Identification of heavily glycated proteoforms by hydrophilic-interaction liquid chromatography and native size-exclusion chromatography - High-resolution mass spectrometry.

BACKGROUND: The non-enzymatic glycation of proteins and their advanced glycation end products (AGEs) are associated with protein transformations such as in the development of diseases and biopharmaceutical storage. The characterization of heavily glycated proteins at the intact level is of high interest as it allows to describe co-occurring protein modifications. However, the high heterogeneity of glycated protein makes this process challenging, and novel methods are required to accomplish this. RESULTS: In this study, we investigated two novel LC-HRMS methods to study glycated reference proteins at the intact protein level: low-flow hydrophilic-interaction liquid chromatography (HILIC) and native size-exclusion chromatography (SEC). Model proteins were exposed to conditions that favored extensive glycation and the formation of AGEs. After glycation, complicated MS spectra were observed, along with a sharply reduced signal response, possibly due to protein denaturation and the formation of aggregates. When using HILIC-MS, the glycated forms of the proteins could be resolved based on the number of reducing monosaccharides. Moreover, some positional glycated isomers were separated. The SEC-MS method under non-denaturing conditions provided insights into glycated aggregates but offered only a limited separation of glycated species based on molar mass. Overall, more than 25 different types of species were observed in both methods, differing in molar mass by 14-162 Da. 19 of these species have not been previously reported. SIGNIFICANCE: The proposed strategies show great potential to characterize highly glycated intact proteins from native and denaturing perspectives and provide new opportunities for fast clinical diagnoses and investigating glycation-related diseases.

Comprehensive two-dimensional gas chromatography- A discussion on recent innovations.

Although comprehensive 2-D GC is an established and often applied analytical method, the field is still highly dynamic thanks to a remarkable number of innovations. In this review, we discuss a number of recent developments in comprehensive 2-D GC technology. A variety of modulation methods are still being actively investigated and many exciting improvements are discussed in this review. We also review interesting developments in detection methods, retention modeling, and data analysis.

Algorithm for tracking peaks amongst numerous datasets in comprehensive two-dimensional chromatography to enhance data analysis and interpretation.

Analytical data processing often requires the comparison of data, i.e. finding similarities and differences within separations. In this context, a peak-tracking algorithm was developed to compare multiple datasets in one-dimensional (1D) and two-dimensional (2D) chromatography. Two application strategies were investigated: i) data processing where all chromatograms are produced in one sequence and processed simultaneously, and ii) method optimization where chromatograms are produced and processed cumulatively. The first strategy was tested on data from comprehensive 2D liquid chromatography and comprehensive 2D gas chromatography separations of academic and industrial samples of varying compound classes (monoclonal-antibody digest, wine volatiles, polymer granulate headspace, and mayonnaise). Peaks were tracked in up to 29 chromatograms at once, but this could be upscaled when necessary. However, the peak-tracking algorithm performed less accurate for trace analytes, since, peaks that are difficult to detect are also difficult to track. The second strategy was tested with 1D liquid chromatography separations, that were optimized using automated method-development. The strategy for method optimization was quicker to detect peaks that were still poorly separated in earlier chromatograms compared to assigning a target chromatogram, to which all other chromatograms are compared. Rendering it a useful tool for automated method optimization.

Capacitively coupled contactless conductivity detection to account for system-induced gradient deformation in liquid chromatography.

The time required for method development in gradient-elution liquid chromatography (LC) may be reduced by using an empirical modelling approach to describe and predict analyte retention and peak width. However, prediction accuracy is impaired by system-induced gradient deformation, which can be especially prominent for steep gradients. As the deformation is unique to each LC instrument, it needs to be corrected for if retention modelling for optimization and method transfer is to become generally applicable. Such a correction requires knowledge of the actual gradient profile. The latter has been measured using capacitively coupled "contactless" conductivity detection (C4D), featuring a low detection volume (approximately 0.05 µL) and compatibility with very high pressures (80 MPa or more). Several different solvent gradients, from water to acetonitrile, water to methanol, and acetonitrile to tetrahydrofuran, could be measured directly without the addition of a tracer component to the mobile phase, exemplifying the universal nature of the approach. Gradient profiles were found to be unique for each solvent combination, flowrate, and gradient duration. The profiles could be described by convoluting the programmed gradient with a weighted sum of two distribution functions. Knowledge of the exact profiles was used to improve the inter-system transferability of retention models for toluene, anthracene, phenol, emodin, sudan-I and several polystyrene standards.

Characterizing Non-covalent Protein Complexes Using Asymmetrical Flow Field-Flow Fractionation On-Line Coupled to Native Mass Spectrometry.

We report an online analytical platform based on the coupling of asymmetrical flow field-flow fractionation (AF4) and native mass spectrometry (nMS) in parallel with UV-absorbance, multi-angle light scattering (MALS), and differential-refractive-index (UV-MALS-dRI) detectors to elucidate labile higher-order structures (HOS) of protein biotherapeutics. The technical aspects of coupling AF4 with nMS and the UV-MALS-dRI multi-detection system are discussed. The "slot-outlet" technique was used to reduce sample dilution and split the AF4 effluent between the MS and UV-MALS-dRI detectors. The stability, HOS, and dissociation pathways of the tetrameric biotherapeutic enzyme (anticancer agent) l-asparaginase (ASNase) were studied. ASNase is a 140 kDa homo-tetramer, but the presence of intact octamers and degradation products with lower molecular weights was indicated by AF4-MALS/nMS. Exposing ASNase to 10 mM NaOH disturbed the equilibrium between the different non-covalent species and led to HOS dissociation. Correlation of the information obtained by AF4-MALS (liquid phase) and AF4-nMS (gas phase) revealed the formation of monomeric, tetrameric, and pentameric species. High-resolution MS revealed deamidation of the main intact tetramer upon exposure of ASNase to high pH (NaOH and ammonium bicarbonate). The particular information retrieved from ASNase with the developed platform in a single run demonstrates that the newly developed platform can be highly useful for aggregation and stability studies of protein biopharmaceuticals.

Micro-flow size-exclusion chromatography for enhanced native mass spectrometry of proteins and protein complexes.

Size-exclusion chromatography (SEC) employing aqueous mobile phases with volatile salts at neutral pH combined with native mass spectrometry (nMS) is a valuable tool to characterize proteins and protein aggregates in their native state. However, the liquid-phase conditions (high salt concentrations) frequently used in SEC-nMS hinder the analysis of labile protein complexes in the gas phase, necessitating higher desolvation-gas flow and source temperature, leading to protein fragmentation/dissociation. To overcome this issue, we investigated narrow SEC columns (1.0 mm internal diameter, I.D.) operated at 15-µL/min flow rates and their coupling to nMS for the characterization of proteins, protein complexes and higher-order structures (HOS). The reduced flow rate resulted in a significant increase in the protein-ionization efficiency, facilitating the detection of low-abundant impurities and HOS up to 230 kDa (i.e., the upper limit of the Orbitrap-MS instrument used). More-efficient solvent evaporation and lower desolvation energies allowed for softer ionization conditions (e.g., lower gas temperatures), ensuring little or no structural alterations of proteins and their HOS during transfer into the gas phase. Furthermore, ionization suppression by eluent salts was decreased, permitting the use of volatile-salt concentrations up to 400 mM. Band broadening and loss of resolution resulting from the introduction of injection volumes exceeding 3% of the column volume could be circumvented by incorporating an online trap-column containing a mixed-bed ion-exchange (IEX) material. The online IEX-based solid-phase extraction (SPE) or "trap-and-elute" set-up provided on-column focusing (sample preconcentration). This allowed the injection of large sample volumes on the 1-mm I.D. SEC column without compromising the separation. The enhanced sensitivity attained by the micro-flow SEC-MS, along with the on-column focusing achieved by the IEX precolumn, provided picogram detection limits for proteins.

Principles and potential of solvent gradient size-exclusion chromatography for polymer analysis.

The properties of a polymeric material are influenced by its underlying molecular distributions, including the molecular-weight (MWD), chemical-composition (CCD), and/or block-length (BLD) distributions. Gradient-elution liquid chromatography (LC) is commonly used to determine the CCD. Due to the limited solubility of polymers, samples are often dissolved in strong solvents. Upon injection of the sample, such solvents may lead to broadened or poorly shaped peaks and, in unfavourable cases, to "breakthrough" phenomena, where a part of the sample travels through the column unretained. To remedy this, a technique called size-exclusion-chromatography gradients or gradient size-exclusion chromatography (gSEC) was developed in 2011. In this work, we aim to further explore the potential of gSEC for the analysis of the CCD, also in comparison with conventional gradient-elution reversed-phase LC, which in this work corresponded to gradient-elution reversed-phase liquid chromatography (RPLC). The influence of the mobile-phase composition, the pore size of the stationary-phase particles, and the column temperature were investigated. The separation of five styrene/ethyl acrylate copolymers was studied with one-dimensional RPLC and gSEC. RPLC was shown to lead to a more-accurate CCD in shorter analysis time. The separation of five styrene/methyl methacrylate copolymers was also explored using comprehensive two-dimensional (2D) LC involving gSEC, i.e. SEC × gSEC and SEC × RPLC. In 2D-LC, the use of gSEC was especially advantageous as no breakthrough could occur.

Composition mapping of highly substituted cellulose-ether monomers by liquid chromatography-mass spectrometry and probability-based data deconvolution.

Cellulose ethers (CEs) are semi-synthetic polymers produced by derivatization of natural cellulose, yielding highly substituted products such as ethyl hydroxyethyl cellulose (EHEC) or methyl ethyl hydroxyethyl cellulose (MEHEC). CEs are commonly applied as pharmaceutical excipients and thickening agents in paints and drymix mortars. CE properties, such as high viscosity in solution, solubility, and bio-stability are of high interest to achieve required product qualities, which may be strongly affected by the substitution pattern obtained after derivatization. The average and molar degree of substitution often cannot explain functional differences observed among CE batches, and more in-depth analysis is needed. In this work, a new method was developed for the comprehensive mapping of the substitution degree and composition of ß-glucose monomers of CE samples. To this end, CEs were acid-hydrolyzed and then analyzed by gradient reversed-phase liquid chromatography-mass spectrometry (LC-MS) using an acid-stable LC column and time-of-flight (TOF) mass spectrometer. LC-MS provided monomer resolution based on ethylene oxide, hydroxyl, and terminating methyl/ethyl content, allowing the assignment of detailed compositional distributions. An essential further distinction of constitutional isomer distributions was achieved using an in-house developed probability-based deconvolution algorithm. Aided by differential heat maps for visualization and straightforward interpretation of the measured LC-MS data, compositional variation between bio-stable and non-bio-stable CEs could be identified using this new approach. Moreover, it disclosed unexpected methylations in EHEC samples. Overall, the obtained molecular information on relevant CE samples demonstrated the method's potential for the study of CE structure-property relationships.

Incorporating a liquid-core-waveguide cell in recycling liquid chromatography for detailed studies of photodegradation reactions.

In this work, a microfluidic photoreactor was embedded in a recycling liquid-chromatography system. Mixtures were separated on an analytical column and compounds of interest were subsequently introduced into the light-reactor cell. After degradation, the content of the light-reactor cell was reinjected onto the same column to separate the parent compound from its degradation products. A separated degradation product could be re-introduced into the photoreactor and irradiated again. The next generation of degradation products could again be separated on the same analytical column. This recycling procedure proved an excellent tool to elucidate degradation pathways. This was demonstrated using riboflavin, better known as vitamin B2. By degrading it in the first cycle, degradation products were isolated and subjected to a second degradation in the light-reactor cell. This allows pinpointing secondary products and connect these with primary degradation products. Compared to previous work, this configuration is simpler, cheaper, and more user-friendly, while offering the unique possibility to easily connect degradation products to the initial compounds in a mixture.

Influence of ion-pairing reagents on the separation of intact glycoproteins using hydrophilic-interaction liquid chromatography - high-resolution mass spectrometry.

Hydrophilic-interaction liquid chromatography (HILIC) of intact proteins offers high-resolution separations of glycoforms of glycoproteins differing in the number of (neutral) glycans. However, to obtain efficient separations it is essential that the positively charged sites of the proteins are shielded by acidic (negative) ion-pair reagents (IPRs), so as to enhance the contribution of the hydroxyl groups of the (neutral) sugars in the glycoprotein. Here, we studied the influence of various IPRs that differ in physico-chemical properties, such as hydrophobicity and acidity, on the capillary-scale HILIC separation of intact (glyco)proteins. We evaluated the use of fluoroacetic acid (MFA), difluoroacetic acid (DFA), trifluoroacetic acid (TFA), and heptafluorobutyric acid (HFBA) as diluents for sample preparation, as solvents for sample loading on a reversed-phase trap prior to the HILIC separation, and as mobile-phase components for HILIC and HILIC-MS. To reduce the contribution of ion-exchange interaction with the (silica-based) stationary phase, we used an acrylamide-based monolithic column. We studied the influence of the different IPRs on each step of the separation of a mixture of proteins of different size and hydrophilicity and on the separation of the five glycoforms of ribonuclease B. The content of IPR in the sample was shown not to affect the separation and the MS detection. However, a low content of TFA and DFA in the mobile phase is favourable, as it reduces adduct formation and leads to higher signal intensity. The optimized HILIC conditions successfully resolved nine major glycoforms groups of a ∼40 kDa glycoprotein horseradish peroxidase (HRP), as an example of a complex glycoprotein.

Two-dimensional tools for analyzing polymer microstructure; coupling non-aqueous ion-exchange chromatography to size-exclusion chromatography.

Traditional liquid-chromatographic techniques, such as size-exclusion chromatography, (critical) interaction chromatography, and hydrodynamic chromatography, can all reveal certain aspects of polymers and the underlying distributions. The distribution of incorporated acid groups present in polyacrylates can be determined by non-aqueous ion-exchange chromatography, independent of other distributions present. The microstructural details on how this number of acid groups is incorporated in the polymer remains unknown. A low-molar mass polymer molecule with high acid content and a high-molar mass polymer with a low acid content may have the exact same number of acid groups. To take a next step towards understanding the polymer microstructure of water-borne resins, the distribution of incorporated acid groups over the molar-mass distribution has been investigated. For this purpose, an on-line coupling of non-aqueous ion-exchange chromatography (NAIEX) to size-exclusion chromatography (SEC) was established. Practical considerations regarding the system setup with respect to chromatography modes and column- and valve switching dimensionality are discussed. The orthogonality of NAIEX and SEC is demonstrated. Both liquid chromatography modes may be calibrated using polymer standards, yielding a calibrated separation plane. Cross-sectional data on either the molar mass distribution or the acid group distribution at a certain point of the separation plane is obtained. The value of the designed setup was demonstrated by the detailed characterization of the combined acid-group and molar-mass distribution in polymers with a low acid content, in the order of a few mass-%. Several stages of the emulsion polymerization process could be identified using the combined power of NAIEX and SEC.

Continuous Flow Biocatalytic Reductive Amination by Co-Entrapping Dehydrogenases with Agarose Gel in a 3D-Printed Mould Reactor.

Herein, we show how the merge of biocatalysis with flow chemistry aided by 3D-printing technologies can facilitate organic synthesis. This concept was exemplified for the reductive amination of benzaldehyde catalysed by co-immobilised amine dehydrogenase and formate dehydrogenase in a continuous flow micro-reactor. For this purpose, we investigated enzyme co-immobilisation by covalent binding, or ion-affinity binding, or entrapment. Entrapment in an agarose hydrogel turned out to be the most promising solution for this biocatalytic reaction. Therefore, we developed a scalable and customisable approach whereby an agarose hydrogel containing the co-entrapped dehydrogenases was cast in a 3D-printed mould. The reactor was applied to the reductive amination of benzaldehyde in continuous flow over 120 h and afforded 47 % analytical yield and a space-time yield of 7.4 g L day-1 using 0.03 mol% biocatalysts loading. This work also exemplifies how rapid prototyping of enzymatic reactions in flow can be achieved through 3D-printing technology.

Assessing the feasibility of stationary-phase-assisted modulation for two-dimensional liquid-chromatography separations.

Two-dimensional liquid chromatography (2DLC) offers great separation power for complex mixtures. The frequently encountered incompatibility of two orthogonal separation systems, however, makes its application complicated. Active-modulation strategies can reduce such incompatibility issues considerably. Stationary-phase-assisted modulation (SPAM) is the most-common of these techniques, but also the least robust due to the major disadvantage that analytes may elute prematurely. The range of liquid chromatography (LC) applications continues to expand towards ever more complex mixtures. Retention modelling is increasingly indispensable to comprehend and develop LC separations. In this research, a tool was designed to assess the feasibility of applying SPAM in 2DLC. Several parameters were investigated to accurately predict isocratic retention of analytes on trap columns under dilution-flow conditions. Model parameters were derived from scanning-gradient experiments performed on analytical columns. The trap-to-trap repeatability was found to be similar to the prediction error. Dead volumes for the trap columns could not be accurately determined through direct experimentation. Instead, they were extrapolated from dead-volume measurements on analytical columns. Several known retention models were evaluated. Better predictions were found using the quadratic model than with the log-linear ("linear-solvent-strength") model. Steep scanning gradients were found to result in inaccurate predictions. The impact of the dilution flow on the retention of analytes proved less straightforward than anticipated. Under certain conditions dilution with a weaker eluent was found to be counter productive. A tool was developed to quantify the effect of the dilution flow and to predict whether SPAM could be applied in specific situations. For nine different analytes under 36 different sets of conditions and with three different modulation times, the SPAM tool yielded a correct assessment in more than 95% of all cases (less than 5% false positives plus false negatives).

Recycling gradient-elution liquid chromatography for the analysis of chemical-composition distributions of polymers.

Synthetic polymers typically show dispersity in molecular weight and potentially in chemical composition. For the analysis of the chemical-composition distribution (CCD) gradient liquid chromatography may be used. The CCD obtained using this method is often convoluted with an underlying molecular-weight distribution (MWD). In this paper we demonstrate that the influence of the MWD can be reduced using very steep gradients and that such gradients are best realized utilizing recycling gradient liquid chromatography (LC↻LC). This method allows for a more-accurate determination of the CCD and the assessment of (approximate) critical conditions (if these exist), even when high-molecular-weight standards of narrow dispersity are not readily available. The performance and usefulness of the approach is demonstrated for several polystyrene standards, and for the separation of statistical copolymers consisting of styrene/methyl methacrylate and methyl methacrylate/butyl methacrylate. For the latter case, approximate critical compositions of the copolymers were calculated from the critical compositions of two homopolymers and one copolymer of known chemical composition, allowing for a determination of the CCD of unknown samples. Using this approach it is shown that the copolymers elute significantly closer to the predicted critical compositions after recycling of the gradient. This is most clear for the lowest-molecular-weight copolymer (Mw = 4.2 kDa), for which the difference between measured and predicted elution composition decreases from 7.9% without recycling to 1.4% after recycling.

Introduction of Octadecyl-Bonded Porous Particles in 3D-Printed Transparent Housings with Multiple Outlets.

Microfluidic devices for comprehensive three-dimensional spatial liquid chromatography will ultimately require a body of stationary phase with multiple in- and outlets. In the present work, 3D printing with a transparent polymer resin was used to create a simplified device that can be seen as a unit cell for an eventual three-dimensional separation system. Complete packing of the device with 5-µm C18 particles was achieved, with reasonable permeability. The packing process could be elegantly monitored from the pressure profile, which implies that optical transparency may not be required for future devices. The effluent flow was different for each of the four outlets of the device, but all flows were highly repeatable, suggesting that correction for flow-rate variations is possible. The investigation into flow patterns through the device was supported by computational-fluid-dynamics simulations. A proof-of-principle separation of four standard peptides is described, with mass-spectrometric detection for each of the four channels separately. Supplementary Information: The online version contains supplementary material available at 10.1007/s10337-022-04156-w.

Combining Photodegradation in a Liquid-Core-Waveguide Cell with Multiple-Heart-Cut Two-Dimensional Liquid Chromatography.

Photodegradation greatly affects everyday life. It poses challenges when food deteriorates or when objects of cultural heritage fade, but it can also create opportunities applied in advanced oxidation processes in water purification. Studying photodegradation, however, can be difficult because of the time needed for degradation, the inaccessibility of pure compounds, and the need to handle samples manually. A novel light-exposure cell, based on liquid-core-waveguide (LCW) technology, was embedded in a multiple-heart-cut two-dimensional liquid chromatography system by coupling the LCW cell to the multiple-heart-cut valve. The sample was flushed from the heart-cut loops into the cell by an isocratic pump. Samples were then irradiated using different time intervals and subsequently transferred by the same isocratic pump to a second-dimension sample loop. The mixture containing the transformation products was then subjected to the second-dimension separation. In the current setup, about 30-40% of the selected fraction was transferred. Multiple degradation products could be monitored. Degradation was found to be faster when a smaller sample amount was introduced (0.3 µg as compared to 1.5 µg). The system was tested with three applications, that is, fuchsin, a 19th-century synthetic organic colorant, annatto, a lipophilic food dye, and vitamin B complex.

Co-Polymer sequence determination over the molar mass distribution by size-exclusion chromatography combined with pyrolysis - gas chromatography.

The chain sequence of co-polymers strongly affects their physical properties. It is, therefore, of crucial importance for the development and final properties of novel materials. Currently however, few analytical methods are available to monitor the sequence of copolymers. The currently preferred method in copolymer-sequence determination, nuclear-magnetic-resonance spectroscopy (NMR), is insensitive (especially when 13C-NMR is required) and often offers little spectral resolution between signals indicative of different subunits. These limitations are especially challenging when one is interested in monitoring the sequence across the molar-mass distribution or in quantifying low abundant subunits. Therefore, we set out to investigate pyrolysis - gas chromatography (Py-GC) as an alternative method. Py-GC is more sensitive than NMR and offers better resolution between various subunits, but it does require calibration, since the method is not absolute. We devised a method to fuse data from NMR and Py-GC to obtain quantitative information on chain sequence and composition for a set of random and block poly(methyl methacrylate-co-styrene) copolymer samples, which are challenging to analyse as MMA tends to fully depolymerize. We demonstrated that the method can be successfully used to determine the chain sequence of both random and block copolymers. Furthermore, we managed to apply Py-GC to monitor the sequence of a random and a block copolymer across the molar-mass distribution.

Critical comparison of background correction algorithms used in chromatography.

The objective of the present work was to make a quantitative and critical comparison of a number of drift and noise-removal algorithms, which were proven useful by other researchers, but which had never been compared on an equal basis. To make a rigorous and fair comparison, a data generation tool is developed in this work, which utilizes a library of experimental backgrounds, as well as peak shapes obtained from curve fitting on experimental data. Several different distribution functions are used, such as the log-normal, bi-Gaussian, exponentially convoluted Gaussian, exponentially modified Gaussian and modified Pearson VII distributions. The tool was used to create a set of hybrid (part experimental, part simulated) data, in which the background and all peak profiles and areas are known. This large data set (500 chromatograms) was analysed using seven different drift-correction and five different noise-removal algorithms (35 combinations). Root-mean square errors and absolute errors in peak area were determined and it was shown that in most cases the combination of sparsity-assisted signal smoothing and asymmetrically reweighted penalized least-squares resulted in the smallest errors for relatively low-noise signals. However, for noisier signals the combination of sparsity-assisted signal smoothing and a local minimum value approach to background correction resulted in lower absolute errors in peak area. The performance of correction algorithms was studied as a function of the density and coverage of peaks in the chromatogram, shape of the background signal, and noise levels. The developed data-generation tool is published along with this article, so as to allow similar studies with other simulated data sets and possibly other algorithms. The rigorous assessment of correction algorithms in this work may facilitate further automation of data-analysis workflows.

Improving retention-time prediction in supercritical-fluid chromatography by multivariate modelling.

The prediction of chromatographic retention under supercritical-fluid chromatography (SFC) conditions was studied, using established and novel theoretical models over ranges of modifier content, pressure and temperature. Whereas retention models used for liquid chromatography often only consider the modifier fraction, retention in SFC depends much more strongly on pressure and temperature. The viability of combining several retention models into surfaces that describe the effects of both modifier fraction and pressure was investigated. The ability of commonly used retention models to describe retention as a function of modifier fraction, expressed either as mass or volume fraction, pressure and density was assessed. Using the multivariate surfaces, retention-time prediction for isocratic separations at constant temperature improved significantly compared to univariate modelling when both pressure and modifier fractions were changed. The "mixed-mode" model with an additional exponential pressure or density parameter was able to predict retention times within 5%, with the majority of the predictions within 2%. The use of mass fraction and density further improves retention modelling compared to volume fraction and pressure. These variables however, do require extra computations.