Search Results (28)

Modern biotechnology has rapidly developed, and biotechnological drugs have become the center of global drug research and development as an important aspect of clinical treatment. These drugs have unique advantages, such as strong species specificity and prominent targeting, and they are widely used in the treatment of various intractable diseases. However, their complex molecular structure, poor stability, and significant heterogeneity make quality control much more difficult than that of traditional small-molecule drugs that require high-precision analytical methods. Analytical ultracentrifugation (AUC) technology was pioneered by Theodor Svedberg during the early 20th century, and it has become an indispensable biophysical tool through technological innovation. This technology has unique advantages for the quality control of biotechnological drugs, including non-destructive detection, high resolution, and wide applicability. Therefore, AUC has been extensively adopted for the characterization of various biological products. This review systematically summarizes AUC technology applications in major categories of biotechnological drugs, with the aim to provide technical guidance and promote the standardized application of AUC. Full article

Applications for machine learning (ML) and deep learning (DL) are constantly growing and have already been adopted in the field of particle measurement technology. Even though analytical (ultra-)centrifugation (AC/AUC) is a widely used technique for characterizing dispersed particle systems, ML and DL have not yet been applied in this area. Data evaluation and interpretation in AC/AUC can be challenging and often requires expert knowledge. DL models can help, but their development is limited by a lack of annotated training data. One solution is to generate and use synthetic data instead. In the first part of this study, a model was trained to synthesize data from experiments using a combination of Variational Autoencoder (VAE) and Generative Adversarial Networks (GANs). The results appear highly realistic. Novice users could distinguish real from synthetic samples with only 63% accuracy. Then, a classifier was trained on experimental AC data to categorize real-world examples based on their underlying separation kinetics, testing different DL architectures. After initial training, the models were further fine-tuned with synthetic AC data. ResNet34 models achieved the best performance with 94% accuracy, comparable to an AC expert (91%), while inexperienced users reached only 53%. In the second part of our study, a regression model was trained for the analysis of sedimentation coefficients. Therefore, various generative models were developed and evaluated for synthesizing AUC data based on numerically simulated sedimentation boundaries. The best results were achieved by combining VAE and GAN architectures with embedded physical constraints. However, the generative networks have so far led to additional smearing of the profiles, resulting in a broadening of the sedimentation coefficient distribution and indicating that further refinement is necessary. Full article

Antibody–drug conjugates (ADCs) comprise a monoclonal antibody covalently bound to a cytotoxic payload by a linker. ADCs minimize off-target effects on healthy tissues, leveraging the specificity of monoclonal antibodies to deliver cytotoxic drugs to the intended tumor site. ADCs can be prone to poor behavior, including aggregation and misfolding, leading to poor efficacy, impaired pharmacokinetics, and immunogenicity. It is advantageous to understand the developability and potential liabilities of a protein candidate prior to costly in vivo studies or clinical trials. This review summarizes biophysical and structural techniques used to characterize ADCs and introduces emerging techniques aimed at accurately assessing the developability of protein candidates. Stability is commonly assayed using techniques like differential scanning calorimetry (DSC), differential scanning fluorimetry (DSF), or spectroscopic probes such as circular dichroism and intrinsic fluorescence. Drug-to-antibody ratio (DAR) is a critical parameter that can be measured using absorbance spectroscopy or chromatographic analysis. Aggregation and self-association can be probed using scattering techniques such as dynamic light scattering (DLS), static light scattering (SLS), and size exclusion chromatography–multi-angle light scattering (SEC-MALS), as well as more specialized approaches such as fluorescence correlation spectroscopy (FCS) and analytical ultracentrifugation (AUC). Mass spectrometry (MS) provides extremely valuable insight into stability, covalent modifications, and, through approaches like hydrogen–deuterium exchange (HDX-MS), structural dynamics of ADCs. Looking forward, the use of biophysical assays in ex vivo matrices and strategic use of artificial intelligence/machine learning (AI/ML) approaches are likely to advance the efficient and rapid development of ADCs and other next-generation protein therapeutics. Full article

Background: As essential biomolecules composed of proteins and carbohydrate moieties, glycoproteins play pivotal roles in numerous biological processes. The glycosylation level plays a crucial role in determining the functionality of glycoproteins. Therefore, the precise quantification of glycan components in proteins holds significant importance for research on and development of polysaccharide–protein-conjugated vaccines. Methods: In this study, a novel glycan quantification approach was developed, leveraging analytical ultracentrifugation (AUC) technology that synergistically utilizes ultraviolet wavelength absorption and interference data to directly determine glycan mass fractions in glycoproteins. Results: This methodology expands the analytical framework for glycoproteins while retaining the intrinsic advantages of AUC, enabling analysis in native states with high reproducibility as indicated by low standard deviation across replicates. Conclusions: The approach was implemented in our proprietary AUC data analysis software called AUCAgent (v1.8.8), providing a new method for glycoprotein quantification and polysaccharide ratio determination in polysaccharide-protein-conjugate vaccines. Full article

Adeno-associated viruses (AAVs) are a leading vector for gene therapy, yet their clinical utility is limited by the lack of robust quality control methods to distinguish between empty (AAV_empty), partially loaded (AAV_partial), and fully DNA loaded (AAV_full) capsids. Current analytical techniques provide partial insights but remain limited in sensitivity, throughput, or resolution. Here we present a multimodal plasmonic nanopore sensor that integrates optical trapping with electrical resistive-pulse sensing to characterize AAV9 capsids at the single-particle level in tens of μL sample volumes and fM range concentrations. As a model system, we employed AAV9 capsids not loaded with DNA, capsids loaded with a self-complementary 4.7 kbp DNA (AAV_scDNA), and ones loaded with single-stranded 4.7 kbp DNA (AAV_ssDNA). Ground-truth validation was performed with analytical ultracentrifugation (AUC). Nanosensor data were acquired concurrently for optical step changes (occurring at AAV trapping and un-trapping) both in transmittance and reflectance geometries, and electrical nanopore resistive pulse signatures, making for a total of five data dimensions. The acquired data was then filtered and clustered by Gaussian mixture models (GMMs), accompanied by spectral clustering stability analysis, to successfully separate between AAV species based on their DNA load status (AAV_empty, AAV_partial, AAV_full) and DNA load type (AAV_scDNA versus AAV_ssDNA). The motivation for quantifying the AAV_empty and AAV_partial population fractions is that they reduce treatment efficacy and increase immunogenicity. Likewise, the motivation to identify AAV_scDNA population fractions is that these have much higher transfection rates. Importantly, the results showed that the nanosensor could differentiate between AAV_scDNA and AAV_ssDNA despite their identical masses. In contrast, AUC could not differentiate between AAV_scDNA and AAV_ssDNA. An equimolar mixture of AAV_scDNA, AAV_ssDNA and AAV_empty was also measured with the sensor, and the results showed the expected population fractions, supporting the capacity of the method to differentiate AAV load status in heterogeneous solutions. In addition, less common optical and electrical signal signatures were identified in the acquired data, which were attributed to debris, rapid entry re-entry to the optical trap, or weak optical trap exits, representing critical artifacts to recognize for correct interpretation of the data. Together, these findings establish plasmonic nanopore sensing as a promising platform for quantifying AAV DNA loading status and genome type with the potential to extend ultra-sensitive single-particle characterization beyond the capabilities of existing methods. Full article

MRNA-based therapeutics and vaccines represent a rapidly expanding frontier in biomedical innovation, with lipid nanoparticles (LNPs) serving as a clinically validated delivery platform. This study explores critical quality attributes of LNP-mRNA formulations, with a particular focus on in vitro biological activity, a key quality attribute of vaccine activity and batch-to-batch consistency. We discuss the importance of optimizing both LNP components and mRNA structure, highlighting recent advances in formulation strategies. Furthermore, we examine the influence of factors such as cell-line selection, experimental design, storage conditions, and targeted cellular delivery on transduction efficiency. Our findings underscore the need for standardized in vitro assays and process-integrated monitoring to support the scalable development and regulatory assessment of mRNA-based therapies. Full article

The search for sustainable, economically viable, and effective plant protection strategies against pathogenic bacteria, fungi, and viruses is a major challenge in modern agricultural practices. Chitosan (CS) is an abundant cationic natural biopolymer known for its biocompatibility, low toxicity, and antimicrobial properties. Its potential use in agriculture for pathogen control is a promising alternative to traditional chemical fertilisers and pesticides, which raise concerns regarding public health, environmental protection, and pesticide resistance. This study focused on the preparation of chitosan nanoparticles (CS-NPs) through cross-linking with organic molecules, such as tannic acid (TA). Various formulations were explored for the development of stable nanoscale particles having encapsulation capabilities towards low compounds of varying polarity and with potential agricultural applications relevant to plant health and growth. The solution properties of the NPs were assessed using dynamic and electrophoretic light scattering (DLS and ELS); their morphology was observed through atomic force microscopy (AFM), while analytical ultracentrifugation (AUC) measurements provided insights into their molar mass. Their properties proved to be primarily influenced by the concentration of CS, which significantly affected its intrinsic conformation. Additional structural insights were obtained via infrared and UV–Vis spectroscopic measurements, while detailed fluorescence analysis with the use of three different probes, as model cargo molecules, provided information regarding the hydrophobic and hydrophilic microdomains within the particles. Full article

Cry toxins from Bacillus thuringiensis are effective biopesticides that kill lepidopteran pests, replacing chemical pesticides that indiscriminately attack both target and non-target organisms. However, resistance in susceptible pests is an emerging problem. B. thuringiensis also produces vegetative insecticidal protein (Vip3A), which can kill insect targets in the same group as Cry toxins but using different host receptors, making the combined application of Cry and Vip3A an exciting possibility. Vip3A toxicity requires the formation of a homotetramer. Hence, screening of Vip3A mutants for increased stability requires orthogonal biophysical assays that can test both tetrameric integrity and monomeric robustness. For this purpose, we have used herein for the first time a combination of analytical ultracentrifugation (AUC), mass photometry (MP), differential static light scattering (DSLS) and differential scanning fluorimetry (DSF) to test five mutants at domains I and II. Although all mutants appeared more stable than the wild type (WT) in DSLS, mutants that showed more dissociation into dimers in MP and AUC experiments also showed earlier thermal unfolding by DSF at domains IV–V. All of the mutants were less toxic than the WT, but toxicity was highest for domain II mutations N242C and F229Y. Activation of the protoxin was complete and resulted in a form with a lower sedimentation coefficient. Future high-resolution structural data may lead to a deeper understanding of the increased stability that will help with rational design while retaining native toxicity. Full article

We isolated a stress-tolerance-related gene from a genome library of Synechococcus sp. NKBG15041c. The expression of the gene in E. coli confers resistance against various stresses. The gene encodes a MoxR AAA+ ATPase, which was designated SyMRP since it belongs to the MRP subfamily. The recombinant SyMRP showed weak ATPase activity and protected citrate synthase from thermal aggregation. Interestingly, the chaperone activity of SyMRP is ATP-dependent. SyMRP exists as a stable hexamer, and ATP-dependent conformation changes were not detected via analytical ultracentrifugation (AUC) or small-angle X-ray scattering (SAXS). Although the hexameric structure predicted by AlphaFold 3 was the canonical flat-ring structure, the structures observed by atomic force microscopy (AFM) and transmission electron microscopy (TEM) were not the canonical ring structure. In addition, the experimental SAXS profiles did not show a peak that should exist in the symmetric-ring structure. Therefore, SyMRP seems to form a hexameric structure different from the canonical hexameric structure of AAA+ ATPase. Full article

Recombinant adeno-associated viruses (rAAVs) play a pivotal role in the treatment of genetic diseases. However, current production and purification processes yield AAV-based preparations that often contain unwanted empty, partially filled or damaged viral particles and impurities, including residual host cell DNA and proteins, plasmid DNA, and viral aggregates. To precisely understand the composition of AAV preparations, we systematically compared four different single-stranded AAV (ssAAV) and self-complementary (scAAV) fractions extracted from the CsCl ultracentrifugation gradient using established methods (transduction efficiency, analytical ultracentrifugation (AUC), quantitative and digital droplet PCR (qPCR and ddPCR), transmission electron microscopy (TEM) and enzyme-linked immunosorbent assay (ELISA)) alongside newer techniques (multiplex ddPCR, multi-angle light-scattering coupled to size-exclusion chromatography (SEC-MALS), multi-angle dynamic light scattering (MADLS), and high-throughput sequencing (HTS)). Suboptimal particle separation within the fractions resulted in unexpectedly similar infectivity levels. No single technique could simultaneously provide comprehensive insights in the presence of both bioactive particles and contaminants. Notably, multiplex ddPCR revealed distinct vector genome fragmentation patterns, differing between ssAAV and scAAV. This highlights the urgent need for innovative analytical and production approaches to optimize AAV vector production and enhance therapeutic outcomes. Full article

The approval of safe and effective LNP-mRNA vaccines during the SARS-CoV-2 pandemic is catalyzing the development of the next generation of mRNA therapeutics. Proper characterization methods are crucial for assessing the quality and efficacy of these complex formulations. Here, we show that analytical ultracentrifugation (AUC) can measure, simultaneously and without any sample preparation step, the sedimentation coefficients of both the LNP-mRNA formulation and the mRNA molecules. This allows measuring several quality attributes, such as particle size distribution, encapsulation efficiency and density of the formulation. The technique can also be applied to study the stability of the formulation under stress conditions and different buffers. Full article

As nanoparticle syntheses on a large scale usually yield products with broad size and shape distributions, the properties of nanoparticle-based products need to be tuned after synthesis by narrowing the size and shape distributions or via the removal of undesired fractions. The development of property-selective classification processes requires a universal framework for the quantitative evaluation of multi-dimensional particle fractionation processes. This framework must be applicable to any property and any particle classification process. We extended the well-known one-dimensional methodology commonly used for describing particle size distributions and fractionation processes to the multi-dimensional case to account for the higher complexity of the property distribution and separation functions. In particular, multi-dimensional lognormal distributions are introduced and applied to diameter and length distributions of gold nanorods. The fractionation of nanorods via centrifugation and by orthogonal centrifugal and electric forces is modeled. Moreover, we demonstrate that analytical ultracentrifugation with a multi-wavelength detector (MWL-AUC) is a fast and very accurate method for the measurement of two-dimensional particle size distributions in suspension. The MWL-AUC method is widely applicable to any class of nanoparticles with size-, shape- or composition-dependent optical properties. In addition, we obtained distributions of the lateral diameter and the number of layers of molybdenum disulfide nanosheets via stepwise centrifugation and spectroscopic evaluation of the size fractions. Full article

The enterovirus A71 (EV71) inactivated vaccine is an effective intervention to control the spread of the virus and prevent EV71-associated hand, foot, and mouth disease (HFMD). It is widely administered to infants and children in China. The empty particles (EPs) and full particles (FPs) generated during production have different antigenic and immunogenic properties. However, the antigen detection methods currently used were established without considering the differences in antigenicity between EPs and FPs. There is also a lack of other effective analytical methods for detecting the different particle forms, which hinders the consistency between batches of products. In this study, we analyzed the application of sedimentation velocity analytical ultracentrifugation (SV-AUC) in characterizing the EPs and FPs of EV71. Our results showed that the proportions of the two forms could be quantified simultaneously by SV-AUC. We also determined the repeatability and accuracy of this method and found that both parameters were satisfactory. We assessed SV-AUC for bulk vaccine quality control, and our findings indicated that SV-AUC can be used effectively to analyze the percentage of EPs and FPs and monitor the consistency of the process to ensure the quality of the vaccine. Full article

Mass photometry (MP) is a fast and simple analysis method for the determination of the proportions of subpopulations in an AAV sample. It is label-free and requires minimal sample volumes between 5–10 µL, which makes it a promising candidate over orthogonal techniques such as analytical ultracentrifugation (AUC), cryo-transmission electron microscopy (Cryo-TEM) or charge-detection mass spectrometry (CDMS). However, these methods are limited in their application to purified samples only. Here we developed a purification step based on single-domain monospecific antibody fragments immobilised on either a poly(styrene-divinylbenzene) resin or on magnetic beads prior to MP analysis that allows the quantification of empty, partially filled, full and overfull AAV vectors in crude cell extracts. This is aimed at identifying potentially promising harvest conditions that yield large numbers of filled AAV vectors during the early stages of the viral vector development platform, e.g., the type of transfection reagent used. Furthermore, we provide a direct comparison of the automated and manual handling of the mass photometer with respect to the quantities of AAV subspecies, molar mass of the capsid and payload, and highlight the differences between the “buffer-free” sample measurement and the “buffer-dilution” mode. In addition, we provide information on which candidates to use for calibration and demonstrate the limitations of the mass photometer with respect to the estimation of the capsid titer. Full article

Analytical ultracentrifugation (AUC) analysis shows that the SARS-CoV-2 trimeric Spike (S) protein adopts different quaternary conformations in solution. The relative abundance of the “open” and “close” conformations is temperature-dependent, and samples with different storage temperature history have different open/close distributions. Neutralizing antibodies (NAbs) targeting the S receptor binding domain (RBD) do not alter the conformer populations; by contrast, a NAb targeting a cryptic conformational epitope skews the Spike trimer toward an open conformation. The results highlight AUC, which is typically applied for molecular mass determination of biomolecules as a powerful tool for detecting functionally relevant quaternary protein conformations. Full article