Characterization Of Protein Aggregates Research Articles

Mass Spectrometry-Based Characterization of Protein Aggregates in Tissues and Biofluids.

Protein aggregation is a common mechanism in multiple neurodegenerative and heart diseasesand the accumulation of proteins in aggregates is toxic to cells, causing injury and death. The degree of protein aggregation directly correlates with the severity of the disease. Misfolded proteins present thermodynamic barriers that culminate in the loss of structure and function and the exposure of hydrophobic residues. The exposure of hydrophobic residues is the driving force behind protein aggregation, as it reduces surface free energy and increases the propensity for the formation of large insoluble aggregates. Exploring the protein content of aggregates is fundamental to understanding their formation mechanism and pathophysiological effects. We demonstrate here a method for isolating aggregated protein content in human plasma and mouse brain samples. The samples were characterized by mass spectrometry analysis, transmission electron microscopy, and western blotting. We report the identification of proteins associated with neurodegenerative diseases in the isolated pellets. The western blotting analyses of the isolated pellet showed the positivity for CD89 and CD63, consolidated markers of exosomes, confirming the presence of exosomes within the pellet but not in the supernatant in human plasma. Notably, the concomitant isolation of exosomes together with the protein aggregates was feasible starting from 200 μL of human plasma. Moreover, the presented methodology separated albumin from the aggregated pellet, allowing identification of larger diversity of proteins through mass spectrometry analysis.

Characterization of protein aggregates in cream and skimmed human milk after heat and high-pressure pasteurization treatments.

Preservation processes applied to ensure microbial safety of human milk (HM) can modify the native structure of proteins and their bioactivities. Consequently, this study evaluated the effect of pasteurization methods (Holder pasteurization, high-temperature short-time (HTST), and high hydrostatic pressure (HHP)) of whole human milk (HM) on protein aggregates in skim milk and cream fractions. For heat-treated whole milk, insoluble protein aggregates at milk fat globule membrane (MFGM) were formed by disulfide and non-covalent bonds, but insoluble skim milk protein aggregates were only stabilized by non-covalent interactions. Contrary to heat treatment, the insolubilization of main proteins at the MFGM of HHP-treated HM was only through non-covalent interactions rather than disulfide bonds. Moreover, only heat treatment induced the insoluble aggregation of ⍺-lactalbumin. Overall, compared to heat treatment, HHP produced a milder effect on protein aggregation, validating the use of this process to better preserve the native state of HM bioactive proteins.

Investigation of α-Synuclein and Amyloid-β(42)-E22Δ Oligomers Using SiN Nanopore Functionalized with L-Dopa.

Solid-state nanopores are an emerging technology used as a high-throughput, label-free analytical method for the characterization of protein aggregation in an aqueous solution. In this work, we used Levodopamine to coat a silicon nitride nanopore surface that was fabricated through a dielectric breakdown in order to reduce the unspecific adsorption. The coating of inner nanopore wall by investigation of the translocation of heparin. The functionalized nanopore was used to investigate the aggregation of amyloid-β and α-synuclein, two biomarkers of degenerative diseases. In the first application, we demonstrate that the α-synuclein WT is more prone to form dimers than the variant A53T. In the second one, we show for the Aβ(42)-E22Δ (Osaka mutant) that the addition of Aβ(42)-WT monomers increases the polymorphism of oligomers, while the incubation with Aβ(42)-WT fibrils generates larger aggregates.

A Transfer Free Energy Based Implicit Solvent Model for Protein Simulations in Solvent Mixtures: Urea-Induced Denaturation as a Case Study.

We developed a method for implicit solvent molecular dynamics simulations of proteins in solvent mixtures (model with implicit solvation thermodynamics, MIST). The MIST method introduces experimental group transfer free energies to the generalized Born formulation for generating molecular trajectories without the need for developing rigorous explicit-solvent force fields for multicomponent solutions. As a test case, we studied the urea-induced denaturation of the Trp-cage miniprotein in water. We demonstrate that our method allows efficient exploration of the conformational space of the protein in only a few hundreds of nanoseconds of all-atom unbiased simulations. Furthermore, selective implementation of the transfer free energies of specific peptide groups, backbone, and side chains enables us to decouple their specific energetic contributions to the conformational changes of the protein. The approach herein developed can readily be extended to the investigation of complex matrices as well as to the characterization of protein aggregation. The MIST method is implemented in Plumed (ver. 2.8) as a separate module called SASA.

Methods for the Characterization of Protein Aggregates.

The physicochemical characterization of protein aggregates yields an important contribution to further our understanding on many diseases for which the formation of protein aggregates is one of the pathological hallmarks. On the other hand, bacterial inclusion bodies (IBs) have recently been shown to be highly pure proteinaceous aggregates of a few hundred nanometers, produced by recombinant bacteria supporting the biological activities of the embedded polypeptides. Despite the wide spectrum of uses of IBs as functional and biocompatible materials upon convenient engineering, very few is known about their physicochemical properties.In this chapter we present methods for the characterization of protein aggregates as particulate materials relevant to their physicochemical and nanoscale properties.Specifically, we describe the use of dynamic light scattering (DLS) for sizing, nanoparticle tracking analysis for sizing and counting, and zeta potential measurements for the determination of colloidal stability. To study the morphology of protein aggregates we present the use of atomic force microscopy (AFM) and scanning electron microscopy (SEM). Cryo-transmission electron microscopy (cryo-TEM) will be used for the determination of the internal structuration. Moreover, wettability and nanomechanical characterization can be performed using contact angle (CA) and force spectroscopic AFM (FS-AFM) measurements of the proteinaceous nanoparticles, respectively. Finally, the 4'4-dithiodipyridine (DTDP) method is presented as a way of relatively quantifying accessible sulfhydryl groups in the structure of the nanoparticle .The physical principles of the methods are briefly described and examples are given to help clarify capabilities of each technique.

Label-Free Infrared Spectroscopic Imaging Reveals Heterogeneity of β-Sheet Aggregates in Alzheimer's Disease.

The aggregation of the amyloid beta (Aβ) protein into plaques is a pathological feature of Alzheimer's disease (AD). While amyloid aggregates have been extensively studied in vitro, their structural aspects and associated chemistry in the brain are not fully understood. In this report, we demonstrate, using infrared spectroscopic imaging, that Aβ plaques exhibit significant heterogeneities in terms of their secondary structure and phospholipid content. We show that the capabilities of discrete frequency infrared imaging (DFIR) are ideally suited for characterization of amyloid deposits in brain tissues and employ DFIR to identify nonplaque β-sheet aggregates distributed throughout brain tissues. We further demonstrate that phospholipid-rich β-sheet deposits exist outside of plaques in all diseased tissues, indicating their potential clinical significance. This is the very first application of DFIR toward a characterization of protein aggregates in an AD brain and provides a rapid, label-free approach that allows us to uncover β-sheet heterogeneities in the AD, which may be significant for targeted therapeutic strategies in the future.

Online hyphenation of size-exclusion chromatography and gas-phase electrophoresis facilitates the characterization of protein aggregates.

Gas‐phase electrophoresis yields size distributions of polydisperse, aerosolized analytes based on electrophoretic principles. Nanometer‐sized, surface‐dry, single‐charged particles are separated in a high laminar sheath flow of particle‐free air and an orthogonal tunable electric field. Additionally, nano Electrospray Gas‐Phase Electrophoretic Mobility Molecular Analyzer (nES GEMMA) data are particle‐number based. Therefore, small particles can be detected next to larger ones without a bias, for example, native proteins next to their aggregates. Analyte transition from the liquid to the gas phase is a method inherent prerequisite. In this context, nonvolatile sample buffers influence results. In the worst case, the (bio‐)nanoparticle signal is lost due to an increased baseline and unspecific clustering of nonvolatile components. We present a novel online hyphenation of liquid chromatography and gas‐phase electrophoresis, coupling a size‐exclusion chromatography (SEC) column to an advanced nES GEMMA. Via this novel approach, it is possible to (i) separate analyte multimers already present in liquid phase from aggregates formed during the nES process, (ii) differentiate liquid phase and spray‐induced multimers, and (iii) to remove nonvolatile buffer components online before SEC–nES GEMMA analysis. Due to these findings, SEC–nES GEMMA has the high potential to help to understand aggregation processes in biological buffers adding the benefit of actual size determination for noncovalent assemblies formed in solution. As detection and characterization of protein aggregation in large‐scale pharmaceutical production or sizing of noncovalently bound proteins are findings directly related to technologically and biologically relevant situations, we proposed the presented method to be a valuable addition to LC‐MS approaches.

Pulsed Force Kelvin Probe Force Microscopy.

Measurement of the contact potential difference (CPD) and work functions of materials are important in analyzing their electronic structures and surface residual charges. Kelvin probe force microscopy (KPFM), an imaging technique of atomic force microscopy, has been widely used for surface potential and work function mapping at the nanoscale. However, the conventional KPFM variants are often limited in their spatial resolution to 30-100 nm under ambient conditions. The continuingly decreasing size and increasing complexity of photoactive materials and semiconductor devices will present future challenges in uncovering their nanometer-scale electrical properties through KPFM. Here, we introduce a KPFM technique based on the pulsed force mode of atomic force microscopy. Our technique, named pulsed force Kelvin Probe Force Microscopy (PF-KPFM), is a single-pass technique that utilizes the intrinsic Fermi level alignment between the AFM tip and the conductive sample without the need for an external oscillating voltage. Induced cantilever oscillations generated by a spontaneous redistribution of electrons between tip and sample are extracted and used to obtain the cantilever oscillation amplitude and to derive the surface potential. The spatial resolution of PF-KPFM is shown to be <10 nm under ambient conditions. The high spatial resolution surface potential mapping enables in situ determination of ohmic and nonohmic contacts between metals and semiconductors, mapping boundaries of ferroelectric domains of BaTiO3, as well as characterization of protein aggregates. High spatial resolution measurements with PF-KPFM will facilitate further studies directed at uncovering electrical properties for emerging photoactive materials, biological samples, and semiconductor devices.

Characterization of Protein Aggregation Using Hydrogel-Encapsulated nIR Fluorescent Nanoparticle Sensors.

The monitoring of biopharmaceutical critical quality attributes in-process, at both the process development and manufacturing stages, is necessary for the implementation of process analytical technology and quality-by-design principles. Among these attributes, it is important to monitor and control protein aggregation during the manufacturing of biological therapeutics to prevent adverse immunogenic responses and minimize negative impacts on drug deliverability. In this work, we explore hydrogel-encapsulated, label-free fluorescent nanosensors for the characterization of protein aggregation. A mathematical model is used to describe the diffusion and binding of a series of stressed pharmaceutical samples to such sensors, describing their dynamic response. We use mathematical modeling to map the influence of hydrogel properties on the separation performance, given the composition of UV-stressed IgG1 samples. Using this modified model, the compositions of light-stressed IgG1 samples were fit to experimental data and correlated with size-exclusion chromatography data. The results demonstrate the ability to detect the presence of high-molecular-weight protein species at a concentration as low as 1%. This work represents a significant step toward the development and deployment of rapid process analytical technologies for biopharmaceutical characterization.

An Ionic Liquid-Based Sample Preparation Method for Next-Stage Aggregate Proteomic Analysis.

A wide variety of proteomic methods have been applied for protein profiling of insoluble aggregates or inclusion bodies deposited in various cells or tissues. However, these are essentially optimized or modified classical protein chemistry techniques using conventional denaturing agents such as formic acid, urea, and sodium dodecyl sulfate (SDS). The use of these denaturants has several shortcomings, including limited solubilization, contamination, and restrictions on absolute sample quantity and throughput. Here, we describe an alternative proteomic sample preparation platform for widespread aggregation analysis. This approach combines two techniques, (1) the use of ionic liquid for protein solubilization and (2) the recently published microbead-based and organic-media-assisted proteolysis strategy (BOPs), into a single-tube workflow. We demonstrate that the combined approach (iBOPs) enabled the successful solubilization of heat-aggregated hen egg whites within 10 min and supported sensitive mass spectrometry (MS) analysis. The performance of the iBOPs system surpassed those of conventional detergents and chaotropes. Moreover, this technology enabled ultrasensitive proteomic characterization of protein aggregates deposited in individual Caenorhabditis elegans nematodes. We identified ubiquitin and other molecules as candidate stochastic factors whose accumulation levels varied among aging nematode individuals. The sensitivity and applicability of the present iBOPs make it especially attractive for next-stage aggregate proteomic analysis of various biological processes.

Rapid, quantitative determination of aggregation and particle formation for antibody drug conjugate therapeutics with label-free Raman spectroscopy

Lot release and stability testing of biologics are essential parts of the quality control strategy for ensuring therapeutic material dosed to patients is safe and efficacious, and consistent with previous clinical and toxicological experience. Characterization of protein aggregation is of particular significance, as aggregates may lose the intrinsic pharmaceutical properties as well as engage with the immune system instigating undesirable downstream immunogenicity. While important, real-time identification and quantification of subvisible particles in the monoclonal antibody (mAb) drug products remains inaccessible with existing techniques due to limitations in measurement time, sensitivity or experimental conditions. Here, owing to its exquisite molecular specificity, non-perturbative nature and lack of sample preparation requirements, we propose label-free Raman spectroscopy in conjunction with multivariate analysis as a solution to this unmet need. By leveraging subtle, but consistent, differences in vibrational modes of the biologics, we have developed a support vector machine-based regression model that provides fast, accurate prediction for a wide range of protein aggregations. Moreover, in blinded experiments, the model shows the ability to precisely differentiate between aggregation levels in mAb like product samples pre- and post-isothermal incubation, where an increase in aggregate levels was experimentally determined. In addition to offering fresh insights into mAb like product-specific aggregation mechanisms that can improve engineering of new protein therapeutics, our results highlight the potential of Raman spectroscopy as an in-line analytical tool for monitoring protein particle formation.

Characterization of Protein Aggregates, Silicone Oil Droplets, and Protein-Silicone Interactions Using Imaging Flow Cytometry

Protein therapeutic exposure to siliconized surfaces during manufacturing and storage has potential to induce protein aggregation or generate protein-silicone complexes that are potentially immunogenic. Consequently, assessing the stability and safety of protein therapeutics requires discrimination of protein and silicone oil particles and evaluation of protein–silicone oil interactions. Industry-established methods are challenged to distinguish protein aggregates from silicone oil droplets for particles smaller than 5 μm. In addition, emerging techniques for accessing particles in the sub-5 μm range are limited by low sampling volumes, narrow size ranges, complications such as clogging, and an inability to evaluate protein-silicone interactions. In this study, imaging flow cytometry was evaluated as a new method for discrimination of protein aggregates and silicone oil droplets, as well as for quantification of protein-silicone interactions. A simple and fast fluorescence labeling protocol using low concentrations of extrinsic dyes was developed. The results demonstrate that imaging flow cytometry can be used to discriminate fluorescently labeled protein aggregates and silicone oil droplets with greater than 95% accuracy, regardless of size, and protein–silicone oil interactions can be assessed qualitatively through inspection of image data or quantitatively using features extracted from the image data.

Evaluation of Temporal Aggregation Processes Using Spatial Intensity Distribution Analysis.

Small proteinaceous oligomeric species contribute to the formation of larger aggregates, a phenomenon that is of direct relevance to the characterization of protein aggregation in biopharmaceuticals and understanding the underlying processes contributing to neurodegenerative diseases.The ability to monitor in situ oligomerization and aggregation processes renders imaging and image analysis an attractive approach for gaining a mechanistic insight into early processes contributing to the formation of larger aggregates in disease models and biologics. The combination of image analysis tools enables the detection of both oligomeric and larger aggregate subtype in contrast to conventional kinetic-based approaches that lack the ability to resolve dimers from monomeric moieties in samples containing mixed populations.In this chapter, we describe the process for confocal time series image acquisition for monitoring the in situ loss of monomers, and the subsequent analysis pipeline using spatial intensity distribution analysis (SpIDA) to evaluate oligomer content.

Toward the Proper Biophysical Characterization of Aggregates in Biopharmaceuticals

Biopharmaceuticals are often formulated as liquid dosage forms. During manufacturing and storage, protein molecules and active pharmaceutical ingredients form aggregates due to various stresses, including shaking and agitation, as well as by contact with silicone oils coated on pre-fillable syringes. The diameter of protein aggregates ranges from 15-20 nm, and that of dimers comprising a large number of antibody molecules can be up to 100 μm. Among these aggregates, those with a diameter of <100 nm are called nanometer aggregates, while those ranging between 100 nm and 1 μm are called sub-micron aggregates, and those ranging between 1 and 100 μm are called micron aggregates. In the last ten years, aggregates have been studied to determine their physical characteristics and their impact on immunogenicity. As a result, novel analytical methods and instruments for such characterizations have been established for a majority of aggregates, including those that are difficult to evaluate. Here, the biophysical features of protein aggregates are explained, followed by an introduction to the different methods for aggregate characterization, including their advantages and actual results. Finally, future perspectives and expectations regarding the characterization of protein aggregates are proposed.

Holographic Characterization of Protein Aggregates in the Presence of Silicone Oil and Surfactants

Characterizing protein aggregates in the presence of silicone oil is a long standing challenge for the pharmaceutical industry. Silicone oil is often used as a lubricant in devices that deliver and store therapeutic protein products and has been linked to protein aggregation, which can compromise a drug’s effectiveness or cause autoimmune responses in patients. Most traditional technologies cannot quantitatively distinguish protein aggregates and silicone oil in their native formulations for sizes less than 5 μm. We use holographic video microscopy to study protein aggregation to demonstrate its capability to quantitatively distinguish protein aggregates and silicone oil in the presence of varying amounts of the surfactants SDS and polysorbate 80 in the size range of 0.5-10 μm without the need for dilution or special sample preparation. We show that SDS denatures proteins and stabilizes silicone oil. We also show that polysorbate 80 may limit protein aggregate formation if it is added to an IgG solution before introducing silicone oil.

Flow Cytometric Analysis of Protein Aggregates.

Misfolding of proteins often leads to aggregation. Accumulation of diverse protein aggregates in various cells, tissue and organs is the hallmark of many diseases, such as Alzheimer's disease and Parkinson's disease. The main objective of this study was to present a novel method of characterization of protein aggregates, associated with differential toxicity with different size and composition in vitro using flow cytometry. A Beckman Coulter Epics XL flow cytometer with argon ion laser operating at 488 nm was used for flow cytometry analysis. The voltage and the gain settings for individual channels were set at high voltage and gain for the detections of autofluorescence, fluorescence of adsorbed Congo red, forward scattering (FSC) and side scattering (SSC) intensities from the aggregates of proteins and nanoparticles. Each sample was analyzed to characterize and quantify the number of aggregates with a limit of maximum 20,000 events. The flow cytometry data were analyzed using Flowing software version 2.5.1 and Origin 8.0. Autofluorescence and scattering intensities could distinguish between amyloid and nonamyloid aggregates. Dot plots of both side scattering (SSC) and forward scattering (FSC) intensities also showed characteristic fingerprint of both the types of aggregates when compared with those of well known nanoparticles of oxides of Fe and Cu. This work reports a novel, simple and robust flow cytometric method of characterization of protein aggregates of different size and composition which would find wider application in characterization of biomolecular aggregates, in general.

In Vitro Analysis of α-Synuclein Amyloid Formation and Cross-Reactivity.

In vitro time-resolved characterization of protein aggregation into amyloid fibers and the effects of other proteins on the aggregation process are fundamentally important measurements to obtain a better understanding of the mechanisms contributing to neurodegeneration, as well as other diseases involving amyloid formation. Here, we describe how to perform in vitro aggregation experiments with α-synuclein, the amyloidogenic protein involved in Parkinson's disease, including how to assess the starting material, useful experimental/instrumental conditions, as well as how to set up cross-seeding and co-aggregation experiments. The high variability of data reported for in vitro α-synuclein amyloid formation may in part be explained by experimental differences.

Water Proton NMR: A Tool for Protein Aggregation Characterization.

Formulation stability is a critical attribute of any protein-based biopharmaceutical drug due to a protein's inherent tendency to aggregate. Advanced analytical techniques currently used for characterization of protein aggregates are prone to a number of limitations and usually require additional manipulations with the sample, such as dilution, separation, labeling, and use of special cuvettes. In the present work, we compared conventional techniques for the analysis of protein aggregates with a novel approach that employs the water proton transverse relaxation rate R2(1H2O). We explored differences in the sensitivity of conventional techniques, size-exclusion chromatography (SEC), microflow imaging (MFI), and dynamic light scattering (DLS), and water NMR (wNMR) toward the presence of monoclonal antibody aggregates generated by different stresses. We demonstrate that wNMR outperformed SEC, DLS, and MFI in that it was most consistently sensitive to increases in both soluble and insoluble aggregates, including subvisible particles. The simplicity of wNMR, its sensitivity, and possibility of noninvasive measurements are unique advantages that would permit its application for more efficient and higher throughput optimization of protein formulations.

Characterization of Protein Aggregation by Solid-State Nanopore

In this report, we use solid-state nanopore device to characterize native state aggregation of s-lactoglobulin variant A (βLGa) protein as a function of salt concentration, temperature, pH, and electric field strength. Silicon nitride nanopores used in this work, 5-20 nm in diameter, are fabricated by low energy ion beam sculpting method. The main component of a nanopore device is a nanopore supported by a silicon substrate which separates two PDMA chambers containing salt solution. When a charged protein molecule or a protein aggregate passes through a nanopore driven by an applied voltage across the nanopore chip, a protein aggregate that has larger volume than a single protein molecule,will generate larger current blockage, therefore a nanopore device can be used to characterize protein aggregation. We present data of βLGa self-association and aggregation at pH 4.6 as a function of temperature measured in 2M and 0.1M salt. The nanopore geometry is calibrated by a standard that has known geometry such as a long rod shaped dsDNA molecule. The volume of a translocating proteins or protein aggregates are estimated using the calibrated nanopore. We show that by using a reference dsDNA molecule, solid-state nanopore method is capable of measuring protein aggregation number and the aggregation number distribution in the conditions that is close to their native aqueous solution environment.

Automated 2D-HPLC method for characterization of protein aggregation with in-line fraction collection device.

Monoclonal antibodies are mainly produced by mammalian cell culture, which due to its complexity, results in a wide range of product variants/isoforms. With the growing implementation of Quality by Design (QbD) and Process Analytical Technology (PAT) in drug manufacturing, monitoring and controlling quality attributes within a predefined range during manufacturing may provide added consistency to product quality. To implement these concepts, more robust analytical tools could reduce the time needed for monitoring quality attributes during upstream processing. The formation of protein aggregates is one such quality attribute that can lead to safety and efficacy issues in the final drug product. Described in this study is a fully automated two-dimensional high performance liquid chromatography (2D-HPLC) method for characterizing protein aggregation of crude in-process bioreactor samples. It combines protein A purification and separation by size exclusion into a single analytical module that has the potential to be employed at-line within a bioprocessing system. This method utilizes a novel in-line fraction collection device allowing for the collection of up to twelve fractions from a single sample or peak which facilitates the subsequent linked analysis of multiple protein peaks of interest in one chromatography module.