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

ERβ1 Sensitizes and ERβ2 Desensitizes ERα-Positive Breast Cancer Cells to the Inhibitory Effects of Tamoxifen, Fulvestrant and Their Combination with All-Trans Retinoic Acid

Adjuvant endocrine therapy (AET) is the treatment of choice for early-stage estrogen receptor alpha (ERα)-positive breast cancer (BC). However, almost 40% of tamoxifen-treated cases display no response or a partial response to AET, thus increasing the need for new treatment options and strong predictors of the therapeutic response of patients at high risk of relapse. In addition to ERα, BC research has focused on ERβ1 and ERβ2 (isoforms of ERβ), the second ER isotype. At present, the impact of ERβ isoforms on ERα-positive BC prognosis and treatment remains elusive. In the present study, we established clones of MCF7 cells constitutively expressing human ERβ1 or ERβ2 and investigated their role in the response of MCF7 cells to antiestrogens [4-hydroxytamoxifen (OHΤ) and fulvestrant (ICI182,780)] and retinoids [all-trans retinoic acid (ATRA)]. We show that, compared to MCF7 cells, MCF7-ERβ1 and MCF7-ERβ2 cells were sensitized and desensitized, respectively, to the antiproliferative effect of the antiestrogens, ATRA and their combination and to the cytocidal effect of the combination of OHT and ATRA. Analysis of the global transcriptional changes upon OHT-ATRA combinatorial treatment revealed uniquely regulated genes associated with anticancer effects in MCF7-ERβ1 cells and cancer-promoting effects in MCF7-ERβ2 cells. Our data are favorable to ERβ1 being a marker of responsiveness and ERβ2 being a marker of resistance of MCF7 cells to antiestrogens alone and in combination with ATRA.

Combination of Experimental and Bioinformatic Approaches for Identification of Immunologically Relevant Protein-Peptide Interactions

Protein-peptide interactions are an essential player in cellular processes and, thus, of great interest as potential therapeutic agents. However, identifying the protein's interacting surface has been shown to be a challenging task. Here, we present a methodology for protein-peptide interaction identification, implementing phage panning, next-generation sequencing and bioinformatic analysis. One of the uses of this methodology is identification of allergen epitopes, especially suitable for globular inhaled and venom allergens, where their binding capability is determined by the allergen's conformation, meaning their interaction cannot be properly studied when denatured. A Ph.D. commercial system based on the M13 phage vector was used for the panning process. Utilization of various bioinformatic tools, such as PuLSE, SAROTUP, MEME, Hammock and Pepitope, allowed us to evaluate a large amount of obtained data. Using the described methodology, we identified three peptide clusters representing potential epitopes on the major wasp venom allergen Ves v 5.

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

Phage-displayed peptide selections generate complex repertoires of several hundred thousand peptides as revealed by next-generation sequencing (NGS). In repeated peptide selections, however, even in identical experimental in vitro conditions, only a very small number of common peptides are found. The repertoire complexities are evidence of the difficulty of distinguishing between effective selections of specific peptide binders to exposed targets and the potential high background noise. Such investigation is even more relevant when considering the plethora of in vivo expressed targets on cells, in organs or in the entire organism to define targeting peptide agents. In the present study, we compare the published NGS data of three peptide repertoires that were obtained by phage display under identical experimental in vitro conditions. By applying the recently developed tool PepSimili we evaluate the calculated similarities of the individual peptides from each of these three repertoires and perform their mappings on the human proteome. The peptide-to-peptide mappings reveal high similarities among the three repertoires, confirming the desired reproducibility of phage-displayed peptide selections.

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

Next generation sequencing (NGS) in combination with phage surface display (PSD) are powerful tools in the newly equipped molecular biology toolbox for the identification of specific target binding biomolecules. Application of PSD led to the discovery of manifold ligands in clinical and material research. However, limitations of traditional phage display hinder the identification process. Growth-based library biases and target-unrelated peptides often result in the dominance of parasitic sequences and the collapse of library diversity. This study describes the effective enrichment of specific peptide motifs potentially binding to arsenic as proof-of-concept using the combination of PSD and NGS. Arsenic is an environmental toxin, which is applied in various semiconductors as gallium arsenide and selective recovery of this element is crucial for recycling and remediation. The development of biomolecules as specific arsenic-binding sorbents is a new approach for its recovery. Usage of NGS for all biopanning fractions allowed for evaluation of motif enrichment, in-depth insight into the selection process and the discrimination of biopanning artefacts, e.g., the amplification-induced library-wide reduction in hydrophobic amino acid proportion. Application of bioinformatics tools led to the identification of an SxHS and a carboxy-terminal QxQ motif, which are potentially involved in the binding of arsenic. To the best of our knowledge, this is the first report of PSD combined with NGS of all relevant biopanning fractions.

InteractomeSeq: a web server for the identification and profiling of domains and epitopes from phage display and next generation sequencing data

High-Throughput Sequencing technologies are transforming many research fields, including the analysis of phage display libraries. The phage display technology coupled with deep sequencing was introduced more than a decade ago and holds the potential to circumvent the traditional laborious picking and testing of individual phage rescued clones. However, from a bioinformatics point of view, the analysis of this kind of data was always performed by adapting tools designed for other purposes, thus not considering the noise background typical of the 'interactome sequencing' approach and the heterogeneity of the data. InteractomeSeq is a web server allowing data analysis of protein domains ('domainome') or epitopes ('epitome') from either Eukaryotic or Prokaryotic genomic phage libraries generated and selected by following an Interactome sequencing approach. InteractomeSeq allows users to upload raw sequencing data and to obtain an accurate characterization of domainome/epitome profiles after setting the parameters required to tune the analysis. The release of this tool is relevant for the scientific and clinical community, because InteractomeSeq will fill an existing gap in the field of large-scale biomarkers profiling, reverse vaccinology, and structural/functional studies, thus contributing essential information for gene annotation or antigen identification. InteractomeSeq is freely available at https://InteractomeSeq.ba.itb.cnr.it/.

Evolving a Peptide: Library Platforms and Diversification Strategies

Peptides are widely used in pharmaceutical industry as active pharmaceutical ingredients, versatile tools in drug discovery, and for drug delivery. They find themselves at the crossroads of small molecules and proteins, possessing favorable tissue penetration and the capability to engage into specific and high-affinity interactions with endogenous receptors. One of the commonly employed approaches in peptide discovery and design is to screen combinatorial libraries, comprising a myriad of peptide variants of either chemical or biological origin. In this review, we focus mainly on recombinant peptide libraries, discussing different platforms for their display or expression, and various diversification strategies for library design. We take a look at well-established technologies as well as new developments and future directions.