Employment of mastoparan-like peptides to prevent Staphylococcus aureus associated with bovine mastitis.

Bovine mastitis is a frequent infection in lactating cattle, causing great economic losses. Staphylococcus aureus represents the main etiological agent, which causes recurrent and persistent intramammary infections because conventional antibiotics are ineffective against it. Mastoparan-like peptides are multifunctional molecules with broad antimicrobial potential, constituting an attractive alternative. Nevertheless, their toxicity to host cells has hindered their therapeutic application. Previously, our group engineered three mastoparan-L analogs, namely mastoparan-MO, mastoparan-R1, and [I5, R8] MP, to improve cell selectivity and potential. Here, we were interested in comparing the antibacterial efficacy of mastoparan-L and its analogs against bovine mastitis isolates of S. aureus strains, making a correlation with the physicochemical properties and structural arrangement changes promoted by the sequence modifications. As a result, the analog's hemolytic and/or antimicrobial activity was balanced. All the peptides displayed α-helical folding in hydrophobic and membrane-mimetic environments, as determined by circular dichroism. The peptide [I5, R8] MP stood out for its enhanced selectivity and antibacterial features related to mastoparan-L and the other derivatives. Biophysical approaches revealed that [I5, R8] MP rapidly depolarizes the bacterial membrane of S. aureus, causing cell death by subsequent membrane disruption. Our results demonstrated that the [I5, R8] MP peptide could be a starting point for the development of peptide-based drugs for the treatment of bovine mastitis, with the advantage of no residue in milk, which would help reduce the use of classical antibiotics.IMPORTANCEStaphylococcus aureus is a leading cause of mastitis, the world's most important dairy cattle disease. The multidrug resistance and zoonotic potential of S. aureus, besides the likelihood of antibiotic residues in milk, are of critical concern to public and animal health. Antimicrobial peptides offer a novel antimicrobial strategy. Here, we demonstrate that [I5, R8] MP is a potent and selective peptide, which acts on S. aureus by targeting the bacterial membrane. Therefore, understanding the physicochemical determinants and the modes of action of this class of antimicrobials opens novel prospects for peptide development with enhanced activities in the bovine mastitis context.

Deciphering the structure and mechanism of action of computer-designed mastoparan peptides.

Mastoparans are cationic peptides with multifunctional pharmacological properties. Mastoparan-R1 and mastoparan-R4 were computationally designed based on native mastoparan-L from wasps and have improved therapeutic potential for the control of bacterial infections. Here, we evaluated whether these peptides maintain their activity against Escherichia coli strains under a range of salt concentrations. We found that mastoparan-R1 and mastoparan-R4 preserved their activity under the conditions tested, including having antibacterial activities at physiological salt concentrations. The overall structure of the peptides was investigated using circular dichroism spectroscopy in a range of solvents. No significant changes in secondary structure were observed (random coil in aqueous solutions and α-helix in hydrophobic and anionic environments). The three-dimensional structures of mastoparan-R1 and mastoparan-R4 were elucidated through nuclear magnetic resonance spectroscopy, revealing amphipathic α-helical segments for Leu3-Ile13 (mastoparan-R1) and Leu3-Ile14 (mastoparan-R4). Possible membrane-association mechanisms for mastoparan-R1 and mastoparan-R4 were investigated through surface plasmon resonance and leakage studies with synthetic POPC and POPC/POPG (4:1) lipid bilayers. Mastoparan-L had the highest affinity for both membrane systems, whereas the two analogs had weaker association, but improved selectivity for lysing anionic membranes. This finding was also supported by molecular dynamics simulations, in which mastoparan-R1 and mastoparan-R4 were found to have greater interactions with bacteria-like membranes compared with model mammalian membranes. Despite having a few differences in their functional and structural profiles, the mastoparan-R1 analog stood out with the highest activity, greater bacteriostatic potential, and selectivity for lysing anionic membranes. This study reinforces the potential of mastoparan-R1 as a drug candidate.

Utilizing bacteriophage to define the minimum residence time within a plug flow reactor.

As part of a viral mitigating strategy for continuous bioprocessing, that utilizes a plug flow reactor (PFR) for continuous viral inactivation (CVI), understanding the minimum residence time as a function of reactor scale and operational conditions is critical. An empirical-based model was utilized to calculate the minimum duration a virus particle experiences within a plug flow reactor as a function of reactor design and operational conditions. This empirical model's calculations were challenged by pulse injecting the bacteriophage ΦX-174 in non-inactivating conditions and monitoring the discharge of the PFR with infectivity assays. The initial proposed empirical model, with the constraint of requiring an operational Dean number of >100, proved to be effective at calculating first breakthrough of ΦX-174 but only for the appropriate Dean number conditions. With the knowledge gained from the first empirical model, a second was generated to eliminate the Dean number constraint. This second modified empirical model proved to be successful at calculating the first breakthrough at all Dean number's tested, however CVI operation at the lower Dean's number will lead to an increased asymmetry (i.e., increased tailing) in the residence time distribution.

Highland games: A benchmarking exercise in predicting biophysical and drug properties of monoclonal antibodies from amino acid sequences.

Biopharmaceutical product and process development do not yet take advantage of predictive computational modeling to nearly the degree seen in industries based on smaller molecules. To assess and advance progress in this area, spirited coopetition (mutually beneficial collaboration between competitors) was successfully used to motivate industrial scientists to develop, share, and compare data and methods which would normally have remained confidential. The first "Highland Games" competition was held in conjunction with the October 2018 Recovery of Biological Products Conference in Ashville, NC, with the goal of benchmarking and assessment of the ability to predict development-related properties of six antibodies from their amino acid sequences alone. Predictions included purification-influencing properties such as isoelectric point and protein A elution pH, and biophysical properties such as stability and viscosity at very high concentrations. Essential contributions were made by a large variety of individuals, including companies which consented to provide antibody amino acid sequences and test materials, volunteers who undertook the preparation and experimental characterization of these materials, and prediction teams who attempted to predict antibody properties from sequence alone. Best practices were identified and shared, and areas in which the community excels at making predictions were identified, as well as areas presenting opportunities for considerable improvement. Predictions of isoelectric point and protein A elution pH were especially good with all-prediction average errors of 0.2 and 1.6 pH unit, respectively, while predictions of some other properties were notably less good. This manuscript presents the events, methods, and results of the competition, and can serve as a tutorial and as a reference for in-house benchmarking by others. Organizations vary in their policies concerning disclosure of methods, but most managements were very cooperative with the Highland Games exercise, and considerable insight into common and best practices is available from the contributed methods. The accumulated data set will serve as a benchmarking tool for further development of in silico prediction tools.

Leveraging flow mechanics to determine critical process and scaling parameters in a continuous viral inactivation reactor.

A continuous viral inactivation (CVI) chamber has been designed to operate with acceptable residence time distribution (RTD) characteristics. However, altering the CVI's geometry and operation to accommodate the scale was not obvious. In this work, we elucidate the influence of Dean vortices and leverage the transition into the weak turbulent regime to establish relationships between input variables and process outputs. This study was targeted to understand and quantify the impact of viscosity, Dean number, internal diameter, and path length on the RTD. When the Dean number exceeds 70, radial mixing generated by the Dean vortices began to consistently alter the axial dispersive effects experienced by the pulse injection. Increasing to a Dean number of >100, the axial dispersive effects were dominated by the Dean vortices which allowed the calculation of the minimum and maximum residence time to be generated. This work provides a method to calculate operational solutions for a tubular incubation reactor in terms of path length, internal diameter, flow rate, and target minimum and maximum residence time specifications that assures both viral residence times while also establishing criteria to maximize product quality during continuous operation.

Impact of Dean Vortices on the Integrity Testing of a Continuous Viral Inactivation Reactor.

We propose a standard protocol for integrity testing the residence-time distribution (RTD) in a "Jig in a Box" design (JIB)-a previously described tortuous-path, tubular, low-pH, continuous viral inactivation reactor, ensuring that biopharmaceutical products will be incubated for the required minimum residence time, tmin . tmin is the time by which just 0.001% of the total product containing virus has exited the incubation chamber (i.e., t0.00001 ). This t0.00001 is selected to ensure a >4-log reduction in viral load. As current tracers and in-line analytical technologies may not be able to detect tracers at the 0.001% level, an alternative approach is required. The authors describe a method for deriving tmin from t0.005 (i.e., the time at which 0.5% of the product has emerged from the reactor outlet) and an experimentally confirmed offset value, toffset = t0.005 -t0.00001 . The authors also evaluate tracer candidates-including 100-nm-diameter gold nanoparticles, dextrose, monoclonal antibody, and riboflavin-for pre-process acceptability and the effects of viscosity, molecular diffusion coefficient, and particle size. The authors show that a JIB will yield tmin and RTDs that are nearly identical for multiple tracers due to Dean vortex induced mixing. Results indicate that almost any small-molecule tracer that is generally recognized as safe can be used in pre-use integrity testing of a continuous viral inactivation reactor under the Deans values (De) of 119-595.

Computer-Aided Design of Antimicrobial Peptides: Are We Generating Effective Drug Candidates?

Antimicrobial peptides (AMPs), especially antibacterial peptides, have been widely investigated as potential alternatives to antibiotic-based therapies. Indeed, naturally occurring and synthetic AMPs have shown promising results against a series of clinically relevant bacteria. Even so, this class of antimicrobials has continuously failed clinical trials at some point, highlighting the importance of AMP optimization. In this context, the computer-aided design of AMPs has put together crucial information on chemical parameters and bioactivities in AMP sequences, thus providing modes of prediction to evaluate the antibacterial potential of a candidate sequence before synthesis. Quantitative structure-activity relationship (QSAR) computational models, for instance, have greatly contributed to AMP sequence optimization aimed at improved biological activities. In addition to machine-learning methods, the de novo design, linguistic model, pattern insertion methods, and genetic algorithms, have shown the potential to boost the automated design of AMPs. However, how successful have these approaches been in generating effective antibacterial drug candidates? Bearing this in mind, this review will focus on the main computational strategies that have generated AMPs with promising activities against pathogenic bacteria, as well as anti-infective potential in different animal models, including sepsis and cutaneous infections. Moreover, we will point out recent studies on the computer-aided design of antibiofilm peptides. As expected from automated design strategies, diverse candidate sequences with different structural arrangements have been generated and deposited in databases. We will, therefore, also discuss the structural diversity that has been engendered.

Design of a novel continuous flow reactor for low pH viral inactivation.

Insufficient mixing in laminar flow reactors due to diffusion-dominated flow limits their use in applications where narrow residence time distribution (RTD) is required. The aim of this study was to design and characterize a laminar flow (Re 187.7-375.5) tubular reactor for low pH viral inactivation with enhanced radial mixing via the incorporation of curvature and flow inversions. Toward this aim, the reactor described here, Jig in a Box (JIB), was designed with a flow path consisting of alternating 270° turns. The design was optimized by considering the strength of secondary flows characterized by the Dean No., the corresponding secondary flow development length, and the reactor turn lengths. Comprehensive CFD analysis of the reactor centerline velocity profile, cross-sectional velocity, and secondary flow streamlines confirmed enhanced radial mixing due to secondary flows and changes in flow direction. For initial CFD and experimental studies the reactor was limited to a 16.43 m length. Pulse tracer studies for the reactor were computationally simulated and experimentally generated to determine the RTD, RTD variance, and minimum residence time for the tracer fluid elements leaving the reactor, as well as to validate the computational model. The reactor was scaled length wise to increase incubation time and it was observed that as the reactor length increases the RTD variance increases linearly and the dimensionless RTD profile becomes more symmetrical and tighter about the mean residence time.

Design, construction, and optimization of a novel, modular, and scalable incubation chamber for continuous viral inactivation.

We designed, built or 3D printed, and screened tubular reactors that minimize axial dispersion to serve as incubation chambers for continuous virus inactivation of biological products. Empirical residence time distribution data were used to derive each tubular design's volume equivalent to a theoretical plate (VETP) values at a various process flow rates. One design, the Jig in a Box (JIB), yielded the lowest VETP, indicating optimal radial mixing and minimal axial dispersion. A minimum residence time (MRT) approach was employed, where the MRT is the minimum time the product spends in the tubular reactor. This incubation time is typically 60 minutes in a batch process. We provide recommendations for combinations of flow rates and device dimensions for operation of the JIB connected in series that will meet a 60-min MRT. The results show that under a wide range of flow rates and corresponding volumes, it takes 75 ± 3 min for 99% of the product to exit the reactor while meeting the 60-min MRT criterion and fulfilling the constraint of keeping a differential pressure drop under 5 psi. Under these conditions, the VETP increases slightly from 3 to 5 mL though the number of theoretical plates stays constant at about 1326 ± 88. We also demonstrated that the final design volume was only 6% ± 1% larger than the ideal plug flow volume. Using such a device would enable continuous viral inactivation in a truly continuous process or in the effluent of a batch chromatography column. Viral inactivation studies would be required to validate such a design. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:954-965, 2017.

Síndrome de Kawasaki: a propósito de un infante con meningitis aséptica y cambios en la cicatriz de BCG / Kawasaki syndrome: a child with aseptic meningitis and changes at BCG scar site

Presentamos el caso de un niño de 12 meses de edad referido al Hospital Nacional de Niños con diagnóstico presuntivo de exantema súbito, meningitis aséptica y choque incipiente. El paciente se ingresa, tras múltiples consultas a un hospital periférico, al día 14 de fiebre como síntoma más importante. A su ingreso se documentó meningitis aséptica, induración y enrojecimiento en el sitio de aplicación de la vacuna de la BCG, aparte de los criterios clásicos para Síndrome de Kawasaki. El ecocardiograma inicial mostró dilatación coronaria. El Síndrome de Kawasaki debe formar parte del diagnóstico diferencial del infante y niño con enfermedad eruptiva febril, y debe tenerse un alto índice de sospecha clínica de esta entidad