- Introduction: Gene therapy holds great potential for treating a wide range of diseases, and adeno-associated virus (AAV) vectors have emerged as promising vehicles for delivering therapeutic genes. However, one of the challenges in AAV-mediated gene therapy is achieving efficient targeting of specific cell types and tissues. The objective of this Master thesis project is to develop a comprehensive bioinformatic pipeline that enables the identification of DNA barcodes associated with AAV vectors, thereby facilitating the evaluation of AAV variant efficiency and tropism in mammalian species.
- Background and Significance: The project builds upon previous studies in AAV vector design, which have shown that modifications to the viral capsid can alter AAV tropism. By introducing peptide insert modifications into the AAV capsid, the viral vectors can be engineered to target specific cell types and tissues. However, a systematic approach is needed to identify the most efficient AAV variants for different cell types, tissue types, and specific targets while avoiding off-target effects, particularly in non-target tissues such as the liver.
- Methodology: The project will utilize a combination of experimental and bioinformatic techniques to achieve its goals. The experimental part involves the use of diverse AAV libraries with peptide insert modifications, designed to enhance AAV tropism and enable specific targeting of neuronal and non-neuronal populations in the central nervous system (CNS) and other tissue and cell types. Tissue samples will be collected from mammalian species, ranging from rodents to non-human primates (NHPs), and subjected to various sequencing methods, including bulk sequencing of tissue samples, 10X single nuclei sequencing, and Parse Bio single nuclei sequencing.
- Pipeline Development: The bioinformatic pipeline will be developed to process and analyze the sequencing data generated from the experimental part of the project. The pipeline will comprise several key steps, including data preprocessing, quality control, read alignment, and variant calling. To accurately identify the DNA barcodes associated with AAV variants, custom scripts or software modules will be developed and integrated into the pipeline. The pipeline will leverage existing bioinformatics tools and algorithms, as well as employ computational methods for efficient barcode identification.
- Data Analysis and Interpretation: The identified DNA barcodes will undergo thorough data analysis and interpretation to assess AAV variant efficiency and tropism. Statistical analysis, visualization, and comparative studies will be performed to evaluate the performance of different AAV variants across various cell types and tissue types. The focus will be on identifying the most efficient AAV candidates for specific targets while minimizing off-target effects. Special attention will be given to avoiding non-specific tissue infection, particularly in the liver, as it is a common site for unwanted AAV vector delivery.
- Conclusion and Future Directions: The project will conclude with a comprehensive analysis of the results obtained from the bioinformatic pipeline. The findings will be summarized, highlighting the efficiency, accuracy, and scalability of the pipeline in identifying DNA barcodes associated with AAV vectors. The project’s conclusions will be discussed in the context of the broader field of gene therapy, and potential future directions for improvement and further research will be outlined. These may include refining the bioinformatics methods, incorporating advanced data integration techniques, and exploring additional validation strategies to enhance the accuracy and reliability of the pipeline.
Contact:
Marcus Davidsson, PhD, Marcus.Davidsson@raaven.se
COO , rAAVen Therapeutics, Lund, Sweden
www.raaven.se