10916nam 2200553 450 991082992180332120230630003411.03-527-82345-X3-527-82344-13-527-82346-8(CKB)4100000011953300(MiAaPQ)EBC6637758(Au-PeEL)EBL6637758(OCoLC)1257260667(EXLCZ)99410000001195330020220201d2021 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMetabolic engineering concepts and applications /edited by Sang Yup Lee, Jens Nielsen, Gregory StephanopoulosWeinheim, Germany :WILEY-VCH,[2021]©20211 online resource (962 pages)Advanced Biotechnology ;Volume 13b3-527-34662-7 Cover -- Title Page -- Copyright -- Contents -- Preface -- Part 1 Concepts -- Chapter 1 Metabolic Engineering Perspectives -- 1.1 History and Overview of Metabolic Engineering -- 1.2 Understanding Cellular Metabolism and Physiology -- 1.2.1 Computational Methods in Understanding Metabolism -- 1.2.2 Experimental Methods in Understanding Metabolism -- 1.3 General Approaches to Metabolic Engineering -- 1.3.1 Rational Metabolic Engineering -- 1.3.2 Combinatorial Metabolic Engineering -- 1.3.3 Systems Metabolic Engineering -- 1.4 Host Organism Selection -- 1.5 Substrate Considerations -- 1.6 Metabolic Engineering and Synthetic Biology -- 1.7 The Future of Metabolic Engineering -- References -- Chapter 2 Genome‐Scale Models: Two Decades of Progress and a 2020 Vision -- 2.1 Introduction -- 2.2 Flux Balance Analysis -- 2.2.1 Dynamic Mass Balances -- 2.2.2 Analogy to Deriving Enzymatic Rate Equations -- 2.2.3 Formulating Flux Balances at the Genome‐Scale -- 2.2.4 Constrained Optimization -- 2.2.5 Principles -- 2.2.6 Additional Constraints -- 2.2.7 Flux-Concentration Duality -- 2.2.8 Recap -- 2.3 Network Reconstruction -- 2.3.1 Assembling the Reactome -- 2.3.2 Basic Principles of Network Reconstruction -- 2.3.3 Curation -- 2.3.4 GEMs Have a Genomic Basis -- 2.3.5 Computational Queries -- 2.3.6 Scope Expansion -- 2.3.7 Knowledge Bases -- 2.3.8 Availability of GEMs -- 2.3.9 Recap -- 2.4 Brief History of the GEM for E. coli -- 2.4.1 Origin -- 2.4.2 Model Organism -- 2.4.3 Key Predictions -- 2.4.4 Design Algorithms -- 2.4.5 Scope Expansions -- 2.4.6 Recap -- 2.5 From Metabolism to the Proteome -- 2.5.1 ME Models -- 2.5.2 Capabilities of ME Models -- 2.5.2.1 Growth‐Coupled Metabolic Designs Can Be Reproduced in GEMs -- 2.5.2.2 ME Models Can Reflect Properties of the Metalloproteome -- 2.5.2.3 ME Models Can Compute the Biomass Objective Function.2.5.2.4 Computing Stresses -- 2.5.3 Recapitulation -- 2.6 Current Developments -- 2.6.1 Kinetics -- 2.6.2 Transcriptional Regulation -- 2.6.2.1 iModulons -- 2.6.2.2 Activities -- 2.6.3 Protein Structures -- 2.7 Broader Perspectives -- 2.7.1 Distal Causation -- 2.7.2 Contextualization of GEMs Within Workflows -- 2.8 What Does the Future Look Like for GEMs? -- Disclaimer -- Acknowledgments -- References -- Chapter 3 Quantitative Metabolic Flux Analysis Based on Isotope Labeling -- 3.1 Introduction -- 3.1.1 What Metabolic Flux Analysis Is About -- 3.1.2 The Variants of 13C‐MFA -- 3.2 A Toy Example Illustrates the Basic Principles -- 3.2.1 Fluxomics: More Than Just a Branch of Metabolomics -- 3.2.2 Isotope Labeling: The Key to Metabolic Fluxes -- 3.2.3 From the Data to the Intracellular Fluxes -- 3.2.4 INST‐13C‐MFA: Metabolic Stationary, but Isotopically Nonstationary -- 3.2.5 From Measurements to Flux Estimates: Parameter Fitting -- 3.2.6 Flux Estimates Have Confidence Bounds: Statistical Analysis -- 3.2.7 The Classical Approach at Metabolic and Isotopic Stationary State -- 3.2.8 An Additional Source of Information: Carbon Atom Transitions -- 3.2.9 Input Labeling Design: How Informative Can an Experiment Be Made? -- 3.2.10 The Isotopomers of a Single Metabolite can be a Rich Source of Information -- 3.2.11 Bidirectional Reaction Steps: More Than Just Nuisance Factors -- 3.2.12 Isotopomer Fractions Cannot Be Measured Comprehensively -- 3.3 Lessons Learned from the Example -- 3.3.1 Definition of 13C‐MFA Revisited -- 3.3.2 Statistical Evaluation and Optimal Experimental Design -- 3.4 How to Configure an Isotope Labeling Experiment -- 3.4.1 Modeling and Simulation of Isotope Labeling Experiments -- 3.4.2 Metabolic Network Specification -- 3.4.3 Atom Transition Network Specification -- 3.4.4 Input Labeling Composition -- 3.4.5 Measurement Specification.3.4.6 Flux Constraints -- 3.4.7 In Silico Experimental ILE Design -- 3.5 Putting Theory into Practice -- 3.5.1 A Recipe How to Start -- 3.5.2 Metabolic and Isotopic Stationarity -- 3.5.3 Measuring Extracellular Fluxes -- 3.5.4 Administering Labeled Substrate(s) -- 3.5.5 Metabolomics: Sampling, Sample Preparation, and Analytical Procedures -- 3.5.6 Adjusting Labeling Enrichments for Isotopic Steady State Approximation -- 3.5.7 Correcting Labeling Enrichments for Natural Isotope Abundance -- 3.5.8 Simulation of Labeling Data and Flux Estimation -- 3.5.9 Delicacies of INST‐13C‐MFA -- 3.6 Future Challenges of 13C‐MFA -- Acknowledgments -- Abbreviations -- References -- Chapter 4 Proteome Constraints in Genome‐Scale Models -- 4.1 Introduction -- 4.2 Cellular Constraints -- 4.3 Formulation of Proteome Constraints -- 4.3.1 Coarse‐Grained Integration of Proteome Constraints -- 4.3.2 Fine‐Tuned Integration of Proteome Constraints -- 4.4 Perspectives -- References -- Chapter 5 Kinetic Models of Metabolism -- 5.1 Introduction -- 5.2 Definition of Enzyme Kinetics -- 5.2.1 Michaelis-Menten Formula -- 5.3 Factors Affecting Intracellular Enzyme Kinetics -- 5.4 Kinetic Model: Definition and Scope -- 5.4.1 What Is a Kinetic Model? -- 5.4.2 Scope of Kinetic Models -- 5.4.3 How to Build a Functional Kinetic Model? -- 5.5 Main Mathematical Expressions in Description of Reaction Rates -- 5.5.1 Mechanistic Rate Expressions -- 5.6 Approximative Rate Expressions -- 5.7 Approaches to Assign Parameters in the Rate Expressions -- 5.7.1 Direct Measurements of Kinetic Parameters in Enzyme Assays -- 5.7.2 Querying Databases -- 5.7.3 Inferring from Measured Fluxes -- 5.7.4 Parameters Inference Using the Statistical Analysis -- 5.8 Applications -- 5.9 Perspectives -- References -- Chapter 6 Metabolic Control Analysis.6.1 The Metabolic Engineering Context of Metabolic Control Analysis -- 6.2 MCA Theory -- 6.2.1 Metabolic Steady State -- 6.2.2 Flux Control Coefficients -- 6.2.3 Examples of the Flux-Enzyme Relationship -- 6.2.4 Flux Summation Theorem -- 6.2.5 Concentration Control Coefficients -- 6.2.6 Linking Control Coefficients to Enzyme Properties -- 6.2.6.1 Enzyme Rate Equations and Elasticity Coefficients -- 6.2.6.2 Elasticities and Control Coefficients -- 6.2.6.3 Block Coefficients and Top‐Down Analysis -- 6.2.7 Feedback Inhibition -- 6.2.8 Large Alterations of Enzyme Activity -- 6.3 Implications of MCA for Metabolic Engineering Strategies -- 6.3.1 Abolishing Feedback Inhibition -- 6.3.2 Increasing Demand for Product -- 6.3.3 Inhibition of Competing Pathways -- 6.3.4 Designing Large Changes in Metabolic Flux -- 6.3.4.1 Yeast Tryptophan Synthesis -- 6.3.4.2 The Universal Method -- 6.3.4.3 Bacterial Production of Aromatic Amino Acids -- 6.3.4.4 Penicillin and Other Instances -- 6.3.5 Impacts on Yield from a Growing System -- 6.4 Conclusion -- Appendix 6.A: Feedback Inhibition Simulation -- References -- Chapter 7 Thermodynamics of Metabolic Pathways -- 7.1 Bioenergetics in Life and in Metabolic Engineering -- 7.2 Thermodynamics‐Based Flux Analysis Workflow -- 7.2.1 Thermodynamic Model Curation -- 7.2.1.1 Estimation of the Standard Free Energies of Formation -- 7.2.1.2 Compensating for Compartment‐Specific Ionic Strength and pH -- 7.2.1.3 Compensating the Free Energy of Formation for Isomer Distributions -- 7.2.1.4 Computing the Transformed Free Energies of Reaction -- 7.2.2 Mathematical Formulation -- 7.3 Thermodynamics‐Based Flux Analysis Applications -- 7.3.1 Constraining the Flux Space with Metabolomics Data -- 7.3.2 Characterizing the Feasible Concentration Space -- 7.4 Conclusion and Future Perspectives -- References -- Chapter 8 Pathway Design.Definition -- 8.1 De Novo Design of Metabolic Pathways -- 8.1.1 Manual Versus Computational Design -- 8.2 Pathway Design Workflow -- 8.2.1 Biochemical Search Space -- 8.2.1.1 Reaction Prediction -- 8.2.1.2 Retrobiosynthesis -- 8.2.1.3 Network Data Representation -- 8.2.2 Pathway Search -- 8.2.2.1 Stoichiometric Matrix‐Based Search -- 8.2.2.2 Graph‐Based Search -- 8.2.2.3 Pathway Ranking -- 8.2.3 Enzyme Assignment -- 8.2.3.1 Enzyme Prediction for Orphan and Novel Reactions -- 8.2.3.2 Choice of Protein Sequence -- 8.2.4 Pathway Feasibility -- 8.2.4.1 Chassis Metabolic Model -- 8.2.4.2 Stoichiometric Feasibility -- 8.2.4.3 Thermodynamic Feasibility -- 8.2.4.4 Kinetic Feasibility -- 8.2.4.5 Toxicity of Intermediates -- 8.3 Applications -- 8.3.1 Available Tools for Pathway Design -- 8.3.2 Successful Applications of Pathway Design Tools -- 8.3.3 Practical Example of Pathway Design -- 8.3.3.1 Creating a Biochemical Network Around BDO -- 8.3.3.2 Search for Biosynthetic Pathways -- 8.3.3.3 Finding Enzymes for Novel Reactions -- 8.3.3.4 Stoichiometric and Thermodynamic Pathway Evaluation -- 8.3.3.5 Overall Ranking of Pathways -- 8.4 Conclusions and Future Perspectives -- References -- Chapter 9 Metabolomics -- 9.1 Introduction -- 9.2 Fundamentals -- 9.2.1 Experimental Design -- 9.2.2 Targeted and Untargeted Metabolomics -- 9.2.3 Sequences and Standards -- 9.3 Analytical Techniques -- 9.3.1 Sample Preparation -- 9.3.2 Separation Techniques -- 9.3.2.1 Liquid Chromatography -- 9.3.2.2 Gas Chromatography -- 9.3.2.3 Alternative Separation Techniques -- 9.3.3 Mass Spectrometry -- 9.3.3.1 Ionization Techniques -- 9.3.3.2 Low‐Resolution MS -- 9.3.3.3 High‐Resolution MS -- 9.3.3.4 Acquisition Modes for Targeted MS -- 9.3.3.5 Acquisition Modes for Untargeted Metabolomics -- 9.4 Data Analysis -- 9.4.1 Data Processing in Untargeted Metabolomics.9.4.1.1 Preprocessing of Individual MS Runs.Advanced biotechnology ;Volume 13b.Microbial biotechnologyMicrobial genetic engineeringMicrobial biotechnology.Microbial genetic engineering.660.62Yi Sang-yŏp1964-Nielsen JensStephanopoulos GregoryMiAaPQMiAaPQMiAaPQBOOK9910829921803321Metabolic engineering2425022UNINA04393nam 22006735 450 991036659100332120251202150643.03-030-30318-710.1007/978-3-030-30318-1(CKB)4100000009374651(DE-He213)978-3-030-30318-1(MiAaPQ)EBC5904624(PPN)244349207(MiAaPQ)EBC29092644(EXLCZ)99410000000937465120190925d2020 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierStrategies for Circular Economy and Cross-sectoral Exchanges for Sustainable Building Products Preventing and Recycling Waste /by Marco Migliore, Cinzia Talamo, Giancarlo Paganin1st ed. 2020.Cham :Springer International Publishing :Imprint: Springer,2020.1 online resource (XI, 233 p.) Springer Tracts in Civil Engineering,2366-26033-030-30317-9 Includes bibliographical references.Waste and circular economy in the European policies -- Construction and demolition waste -- Reuse as a bridge between waste prevention and the circular economy -- Waste up-cycling in EU co-funded projects -- A virtual marketplace for the waste valorization -- Circular economy and sustainable procurement: the role of the attestation of conformity -- Crossing the boundaries: from agriculture and livestock to the building industry -- Information and Communication Technologies (ICTs) for advanced scraps/waste management -- Integrated Design and Living Labs to Fostering Smart (Waste) Networks.This book offers a valuable tool for understanding current efforts to promote the reuse and enhancement of pre-consumer waste in the development of new products for the construction sector, as well as the financial and regulatory tools being used to support this trend. It explores the vast and complex topic of the circular economy from the perspective of strategies for the reuse/recycling of waste, and develops a number of key premises: waste reuse/recycling must be considered using a logic of cross-sectoriality, recognizing the need to enhance the “dialogue” between different sectors; pre-consumer waste is particularly interesting for the recycling market because the construction sector can reduce its environmental impacts by enhancing its capacity to use secondary raw materials and by-products from other sectors; and lastly, the manufacturing sector is currently experimenting with promising forms of reducing/recycling pre-consumer waste and is at the same time providing by-products that can be used in other production chains. As such, the book offers a valuable asset for professionals who are interested in sustainability in construction, and in the study of construction products; however, it will be equally useful for local decision-makers tasked with implementing development policies and innovations in the industrial sector.Springer Tracts in Civil Engineering,2366-2603Construction industryManagementRefuse and refuse disposalSustainable architectureEnvironmentConstruction ManagementWaste Management/Waste TechnologySustainable Architecture/Green BuildingsEnvironmental SciencesConstruction industryManagement.Refuse and refuse disposal.Sustainable architecture.Environment.Construction Management.Waste Management/Waste Technology.Sustainable Architecture/Green Buildings.Environmental Sciences.624624Migliore Marcoauthttp://id.loc.gov/vocabulary/relators/aut418947Talamo Cinziaauthttp://id.loc.gov/vocabulary/relators/autPaganin Giancarloauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910366591003321Strategies for Circular Economy and Cross-sectoral Exchanges for Sustainable Building Products2104201UNINA