| Chapter title |
Generating and Purifying Fab Fragments from Human and Mouse IgG Using the Bacterial Enzymes IdeS, SpeB and Kgp.
|
|---|---|
| Chapter number | 21 |
| Book title |
Bacterial Pathogenesis
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-6673-8_21 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6671-4, 978-1-4939-6673-8
|
| Authors |
Jonathan Sjögren Ph.D., Linda Andersson M.Sc., Malin Mejàre Ph.D., Fredrik Olsson M.Sc., Jonathan Sjögren, Linda Andersson, Malin Mejàre, Fredrik Olsson |
| Editors |
Pontus Nordenfelt, Mattias Collin |
| Abstract |
Fab fragments are valuable research tools in various areas of science including applications in imaging, binding studies, removal of Fc-mediated effector functions, mass spectrometry, infection biology, and many others. The enzymatic tools for the generation of Fab fragments have been discovered through basic research within the field of molecular bacterial pathogenesis. Today, these enzymes are widely applied as research tools and in this chapter, we describe methodologies based on bacterial enzymes to generate Fab fragments from both human and mouse IgG. For all human IgG subclasses, the IdeS enzyme from Streptococcus pyogenes has been applied to generate F(ab')2 fragments that subsequently can be reduced under mild conditions to generate a homogenous pool of Fab' fragments. The enzyme Kgp from Porphyromonas gingivalis has been applied to generate intact Fab fragments from human IgG1 and the Fab fragments can be purified using a CH1-specific affinity resin. The SpeB protease, also from S. pyogenes, is able to digest mouse IgGs and has been applied to digest antibodies and Fab fragments can be purified on light chain affinity resins. In this chapter, we describe methodologies that can be used to obtain Fab fragments from human and mouse IgG using bacterial proteases. |
X Demographics
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| Unknown | 1 | 100% |
Demographic breakdown
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| Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 16 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 25% |
| Researcher | 3 | 19% |
| Student > Bachelor | 2 | 13% |
| Student > Ph. D. Student | 1 | 6% |
| Lecturer | 1 | 6% |
| Other | 2 | 13% |
| Unknown | 3 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 31% |
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| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 6% |
| Immunology and Microbiology | 1 | 6% |
| Agricultural and Biological Sciences | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 5 | 31% |