High sensitivity chemiluminescence enzyme immunoassay for detecting staphylococcal enterotoxin A in multi-matrices

In this study, detection of staphylococcal enterotoxin A (SEA) in multi-matrices using a highly sensitive and specific microplate chemiluminescence enzyme immunoassay (CLEIA) has been established. A pair of monoclonal antibodies (mAbs) was selected from 37 anti-SEA mAbs by pairwise analysis, and the experimental conditions of the CLEIA were optimized. This CLEIA exhibited high performance with a wide dynamic range from 6.4 pg mL⁻¹ to 1600 pg mL⁻¹, and the measured low limit of detection (LOD) was 3.2 pg mL⁻¹. No cross-reactivity was observed when this method was applied to test SEB, SEC1, and SED. It has also been successfully applied for analyzing SEA in a variety of environmental, biological, and clinical matrices, such as sewage, tap water, river water, roast beef, peanut butter, cured ham, 10% nonfat dry milk, milk, orange juice, human urine, and serum. Thus, the highly sensitive and SEA-specific CLEIA should make it attractive for quantifying SEA in public health and diagnosis in near future.     

Model-Based Optimization of a Fed-Batch Bioreactor for mAb Production Using a Hybridoma Cell Culture

Production of monoclonal antibodies (mAbs) is a well-known method used to synthesize a large number of identical antibodies, which are molecules of huge importance in medicine. Due to such reasons, intense efforts have been invested to maximize the mAbs production in bioreactors with hybridoma cell cultures. However, the optimal control of such sensitive bioreactors is an engineering problem difficult to solve due to the large number of state-variables with highly nonlinear dynamics, which often translates into a non-convex optimization problem that involves a significant number of decision (control) variables. Based on an adequate kinetic model adopted from the literature, this paper focuses on developing an in-silico (model-based, offline) numerical analysis of a fed-batch bioreactor (FBR) with an immobilized hybridoma culture to determine its optimal feeding policy by considering a small number of control variables, thus ensuring maximization of mAbs production. The obtained time stepwise optimal feeding policies of FBR were proven to obtain better performances than those of simple batch operation (BR) for all the verified alternatives in terms of raw material consumption and mAbs productivity. Several elements of novelty (i–iv) are pointed out in the “conclusions” section (e.g., considering the continuously added biomass as a control variable during FBR).     

Development of highly sensitive chemiluminescence enzyme immunoassay based on the anti-recombinant HC subunit of botulinum neurotoxin type A monoclonal antibodies

Botulinum neurotoxins (BoNTs) are the most poisonous substances ever known. The early detection of these toxins could bear more time for appropriate medical intervention. The standard method for detecting BoNTs is the mouse bioassay, which is time consuming (up to 4 days) and requires a large number of laboratory animals. The immunologic detection methods could detect the toxins within a day, but most of these methods are less sensitive compared with the mouse bioassay due to the lack of high-affinity antibodies. Recently, the recombinant H_C subunit of botulinum neurotoxin type A (rAH_C) was expressed as an effective vaccine against botulism, indicating that the rAH_C could be an effective immunogen that raises the monoclonal antibody (mAb) for detecting BoNT/A. After immunized BALB/c mice with rAH_C, 56 mAbs were generated. Two of these mAbs were selected to establish a highly sensitive sandwich chemiluminescence enzyme immunoassay (CLEIA), in which FMMU-BTA-49 and FMMU-BTA-22 were used as capture antibody and detection antibody, respectively. The calculated limit of detection (LOD) based on molecular weight of rAH_C and BoNT/A reached 0.45 pg mL⁻¹. This CLEIA can be used in the detection of BoNT/A in matrices such as milk and beef extract. This method has 20–40 fold lower LOD than that of the mouse bioassay and takes only 3 h to complete the detection, indicating that it can be used as a valuable method to detect and quantify BoNT/A.     

甲胺化衍生结合基于硅氢化物固定相的正相色谱用于单克隆抗体药物的N-糖基化表征

采用甲胺化衍生结合基于硅氢化物固定相的正相色谱（SiH-NPC）分析单抗的N-糖基化。样品经酶切、甲胺化衍生、纯化后由液相色谱-质谱进行分析。结果表明,相较于亲水相互作用色谱（HILIC）,SiH-NPC分离机制不同,使用常规的无盐流动相即可实现高分离度,避免污染质谱,色谱柱结构稳定,使用寿命长,更适合快速分析。结合唾液酸衍生方法,SiH-NPC在液相色谱-质谱联用鉴定酸性糖和糖异构体方面呈现显著优势,在生物制药行业中具有重要的应用潜力。     

Rapid analysis of charge variants of monoclonal antibodies with capillary zone electrophoresis in dynamically coated fused-silica capillary

A capillary zone electrophoresis (CZE) method was developed for the rapid analysis of charge heterogeneity of immunoglobulin G (IgG) monoclonal antibodies (mAbs). The separation was carried out in a short, dynamically coated fused-silica capillary. A number of separation parameters were investigated and optimized, including pH, concentration of the separation buffer (ε-amino caproic acid), concentration of the triethylenetetramine (TETA) dynamic coating, the capillary internal diameter and the field strength used for the separation. The effects of between-run flushing of the capillary and the data acquisition rate were also evaluated. Under the optimized conditions, a fast (<5 min), selective and reproducible separation of mAb charge variants was achieved under a very high electric field strength (1000 V/cm). This method also requires only a short conditioning of the capillary, with between-run conditioning completed within 2 min. The method was evaluated for specificity, sensitivity, linearity, accuracy and precision. The same separation conditions were applied to the rapid separation (2-5 min) of charge variants of multiple monoclonal antibodies with pI in the range of 7.0-9.5. Compared with other existing methods for charge variants analysis, this method has several advantages including a short run time, rapid capillary conditioning and simple sample preparation.     

The Evolving Role of Microsampling in Therapeutic Drug Monitoring of Monoclonal Antibodies in Inflammatory Diseases

Monoclonal antibodies (mAbs) have been extensively developed over the past few years, for the treatment of various inflammatory diseases. They are large molecules characterized by complex pharmacokinetic and pharmacodynamic properties. Therapeutic drug monitoring (TDM) is routinely implemented in the therapy with mAbs, to monitor patients’ treatment response and to further guide dose adjustments. Serum has been the matrix of choice in the TDM of mAbs and its sampling requires the visit of the patients to laboratories that are not always easily accessible. Therefore, dried blood spots (DBS) and various microsampling techniques have been suggested as an alternative. DBS is a sampling technique in which capillary blood is deposited on a special filter paper. It is a relatively simple procedure, and the patients can perform the home-sampling. The convenience it offers has enabled its use in the quantification of small-molecule drugs, whilst in the recent years, studies aimed to develop microsampling methods that will facilitate the TDM of mAbs. Nevertheless, hematocrit still remains an obstacle that hinders a more widespread implementation of DBS in clinical practice. The introduction of novel analytical techniques and contemporary microsampling devices can be considered the steppingstone to the attempts made addressing this issue.     

Molecular modeling of Protein A affinity chromatography

The properties of the complex between fragment B of Protein A and the Fc domain of IgG were investigated adopting molecular dynamics with the intent of providing useful insight that might be exploited to design mimetic ligands with properties similar to those of Protein A. Simulations were performed both for the complex in solution and supported on an agarose surface, which was modeled as an entangled structure constituted by two agarose double chains. The energetic analysis was performed by means of the molecular mechanics Poisson Boltzmann surface area (MM/PBSA), molecular mechanics generalized Born surface area (MM/GBSA), and the linear interaction energy (LIE) approaches. An alanine scan was performed to determine the relative contribution of Protein A key amino acids to the complex interaction energy. It was found that three amino acids play a dominant role: Gln 129, Phe 132 and Lys 154, though also four other residues, Tyr 133, Leu 136, Glu 143 and Gln 151 contribute significantly to the overall binding energy. A successive molecular dynamics analysis of Protein A re-organization performed when it is not in complex with IgG has however shown that Phe 132 and Tyr 133 interact among themselves establishing a significant π–π interaction, which is disrupted upon formation of the complex with IgG and thus reduces consistently their contribution to the protein–antibody bond. The effect that adsorbing fragment B of Protein A on an agarose support has on the stability of the protein–antibody bond was investigated using a minimal molecular model and compared to a similar study performed for a synthetic ligand. It was found that the interaction with the surface does not hinder significantly the capability of Protein A to interact with IgG, while it is crucial for the synthetic ligand. These results indicate that ligand–surface interactions should be considered in the design of new synthetic affinity ligands in order to achieve results comparable to those of Protein A right from the ligand design stage.     

A New Alternative Tool to Analyse Glycosylation in Monoclonal Antibodies Based on Drop-Coating Deposition Raman imaging: A Proof of Concept

Glycosylation is considered a critical quality attribute of therapeutic proteins as it affects their stability, bioactivity, and safety. Hence, the development of analytical methods able to characterize the composition and structure of glycoproteins is crucial. Existing methods are time consuming, expensive, and require significant sample preparation, which can alter the robustness of the analyses. In this context, we developed a fast, direct, and simple drop-coating deposition Raman imaging (DCDR) method combined with multivariate curve resolution alternating least square (MCR-ALS) to analyze glycosylation in monoclonal antibodies (mAbs). A database of hyperspectral Raman imaging data of glycoproteins was built, and the glycoproteins were characterized by LC-FLR-MS as a reference method to determine the composition in glycans and monosaccharides. The DCDR method was used and allowed the separation of excipient and protein by forming a “coffee ring”. MCR-ALS analysis was performed to visualize the distribution of the compounds in the drop and to extract the pure spectral components. Further, the strategy of SVD-truncation was used to select the number of components to resolve by MCR-ALS. Raman spectra were processed by support vector regression (SVR). SVR models showed good predictive performance in terms of RMSECV, R²_CV.