NGS data analysis improves the investigation of in vitro and in vivo selection processes

AptaIT has developed two complimentary software tools – AptaAnalyzer™ and COMPAS – to provide innovative solutions for next-generation sequencing (NGS) data analysis. Next-generation sequencing, sometimes called deep sequencing, is a powerful tool to streamline the discovery platforms of pharmaceutical companies and academic institutions. Millions of sequences provide an in depth picture of the processes how ligands or receptors (leads) are evolved in vitro or in vivo. Lead molecules can be antibodies, immune receptors, peptides, aptamers, or other novel biologics. Next-generation sequencing data analysis can address virtual any pheno-genotype linked selection procedure whether synthetic selections or natural immune responses.

NGS data analysis supports screening processes at three relevant stages:

Our sequencing data analysis platform enables:

• NGS data analysis for biopanning or SELEX experiments
• Immune receptor profiling by analysis of deep sequencing data
• Processing of the complete workflow: From sequencing data analysis to publication level results
• Archiving of sequencing data with database internal linkage to experimental data
• Individual solutions by our easy-to-use NGS data analysis software AptaAnalyzer™ or highly sophisticated and flexible analysis services

Sequencing data analysis for biopanning or SELEX experiments

We at AptaIT specifically designed our sequence analysis software to optimize existing selection platforms like phage display or SELEX. NGS data analysis of sequences derived from SELEX or biopanning experiments is an excellent way to bring light into the black box of in vitro selections. It supports quality control of combinatorial starting libraries, improved analysis of enriched libraries, optimization of identified leads, and improved patenting strategies based on profound sequencing data information.

Identification of protein ligands or aptamers by analyzing NGS data:

After the selection procedure, the sequences derived from individual experiments, e.g. successive selection rounds, are indexed and combined for digitalization via the analysis of next-generation sequencing data. Indexed dataset sequences are assigned to their respective original experiment. The defined selection cycles are analyzed or compared against each other. Where appropriate, it is possible to relate secondary structure prediction (aptamers) or experimental data to individual sequences to aid the identification of the best ligands and their subsequent optimization.

Immune repertoire profiling by analysis of deep sequencing data

Besides screening technologies, our software is applicable to virtually any selection process, in which geno- and phenotypes are linked. AptaIT has a special focus on providing bioinformatics solutions to enhance immune repertoire profiling by NGS data analysis. Next-generation sequencing is the method of choice to investigate the repertoires of T cells and B cells in an individual on the monoclonal level. The deep sequencing information provides a complete picture of types and frequencies of antigen receptors at a given point in time. The sequencing data analysis helps to structure these results, enables to identify prominent and very rare clones, or compares the status of the immune system before and after challenging events like infections, transplantations, or vaccinations.

NGS data analysis of immune repertoires:

NGS data analysis is therefore an invaluable research tool for the investigation of the immune system in animals and humans. It furthermore supports the development of antibodies, immune therapies, or vaccines and provides a new route for the identification of novel biomarkers.