Comparison of motif-based and whole-unique-sequence-based analyses of phage display library datasets generated by biopanning of anti-Borrelia burgdorferi immune sera

Next Generation SICLOPPS Screening for the Identification of Inhibitors of the HIF-1α/HIF-1β Protein-Protein Interaction

Split-intein circular ligation of proteins and peptides (SICLOPPS) is a method for generating intracellular libraries of cyclic peptides that has yielded several first-in-class inhibitors. Here, we detail a revised high-content, high-throughput SICLOPPS screening protocol that utilizes next-generation sequencing, biopanning, and computational tools to identify hits against a given protein-protein interaction. We used this platform for the identification of inhibitors of the HIF-1α/HIF-1β protein-protein interaction. The revised platform resulted in a significantly higher positive hit rate than that previously reported for SICLOPPS screens, and the identified cyclic peptides were more active in vitro and in cells than our previously reported inhibitors. The platform detailed here may be used for the identification of inhibitors of a wide range of other targets.

Revolutionizing Synthetic Antibody Design: Harnessing Artificial Intelligence and Deep Sequencing Big Data for Unprecedented Advances

Synthetic antibodies (Abs) represent a category of engineered proteins meticulously crafted to replicate the functions of their natural counterparts. Such Abs are generated in vitro, enabling advanced molecular alterations associated with antigen recognition, paratope site engineering, and biochemical refinements. In a parallel realm, deep sequencing has brought about a paradigm shift in molecular biology. It facilitates the prompt and cost-effective high-throughput sequencing of DNA and RNA molecules, enabling the comprehensive big data analysis of Ab transcriptomes, including specific regions of interest. Significantly, the integration of artificial intelligence (AI), based on machine- and deep- learning approaches, has fundamentally transformed our capacity to discern patterns hidden within deep sequencing big data, including distinctive Ab features and protein folding free energy landscapes. Ultimately, current AI advances can generate approximations of the most stable Ab structural configurations, enabling the prediction of de novo synthetic Abs. As a result, this manuscript comprehensively examines the latest and relevant literature concerning the intersection of deep sequencing big data and AI methodologies for the design and development of synthetic Abs. Together, these advancements have accelerated the exploration of antibody repertoires, contributing to the refinement of synthetic Ab engineering and optimizations, and facilitating advancements in the lead identification process.

Development of Organoids to Study Infectious Host Interactions

Emerging organoid research is paving way for studies in infectious diseases. Described here is a technique for the generation of stem-cell derived organoids for human small intestine and lung together with methods to infect such organoids with a mock pathogen (Cryptosporidium parvum). Such systems are amenable to imaging and processing for molecular biological analyses. It is the intent of this chapter to provide a simple, routine organoid procedure so that in vitro studies with Borrelia such as cell invasion and dissemination can be conducted.

Modeling the sequence dependence of differential antibody binding in the immune response to infectious disease

Past studies have shown that incubation of human serum samples on high density peptide arrays followed by measurement of total antibody bound to each peptide sequence allows detection and discrimination of humoral immune responses to a variety of infectious diseases. This is true even though these arrays consist of peptides with near-random amino acid sequences that were not designed to mimic biological antigens. This "immunosignature" approach, is based on a statistical evaluation of the binding pattern for each sample but it ignores the information contained in the amino acid sequences that the antibodies are binding to. Here, similar array-based antibody profiles are instead used to train a neural network to model the sequence dependence of molecular recognition involved in the immune response of each sample. The binding profiles used resulted from incubating serum from 5 infectious disease cohorts (Hepatitis B and C, Dengue Fever, West Nile Virus and Chagas disease) and an uninfected cohort with 122,926 peptide sequences on an array. These sequences were selected quasi-randomly to represent an even but sparse sample of the entire possible combinatorial sequence space (~1012). This very sparse sampling of combinatorial sequence space was sufficient to capture a statistically accurate representation of the humoral immune response across the entire space. Processing array data using the neural network not only captures the disease-specific sequence-binding information but aggregates binding information with respect to sequence, removing sequence-independent noise and improving the accuracy of array-based classification of disease compared with the raw binding data. Because the neural network model is trained on all samples simultaneously, a highly condensed representation of the differential information between samples resides in the output layer of the model, and the column vectors from this layer can be used to represent each sample for classification or unsupervised clustering applications.

A White Plaque, Associated with Genomic Deletion, Derived from M13KE-Based Peptide Library Is Enriched in a Target-Unrelated Manner during Phage Display Biopanning Due to Propagation Advantage

The nonspecific enrichment of target-unrelated peptides during biopanning remains a major drawback for phage display technology. The commercial Ph.D.^TM-7 phage display library is used extensively for peptide discovery. This library is based on the M13KE vector, which carries the lacZα sequence, leading to the formation of blue plaques on IPTG-X-gal agar plates. In the current study, we report the isolation of a fast-propagating white clone (displaying WSLGYTG peptide) identified through screening against a recombinant protein. Sanger sequencing demonstrated that white plaques are not contamination from environmental M13-like phages, but derive from the library itself. Whole genome sequencing revealed that the white color of the plaques results from a large 827-nucleotide genomic deletion. The phenotypic characterization of propagation capacity through plaque count- and NGS-based competitive propagation assay supported the higher propagation rate of Ph-WSLGYTG clone compared with the library. According to our data, white plaques are likely to arise endogenously in Ph.D. libraries due to mutations in the M13KE genome and should not always be viewed as exogenous contamination. Our findings also led to the conclusion that the deletion observed here might be an ancestral mutation already present in the naïve library, which causes target-unrelated nonspecific enrichment of white clone during biopanning due to propagation advantage.

Antiphospholipid autoantibodies in Lyme disease arise after scavenging of host phospholipids by Borrelia burgdorferi

A close association with its vertebrate and tick hosts allows Borrelia burgdorferi, the bacterium responsible for Lyme disease, to eliminate many metabolic pathways and instead scavenge key nutrients from the host. A lipid-defined culture medium was developed to demonstrate that exogenous lipids are an essential nutrient of B. burgdorferi, which can accumulate intact phospholipids from its environment to support growth. Antibody responses to host phospholipids were studied in mice and humans using an antiphospholipid ELISA. Several of these environmentally acquired phospholipids including phosphatidylserine and phosphatidic acid, as well as borrelial phosphatidylcholine, are the targets of antibodies that arose early in infection in the mouse model. Patients with acute infections demonstrated antibody responses to the same lipids. The elevation of antiphospholipid antibodies predicted early infection with better sensitivity than did the standardized 2-tier tests currently used in diagnosis. Sera obtained from patients with Lyme disease before and after antibiotic therapy showed declining antiphospholipid titers after treatment. Further study will be required to determine whether these antibodies have utility in early diagnosis of Lyme disease, tracking of the response to therapy, and diagnosis of reinfection, areas in which current standardized tests are inadequate.