Chapter title |
Controlling AAV Tropism in the Nervous System with Natural and Engineered Capsids
|
---|---|
Chapter number | 10 |
Book title |
Gene Therapy for Neurological Disorders
|
Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3271-9_10 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3270-2, 978-1-4939-3271-9
|
Authors |
Michael J. Castle, Heikki T. Turunen, Luk H. Vandenberghe, John H. Wolfe, Castle, Michael J., Turunen, Heikki T., Vandenberghe, Luk H., Wolfe, John H. |
Abstract |
More than one hundred naturally occurring variants of adeno-associated virus (AAV) have been identified, and this library has been further expanded by an array of techniques for modification of the viral capsid. AAV capsid variants possess unique antigenic profiles and demonstrate distinct cellular tropisms driven by differences in receptor binding. AAV capsids can be chemically modified to alter tropism, can be produced as hybrid vectors that combine the properties of multiple serotypes, and can carry peptide insertions that introduce novel receptor-binding activity. Furthermore, directed evolution of shuffled genome libraries can identify engineered variants with unique properties, and rational modification of the viral capsid can alter tropism, reduce blockage by neutralizing antibodies, or enhance transduction efficiency. This large number of AAV variants and engineered capsids provides a varied toolkit for gene delivery to the CNS and retina, with specialized vectors available for many applications, but selecting a capsid variant from the array of available vectors can be difficult. This chapter describes the unique properties of a range of AAV variants and engineered capsids, and provides a guide for selecting the appropriate vector for specific applications in the CNS and retina. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Japan | 1 | 13% |
Unknown | 7 | 88% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 8 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 184 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 33 | 18% |
Researcher | 27 | 15% |
Student > Master | 22 | 12% |
Student > Bachelor | 20 | 11% |
Other | 9 | 5% |
Other | 22 | 12% |
Unknown | 51 | 28% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 45 | 24% |
Neuroscience | 33 | 18% |
Agricultural and Biological Sciences | 22 | 12% |
Medicine and Dentistry | 11 | 6% |
Engineering | 4 | 2% |
Other | 13 | 7% |
Unknown | 56 | 30% |