The role of the medium in the effective-sphere interpretation of holographic particle characterization data

Improving the Signal-to-Noise Ratio of Axial Displacement Measurements of Microspheres Based on Compound Digital Holography Microscopy Combined with the Reconstruction Centering Method

In 3D microsphere tracking, unlike in-plane motion that can be measured directly by a microscope, axial displacements are resolved by optical interference or a diffraction model. As a result, the axial results are affected by the environmental noise. The immunity to environmental noise increases with measurement accuracy and the signal-to-noise ratio (SNR). In compound digital holography microscopy (CDHM)-based measurements, precise identification of the tracking marker is critical to ensuring measurement precision. The reconstruction centering method (RCM) was proposed to suppress the drawbacks caused by installation errors and, at the same time, improve the correct identification of the tracking marker. The reconstructed center is considered to be the center of the microsphere, rather than the center of imaging in conventional digital holographic microscopy. This method was verified by simulation of rays tracing through microspheres and axial moving experiments. The axial displacements of silica microspheres with diameters of 5 μm and 10 μm were tested by CDHM in combination with the RCM. As a result, the SNR of the proposed method was improved by around 30%. In addition, the method was successfully applied to axial displacement measurements of overlapped microspheres with a resolution of 2 nm.

Monitoring polysorbate 80 degradation in protein solutions using Total Holographic Characterization

The degradation of polysorbate surfactants can limit the shelf life of biologic pharmaceutical products. Polysorbate is susceptible to degradation via either oxidation or hydrolysis pathways which releases free fatty acids (FFA) and other complex polymers. Degradants from Polysorbate 80 (PS80) can form particles and impact drug product quality. PS80 degradation products appear at low concentrations, and their refractive indexes are similar to that of the buffer, making them very challenging to detect. Furthermore, aggregates of FFA are similar in size and refractive index to protein aggregates adding complexity to characterizing these particles in protein solutions. Total Holographic Characterization (THC) is used in this work to characterize FFA particles of oleic acid and linoleic acid, the two most common degradation products of PS80. We demonstrate that the characteristic THC profile of the FFA oleic acid emulsion droplets can be used to monitor the degradation of PS80. THC can detect oleic acid at a concentration down to less than 100 ng/mL. Using the characteristic THC signal of oleic acid as a marker, the degradation of PS80 in protein solutions can be monitored quantitatively even in the presence of other contaminants of the same size, including silicone oil emulsion droplets and protein aggregates.

Dual-Angle Interferometric Scattering Microscopy for Optical Multiparametric Particle Characterization

Traditional single-nanoparticle sizing using optical microscopy techniques assesses size via the diffusion constant, which requires suspended particles to be in a medium of known viscosity. However, these assumptions are typically not fulfilled in complex natural sample environments. Here, we introduce dual-angle interferometric scattering microscopy (DAISY), enabling optical quantification of both size and polarizability of individual nanoparticles (radius <170 nm) without requiring a priori information regarding the surrounding media or super-resolution imaging. DAISY achieves this by combining the information contained in concurrently measured forward and backward scattering images through twilight off-axis holography and interferometric scattering (iSCAT). Going beyond particle size and polarizability, single-particle morphology can be deduced from the fact that the hydrodynamic radius relates to the outer particle radius, while the scattering-based size estimate depends on the internal mass distribution of the particles. We demonstrate this by differentiating biomolecular fractal aggregates from spherical particles in fetal bovine serum at the single-particle level.

Aberration compensation for enhanced holographic particle characterization

Holographic particle characterization treats holographic microscopy of colloidal particles as an inverse problem whose solution yields the diameter, refractive index and three-dimensional position of each particle in the field of view, all with exquisite precision. This rich source of information on the composition and dynamics of colloidal dispersions has created new opportunities for fundamental research in soft-matter physics, statistical physics and physical chemistry, and has been adopted for product development, quality assurance and process control in industrial applications. Aberrations introduced by real-world imaging conditions, however, can degrade performance by causing systematic and correlated errors in the estimated parameters. We identify a previously overlooked source of spherical aberration as a significant source of these errors. Modeling aberration-induced distortions with an operator-based formalism identifies a spatially varying phase factor that approximately compensates for spherical aberration in recorded holograms. Measurements on model colloidal dispersions demonstrate that phase-only aberration compensation greatly improves the accuracy of holographic particle characterization without significantly affecting measurement speed for high-throughput applications.

Anomalous tumbling of colloidal ellipsoids in Poiseuille flows

Shear flows cause aspherical colloidal particles to tumble so that their orientations trace out complex trajectories known as Jeffery orbits. The Jeffery orbit of a prolate ellipsoid is predicted to align the particle's principal axis preferentially in the plane transverse to the axis of shear. Holographic microscopy measurements reveal instead that colloidal ellipsoids' trajectories in Poiseuille flows strongly favor an orientation inclined by roughly π/8 relative to this plane. This anomalous observation is consistent with at least two previous reports of colloidal rods and dimers of colloidal spheres in Poiseuille flow and therefore appears to be a generic, yet unexplained feature of colloidal transport at low Reynolds numbers.

Dynamic frustrated charge hotspots created by charge density modulation sequester globular proteins into complex coacervates

This study presents a simple strategy for the sequestration of globular proteins as clients into synthetic polypeptide-based complex coacervates as a scaffold, thereby recapitulating the scaffold-client interaction found in biological condensates. Considering the low net charges of scaffold proteins participating in biological condensates, the linear charge density (σ) on the polyanion, polyethylene glycol-b-poly(aspartic acids), was reduced by introducing hydroxypropyl or butyl moieties as a charge-neutral pendant group. Complex coacervate prepared from the series of reduced-σ polyanions and the polycation, homo-poly-l-lysine, could act as a scaffold that sequestered various globular proteins with high encapsulation efficiency (>80%), which sometimes involved further agglomerations in the coacervates. The sequestration of proteins was basically driven by electrostatic interaction, and therefore depended on the ionic strength and charges of the proteins. However, based on the results of polymer partitioning in the coacervate in the presence or absence of proteins, charge ratios between cationic and anionic polymers were maintained at the charge ratio of unity. Therefore, the origin of the electrostatic interaction with proteins is considered to be dynamic frustrated charges in the complex coacervates created by non-neutralized charges on polymer chains. Furthermore, fluorescence recovery after photobleaching (FRAP) measurements showed that the interaction of side-chains and proteins changed the dynamic property of coacervates. It also suggested that the physical properties of the condensate are tunable before and after the sequestration of globular proteins. The present rational design approach of the scaffold-client interaction is helpful for basic life-science research and the applied frontier of artificial organelles.

Machine learning enables precise holographic characterization of colloidal materials in real time

Holographic particle characterization uses in-line holographic video microscopy to track and characterize individual colloidal particles dispersed in their native fluid media. Applications range from fundamental research in statistical physics to product development in biopharmaceuticals and medical diagnostic testing. The information encoded in a hologram can be extracted by fitting to a generative model based on the Lorenz-Mie theory of light scattering. Treating hologram analysis as a high-dimensional inverse problem has been exceptionally successful, with conventional optimization algorithms yielding nanometer precision for a typical particle's position and part-per-thousand precision for its size and index of refraction. Machine learning previously has been used to automate holographic particle characterization by detecting features of interest in multi-particle holograms and estimating the particles' positions and properties for subsequent refinement. This study presents an updated end-to-end neural-network solution called CATCH (Characterizing and Tracking Colloids Holographically) whose predictions are fast, precise, and accurate enough for many real-world high-throughput applications and can reliably bootstrap conventional optimization algorithms for the most demanding applications. The ability of CATCH to learn a representation of Lorenz-Mie theory that fits within a diminutive 200 kB hints at the possibility of developing a greatly simplified formulation of light scattering by small objects.

The Strengths of Total Holographic Video Microscopy in Detecting Sub-Visible Protein Particles in Biopharmaceuticals: A Comparison to Flow Imaging and Resonant Mass Measurement

Determination of subvisible particle (SVP) content in biopharmaceuticals is a prerequisite to ensure the quality of liquid biopharmaceutical products. Here, we present a comparison of the recently introduced holographic video microscopy (total holographic characterization, THC) with two orthogonal and well-established analytical technologies: micro flow imaging (MFI) and resonant mass measurement (RMM). The capabilities of the THC were investigated under conditions commonly applied in drug product development. Three different antibody products were used at different concentrations and formulations to cover a wide range of realistic use-cases. The comparison was particularly focused on protein aggregates to investigate the applicability of THC to this critical class of particles in drug product development. Protein concentrations up to 100 mg/ml were investigated covering a broad range of viscosity and refractive indices, both important parameters in particle detection. The comparison reveals that THC is highly sensitive to detect protein aggregates in a size range from 0.5 µm to 10 µm. THC shows a significant superiority to FI and RMM in detecting heterogenous protein aggregates which often appear as transparent and porous particles. Additionally, THC needs very small sample amount of about 30 µl and short measurement times, making it applicable for early development stages and high-throughput approaches. These results show that THC is a valuable supplement to the existing particle characterization method portfolio in drug product development.

Multi-angle holographic characterization of individual fractal aggregates

Holographic particle characterization uses quantitative analysis of holographic microscopy data to precisely and rapidly measure the diameter and refractive index of individual colloidal spheres in their native media. When this technique is applied to inhomogeneous or aspherical particles, the measured diameter and refractive index represent properties of an effective sphere enclosing each particle. Effective-sphere analysis has been applied successfully to populations of fractal aggregates, yielding an overall fractal dimension for the population as a whole. Here, we demonstrate that holographic characterization also can measure the fractal dimensions of an individual fractal cluster by probing how its effective diameter and refractive index change as it undergoes rotational diffusion. This procedure probes the structure of a cluster from multiple angles and thus constitutes a form of tomography. Here we demonstrate and validate this effective-sphere interpretation of aspherical particles' holograms through experimental studies on aggregates of silica nanoparticles grown under a range of conditions.

Holographic analysis of colloidal spheres sedimenting in horizontal slit pores

The mobility of a colloidal particle in a slit pore is modified by the particle's hydrodynamic coupling to the bounding surfaces and therefore depends on the particle's position within the pore and its direction of motion. We report holographic particle tracking measurements of colloidal particles' diffusion and sedimentation between parallel horizontal walls that yield the mobility for motions perpendicular to the walls, including its dependence on height within the channel. These measurements complement previous studies that probed colloidal mobility parallel to confining surfaces. When interpreted with effective-medium theory, holographic characterization measurements yield estimates for the sedimenting spheres' densities that can be compared with kinematic values to draw insights into the spheres' compositions. This comparison suggests, for example, that the silica spheres used in this study are slightly porous, but that their pores are too small for water to penetrate.

Label-free viability assay using in-line holographic video microscopy

Total holographic characterization (THC) is presented here as an efficient, automated, label-free method of accurately identifying cell viability. THC is a single-particle characterization technology that determines the size and index of refraction of individual particles using the Lorenz-Mie theory of light scattering. Although assessment of cell viability is a challenge in many applications, including biologics manufacturing, traditional approaches often include unreliable labeling with dyes and/or time consuming methods of manually counting cells. In this work we measured the viability of Saccharomyces cerevisiae yeast in the presence of various concentrations of isopropanol as a function of time. All THC measurements were performed in the native environment of the sample with no dilution or addition of labels. Holographic measurements were made with an in-line holographic microscope using a 40[Formula: see text] objective lens with plane wave illumination. We compared our results with THC to manual counting of living and dead cells as distinguished with trypan blue dye. Our findings demonstrate that THC can effectively distinguish living and dead yeast cells by the index of refraction of individual cells.

Measuring the refractive index and sub-nanometre surface functionalisation of nanoparticles in suspension

Direct measurements to determine the degree of surface coverage of nanoparticles by functional moieties are rare, with current strategies requiring a high level of expertise and expensive equipment. Here, a practical method to determine the ratio of the volume of the functionalisation layer to the particle volume based on measuring the refractive index of nanoparticles in suspension is proposed. As a proof of concept, this technique is applied to poly(methyl methacrylate) (PMMA) nanoparticles and semicrystalline carbon dots functionalised with different surface moieties, yielding refractive indices that are commensurate to those from previous literature and Mie theory. In doing so, it is demonstrated that this technique is able to optically detect differences in surface functionalisation or composition of nanometre-sized particles. This non-destructive and rapid method is well-suited for in situ industrial particle characterisation and biological applications.

Light scattering from colloidal aggregates on a hierarchy of length scales

Disordered dielectrics with structural correlations on length scales comparable to visible light wavelengths exhibit interesting optical properties. Such materials exist in nature, leading to beautiful structural non-iridescent color, and they are also increasingly used as building blocks for optical materials and coatings. In this article, we explore the angular resolved single-scattering properties of micron-sized, disordered colloidal assemblies. The aggregates act as structurally colored supraparticles or as building blocks for macroscopic photonic glasses. We obtain first experimental data for the differential scattering and transport cross-section. Based on existing macroscopic models, we develop a theoretical framework to describe the scattering from densely packed colloidal assemblies on a hierarchy of length scales.

Holographic characterization and tracking of colloidal dimers in the effective-sphere approximation

An in-line hologram of a colloidal sphere can be analyzed with the Lorenz-Mie theory of light scattering to measure the sphere's three-dimensional position with nanometer-scale precision while also measuring its diameter and refractive index with part-per-thousand precision. Applying the same technique to aspherical or inhomogeneous particles yields measurements of the position, diameter and refractive index of an effective sphere that represents an average over the particle's geometry and composition. This effective-sphere interpretation has been applied successfully to porous, dimpled and coated spheres, as well as to fractal clusters of nanoparticles, all of whose inhomogeneities appear on length scales smaller than the wavelength of light. Here, we combine numerical and experimental studies to investigate effective-sphere characterization of symmetric dimers of micrometer-scale spheres, a class of aspherical objects that appear commonly in real-world dispersions. Our studies demonstrate that the effective-sphere interpretation usefully distinguishes small colloidal clusters in holographic characterization studies of monodisperse colloidal spheres. The effective-sphere estimate for a dimer's axial position closely follows the ground truth for its center of mass. Trends in the effective-sphere diameter and refractive index, furthermore, can be used to measure a dimer's three-dimensional orientation. When applied to colloidal dimers transported in a Poiseuille flow, the estimated orientation distribution is consistent with expectations for Brownian particles undergoing Jeffery orbits.

Oil-Immersion Flow Imaging Microscopy for Quantification and Morphological Characterization of Submicron Particles in Biopharmaceuticals

Flow imaging microscopy (FIM) is widely used to analyze subvisible particles starting from 2 μm in biopharmaceuticals. Recently, an oil-immersion FIM system emerged, the FlowCam Nano, designed to enable the characterization of particle sizes even below 2 μm. The aim of our study was to evaluate oil-immersion FIM (by using FlowCam Nano) in comparison to microfluidic resistive pulse sensing and resonant mass measurement for sizing and counting of particles in the submicron range. Polystyrene beads, a heat-stressed monoclonal antibody formulation and a silicone oil emulsion, were measured to assess the performance on biopharmaceutical relevant samples, as well as the ability to distinguish particle types based on instrument-derived morphological parameters. The determination of particle sizes and morphologies suffers from inaccuracies due to a low image contrast of small particles and light-scattering effects. The ill-defined measured volume impairs an accurate concentration determination. Nevertheless, FlowCam Nano in its current design complements the limited toolbox of submicron particle analysis of biopharmaceuticals by providing particle images in a size range that was previously not accessible with commercial FIM instruments.

Holographic immunoassays: direct detection of antibodies binding to colloidal spheres

The size of a probe bead reported by holographic particle characterization depends on the proportion of the surface area covered by bound target molecules and so can be used as an assay for molecular binding. We validate this technique by measuring the kinetics of irreversible binding for the antibodies immunoglobulin G (IgG) and immunoglobulin M (IgM) as they attach to micrometer-diameter colloidal beads coated with protein A. These measurements yield the antibodies' binding rates and can be inverted to obtain the concentration of antibodies in solution. Holographic molecular binding assays therefore can be used to perform fast quantitative immunoassays that are complementary to conventional serological tests.

Interpreting holographic molecular binding assays with effective medium theory

Holographic molecular binding assays use holographic video microscopy to directly detect molecules binding to the surfaces of micrometer-scale colloidal beads by monitoring associated changes in the beads' light-scattering properties. Holograms of individual spheres are analyzed by fitting to a generative model based on the Lorenz-Mie theory of light scattering. Each fit yields an estimate of a probe bead's diameter and refractive index with sufficient precision to watch a population of beads grow as molecules bind. Rather than modeling the molecular-scale coating, however, these fits use effective medium theory, treating the coated sphere as if it were homogeneous. This effective-sphere analysis is rapid and numerically robust and so is useful for practical implementations of label-free immunoassays. Here, we assess how measured effective-sphere properties reflect the actual properties of molecular-scale coatings by modeling coated spheres with the discrete-dipole approximation and analyzing their holograms with the effective-sphere model.

Quantitative Differentiation of Protein Aggregates From Other Subvisible Particles in Viscous Mixtures Through Holographic Characterization

We demonstrate the use of holographic video microscopy to detect individual subvisible particles dispersed in biopharmaceutical formulations and to differentiate them based on material characteristics measured from their holograms. The result of holographic analysis is a precise and accurate measurement of the concentrations and size distributions of multiple classes of subvisible contaminants dispersed in the same product simultaneously. We demonstrate this analytical technique through measurements on model systems consisting of human IgG aggregates in the presence of common contaminants such as silicone oil emulsion droplets and fatty acids. Holographic video microscopy also clearly identifies metal particles and air bubbles. Being able to differentiate and characterize the individual components of such heterogeneous dispersions provides a basis for tracking other factors that influence the stability of protein formulations including handling and degradation of surfactant and other excipients.