DNA Subtraction of In Vivo Selected Phage Repertoires for Efficient Peptide Pathology Biomarker Identification in Neuroinflammation Multiple Sclerosis Model

Specific nanoprobe design for MRI: Targeting laminin in the blood-brain barrier to follow alteration due to neuroinflammation

Chronic neuroinflammation is characterized by increased blood-brain barrier (BBB) permeability, leading to molecular changes in the central nervous system that can be explored with biomarkers of active neuroinflammatory processes. Magnetic resonance imaging (MRI) has contributed to detecting lesions and permeability of the BBB. Ultra-small superparamagnetic particles of iron oxide (USPIO) are used as contrast agents to improve MRI observations. Therefore, we validate the interaction of peptide-88 with laminin, vectorized on USPIO, to explore BBB molecular alterations occurring during neuroinflammation as a potential tool for use in MRI. The specific labeling of NPS-P88 was verified in endothelial cells (hCMEC/D3) and astrocytes (T98G) under inflammation induced by interleukin 1β (IL-1β) for 3 and 24 hours. IL-1β for 3 hours in hCMEC/D3 cells increased their co-localization with NPS-P88, compared with controls. At 24 hours, no significant differences were observed between groups. In T98G cells, NPS-P88 showed similar nonspecific labeling among treatments. These results indicate that NPS-P88 has a higher affinity towards brain endothelial cells than astrocytes under inflammation. This affinity decreases over time with reduced laminin expression. In vivo results suggest that following a 30-minute post-injection, there is an increased presence of NPS-P88 in the blood and brain, diminishing over time. Lastly, EAE animals displayed a significant accumulation of NPS-P88 in MRI, primarily in the cortex, attributed to inflammation and disruption of the BBB. Altogether, these results revealed NPS-P88 as a biomarker to evaluate changes in the BBB due to neuroinflammation by MRI in biological models targeting laminin.

New carbohydrate binding domains identified by phage display based functional metagenomic screens of human gut microbiota

Uncultured microbes represent a huge untapped biological resource of novel genes and gene products. Although recent genomic and metagenomic sequencing efforts have led to the identification of numerous genes that are homologous to existing annotated genes, there remains, yet, an enormous pool of unannotated genes that do not find significant sequence homology to existing annotated genes. Functional metagenomics offers a way to identify and annotate novel gene products. Here, we use functional metagenomics to mine novel carbohydrate binding domains that might aid human gut commensals in adherence, gut colonization, and metabolism of complex carbohydrates. We report the construction and functional screening of a metagenomic phage display library from healthy human fecal samples against dietary, microbial and host polysaccharides/glycoconjugates. We identify several protein sequences that do not find a hit to any known protein domain but are predicted to contain carbohydrate binding module-like folds. We heterologously express, purify and biochemically characterize some of these protein domains and demonstrate their carbohydrate-binding function. Our study reveals several previously unannotated carbohydrate-binding domains, including a levan binding domain and four complex N-glycan binding domains that might be useful for the labeling, visualization, and isolation of these glycans.

Screening for Interacting Proteins with Peptide Biomarker of Blood-Brain Barrier Alteration under Inflammatory Conditions

Neurodegenerative diseases are characterized by increased permeability of the blood-brain barrier (BBB) due to alterations in cellular and structural components of the neurovascular unit, particularly in association with neuroinflammation. A previous screening study of peptide ligands to identify molecular alterations of the BBB in neuroinflammation by phage-display, revealed that phage clone 88 presented specific binding affinity to endothelial cells under inflammatory conditions in vivo and in vitro. Here, we aimed to identify the possible target receptor of the peptide ligand 88 expressed under inflammatory conditions. A cross-link test between phage-peptide-88 with IL-1β-stimulated human hCMEC cells, followed by mass spectrometry analysis, was used to identify the target of peptide-88. We modeled the epitope-receptor molecular interaction between peptide-88 and its target by using docking simulations. Three proteins were selected as potential target candidates and tested in enzyme-linked immunosorbent assays with peptide-88: fibronectin, laminin subunit α5 and laminin subunit β-1. Among them, only laminin subunit β-1 presented measurable interaction with peptide-88. Peptide-88 showed specific interaction with laminin subunit β-1, highlighting its importance as a potential biomarker of the laminin changes that may occur at the BBB endothelial cells under pathological inflammation conditions.

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.

A Peptide Targeting Inflammatory CNS Lesions in the EAE Rat Model of Multiple Sclerosis

Multiple sclerosis is characterized by inflammatory lesions dispersed throughout the central nervous system (CNS) leading to severe neurological handicap. Demyelination, axonal damage, and blood brain barrier alterations are hallmarks of this pathology, whose precise processes are not fully understood. In the experimental autoimmune encephalomyelitis (EAE) rat model that mimics many features of human multiple sclerosis, the phage display strategy was applied to select peptide ligands targeting inflammatory sites in CNS. Due to the large diversity of sequences after phage display selection, a bioinformatics procedure called "PepTeam" designed to identify peptides mimicking naturally occurring proteins was used, with the goal to predict peptides that were not background noise. We identified a circular peptide CLSTASNSC called "Ph48" as an efficient binder of inflammatory regions of EAE CNS sections including small inflammatory lesions of both white and gray matter. Tested on human brain endothelial cells hCMEC/D3, Ph48 was able to bind efficiently when these cells were activated with IL1β to mimic inflammatory conditions. The peptide is therefore a candidate for further analyses of the molecular alterations in inflammatory lesions.

Phage display peptide libraries: deviations from randomness and correctives

Peptide-expressing phage display libraries are widely used for the interrogation of antibodies. Affinity selected peptides are then analyzed to discover epitope mimetics, or are subjected to computational algorithms for epitope prediction. A critical assumption for these applications is the random representation of amino acids in the initial naïve peptide library. In a previous study, we implemented next generation sequencing to evaluate a naïve library and discovered severe deviations from randomness in UAG codon over-representation as well as in high G phosphoramidite abundance causing amino acid distribution biases. In this study, we demonstrate that the UAG over-representation can be attributed to the burden imposed on the phage upon the assembly of the recombinant Protein 8 subunits. This was corrected by constructing the libraries using supE44-containing bacteria which suppress the UAG driven abortive termination. We also demonstrate that the overabundance of G stems from variant synthesis-efficiency and can be corrected using compensating oligonucleotide-mixtures calibrated by mass spectroscopy. Construction of libraries implementing these correctives results in markedly improved libraries that display random distribution of amino acids, thus ensuring that enriched peptides obtained in biopanning represent a genuine selection event, a fundamental assumption for phage display applications.