Next-generation sequencing coupled with a cell-free display technology for high-throughput production of reliable interactome data

A First-Class Degrader Candidate Targeting Both KRAS G12D and G12V Mediated by CANDDY Technology Independent of Ubiquitination

"Undruggable" targets such as KRAS are particularly challenging in the development of drugs. We devised a novel chemical knockdown strategy, CANDDY (Chemical knockdown with Affinity aNd Degradation DYnamics) technology, which promotes protein degradation using small molecules (CANDDY molecules) that are conjugated to a degradation tag (CANDDY tag) modified from proteasome inhibitors. We demonstrated that CANDDY tags allowed for direct proteasomal target degradation independent of ubiquitination. We synthesized a KRAS-degrading CANDDY molecule, TUS-007, which induced degradation in KRAS mutants (G12D and G12V) and wild-type KRAS. We confirmed the tumor suppression effect of TUS-007 in subcutaneous xenograft models of human colon cells (KRAS G12V) with intraperitoneal administrations and in orthotopic xenograft models of human pancreatic cells (KRAS G12D) with oral administrations. Thus, CANDDY technology has the potential to therapeutically target previously undruggable proteins, providing a simpler and more practical drug targeting approach and avoiding the difficulties in matchmaking between the E3 enzyme and the target.

PURE mRNA display and cDNA display provide rapid detection of core epitope motif via high-throughput sequencing

The reconstructed in vitro translation system known as the PURE system has been used in a variety of cell-free experiments such as the expression of native and de novo proteins as well as various display methods to select for functional polypeptides. We developed a refined PURE-based display method for the preparation of stable messenger RNA (mRNA) and complementary DNA (cDNA)-peptide conjugates and validated its utility for in vitro selection. Our conjugate formation efficiency exceeded 40%, followed by gel purification to allow minimum carry-over of components from the translation system to the downstream assay enabling clean and efficient random peptide sequence screening. We chose the commercially available anti-FLAG M2 antibody as a target molecule for validation. Starting from approximately 1.7 × 10¹² random sequences, a round-by-round high-throughput sequencing showed clear enrichment of the FLAG epitope DYKDDD as well as revealing consensus FLAG epitope motif DYK(D/L/N)(L/Y/D/N/F)D. Enrichment of core FLAG motifs lacking one of the four key residues (DYKxxD) indicates that Tyr (Y) and Lys (K) appear as the two key residues essential for binding. Furthermore, the comparison between mRNA display and cDNA display method resulted in overall similar performance with slightly higher enrichment for mRNA display. We also show that gel purification steps in the refined PURE-based display method improve conjugate formation efficiency and enhance the enrichment rate of FLAG epitope motifs in later rounds of selection especially for mRNA display. Overall, the generalized procedure and consistent performance of two different display methods achieved by the commercially available PURE system will be useful for future studies to explore the sequence and functional space of diverse polypeptides.

High throughput sequencing of in vitro selections of mRNA-displayed peptides: data analysis and applications

In vitro selection using mRNA display is currently a widely used method to isolate functional peptides with desired properties. The analysis of high throughput sequencing (HTS) data from in vitro evolution experiments has proven to be a powerful technique but only recently has it been applied to mRNA display selections. In this Perspective, we introduce aspects of mRNA display and HTS that may be of interest to physical chemists. We highlight the potential of HTS to analyze in vitro selections of peptides and review recent advances in the application of HTS analysis to mRNA display experiments. We discuss some possible issues involved with HTS analysis and summarize some strategies to alleviate them. Finally, the potential for future impact of advancing HTS analysis on mRNA display experiments is discussed.

Development and Application of Computational Methods in Phage Display Technology

BACKGROUND

Phage display is a powerful and versatile technology for the identification of peptide ligands binding to multiple targets, which has been successfully employed in various fields, such as diagnostics and therapeutics, drug-delivery and material science. The integration of next generation sequencing technology with phage display makes this methodology more productive. With the widespread use of this technique and the fast accumulation of phage display data, databases for these data and computational methods have become an indispensable part in this community. This review aims to summarize and discuss recent progress in the development and application of computational methods in the field of phage display.

METHODS

We undertook a comprehensive search of bioinformatics resources and computational methods for phage display data via Google Scholar and PubMed. The methods and tools were further divided into different categories according to their uses.

RESULTS

We described seven special or relevant databases for phage display data, which provided an evidence-based source for phage display researchers to clean their biopanning results. These databases can identify and report possible target-unrelated peptides (TUPs), thereby excluding false-positive data from peptides obtained from phage display screening experiments. More than 20 computational methods for analyzing biopanning data were also reviewed. These methods were classified into computational methods for reporting TUPs, for predicting epitopes and for analyzing next generation phage display data.

CONCLUSION

The current bioinformatics archives, methods and tools reviewed here have benefitted the biopanning community. To develop better or new computational tools, some promising directions are also discussed.

More than one way to bind to cholesterol: atypical variants of membrane-binding domain of perfringolysin O selected by ribosome display

Herein, we report a high-throughput approach for the selection of peripheral protein domains that bind specifically to cholesterol in lipid membranes. We discovered variants of perfringolysin O, with non-conserved amino acid substitutions at regions crucial for cholesterol recognition, demonstrating an unprecedented amino acid sequence variability with binding ability for cholesterol. The developed approach provides an effective platform for a comprehensive study of protein lipid interactions.

By using developed ribosomal display, we discovered variants of perfringolysin O, a pore forming toxin from bacteria Clostridium perfringens, with non-conserved amino acid substitutions at regions crucial for cholesterol recognition.

Combination of ribosome display and next generation sequencing as a powerful method for identification of affibody binders against β-lactamase CTX-M15

CTX-M15 is one of the most widespread, extended spectrum β-lactamases, a major determinant of antibiotic resistance representing urgent public health threats, among enterobacterial strains infecting humans and animals. Here we describe the selection of binders to CTX-M15 from a combinatorial affibody library displayed on ribosomes. Upon three increasingly selective ribosome display iterations, selected variants were identified by next generation sequencing (NGS). Nine affibody variants with high relative abundance bearing QRP and QLH amino acid motifs at residues 9-11 were produced and characterized in terms of stability, affinity and specificity. All affibodies were correctly folded, with affinities ranging from 0.04 to 2 μM towards CTX-M15, and successfully recognized CTX-M15 in bacterial lysates, culture supernatants and on whole bacteria. It was further demonstrated that the binding of affibody molecules to CTX-M15 modulated the enzyme's kinetic parameters. This work provides an approach using ribosome display coupled to NGS for the rapid generation of protein ligands of interest in diagnostic and research applications.

The in vitro selection world

Through iterative cycles of selection, amplification, and mutagenesis, in vitro selection provides the ability to isolate molecules of desired properties and function from large pools (libraries) of random molecules with as many as 10(16) distinct species. This review, in recognition of a quarter of century of scientific discoveries made through in vitro selection, starts with a brief overview of the method and its history. It further covers recent developments in in vitro selection with a focus on tools that enhance the capabilities of in vitro selection and its expansion from being purely a nucleic acids selection to that of polypeptides and proteins. In addition, we cover how next generation sequencing and modern biological computational tools are being used to complement in vitro selection experiments. On the very least, sequencing and computational tools can translate the large volume of information associated with in vitro selection experiments to manageable, analyzable, and exploitable information. Finally, in vivo selection is briefly compared and contrasted to in vitro selection to highlight the unique capabilities of each method.

Next-generation technologies for multiomics approaches including interactome sequencing

The development of high-speed analytical techniques such as next-generation sequencing and microarrays allows high-throughput analysis of biological information at a low cost. These techniques contribute to medical and bioscience advancements and provide new avenues for scientific research. Here, we outline a variety of new innovative techniques and discuss their use in omics research (e.g., genomics, transcriptomics, metabolomics, proteomics, and interactomics). We also discuss the possible applications of these methods, including an interactome sequencing technology that we developed, in future medical and life science research.

Multiplex single-molecule interaction profiling of DNA-barcoded proteins

In contrast with advances in massively parallel DNA sequencing, high-throughput protein analyses are often limited by ensemble measurements, individual analyte purification and hence compromised quality and cost-effectiveness. Single-molecule protein detection using optical methods is limited by the number of spectrally non-overlapping chromophores. Here we introduce a single-molecular-interaction sequencing (SMI-seq) technology for parallel protein interaction profiling leveraging single-molecule advantages. DNA barcodes are attached to proteins collectively via ribosome display or individually via enzymatic conjugation. Barcoded proteins are assayed en masse in aqueous solution and subsequently immobilized in a polyacrylamide thin film to construct a random single-molecule array, where barcoding DNAs are amplified into in situ polymerase colonies (polonies) and analysed by DNA sequencing. This method allows precise quantification of various proteins with a theoretical maximum array density of over one million polonies per square millimetre. Furthermore, protein interactions can be measured on the basis of the statistics of colocalized polonies arising from barcoding DNAs of interacting proteins. Two demanding applications, G-protein coupled receptor and antibody-binding profiling, are demonstrated. SMI-seq enables 'library versus library' screening in a one-pot assay, simultaneously interrogating molecular binding affinity and specificity.

Beyond GWAS in COPD: probing the landscape between gene-set associations, genome-wide associations and protein-protein interaction networks

OBJECTIVES

To use a systems biology approach to integrate genotype and protein-protein interaction (PPI) data to identify disease network modules associated with chronic obstructive pulmonary disease (COPD) and to perform traditional pathway analysis.

METHODS

We utilized a standard gene-set association approach (FORGE) using gene-based association analysis and gene-set definitions from the molecular signatures database (MSigDB). As a discovery step, we analyzed GWAS results from 2 well-characterized COPD cohorts: COPDGene and GenKOLS. We used a third well-characterized COPD case-control cohort for replication: ECLIPSE. Next, we used dmGWAS, a method that integrates GWAS results with PPI, to identify COPD disease modules.

RESULTS

No gene-sets reached experiment-wide significance in either discovery population. We identified a consensus network of 10 genes identified in modules by integrating GWAS results with PPI that replicated in COPDGene, GenKOLS, and ECLIPSE. Members of 4 gene-sets were enriched among these 10 genes: (i) lung adenocarcinoma tumor-sequencing genes, (ii) IL-7 pathway genes, (iii) kidney cell response to arsenic, and (iv) CD4 T-cell responses. Further, several genes have also been associated with pathophysiology relevant to COPD including KCNK3, NEDD4L, and RIN3. In particular, KCNK3 has been associated with pulmonary arterial hypertension, a common complication in advanced COPD.

CONCLUSION

We report a set of new genes that may influence the etiology of COPD that would not have been identified using traditional GWAS and pathway analyses alone.

Towards personalized medicine mediated by in vitro virus-based interactome approaches

We have developed a simple in vitro virus (IVV) selection system based on cell-free co-translation, using a highly stable and efficient mRNA display method. The IVV system is applicable to the high-throughput and comprehensive analysis of proteins and protein–ligand interactions. Huge amounts of genomic sequence data have been generated over the last decade. The accumulated genetic alterations and the interactome networks identified within cells represent a universal feature of a disease, and knowledge of these aspects can help to determine the optimal therapy for the disease. The concept of the “integrome” has been developed as a means of integrating large amounts of data. We have developed an interactome analysis method aimed at providing individually-targeted health care. We also consider future prospects for this system.

Molecular network analysis enhances understanding of the biology of mental disorders

We provide an introduction to network theory, evidence to support a connection between molecular network structure and neuropsychiatric disease, and examples of how network approaches can expand our knowledge of the molecular bases of these diseases. Without systematic methods to derive their biological meanings and inter-relatedness, the many molecular changes associated with neuropsychiatric disease, including genetic variants, gene expression changes, and protein differences, present an impenetrably complex set of findings. Network approaches can potentially help integrate and reconcile these findings, as well as provide new insights into the molecular architecture of neuropsychiatric diseases. Network approaches to neuropsychiatric disease are still in their infancy, and we discuss what might be done to improve their prospects.

DNA sequencing methods in human genetics and disease research

DNA sequencing has revolutionized biological and medical research, and is poised to have a similar impact in medicine. This tool is just one of a number of developments in our capability to identify, quantitate and functionally characterize the components of the biological networks keeping us healthy or making us sick, but in many respects it has played the leading role in this process. The new technologies do, however, also provide a bridge between genotype and phenotype, both in man and model (as well as all other) organisms, revolutionize the identification of elements involved in a multitude of human diseases or other phenotypes, and generate a wealth of medically relevant information on every single person, as the basis of a truly personalized medicine of the future.

Development of Next-Generation Peptide Binders Using In vitro Display Technologies and Their Potential Applications

During the last decade, a variety of monoclonal antibodies have been developed and used as molecular targeting drugs in medical therapies. Although antibody drugs tend to have intense pharmacological activities and negligible side effects, several issues in their development and prescription remain to be resolved. Synthetic peptides with affinities and specificities for a desired target have received significant attention as alternatives to antibodies. In vitro display technologies are powerful methods for the selection of such peptides from combinatorial peptide libraries. Various types of peptide binders are being selected with such technologies for use in a wide range of fields from bioscience to medicine. This mini review article focuses on the current state of in vitro display selection of synthetic peptide binders and compares the selected peptides with natural peptides/proteins to provide a better understanding of the target affinities and inhibitory activities derived from their amino acid sequences and structural frameworks. The potential of synthetic peptide binders as alternatives to antibody drugs in therapeutic applications is also reviewed.

Efficiency of puromycin-based technologies mediated by release factors and a ribosome recycling factor

Two puromycin-based techniques, in vitro virus (IVV) and C-terminal labelling of proteins, were developed based on the observation that puromycin binds the C-terminus of a protein. Puromycin technology is a useful tool for the detection of proteins and analysis of protein–protein interactions (PPIs); however, problems arise due to the existence of stop codons in the native mRNAs. Release factors (RFs) that enter the A-site of the ribosome at stop codons compete with puromycin. To overcome this issue, we have used a highly controllable reconstituted cell-free system for puromycin-based techniques, and observed efficient IVV formation and C-terminal labelling using templates possessing a stop codon. The optimal conditions of IVV formation using templates possessing a stop codon was RF (−), while that of C-terminal labelling was RF (−) and the ribosome recycling factor (RRF) (+). Thus, we have overcome the experimental limitations of conventional IVV. In addition, we discovered that RRF significantly increases the efficiency of C-terminal protein labelling, but not IVV formation.