Molecular Pharming E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 1105

Veröffentlichungsjahr: 2018

Beschreibung

A single volume collection that surveys the exciting field of plant-made pharmaceuticals and industrial proteins This comprehensive book communicates the recent advances and exciting potential for the expanding area of plant biotechnology and is divided into six sections. The first three sections look at the current status of the field, and advances in plant platforms and strategies for improving yields, downstream processing, and controlling post-translational modifications of plant-made recombinant proteins. Section four reviews high-value industrial and pharmacological proteins that are successfully being produced in established and emerging plant platforms. The fifth section looks at regulatory challenges facing the expansion of the field. The final section turns its focus toward small molecule therapeutics, drug screening, plant specialized metabolites, and plants as model organisms to study human disease processes. Molecular Pharming: Applications, Challenges and Emerging Areas offers in-depth coverage of molecular biology of plant expression systems and manipulation of glycosylation processes in plants; plant platforms, subcellular targeting, recovery, and downstream processing; plant-derived protein pharmaceuticals and case studies; regulatory issues; and emerging areas. It is a valuable resource for researchers that are in the field of plant molecular pharming, as well as for those conducting basic research in gene expression, protein quality control, and other subjects relevant to molecular and cellular biology. * Broad ranging coverage of a key area of plant biotechnology * Describes efforts to produce pharmaceutical and industrial proteins in plants * Provides reviews of recent advances and technology breakthroughs * Assesses realities of regulatory and cost hurdles * Forward looking with coverage of small molecule technologies and the use of plants as models of human disease processes Providing wide-ranging and unique coverage, Molecular Pharming: Applications, Challenges and Emerging Areas will be of great interest to the plant science, plant biotechnology, protein science, and pharmacological communities.

Leseprobe

Table of Contents

Cover

Title Page

List of Contributors

Preface

Part One: The Molecular Farming/Pharming Landscape

1 Current Status and Perspectives of the Molecular Farming Landscape

Abbreviations

1.1 Introduction

1.2 Brief history of Molecular Farming

1.3 Recent developments in R&D and commercialization

1.4 Commercial products and platforms

1.5 Downstream processing and infrastructure

1.6 Plant matrix encapsulation as an alternative to purification

1.7 Perspectives and opportunities for the future

1.8 Conclusions

Acknowledgements

References

Part Two: Molecular Biology of Plant Expression Systems and Manipulation of Glycosylation Processes in Plants

2 Synthetic Transcription Activator‐Like Effector‐Activated Promoters for Coordinated Orthogonal Gene Expression in Plants: Applications for Regulatory Circuit and Metabolic Engineering

Abbreviations

2.1 Introduction

2.2 Synthetic TALE‐activated Promoters: Design, Construction, and Testing

2.3 Designing Regulatory Circuits

2.4 Modeling the networks

2.5 Input signals

2.6 Output

2.7 Conclusions

References

3 Contemporary and Emerging Technologies for Precise N‐glycan Analyses

Abbreviations

3.1 Introduction

3.2 Common and Disparate Features During Biosynthesis

3.3 Basic Considerations for Glycomics

3.4 N‐glycan release

3.5 N‐glycan purification

3.6 N‐glycan derivatization

3.7 N‐glycan HPLC and CE

3.8 N‐glycan Mass Spectrometry

3.9 Exoglycosidase and Chemical Digestion of glycans

3.10 N‐glycan arrays

3.11 Glycomic databases

3.12 N‐glycans from plants and algae

3.13 Conclusions

References

4 Production of Functionally Active Recombinant Proteins in Plants: Manipulating

N

‐ and

O

‐glycosylation

Abbreviations

4.1 Introduction

4.2

N

‐Glycan engineering

4.3

O

‐glycan engineering

4.4 Outlook: The emerging field of Genome Editing

Acknowledgements

References

Part Three: Plant Platforms, Subcellular Targeting, Recovery, and Downstream Processing

5 Seeds as Bioreactors

Abbreviations

5.1 Introduction

5.2 Plant Bioreactor Systems

5.3 Seeds are Native Protein Bioreactors

5.4 Seed Protein Storage Vacuole as Bioreactors

5.5 Seed Oil Bodies as bioreactors

5.6 Examples of seed‐derived Recombinant Proteins

5.7 Considerations for the use of seeds as bioreactors: Factors and approaches

5.8 Conclusions and Future Prospects

Acknowledgements

References

6 Strategies to Increase Expression and Accumulation of Recombinant Proteins

Abbreviations

6.1 Introduction

6.2 Strategies for enhancing the expression and accumulation of Recombinant Proteins

6.3 Summary and Conclusions

References

7 The Impact of Six Critical Impurities on Recombinant Protein Recovery and Purification from Plant Hosts

Abbreviations

7.1 Introduction

7.2 Plant Expression Platforms and Implications on Downstream Processing

7.3 The 6Ps

7.4 Summary and Conclusion

References

8 Plant Recombinant Lysosomal Enzymes as Replacement Therapeutics for Lysosomal Storage Diseases: Unique Processing for Lysosomal Delivery and Efficacy

Abbreviations

8.1 Introduction

8.2 Human Lysosomal Storage Diseases and the Development of Enzyme Replacement Therapies

8.3 General Challenges Associated with Conventional mammalian‐cell‐based Production Platforms

8.4 Plant‐based Production Systems – General Advantages and challenges for generating LSD Replacement Therapeutics

8.5 Biochemistry Underlying the Mammalian Cellular machinery for M6P elaboration in More Detail

8.6 Approaches to effect the M6P tagging of plant‐Produced Recombinant Lysosomal Enzymes Under Development for ERT

8.7 Alternative strategies for Lysosomal Delivery and Improved Biodistribution of ERTs

8.8 Future directions

Acknowledgements

References

Part Four: Plant‐Derived Protein Pharmaceuticals and Case Studies

9 Plant‐Produced Antibodies and Post‐Translational Modification

Abbreviations

9.1 Introduction

9.2 IgGs and Post‐Translational Engineering

9.3 Production and Engineering of IgA and IgM mAbs

9.4 Conclusions

Acknowledgements

References

10 Molecular Pharming: Plant‐Made Vaccines

Abbreviations

10.1 Introduction

10.2 Overview of Mammalian Immune System and Vaccines

10.3 Plant Expression Systems

10.4 Plant‐made vaccines

10.5 Prospects for future Development of plant‐made Vaccines

Acknowledgments

References

11 Transgenic Rice for the Production of Recombinant Pharmaceutical Proteins: A Case Study of Human Serum Albumin

Abbreviations

11.1 Introduction: Challenges of Generating Recombinant Human Serum Albumin

11.2 Strategies to overcome the challenges of Generating Recombinant HSA

11.3 Characterization of OsrHSA

11.4 Processing and manufacturing OsrHSA from Rice Grain

11.5 Safety assessment of OsrHSA

11.6 OsrHSA and pHSA Exhibit Similar Pharmacokinetic Features

11.7 OsrHSA Exhibits Similar Therapeutic Efficacy to pHSA

11.8 Conclusions and perspectives

References

12 Enzymes for Industrial and Pharmaceutical Applications – From Individual to Population Level Impact

Abbreviations

12.1 Introduction

12.2 Industrial enzymes

12.3 Pharmaceutical enzymes

12.4 Future directions

Acknowledgements

References

Part Five: Regulatory Issues

13 Biosafety, Risk Assessment, and Regulation of Molecular Farming

Abbreviations

13.1 Introduction

13.2 The need for a Regulatory System

13.3 International regulation of GM crops

13.4 Regulation of the Intended Use of the product

13.5 Molecular Farming Platforms – Key Regulatory Aspects

13.6 Molecular Farming Products – Key Regulatory Aspects

13.7 Case studies

13.8 Conclusions and Future Perspectives

Acknowledgements

References

Part Six: Emerging Areas: Plant Specialized Metabolites and Small Molecule Drugs

14 Harnessing Plant Trichome Biochemistry for the Production of Useful Compounds

Abbreviations

14.1 Introduction

14.2 Diversity of Compounds Produced by Glandular Trichomes

14.3 Glandular Trichomes as a Source of Enzymes and Genes for Metabolic Engineering

14.4 Can Other Organisms Compete for the Production of Trichome‐Based Compounds?

14.5 Engineering Trichomes for the Production of Novel Compounds

14.6 Conclusions

References

15 Reconstitution of Medicinally Important Plant Natural Products in Microorganisms

Abbreviations

15.1 Introduction

15.2 Heterologous Production of Medicinally Important Plant Natural Products

15.3 Conclusions

Acknowledgements

References

16 Screening of Epidermal Growth Factor Receptor Inhibitors in Natural Products Derived From Extracts of Traditional Chinese Medicines

Abbreviations

16.1 Introduction

16.2 Strategies for Screening Bioactive Compounds From Natural Product Resources

16.3 New Technologies Used for Natural Product Dereplication

16.4 Development of an EGFR Inhibition Assay Method with Capillary Electrophoresis

16.5 Screening of Natural Product Extracts and Identification of the Active Components

16.6 Conclusions

Acknowledgments

References

17 Target‐Directed Evolution of Mutant Transgenic Plant Cells as a Novel Source of Drugs

Abbreviations

17.1 Introduction

17.2 Development of the Technology – the Mutagenic Strategy

17.3 Development of the Technology‐Selection of Mutants

17.4 Target‐Directed Evolution

17.5 Proof of Concept for Target‐Directed Evolution in

Lobelia cardinalis

17.6 Generation and Selection of Transgenic (

hDAT

) Cell Cultures

17.7 Pharmacological Analysis of Culture Extracts

17.8 Development of Traditional Medicinal Plant Extracts

17.9 Chemical analysis of Culture Extracts for Lobinaline Content

17.10 Biosynthetic Production Systems

17.11 Other Metabolites with Inhibitory Activity on the DAT?

17.12 Chemical and Biosynthetic Compound Libraries

17.13 A Bonus! Neuroprotective Metabolites

17.14 Another Bonus! Cytoprotective Gene Targets

17.15 Using the Technology in Reverse

17.16 Conclusions

References

18 Plant Thermotolerance Proteins, Misfolded Proteins, and Neurodegenerative Diseases

Abbreviations

18.1 Introduction

18.2 Human Neurodegenerative Diseases

18.3 Conservation of the Plant and Human Genomes Provides a Tool to Further Understand Human Diseases

18.4 Numerous Neuronal Proteins are Conserved in Plants

18.5 Conservation of Kinases and Ubiquitin Ligase Functions

18.6 Thermotolerance and Proteases – the Clearance of Misfolded Proteins

18.7 Conservation of Oxidative Stress Related Proteins and the Link to Neurodegeneration

18.8 The Value of Plants in Understanding the Mechanisms of Non‐plant Proteins Associated with Neurodegeneration

18.9 Concluding Remarks and Future Directions

References

Index

End User License Agreement

List of Tables

Chapter 05

Table 5.1 List of recombinant proteins using seeds as bioreactors.

Table 5.2 Specific factors to consider when using seeds as bioreactors.

Chapter 08

Table 8.1 Biochemical and clinical features of three of the lysosomal storage diseases (LSDs) for which plant‐based therapeutics are being developed.

Table 8.2 Factors to be considered for

in planta

synthesis of phosphotransferase (α‐, β‐, γ‐subunits) and UCE (see Figure 8.3).

Table 8.3 Strategies under development to improve ERT and potential mechanisms underlying improved biodistribution.

Chapter 11

Table 11.1 Amino acid composition of OsrHSA from different batches.

Table 11.2 Molecular mass of OsrHSA by ESI–Q‐TOF.

Table 11.3 OsrHSA crystal data collection and refinement statistics.

Table 11.4 Glycation of OsrHSA analyzed by LC‐MS.

Table 11.5 Pilot manufacturing of OsrHSA.

Chapter 13

Table 13.1 The process/product application matrix of molecular farming showing how the regulations designed to apply to a production process and a product application can be superimposed.

Table 13.2 Overview of EU environmental regulations for GMOs.

Table 13.3 Overview of EU regulations for pharmaceuticals, other medical products, and cosmetics.

Chapter 14

Table 14.1 Examples of enzyme classes identified in plant glandular trichomes.

Table 14.2 Recent examples of metabolic engineering of the artemisinin pathway in glandular trichomes of

Artemisia annua

.

Chapter 16

Table 16.1 A library of natural compound extracts for inhibitor screening.

List of Illustrations

Chapter 01

Figure 1.1 The diversity of molecular farming platforms and products. This graphical overview shows the most important platforms and corresponding product categories based on an analysis of the literature from January 2011 to June 2016.

Figure 1.2 Frequency of molecular farming publications according to the expression platform, product type, and development level. The spot radius is proportional to the number of publications from January 2011 to June 2016. Nb,

N. benthamiana

; Nb VR,

N. benthamiana

viral replicon.

Figure 1.3 Increase in the number of publications concerning the downstream processing of PMPs and the corresponding increase in manufacturing capacity. (A) The number of total publications (circles) and review articles (open squares) focusing on the downstream processing of PMPs has increased since January 2011 and we expect this trend to continue in the future. (B) Several pilot‐scale facilities (<1000 kg biomass output per week) using whole plants were built before 2015, when the first process‐scale facility became operational. Several companies have already announced or commenced additional projects to further increase their manufacturing capacity.

Figure 1.4 Distribution of different products and clarification methods reported in publications focusing on the downstream processing of PMPs in 2011 (n = 7) and 2016 (n = 13).

Chapter 02

Figure 2.1 Architecture of the synthetic TALE‐activated promoters (STAPs). The 19 nucleotide long effector binding element (EBE) specifically recognized by a TALE is flanked by the TATA box immediately downstream and by two degenerate sequences of 19 and 43 nucleotides upstream and downstream, respectively. The STAPs are cloned directly upstream of the coding sequence of the gene of interest (

GOI

).

Figure 2.2 Examples of possible regulatory circuits. (A) A simple ON switch whose activity depends on the activity of the input promoter. (B) An ON switch with a built‐in positive feedback loop ensuring durable expression after the initial activation of the input promoter (top). The signal can be amplified by the introduction of an intermediate activating TALE (bottom). (C) An oscillator circuit with an activating TALE and a repressor (TALOR), which regulate each other and the output gene. (D) An OFF switch with a TALOR repressing the expression of a target gene; the TALOR itself could be under the control of an activating TALE. (E) A transient expression circuit. A TALE activates both a target gene and a TALOR, which represses the activating TALE. Activity profiles for each circuit are given on the right panel (bottom).

Figure 2.3 Overview of STAPs based regulatory circuits for metabolic pathways. The genes for the engineered pathways are under the control of a series of STAPs, with the expression of each gene optimized for a balanced metabolic flux. In parallel, genes of competing pathways (pathway competitors;

PaCos

) can be repressed by a catalytic inactive Cas9 (dCas9), itself under the control of the activating TALE. The dCas9‐repressor is targeted to

PaCos

by specific sgRNAs.

Chapter 03

Figure 3.1 Overview of N‐glycan processing and example N‐glycan structures. The major steps in post‐transfer N‐glycan processing are shown in the dashed box together with the names of the key processing enzymes conserved in all multicellular organisms. The example final structures (oligomannosidic, mammalian biantennary complex, plant paucimannosidic, and plant complex) are also shown together with the symbolic nomenclature for the most common eukaryotic monosaccharides.

Figure 3.2 Summary of glycan release methods. The basic enzymatic and chemical release methods are shown together with a potential workflow to separate various classes of protein‐linked glycans. Abbreviations are: CEX (cation exchange), GF (gel filtration), nPGC (non‐porous graphitized carbon), C18 (reversed‐phase material), red. end (reducing end). Examples of glycans resulting from the various steps are also shown (based on a number of different studies from invertebrates and mammals).

Figure 3.3 Summary of typical N‐glycan analysis methods. The various mass spectrometric, spectroscopic, and chromatographic choices are indicated with the potential workflows; the information yielded as well as the advantages and disadvantages of the methods are also summarized. Types of MS/MS fragments (A, B, C, X, Y, and Z) are also shown for a disaccharide. On‐line strategies refer to analyses in which a chromatography system is directly coupled to a mass spectrometer; off‐line to where fractions are first collected and then individually subject to MS.

Chapter 04

Figure 4.1

N

‐glycan processing pathway and

N

‐glycan‐engineering approaches.

N

‐glycan trimming and maturation involves α‐glucosidase I and II (GCSI, GCSII), ER‐ α‐mannosidase I (ER‐MI), Golgi‐α‐mannosidase I (GMI),

N

‐acetylglucosaminyltransferase I (GnTI), Golgi‐α‐mannosidase II (GMII), and

N

‐acetylglucosaminyltransferase II (GnTII). In plants, complex

N

‐glycans are commonly modified by β1,2‐xylosyltransferase (XylT) and core α1,3‐fucosyltransferase (FucT). On some glycoproteins Le

a

structures are generated by β1,3‐galactosyltransferase (GALT1) and α1,4‐fucosyltransferase (FUT13). Paucimannosidic

N

‐glycans (MMXF) result from β‐hexosaminidase (HEXO) activity in the apoplast (HEXO3) or vacuole (HEXO1). In mammals, GnGn serves as acceptor glycan for core α1,6‐fucosyltransferase (FUT8), N‐acetylglucosaminyltransferase III (GnTIII), IV (GnTIV), V (GnTV), and β1,4‐galactosyltransferase (B4GALT1). Further elongations are catalyzed by sialyltransferases (ST) and in rare cases by enzymes like α1,3‐fucosyltransferase (FUT9). Different

N

‐glycan engineering approaches are indicated: H/KDEL‐tag‐mediated ER accumulation; elimination of unwanted endogenous glycosyltransferase activities like GnTI, XylT, FucT, and GALT1; expression of missing mammalian glycosyltransferases (GTs); targeting to the vacuole or knockout of HEXO3. Glycan cartoons were drawn using the Consortium for Functional Glycomics symbols (www.functionalglycomics.org). For a detailed explanation of N‐glycan abbreviations see (www.proglycan.com).

Figure 4.2 Mucin‐type

O

‐glycan processing pathway and

O

‐glycan‐engineering approaches in plants. In mammals, mucin‐type

O

‐glycan formation is typically initiated in the

cis

to medial Golgi by polypeptide GalNAc‐transferases (GalNAc‐Ts). Sialylated core 1 formation requires the Golgi‐resident galactosyltransferases C1GalT1 (and the chaperone Cosmc) and sialyltransferases (STs). In plants, proline residues next to

O

‐glycosylation sites are modified in the ER or Golgi by prolyl 4‐hydroxylases (P4H). The shown sequence motif is present in different recombinant proteins that have been expressed in plants including mucin 1, IgA1, and EPO. The resulting hydroxyproline (Hyp) residue is typically further elongated, for example, by arabinosyltransferases (AraTs). Mucin‐type

O

‐glycan engineering approaches involve knockout of P4H;

in planta

expression of GalNAc‐Ts (e.g. T2/T4),

Drosophila melanogaster

C1GalT1 (DsC1GalT1), the enzymes for CMP‐sialic acid biosynthesis, the Golgi transporter, and the mammalian STs.

Chapter 05

Figure 5.1 Diverse organelles as plant bioreactors. In a plant‐based bioreactor system, desired proteins are expressed and transported to the final destination for storage, including various intracellular organelles and extracellular spaces. The protein trafficking relies on distinct vesicular pathways, with proper modifications in the process. In plant bioreactors, five targeting mechanisms can be used to deliver the synthesized proteins to reach the specific storage compartments. Plant‐specific glycosylation is undesirable for many recombinant proteins; this can be avoided via Golgi‐bypassing pathways. ER, endoplasmic reticulum; PSV, protein storage vacuole; TGN, trans‐Golgi network; PVC, prevacuolar compartment; MVB, multivesicular body.

Figure 5.2 Visualization of various intracellular organelles as bioreactors using transmission electron microscopy. (a) A 5‐day‐old dark‐grown cress (

Lepidium sativum

) leaf cell. (b) Arabidopsis mature embryo. (c) Oil body of a 5‐day‐old dark‐grown cress leaf cell. The most abundant gray spherical particles are oil bodies. (d) Chloroplast of a 5‐day‐old dark‐grown cress leaf cell.

Figure 5.3 Stable accumulation of recombinant proteins GFP‐CT24 in protein storage vacuoles (PSVs) of transgenic Arabidopsis seeds.

Figure 5.4 Membrane anchors for PSV targeting in seed bioreactors. Various unique sequences from plant proteins can be used as membrane anchors to target the recombinant proteins to specific PSV subcompartments for accumulation in seed bioreactors. NT, N terminus; TMD, trans‐membrane domain; CT, cytoplasmic tail.

Chapter 06

Figure 6.1 Co‐expression of the ELP‐, HFBI‐, and Zera‐fused fluorescent proteins. GFP‐ELP (a), GFP‐HFBI (b), RFP‐HFBI (c) and Zera‐DsRed (d) induce PB formation when expressed alone. Upon co‐expression of GFP‐ELP and RFP‐HFBI, both proteins co‐localize to the same PBs (e–g). When GFP‐ELP and Zera‐DsRed are co‐expressed, separate PBs form (h–j) similar to co‐expression of GFP‐HFBI and Zera DsRed (k–m). All images were acquired in sequential mode. Bar, 10 µm.

Chapter 07

Figure 7.1 Downstream processing diagram with unit operations for recombinant protein purification from leaf‐based, seed‐based, and bioreactor‐based systems.

Figure 7.2 Sugarcane juice (left) and sugarcane extract (right).

Chapter 08

Figure 8.1 Typical N‐glycans found on mammalian glycoproteins versus plant glycoproteins highlighting differences. See text for details. Red boxes indicate mammalian‐specific N‐glycan modifications; green box indicates examples of plant specific N‐glycans. The N‐glycans of mammalian glycoproteins including those of individual mammalian lysosomal hydrolases (e.g. α‐

L

‐iduronidase, β‐glucuronidase, acid α‐glucosidase) are typically a mixture of high‐mannose, M6P‐terminated, and “matured” (i.e. complex) N‐glycans. Plant cells do not possess the enzymatic machinery required for mannose‐6‐phosphate elaboration onto high‐mannose N‐glycans (boxes 4 and 5). Not all trimming reactions and modifications are shown. Abbreviations: α‐GSC: α‐glucosidases I and II; α‐Man: Golgi α1,2‐mannosidase I.

Figure 8.2 Lysosomal enzyme trafficking in mammalian cells and ERT that exploits receptor‐mediated uptake at cell surface. During synthesis on the rough ER, the lysosomal enzyme is translocated into the ER lumen where it undergoes N‐glycosylation. As the lysosomal enzyme transits through the ER lumen, its high‐mannose N‐glycans are trimmed, such that upon leaving this compartment, the typical N‐glycan structure(s) on the glycoprotein is Man

8‐9

GlcNAc

2

. If the lysosomal enzyme passes ER quality control, it is trafficked via vesicles to the Golgi complex where accessible N‐glycans are further trimmed and processed. M6P‐tags are added to select mannose residues of high mannose N‐glycans via a two‐step enzymatic process involving GlcNAc‐phosphotransferase (PTase) of the

cis

‐Golgi and the uncovering enzyme (UCE) of the

trans

‐Golgi network (see text for details). (Other accessible N‐glycans on the lysosomal hydrolase may be “matured” into complex N‐glycans). The majority of the M6P‐tagged lysosomal enzymes bind to M6P receptors (M6PR) within the

trans

‐Golgi network (TGN), a process which mediates the intracellular trafficking of lysosomal proteins from the TGN to the lysosome. Saturation of M6P receptors that mediate this intracellular lysosomal trafficking pathway can result in inappropriate secretion of a proportion of lysosomal enzymes. Yet some of the same receptors – e.g. M6PRs – cycle out to the cell surface as they also participate in endocytosis. The process of ERT largely exploits endogenous “salvage” (uptake) pathways of human cells that are mediated by these cell‐surface endocytic receptors. “Retrieval” or sequestration of any extracellular (e.g. recombinant) lysosomal enzyme is thus effected, as is the subsequent intracellular routing of recombinant enzyme to the lysosome, a process that is able to partially restore the enzyme deficiency. In this way ERT partially alleviates some of the pathological symptoms and processes (e.g. substrate storage) that underlie LSDs.

Figure 8.3 Conformation, localization, and post‐translational processing of the M6P‐elaborating enzymes (upper panel: phosphotransferase and lower panel: uncovering enzyme) of mammalian cells in situ (Table 8.2).

Chapter 09

Figure 9.1 Structure and glycosylation status of IgG1, IgM, and IgA1. Numbering indicates glycosylation sites; light gray dots: oligomannosidic structures; dark gray dots: complex N‐glycans terminating mostly in galactose and sialic acid, respectively; dark area with an asterisk (IgA1): sialylated O‐glycans in the hinge region. Some antibodies are tyrosine‐sulfated in the Fab (CDR3) region (SO

4

). Polymeric form of IgM and IgA1 is indicated next to the respective Y‐shaped homodimer. The Fc N‐glycan conserved across Ab classes is underlined. J, joining chain.

Figure 9.2 IgG1 Fc‐glycosylation. (A): Major glycoforms of human serum IgG. (B)

In planta

Fc‐glyco‐engineering. IgG N‐glycans (1) in wild‐type plants: GnGnXF

3

; (1a) using the GlycoDelete approach; (2) in ∆XT/FT

3

plants (RNAi downregulated XylT and FucT genes): GnGn (common eukaryotic core structure); (2a) using transgenic plants expressing GalT (AA structures); (3) in ∆XT/FT

3

 + FT

6

 : GnGnF

6

; (4) ∆XT/FT

3

 + FT

6

 + GnTIII : GnGnbiF

6

; (5) in ∆XT/FT

3

 + FT

6

+ GnTIV : GnGnGn F

6

; (6) in ∆XT/FT

3

 + FT

6

+ GalT : AAF

6

; (7) in ∆XT/FT

3

along with six mammalian genes of the mammalian sialic acid pathway: NaNaF

6

. FT

6

, α1,6‐fucosyltransferase; GalT, β1,4‐galactosyltransferase; ST, α2,6‐sialyltransferase; GnTIII, IV, N‐acetylglucosaminyltransferase III, IV. Glycan abbreviations according to proglycan.com.

Chapter 10

Figure 10.1 Chimeric HBcAg VLPs displaying Domain III of the envelope protein of Zika virus. HBcAg‐DIII cVLPs were purified from

N. benthamiana

leaves infiltrated with

Agrobacterium

carrying the HBcAg‐ZIKV DIII fusion construct. Purified HBcAg‐DIII cVLPs were stained with 0.2% aqueous uranyl acetate, and examined by transmission electron microscopy.

Chapter 11

Figure 11.1 The SDS‐PAGE of crude extracts from transgenic rice seeds. M: molecular mass; Lane 1, a transgenic rice line 4‐114‐7; Lanes 2–6 transgenic rice line 4‐114‐7‐9‐9‐37‐23.

Figure 11.2 Diagram of peptide fingerprinting of OsrHSA (blue) versus pHSA (red).

Figure 11.3 CD spectra of pHSA (blue curve) and OsrHSA (red curve).

Figure 11.4 Crystal structure of OsrHSA (PDB ID code 3SQJ).(A) Overall structure of OsrHSA. Bound mysritic acid molecules are depicted in a sphere representation. Subdomains IA, IB, IIA, IIB, IIIA, and IIIB are colored yellow, blue, orange, green, red, and magenta, respectively. (B) Superposition of molecule of OsrHSA (green) and HSA from PDB files with codes 2I2Z (blue) and 1BJ5 (red); rmsd (2I2Z) = 0.67 Å, rmsd (1BJ5) = 0.69 Å. (C) Disulfide profile of OsrHSA with disulfides shown as red sticks, each disulfide from domain I to III are labeled, cysteines involving in disulfides formation are (1) C53–C62; (2) C75–C91; (3) C90–C101; (4) C124–C169; (5) C168–C177; (6) C200–C246; (7) C245–C253; (8) C265–C279; (9) C278–C289; (10) C316–C361; (11) C360–C369; (12) C392–C438; (13) C437–C448; (14) C461 –C477; (15) C476–C487; (16) C514–C559; and (17) C558–C567. (D) Comparison of location of bound myristic acids (light gray) in OsrHSA (green) and those (dark gray) in HSA from PBD with codes 1E7G (red), rmsd = 0.72 Å. (E) Drug‐binding site I in OsrHSA. (F) Drug‐binding site II in OsrHSA. Myristic acids bound near a drug site are presented as spheres.

Figure 11.5 Image of SDS‐PAGE of the extraction condition optimization with different pH and extraction times.

Figure 11.6 Effects of salt concentrations, pH, temperatures, and extraction time for OsrHSA extraction. (A) Extraction effects of different temperatures and times for OsrHSA extraction. (B) Image of SDS‐PAGE from A. (C) Extraction effects of different salt concentrations and pH for OsrHSA extraction. (D) Image of SDS‐PAGE from C.

Figure 11.7 The image of SDS‐PAGE of the first chromatography step for enriching and purifying OsrHSA from crude extracts. M: molecular mass; Ld, loading sample; Ft: flow through fraction; Wh, washing fraction; Elu, eluent fraction; CIP, cleaning in place fraction.

Figure 11.8 SDS‐PAGE of the second chromatography step to purify OsrHSA from the first purification step. (A) Sepharose Q Fast Flow. (B) Capto adhere. M, molecular mass; Ld, loading sample; Ft, flow through fraction; Elu, elution fraction; CIP, cleaning‐in‐place fraction.

Figure 11.9 SDS‐PAGE of the third purification step for polishing OsrHSA by hydrophobic chromatography. Lanes 1–3 are loading sample, flow through fraction, and elution fraction from Phenyl Sepharose High Performance, respectively. Lanes 5–7 are loading sample, flow through fraction, and elution fraction from Phenyl Sepharose Fast Flow, respectively. Lanes 4 and 8 are the molecular mass standards.

Figure 11.10 A process flow diagram of the purification of OsrHSA from transgenic rice seeds.

Figure 11.11 Purity analysis with C4 reverse‐phase HPLC (A) and silver staining of SDS‐PAGE (B) characterization of purified OsrHSA from large‐scale production of lots. The purities of OsrHSA from different batches are: 1013 (99.09%), 1020 (99.42%), 1022 (99.60%), 1025 (99.45%), 1027 (99.59%), 1031 (99.55%), and 110 (99.09%). Purity was calculated by size‐exclusion HPLC.

Figure 11.12 Manufacturing of OsrHSA with GMP compliance.

Figure 11.13 Purity of large‐scale manufacturing of OsrHSA. (A) Purity of OsrHSA by non‐reducing SDS‐PAGE. (B) Purity of OsrHSA by SEC‐HPLC.

Figure 11.14 Immunodiffusion of OsrHSA versus pHSA.

Figure 11.15 Changes of total antibody in blood triggered by OsrHSA or pHSA. (A) Changes of total IgA and IgM. (B) Changes of total IgE and IgG.

Figure 11.16 Passive cutaneous anaphylaxis (PCA) assay in response to OsrHSA. Black circles indicate reaction with Evan’s blue.

Figure 11.17 Flow chart of preparation of HCPs from rice crude extracts and developing ELISA assay for residual HCPs assay.

Figure 11.18 The specificity of anti‐HCPs sera from the HCP preparation from processing steps. SDS‐PAGE (left) and Western blot (right) analysis using anti‐HCPs sera. Lane 1: crude extracts; lanes 2 and 3, the loading and the elution fractions from cation chromatography, respectively; lane 4, acidic precipitation; lanes 5 and 6, the loading and the elution fractions from anion chromatography, respectively; lanes 7 and 8, the loading and flow through fractions from phenyl hydrophobic chromatography, respectively; lane 9, after the sample concentration; M, molecular mass standard.

Figure 11.19 Pharmacokinetics of OsrHSA in cynomolgus monkey.(A) Pharmacokinetic of OsrHSA with different doses of 0.17 g.kg

−1

125

I ‐ OsrHSA. (B) Comparison of pharmacokinetic between OsrHSA and pHSA.

Figure 11.20 Therapeutic efficacy of OsrHSA on ascites in liver cirrhosis rats. (A) Decrease in abdominal circumference. (B) Increase in urinary volume. (C) The albumin content in the plasma of differently treated groups. (D) Urinary protein content seen with different treatments. (E) Changes in osmotic pressure of plasma after treatment with OsrHSA or pHSA. Bars in white, gray, and dark gray represent treatment with saline, OsrHSA, and pHSA, respectively. *P < 0.05, **P < 0.01 versus saline group. (F) Correlation of abdominal circumference change and urine volume change. N is the number of rats with each point representing a change from pre‐treatments. The black squares, red circles, and blue triangles represent data collected from treatments with OsrHSA at dosages of 0.25, 0.5, and 1.0 g/kg, respectively.

Chapter 12

Figure 12.1 Plant biotechnology can be used across a spectrum of resolutions that affect a single person (iIND) to manufacture a drug for a rare disease, up to many billions of people to resolve polluting manufacturing or environmental clean‐up.

Chapter 14

Figure 14.1 Examples of plant glandular trichomes. (A) Peltate trichome of peppermint (

Mentha x piperita

); view from above (top) and sectional view from the side (bottom). (B) Biseriate trichome from

Artemisia annua

. (C) Type VI glandular trichome from tomato (

Solanum lycopersicum

). (D) Tall capitate trichomes of wild tobacco (

Nicotiana sylvestris

). SC: subcuticular storage cavity where volatile metabolites are stored, GC: glandular cells (colored in gray in all trichome types represented), BC: basal cell, IC: intermediate cell, St.C: stalk cell.

Figure 14.2 Strategy for metabolic engineering of glandular trichomes. Endogenous competing pathways can first be downregulated or knocked‐out using gene silencing or genome editing technologies (left). Trichome‐specific promoters will ensure expression of transgenes restricted to the glandular cells (middle). Finally, the expression of multiple genes of the engineered pathway together with transporters is achieved with the STAPs activated by a designer TALE, itself under the control of a trichome specific promoter.

Chapter 15

Figure 15.1 Classification of terpenoids based on the building blocks and precursor‐providing pathways of MVA and MEP. HMG‐CoA, 3‐hydroxyl‐3‐methyl‐glutaryl‐CoA; mevalonate‐5‐P, mevalonate‐5‐phosphate; mevalonate‐PP, mevalonate pyrophosphate; DOXP, 1‐deoxy‐

D

‐xylulose 5‐phosphate; MEP, 2‐

C

‐methyl‐

D

‐erythritol 4‐phosphate; CDP ME, 4‐(cytidine 5'‐diphospho)‐2‐

C

‐methyl‐

D

‐erythritol; CDP MEP, 2‐phospho‐4‐(cytidine 5'‐diphospho)‐2‐

C

‐methyl‐

D

‐erythritol; MEcPP, 2‐

C

‐methyl‐

D

‐erythritol 2,4‐cyclodiphosphate; HMBPP, 4‐hydroxy‐3‐methyl‐but‐2‐enyl‐diphosphate.

Figure 15.2 Biosynthetic pathway of artemisinin. GPPS, geranyl diphosphate synthase; FPPS, farnesyl pyrophosphate synthase; ADS, amorphadiene synthase; CYP71AV1, cytochrome P450 enzyme from

A. annua

; DBR2, artemisinic aldehyde Δ11(13) double bond reductase from

A. annua

; ALDH1, aldehyde dehydrogenase 1 (Zhang, Wang, and Zhan, 2016).

Figure 15.3 Chemical structures of some oxygen‐free and oxygenated carotenoids.

Figure 15.4 Schematic overview of biosynthetic pathways leading to various plant polyketides. TAL, tyrosine ammonia lyase; PAL, phenylalanine ammonia lyase; C4H, cinnamate‐4‐hydroxylase; 4CL, 4‐coumaroyl‐CoA ligase; CHS, chalcone synthase; CHI, chalcone isomerase; STS, stilbene synthase; CUS, curcuminoid synthase.

Figure 15.5 Some of the medical applications of various alkaloids and their chemical structures. (a) vinblastine; (b) berberine; (c) quinine; (d) tubocurarine; (e) morphine.

Chapter 16

Figure 16.1 Schematic illustration of the workflow for a strategy to screen inhibitors toward EGFR from complex natural extracts.

Figure 16.2 Identification of the phosphorylated product pF‐EGFR by analysis with HPLC‐MS/MS. The following conditions were applied: reversed‐phase column (Agilent ZORBAX Eclipse XDB‐C18, 2.1 mm × 150 mm, 3.5 µm, 80 Å); solvent A, water (0.1% (v/v) HCOOH), solvent B, ACN (0.1 (v/v) HCOOH). Gradient: 10% B to 50% B over 15 min, 50% to 100% over 5 min; flow rate, 0.4 mL/min; the injection volume, 5 μL. (a) Fluorescence chromatogram, the unit of ordinate is fluorescence intensity; (b) base peak chromatogram; (c) MS spectra of F‐EGFR and (d) MS spectra of pF‐EGFR.

Figure 16.3 Typical electropherograms demonstrating identification and separation of pF‐EGFR from F‐EGFR and the internal standard. The following conditions were applied: fused silica capillary, 50 µm I.D. × 31.0 cm (20.5 cm to detection window); running buffer, 200 mM boric acid buffer (pH = 9.0); samples were injected by a pressure of 1379 Pa for 3s; applied voltage, 15 kV; (a) presence of ATP in the reaction solution; (b) absence of ATP in the reaction solution. Peaks: 1 = F‐EGFR, 2 = the internal standard, 3 = pF‐EGFR.

Figure 16.4 Dependence of production of pF‐EGFR on EGFR concentration and the incubation time. The following conditions were applied: EGFR concentrations, 10 µg/mL and 6 µg/mL; F‐EGFR concentration, 10 μM; incubation time: 0 to 60 min all other electrophoretic conditions are the same as in Figure 16.3.

Figure 16.5 The Lineweaver‐Burk plots of EGFR. (a) ATP concentration was fixed at 1 mM, and the F‐EGFR concentrations varied from 2.5 μM to 25 μM. (b) F‐EGFR concentration was fixed at 20 μM, and the ATP concentrations varied from 0.01 mM to 0.1 mM.

Figure 16.6 Inhibition plot of OSI‐744 and ZD 1839. The concentrations of OSI‐744 and ZD 1839 in the reaction solution varied from 10

−11

M to 10

−6

M.

Figure 16.7 Electropherograms illustrating screening of EGFR inhibitors from natural product extracts. Electropherogram traces: (a) negative control; (b) positive control – 100 nM OSI‐744 in reaction buffer; (c) the natural extract of

Lycopus lucidus

(0.5 mg/mL in the reaction buffer). Peaks: 1. F‐EGFR; 2. internal standard; 3. pF‐EGFR.

Figure 16.8 Chromatograms and mass spectra for HPLC‐MS/MS analysis of the extract of

Lycopus lucidus

. The UV (a) and base peak (b) chromatograms for separation of the extract; (c) MS

2

mass spectra of quercetin; (d) MS

2

mass spectra of rutin. Conditions: Agilent XDB‐C18 reversed‐phase column (4.6 mm × 250 mm, 5 µm, 80 Å). Solvent A, formic acid aqueous solution 0.1% (v/v); solvent B, acetonitrile containing 0.1% (v/v) formic acid. Flow rate, 1 mL/min; gradient elution, 10% to 20% B over 5 min, 20% to 40% B over 30 min, 40% to 100% B over 5 min. The UV detection wavelength, 254 nm. Primary peak: 1 = protocatechuic acid; 2 = caffeic acid; 3 = rutin; 4 = chrysoeriol‐7‐O‐β‐D‐glucopyranoside; 5 = rosmarinic acid; 6 = luteoloside; 7 = ursolic acid; 8 = chrysoeriol; 9 = luteolin; 10 = quercetin; 11 = betulinic acid. The active constituents are marked with asterisks.

Figure 16.9 Inhibition plots for quercetin (a) and rutin (b). For the preparation of the inhibition plot, the concentrations of quercetin varied from 10

−9

 M to 10

−4

 M, and the concentrations of rutin varied from 10

−8

 M to 10

−3

 M. Other conditions were as in Figure 16.3.

Chapter 17

Figure 17.1 The sequence of steps associated with the technology in which plant cells are transformed and then mutants are selected for the required pharmacological activity. In the present case, the objective is to generate increased biosynthesis of metabolites with inhibitory activity toward the target protein. When a line of transgenic plant cells has been created that stably expresses the functional target protein a mutant population of these transgenic cells is created. This mutant population is then selected under conditions in which the desired inhibitory effect on the target protein confers a survival advantage. For example, if the target protein in this example is a human enzyme the aim would be to select plant cells in the presence of a substrate that is converted to a cytotoxic product by the target enzyme. The population that survives should then be “enriched” in mutants that overproduce metabolites that inhibit the target protein. Conversely, if the objective is to find metabolites that activate the target protein, the transgenic mutants would be exposed to a cytotoxic substrate that is inactivated by activity of the enzyme.

Figure 17.2 Chemical structure of lobinaline. Shown as described by Manske (1938). Lobinaline was the first binitrogenous alkaloid described, and it is a complex decahydroquinoline with five chiral centers around the central ring. The ring structure has been synthesized chemically by Robison

et al

. (1966) in the all‐trans conformation. However, it is not yet known whether this conformation has the pharmacological activity possessed by the natural alkaloid.

Figure 17.3 Sequence of steps and plant cell transformations required for target‐directed biosynthesis toward metabolites that inhibit the human dopamine transporter (hDAT). First a transgenic line of plant cells stably expressing the functional hDAT is created. A mutant population of these cells containing random gain of function mutations is then produced and these mutants are selected for their ability to survive in the presence of a toxin that is a substrate for the hDAT; as such, the transgenic hDAT cells will therefore contain the accumulated metabolite. Under these conditions, the surviving transgenic population should be enriched in mutants that overproduce metabolites that inhibit the hDAT target. Many other mechanisms for toxin resistance are also possible; for example, mutants may be created in which the intracellular mechanism of toxicity is inhibited. Pharmacological screening of culture extracts for inhibitory activity at the DAT can exclude these “false positives” from the toxin‐resistant population. However, even these “negative” cultures may have value as sources of novel biosynthetic lead compounds (see Section 17.12).

Figure 17.4 Schematic of the human dopaminergic nerve terminal on the left and the transgenic plant cell on the right. In the human nerve terminal, activity of the hDAT leads to intracellular accumulation of neurotoxins, including MPP+ (as shown in the diagram), that cause neurodegeneration via mitochondrial damage and free radical production (reactive oxygen species (ROS)). This is commonly used as a model for the neurodegenerative changes that occur in Parkinson’s disease. In the plant cell, expression of the functional hDAT makes the plant cell susceptible to the toxicity caused by MPP+ (which closely resembles the phytotoxic herbicide, methyl viologen). The toxicity of MPP+ in the human and the plant cell is probably via a closely similar mechanism. Transgenic (

hDAT

) plant cells that survive MPP+ for whatever reason may therefore provide clues as to therapeutic approaches to dopaminergic neurodegeneration in addition to being a source of metabolites that inhibit the hDAT.

Figure 17.5 Generation of a secondary transgenic (hDAT) mutant under selection in 100 μM MPP+. Photograph shows a dish containing ~20 primary transgenic (hDAT) hairy roots of

L. cardinalis

that have all been infected with

A. rhizogenes

carrying the ATM vector. Under normal culture conditions this “hairy root to hairy root” transformation would give rise to about 20 secondary hairy roots from each primary hairy root. However, these primary hairy roots were immediately transferred to medium containing 100 μM MPP+ (which is lethal to all primary transgenic (hDAT) hairy roots). The photograph shows that indeed all the primary hairy roots have died, but there is a single secondary hairy root developing from a now dead primary hairy root in the center of the dish. This is one of the 120 MPP + ‐resistant mutant (

hDAT

) hairy roots that were selected for survival in this way.

Figure 17.6 Scattergram of DAT inhibitory activity in extracts from individual hairy roots in each population of

L. cardinalis

hairy roots. The scattergrams show the levels of DAT inhibitory activity ([3H]dopamine uptake into rat striatal synaptosomes) obtained in extracts from every individual culture in these hairy root populations (n = 68–109). The DAT inhibition is expressed as “lobinaline equivalents” based on extrapolation from a concentration response curve for purified lobinaline. Blue circles (extreme left) represent wild‐type cultures that were transformed to primary hairy roots by

A. rhizogenes

lacking the cDNA of the hDAT (i.e. they are DAT(−)). The next population (red circles) represents the transgenic (

hDAT

) primary hairy roots (DAT+) with no mutagenesis. The next population (“ATM” – green circles) represent secondary transgenic (hDAT) hairy roots that were subjected to mutagenesis by

A. rhizogenes

carrying the ATM vector, but that were not selected in MPP+. The means of these three populations do not differ significantly and there is also little difference in the distribution around the mean. The final population “RHR” represents the “resistant hairy roots” that were exposed to 100 μM MPP+. These are secondary transgenic (hDAT) cultures that developed under selection in the toxin after exposure of primary transgenic (hDAT) hairy roots to

A. rhizogenes

carrying the ATM vector. The mean DAT inhibition is significantly higher than that of any other population and the distribution is clearly different (population analysis indicates that it is logarithmic). Extracts from 11 individuals in this population had such high levels of activity that they could not be accommodated on this scale and have not been included in the statistical analysis (see Section 17.11).

Figure 17.7 Scattergram of lobinaline concentration in extracts from individual hairy roots in each population. The figure shows the concentration of lobinaline (measured and identified by GC/MS) in extracts from every hairy root in the same populations of hairy roots shown in Figure 17.2. Values are all in µg/ml (as for lobinaline equivalents as in Figure 17.6) but are not strictly comparable because DAT inhibition was measured in aqueous buffer after a methanol extract of each culture had been dried and solubilized in dimethyl sulfoxide (DMSO), whereas lobinaline content was measured directly in the methanol extract. The data show no difference between the DAT− and DAT+ groups, indicating that the expression of the hDAT gene does not alter lobinaline content. However, the ATM and RHR groups have a significantly higher mean than the other groups, indicating that the exposure to

A. rhizogenes

to create secondary hairy roots has increased the biosynthesis of this alkaloid. Extracts from the population of secondary hairy roots that were generated under selection in 100 μM MPP+ contained about 2x the number of lobinaline overproducers in the “RHR” population as compared to the “ATM” population (see Section 17.11). However, when comparing the DAT inhibition with lobinaline content in the MPP + ‐resistant population it is clear that the distributions differ, and that there are probably many cultures in which very high levels of DAT inhibition cannot be explained by lobinaline content alone (see Section 17.11).

Figure 17.8 A single lobinaline‐overproducing mutant hairy root growing in liquid culture. Photograph shows a transgenic (

hDAT

) MPP + ‐resistant hairy root that had been subcultured from solid medium to liquid medium. This hairy root has a lobinaline content about 20x that which is found in wild‐type cultures. These cultures of

L. cardinalis

grow very rapidly under these conditions and could easily be developed into production systems for lobinaline if this alkaloid ever becomes of commercial value. Similar cultures of other species could be used in the production of very high value plant alkaloids such as the Vinca and Taxus alkaloids used in chemotherapy (see Section 17.10).

Figure 17.9 Shows the principle underlying recombinant expression of human nuclear receptors in plants as a “gene switch” strategy. Because human nuclear receptors (including the estrogen receptor (ER)) are designed to drive gene expression they can readily be adapted to be used as “gene switches” in plants. Here the objective is to increase the biosynthesis of metabolites that activate the beta subtype of ER and so the plant cell is transformed with a construct which will express the ERbeta protein as well as the estrogen responsive element (ERE) and a plant promoter linked to a foreign gene that will cause cell survival when expressed by the plant cell. In this example a bacterial gene that causes kanamycin resistance is used. Now mutants that overproduce phytoestrogens capable of activating ERbeta will cause this receptor, via interaction with the ERE, to increase expression of the kanamycin resistance gene. A population of transgenic (

ERbeta

) mutants selected for survival in kanamycin should therefore result in a subpopulation in which there is increased biosynthesis of ERbeta ligands. This therefore applies target‐directed biosynthesis to increasing ligands for a specific subtype of human nuclear receptor.

Figure 17.10 Target‐directed inhibition of biosynthesis applied to human estrogen receptor (ER) alpha. The diagram shows how the same technology illustrated in Figure 17.9 can be used “in reverse” to inhibit the biosynthesis of plant metabolites that have “unwanted” or toxic effects. Plant extracts containing phytoestrogens are commonly used as “estrogen supplements” to reduce post‐menopausal symptoms. However, agonist activity of these plant metabolites at ERalpha is of some concern because, post‐menopause, this ER subtype stimulates growth and division of hormone responsive breast cancer cells. In order to increase the biosynthesis of metabolites with “desirable” ERbeta activity, the approach shown in Figure 17.9 can be used, but this does not reduce the biosynthesis of non‐selective phytoestrogens that activate ERalpha as well as ERbeta. Figure 17.10 shows how this reduction in ERalpha ligands can be achieved. A construct containing the gene for ERalpha together with the ERE, a promoter, and a foreign gene that can cause plant cell death is introduced into the plant cell. In this example the foreign “death gene” is for human D‐amino acid oxidase (

hDAO1

) which, when expressed, converts D‐isoleucine to a toxic product (Erikson, Hertzberg, and Näsholm, 2004). Mutants that overproduce ligands for ERalpha should now die when exposed to D‐isoleucine, whereas mutants that “underproduce” such metabolites should survive. A combination of these approaches in cells expressing the ERbeta and the ERalpha constructs is predicted to lead to a selective overproduction of metabolites with ERbeta agonist activity.

Chapter 18

Figure 18.1 Schematic diagram showing upstream determinants (genes and molecular pathology) and downstream effects (clinical phenotypes) for the main neurodegenerative disorders. Causative genetic mutations are shown by solid arrows and genetic risk factors by dotted arrows.

Gene abbreviations:

HTT, huntingtin; GBA, beta‐glucocerebrosidase; APOE, apolipoprotein E; TOMM40, translocase of outer mitochondrial membrane 40; TREM2, triggering receptor expressed on myeloid cells 2; APP, amyloid precursor protein; PS1, presenilin 1; PS2, presenilin 2; MAPT, microtubule‐associated protein tau; TARDBP, TAR DNA‐binding protein 43; VCP, valosin‐containing protein; GRN, progranulin;

C9ORF72

, chromosome 9 open reading frame 72; FUS, RNA‐binding protein FUS; SOD1, superoxide dismutase 1.

Clinical phenotype abbreviations:

DLB, dementia with Lewy bodies; PD, Parkinson disease; PSP, progressive supranuclear palsy; LOAD, late‐onset Alzheimer's disease (onset, >65 years); EOAD, early‐age‐of‐ons

et

Alzheimer's disease (onset, <65 years); PCA, posterior cortical atrophy; PPA, primary progressive aphasia; bvFTD, behavioral variant of frontotemporal degeneration; ALS, Amyotrophic lateral sclerosis.

Figure 18.2 Overexpression of AtPARK13, a serine protease, confers thermotolerance in Arabidopsis. (A)

AtPARK13

overexpressed in WT (Col) Arabidopsis using the CaMV35S constitutive promoter (pBA002 vector backbone). Two independent transgenic lines show more than 4‐fold higher

AtPARK13

transcript levels as compared to the wild‐type plants when exposed to 21 °C and 37 °C for 5 hours. (B)

AtPARK13

conferred thermotolerance at 37 °C in

AtPARK13

‐overexpressing transgenic plants (pBA002/AtPARK13) as compared to transgenic plants expressing the empty vector (pBA002) as a control after 12 days of heat exposure. (C)

AtPARK13

conferred thermotolerance at 42 °C in two independent

AtPARK13

‐overexpressing transgenic lines (pBA002/AtPARK13) as compared to wild‐type Arabidopsis as a control after 24 hours of heat exposure. (D)

AtPARK13

overexpressed in WT (Col) Arabidopsis using the β‐estradiol‐inducible promoter (pER10 vector backbone). Two independent transgenic lines identified show more than 40‐ and 100‐fold higher AtPARK13 transcript levels after β‐estradiol induction as compared with the non‐induced lines (E)

AtPARK13

conferred thermotolerance at 42 °C in two independent

AtPARK13

‐overexpressing transgenic plants (pER10/AtPARK13) as compared to the pER10 empty vector control after 24 hours of heat exposure.

Figure 18.3 AtDJ‐1a deficiency results in cell‐death lesions, whereas elevated AtDJ‐1a levels protect Arabidopsis against oxidative stress. (A) Phenotypes of wild‐type (WT), mutant (Mut) and AtDJ1a‐YFP‐overexpressing (Ox) transgenic plants grown under elevated light conditions (280 mmole/m

2

/second). In aging plants, the Mut leaves exhibited multiple cell death lesions and increased anthocyanin accumulation (purple) as compared to WT leaves. Ox leaves exhibited no cell death lesions or anthocyanin accumulation. (B) Genetic analysis of homozygous plants (M1‐M3) by PCR using gene‐specific primers (F) and a T‐DNA‐specific left border primer (L) showing the amplification of the endogenous gene in WT and the T‐DNA insertion in the mutated lines. (C) Reverse transcriptase polymerase chain reaction to confirm lack of the

AtDJ‐1a

transcript in the knockout mutant and elevated

AtDJ‐1a

transcript levels in transgenic Arabidopsis overexpressing the

AtDJ1a‐YFP

transgene. (D) Western blot showing elevated AtDJ1a‐YFP protein levels in transgenic Arabidopsis overexpressing the

AtDJ1a‐YFP

transgene. (E) Phenotypic analysis of WT, mutant (Mut/N830498) and AtDJ‐1a overexpressing (Ox) transgenic plants in response to H

2

O

2

and paraquat (MV) treatment. Both H

2

O

2

and MV exposure induced multiple cell death lesions in mutant leaves compared to fewer lesions in WT plants. No lesions where observed in the Ox plants.

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Molecular Pharming

Applications, Challenges, and Emerging Areas

Editor, Allison R. Kermode

Department of Biological Sciences

Simon Fraser University

Associate Editor, Liwen Jiang

School of Life Sciences

The Chinese University of Hong Kong

This edition first published 2018© 2018 John Wiley & Sons, Inc.

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.

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List of Contributors

Naghmeh AbiriCollege of Life SciencesWuhan University, WuchangWuhan, China

Georgia O.F. Barros3 M Brazil, Sumaré, SP, Brazil

Indranil BasakDepartment of Biological SciencesSt. John’s University, New YorkNY, USA

Dustin BrownUniversity of Kentucky Department of Anatomy and NeurobiologyLexington, KY, USA

Johannes F. BuyelFraunhofer Institute for Molecular Biology and Applied Ecology IME,Aachen, Germany;Institute for Molecular BiotechnologyRWTH Aachen UniversityAachen, Germany

Alexandra CastilhoDepartment of Applied Genetics and Cell Biology, University of Natural Resources and Life SciencesVienna, Austria

Qiang ChenCenter for Immunotherapy, Vaccines, and VirotherapyBiodesign Institute at ASU and School of Life SciencesArizona State, UniversityTempe, AZ, USA

Carole L. CramerArkansas State University Biosciences InstituteState University,AR, USA; BioStrategiesLC, State University, AR, USA

Matthew DentCenter for ImmunotherapyVaccines and VirotherapyBiodesign Institute at ASU and School of Life SciencesArizona State UniversityTempe, AZ, USA

Chelsea DixonBiological and Agricultural Engineering Department, Kansas State UniversityManhattanKS, USA

Deane FalconeDepartment of Biology, University of Massachusetts‐Lowell, Lowell Massachusetts, USA

Li FengProvince Key Laboratory of Surface Engineering and RemanufacturingSchool of Chemical EngineeringXi’an University, Shannxi, China; State Key Laboratory of Bioorganic and Natural Products ChemistryCenter for Excellence in Molecular SynthesisShanghai Institute of Organic ChemistryChinese Academy of SciencesShanghaiChina

Ozkan FidanDepartment of Biological EngineeringUtah State UniversityLoganUT, USA

Gregory GerhardtUniversity of Kentucky Department of Anatomy and NeurobiologyLexington, KY, USA

Samir GunjanUniversity of Kentucky Department of PsychologyLexington, KY, USA

Zhibin GuoCenter of Engineering Research for Molecular Pharming, BiolakeWuhan, Hubei

Elizabeth E. HoodArkansas State University Biosciences Institute, State UniversityAR, USA and Infinite Enzymes LLC, State UniversityAR, USA

Penelope A.C. Hundleby(nee Sparrow) John Innes Centre, Norwich Research Park Norwich, UK

Liwen JiangState Key Laboratory of AgrobiotechnologyCentre for Cell and Developmental Biology, School of Life SciencesThe Chinese University of Hong KongShatin, New Territories, Hong KongChina; CUHK Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China

Chunsheng JinInstitutionen för Biomedicin, Göteborgs Universitet, Göteborg, Sweden

Jingwu KangState Key Laboratory of Bioorganic and Natural Products Chemistry, Center for Excellence in Molecular SynthesisShanghai Institute of Organic ChemistryChinese Academy of Sciences Shanghai, China

Allison R. KermodeDepartment of Biological Sciences, Simon Fraser UniversityBurnabyBC, Canada

John LittletonUniversity of Kentucky Department of Psychology, Lexington, KY, USA

Andreas LoosAridis Pharmaceuticals LLCSan Jose, CA, USA

Hugh MasonCenter for ImmunotherapyVaccines, and VirotherapyBiodesign Institute at ASU and School of Life Sciences, Arizona StateUniversity, Tempe, AZ, USA

Grant McNairDepartment of Biological SciencesSimon Fraser UniversityBurnabyBC, Canada

Rima MenassaAgriculture and Agri‐Food CanadaLondon Research and Development Centre, London, ONCanada

Simon G. MøllerDepartment of Biological SciencesSt. John’s University, New YorkNY, USANorwegian Center for Movement DisordersStavanger University HospitalStavanger, Norway

Jiquan OuCenter of Engineering Research for Molecular Pharming, Biolake Wuhan, Hubei

Katharina PaschingerDepartment für ChemieUniversität für Bodenkultur WienWien, Austria

Owen PierceDepartment für Chemie, Universität für Bodenkultur WienWien, Austria

Dennis T. RogersNaprogenix Inc.Lexington, KY, USA

Reza SaberianfarAgriculture and Agri‐Food Canada, London Research and Development Centre, LondonON, Canada

Markus SackInstitute for Molecular BiotechnologyRWTH Aachen University Aachen, Germany

Jatinder SambiNaprogenix Inc.Lexington, KY, USA

Tom SchreiberDepartment of Cell and Metabolic Biology, Leibniz‐Institute of Plant BiochemistryHalle (Saale), Germany

Jinbo ShenState Key Laboratory of Agrobiotechnology, Centre for Cell and Developmental Biology, School of Life SciencesThe Chinese University of Hong Kong, ShatinNew TerritoriesHong Kong, China

Bo ShiCenter of Engineering Research for Molecular PharmingBiolake, WuhanHubei

Jingni ShiCenter of Engineering Research for Molecular Pharming, BiolakeWuhan, Hubei

Holger SpiegelFraunhofer Institute for Molecular Biology and Applied Ecology IMEAachen, Germany

Herta SteinkellnerDepartment of Applied Genetics and Cell Biology, University of Natural Resources and Life SciencesVienna, Austria

Eva StögerDepartment of Applied Genetics and Cell Biology, University of Natural Resources and Life SciencesVienna, Austria

Richard StrasserDepartment of Applied Genetics and Cell Biology, University of Natural Resources and Life SciencesVienna, Austria

Alain TissierDepartment of Cell and Metabolic Biology, Leibniz‐Institute of Plant BiochemistryHalle (Saale), Germany

Richard M. TwymanTRM Ltd., YorkUK

Jorick VanbeselaereDepartment für ChemieUniversität für Bodenkultur WienWien, Austria

Xiangfeng WangState Key Laboratory of Agrobiotechnology, Centre for Cell and Developmental Biology School of Life SciencesThe Chinese University of Hong KongShatin, New TerritoriesHong Kong, China

Lisa R. WilkenBiological and Agricultural Engineering Department, Kansas State UniversityManhattan, KS, USA

Iain B.H. Wilson Department für ChemieUniversität für Bodenkultur WienWien, Austria

Susan L. WoodardNational Center for Therapeutics Manufacturing, The Texas A&M Engineering Experiment StationTX, USA

Daichang YangCollege of Life Sciences, Wuhan University, WuchangWuhan, China

Jixun ZhanDepartment of Biological EngineeringUtah State UniversityLogan, UT, USA

Preface