Isolation of Extracellular Outer Membrane Vesicles (OMVs) from Escherichia coli Using EVscore47 Beads.

Outer membrane vesicles (OMVs) are attractive for biomedical applications based on their intrinsic properties in relation to bacteria and vesicles. However, their widespread use is hampered by low yields and purities. In this study, EVscore47 multifunctional chromatography microspheres were synthesized and used to efficiently isolate functional OMVs from Escherichia coli. Through this technology, OMV loss can be kept to a minimum, and OMVs can be harvested using EVscore47 at 11-fold higher yields and ~13-fold higher purity than those achieved by means of ultracentrifugation. Based on the results presented here, we propose a novel EVscore47-based isolation of OMVs that is fast and scalable.

Evaluation of Physicochemical Properties of Ipsapirone Derivatives Based on Chromatographic and Chemometric Approaches.

Drug discovery is a challenging process, with many compounds failing to progress due to unmet pharmacokinetic criteria. Lipophilicity is an important physicochemical parameter that affects various pharmacokinetic processes, including absorption, metabolism, and excretion. This study evaluated the lipophilic properties of a library of ipsapirone derivatives that were previously synthesized to affect dopamine and serotonin receptors. Lipophilicity indices were determined using computational and chromatographic approaches. In addition, the affinity to human serum albumin (HSA) and phospholipids was assessed using biomimetic chromatography protocols. Quantitative Structure-Retention Relationship (QSRR) methodologies were used to determine the impact of theoretical descriptors on experimentally determined properties. A multiple linear regression (MLR) model was calculated to identify the most important features, and genetic algorithms (GAs) were used to assist in the selection of features. The resultant models showed commendable predictive accuracy, minimal error, and good concordance correlation coefficient values of 0.876, 0.149, and 0.930 for the validation group, respectively.

Establishment of a graphene oxide-assisted nucleic acid chromatography strip detection technology for Prorocentrum minimum.

In recent decades, the harmful algal blooms (HABs) caused by Prorocentrum minimum have caused serious environmental damage and economic losses. The detection of P. minimum plays an important role in warning the outbreak of P. minimum-forming HABs. By utilizing the powerful absorption of graphene oxide (GO) on short-stranded DNA, a GO-assisted nucleic acid chromatography strip (GO-NACS) was proposed here to achieve a highly sensitive, specific, intuitive, and convenient detection of P. minimum. In particular, this study used our previously reported conventional-NACS (C-NACS) as a control to evaluate the improvement of detection performance with the use of GO. The performance of GO-NACS was evaluated from the perspectives of specificity, sensitivity, stability, and practicality. The specificity test demonstrated that it had a high degree of specificity and did not display cross-reacting with non-target algal species. The sensitivity test with the genomic DNA indicated that it had a detection limit of 1.30 × 10-3 ng µL-1, representing a 10-fold higher sensitivity than C-NACS and a 100-fold higher sensitivity than agarose gel electrophoresis (AGE). The interference test with non-target algal species demonstrated that it had a good detection stability, and the interfering algal species had no obvious effect on the detection of P. minimum. The practicality test with simulated natural water samples showed that the cellular detection limit of GO-NACS was 6.8 cells mL-1, which was 10-fold and 100-fold lower than that of C-NACS and AGE, respectively. In conclusion, the established GO-NACS may offer a novel alternative technique for the detection of P. minimum while guaranteeing specificity and enhancing sensitivity without requiring extensive apparatus.

A Rapid, Equipment-Free DNA Isolation Method for DNA Barcoding.

This rapid, equipment-free DNA isolation procedure using chromatography paper is a simple method that can be performed in less than 30 min and requires no wet lab experience. With minimal expense, it offers an affordable alternative for anyone wanting to explore biodiversity. It also provides an excellent option for use in classrooms or other activities that are time limited. The method works best for plants or lichens, producing stable DNA on Whatman® chromatography paper at room temperature, which can be eluted as needed.

[Ion chromatography for the determination of n-butylamine in the workplace air].

Objective: To establish a method for the determination of n-butylamine in the air of the workplace by ion chromatography. Methods: In February 2022, on-site sampling was carried out using an atmospheric sampler. N-butylamine was adsorbed by a neutral silica gel tube and then performed for qualitative and quantitative determination by ion chromatography after ultrasonic desorption with 10 mmol/L sulfuric acid solution. Results: The linear range of the method was 0.0375-100.0 µg/ml, the linear equation of the standard curve was y=0.0713x-0.0327, the correlation coefficient was 0.9992. The detection limit of the method was 11.25 µg/L, and the lower limit of quantification was 37.50 µg/L, the lowest quantitative concentration was 0.025 mg/m(3) (in term of sampling 7.5 L). The average desorption efficiency of the method was 91.50%-95.38%, the precision was 1.10%-2.30%, the standard recovery was 83.83%-100.02%, sampling efficiency was 100.00%. Conclusion: This method is fast, sensitive and accurate, and can be used for the determination of n-butylamine in the air of workplace.

Rapid indirect separation of glutamine enantiomers by micellar electrokinetic chromatography. Analysis of dietary supplements.

Glutamine is the most abundant free proteinogenic α-amino acid. It is naturally produced in the organism and acts as a precursor for the synthesis of different biologically important molecules (such as proteins or nucleotides). However, under stressful conditions, the organism is unable to produce it in enough amounts to function properly. Thus, glutamine (Gln)-based supplements have become increasingly popular over the last decade. Since legal regulations establish that amino acid-based dietary supplements must contain only the L-enantiomer and not the racemate, adequate chiral methodologies are required to achieve their quality control. In this work, an analytical methodology based on the use of micellar electrokinetic chromatography is proposed for the rapid enantiomeric determination of DL-Gln in dietary supplements. Using (+)-1-(9-fluorenyl)-ethyl chloroformate as a derivatizing agent and ammonium perfluorooctanoate as separation medium, the Gln diastereoisomers formed under optimal conditions were separated in 8 min with a resolution of 2.8. The analytical characteristics of the method were evaluated in terms of linearity, precision, accuracy, and limits of detection/quantitation, and they were found appropriate for the analysis of L-Gln-based dietary supplements.

Application of mechanistic modelling in membrane and fiber chromatography for purification of biotherapeutics - A review.

Mechanistic modelling is a simulation tool which has been effectively applied in downstream bioprocessing to model resin chromatography. Membrane and fiber chromatography are newer approaches that offer higher rates of mass transfer and consequently higher flow rates and reduced processing times. This review describes the key considerations in the development of mechanistic models for these unit operations. Mass transfer is less complex than in resin columns, but internal housing volumes can make modelling difficult, particularly for laboratory-scale devices. Flow paths are often non-linear and the dead volume is often a larger fraction of the overall volume, which may require more complex hydrodynamic models to capture residence time distributions accurately. In this respect, the combination of computational fluid dynamics with appropriate protein binding models is emerging as an ideal approach.

Parameter-by-parameter estimation method for adsorption isotherm in hydrophobic interaction chromatography.

Hydrophobic interaction chromatography (HIC) is used as a critical polishing step in the downstream processing of biopharmaceuticals. Normally the process development of HIC is a cumbersome and time-consuming task, and the mechanical models can provide a powerful tool to characterize the process, assist process design and accelerate process development. However, the current estimation of model parameters relies on the inverse method, which lacks an efficient and logical parameter estimation strategy. In this study, a parameter-by-parameter (PbP) method based on the theoretical derivation and simplifying assumptions was proposed to estimate the Mollerup isotherm parameters for HIC. The method involves three key steps: (1) linear regression (LR) to estimate the salt-protein interaction parameter and the equilibrium constant; (2) linear approximation (LA) to estimate the stoichiometric parameter and the maximum binding capacity; and (3) inverse method to estimate the protein-protein interaction parameter and the kinetic coefficient. The results indicated that the LR step should be used for dilution condition (loading factor below 5%), while the LA step should be conducted when the isotherm is in the transition or nonlinear regions. Six numerical experiments were conducted to implement the PbP method. The results demonstrated that the PbP method developed allows for the systematic estimation of HIC parameters one-by-one, effectively reducing the number of parameters required for inverse method estimation from six to two. This helps prevent non-identifiability of structural parameters. The feasibility of the PbP-HIC method was further validated by real-world experiments. Moreover, the PbP method enhances the mechanistic understanding of adsorption behavior of HIC and shows a promising application to other stoichiometric displacement model-derived isotherms.

Altering the mobile phase composition to enhance self-disproportionation of enantiomers in achiral chromatography.

The influence of mobile phase composition on the efficiency of enantiomer separation by achiral chromatography (ACh) was investigated. The separation was induced by the phenomenon of self-disproportionation of enantiomers (SDE) triggered by their homo and hetero-chiral interactions in an achiral environment. Typically, SDE occurs in apolar mobile phases of weak elution strength, which causes the separation time to extend and the process productivity to deteriorate. To mitigate that effect, we altered the content of a strong solvent (modifier) in the mobile phase by use of a solvent gradient in which the target enantiomer was separated in the presence of the weak solvent, whereas the unresolved mixture of enantiomers was eluted by increasing the modifier content in the mobile phase. This enabled accelerating the solute elution while preserving the separation selectivity. The approach was examined for the separation of nonracemic mixtures of two structurally different compounds that exhibited the SDE effect in ACh, i.e., metalaxyl (MX) and methyl p-tolyl sulfoxide (MTSO). The target compound of the separation was the more abundant enantiomer in the enantiomeric mixture. The process realization was preceded by the determination of the effect of the modifier content on the separation yield for enantiomeric mixtures of MX and MTSO of different enantiomeric excess (ee). In the case of MX, yield of the pure target enantiomer varied from 2 %, for the maximum concentration of the modifier, to 45 % for the minimum modifier concentration and the largest ee used in the experiments. In the case of MTSO, the yield varied from minimum 40 % to maximum 66 %. To predict the process, we employed a dynamic model, in which underlying thermodynamic dependencies were implemented.

An alternative general model for the effective longitudinal diffusion in chromatographic beds filled with ordered porous particles.

The two-zone moment-analysis method for the determination of the dispersion tensor in hierarchical retentive porous media has been adopted to compute and model the effective longitudinal diffusion Deff, or equivalently the B-term band broadening, in chromatographic beds filled with ordered porous particles. On the one hand, this approach offers accurate numerical results for Deff while keeping computational expenses low. On the other hand, it also gives direct insight for the analytical modelling, readily revealings the two main essential quantities (resp. referred to as the mobile-zone and stationary-zone effective diffusion factors γm and γs) that contribute to Deff. Modelling these two main parameters provided us with two new analytical models for Deff: a general one, valid for diluted and concentrated packings and accurate in the whole range of relevant intra-particle diffusion coefficient Dpz, and an approximate one, reliable for diluted packings and accurate also for concentrated packings with low to intermediate values of Dpz. The large advantage of both models is that they do not need any fitting parameter because all the required information is incorporated into the experimentally accessible geometric obstruction factor in the mobile phase originating from the tortuosity of the through-pore space (limiting case of fully solid particles without any retention). These models hence serve as an alternative to the Effective Medium Theory (EMT) models used so far in the literature. To validate the theory, five ordered geometries have been investigated. The accuracy of the general model proposed has been quantified and found to be comparable with that of the 3rd order approximate Torquato model for four geometries, even for macro-porosities close to the close-packing limit. The case of a 2-d triangular array of ellipsoidal particles with different elongations is also investigated to show the general validity and applicability of the models.

The beneficial impact of kosmotropic salts on the resolution and selectivity of Protein A chromatography.

During the manufacturing of therapeutic antibodies, effective Protein A chromatography as initial column step is crucial to simplify the remaining purification effort for subsequent polishing steps. This is particularly relevant for molecules with high impurity content so that desired product purity can be attained. The present study demonstrates beneficial effects on impurity removal when applying kosmotropic salts, e.g., sodium sulfate or sodium chloride, in the elution phase. Initially, a screen using negative linear pH gradient elution evaluated the impact of the kosmotropic salts in comparison to no additive and chaotropic urea using three mAbs and three common resins. Retaining acceptable yield, the kosmotropic salts improved resolution of monomer and impurities and reduced the contents of process-related host cell proteins and DNA as well as of product-related low and high molecular weight forms, despite some resin- and mAb-dependent variations. Moreover, a decrease in hydrolytic activity measured by a new assay for polysorbase activity was observed. In contrast, urea was hardly effective. The findings served to establish optimized step elution conditions with 0.25 M of sodium sulfate for a challenging mAb with complex format (bispecific 2 + 1 CrossMab) displaying high relative hydrophobicity and impurity levels. With yield and purity both in the range of 90 %, the contents of all impurity components were reduced, e.g., low molecular weight forms by two-fold and polysorbase activity by four-fold. The study indicates the potential of kosmotropic salts to establish efficient and comprehensive impurity separation by Protein A for facilitated downstream processing and economic manufacturing of complex antibodies.

On-line PAT based monitoring and control of resin aging in protein A chromatography for COGs reduction.

Resin aging is a common occurrence in chromatographic processes and generally influenced by factors such as cleaning procedure and composition of the feed stream. Two major events occur along with protein fouling, one is the loss of protein A ligand and the other is non-specific, irreversible interactions of foulants with resin particles. Both these are responsible for resin aging. As a result, the performance of the resin suffers a fall, and this can be quantified through indicators like reduction in dynamic binding capacity, increased column pressure, or peak broadening. The number of reuse cycles of a resin has a major influence on the cost per batch. This is even more significant in the case of protein A resin, which is the primary cost driver for downstream processing. In this work, we first identify chromatogram characteristics that correlate to resin aging. Next, we propose a data monitoring-based tool for prediction of resin aging. Principal component analysis of the UV data of Mab 1 showed a deviation at 120th cycle and an out of specification at around 149th cycle, corroborating with yield decline. Batch level modelling could deliver a predictable trend for resin aging and was demonstrated for two different Mabs (Mab1 and Mab2). The results demonstrate that significant resin aging can be detected 20-25 cycles prior to observable yield decline. A control strategy has been suggested such that once the deviation has been detected, additional resin cleaning is triggered. Overall, a 50-100 Protein A cycle enhancement in resin lifespan could be achieved.

Factors affecting therapeutic protein purity and yield during chromatographic purification.

Therapeutic proteins are recombinant proteins generated through recombinant DNA technology and have attracted a great deal of interest in numerous applications, including pharmaceutical, cosmetic, human and animal health, agriculture, food, and bioremediation. Producing therapeutic proteins on a large scale, mainly in the pharmaceutical industry, necessitates a cost-effective, straightforward, and adequate manufacturing process. In industry, a protein separation technique based mainly on protein characteristics and modes of chromatography will be applied to optimize the purification process. Typically, the downstream process of biopharmaceutical operations may involve multiple chromatography phases that require the use of large columns pre-packed with resins that must be inspected before use. Approximately 20% of the proteins are assumed to be lost at each purification stage during the production of biotherapeutic products. Hence, to produce a high quality product, particularly in the pharmaceutical industry, the correct approach and understanding of the factors influencing purity and yield during purification are necessary.

Large-scale crystallization as an intermediate processing step in insulin downstream process: explored advantages and identified tool for process intensification.

The rising global prevalence of diabetes and increasing demand for insulin, calls for an increase in accessibility and affordability of insulin drugs through efficient and cost-effective manufacturing processes. Often downstream operations become manufacturing bottlenecks while processing a high volume of product. Thus, process integration and intensification play an important role in reducing process steps and time, volume reduction, and lower equipment footprints, which brings additional process efficiencies and lowers the production cost. Manufacturers thrive to optimize existing unit operation to maximize its benefit replacing with simple but different efficient technologies. In this manuscript, the typical property of insulin in forming the pH-dependent zinc-insulin complex is explored. The benefit of zinc chloride precipitation/crystallization has been shown to increase the in-process product purity by reducing the product and process-related impurities. Incorporation of such unit operation in the insulin process has also a clear potential for replacing the high cost involved capture chromatography step. Same time, the reduction in volume of operation, buffer consumption, equipment footprint, and capabilities of product long time storage brings manufacturing flexibility and efficiencies. The data and capabilities of simple operation captured here would be significantly helpful for insulins and other biosimilar manufacturer to make progresses on cost-effective productions.

Radiostrontium determination by combination of automated Sr isolation and "on-column" Cherenkov detection using chromatographic model.

A novel analytical solution of non-linear chromatography in case of parabolic isotherm for frontal analysis was obtained by combination of Cole-Hopf and Laplace transform. It was used for simulation of strontium capturing on chromatographic column with aim to improve quantitative determination of low-level 90Sr activities. From the experimentally determined breakthrough curves, the retention factor and the number of theoretical plates were calculated using the Glueckauf and Wenzel relations and by fitting the breakthrough curves for the linear isotherm using MatLab. These were used to simulate the breakthrough curves using a parabolic isotherm solution where the non-linear term of the isotherm was taken as a small negative deviation of the retention factor. On the base of theoretical prediction and experimental data, procedure for automated capturing of strontium on chromatographic column with specific dimension and off line "on-column" Cherenkov detection on commercial ultra low-level liquid scintillation counter was developed. It was shown that analytical solution for parabolic isotherm in comparison with solution for linear isotherm gives better prediction of mass of captured Sr on column filled with small amount of Sr resin and SuperLig®620 in case of elevated Sr concentration, even when non-linear effect is not obvious. The solution also makes it possible to predict the mass of resin required for strontium isolation at 100% yield under given conditions. Considering the limited dimensions of the column, and consequently small mass of the resin in them, it resulted in the low efficiency of the columns, which, however, did not affect the yield in real conditions of isolation. The results have shown that the yields achieved after isolation on SuperLig®620 from real samples are 100%. In addition, it is shown that captured 90Sr can be detected through 90Y ingrowth, on column filled with strontium specific resin, with Cherenkov detection efficiency of at least 50%. The efficiency may be enhanced to 60%, depending on parameters which can affect detection efficiency change (type of column, resin type, surrounding solution, etc.). The developed procedures enable quantitative determination of 90Sr in natural water samples with MDAC below 12 mBq l-1 and solid (soil and vegetation) samples with MDAC below 6 Bq kg-1 within 2-3 days. The proposed solution may easily be implemented in radiochemical laboratories where this type of analysis is routinely done within environmental monitoring or other purposes.

Hybrid model development for parameter estimation and process optimization of hydrophobic interaction chromatography.

Hydrophobic Interaction Chromatography (HIC) is often employed as a polishing step to remove aggregates for the purification of therapeutic proteins in the biopharmaceutical industry. To accelerate the process development and save the costs of performing time- and resource-intensive experiments, advanced model-based process design and optimization are necessary. Due to the unclear adsorption mechanism of the salt-dependent interaction between the protein and resin, the development of an accurate mechanistic model to describe the complex HIC behavior is challenging. In this work, an isotherm derived from Wang et al. is modified by adding three extra parameters together with an equilibrium dispersive model to represent the HIC process. To reduce the development effort of isotherm equations and extract missing information from the available data, a hybrid model is constructed by combining a simple and well-known multi-component Langmuir isotherm (MCL) with a neural network (NN). It is observed that the structure of the hybrid model is of critical importance to the accuracy of the developed model. During parameter estimation, a regularization strategy is incorporated to prevent overfitting. Furthermore, the impact of NN structures and regularization rates are comprehensively investigated. One of the interesting findings was that a simple NN with one hidden layer with two nodes and sigmoid as the activation function, significantly outperforms the mechanistic model, with a 62% improvement in accuracy in calibration and 31.4% in validation. To ensure the generalizability of the developed hybrid model, an in-silico dataset is generated using the mechanistic model to test the extrapolation capability of the hybrid model. Process optimization is also carried out to find the optimal operating conditions under product quality constraints using the developed hybrid model.

Elucidating the mechanisms of additive effects at high concentrations on hydrophobic interaction chromatography.

Hydrophobic interaction chromatography (HIC) is a commonly used chromatography technique for purifying proteins. It utilizes salting-out salts to facilitate the binding of native proteins to weakly hydrophobic ligands. There have been three proposed mechanisms for the promoting effects of salting-out salts, which include the dehydration of proteins by salts, cavity theory, and salt exclusion. To evaluate the above three mechanisms, an HIC study was conducted on Phenyl Sepharose using four different additives. These additives included a salting-out salt (NH4)2SO4, sodium phosphate that increases the surface tension of water, a salting-in salt MgCl2, and an amphiphilic protein-precipitant polyethylene glycol (PEG). Results indicated that the first two salts resulted in protein binding, while MgCl2 and PEG led to flow-through. These findings were then used to interpret the three proposed mechanisms, which showed that MgCl2 and PEG deviated from the dehydration mechanism, and MgCl2 also deviated from the cavity theory. The observed effects of these additives on HIC were reasonably well explained for the first time by their interactions with proteins.

A fast and simple extraction method for analysing levoglucosan and its isomers in sediments by ion chromatography tandem mass spectrometry.

The ability to trace current and past biomass burning events is important for understanding the links between human activity, fire frequency, and climate. One method of tracing biomass burning is to measure the concentrations of certain monosaccharides anhydrides (MAs), specifically levoglucosan (LEV) and its isomers, mannosan (MAN) and galactosan (GAL), which are products of cellulose and hemicellulose pyrolysis. This work presents a simple extraction method allowing for the rapid, sensitive, and selective determination of MAs in sediments. MAs detection was performed using suppressed ion chromatography with electrospray - triple-stage quadrupole tandem mass spectrometry (IC-TSQ-MS). The extraction method involves ultrasound probe sonication using water as the solvent. Extraction time, amplitude, and sonication mode were optimised. Recoveries higher than 86% for all MAs tested were achieved by applying 70% amplitude in continuous mode for 60 s. Analytical performance of the method included instrumental LODs of 0.10, 0.12 and 0.50 µg L-1 for LEV, MAN and GAL, respectively. No carryover issues, no matrix effect and no co-elution of targeted MAs with other sugars likely present in sediments samples were observed. The developed extraction method was further validated by the analysis of LEV and MAN in NIST® 1649b urban dust reference material and the resulting concentrations were in excellent agreement with previously reported values. MAs quantification in 70 lake sediment samples were carried out with concentrations found to range from 0.009 to 0.390 µg g-1 for LEV and from 0.009 to 0.194 µg g-1 for MAN. Plotting MAs concentrations versus approximate sediment age allowed the reconstruction of recent fire events impacting two locations in the Central Highlands of Tasmania, Australia.

Optimization of fluid flow in membrane chromatography devices using computational fluid dynamic simulations.

Flow uniformity within the device is critically important in membrane chromatography. Recent studies have shown that the design of the device has a significant impact on flow uniformity, and thereby on separation efficiency. The main premise of this work is that computational fluid dynamics (CFD) could serve as a fast and inexpensive tool for preliminary optimization of the design of a membrane chromatography device. CFD also helps in identifying factors that affect flow uniformity. In this paper, CFD is used to compare the fluidic attributes of conventional membrane chromatography devices such as the stacked disc and radial flow devices with those of more recently developed ones such as the different versions of the laterally-fed membrane chromatography (LFMC) device. These are compared based on pulse tracer solute dispersion, which is a useful metric for measuring flow uniformity, and is thereby a good predictor of chromatographic separation performance. The poor separation performance typically observed with conventional membrane chromatography devices could be attributed to the high degree of solute dispersion within these devices. CFD is then used to analyze the impact of factors such as membrane aspect ratio, and channel dimensions on the performance of z2-laterally-fed membrane chromatography (z2LFMC) devices. The results discussed in the paper demonstrate that CFD could indeed serve as a powerful optimization and performance prediction tool for membrane chromatography.