Development of Analysis and Visualization Methods for Next-Generation Sequencing Phage Surface Display Data, Master thesis 2022

Efforts in the field of biomolecular probes and materials science have been accelerated by the application of phage surface display technology. A practical complement to this technology is next-generation sequencing. This combination provides deeper insight into biopanning rounds with impurity identification, display of sequence read content, visualization of phage library evolution, and methods for displaying binding motifs. To implement these approaches, a pipeline was developed to preprocess the next-generation sequencing data using Sequana and fastqjoin. The raw sequences are then extracted and the inserts of the pIII coat protein genes of the M13 phage are isolated. The inserts are translated and written into a frequency list. From this, a series of matrices are formed to detect enrichments of amino acid abundances per position in the library. Protein sequences are also clustered and written to additional matrices to create sequence logos for sequence motif discovery. The pipeline was used to analyze two data sets. In the first dataset, a customized, unamplified mini-library was created and tested for bias. No preservation of sequence motifs was detected. The second data set was used to test whether the sequence motifs QxQ and SxHS could be confirmed as conserved sequence motifs. However, this data set had serious qualitative problems and no meaningful results could be obtained. Overall, it can be concluded that the created pipeline provides good results for large data sets if
the quality is sufficient.