AAVolve: Concatenated long-read deep sequencing enables whole capsid tracking during shuffled AAV library selection

Suzanne Scott; Adrian Westhaus; Deborah Nazareth; Marti Cabanes-Creus; Renina Gale Navarro; Deborah Chandra; Erhua Zhu; Aravind Venkateswaran; Ian E. Alexander; Denis C. Bauer; Laurence O.W. Wilson; Leszek Lisowski

Molecular Therapy: Methods & Clinical Development (Dec 2024)

AAVolve: Concatenated long-read deep sequencing enables whole capsid tracking during shuffled AAV library selection

Suzanne Scott,
Adrian Westhaus,
Deborah Nazareth,
Marti Cabanes-Creus,
Renina Gale Navarro,
Deborah Chandra,
Erhua Zhu,
Aravind Venkateswaran,
Ian E. Alexander,
Denis C. Bauer,
Laurence O.W. Wilson,
Leszek Lisowski

Affiliations

Suzanne Scott: Translational Vectorology Research Unit, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW 2145, Australia; Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Westmead, NSW 2145, Australia
Adrian Westhaus: Translational Vectorology Research Unit, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW 2145, Australia
Deborah Nazareth: Translational Vectorology Research Unit, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW 2145, Australia
Marti Cabanes-Creus: Translational Vectorology Research Unit, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW 2145, Australia
Renina Gale Navarro: Translational Vectorology Research Unit, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW 2145, Australia
Deborah Chandra: Translational Vectorology Research Unit, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW 2145, Australia
Erhua Zhu: Gene Therapy Research Unit, Children’s Medical Research Institute and The Children’s Hospital at Westmead, Faculty of Medicine and Health, The University of Sydney, and Sydney Children’s Hospitals Network, Westmead, NSW 2145, Australia
Aravind Venkateswaran: Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Westmead, NSW 2145, Australia
Ian E. Alexander: Gene Therapy Research Unit, Children’s Medical Research Institute and The Children’s Hospital at Westmead, Faculty of Medicine and Health, The University of Sydney, and Sydney Children’s Hospitals Network, Westmead, NSW 2145, Australia; Discipline of Child and Adolescent Health, The University of Sydney, Sydney Medical School, Faculty of Medicine and Health, Westmead, NSW 2145, Australia
Denis C. Bauer: Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Westmead, NSW 2145, Australia; Department of Biomedical Sciences, Faculty of Medicine and Health Science, Macquarie University, Macquarie Park, NSW 2113, Australia; Applied BioSciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW 2113, Australia
Laurence O.W. Wilson: Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Westmead, NSW 2145, Australia; Applied BioSciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW 2113, Australia
Leszek Lisowski: Translational Vectorology Research Unit, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW 2145, Australia; Laboratory of Molecular Oncology and Innovative Therapies, Military Institute of Medicine – National Research Institute, 04-141 Warsaw, Poland; Corresponding author: Leszek Lisowski, Translational Vectorology Research Unit, Children’s Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW 2145, Australia.

Journal volume & issue: Vol. 32, no. 4
p. 101351

Abstract

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Gene therapies using recombinant adeno-associated virus (AAV) vectors have demonstrated considerable clinical success in the treatment of genetic disorders. Improved vectors with favorable tropism profiles, decreased immunogenicity, and enhanced manufacturability are poised to further improve the state of gene therapies. Such vectors can be identified through directed evolution, a process of subjecting a diverse capsid library to a selection pressure to identify individual variants with a desired trait. Currently, libraries that involve changes distributed throughout the AAV capsid coding region, such as DNA family shuffled libraries, are largely characterized using low-throughput Sanger sequencing of individual clones. However, improvements in long-read sequencing technologies have increased their applicability to capsid libraries and evaluation of the selection process. Here, we explore the application of Oxford Nanopore Technologies refined by a concatemeric consensus method for initial library characterization and monitoring selection of a shuffled AAV capsid library. Furthermore, we present AAVolve, a bioinformatic pipeline for processing long-read data from AAV-directed evolution experiments. Our approach allows high-throughput characterization of AAV capsids in a streamlined manner, facilitating deeper insights into library composition through multiple rounds of selection, and generalization through training of machine learning models.

Published in Molecular Therapy: Methods & Clinical Development

ISSN: 2329-0501 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Science: Biology (General): Genetics; Science: Biology (General): Cytology
Website: http://www.cell.com/molecular-therapy-family/methods/latest-content

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