Emerging Areas in Bioengineering E-Book
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- Herausgeber: Wiley-VCH Verlag GmbH & Co. KGaA
- Kategorie: Fachliteratur
- Serie: Advanced Biotechnology
- Sprache: Englisch
With more than 40 contributions from expert authors, this is an extensive overview of all important research topics in the field of bioengineering, including metabolic engineering, biotransformations and biomedical applications.
Alongside several chapters dealing with biotransformations and biocatalysis, a whole section is devoted to biofuels and the utilization of biomass. Current perspectives on synthetic biology and metabolic engineering approaches are presented, involving such example organisms as Escherichia coli and Corynebacterium glutamicum, while a further section covers topics in biomedical engineering including drug delivery systems and biopharmaceuticals. The book concludes with chapters on computer-aided bioprocess engineering and systems biology.
This is a part of the Advanced Biotechnology book series, covering all pertinent aspects of the field with each volume prepared by eminent scientists who are experts on the topic in question. Invaluable reading for biotechnologists and bioengineers, as well as those working in the chemical and pharmaceutical industries.
Advanced Biotechnology
Biotechnology is a broad, interdisciplinary field of science, combining biological sciences and relevant engineering disciplines, that is becoming increasingly important as it benefits the environment and society as a whole. Recent years have seen substantial advances in all areas of biotechnology, resulting in the emergence of brand new fields. To reflect this progress, Sang-Yup Lee (KAIST, South Korea), Jens Nielsen (Chalmers University, Sweden), and Gregory Stephanopoulos (MIT, USA) have joined forces as the editors of a new Wiley-VCH book series. Advanced Biotechnology will cover all pertinent aspects of the field and each volume will be prepared by eminent scientists who are experts on the topic in question.
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Seitenzahl: 1616
Veröffentlichungsjahr: 2017
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Table of Contents
Cover
Related Titles
Title Page
Copyright
List of Contributors
About the Series Editors
Part I: Biocatalysis
Chapter 1: Introduction to Emerging Areas in Bioengineering
1.1 Biotechnology
1.2 Bioengineering
1.3 Emerging Areas
1.4 Current Volume
Acknowledgments
References
Chapter 2: Over-Expression of Functionally Active Inclusion Bodies of Enzymes in Recombinant Escherichia coli
2.1 Introduction
2.2 Formation and Composition of IBs
2.3 Enhancement of Protein Quality and Enzymatic Activity in IBs
2.4 Applications of Enzyme-Based IBs
2.5 An Example of IBs:
N
-acetyl-d-neuraminic Acid Aldolase
2.6 Concluding Remarks
Acknowledgments
References
Chapter 3: Enzymatic Reactions in Ionic Liquids
3.1 Introduction
3.2 Enzymatic Reactions in Ionic Liquids
3.3 Factors Affecting Enzymatic Reactions in Ionic Liquids
3.4 Methods to Improve Enzyme Activity and Stability in Ionic Liquids
3.5 Conclusions and Perspectives
Abbreviations of Ionic Liquids
References
Chapter 4: Enzyme Immobilization on Nanoparticles: Recent Applications
4.1 Introduction
4.2 Preparation of Enzyme-Immobilized Nanoparticles
4.3 Application of Enzyme Nanoparticles
4.4 Conclusion and Perspectives
References
Chapter 5: Whole Cell Biocatalysts Using Enzymes Displayed on Yeast Cell Surface
Concise Definition of Subject
5.1 Introduction
5.2 GPI-Anchoring System
5.3 C-Terminus Free Display Systems
5.4 Applications of the Yeast Cell Surface Display System for Biocatalysts
5.5 Improvement of Catalytic Activity on the Yeast Cell Surface
5.6 Conclusions
References
Chapter 6: Design of Artificial Supramolecular Protein Assemblies by Enzymatic Bioconjugation for Biocatalytic Reactions
Concise Definition of Subject
6.1 Introduction
6.2 Protein Assembly on a Template with Specific Interaction/Reaction Sites
6.3 Protein Assembly without a Template: Self-Assembly of Protein Units
6.4 Future Prospects
Acknowledgment
Conflict of Interest
References
Chapter 7: Production of Valuable Phenolic Compounds from Lignin by Biocatalysis: State-of-the-Art Perspective
7.1 Lignin and Its Composition
7.2 Phenol Derivatives Derived from Lignin Deconstruction
7.3 Biocatalysis to Increase the Value of Lignin-Derived Phenolic Compounds
7.4 Outlook and Future Perspectives
Acknowledgments
References
Part II: Biofuels and Renewable Energy from Biomass
Chapter 8: Biofuels, Bio-Power, and Bio-Products from Sustainable Biomass: Coupling Energy Crops and Organic Waste with Clean Energy Technologies
8.1 Introduction
8.2 Sustainable Biomass for Sustainable Development
8.3 Biorefineries and Bioenergy Conversion Pathways
8.4 Conclusions
References
Further Reading/Resources
Chapter 9: Potential Lignocellulosic Biomass Resources in ASEAN Countries
9.1 Introduction and Characterization of Lignocellulosic Biomass in ASEAN Countries
9.2 Forest Residues in ASEAN Countries
9.3 Herbaceous Plants Residues in ASEAN Countries
9.4 Agriculture Residue in ASEAN Countries
9.5 ASEAN Government Programs and Policies on Natural Biomass
References
Chapter 10: Volatile Fatty Acid Platform: Concept and Application
10.1 Concept of Volatile Fatty Acid Platform
10.2 Application of VFA Platform
10.3 Tasks for Commercialization
References
Chapter 11: Biological Pretreatment of Lignocellulosic Biomass for Volatile Fatty Acid Production
11.1 Introduction
11.2 Pretreatments to Improve VFA Production
11.3 Future Prospect and Recent Technology Development
References
Chapter 12: Microbial Lipid Production from Volatile Fatty Acids by Oleaginous Yeast
12.1 Introduction
12.2 VFAs as a Carbon Source
12.3 Quality of Yeast Lipid
12.4 Conclusion
Acknowledgments
References
Chapter 13: Gasification Technologies for Lignocellulosic Biomass
13.1 Introduction
13.2 Gasification of Lignocellulosic Biomass
13.3 Overview of Gasification Technologies of Lignocellulosic Biomass
13.4 Classification of Gasification Technologies
13.5 Types of Gasification Systems
13.6 Performance Evaluation of Biomass Gasifiers
13.7 Industrial Biomass Gasification Plants
13.8 Conclusion
References
Chapter 14: Separation of Butanol, Acetone, and Ethanol
14.1 Gas Stripping
14.2 Liquid–Liquid Extraction
14.3 Adsorption
14.4 Pervaporation
14.5 Distillation
14.6 Conclusion
References
Chapter 15: Overview of Microalgae-Based Carbon Capture and Utilization
15.1 Introduction
15.2 Capturing of Inorganic Carbon Using Photosynthesis
15.3 Microalgal Biofuel Production
15.4 Application of Microalgal By-Products
15.5 Conclusion
References
Chapter 16: Bioengineering of Microbial Fuel Cells: From Extracellular Electron Transfer Pathway to Electroactive Biofilm
16.1 Microbial Fuel Cells: General Concept and Extracellular Electron Transfer
16.2 Electroactive Biofilm Meets with Biocompatible Materials
16.3 Bioengineering of Electroactive Biofilm: From Bacteria to Ecosystem
16.4 Conclusions and Future Perspectives
Acknowledgments
References
Part III: Synthetic Biology and Metabolic Engineering
Chapter 17: Genome Editing Tools for Escherichia coli and Their Application in Metabolic Engineering and Synthetic Biology
17.1 Introduction
17.2 Homologous Recombination-Mediated Tools
17.3 Single-Strand DNA-Mediated Recombination
17.4 Conclusion
References
Chapter 18: Synthetic Biology for Corynebacterium glutamicum: An Industrial Host for White Biotechnology
18.1 Introduction
18.2 Synthetic Elements of Synthetic Biology for
C. glutamicum
18.3 Conclusion and Outlook
References
Chapter 19: Metabolic Engineering of Solventogenic Clostridia for Butanol Production
19.1 Introduction
19.2 Biomass and Its Metabolism
19.3 Metabolic Engineering of Clostridia
19.4 Concluding Remarks and Future Perspectives
References
Chapter 20: Metabolic Engineering of Microorganisms for the Production of Lactate-Containing Polyesters
Acknowledgments
References
Chapter 21: Microbial Metabolic Engineering for Production of Food Ingredients
21.1 Metabolic Engineering
21.2 Biological Production of Functional Food Materials
21.3 Future Prospects
References
Part IV: Products
Chapter 22: Application of Lactic Acid Bacteria for Food Biotechnology
Concise Definition of Subject and Its Importance
22.1 Lactic Acid Bacteria
22.2 Expression Systems in LAB
22.3
In silico
Metabolic Pathway Model for LAB
22.4 The Prospect: Lactic Acid Bacteria as an Edible Therapeutic Probiotics
References
Chapter 23: Biopolymers Based on Raw Materials from Biomass
23.1 Introduction
23.2 Poly(butylene succinate)
23.3 Conclusion
References
Chapter 24: Bacterial Biofertilizers: High Density Cultivation
24.1 Introduction
24.2 Cultivation Strategies for a Few Important Bacterial Inoculants
Conflict of Interest
References
Part V: Biosensing and Nanobiotechnology
Chapter 25: Current Research in Korean Herbal Cosmetics
25.1 Introduction
25.2 Korean Herbal Medicine and Bioscience
25.3 Bioprocessing of Natural Compounds in Traditional Herbal Medicine
25.4 Skin Delivery Systems in Cosmetics
25.5 Conclusions
References
Chapter 26: Advanced Genetic Engineering of Microbial Cells for Biosensing Applications
26.1 Introduction
26.2 Genetic Engineering of Microbial Reporter Cells
26.3 Methods to Immobilize Cells and Maintain Cell Viability
26.4 Microbial Biosensors Based on Transducers
26.5 Conclusion and Future Prospects
Acknowledgments
References
Chapter 27: Bioelectronic Nose
27.1 Introduction
27.2 Concept of Bioelectronic Nose
27.3 Primary Transducer for Bioelectronic Nose
27.4 Secondary Transducer for Bioelectronic Nose
27.5 Applications
27.6 Conclusion
Acknowledgment
References
Chapter 28: Noninvasive Optical Imaging Techniques in Clinical Application
28.1 Fluorescence Diagnosis of Skin or Mucosa
28.2 Fluorescence Endoscopic Surgery
28.3 Fluorescence Image-Guided Intraoperative Open Surgery
28.4 Conclusion
Acknowledgments
References
Chapter 29: Advanced Short Tandem Repeat Genotyping for Forensic Human Identification
29.1 DNA Sample Sources and Collection
29.2 DNA Extraction from Biological Sources
29.3 Short Tandem Repeat Markers and Commercial Kits
29.4 Amplification of STR Loci
29.5 Capillary Electrophoretic Separation of STR Amplicons
29.6 Total Integrated Forensic STR Typing System
29.7 Conclusion
References
Chapter 30: DNA Microarray-Based Technologies to Genotype Single Nucleotide Polymorphisms
30.1
A
llele-Specific Oligonucleotide Competitive Hybridization (ASOCH)
30.2 Zip-Code Microarray
30.3 Universal Amplification-Based Technology
30.4 Bead Array Platform-Based SNP Genotyping
30.5 Conclusion
References
Chapter 31: Advanced Applications of Nanoscale Measuring System for Biosensors
Chapter Outline
31.1 Nanoscale Gravimetric Measuring System for Chiral Recognition
31.2 Nanoscale Measuring System Using Two-Photon-Adsorbed Photopolymerization for Biosensors
31.3 Nanoscale Measuring Systems Using AFM for Biosensors
31.4 Nanoscale Measuring Systems with Nanoscale Motion Detection
References
Chapter 32: Biosynthesis and Applications of Silver Nanoparticles
Concise Definition of Subject
32.1 Introduction
32.2 Silver Nanoparticles
32.3 Plants in Nanoparticle Synthesis
32.4 Parameters Affecting Synthesis of AgNPs
32.5 Mechanism of AgNP Synthesis
32.6 Applications of AgNPs
32.7 Conclusion
References
Part VI: Biomedical Engineering and Biopharmaceuticals
Chapter 33: Smart Drug Delivery Devices and Implants
33.1 Introduction
33.2 External Drug Delivery Devices
33.3 Internal Drug Delivery Implants
33.4 Image-Guided Drug Delivery Systems
33.5 Summary and Perspectives
Acknowledgments
References
Chapter 34: Controlled Delivery Systems of Protein and Peptide Therapeutics
34.1 Introduction
34.2 Drug Delivery Systems for Protein and Peptide Therapeutics
34.3 Clinical Development of Protein and Peptide Delivery Systems
34.4 Summary and Perspectives
References
Chapter 35: Cell Delivery Systems Using Biomaterials
35.1 Introduction to Cell-Based Therapeutics
35.2 Biomaterials as Cell Delivery Vehicles
35.3 Cell Delivery Strategies
35.4 Conclusion and Future Perspective
References
Chapter 36: Bioengineered Cell-Derived Vesicles as Drug Delivery Carriers
36.1 Introduction
36.2 Prokaryotic Cell-Derived Nanocarriers
36.3 Eukaryotic Cell-Derived Nanocarriers
36.4 Cell Membrane-Camouflaged Nanoparticles
36.5 Conclusions
Acknowledgments
References
Chapter 37: Advanced Genetic Fusion Techniques for Improving the Pharmacokinetic Properties of Biologics
Concise Definition of the Subject
37.1 Background
37.2 Fc-Fusion Technology
37.3 Albumin Fusion Technology
37.4 Transferrin Fusion Technology
37.5 CTP Fusion Technology
37.6 Summary
References
Chapter 38: Mussel-Mimetic Biomaterials for Tissue Engineering Applications
38.1 Introduction
38.2 Synthetic and Natural Polymer-Based Mussel-Mimetic Biomaterials
38.3 Tissue Adhesives
38.4 Biomolecule Immobilization and Drug Delivery
38.5 Concluding Remarks
Acknowledgments
References
Chapter 39: Mass Production of Full-Length IgG Monoclonal Antibodies from Mammalian, Yeast, and Bacterial Hosts
39.1 Mass Production of Biosimilar Monoclonal Antibodies in Mammalian Cells
39.2 Mass Production of Monoclonal Antibodies in Yeast
39.3 Mass Production of Monoclonal Antibodies in
Escherichia coli
39.4 Conclusion
References
Chapter 40: Recent Advances in Mass Spectrometry-Based Proteomic Methods for Discovery of Protein Biomarkers for Complex Human Diseases
Concise Definition of Subject
40.1 Introduction
40.2 MS-Based Proteomic Analysis Pipeline for Discovery of Protein Biomarkers
40.3 Discovery of Protein Biomarkers Using LC–MS/MS Analysis
40.4 Analysis of Proteomic Data for the Biomarker Discovery
40.5 Verification and Validation of Biomarker Candidates
References
Part VII: Computer-Aided Bioprocess Design and Systems Biology
Chapter 41: Overview on Bioprocess Simulation
41.1 Introduction
41.2 Modeling and Design of Bioprocess
41.3 Monitoring of Bioprocess
41.4 Control of Bioprocess
41.5 Computational Fluid Dynamics in Bioprocess Simulation
References
Chapter 42: Bioprocess Simulation and Scheduling
42.1 The Purpose of Bioprocess Simulation
42.2 Detailed Modeling of Single Batch Bioprocesses
42.3 Design and Operation of Multiproduct Facilities
42.4 Conclusion
Abbreviations
References
Chapter 43: Metabolism-Combined Growth Model Construction and Its Application to Optimal Bioreactor Operation
43.1 Introduction
43.2 Growth Model Construction and a Diversity of Modification Methods
43.3 Optimal Decision-Making System
43.4 Case Study
43.5 Summary
Acknowledgments
References
Chapter 44: Software Applications for Phenotype Analysis and Strain Design of Cellular Systems
44.1 Introduction
44.2 COBRA Framework
44.3 COBRA Software Applications
44.4 Utilizing the Potential of COBRA Software Applications Suite: A Practical Case Study
44.5 Conclusions and Future Perspectives
References
Chapter 45: Metabolic Network Modeling for Computer-Aided Design of Microbial Interactions
45.1 Biological Computer-Aided Design of
Interactions
45.2 Community Metabolic Network Reconstruction
45.3 Prediction of Interactions Using Metabolic Networks
45.4 Conclusions
Acknowledgments
Conflicts of Interest
References
Index
End User License Agreement
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Guide
Cover
Table of Contents
Part I: Biocatalysis
Begin Reading
List of Illustrations
Chapter 1: Introduction to Emerging Areas in Bioengineering
Figure 1.1 Application areas of biotechnology [4].
Figure 1.2 Various areas of biotechnology industries: chemicals (industrial biotechnology, proteins, and peptides), agriculture, pharmaceuticals, medical devices and equipment, information technology (digital healthcare, telemedicine, optics, biological computing, quantum computing), facilities and infrastructure management, and nanotechnology [5].
Figure 1.3 Three major biotech markets: (a) three sectors and (b) segmental industrial markets [6].
Figure 1.4 Polymer nanofiber and its application [33].
Figure 1.5 The fourth industrial revolution – industry 4.0 [46].
Chapter 2: Over-Expression of Functionally Active Inclusion Bodies of Enzymes in Recombinant Escherichia coli
Figure 2.1 The mechanism of chaperone-assisted protein folding and possible sources for the formation of IBs. Steps for which further evidence is required are highlighted with question marks. TF and N in the Figure denote the ribosome-associated TF and the N-terminus, respectively.
Figure 2.2 The SEM images (×15 000 magnification) of IBs from (a)
E. coli
BL21 expressing GST-Neu5Ac aldolase-5R and (b)
E. coli
BL21 co-expressing GST-Neu5Ac aldolase-5R and σ
32
at 2 h post-induction. Every granular particle shown in the images, panels (a) and (b), is IBs. Few IBs particles were randomly selected and marked in the images. Bars: 5 µm.
Chapter 3: Enzymatic Reactions in Ionic Liquids
Figure 3.1 Structure of common ionic liquid cations and anions.
Figure 3.2 General illustration of enzymatic reaction in ILs: (a) monophasic IL, (b) biphasic IL/organic solvent, (c) biphasic IL/scCO
2
, and (d) biphasic ILs/aqueous system.
Chapter 4: Enzyme Immobilization on Nanoparticles: Recent Applications
Figure 4.1 Illustration of general enzyme immobilization methods and reaction of immobilized enzyme.
Chapter 5: Whole Cell Biocatalysts Using Enzymes Displayed on Yeast Cell Surface
Figure 5.1 Gene cassettes for yeast cell surface display. (a) Gene cassette for the GPI-anchoring system (N-terminus free display system). (b) Gene cassette for the C-terminus free display system.
Figure 5.2 Schematic illustration of yeast cell surface display using a GPI-anchoring system.
Figure 5.3 Schematic illustration of yeast cell surface display system for construction of a mini-cellulosome. EG, endoglucanase; CBH, cellobiohydrolase; BGL, β-glucosidase; CBD, cellulose-binding domain.
Chapter 6: Design of Artificial Supramolecular Protein Assemblies by Enzymatic Bioconjugation for Biocatalytic Reactions
Figure 6.1 Protein assembly strategies on a template with specific interaction/reaction sites or self-assembling moieties.
Figure 6.2 Schematic illustration of site-specific bis-biotinylation of a dimeric enzyme for 1D assembly. (a) Molecular structures of new biotinylation substrates (b) and bacterial alkaline phosphatase (PDB ID: 1ALK) with the K-loop insertion sites for MTG-mediated biotinylation to yield long or short axis mutants (c).
Figure 6.3 Site-specific covalent attachment of protein units by Y tag-specific radical coupling for polymerization of functional proteins (a) or covalent conjugation between specific peptide–protein pairs (b).
Chapter 7: Production of Valuable Phenolic Compounds from Lignin by Biocatalysis: State-of-the-Art Perspective
Figure 7.1 Chemical structures of syringyl (a), guaiacyl (b), and
p
-hydroxyphenyl (c) moieties that are derived from their corresponding monolignols – sinapyl alcohol (d), coniferyl alcohol (e), and
p
-coumaryl alcohol (f). Structure on the right shows the C
β
−O−C
4
−aryl ether linkages (g).
Figure 7.2 Overview summary of the phenylpropanoid derivatives resulting from different chemical processes (a, alkali; b, acid; c, ionic liquid; d, supercritical fluid; e, metal) and physicochemical processes (f, photochemistry; g, thermochemistry; h, mechanochemistry) used for the deconstruction of lignin model compounds containing C
β
−O−C
4
aryl ether linkages.
Figure 7.3 Overview of the phenylpropanoid derivatives that can be derived from lignin deconstruction by biological processes. (a) Compounds that can be derived from reactions of bacteria and fungi with lignins containing C
β
−O−C
4
aryl ether linkages. (b) Products from the cleavage of lignin model compounds with laccase, LiP, and β-etherase.
Figure 7.4 Caffeic acid 3-
O
- and 4-
O
-α-glucopyranoside products of glucosylation catalyzed by α-amylase.
Figure 7.5 Hydroxylation of phenolic acids such as cinnamic acid,
p
-coumaric acid, and ferulic acid by various hydroxylases to synthesize the corresponding products –
p
-coumaric acid (a), caffeic acid (b), and 5-hydroxyferulic acid (c), respectively.
p
-Coumaric acid can be completely converted to 3,4,5-trihydroxycinnamic acid (3,4,5-THCA) (d) via caffeic acid. This reaction is catalyzed by the Y398S variant of HPAH from
Acinetobacter baumannii
. (Dhammaraj
et al
. 2015 [30]. Reproduced with permission of American Chemical Society.)
Figure 7.6 Hydroxylation of coniferyl alcohol derivatives (a) by ferulic acid 5-hydroxylase (F5H) to synthesize hydroxylated products (b) that can be used as precursors for sinapic acid synthesis (c).
Figure 7.7 Methylation of caffeyl and 5-hydroxyconiferyl derivatives (a) by SAM-dependent
O
-methyltransferase to produce coniferyl and sinapyl derivatives (b).
Figure 7.8 Demethylation of vanillic acid (a) to generate protocatechuic acid (PCA) (b).
Figure 7.9 Reversible conversion of ferulic acid (a) to generate 4-vinylguaiacol (b) via phenolic acid decarboxylase (PAD)-catalyzed decarboxylation/carboxylation reaction.
Chapter 8: Biofuels, Bio-Power, and Bio-Products from Sustainable Biomass: Coupling Energy Crops and Organic Waste with Clean Energy Technologies
Figure 8.1 Biomass conversion pathways [16].
Figure 8.2 Organic waste anaerobic digestion to energy concept.
Figure 8.3 Transesterification reaction of triglycerides for biodiesel production. (Ferreira
et al
. [31], https://www.hindawi.com/journals/isrn/2012/142857/. Used under CC BY 3.0, https://creativecommons.org/licenses/by/3.0/.)
Figure 8.4 Biomass gasification stages.
Chapter 9: Potential Lignocellulosic Biomass Resources in ASEAN Countries
Figure 9.1 Common structure of lignocellulosic material [3].
Chapter 10: Volatile Fatty Acid Platform: Concept and Application
Figure 10.1 Platforms for biofuel production. Two major platforms using sugar and syngas were underlined.
Figure 10.3 Concept of VFA platform.
Figure 10.2 COD flux for a particulate composite comprised of 10% inerts and 30% each of carbohydrates, proteins, and lipids (in terms of COD) [5]. All organic parts of living things are broken down to volatile fatty acids (a mixture of C2–C6 acids including acetic acid, propionic acid/lactic acid, butyric acid, valeric acid, and caproic acid), which turn into methane and CO
2
gas by anaerobic hydrolysis. Methane will be chemically or biologically oxidized into CO
2
and H
2
O. Nitrogen and phosphate compounds in living things (animals, plants, and microbial cell mass) can be recycled eventually into N
2
gas and phosphate salts, through a series of chemical or biological reactions. Sulfur compounds digested anaerobically are converted into H
2
S gas. Propionic acid (10%), butyric acid (12%), and valeric acid (7%) are grouped in the Figure for simplicity. Abbreviations include LCFA (long-chain fatty acids), HPr (propionic acid), Hbu (butyric acid), and HVa (valeric acid).
Figure 10.4 Useful carboxylates with high volume market potential to be produced in VFAs fermentation.
Figure 10.5 MixAlco® process developed at Texas A&M University.
Figure 10.6 Extended VFA platform.
Figure 10.7 Cost estimation of fuel alcohols. (a) Mixed alcohol production costs from various raw materials depending on the biomass price. The biomass materials include (i) lignocelluloses, (ii) marine biomass cultivated in huge scale, (iii) organic wastes, and (iv) Korean food waste. Hydrogen price was assumed as $2.0/kg
−1
. The plant size was 500 dry biomass tons per day or 180 000 dry biomass tons per year. (b) Comparison of ethanol costs in typical production processes. Values were estimated by (1) IEA/OECD, 2006 and (2) by our group. The mixed alcohols from VFA platform was converted to ethanol equivalent amount based on the energy equivalence and compared with other ethanol costs.
Figure 10.8 Research topics needed in VFA platform.
Chapter 11: Biological Pretreatment of Lignocellulosic Biomass for Volatile Fatty Acid Production
Figure 11.1 Comparison between volatile fatty acid (VFA) platform and sugar platform.
Chapter 12: Microbial Lipid Production from Volatile Fatty Acids by Oleaginous Yeast
Figure 12.1 Platforms for biofuel production (NREL).
Figure 12.2 Anaerobic digestion stages.
Chapter 13: Gasification Technologies for Lignocellulosic Biomass
Figure 13.1 Comparison of dry gas composition of various fixed bed gasifiers (sorted by gasifying agent and hydrogen content).
Figure 13.2 Comparison of dry gas composition in fixed bed gasification in terms of equivalence ratios: (a) Hydrogen. (b) Carbon monoxide. (c) Methane.
Figure 13.3 Schematic diagram of a BFB gasifier (a). Sequential reaction in the gasifier (b) (Kim
et al.
). Direct photo of a BFB gasifier (c, courtesy of KITECH).
Figure 13.4 Comparison of dry gas composition of various BFB gasifiers (sorted by gasifying agent and hydrogen content).
Figure 13.5 Comparison of dry gas composition in BFB gasification in terms of equivalence ratios. (a) Hydrogen. (b) Carbon monoxide. (c) Methane.
Figure 13.6 Schematic diagram of a CFB gasifier (a). Direct photo of a CFB gasifier (b, courtesy of Hasol Seentec co. Ltd).
Figure 13.7 Comparison of dry gas composition of various CFB gasifiers (sorted by gasifying agent and hydrogen content).
Figure 13.8 Comparison of dry gas composition in CFB gasification in terms of equivalence ratios. (a) Hydrogen. (b) Carbon monoxide. (c) Methane.
Figure 13.9 Schematic diagram of DFB gasifier (a). Direct photo of a DFB gasifier (b, courtesy of KITECH).
Figure 13.10 Concept diagram of DFB gasifier.
Figure 13.11 Comparison of dry gas composition of various DFB gasifiers (sorted by gasifying agent and hydrogen content).
Figure 13.12 Comparison of dry gas composition in DFB gasification in terms of equivalence ratios: (a) Hydrogen. (b) Carbon monoxide. (c) Methane.
Chapter 14: Separation of Butanol, Acetone, and Ethanol
Figure 14.1 Schematic diagram of the gas stripping process. (a) Recycled scenario (b) Single-pass scenario.
Figure 14.2 Schematic diagram of acetone–butanol–ethanol (ABE) production recovery by vacuum.
Figure 14.3 A comparison of energy requirement to separate ABE from fermentation broth using various energy-efficient techniques. SS, steam stripping distillation; GS, gas stripping; Perv, pervaporation; Ext, liquid–liquid extraction; Ad, adsorption onto silicalite [36].
Figure 14.4 A schematic diagram of ABE separation and concentration from fermentation broth using adsorbent.
Figure 14.5 Schematic diagram of a simplified pervaporation system.
Figure 14.6 Illustrations of various membrane module configurations: (a) spiral wound, (b) monolithic ceramic, (c) vibrating disk stack, (d) hollow fiber, and (e) plate and frame [73].
Figure 14.7 Illustration of integration processes of pervaporation and distillation. (a) Pervaporation–distillation system; (b) Pervaporation for both ethanol recovery and product dehydration [73].
Figure 14.8 Schematic diagram of liquid–liquid extraction associated distillation system [41].
Figure 14.9 Schematic diagram of a two-column distillation decanter coupled system for butanol purification [24, 130].
Figure 14.10 Schematic diagram of the five stages of distillation process using ABE fermentation broth.
Figure 14.11 Schematic diagram of five stage of distillation process using ABE fermentation broth. (a) Heat exchange system [133]. (b) Decanter in paralleled with the beer column [134].
Figure 14.12 Schematic diagram of fermentation–separation–purification integrated system. (a) gas stripping–liquid extraction associated with distillation-coupled process [41]. (b) flash fermentation-multiple stage distillation coupled process [8]; (c) pervaporation-multiple stage distillation coupled process [125, 126].
Chapter 15: Overview of Microalgae-Based Carbon Capture and Utilization
Figure 15.1 A general scheme of the biological CO
2
converting system of microalgae, separated by upper and downstream processes.
Chapter 16: Bioengineering of Microbial Fuel Cells: From Extracellular Electron Transfer Pathway to Electroactive Biofilm
Scheme 16.1 (a) Two-chamber MFCs with glucose as anode fuel and oxygen as cathode fuel. (b) Potential increase from the anode substrate degradation to cathode reaction in bioelectricity generation.
Scheme 16.2 (a) DET by cytochrome in MFCs. (b) DET by conductive pili in MFCs. (c) MET in MFCs.
Chapter 17: Genome Editing Tools for Escherichia coli and Their Application in Metabolic Engineering and Synthetic Biology
Figure 17.1 (a) One-step inactivation of a gene using the λ-Red and the SSR recombinase system. (b) Markerless gene deletion by
I-SceI
endonuclease. (c) Two-step markerless gene deletion by dual selection strategy.
Figure 17.2 CRISPR/Cas9-mediated genome editing. DSBs introduced by the Cas9-gRNA complex are repaired either by the host HR system in combination with chromosome/vector-based templates or by a heterologous recombineering system and linear ssDNA or dsDNA templates. In eukaryotes, DSBs are repaired by the NHEJ mechanism.
Figure 17.3 MAGE iterative cycle.
Figure 17.4 Schematic illustration of the CRMAGE system. Beta is co-expressed with dam, which gives a
mut
S mutator phenotype. Cas9 is expressed with
recX
, which blocks the repair of DSBs (pMA7CR_2.0). The tetracycline-inducible sgRNA is used for selection against the wild-type sequence, and a self-eliminating circuit targets its own backbone to enable plasmid recycling and sequential recombineering (pMAZ-SK).
Chapter 18: Synthetic Biology for Corynebacterium glutamicum: An Industrial Host for White Biotechnology
Figure 18.1 Synthetic biology platform for
Corynebacterium glutamicum
. For DNA parts, native promoters have been characterized and fully synthetic promoters for
C. glutamicum
have been developed. Small RNAs of
C. glutamicum
have been identified, and engineered antisense RNAs could be used to regulate the transcription of target genes. BioBrick restriction enzyme sites have been integrated in expression vectors of pTGR and CoryneBrick vectors (details in the text). Several replications of origins have been cloned to provide the different copies of the plasmid for different expression levels. For devices or biosensors, l-lysine-detecting metabolite sensor has been developed, based on the transcriptional regulator and its hybrid promoter. Native LysG of
C. glutamicum
activates the eYFP proteins whose signals were detected and sorted out by FACS. For chassis, optimum genome of
C. glutamicum
has been implemented to the wild-type by reducing 22% genome size (details in the text).
Chapter 19: Metabolic Engineering of Solventogenic Clostridia for Butanol Production
Figure 19.1 The proposed metabolic pathway for butanol production from various biomass in a microorganism. (a) The clostridial fermentative pathway, (b) pentose phosphate pathway, (c) glycerol catabolic pathway, (d) macroalgae degradation pathway, (e) Wood–Ljungdahl pathway, and (f) 2-ketoacid pathway. Solid and dashed arrows indicate direct and indirect pathways, respectively.
Chapter 20: Metabolic Engineering of Microorganisms for the Production of Lactate-Containing Polyesters
Figure 20.1 Metabolic engineering of
E. coli
for the production of PLA and copolymers. Cross marks show knocked out genes to eliminate competing pathways. Dotted arrows indicate overexpression by the use of strong promoters. Gray arrows represent multiple steps. (Ppc: phosphoenolpyruvate carboxylase or frdABCD: fumarate reductase, ptsG: IIBC
Glc
, glucose transporter, poxB: pyruvate oxidase, dld: d-lactate dehydrogenase, aceB: malate synthase A, glcB: malate synthase G, glcDEFG: glycolate oxidase, ilvA: threonine dehydratase, ldhA: (d)-lactate dehydrogenase, pflB: pyruvate formate lyase, ackA: acetate kinase, Acs: acetyl-CoA synthase, PhaA: β-ketothiolase, PhaB: acetoacetyl reductase, adhE: acetaldehyde/alcohol dehydrogenase, CimA: citramalate synthase, LeuB: 3-isopropylmalate dehydrogenase, LeuCD: Isopropylmalate (IPM) isomerase, PanE: 2-hydroxyacid dehydrogenase, Pct540: evolved propionyl-CoA transferase, PhaC1437: evolved PHA synthase, XylB: xylose dehydrogenase, XylC: xylonolactonase, lacI: transcriptional repressor) [10–14].
Figure 20.2 The key enzymes for biosynthesis of lactate-containing polymers. Particular residues of the
Clostridium propionicum
propionyl-CoA transferase (Pct
Cp
) and
Pseudomonas
sp. 6-19 PHA synthase I (PhaC1
Ps6-19
) are engineered to exhibit higher activities
in vivo
. The mutated sequences are shown in comparison with the wild-type residues in the original polypeptides. Pct532 and Pct540 are the mutants derived from the
C. propionicum
Pct by error-prone PCR. Pct532 has an amino acid mutation (A243T) in addition to the silent nucleotide mutation (A1200G). Pct540 has an amino acid mutation (V193A) and four silent nucleotide mutations (T78C, T669C, A1125G, and T1158C). PhaC1202, PhaC1310, PhaC1400, and PhaC1437 are the mutants derived from the
Pseudomonas
sp. 6-19 PHA synthase I (PhaC1
Ps6-19
). PhaC1202, PhaC1 mutant having double mutations (E130D and Q481K); PhaC1310, PhaC1 mutant having triple mutations (E130D, S447F, and Q481K); PhaC1400, PhaC1 mutant having quadruple mutations (E130D, S325T, S477R, and Q481M); PhaC1437, PhaC1 mutant having quadruple mutations (E130D, S325T, S477G, and Q481K) [10].
Chapter 21: Microbial Metabolic Engineering for Production of Food Ingredients
Figure 21.1 Value-added biotransformation through microbial fermentation.
Figure 21.2 Microbial metabolic engineering to produce food ingredients. (a) Metabolic engineering approaches for the production of 2-FL in engineered
E. coli
consist of three elements including efficient supply of lactose, overproduction of GDP-l-fucose, and high levels of active α-1,2-fucosyltransferase. (b) Sorbitol production in LAB. Metabolic engineering strategies to prevent reutilization of the produced sorbitol, to inactivate mannitol-producing pathways, and to improve redox balance have been attempted. (c) Riboflavin production in
B. subtilis
. Efficient supply of important metabolic precursors and overexpression of purine pathway genes led to enhanced production of riboflavin. (d) Folate production in
L. lactis
. The increased availability of
para
-aminobenzoic acid (
p
ABA) resulted in improved folate production. Glc-6-P: glucose-6-phosphate, Fru-6-P: fructose-6-phosphate, Man-6-P: mannose-6-phosphate, Man-1-P: mannose-1-phosphate, GDP-Man: guanosine diphosphate mannose, GDP-4-keto-6-dMan: guanosine diphosphate-4-keto-6-deoxymannose. GDP-Fuc: guanosine diphosphate fucose, Glc-1-P: glucose-1-phosphate, UDP-Glc: uridine diphosphate glucose, UDP-Gal: uridine diphosphate galactose, PTS: phosphotransferase system, EMP: Embden-Meyerhof-Parnas pathway, TCA: tricarboxylic acid cycle, S7P: sedoheptulose-7-phosphate, X5P: xylulose-5-phosphate, Gluconate-6-P: gluconate-6-phosphate, Ru-5-P: ribulose-5-phosphate, Ribo-5-P: ribose-5-phosphate, PRPP: phosphoribosyl pyrophosphate, IMP: inosine monophosphate, GTP: guanosine tri-phosphate, ArP: 4-(1-D-ribitylamino)-5-amino-2,6-dihydroxypyrimidine, DHPB, 3,4-dihydroxy-2-butanone 4-phosphate, DRL: 6,7-dimethyl-8-ribityl-lumazine, Gly: glycine, Gln: glutamine, 10-formyl-THF: 10-formyl tetrahydrofolate, PPP: pentose phosphate pathway, PEP: phosphoenolpyruvate,
p
ABA:
para
-aminobenzoic acid, DHF: dihydrofolate, THF: tetrahydrofolate. The dashed arrows indicate inactivation of the pathways.
Chapter 22: Application of Lactic Acid Bacteria for Food Biotechnology
Figure 22.1 General metabolism of
Leuconostoc
[77]. Major products formed are indicated in bold. Numbers refer to enzymes involved or steps: 1, dextransucrase; 2, mannitol-dehydrogenase; 3, β-galactosidase; 4, esterase; 5, NADH oxidase; 6, alcohol dehydrogenase; 7, phosphoketolase; 8, phosphotransacetylase, 9, α-acetolactate decarboxylase; 10, acetate kinase; 11, α-acetolactate synthase; 12, non-enzymatic formation; 13, diacetyl reductase; 14, oxaloacetate decarboxylase; 15, lactate dehydrogenase; 16, citrate lyase; 17, malate dehydrogenase; 18, formation of aspartate; 19, malolactic enzyme; and 20, ATPase.
Chapter 23: Biopolymers Based on Raw Materials from Biomass
Figure 23.1 Synthesis of succinic acid (SA) and 1,4-butanediol (BD) from furfural [19].
Figure 23.2 Polymerization of PBS: (a) direct polycondensation, (b) transesterification polycondensation, and (c) enzymatic polymerization.
Figure 23.3 Schematic diagram of biodegradable polymer recycling [29].
Figure 23.4 Hydrolysis and dehydration reactions of PBS [29].
Figure 23.5 Hydrolysis and polymerization of PLA.
Figure 23.6 Young's modulus of PBS/CNT nanocomposites as a function of CNT content.
Figure 23.7 Tensile properties of PBS/CNT nanocomposites with different CNT contents.
Figure 23.8 Electrical conductivities of PBS/CNT nanocomposites as a function of CNT content.
Figure 23.9 Tensile strength of untreated and alkali-treated coir fiber/PBS biodegradable composites (mean value and standard deviation).
Figure 23.10 Tensile modulus of untreated and alkali-treated coir fiber/PBS biodegradable composites (mean value and standard deviation).
Figure 23.11 Elongation at break of untreated and alkali-treated coir fiber/PBS biodegradable composites (mean value and standard deviation).
Figure 23.12 Tensile properties of PBS/jute fiber composites [113].
Figure 23.13 Fracture surfaces of PBS composites reinforced with (a) untreated, (b) 2% NaOH-treated, and (c) coupling agent-treated jute fibers.
Figure 23.14 Effect of silane treatment (with 3% APTMS) on the (a) tensile strength and (b) elongation at break of PBS/CF composites.
Chapter 24: Bacterial Biofertilizers: High Density Cultivation
Figure 24.1 Sequence of process operations during production of bio-inoculant.
Chapter 25: Current Research in Korean Herbal Cosmetics
Figure 25.1 HPLC profile of green tea seed extract and the hydrolysis of GTSE with the commercial glycolytic enzymes: (a) green tea seed extract, (b) reaction with hesperidinase, (c) reaction with cellulase, and (d) reaction with β-galactosidase.
Figure 25.2 HPLC profile of hydrolysate of GTSE using mixed enzyme reaction; (a) green tea seed extract; (b) reaction with β-galactosidase; (c) reaction with (b) and hesperidinase; key to peak identity: (1) compound
1
; (2) compound
2
; (4) compound
4
; (5) compound
5
(kaempferol).
Figure 25.3 Structure of glycosidic flavonoids isolated from green tea seed and its enzymatic hydrolyzed product, kaempferol; Glc: glucopyranoside, Gal: galactopyranoside, Xyl: xylopyranoside, Rha: rhamnopyranoside.
Figure 25.4 Structure of oxyisoflavone isolated from 5-year-old KFS and other isoflavones.
Figure 25.5 Total oxyisoflavones content with different aging periods of KFS. Total amount of oxyisoflavone in KFS for different periods was determined by HPLC. Each value is the mean ± SD (
n
= 3).
Chapter 26: Advanced Genetic Engineering of Microbial Cells for Biosensing Applications
Figure 26.1 Schematic representation of microbial biosensors.
Chapter 27: Bioelectronic Nose
Figure 27.1 Schematic diagram of bioelectronic nose, constructed by the combination of biomaterials and nanomaterial-based sensor elements. The specific binding of analytes to biomaterials can be measured by a nanomaterial-based sensing element. S and D represent “source” and “drain,” respectively, in the nanomaterial-based platform.
Figure 27.2 Proposed three-dimensional structure of the olfactory receptor. Each of the transmembrane regions is numbered.
Figure 27.3 (a) Schematic diagram showing a method to prepare an olfactory-nanovesicle-fused carbon nanotube-transistor biosensor (OCB). A CNT-based transistor was coated with poly-d-lysine (PLD) for the stable adsorption of nanovesicles. Then, olfactory nanovesicles were immobilized on a CNT channel region in the transistor. (b) Schematic diagram showing the sensing mechanism for the detection of hexanal with an OCB. The binding of hexanal to ORs results in Ca
2+
ions inside the nanovesicles, creating a positive gate potential in the vicinity of underlying CNTs, and the increased potential results in the decrease of conductance in the CNT channel.
Figure 27.4 Highly selective and sensitive detection of hexanal with OCB devices. (a) SEM image of nanovesicles immobilized on a CNT channel. The white arrows indicate the nanovesicles. (b) Chemical structures of various odorant molecules. Hexanal is the specific ligand of cfOR5269 protein. Note that the odorants have similar structures, with slight differences in their alkyl chain length, or functional groups. (c) Real-time conductance measurement data obtained from an OCB after the introduction of hexanal. The conductance decreased after the introduction of hexanal solution with a femtomolar concentration. (d) Response curve of OCBs (
n
= 5) to hexanal with different concentrations. The responses of OCBs were fitted to the Langmuir isotherm curve (red solid curve). (e) Real-time conductance measurement data obtained from an OCB after the injection of different odorants. The addition of 1 nM heptanal, octanal, pentanal, and hexanol solutions had no effect on the conductance of the OCB, while the addition of 1 pM hexanal solution caused a sharp decrease in the conductance of the OCB.
Figure 27.5 PRBN for the detection of TMA. Olfactory receptor peptides (ORPs) were self-assembled on the surface of SWNTs during the treatment of ORP-suspended deionized water solutions. The ORPs were immobilized by
π–π
stacking of aromatic rings of three phenylalanine sequences at their C-terminus and attracted TMA molecules very near to the SWNTs.
Figure 27.6 Sensitive and selective detection of TMA using PRBNs. (a) Real-time measurements of conductance changes generated by the introduction of TMA at concentrations ranging from 1 fM to 1 nM using bare (triangle) and ORP-coated (circle) SWNT-FETs. The decrease in conductance was visible after the introduction of 10 fM of TMA, and the responses increased, with an increase in TMA concentrations. (b) Dose-dependent response curve of PRBNs to TMA. Each point and error bar represents the mean and standard deviation (SD), respectively, calculated from five real-time measurements. (c) Real-time recognition of TMA from other small molecules using bare (triangle) and ORP-coated (circle) SWNT-FETs. The addition of 1 pM TMA solution caused a sharp decrease in the conductance of ORP-SWNT devices; however the addition of 1 nM of other molecules had no effect on the conductance. (d) Quantitative comparison of conductance changes, after the injection of TMA and other molecules at a concentration of 1 nM (
n
= 5). TMA, trimethylamine; TEA, triethylamine; DMA, dimethylamine; MP, 2-methyl-1-propanol; EA, ethyl acetate; EtOH, ethanol; MeOH, methanol; AA, acetic acid.
Figure 27.7 Detection of heptanal from human blood plasma using a nanovesicle-based bioelectronic nose. The bioelectronic nose was fabricated using nanovesicles, with olfactory receptor (OR), Gα
olf
, and receptor-transporting protein 1S (RTP1S). (a) A real-time measurement for the influence of plasma on the conductance change in the bioelectronic nose. Human blood plasma samples were diluted to different ratios. The 1/10
−7
-diluted plasma did not show any effect on the conductance, which means that no pretreatment process is required, when 1/10
−7
-diluted plasma is used in the experiment. (b) The real-time detection of heptanal from 1/10
−7
-diluted plasma using a bioelectronic nose. A bioelectronic nose based on nanovesicles with OR, Gα
olf
, and RTP1S was able to detect 1 × 10
−13
M heptanal (square), whereas a bioelectronic nose without ORs was not (triangle).
Figure 27.8 Detection of trimethylamine (TMA) from spoiled seafood using peptide receptor-based bioelectronic nose. (a) A real-time measurement data exhibiting the conductance change generated by repeated treatments with a spoiled oyster sample, which was produced by storing the oyster sample at 25 °C for 2 days. Consistent and prompt responses were generated. The gray dotted line represents the initial base line. (b) Real-time measurements of conductance changes generated by treatments with oyster (circle), shrimp (square), and lobster (triangle) samples, spoiled for different periods of time. Significant decreases in the conductance were observed for the 2-day spoiled oyster, 1-day spoiled shrimp, and 2-day spoiled lobster, and the responses increased with the spoilage time. (c) Response patterns versus the degree of spoilage of the three spoiled seafood samples (oyster, shrimp, and lobster). The generated responses tended to increase with the degree of spoilage. (d) Real-time recognition and distinction of spoiled oyster from other types of spoiled foods (milk, tomato, broccoli, and beef) and fresh oyster. The sample solutions of milk, tomato, broccoli, and beef spoiled for 4 days and the fresh oyster had no significant effect on the conductance. However, the injection of the oyster sample that had been spoiled for 2 days caused a sharp decrease in conductance.
Chapter 28: Noninvasive Optical Imaging Techniques in Clinical Application
Figure 28.1 (a) Acne, (b) psoriasis, (c) pigmentation, and (d) scar.
Figure 28.2 (a) Cervix after cold knife conization. (b) Cervix of a patient prior to radioactive treatment, showing residual cancer.
Figure 28.3 Superficial bladder cancer: (a) T1 tumor and (b) carcinoma
in situ
(CIS).
Figure 28.4 Absorbance and radiation characteristics of ICG, detection results of SN at white, near-IR, and white + near-IR rays.
Figure 28.5 (a) Open brain surgery for malignant glioma, (b) 5-ALA-induced fluorescence image, and (c) 5-ALA photodynamic therapy after partial debulking versus surgical excision.
Chapter 29: Advanced Short Tandem Repeat Genotyping for Forensic Human Identification
Figure 29.1 (a) The QIAGEN the QIAGEN QIAamp DNA mini kits (top) and the conventional DNA extraction instrument, which is Automate Express Forensic DNA Extraction System made by ABI (down), and (b) the microchannel that is packed with the silica beads for capturing genomic DNAs.
Figure 29.2 (a) The conventional thermal cycler (top) and the GlobalFiler Express STR typing kit made by Applied Biosystems (down left) and PowerPlex 18D (down right). (b) The integrated PCR-CE chip that shows an enlarged PCR chamber that was fabricated on the glass wafer together with micropatterned gold electrodes (red) and resistance temperature detectors (green).
Figure 29.3 (a) The conventional ABI Prism 3500 Genetic Analyzer for CE separation and laser-induced fluorescence detection. (b) A microfabricated 96-channel capillary array electrophoresis device. STR Profiles using (c) a PowerPlex 16 and (d) a Profiler Plus analyzed on the 96-channel capillary array electrophoresis system.
Figure 29.4 (a) RapidHIT
TM
system from IntegenX Inc. for a total integrated STR typing platform with sample-in–answer-out capability. (b) A fully integrated microdevice that incorporated sequence-specific DNA purification, μPCR, post-PCR cleanup, in-line injection, and μCE.
Figure 29.5 (Top panel) The current state-of-the-art STR typing processes and (bottom panel) the microfluidic-based STR typing processes. The total integration becomes feasible for rapid and on-site STR human identification.
Chapter 30: DNA Microarray-Based Technologies to Genotype Single Nucleotide Polymorphisms
Figure 30.1 (a) Schematic representation of SNP genotyping by ASOCH. (b) Typical image obtained from hybridization on the DNA microarray.
Figure 30.2 Schematic representation of SNP genotyping utilizing DNA zip-code microarray. Allelic discrimination is achieved by employing appropriately designed probes and SNP-specific enzymatic reactions including ligation, SBE, and enzymatic cleavage. The fluorescence-labeled probe consisting of gene-specific sequence and complementary zip-code sequence is addressed to its corresponding zip-code sequence.
Figure 30.3 Schematic representation of SNP genotyping by ligation-based zip-code microarray.
Figure 30.4 Schematic representation of SNP genotyping by SBE-based zip-code microarray.
Figure 30.5 Schematic representation of SNP genotyping by SSS nuclease assay-based zip-code microarray.
Figure 30.6 Schematic representation of MIP technology-based SNP genotyping method. The probes contain target DNA annealing sites, universal PCR primer binding sites, complementary zip-code sequence, and two cleavage sites. After MIP annealed to the target DNA, gap-filling extension and ligation are performed. By cleaving cleavage site 1, the probes are inverted, and then universal PCR occurs. On the microarray, the amplified complementary zip-code sequences are hybridized together with biotin–streptavidin-conjugated signaling probes for fluorescence signaling.
Figure 30.7 Schematic representation of MIP technology-based allelic discrimination on the DNA microarray by four separated gap-filling extension and ligation.
Figure 30.8 Schematic representation of GoldenGate assay. Genomic DNA is captured on a solid support. At the 3′-region, complementary oligonucleotide primer (either P1 or P2) is bound, and at the 5′-region, LSO is bound. The extension and ligation between ASO and LSO is then carried out to produce an artificial PCR template. After universal PCR amplification, address region in LSO will bind to capture probes on microarray and the fluorescent signals are interpreted.
Figure 30.9 Schematic representation of ASLP technology-based allelic discrimination on the DNA microarray by allele-specific ligation, universal primer extension, biotin-based separation, and universal amplification of ligated product.
Figure 30.10 Schematic representation of encoding and distribution of the beads. (a) Encoding each type of the beads and gathering in a single tube to produce a mixture of the beads. (b) Distribution of the beads on the Sentrix BeadChip. (c) Distribution of the beads on the SAM.
Figure 30.11 Schematic representation of Infinium assay. (a) WGA products. (b) Hybridization of WGA products to capture probes on the bead array. (c) ASPE of correctly captured DNA with fluorescent dNTPs.
Chapter 31: Advanced Applications of Nanoscale Measuring System for Biosensors
Figure 31.1 Schematic presentation of fabrication process of S-MA derivative-modified QCM sensor: 4-ATP modification (a), S-MA coupling reaction (b), protecting group removal (c), and finally modified S-MA derivative surface (d).
Figure 31.2 Force–distance curves measured using the normal tip (a) and the polymeric tip (b) on a freshly cleaved mica surface in the air and the comparison of DNA topographic images obtained using the normal tip (c) and the polymeric tip (d). (e) and (f) show expanded views of background mica surface with the normal tip (e ) and the polymeric tip (f). Scale bars means 1 µm (c, d) and 40 nm (e, f).
Figure 31.3 A schematic illustration for the interaction measurement between Cu
2+
ion and histidine.
Figure 31.4 Schematic representation of the preparation of protein-modified microspheres and gel samples for affinity detection of IgG beads (orange) and biotin-IgG beads (orange) with Sav (a), profilin beads (orange) with actin (b), and mixture of IgG-beads (yellow green) and biotin-IgG beads (orange) with Sav (c).
Chapter 32: Biosynthesis and Applications of Silver Nanoparticles
Figure 32.1 Top-down and bottom-up strategies for the synthesis of nanomaterials and fabrication of nanostructures.
Figure 32.2 General scheme of biological synthesis of nanoparticles.
Chapter 33: Smart Drug Delivery Devices and Implants
Figure 33.1
Microneedle drug delivery devices
. (a) The delivery of sulforhodamine in
ex vivo
pig skin by biodegradable PVP microneedle.
Figure 33.2
Trans-skin wearable devices
. (a) Wearable electronic patch composed of data storage modules, diagnostic tools, and therapeutic actuating elements. ( Reproduced with permission from [22] © 2014, Rights Managed by Nature Publishing Group.) (b) Wearable interactive device integrated with touch and temperature sensors, a wireless coil, and a DDP.
Figure 33.3
Drug-eluting stent
. (a) Biodegradable everolimus-eluting coronary stent. (Adapted from Ormiston
et al
. 2008 [26]. Reproduced with permission of Elsevier.) (b) Bioresorbable electronic stent system.
Figure 33.4
Programmable drug delivery implants
. Light-guiding hydrogels encapsulating cells for
in vivo
sensing and therapy.
Figure 33.5
Image-guided therapeutic delivery devices
. Nanotheranostics that transform into concrete practice the concept of personalized nanomedicine.
Chapter 34: Controlled Delivery Systems of Protein and Peptide Therapeutics
Figure 34.1 (a) Long-acting drug delivery systems (DDSs). Polymer-conjugated drugs can circumvent renal clearance due to its large size. (b) Controlled DDS such as a drug depot system can prolong the drug release. (c) Targeted DDS can be developed using target-specific antibody and peptide.
Figure 34.2 Transdermal delivery of hyaluronate (HA)–protein conjugate for needle-free immunization. HA–vaccine conjugates can penetrate into deep dermal tissues and induce immune responses by interacting with dendritic cells.
Figure 34.3 (a) Drug depot systems prepared with PLGA for controlled release of LH–RH and (b) micelle-like nanoparticles of self-assembling anti-Flt1 peptide–hyaluronate (HA) conjugate. (c) HA hydrogel for controlled delivery of protein and peptide therapeutics. The mesh size is designed to be in the range of protein particle size, enabling the controlled release of protein molecules.
Figure 34.4 Gold nanoparticle (AuNP)
-
based drug delivery system with HA and antibody modification for the treatment of rheumatoid arthritis.
Figure 34.5 Schematic illustration of drug delivery systems via various administration routes.
Chapter 35: Cell Delivery Systems Using Biomaterials
Figure 35.1 Schematic diagram of methodologies used to modify surface of therapeutic cells. (1) Covalent attachment of therapeutic materials to membrane proteins through the interaction of reactive groups such as N-hydroxysuccinamide (–NHS), thiol (–SH), and catechol with amine (–NH2) of cell membrane. (2) Layer-by-layer coating of therapeutic materials by nonspecific electrostatic adsorption to negatively charged cell membrane. (3) Anchoring amphiphilic therapeutic materials by insertion of hydrophobic part to lipid bilayer membrane. (4) Conjugation of therapeutic materials through mediated specific couplings such as biotin–streptavidin, DNA hybridization, and thiol–maleimide (TM: therapeutic material).
Figure 35.2 Diagrammatic sketch to illustrate the relationship between cells and scaffold. Microenvironment provided by the scaffold affects cell behavior and signaling pathways. Cells are generally attached to the scaffold via integrin receptors that are closely connected to the cytoskeleton of cell. The receptors relay information to the cell, thereby affecting cell function.
Figure 35.3 Effects of nature of biomaterial in cellular transport processes. Optimized degree of cross-linking and pore size (a) facilitate the diffusion of nutrients and oxygen to the site of cell and waste materials from the microenvironment to outside preventing infiltration of immune cells. In contrast, a high degree of cross-linking and decreased pore size (b) limits the transport processes to and from the cell microenvironment.
Chapter 36: Bioengineered Cell-Derived Vesicles as Drug Delivery Carriers
Figure 36.1 Bacterial OMVs as drug delivery carriers. (a) The bioengineering strategy for OMVs is shown. The anti-HER affibody was expressed on the outer membrane of msbB mutant W3110 derived K12 strain. The purified Affi
HER2
OMV's were loaded with siRNA (Affi
HER2
OMV
siRNA
) and kinetics of Affi
HER2
OMV
siRNA
was evaluated
in vitro
and
in vivo
. (b)
In vivo
therapeutic efficacy of Affi
HER2
OMV
siRNA
was evaluated against different controls. HER2 targeted Affi
HER2
OMV
siRNA
showed significant tumor regression effect compared with controls. (Gujrati
et al
. 2014 [14]. Reproduced with permission of American Chemical Society.)
Figure 36.2 (a) Schematic showing MV generation and loading of agents with different physicochemical properties. Cancer-specific distribution of MVs
in vitro
(a) and
in vivo
(b). (Lee
et al
. 2015 [35]. Reproduced with permission of American Chemical Society.)
Figure 36.3 Functionalization of AuNPs with RBC membranes. RBC vesicles were developed by removing intracellular contents of RBCs and repeatedly extruding the RBC ghosts. Next, citrate-stabilized AuNPs were extruded with RBC vesicles resulting in membrane coating of AuNPs and formation of RBC-AuNPs. (Reproduced with permission [43]. Copyright 2013, John Wiley & Sons.)
Chapter 38: Mussel-Mimetic Biomaterials for Tissue Engineering Applications
Figure 38.1 Schematic diagram of the adhesion chemistry used by mussel-mimetic biomaterials containing DOPA residues. The reduced catechol form of DOPA binds to surfaces directly for adhesion (upper left image). The oxidized states of DOPA, semiquinone and quinone, may be reduced by a thiol-rich partner protein to regain surface-binding ability. Cohesion within the bulk material can be brought about by metal ion templating and oxidation chemistry, including radical–radical coupling (upper-right image). Mussel-mimetic biomaterials adhere to biological tissue surfaces using various possible mechanisms (lower image) [7–9].
Figure 38.2 Biomolecules, such as proteins, peptides, calcium phosphate (CaP), and drugs, can be immobilized on functionalized target surfaces or scaffolds that are coated with mussel-mimetic biomaterials for a wide range of applications [26, 83, 91, 92, 100–103].
Chapter 39: Mass Production of Full-Length IgG Monoclonal Antibodies from Mammalian, Yeast, and Bacterial Hosts
Figure 39.1 Crystal structure of full-length IgG (PDB: 1HZH). The Fc region is represented in a circle.
Figure 39.2 Aglycosylated Fc variants engineered for binding to both FcγRIIa and FcγRIIb (a), for selective binding to FcγRI (b), and for binding FcγRIIa over FcγRIIb (c). The mutations are represented on the crystal structure of aglycosylated Fc (PDB: 3S7G).
Chapter 40: Recent Advances in Mass Spectrometry-Based Proteomic Methods for Discovery of Protein Biomarkers for Complex Human Diseases
Figure 40.1 Overall pipeline for the proteomics-based discovery of protein biomarkers involving unbiased discovery, targeted verification, and clinical validation.
Figure 40.2 Workflow of proteomics analysis employed during the discovery phase.
Figure 40.3 Workflow of MRM–MS analysis. Each targeted peptide is preselected in Q1 and then fragmented by the collision-induced dissociation in Q2, and particular transitions are detected among fragmented ions in Q3.
Chapter 42: Bioprocess Simulation and Scheduling
Figure 42.1 Benefits from the use of computer aids.
Figure 42.2 Monoclonal antibody production flow sheet.
Figure 42.3 The operations associated with the P-5 unit procedure of Figure 42.2.
Figure 42.4 One bioreactor train feeding one purification train.
Figure 42.5 Four bioreactor trains feeding one purification train.
Figure 42.6 Production cost of MAb as a function of the number of bioreactor trains.
Figure 42.7 Production cost of MAb as a function of product titer and production bioreactor volume.
Figure 42.8 Line occupancy chart for capacity analysis and strategic planning.
Figure 42.9 Recipe Gantt chart.
Figure 42.10 Production schedule of two products with shared equipment.
Figure 42.11 Scheduling of buffer preparation and holding activities.
Figure 42.12 Operator labor demand for multiple campaigns.
Figure 42.13 Scheduling conflicts due to a delay.
Figure 42.14 WFI demand chart for utility sizing.
Figure 42.15 WFI system operation.
Figure 42.16 Mobile equipment floor space requirement.
Chapter 43: Metabolism-Combined Growth Model Construction and Its Application to Optimal Bioreactor Operation
Figure 43.1 Bioreactor optimization scheme based on the constructed model.
Figure 43.2 Different prediction of lipid concentration of
C. protothecoides
by original (a) and modified model (b) in [11].
Figure 43.3 Structural difference between model-based optimization with DFBA and xDFBA.
Figure 43.4 Comparison of feed rate strategy and cost yield result.
Figure 43.5 Time-varying simulation result of states of two heuristics and optimized strategy.
Chapter 44: Software Applications for Phenotype Analysis and Strain Design of Cellular Systems
Figure 44.1 The two major stages of COBRA framework. (i) Model reconstruction – the initial step in COBRA approach is to reconstruct the metabolic model from genomic, biochemical, and literature information. (ii) Phenotypic analysis and strain design – once the model is reconstructed, constraints from mass balance, thermodynamics, and enzyme capacity are imposed to constrain the flow of metabolites, and the feasible solution(s) can be identified using optimization or exhaustive enumeration. Additionally, the efficient metabolic route for a targeted overproduction of a particular metabolite of interest can also be identified using the model.
Figure 44.2 Timeline showing the development of numerous COBRA software applications and the implementation of various key features within them. The available software tools are categorized into three major classes based on implementation and execution type: stand alone, web based, and toolbox based.
Chapter 45: Metabolic Network Modeling for Computer-Aided Design of Microbial Interactions
Figure 45.1 A schematic illustration of the concept of BioCAD
i
in the typical engineering cycle of design–build–test.
Figure 45.2 Top-down and bottom-up approaches for predicting microbial interactions. The right panel compares the conventional top-down prediction using similarity- and regression-based methods with the bottom-up prediction using the metabolic network simulation.
Figure 45.3 Overall procedures of metabolic network reconstruction: gene sequencing and assembly, gene calling and annotation, semiautomatic network reconstruction, and finally manual curation.
List of Tables
Chapter 2: Over-Expression of Functionally Active Inclusion Bodies of Enzymes in Recombinant Escherichia coli
Table 2.1 Average particle size of IBs and activities of Neu5Ac aldolase in the soluble and insoluble fractions of
E. coli
BL21 cells over-expressing GST-Neu5Ac aldolase-5R, or cells co-expressing GST-Neu5Ac aldolase-5R and σ
32
Chapter 3: Enzymatic Reactions in Ionic Liquids
Table 3.1 Hydrolases in ionic liquids
Table 3.2 Oxidoreductases in ionic liquids
Table 3.3 Other enzymes in ionic liquids
Table 3.4 Whole cell catalysts in ionic liquids
Table 3.5 Effect of ionic liquid physicochemical properties on enzyme activity and stability
Chapter 4: Enzyme Immobilization on Nanoparticles: Recent Applications
Table 4.1 Examples illustrated for general covalent attachments of enzyme immobilization
Table 4.2 Some immobilized enzyme nanoparticles in biosensor applications
Chapter 5: Whole Cell Biocatalysts Using Enzymes Displayed on Yeast Cell Surface
Table 5.1 Applications of the cell surface display system for fungi and bacteria
Chapter 6: Design of Artificial Supramolecular Protein Assemblies by Enzymatic Bioconjugation for Biocatalytic Reactions
Table 6.1 Classification of strategies to assemble recombinant functional proteins
Chapter 7: Production of Valuable Phenolic Compounds from Lignin by Biocatalysis: State-of-the-Art Perspective
Table 7.1 Examples of phenolic compounds derived from lignin deconstruction and their potential applications
Chapter 8: Biofuels, Bio-Power, and Bio-Products from Sustainable Biomass: Coupling Energy Crops and Organic Waste with Clean Energy Technologies
Table 8.1 Cellulose, hemicellulose, and lignin contents in common agricultural residues and wastes
Table 8.2 Ultimate and proximate analyses of various lignocellulosic biomass [75]
Chapter 9: Potential Lignocellulosic Biomass Resources in ASEAN Countries
Table 9.1 Forest, herbaceous, and agricultural residues in ASEAN countries.
Chapter 10: Volatile Fatty Acid Platform: Concept and Application
Table 10.1 Comparison of three major platforms
Table 10.2 Studies for volatile fatty acid production
Table 10.3 Summary of the stoichiometry of lipid production and lipid yield on glucose and VFAs
Table 10.4 Studies for microbial lipid production using VFAs
Chapter 11: Biological Pretreatment of Lignocellulosic Biomass for Volatile Fatty Acid Production
Table 11.1 Effect of biological and combination of pretreatments on anaerobic digestion (AD) and volatile fatty acid (VFA) production
Chapter 12: Microbial Lipid Production from Volatile Fatty Acids by Oleaginous Yeast
Table 12.1 Lipid content of oleaginous microorganisms
Table 12.2 Comparison of three major platforms
Table 12.3 Microbial lipid production by oleaginous yeast under VFAs as a carbon source
Chapter 13: Gasification Technologies for Lignocellulosic Biomass
Table 13.1 Representative gasification and combustion reactions of biomass [109]
Table 13.2 Typical ranges of producer gas composition for selected gasifiers
Table 13.3 Various types of biomass gasifier
Table 13.4 Feedstock and operating details of selected fixed bed gasification systems
Table 13.5 Feedstock and operating details of selected bubbling fluidized bed gasification systems
Table 13.6 Feedstock and operating details of selected circulating fluidized bed gasification systems
Table 13.7 Feedstock and operating details of selected dual fluidized bed gasifiers
Table 13.8 Characteristics of the gasification system and operation details [111]
Table 13.9 Representative demo and commercial biomass gasification plants
Chapter 14: Separation of Butanol, Acetone, and Ethanol
Table 14.1 Comparison of ABE fermentations with integrated gas stripping for online butanol recovery
Table 14.2 Solvent extractants for butanol recovery by liquid–liquid extraction [39, 40]
Table 14.3 Some results of butanol adsorption by different adsorbents
Table 14.4 Pervaporation performances of different PV membranes in acetone, butanol, and alcohol recovery
Table 14.5 Pervaporation performances of different PV membranes for the dehydration of solvents
Table 14.6 Current advances in
in situ
ABE separation from fermentation broth
Chapter 19: Metabolic Engineering of Solventogenic Clostridia for Butanol Production
Table 19.1 Fermentation performance of metabolically engineered
C. acetobutylicum
strains
Table 19.2 Simultaneous fermentation of mixed sugars by metabolically engineered
Clostridia
Chapter 20: Metabolic Engineering of Microorganisms for the Production of Lactate-Containing Polyesters
Table 20.1 Thermal and mechanical properties of PLA and PLA copolymers.
a
Chapter 21: Microbial Metabolic Engineering for Production of Food Ingredients
Table 21.1 Production of food ingredients by engineered microorganisms
Chapter 22: Application of Lactic Acid Bacteria for Food Biotechnology
Table 22.1 List of lactic acid bacteria, probiotics, and biotechnology application strains
Table 22.2 List of lactic acid bacteria, probiotics, and biotechnology application strains
Table 22.3 Constitutive promoters for expression in lactic acid bacteria
Table 22.4 Characteristics of inducible expression systems for LAB [41, 43]
Table 22.5 Features of food-grade selection markers for LAB, including the donors from which the systems were derived and the hosts that allow their application
Table 22.6 Homologous and heterologous proteins produced in
Lc. lactis
[12, 56]
Chapter 23: Biopolymers Based on Raw Materials from Biomass
Table 23.1 Mechanical properties of PBS.
a, b)
Table 23.2 Water contact angles of PBS and other biodegradable polymers [25, 33, 34]
Table 23.3 Biodegradation data for PBS films [25]
Table 23.4 Biodegradation of different forms of PBS after 90 days of composting [43]
Table 23.5 Specifications of OMLS
Table 23.6
G
′ of PBS and nanocomposites at different temperatures [90]
Table 23.7 Tensile properties and O
2
gas permeability of neat PBS and nanocomposites [90]
Table 23.8 Molecular weight of PBS in various samples after 35 days of biodegradation in compost [90]
Table 23.9 Thermal properties of PBS and PBS/CNT nanocomposites [83]
Table 23.10 Physical properties of PBS/graphene nanocomposites [118]
Table 23.11 Chemical composition and structural parameters of some natural fibers [120]
Table 23.12 Properties of some natural and conventional man-made fibers [120]
Table 23.13 Characteristics of jute fibers following surface modification
Chapter 24: Bacterial Biofertilizers: High Density Cultivation
Table 24.1 Spore yields during cultivation of
Bacillus
spp. in various studies
Chapter 25: Current Research in Korean Herbal Cosmetics
Table 25.1 Biological effects of compound
K
and ginsenoside
F
1
on the skin
Table 25.2 DPPH radical scavenging activity of tea seed flavonoids and kaempferol
Table 25.3
13
C NMR and
1
H NMR data of new oxyisoflavone derivatives
Table 25.4 Inhibitory effects of
o
-dihydroxyisoflavones and isoflavones on tyrosinase and melanin formation in melan-a cells
Chapter 26: Advanced Genetic Engineering of Microbial Cells for Biosensing Applications
Table 26.1 Diverse applications of microbial biosensors
Chapter 27: Bioelectronic Nose
Table 27.1 Applications of the bioelectronic nose
Chapter 33: Smart Drug Delivery Devices and Implants
Table 33.1 Summary of image-guided drug delivery devices
Chapter 38: Mussel-Mimetic Biomaterials for Tissue Engineering Applications
Table 38.1 Mussel-inspired short peptides
Table 38.2 Cell and tissue responses to mussel-mimetic surface functionalization in hard tissue engineering
Table 38.3 Biomolecule immobilization and drug delivery using mussel-mimetic polymers
Chapter 39: Mass Production of Full-Length IgG Monoclonal Antibodies from Mammalian, Yeast, and Bacterial Hosts
Table 39.1 Biosimilar drugs approved worldwide [11, 12]
Table 39.2 Analytical methods for physicochemical and functional characterization of antibodies
Table 39.3 Clinical trials of aglycosylated antibodies [43]
Chapter 42: Bioprocess Simulation and Scheduling
Table 42.1 Raw material requirements (MP = purified MAb)
Table 42.2 Major equipment specification and purchase costs (year 2013 prices in U.S. dollar)
Table 42.3 Fixed capital estimate summary (year 2013 prices in U.S. dollar)
Table 42.4 Operating cost summary (year 2013 prices in U.S. dollar)
Table 42.5 Consumables cost breakdown (year 2013 prices in U.S. dollar)
Table 42.6 Raw materials cost breakdown (year 2013 prices in U.S. dollar)
Table 42.7 Operational data for product A and product B recipes
Chapter 43: Metabolism-Combined Growth Model Construction and Its Application to Optimal Bioreactor Operation
