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  • 1
    Online Resource
    Online Resource
    Newark :John Wiley & Sons, Incorporated,
    Keywords: Recombinant proteins. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (439 pages)
    Edition: 1st ed.
    ISBN: 9783527811380
    Series Statement: Advanced Biotechnology Series
    Language: English
    Note: Cover -- Title Page -- Copyright -- Contents -- About the Series Editors -- Chapter 1 Platform Technology for Therapeutic Protein Production -- 1.1 Introduction -- 1.2 Overall Trend Analysis -- 1.2.1 Mammalian Cell Lines -- 1.2.2 Brief Introduction of Advances and Techniques -- 1.3 General Guidelines for Recombinant Cell Line Development -- 1.3.1 Host Selection -- 1.3.2 Expression Vector -- 1.3.3 Transfection/Selection -- 1.3.4 Clone Selection -- 1.3.4.1 Primary Parameters During Clone Selection -- 1.3.4.2 Clone Screening Technologies -- 1.4 Process Development -- 1.4.1 Media Development -- 1.4.2 Culture Environment -- 1.4.3 Culture Mode (Operation) -- 1.4.4 Scale‐up and Single‐Use Bioreactor -- 1.4.5 Quality Analysis -- 1.5 Downstream Process Development -- 1.5.1 Purification -- 1.5.2 Quality by Design (QbD) -- 1.6 Trends in Platform Technology Development -- 1.6.1 Rational Strategies for Cell Line and Process Development -- 1.6.2 Hybrid Culture Mode and Continuous System -- 1.6.3 Recombinant Human Cell Line Development for Therapeutic Protein Production -- 1.7 Conclusion -- Acknowledgment -- Conflict of Interest -- References -- Chapter 2 Cell Line Development for Therapeutic Protein Production -- 2.1 Introduction -- 2.2 Mammalian Host Cell Lines for Therapeutic Protein Production -- 2.2.1 CHO Cell Lines -- 2.2.2 Human Cell Lines -- 2.2.3 Other Mammalian Cell Lines -- 2.3 Development of Recombinant CHO Cell Lines -- 2.3.1 Expression Systems for CHO Cells -- 2.3.2 Cell Line Development Process Using CHO Cells Based on Random Integration -- 2.3.2.1 Vector Construction -- 2.3.2.2 Transfection and Selection -- 2.3.2.3 Gene Amplification -- 2.3.2.4 Clone Selection -- 2.3.3 Cell Line Development Process Using CHO Cells Based On Site‐Specific Integration -- 2.4 Development of Recombinant Human Cell Lines -- 2.4.1 Necessity for Human Cell Lines. , 2.4.2 Stable Cell Line Development Process Using Human Cell Lines -- 2.5 Important Consideration for Cell Line Development -- 2.5.1 Clonality -- 2.5.2 Stability -- 2.5.3 Quality of Therapeutic Proteins -- 2.6 Conclusion -- References -- Chapter 3 Transient Gene Expression‐Based Protein Production in Recombinant Mammalian Cells -- 3.1 Introduction -- 3.2 Gene Delivery: Transient Transfection Methods -- 3.2.1 Calcium Phosphate‐Based Transient Transfection -- 3.2.2 Electroporation -- 3.2.3 Polyethylenimine‐Based Transient Transfection -- 3.2.4 Liposome‐Based Transient Transfection -- 3.3 Expression Vectors -- 3.3.1 Expression Vector Composition and Preparation -- 3.3.2 Episomal Replication -- 3.3.3 Coexpression Strategies -- 3.4 Mammalian Cell Lines -- 3.4.1 HEK293 Cell‐Based TGE Platforms -- 3.4.2 CHO Cell‐Based TGE Platforms -- 3.4.3 TGE Platforms Using Other Cell Lines -- 3.5 Cell Culture Strategies -- 3.5.1 Culture Media for TGE -- 3.5.2 Optimization of Cell Culture Processes for TGE -- 3.5.3 qp‐Enhancing Factors in TGE‐Based Culture Processes -- 3.5.4 Culture Longevity‐Enhancing Factors in TGE‐Based Culture Processes -- 3.6 Large‐Scale TGE‐Based Protein Production -- 3.7 Concluding Remarks -- References -- Chapter 4 Enhancing Product and Bioprocess Attributes Using Genome‐Scale Models of CHO Metabolism -- 4.1 Introduction -- 4.1.1 Cell Line Optimization -- 4.1.2 CHO Genome -- 4.1.2.1 Development of Genomic Resources of CHO -- 4.1.2.2 Development of Transcriptomics and Proteomics Resources of CHO -- 4.2 Genome‐Scale Metabolic Model -- 4.2.1 What Is a Genome‐Scale Metabolic Model -- 4.2.2 Reconstruction of GEMs -- 4.2.2.1 Knowledge‐Based Construction -- 4.2.2.2 Draft Reconstruction -- 4.2.2.3 Curation of the Reconstruction -- 4.2.2.4 Conversion to a Computational Format -- 4.2.2.5 Model Validation and Evaluation -- 4.3 GEM Application. , 4.3.1 Common Usage and Prediction Capacities of Genome‐Scale Models -- 4.3.2 GEMs as a Platform for Omics Data Integration, Linking Genotype to Phenotype -- 4.3.3 Predicting Nutrient Consumption and Controlling Phenotype -- 4.3.4 Enhancing Protein Production and Bioprocesses -- 4.3.5 Case Studies -- 4.4 Conclusion -- Acknowledgments -- References -- Chapter 5 Genome Variation, the Epigenome and Cellular Phenotypes -- 5.1 Phenotypic Instability in the Context of Mammalian Production Cell Lines -- 5.2 Genomic Instability -- 5.3 Epigenetics -- 5.3.1 DNA Methylation -- 5.3.2 Histone Modifications -- 5.3.3 Downstream Effectors -- 5.3.4 Noncoding RNAs -- 5.4 Control of CHO Cell Phenotype by the Epigenome -- 5.5 Manipulating the Epigenome -- 5.5.1 Global Epigenetic Modification -- 5.5.1.1 Manipulating Global DNA Methylation -- 5.5.1.2 Manipulating Global Histone Acetylation -- 5.5.2 Targeted Epigenetic Modification -- 5.5.2.1 Targeted Histone Modification -- 5.5.2.2 Targeted DNA Methylation -- 5.6 Conclusion and Outlook -- References -- Chapter 6 Adaption of Generic Metabolic Models to Specific Cell Lines for Improved Modeling of Biopharmaceutical Production and Prediction of Processes -- 6.1 Introduction -- 6.1.1 Constraint‐Based Models -- 6.1.2 Limitations of Flux Balance Analysis -- 6.1.2.1 Thermodynamically Infeasible Cycles -- 6.1.2.2 Genetic Regulation -- 6.1.2.3 Limitation of Intracellular Space -- 6.1.2.4 Multiple States in the Solution -- 6.1.2.5 Biological Objective Function -- 6.1.2.6 Kinetics and Metabolite Concentrations -- 6.2 Main Source of Optimization Issues with Large Genome‐Scale Models: Thermodynamically Infeasible Cycles -- 6.2.1 Definition of Thermodynamically Infeasible Fluxes -- 6.2.2 Loops Involving External Exchange Reactions -- 6.2.2.1 Reversible Passive Transporters from Major Facilitator Superfamily (MFS). , 6.2.2.2 Reversible Passive Antiporters from Amino Acid‐Polyamine‐organoCation (APC) Superfamily -- 6.2.2.3 Na+‐linked Transporters -- 6.2.2.4 Transport via Proton Symport -- 6.2.3 Tools to Identify Thermodynamically Infeasible Cycles -- 6.2.3.1 Visualizing Fluxes on a Network Map -- 6.2.3.2 Algorithms Developed -- 6.2.4 Methods Available to Remove Thermodynamically Infeasible Cycles -- 6.2.4.1 Manual Curation -- 6.2.4.2 Software and Algorithms Developed for the Removal of Thermodynamically Infeasible Loops from Flux Distributions -- 6.3 Consideration of Additional Biological Cellular Constraints -- 6.3.1 Genetic Regulation -- 6.3.1.1 Advantages of Considering Gene Regulation in Genome‐Scale Modeling -- 6.3.1.2 Methods Developed to Take into Account a Feedback of FBA on the Regulatory Network -- 6.3.2 Context Specificity -- 6.3.2.1 What Are Context‐Specific Models (CSMs)? -- 6.3.2.2 Methods and Algorithms Developed to Reconstruct Context‐Specific Models (CSMs) -- 6.3.2.3 Performance of CSMs -- 6.3.2.4 Cautions About CSMs -- 6.3.3 Molecular Crowding -- 6.3.3.1 Consequences on the Predictions -- 6.3.3.2 Methods Developed to Account for a Total Enzymatic Capacity into the FBA Framework -- 6.4 Conclusion -- References -- Chapter 7 Toward Integrated Multi‐omics Analysis for Improving CHO Cell Bioprocessing -- 7.1 Introduction -- 7.2 High‐Throughput Omics Technologies -- 7.2.1 Sequencing‐Based Omics Technologies -- 7.2.1.1 Historical Developments of Nucleotide Sequencing Techniques -- 7.2.1.2 Genome Sequencing of CHO Cells -- 7.2.1.3 Transcriptomics of CHO Cells -- 7.2.1.4 Epigenomics of CHO Cells -- 7.2.2 Mass Spectrometry‐Based Omics Technologies -- 7.2.2.1 Mass Spectrometry Techniques -- 7.2.2.2 Proteomics of CHO Cells -- 7.2.2.3 Metabolomics/Lipidomics of CHO Cells -- 7.2.2.4 Glycomics of CHO Cells -- 7.3 Current CHO Multi‐omics Applications. , 7.3.1 Bioprocess Optimization -- 7.3.2 Cell Line Characterization -- 7.3.3 Engineering Target Identification -- 7.4 Future Prospects -- References -- Chapter 8 CRISPR Toolbox for Mammalian Cell Engineering -- 8.1 Introduction -- 8.2 Mechanism of CRISPR/Cas9 Genome Editing -- 8.3 Variants of CRISPR‐RNA‐guided Endonucleases -- 8.3.1 Diversity of CRISPR/Cas Systems -- 8.3.2 Engineered Cas9 Variants -- 8.4 Experimental Design for CRISPR‐mediated Genome Editing -- 8.4.1 Target Site Selection and Design of gRNAs -- 8.4.2 Delivery of CRISPR/Cas9 Components -- 8.5 Development of CRISPR/Cas9 Tools -- 8.5.1 CRISPR/Cas9‐mediated Gene Editing -- 8.5.1.1 Gene Knockout -- 8.5.1.2 Site‐Specific Gene Integration -- 8.5.2 CRISPR/Cas9‐mediated Genome Modification -- 8.5.2.1 Transcriptional Regulation -- 8.5.2.2 Epigenetic Modification -- 8.5.3 RNA Targeting -- 8.6 Genome‐Scale CRISPR Screening -- 8.7 Applications of CRISPR/Cas9 for CHO Cell Engineering -- 8.8 Conclusion -- Acknowledgment -- References -- Chapter 9 CHO Cell Engineering for Improved Process Performance and Product Quality -- 9.1 CHO Cell Engineering -- 9.2 Methods in Cell Line Engineering -- 9.2.1 Overexpression of Engineering Genes -- 9.2.2 Gene Knockout -- 9.2.3 Noncoding RNA‐mediated Gene Silencing -- 9.3 Applications of Cell Line Engineering Approaches in CHO Cells -- 9.3.1 Enhancing Recombinant Protein Production -- 9.3.2 Repression of Cell Death and Acceleration of Growth -- 9.3.3 Modulation of Posttranslational Modifications to Improve Protein Quality -- 9.4 Conclusions -- References -- Chapter 10 Metabolite Profiling of Mammalian Cells -- 10.1 Value of Metabolic Data for the Enhancement of Recombinant Protein Production -- 10.2 Technologies Used in the Generation of Metabolic Data Sets -- 10.2.1 Targeted and Untargeted Metabolic Analysis. , 10.2.2 Analytical Technologies Used in the Generation of Metabolite Profiles.
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  • 2
    Online Resource
    Online Resource
    Newark :John Wiley & Sons, Incorporated,
    Keywords: Cyanobacteria-Biotechnology. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (563 pages)
    Edition: 1st ed.
    ISBN: 9783527824922
    Series Statement: Advanced Biotechnology Series
    DDC: 579.39
    Language: English
    Note: Cover -- Title Page -- Copyright -- Contents -- Foreword: Cyanobacteria Biotechnology -- Acknowledgments -- Part I Core Cyanobacteria Processes -- Chapter 1 Inorganic Carbon Assimilation in Cyanobacteria: Mechanisms, Regulation, and Engineering -- 1.1 Introduction - The Need for a Carbon‐Concentrating Mechanism -- 1.2 The Carbon‐Concentrating Mechanism (CCM) Among Cyanobacteria -- 1.2.1 Ci Uptake Proteins/Mechanisms -- 1.2.2 Carboxysome and RubisCO -- 1.3 Regulation of Ci Assimilation -- 1.3.1 Regulation of the CCM -- 1.3.2 Further Regulation of Carbon Assimilation -- 1.3.3 Metabolic Changes and Regulation During Ci Acclimation -- 1.3.4 Redox Regulation of Ci Assimilation -- 1.4 Engineering the Cyanobacterial CCM -- 1.5 Photorespiration -- 1.5.1 Cyanobacterial Photorespiration -- 1.5.2 Attempts to Engineer Photorespiration -- 1.6 Concluding Remarks -- Acknowledgments -- References -- Chapter 2 Electron Transport in Cyanobacteria and Its Potential in Bioproduction -- 2.1 Introduction -- 2.2 Electron Transport in a Bioenergetic Membrane -- 2.2.1 Linear Electron Transport -- 2.2.2 Cyclic Electron Transport -- 2.2.3 ATP Production from Linear and Cyclic Electron Transport -- 2.3 Respiratory Electron Transport -- 2.4 Role of Electron Sinks in Photoprotection -- 2.4.1 Terminal Oxidases -- 2.4.2 Hydrogenase and Flavodiiron Complexes -- 2.4.3 Carbon Fixation and Photorespiration -- 2.4.4 Extracellular Electron Export -- 2.5 Regulating Electron Flux into Different Pathways -- 2.5.1 Electron Flux Through the Plastoquinone Pool -- 2.5.2 Electron Flux Through Fdx -- 2.6 Spatial Organization of Electron Transport Complexes -- 2.7 Manipulating Electron Transport for Synthetic Biology Applications -- 2.7.1 Improving Growth of Cyanobacteria -- 2.7.2 Production of Electrical Power in BPVs -- 2.7.3 Hydrogen Production -- 2.7.4 Production of Industrial Compounds. , 2.8 Future Challenges in Cyanobacterial Electron Transport -- References -- Chapter 3 Optimizing the Spectral Fit Between Cyanobacteria and Solar Radiation in the Light of Sustainability Applications -- 3.1 Introduction -- 3.2 Molecular Basis and Efficiency of Oxygenic Photosynthesis -- 3.3 Fit Between the Spectrum of Solar Radiation and the Action Spectrum of Photosynthesis -- 3.4 Expansion of the PAR Region of Oxygenic Photosynthesis -- 3.5 Modulation and Optimization of the Transparency of Photobioreactors -- 3.6 Full Control of the Light Regime: LEDs Inside the PBR -- 3.7 Conclusions and Prospects -- References -- Part II Concepts in Metabolic Engineering -- Chapter 4 What We Can Learn from Measuring Metabolic Fluxes in Cyanobacteria -- 4.1 Central Carbon Metabolism in Cyanobacteria: An Overview and Renewed Pathway Knowledge -- 4.1.1 Glycolytic Routes Interwoven with the Calvin Cycle -- 4.1.2 Tricarboxylic Acid Cycling -- 4.2 Methodologies for Predicting and Quantifying Metabolic Fluxes in Cyanobacteria -- 4.2.1 Flux Balance Analysis and Genome‐Scale Reconstruction of Metabolic Network -- 4.2.2 13C‐Metabolic Flux Analysis -- 4.2.3 Thermodynamic Analysis and Kinetics Analysis -- 4.3 Cyanobacteria Fluxome in Response to Altered Nutrient Modes and Environmental Conditions -- 4.3.1 Autotrophic Fluxome -- 4.3.2 Photomixotrophic Fluxome -- 4.3.3 Heterotrophic Fluxome -- 4.3.4 Photoheterotrophic Fluxome -- 4.3.5 Diurnal Metabolite Oscillations -- 4.3.6 Nutrient States' Impact on Metabolic Flux -- 4.4 Metabolic Fluxes Redirected in Cyanobacteria for Biomanufacturing Purposes -- 4.4.1 Restructuring the TCA Cycle for Ethylene Production -- 4.4.2 Maximizing Flux in the Isoprenoid Pathway -- 4.4.2.1 Measuring Precursor Pool Size to Evaluate Potential Driving Forces for Isoprenoid Production -- 4.4.2.2 Balancing Intermediates for Increased Pathway Activity. , 4.4.2.3 Kinetic Flux Profiling to Detect Bottlenecks in the Pathway -- 4.5 Synopsis and Future Directions -- Acknowledgments -- References -- Chapter 5 Synthetic Biology in Cyanobacteria and Applications for Biotechnology -- 5.1 Introduction -- 5.2 Getting Genes into Cyanobacteria -- 5.2.1 Transformation -- 5.2.2 Expression from Episomal Plasmids -- 5.2.3 Delivery of Genes to the Chromosome -- 5.3 Basic Synthetic Control of Gene Expression in Cyanobacteria -- 5.3.1 Quantifying Transcription and Translation in Cyanobacteria -- 5.3.2 Controlling Transcription with Synthetic Promoters -- 5.3.2.1 Constitutive Promoters -- 5.3.2.2 Regulated Promoters that Are Sensitive to Added Compounds (Inducible) -- 5.3.2.3 CRISPR Interference for Transcriptional Repression -- 5.3.3 Controlling Translation -- 5.3.3.1 Ribosome Binding Sites (Cis‐Acting) -- 5.3.3.2 Riboswitches (Cis‐Acting) -- 5.3.3.3 Small RNAs (Trans‐Acting) -- 5.4 Exotic Signals for Controlling Expression -- 5.4.1 Oxygen -- 5.4.2 Light Color -- 5.4.3 Cell Density or Growth Phase -- 5.4.4 Engineering Regulators for Altered Sensing Properties: State of the Art -- 5.5 Advanced Regulation: The Near Future -- 5.5.1 Logic Gates and Timing Circuits -- 5.5.2 Orthogonal Transcription Systems -- 5.5.3 Synthetic Biology Solutions to Increase Stability -- 5.5.4 Synthetic Biology Solutions for Cell Separation and Product Recovery -- 5.6 Conclusions -- Acknowledgments -- References -- Chapter 6 Sink Engineering in Photosynthetic Microbes -- 6.1 Introduction -- 6.2 Source and Sink -- 6.3 Regulation of Sink Energy in Plants -- 6.3.1 Sucrose and Other Signaling Carbohydrates -- 6.3.2 Hexokinases -- 6.3.3 Sucrose Non‐fermenting Related Kinases -- 6.3.4 TOR Kinase -- 6.3.5 Engineered Pathways as Sinks in Photosynthetic Microbes -- 6.3.6 Sucrose -- 6.3.7 2,3‐Butanediol -- 6.3.8 Ethylene -- 6.3.9 Glycerol. , 6.3.10 Isobutanol -- 6.3.11 Isoprene -- 6.3.12 Limonene -- 6.3.13 P450, an Electron Sink -- 6.4 What Are Key Source/Sink Regulatory Hubs in Photosynthetic Microbes? -- 6.5 Concluding Remarks -- Acknowledgment -- References -- Chapter 7 Design Principles for Engineering Metabolic Pathways in Cyanobacteria -- 7.1 Introduction -- 7.2 Cofactor Optimization -- 7.2.1 Recruiting NADPH‐Dependent Enzymes Wherever Possible -- 7.2.2 Engineering NADH‐Specific Enzymes to Utilize NADPH -- 7.2.3 Increasing NADH Pool in Cyanobacteria Through Expression of Transhydrogenase -- 7.3 Incorporation of Thermodynamic Driving Force into Metabolic Pathway Design -- 7.3.1 ATP Driving Force in Metabolic Pathways -- 7.3.2 Increasing Substrate Pool Supports the Carbon Flux Toward Products -- 7.3.3 Product Removal Unblocks the Limitations of Product Titer -- 7.4 Development of Synthetic Pathways for Carbon Conserving Photorespiration and Enhanced Carbon Fixation -- 7.5 Summary and Future Perspective on Cyanobacterial Metabolic Engineering -- References -- Chapter 8 Engineering Cyanobacteria for Efficient Photosynthetic Production: Ethanol Case Study -- 8.1 Introduction -- 8.2 Pathway for Ethanol Synthesis in Cyanobacteria -- 8.2.1 Pyruvate Decarboxylase and Type II Alcohol Dehydrogenase -- 8.2.2 Selection of Better Enzymes in the Pdc-AdhII Pathway -- 8.2.3 Systematic Characterization of the PdcZM-Slr1192 Pathway -- 8.3 Selection of Optimal Cyanobacteria "Chassis," Strain for Ethanol Production -- 8.3.1 Synechococcus PCC 6803 and Synechococcus PCC 7942 -- 8.3.2 Synechococcus PCC 7002 -- 8.3.3 Anabaena PCC 7120 -- 8.3.4 Nonconventional Cyanobacteria Species -- 8.4 Metabolic Engineering Strategies Toward More Efficient and Stable Ethanol Production -- 8.4.1 Enhancing the Carbon Flux via Overexpression of Calvin Cycle Enzymes -- 8.4.2 Blocking Pathways that Are Competitive to Ethanol. , 8.4.3 Arresting Biomass Formation -- 8.4.4 Engineering Cofactor Supply -- 8.4.5 Engineering Strategies Guided by In Silico Simulation -- 8.4.6 Stabilizing Ethanol Synthesis Capacity in Cyanobacterial Cell Factories -- 8.5 Exploring the Response in Cyanobacteria to Ethanol -- 8.5.1 Response of Cyanobacterial Cells Toward Exogenous Added Ethanol -- 8.5.2 Response of Cyanobacteria to Endogenous Synthesized Ethanol -- 8.6 Metabolic Engineering Strategies to Facilitate Robust Cultivation Against Biocontaminants -- 8.6.1 Engineering Cyanobacteria Cell Factories to Adapt for Selective Environmental Stresses -- 8.6.2 Engineering Cyanobacteria Cell Factories to Utilize Uncommon Nutrients -- 8.7 Conclusions and Perspectives -- References -- Chapter 9 Engineering Cyanobacteria as Host Organisms for Production of Terpenes and Terpenoids -- 9.1 Terpenoids and Industrial Applications -- 9.2 Terpenoid Biosynthesis in Cyanobacteria -- 9.2.1 Methylerythritol‐4‐Phosphate Pathway -- 9.2.2 Formation of Terpene Backbones -- 9.3 Natural Occurrence and Physiological Roles of Terpenes and Terpenoids in Cyanobacteria -- 9.4 Engineering Cyanobacteria for Terpenoid Production -- 9.4.1 Metabolic Engineering -- 9.4.1.1 Terpene Synthases -- 9.4.1.2 Increasing Supply of Terpene Backbones -- 9.4.1.3 Engineering the Native MEP Pathway -- 9.4.1.4 Implementing the MVA Pathway -- 9.4.1.5 Enhancing Precursor Supply -- 9.4.2 Optimizing Growth Conditions for Production -- 9.4.3 Product Capture and Harvesting -- 9.5 Summary and Outlook -- Acknowledgments -- References -- Chapter 10 Cyanobacterial Biopolymers -- 10.1 Polyhydroxybutryate -- 10.1.1 Introduction -- 10.1.2 PHB Metabolism in Cyanobacteria -- 10.1.3 Industrial Applications of PHB -- 10.1.3.1 Physical Properties of PHB and Its Derivatives -- 10.1.3.2 Biodegradability -- 10.1.3.3 Application of PHB as a Plastic. , 10.1.3.4 Reactor Types.
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  • 3
    Online Resource
    Online Resource
    Boston, MA : Academic Studies Press
    Keywords: Electronic books
    Description / Table of Contents: The Russian Revolutions of 1917: TheNorthern Impact and Beyond consists of twelve articles, written by leadingscholars from Russia, Norway, Sweden and Great Britain. They deal with therepercussions of these revolutions in Russia and Scandinavia, especially in theNorthern parts of these countries.
    Type of Medium: Online Resource
    Pages: 1 online resource (194 pages)
    ISBN: 9781644690659
    DDC: 947.0841
    Language: English
    Note: Description based on publisher supplied metadata and other sources
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  • 4
    Publication Date: 2023-02-08
    Description: Compound-specific isotope analyses (CSIA) of fatty acids (FA) constitute a promising tool for tracing energy flows in food-webs. However, past applications of FA-specific carbon isotope analyses have been restricted to a relatively coarse food-source separation and mainly quantified dietary contributions from different habitats. Our aim was to evaluate the potential of FA-CSIA to provide high-resolution data on within-system energy flows using algae and zooplankton as model organisms. First, we investigated the power of FA-CSIA to distinguish among four different algae groups, namely cyanobacteria, chlorophytes, haptophytes and diatoms. We found substantial within-group variation but also demonstrated that delta C-13 of several FA (e.g. 18:3 omega 3 or 18:4 omega 3) differed among taxa, resulting in group-specific isotopic fingerprints. Second, we assessed changes in FA isotope ratios with trophic transfer. Isotope fractionation was highly variable in daphnids and rotifers exposed to different food sources. Only delta C-13 of nutritionally valuable poly-unsaturated FA remained relatively constant, highlighting their potential as dietary tracers. The variability in fractionation was partly driven by the identity of food sources. Such systematic effects likely reflect the impact of dietary quality on consumers' metabolism and suggest that FA isotopes could be useful nutritional indicators in the field. Overall, our results reveal that the variability of FA isotope ratios provides a substantial challenge, but that FA-CSIA nevertheless have several promising applications in food-web ecology. This article is part of the theme issue 'The next horizons for lipids as 'trophic biomarkers': evidence and significance of consumer modification of dietary fatty acids'.
    Type: Article , PeerReviewed
    Format: text
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  • 5
    Publication Date: 2024-05-08
    Description: Microalgae are the main source of the omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), essential for the healthy development of most marine and terrestrial fauna including humans. Inverse correlations of algal EPA and DHA proportions (% of total fatty acids) with temperature have led to suggestions of a warming-induced decline in the global production of these biomolecules and an enhanced importance of high latitude organisms for their provision. The cold Arctic Ocean is a potential hotspot of EPA and DHA production, but consequences of global warming are unknown. Here, we combine a full-seasonal EPA and DHA dataset from the Central Arctic Ocean (CAO), with results from 13 previous field studies and 32 cultured algal strains to examine five potential climate change effects; ice algae loss, community shifts, increase in light, nutrients, and temperature. The algal EPA and DHA proportions were lower in the ice-covered CAO than in warmer peripheral shelf seas, which indicates that the paradigm of an inverse correlation of EPA and DHA proportions with temperature may not hold in the Arctic. We found no systematic differences in the summed EPA and DHA proportions of sea ice versus pelagic algae, and in diatoms versus non-diatoms. Overall, the algal EPA and DHA proportions varied up to four-fold seasonally and 10-fold regionally, pointing to strong light and nutrient limitations in the CAO. Where these limitations ease in a warming Arctic, EPA and DHA proportions are likely to increase alongside increasing primary production, with nutritional benefits for a non-ice-associated food web.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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