Evaluation of Potential DnaK Modulating Proline-Rich Antimicrobial Peptides Identified by Computational Screening

The day is rapidly approaching where current antibiotic therapies will no longer be effective due to the development of multi-drug resistant bacteria. Antimicrobial peptides (AMPs) are a promising class of therapeutic agents which have the potential to help address this burgeoning problem. Proline-rich AMPs (PrAMPs) are a sub-class of AMPs, that have multiple modes of action including modulation of the bacterial protein folding chaperone, DnaK. They are highly effective against Gram-negative bacteria and have low toxicity to mammalian cells. Previously we used an in silico approach to identify new potential PrAMPs from the DRAMP database. Four of these peptides, antibacterial napin, attacin-C, P9, and PP30, were each chemically assembled and characterized. Together with synthetic oncocin as a reference, each peptide was then assessed for antibacterial activity against Gram-negative/Gram-positive bacteria and for in vitro DnaK modulation activity. We observed that these peptides directly modulate DnaK activity independently of eliciting or otherwise an antibiotic effect. Based on our findings, we propose a change to our previously established PrAMP definition to remove the requirement for antimicrobial activity in isolation, leaving the following classifiers: >25% proline, modulation of DnaK AND/OR the 70S ribosome, net charge of +1 or more, produced in response to bacterial infection AND/OR with pronounced antimicrobial activity.

In Situ Surface Modification of Microfluidic Blood-Brain-Barriers for Improved Screening of Small Molecules and Nanoparticles

Here, we have developed and evaluated a microfluidic-based human blood-brain-barrier (μBBB) platform that models and predicts brain tissue uptake of small molecule drugs and nanoparticles (NPs) targeting the central nervous system. By using a photocrosslinkable copolymer that was prepared from monomers containing benzophenone and N-hydroxysuccinimide ester functional groups, we were able to evenly coat and functionalize μBBB chip channels in situ, providing a covalently attached homogenous layer of extracellular matrix proteins. This novel approach allowed the coculture of human endothelial cells, pericytes, and astrocytes and resulted in the formation of a mimic of cerebral endothelium expressing tight junction markers and efflux proteins, resembling the native BBB. The permeability coefficients of a number of compounds, including caffeine, nitrofurantoin, dextran, sucrose, glucose, and alanine, were measured on our μBBB platform and were found to agree with reported values. In addition, we successfully visualized the receptor-mediated uptake and transcytosis of transferrin-functionalized NPs. The BBB-penetrating NPs were able to target glioma cells cultured in 3D in the brain compartment of our μBBB. In conclusion, our μBBB was able to accurately predict the BBB permeability of both small molecule pharmaceuticals and nanovectors and allowed time-resolved visualization of transcytosis. Our versatile chip design accommodates different brain disease models and is expected to be exploited in further BBB studies, aiming at replacing animal experiments.

(Re)Defining the Proline-Rich Antimicrobial Peptide Family and the Identification of Putative New Members

As we rapidly approach a post-antibiotic era in which multi-drug resistant bacteria are ever-pervasive, antimicrobial peptides (AMPs) represent a promising class of compounds to help address this global issue. AMPs are best-known for their membrane-disruptive mode of action leading to bacteria cell lysis and death. However, many AMPs are also known to be non-lytic and have intracellular modes of action. Proline-rich AMPs (PrAMPs) are one such class, that are generally membrane permeable and inhibit protein synthesis leading to a bactericidal outcome. PrAMPs are highly effective against Gram-negative bacteria and yet show very low toxicity against eukaryotic cells. Here, we review both the PrAMP family and the past and current definitions for this class of peptides. Computational analysis of known AMPs within the DRAMP database (http://dramp.cpu-bioinfor.org/) and assessment of their PrAMP-like properties have led us to develop a revised definition of the PrAMP class. As a result, we subsequently identified a number of unknown and unclassified peptides containing motifs of striking similarity to known PrAMP-based DnaK inhibitors and propose a series of new sequences for experimental evaluation and subsequent addition to the PrAMP family.

Antifibrotic strategies for medical devices

A broad range of medical devices initiate an immune reaction known as the foreign body response (FBR) upon implantation. Here, collagen deposition at the surface of the implant occurs as a result of the FBR, ultimately leading to fibrous encapsulation and, in many cases, reduced function or failure of the device. Despite significant efforts, the prevention of fibrotic encapsulation has not been realized at this point in time. However, many next-generation medical technologies including cellular therapies, sensors and devices depend on the ability to modulate and control the FBR. For these technologies to become viable, significant advances must be made in understanding the underlying mechanism of this response as well as in the methods modulating this response. In this review, we highlight recent advances in the development of materials and coatings providing a reduced FBR and emphasize key characteristics of high-performing approaches. We also provide a detailed overview of the state-of-the-art in strategies relying on controlled drug release, the surface display of bioactive signals, materials-based approaches, and combinations of these approaches. Finally, we offer perspectives on future directions in this field.

Coatings Releasing the Relaxin Peptide Analogue B7-33 Reduce Fibrotic Encapsulation

The development of antifibrotic materials and coatings that can resist the foreign body response (FBR) continues to present a major hurdle in the advancement of current and next-generation implantable medical devices, biosensors, and cell therapies. From an implant perspective, the most important issue associated with the FBR is the prolonged inflammatory response leading to a collagenous capsule that ultimately blocks mass transport and communication between the implant and the surrounding tissue. Up to now, most attempts to reduce the capsule thickness have focused on providing surface coatings that reduce protein fouling and cell attachment. Here, we present an approach that is based on the sustained release of a peptide drug interfering with the FBR. In this study, the biodegradable polymer poly(lactic-co-glycolic) acid (PLGA) was used as a coating releasing the relaxin peptide analogue B7-33, which has been demonstrated to reduce organ fibrosis in animal models. While in vitro protein quantification was used to demonstrate controlled release of the antifibrotic peptide B7-33 from PLGA coatings, an in vitro reporter cell assay was used to demonstrate that B7-33 retains activity against the relaxin family peptide receptor 1 (RXFP1). Subcutaneous implantation of PLGA-coated polypropylene samples in mice with and without the peptide demonstrated a marked reduction in capsule thickness (49.2%) over a 6 week period. It is expected that this novel approach will open the door to a range of new and improved implantable medical devices.

ToF-SIMS and Principal Component Analysis Investigation of Denatured, Surface-Adsorbed Antibodies

Antibody denaturation at solid-liquid interfaces plays an important role in the sensitivity of protein assays such as enzyme-linked immunosorbent assays (ELISAs). Surface immobilized antibodies must maintain their native state, with their antigen binding (Fab) region intact, to capture antigens from biological samples and permit disease detection. In this work, two identical sample sets were prepared with whole antibody IgG, F(ab')₂ and Fc fragments, immobilized to either a silicon wafer or a diethylene glycol dimethyl ether plasma polymer surface. Analysis was conducted on one sample set at day 0, and the second sample set after 14 days in vacuum, with time-of-flight secondary ion mass spectrometry (ToF-SIMS) for molecular species representative of denaturation. A 1003 mass fragment peak list was compiled from ToF-SIMS data and compared to a 35 amino acid mass fragment peak list using principal component analysis. Several ToF-SIMS secondary ions, pertaining to disulfide and thiol species, were identified in the 14 day (presumably denatured) samples. A substrate and primary ion independent marker for denaturation (aging) was then produced using a ratio of mass peak intensities according to denaturation ratio: [I_61.9534 + I_62.9846 + I_122.9547 + I_84.9609 + I_120.9461]/[I_30.9979 + I_42.9991 + I_73.0660 + I_147.0780]. The ratio successfully identifies denaturation on both the silicon and plasma polymer substrates and for spectra generated with Mn⁺, Bi⁺, and Bi₃⁺ primary ions. We believe this ratio could be employed to as a marker of denaturation of antibodies on a plethora of substrates.

Surface Adsorbed Antibody Characterization Using ToF-SIMS with Principal Component Analysis and Artificial Neural Networks

Artificial neural networks (ANNs) form a class of powerful multivariate analysis techniques, yet their routine use in the surface analysis community is limited. Principal component analysis (PCA) is more commonly employed to reduce the dimensionality of large data sets and highlight key characteristics. Herein, we discuss the strengths and weaknesses of PCA and ANNs as methods for investigation and interpretation of a complex multivariate sample set. Using time-of-flight secondary ion mass spectrometry (ToF-SIMS) we acquired spectra from an antibody and its proteolysis fragments with three primary-ion sources to obtain a panel of 72 spectra and a characteristic peak list of 775 fragment ions. We describe the use of ANNs as a means to interpret the ToF-SIMS spectral data, highlight the optimal neural network design and computational parameters, and discuss the technique limitations. Further, employing Bi3(+) as the primary-ion source, ANNs can accurately classify antibody fragments from the parent antibody based on ToF-SIMS spectra.