A Computational Pipeline for the Extraction of Actionable Biological Information From NGS-Phage Display Experiments

Abstract

Phage Display is a powerful method for the identification of peptide binding to targets of variable complexities and tissues, from unique molecules to the internal surfaces of vessels of living organisms. Particularly for in vivo screenings, the resulting repertoires can be very complex and difficult to study with traditional approaches. Next Generation Sequencing (NGS) opened the possibility to acquire high resolution overviews of such repertoires and thus facilitates the identification of binders of interest. Additionally, the ever-increasing amount of available genome/proteome information became satisfactory regarding the identification of putative mimicked proteins, due to the large scale on which partial sequence homology is assessed. However, the subsequent production of massive data stresses the need for high-performance computational approaches in order to perform standardized and insightful molecular network analysis. Systems-level analysis is essential for efficient resolution of the underlying molecular complexity and the extraction of actionable interpretation, in terms of systemic biological processes and pathways that are systematically perturbed. In this work we introduce PepSimili, an integrated workflow tool, which performs mapping of massive peptide repertoires on whole proteomes and delivers a streamlined, systems-level biological interpretation. The tool employs modules for modeling and filtering of background noise due to random mappings and amplifies the biologically meaningful signal through coupling with BioInfoMiner, a systems interpretation tool that employs graph-theoretic methods for prioritization of systemic processes and corresponding driver genes. The current implementation exploits the Galaxy environment and is available online. A case study using public data is presented, with and without a control selection.

Comparative Evaluation of Reproducibility of Phage-Displayed Peptide Selections and NGS Data, through High-Fidelity Mapping of Massive Peptide Repertoires

“…Based on the provided NGS peptide repertoires, we performed an analysis by using the PepSimili algorithm [ 21 ]. The tool performs peptide-to-peptide mapping of massive peptide repertoires obtained by high-throughput sequencing of phage display libraries to the proteome.…”

“…For the comparative evaluation of the three peptide repertoires that were generated on the CAF cell line study [ 15 ], we applied the elements of the PepSimili workflow [ 21 ] that is implemented as a tool in a Galaxy cloud platform [ 26 ], online available. The bioinformatics modules of the Galaxy platform allow manipulation of the raw fastq files including quality filtering, trimming of the sequences to isolate the variable part of the recombinant phages and DNA-to-protein translation.…”

“…To analyze the three generated peptide repertoires that were obtained by in vivo biopanning phage display with a combinatorial library of cyclic 7-mers peptides on a cancer-associated fibroblast (CAF) cell line [ 19 ], we used a new approach. By applying the recently developed computational galaxy pipeline PepSimili [ 21 ] we evaluated the calculated similarities of the individual peptides from each one of the three repertoires to the peptides of the others and perform for all three peptide repertoires their mappings on the human proteome. The calculated mapping scores allowed a comparative ranking of proteins.…”

Application of Next Generation Sequencing (NGS) in Phage Displayed Peptide Selection to Support the Identification of Arsenic-Binding Motifs

“…We could show that Illumina sequencing greatly increases the insight into the phage display selection mechanisms. For future phage display experiments, the authors recommend the extensive usage of bioinformatics tools and databases like PuLSE, pLogo, MEME, ProSite, Phastpep, PepSimili, PhD7Faster, Sarutop and, e.g., MimoDB (incomplete list of suitable reviews and literature [84][85][86][87][88][89][90]). These tools and databases help to unravel NGS results, discover enriched motifs, separate fast-propagation biased sequences and other target-unrelated peptides and to rank identified peptides for their occurrence.…”

Evolving a Peptide: Library Platforms and Diversification Strategies

“…Targeting other tissues requires fairly large phage titers; phages can be rescued from tissue of interest, and amplified for iteration of selection. Deep sequencing enables analysis of the entire repertoire of retained phages [78], and should thereby allow the deduction of specific binders even from single-selection-round experiments [79], especially if independent parallel screens are performed and the same peptides are observed enriched in each case. To limit background phages, vascular perfusion can be harnessed.…”