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Human leucocyte antigen B*27 (HLA-B*27) is strongly associated with inflammatory diseases of the spine and pelvis (for example, ankylosing spondylitis (AS)) and the eye (that is, acute anterior uveitis (AAU)) 1 . How HLA-B*27 facilitates disease remains unknown, but one possible mechanism could involve presentation of pathogenic peptides to CD8 + T cells. Here we isolated orphan T cell receptors (TCRs) expressing a disease-associated public β-chain variable region–complementary-determining region 3β (BV9–CDR3β) motif 2 – 4 from blood and synovial fluid T cells from individuals with AS and from the eye in individuals with AAU. These TCRs showed consistent α-chain variable region (AV21) chain pairing and were clonally expanded in the joint and eye. We used HLA-B*27:05 yeast display peptide libraries to identify shared self-peptides and microbial peptides that activated the AS- and AAU-derived TCRs. Structural analysis revealed that TCR cross-reactivity for peptide–MHC was rooted in a shared binding motif present in both self-antigens and microbial antigens that engages the BV9–CDR3β TCRs. These findings support the hypothesis that microbial antigens and self-antigens could play a pathogenic role in HLA-B*27-associated disease. A study shows that cross-reactivity of microbial antigens and self-antigens presented by HLA-B*27 may be important in the pathogenesis of diseases associated with HLA-B*27 and identifies the shared binding motif responsible.

Non-ribosomal peptide synthetases (NRPSs) are giant enzyme machines that activate amino acids in an assembly line fashion. As NRPSs are not restricted to the incorporation of the 20 proteinogenic amino acids, their efficient manipulation would enable microbial production of a diverse range of peptides; however, the structural requirements for reprogramming NRPSs to facilitate the production of new peptides are not clear. Here we describe a new fusion point inside the condensation domains of NRPSs that results in the development of the exchange unit condensation domain (XUC) concept, which enables the efficient production of peptides, even containing non-natural amino acids, in yields up to 280 mg l −1 . This allows the generation of more specific NRPSs, reducing the number of unwanted peptide derivatives, but also the generation of peptide libraries. The XUC might therefore be suitable for the future optimization of peptide production and the identification of bioactive peptide derivatives for pharmaceutical and other applications. Non-ribosomal peptide synthetases have now been modified and de novo non-ribosomal peptide synthetases constructed using new assembly points within condensation domains. This approach enabled the production of new-to-nature peptides, including some carrying synthetic amino acids, as well as the generation of peptide libraries.

High-diversity genetically-encoded combinatorial libraries (10 8 −10 13 members) are a rich source of peptide-based binding molecules, identified by affinity selection. Synthetic libraries can access broader chemical space, but typically examine only ~ 10 6 compounds by screening. Here we show that in-solution affinity selection can be interfaced with nano-liquid chromatography-tandem mass spectrometry peptide sequencing to identify binders from fully randomized synthetic libraries of 10 8 members—a 100-fold gain in diversity over standard practice. To validate this approach, we show that binders to a monoclonal antibody are identified in proportion to library diversity, as diversity is increased from 10 6 –10 8 . These results are then applied to the discovery of p53-like binders to MDM2, and to a family of 3–19 nM-affinity, α/β-peptide-based binders to 14-3-3. An X-ray structure of one of these binders in complex with 14-3-3σ is determined, illustrating the role of β-amino acids in facilitating a key binding contact. Synthetic peptide libraries can access broad chemical space, but generally examine only ~ 10 6  compounds. Here, the authors show that in-solution affinity selection, interfaced with nLC-MS/MS sequencing, can identify binders from fully randomized synthetic libraries of 10 8 members.

Protein aggregates are associated with numerous diseases. Here we report a platform for the rapid phenotypic selection of protein aggregation inhibitors from genetically encoded cyclic peptide libraries in Escherichia coli based on phage-assisted continuous evolution (PACE). We developed a new PACE-compatible selection for protein aggregation inhibition and used it to identify cyclic peptides that suppress amyloid-β42 and human islet amyloid polypeptide aggregation. Additionally, we integrated a negative selection that removes false positives and off-target hits, greatly improving cyclic peptide selectivity. We show that selected inhibitors are active when chemically resynthesized in in vitro assays. Our platform provides a powerful approach for the rapid discovery of cyclic peptide inhibitors of protein aggregation and may serve as the basis for the future evolution of cyclic peptides with a broad spectrum of inhibitory activities. A platform for the continuous selection of protein aggregation inhibitors from genetically encoded cyclic peptide libraries in Escherichia coli was developed. This platform was used to discover cyclic peptides that suppress aggregation of amyloid-β42 and human islet amyloid polypeptide.

The binding specificities of an individual’s antibody repertoire contain a wealth of biological information. They harbor evidence of environmental exposures, allergies, ongoing or emerging autoimmune disease processes, and responses to immunomodulatory therapies, for example. Highly multiplexed methods to comprehensively interrogate antibody-binding specificities have therefore emerged in recent years as important molecular tools. Here, we provide a detailed protocol for performing ‘phage immunoprecipitation sequencing’ (PhIP-Seq), which is a powerful method for analyzing antibody-repertoire binding specificities with high throughput and at low cost. The methodology uses oligonucleotide library synthesis (OLS) to encode proteomic-scale peptide libraries for display on bacteriophage. These libraries are then immunoprecipitated, using an individual’s antibodies, for subsequent analysis by high-throughput DNA sequencing. We have used PhIP-Seq to identify novel self-antigens associated with autoimmune disease, to characterize the self-reactivity of broadly neutralizing HIV antibodies, and in a large international cross-sectional study of exposure to hundreds of human viruses. Compared with alternative array-based techniques, PhIP-Seq is far more scalable in terms of sample throughput and cost per analysis. Cloning and expression of recombinant proteins are not required (versus protein microarrays), and peptide lengths are limited only by DNA synthesis chemistry (up to 90-aa (amino acid) peptides versus the typical 8- to 12-aa length limit of synthetic peptide arrays). Compared with protein microarrays, however, PhIP-Seq libraries lack discontinuous epitopes and post-translational modifications. To increase the accessibility of PhIP-Seq, we provide detailed instructions for the design of phage-displayed peptidome libraries, their immunoprecipitation using serum antibodies, deep sequencing–based measurement of peptide abundances, and statistical determination of peptide enrichments that reflect antibody–peptide interactions. Once a library has been constructed, PhIP-Seq data can be obtained for analysis within a week.

Peptides are valuable for therapeutic development, with multicyclic peptides showing promise in mimicking antigen-binding potency of antibodies. However, our capability to engineer multicyclic peptide scaffolds, particularly for the construction of large combinatorial libraries, is still limited. Here, we study the interplay of disulfide pairing between three biscysteine motifs, and designed a range of triscysteine motifs with unique disulfide-directing capability for regulating the oxidative folding of multicyclic peptides. We demonstrate that incorporating these motifs into random sequences allows the design of disulfide-directed multicyclic peptide (DDMP) libraries with up to four disulfide bonds, which have been applied for the successful discovery of peptide binders with nanomolar affinity to several challenging targets. This study encourages the use of more diverse disulfide-directing motifs for creating multicyclic peptide libraries and opens an avenue for discovering functional peptides in sequence and structural space beyond existing peptide scaffolds, potentially advancing the field of peptide drug discovery. Multicyclic peptides have the potential to mimic the antigen-binding potency of the complementarity-determining regions of antibodies, enabling the development of potent peptide binders to challenging targets, but the scaffolds of multicyclic peptides are difficult to engineer. Here, the authors design a range of triscysteine motifs with disulfide-directing capability for regulating the oxidative folding of multicyclic peptides and employ them in the design of disulfide-directed multicyclic peptide libraries for discovery of potent peptide binders.

Peptides, or short chains of amino-acid residues, are becoming increasingly important as active ingredients of drugs and as crucial probes and/or tools in medical, biotechnological, and pharmaceutical research. Situated at the interface between small molecules and larger macromolecular systems, they pose a difficult challenge for computational methods. We report an in silico peptide library generation and prioritization workflow using CmDock for identifying tetrapeptide ligands that bind to Fc regions of antibodies that is analogous to known in vitro recombinant peptide libraries’ display and expression systems. The results of our in silico study are in accordance with existing scientific literature on in vitro peptides that bind to antibody Fc regions. In addition, we postulate an evolving in silico library design workflow that will help circumvent the combinatorial problem of in vitro comprehensive peptide libraries by focusing on peptide subunits that exhibit favorable interaction profiles in initial in silico peptide generation and testing.

Antigen discovery technologies have largely focused on major histocompatibility complex (MHC) class I-restricted human T cell receptors (TCRs), leaving methods for MHC class II-restricted and mouse TCR reactivities relatively undeveloped. Here we present TCR mapping of antigenic peptides (TCR-MAP), an antigen discovery method that uses a synthetic TCR-stimulated circuit in immortalized T cells to activate sortase-mediated tagging of engineered antigen-presenting cells (APCs) expressing processed peptides on MHCs. Live, tagged APCs can be directly purified for deconvolution by sequencing, enabling TCRs with unknown specificity to be queried against barcoded peptide libraries in a pooled screening context. TCR-MAP accurately captures self-reactivities or viral reactivities with high throughput and sensitivity for both MHC class I-restricted and class II-restricted TCRs. We elucidate problematic cross-reactivities of clinical TCRs targeting the cancer/testis melanoma-associated antigen A3 and discover targets of myocarditis-inciting autoreactive T cells in mice. TCR-MAP has the potential to accelerate T cell antigen discovery efforts in the context of cancer, infectious disease and autoimmunity. T cell-specific antigens are discovered at high throughput without killing target cells.

Efficient secretion of heterologous proteins is crucial for applications in industrial and biomedical fields. Selecting appropriate signal peptides and bacterial strains is critical for successful protein expression and export. Bacillus thuringiensis , known for its robust secretion capabilities within the Bacillus genus, shows promise as an ideal host for this purpose. We performed genome-based bioinformatic analysis of B . thuringiensis HD73. A total of 525 proteins were predicted to contain signal peptides, exceeding those in other Bacillus species. The extracellular proteome of B . thuringiensis HD73 was analyzed via LC-MS/MS, identifying 100 secreted proteins. A library of 30 signal peptides was constructed by integrating genome-based predictions with experimental secretome data. Using this library, green fluorescent protein secretory expression systems were developed in the acrystalliferous mutant strain B . thuringiensis HD73 − , and the strain carrying signal peptide S17 showed the highest secretion efficiency. Additionally, the top 10 performing signal peptides were used to express and secrete the convenient enzyme cutinase, with the S20 fusion strain exhibiting the highest cutinase activity (3.65 U/mL in the culture supernatant). This study provides the first combined bioinformatic and experimental characterization of the B . thuringiensis secretome. The developed secreted protein expression system and signal peptide library demonstrate effectiveness and offer potential for future heterologous protein secretion in B . thuringiensis . Key points • Genome-based secretome and experimental secretome of B. thuringiensis were characterized . • A SP library comprising 30 SPs derived from B. thuringiensis was constructed . • GFP and cutinase were successfully secreted by B. thuringiensis .

To develop efficient selection strategies and improve the discovery of promising ligands, it is highly desirable to analyze the sequence composition of naïve phage display libraries and monitor the evolution of their peptide content during successive rounds of amplification. In the current study, we performed a comparative analysis of the compositional features in different lots of the same naïve phage display library and monitored alterations in their peptide compositions during three rounds of amplification. We conducted three rounds of duplicate serial amplification of two different lots of the Ph.D.™-12 phage display library. DNA from the samples was subjected to Next-Generation Sequencing (NGS) using an Illumina platform. The NGS datasets underwent a variety of bioinformatic analyses using Python and MATLAB scripts. We observed substantial heterogeneity in the sequence composition of the two lots indicated by differences in the enhanced percentage of wildtype clones, reduced diversity (number of unique sequences), and increased enrichment factors (EFs) during amplification as well as by observing no common sequence between lots and decreased number of common sequences between the naïve library and the consecutive rounds of amplification for each lot. We also found potential propagation-related target-unrelated peptides (TUPs) with the highest EFs in the two lots, which were displayed by the fastest-propagating phage clones. Furthermore, motif analysis of the most enriched subpopulation of amplified libraries led to the identification of some motifs hypothesized to contribute to the increased amplification rates of the respective phage clones. Our results highlight tremendous heterogeneity in the peptide composition of different lots of the same type of naïve phage display library, and the divergent evolution of their compositional features during amplification rounds at the amino acid, peptide, and motif levels. Our findings can be instrumental for phage display researchers by bringing fundamental insights into the vast extent of non-uniformity between phage display libraries and by providing a clear picture of how these discrepancies can lead to different evolutionary fates for the peptide composition of phage pools, which can have profound impacts on the outcome of phage display selections through biopanning.