em>S. cerevisiae</em> CEN.PK113-7D in thiamine-free medium. Overexpression of <em>ScTHI4</em> and/or <em>ScTHI5</em> enabled thiamine-independent growth at 83% of the maximum specific growth rate of the reference strain in vitamin-supplemented medium. Combined overexpression of seven native <em>S. cerevisiae</em> genes and <em>CfBIO1</em> enabled a maximum specific growth rate of 0.33 ± 0.01 h⁻¹ in vitamin-free synthetic medium. This growth rate was only 17 % lower than that of a congenic reference strain in vitamin-supplemented medium. Physiological parameters of the engineered vitamin-independent strain in aerobic glucose-limited chemostat cultures (dilution rate 0.10 h⁻¹) grown on vitamin-free synthetic medium were similar to those of similar cultures of the parental strain grown on vitamin-supplemented medium. Transcriptome analysis revealed only few differences in gene expression between these cultures, which primarily involved genes with roles in Class-B vitamin metabolism. These results pave the way for development of fast-growing vitamin-independent industrial strains of <em>S. cerevisiae</em>.</p></div>","PeriodicalId":18483,"journal":{"name":"Metabolic engineering","volume":null,"pages":null},"PeriodicalIF":8.4,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1096717624000168/pdfft?md5=93ba87ea644e54da54ede368e11849c1&pid=1-s2.0-S1096717624000168-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139746948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"KETCHUP: Parameterizing of large-scale kinetic models using multiple datasets with different reference states","authors":"Mengqi Hu ,&nbsp;Patrick F. Suthers ,&nbsp;Costas D. Maranas","doi":"10.1016/j.ymben.2024.02.002","DOIUrl":"10.1016/j.ymben.2024.02.002","url":null,"abstract":"<div><p>Large-scale kinetic models provide the computational means to dynamically link metabolic reaction fluxes to metabolite concentrations and enzyme levels while also conforming to substrate level regulation. However, the development of broadly applicable frameworks for efficiently and robustly parameterizing models remains a challenge. Challenges arise due to both the heterogeneity, paucity, and difficulty in obtaining flux and/or concentration data but also due to the computational difficulties of the underlying parameter identification problem. Both the computational demands for parameterization, degeneracy of obtained parameter solutions and interpretability of results has so far limited widespread adoption of large-scale kinetic models despite their potential. Herein, we introduce the Kinetic Estimation Tool Capturing Heterogeneous Datasets Using Pyomo (KETCHUP), a flexible parameter estimation tool that leverages a primal-dual interior-point algorithm to solve a nonlinear programming (NLP) problem that identifies a set of parameters capable of recapitulating the (non)steady-state fluxes and concentrations in wild-type and perturbed metabolic networks. KETCHUP is benchmarked against previously parameterized large-scale kinetic models demonstrating an at least an order of magnitude faster convergence than the tool K-FIT while at the same time attaining better data fits. This versatile toolbox accepts different kinetic descriptions, metabolic fluxes, enzyme levels and metabolite concentrations, under either steady-state or instationary conditions to enable robust kinetic model construction and parameterization. KETCHUP supports the SBML format and can be accessed at <span>https://github.com/maranasgroup/KETCHUP</span><svg><path></path></svg>.</p></div>","PeriodicalId":18483,"journal":{"name":"Metabolic engineering","volume":null,"pages":null},"PeriodicalIF":8.4,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139712493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}