Analytica Chimica Acta

The use of Multi-attribute method (MAM) for identity and purity testing of biopharmaceuticals offers the ability to complement and replace multiple conventional analytical technologies with a single mass spectrometry (MS) method. Method qualification and phase-appropriate validation is one major consideration for the implementation of MAM in a current Good Manufacturing Practice (cGMP) environment. We developed an improved MAM workflow with optimized sample preparation using Lys-C digestion for therapeutic monoclonal antibodies. In this study, we qualified the enhanced MAM workflow for mAb-1 identity, product quality attributes (PQAs) monitoring and new peak detection (NPD). The qualification results demonstrated the full potential of the MAM for its intended use in mAb-1 characterization and quality control in regulated labs. To the best of our knowledge, this is the first report of MAM qualification for mAb identity, PQA monitoring, and new peak detection (NPD) in a single assay, featuring 1) the first full qualification of MAM using Lys-C digestion without desalting using a high-resolution MS, 2) a new approach for mAb identity testing using MAM, and 3) the first qualification of NPD for MAM. The developed MAM workflow and the approaches for MAM qualification may serve as a reference for other labs in the industry.

In order to implement quality control measures and create fine flavor products, an important objective in cocoa processing industry is to realize standards for characterization of cocoa raw materials, intermediate and finished products with respect to their processing stages and countries of origin. Towards this end, various works have studied separability or distinguishability of cocoa samples belonging to various processing stages in a typical cocoa processing pipeline or to different origins. Limited amount of success has been possible in this direction in that unfermented and fermented cocoa samples have been shown to group into separate clusters in PCA. However, a clear clustering with respect to the country of origin has remained elusive. In this work we suggest an alternative approach to this problem through the framework of correlation networks. For 140 cocoa samples belonging to eight countries and three progressive stages in a typical cocoa processing pipeline we compute pairwise Spearman and Pearson correlation coefficients based on the LC-MS profiles and derive correlation networks by retaining only correlations higher than a threshold. Progressively increasing this threshold reveals, first, processing stage (or sample type) modules (or network clusters) at low and intermediate values of correlation threshold and then country specific modules at high correlation thresholds. We present both qualitative and quantitative evidence through network visualization and node connectivity statistics. Besides demonstrating separability of the two data properties via this network-based method, our work suggests a new approach for studying classification of cocoa samples with nested attributes of processing stage sample types and country of origin along with possibility of including additional factors, e.g., hybrid variety, etc. in the analysis.

Detecting small amounts of analytes, especially antibodies, presents a significant challenge in high-throughput methods. Fortunately, nucleic acid amplification techniques provide a promising solution. We have successfully developed and tested an innovative technology for detecting anti-glycan antibodies, utilizing a printed glycan array combined with a rolling circle amplification reaction based on the ABO blood group antibody model. This breakthrough has dramatically enhanced the sensitivity of our immunoassay, improving it by over an order of magnitude and allowing us to detect concentrations as low as 1 ng/ml. This advancement opens new approaches for research and clinical applications, making previously undetectable analytes accessible for study.

Lipidomics, a subfield of metabolomics, involves the comprehensive analysis of lipids within biological systems and has become a cornerstone of biomedical research, driven by recent technological advancements. Lipids are crucial biomolecules in cellular functions and have been increasingly recognized for their roles in physiological and pathological processes. This study focuses on innovative strategies for developing, validating, and applying comprehensive analytical methods for untargeted lipidomics using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in human plasma and extracellular vesicles (EVs). We describe improvements based on analytical validation parameters, including inter-day repeatability, limit of quantification, precision, accuracy, recovery, and matrix effects. Plasma samples were used as a proof-of-concept study, and the method was ultimately applied to human macrophage-derived EVs. Samples preparations were achieved through four liquid-liquid extraction methods for lipids in order to achieve a broad coverage of lipid classes as well as high recovery and repeatability. Additionally, we demonstrated that a sonication-assisted homogenization step effectively facilitates lipid extraction from EVs. Through untargeted lipidomics, our study identifies and quantifies a diverse range of lipid species in human plasma (225 molecular lipids) and macrophage-derived EVs (124 molecular lipids) within different classes. Overall, we present an innovative methodology that combines pre-analytical lipid extraction techniques with high-resolution LC-MS/MS to enhance lipidomics research. This approach holds promise for personalized medicine and the discovery of novel lipid cargo associated with the various biological pathways involved with EVs biogenesis.

Phytohemagglutinin (PHA), a natural tetramer comprising PHA-E and PHA-L subunits that preferentially bind to red and white blood cells, respectively, constitutes a significant antinutritional and allergenic factor in common bean seeds. The accurate measurement of PHA content is a prerequisite for ensuring food safety inspections and facilitating genetic improvements in common bean cultivars with reduced PHA levels. Currently, mainstream methods for PHA quantification involve hemagglutination assays and immunodetection, but these methods often require fresh animal blood and lack specificity and accuracy. In this study, we present a novel LC-MS/MS-based method for PHA quantification, leveraging the advantages of isotope dilution mass spectrometry (IDMS). Two signature peptides each for PHA-E and PHA-L, along with a common signature peptide, were identified and employed for quantification, allowing differentiation between PHA-E and PHA-L subunits. The incorporation of amino acid analysis-isotope dilution mass spectrometry (AAA-IDMS) enabled precise determination of the synthetic signature peptides purity during measurement, enhancing metrological accuracy. In addition, the TCA-acetone protocol was established as the optimized method for total protein extraction from dry bean seeds. Quantitative analysis of PHA-E and PHA-L subunits in six common bean varieties using the developed method demonstrated excellent linearity (r > 0.999), sensitivity (limit of detection and quantitation as low as 2.32 ng/mg and 7.73 ng/mg, respectively), recovery (94.18-104.47%), and repeatability (relative standard deviation < 3.45%). This method has the potential to serve as a standard for measuring PHA contents in common beans and other agricultural products containing PHA.

The crucial role of Dendritic Cells (DCs) in anti-tumor immune responses depends on surface Sialic Acid (SA). The regulation of DC surface sialic acid in the Tumor Microenvironment (TME) remains underexplored. Current methods struggle to provide highly sensitive, multiplex analyses of SA and other immune protein changes in single DCs within the tumor microenvironment. Here, we employed a SERS tags method for specific and highly sensitive analysis of SA, MHCII, CD86, and CD40 in DCs using a single DC analysis microfluidic platform. We also explored the differential regulatory effects of various immune-modulating drugs and tumor supernatant on multiple immunophenotypes of DCs in different immune states. The expanded two-cell microfluidic system further allows for phenotypic analysis of DCs at different time points within the tumor microenvironment. Given this method enables highly sensitive single-cell analysis of DCs, further development of this technology for tumor microenvironment applications will aid in deeply understanding the tumor-induced suppression of DC immune function, providing valuable insights for DC-mediated tumor immunotherapy research.

The aim of this study is show that Raman spectroscopy is a sensitive tool, which can be used for analyses eggs obtained in various hens housing system. This study provided a new and simple method for hens eggs breeding systems testing. Raman methods have potential to be applied by commercial inspections in food industry for verification indications placed on eggs. The development of functional technological methods to study the quality of eggs could be an interesting way to gain profitability for the food industry, in addition to improving the general conditions of public health. A label-free Raman method for detecting spectral changes in eggs from cage systems, barn systems, free range systems and ecological systems is presented. The most important advantage of Raman spectroscopy is the ability to identify biomarkers that help estimate the quality of eggs from various hens housing systems based on spectra typical for lipids, proteins and carotenoids. We have proved that ratios 1656/1004, 1656/1444, 1444/1520 and 1656/1156 can be used as universal biomarkers to distinguish eggs from various hens housing systems. Chemometric methods have shown that eggs from ecological systems and barn systems can be distinguished based on their vibrational properties. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/480636v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1b11863org.highwire.dtl.DTLVardef@1b842d1org.highwire.dtl.DTLVardef@2ac3eborg.highwire.dtl.DTLVardef@1a48ad3_HPS_FORMAT_FIGEXP M_FIG C_FIG

In this study, we optimized a polymerization mixture to synthesize polyacrylamide-co-N,N-methylene bisacrylamide monolithic stationary phases for hydrophilic-interaction chromatography (HILIC) of intact proteins. Thermal polymerization was performed, and the effects of varying the amount of crosslinker and the porogen composition on the separation performance of the resulting columns were studied. The homogeneity of the structure and the different porosities were examined through scanning electron microscopy. Further characterization of the monolithic structure revealed a permeable (Kf between 2.5 x 10-15 and 1.40 x 10-13 m2) and polar stationary phase suitable for HILIC. The HILIC separation performance of the different columns was assessed using gradient separation of a sample containing four intact proteins, with the best performing stationary phase exhibiting a peak capacity of 51 in a gradient of 25 min. Polyacrylamide-based materials were compared with a silica-based particulate amide phase (2.7 m core-shell particles). The monolith has no residual silanol sites and, therefore, fewer sites for ion-exchange interactions with proteins. Thus, it required lower concentrations of ion-pair reagent in HILIC of intact proteins. When using 0.1% of trifluoroacetic acid (TFA) the peak capacities of the two columns were similar (31 and 36 for the monolithic and packed column, respectively). However, when decreasing the concentration of TFA to 0.005%, the monolithic column maintained its separation performance and selectivity (peak capacity 26), whereas the packed column showed greatly reduced performance (peak capacity 7), lower selectivity, and inability to elute all four reference proteins. Finally, using a mobile phase containing 0.1% formic acid and 0.005% TFA the HILIC separation on the monolithic column was successfully hyphenated with high-resolution mass spectrometry. Detection sensitivity for protein and glycoproteins was increased and the amount of adducts formed was decreased in comparison with separations performed at 0.1% TFA.

PCR amplification of GC-rich regions often leads to low yield and specificity. Addition of PCR-enhancing compounds is employed in order to overcome these obstacles. PCR-enhancing additives are low molecular polar organic compounds that are included as undisclosed co-solvents in commercial PCR buffers. In the interest of transparency and to permit further optimization by researchers of PCR compositions for challenging amplification problems, we studied eight PCR buffers by GC/MS to identify and quantify their co-solvents. Buffer specificity, both rich in water and salified substances, required a suitable sample preparation before injection into the GC/MS system. The aqueous phase of each buffer was replaced by an organic solvent to remove, by precipitation and filtration, salified substances which are detrimental to the GC/MS analysis. This approach has demonstrated the advantage of eliminating both water and salified substances without any loss of co-solvents. The sensitivity of the developed method was demonstrated as the main co-solvents were easily detected, identified and quantified. The methodology for identifying the co-solvents is mainly based on comparison of both library matching of acquired MS spectra with NIST library and experimental mass spectra obtained from authentic chemical standards. For the quantification of each co-solvent, deuterated Internal standards of similar structure to the cosolvents were used to correct the variable recovery caused by sample preparation, matrix effects, and ion source variability. The recovery ratio of the developed method was verified and found to be in the range 90-120 %. We then characterized the effects of specific organic co-solvents identified during PCR amplification -- using DNA melting, polymerase thermostability, polymerase activity and real-time PCR methods -- in order to elucidate their mechanism of action and to permit further optimization of their effects on amplification efficiency and specificity.

The COVID-19 pandemic has catalyzed interest in immuno-multiple reaction monitoring (immuno-MRM) methods, with the detection of peptides unique to the nucleocapsid protein in nasopharyngeal swabs. While current applications predominantly focus on disease biomarkers, the pandemic has unveiled new opportunities, namely for the quantification of antigen expression following mRNA vaccination. Here, we present an optimized immuno-MRM method for quantifying SARS-CoV-2 spike protein fusion peptide, SFIEDLLFNK, for several practical applications. The method is versatile, applicable to multiple biological matrices, including plasma, and can be extended to nasopharyngeal swabs. It also offers a high-precision tool for assessing protein expression following plasmid and mRNA transfection. Moreover, in parallel to enabling accurate antigen quantification, the flow-through can be used to determine the proteome profile of the infected cells, providing insights into the intracellular immune response. This dual capability supports the rapid optimization of mRNA vaccines, thereby driving advancements in vaccine development strategies.

1Phospholipid oxidation (OxPL) generates a wide variety of products with potentially novel biological activities that may be associated with disease pathogenesis. To understand their role in disease requires precise information about their abundance in biological samples. Liquid chromatography-mass spectrometry (LCMS) is a sensitive technique that can provide detailed information about the oxidative lipidome, but challenges remain. Furthermore, variation in charge of the polar head groups and the extreme diversity of oxidised species make analysis of several classes of OxPLs within one analytical run challenging.\n\nThe work in this study aims to develop improved methods for detection of OxPLs by improvement of chromatographic separation through the serial coupling of polystyrene-divinylbenzene based monolithic, and mixed-mode hydrophilic interaction (HILIC) with use of semi-targeted mass spectrometry approaches. The results suggests that by serially coupling two columns, HILIC and monolith, provided the better coverage of OxPL species in a single analytical run. We tested in-vitro generated oxidized species for phosphatidylcholine (PC) and phosphatidylethanolamine (PE) class and the combination of orthogonal chromatographic separation allowed separation of oxdised species from both the classes, which otherwise coeluted.

Quantitative information on blood metabolites has the potential to be utilized in medical strategies such as early disease detection and prevention. Monitoring of bioactive lipids, such as steroids, bile acids, and polyunsaturated fatty acid (PUFA) metabolites, could be a valuable indicator for health status. However, a method for simultaneous measurement of these bioactive lipids has not been reported at present. Here, we report a liquid chromatography tandem mass spectrometry (LC/MS/MS) method that can simultaneously measure more than 140 bioactive lipids, including steroids, bile acids, and PUFA metabolites, from human plasma, and a sample preparation method for these targets. Protein removal in methanol precipitation and purification operations of bioactive lipids by solid-phase extraction improved the recovery of targeted compounds in human plasma samples, demonstrating the importance of sample preparation methods in a wide range of bioactive lipid analyses. Using the developed method, we measured plasma from healthy human volunteers and confirmed the presence of bioactive lipid molecules associated with sex differences and circadian rhythms. The practical bioactive lipid analysis method developed is expected to be applied to health monitoring and disease biomarker discovery for precision medicine.

Exosomes have been implicated in many biological processes as intercellular communication carriers. Because exosomes are increasingly explored as natural vehicles for cell and gene therapies, and drug delivery applications, it is critical to have high-quality samples. Protein:particle ratio, ELISA, western blotting, polymerase chain reaction, and size-exclusion high-performance liquid chromatography are the main methods that have been extensively applied to analyze exosomes purity in recent years. However, there is currently no well-established method that is convenient for routine quality analysis of small-size impurities in exosomes samples. Here, a size-exclusion high-performance liquid chromatography (SE-HPLC), an ion-exchange high-performance liquid chromatography (IEX-HPLC), and a novel two-dimensional high-performance liquid chromatography (2D-HPLC) method were used to detect the purity of bovine milk-derived exosomes with different processes of exosome isolation in detail. The results showed that the 2D-HPLC method could enhance the accuracy of detecting exosomal purity with higher precision and accuracy of instrumental, reduced personal error and experimental cost, shortened analysis time greatly, and more automation. The 2D-HPLC method is rapid, exhibits high selectivity, and has good sensitivity, thus making it well-suited for application in the pharmaceutical and toxicological analysis of exosomes.

In the last decade, many mass spectrometric fingerprinting methods dedicated to lipidomics have been proposed: either non-targeted approaches, coupled with annotation methods, or targeted strategies, aiming at specifically monitoring a limited number of substances. In a general public health perspective and through a strategy combining non-targeted and targeted lipidomics MS-based approaches, this study aims at identifying disrupted patterns in serum lipidome upon growth promoter treatment in pig and evaluating the relative contributions of the three platforms involved. Pig serum samples collected during an animal experiment involving control and treated animals, whose food had been supplemented with ractopamine, were extracted and characterised using three MS strategies: Non-targeted RP LC-HRMS; the targeted Lipidyzer platform (differential ion mobility associated with shotgun lipidomics) and a homemade LC-HRMS triglyceride platform. The three different platforms showed complementarity insight into lipid characterisation, which, applied to a selected set of samples, enabled highlighting specific lipid profile patterns involving various lipid classes, mainly in relation with cholesterol esters, sphingomyelins, lactosylceramide, phosphatidylcholines and triglycerides. Thanks to the combination of both non-targeted and targeted MS approaches, the exploration of various compartments of the pig serum lipidome could be performed, including commonly characterised lipids (Lipidyzer), triglyceride isomers (Triglyceride platform) -whose accurate analysis was considered an analytical challenge, and unique lipid features (non-targeted LC-HRMS). Thanks to their respective characteristics, the complementarity of the three tools could be demonstrated for public health purposes, with enhanced lipidome coverage, level of characterisation and applicability.

Accurate EV quantitation is essential for ensuring quality, consistency, and safety during large-scale extracellular vesicle (EV) manufacturing. In the upstream phase, EV quantitation allows for the monitoring of cell culture conditions that impact EV yield and quality, while in the downstream phase, it helps to control the efficiency and purity of EV purification. Nanoparticle Tracking Analysis is the most commonly used method for EV quantification, while it faces significant limitations due to interference from nanosize contaminants like protein aggregates, especially in crude samples (e.g. cell culture media). To address this issue, we developed a highly specific and accurate ELISA assay that quantifies EVs even in crude samples. With ultra-pure EV standard samples, this assay showed reliable quantitative result of EV detection to support method development as well as in-process control of large-scale EV manufacture. The detection range of this assay is from 4.1E7 to 3E10 EVs/mL, with an LOD of 1.04E7 EVs/mL and an LOQ of 3.21E7 EVs/mL. We therefore developed this assay into a testing kit and demonstrated that this EV quantification ELISA kit is capable of ensuring minimal interference from impurities and supporting the process development and in-process control in EV production.

Heavy metal contaminants and adulteration in cow milk products are major issues affecting milk safety and quality, posing health risks to consumers of all ages. These contaminants are sometimes difficult to detect with the naked eye and can potentially pass sensory tests, particularly in white cow milk. This research explores the detection of lead(II) poisoning in milk post-production and the adulteration of different milk samples using an alternative approach through chemometric techniques based on RGB and Grey Area image analysis. A controlled photography environment was used. We analyzed over 105 samples of control, adulterated, and lead(II)-added milk in this study using image processing software. Each photograph was analyzed to provide triplicate Regions of Interest (ROI), resulting in a total of 315 statistical datasets. We found that Principal Component Analysis (PCA) effectively clustered control white milk and Pb(II)-contaminated milk. Clusters of different adulterants were recognized simply by feeding RGB and Grey Area data into PCA. However, some clusters, such as mixed chocolate milk and white milk with lead(II) contamination, were not well distinguished. In this early-stage method, a comparison study with infrared spectra will be required in future research. This alternative method shows potential promise for deployment in limited settings for real-world food quality surveillance and regulation.

The mass spectrometry based multi-attribute method (MAM) has gained popularity in the field of biopharmaceutical analysis as it promises a single method for comprehensive monitoring of multiple product quality attributes (PQAs) and product purity. Sample preparation for protein digestion and peptide separation are critical considerations for a reduced peptide mapping-based MAM. To avoid desalting steps required in tryptic protein digestion and in order to improve peptide separation for hydrophilic peptides, we developed an improved robust sample preparation using Lys-C protease for high-throughput MAM testing. Additionally, this method optimizes the peptide retention and separation of a stability-indicating VSNK peptide using a HSS T3 column for comprehensive PQA monitoring. A fully automated sample preparation had similar assay variations for PQAs monitoring compared to manual sample preparation. To the best of our knowledge, this is the first report of a high-resolution MS-based MAM using Lys-C digestion with enhanced PQA monitoring for hydrophilic peptides. The improved, robust MAM workflow for protein digestion and peptide separation will pave the way for broader MAM qualification and its applications for the characterization and quality control of therapeutic monoclonal antibodies.

Metal homeostasis is a complex process wherein essential metals serving structural, catalytic and regulatory roles are acquired, trafficked, and exported once they are present in excess. Understanding changes in metal content and localization in heterogenous tissue types is critical to understanding fundamental physiology as well as a growing number of disease states. Laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOF-MS) imaging is a powerful technique for untargeted quantitation and mapping of metals in biological systems. While the nematode Caenorhabditis elegans (C. elegans) is a well-established model organism for fundamental biological research and metal-based diseases, there have been few reports of mass spectrometry-based imaging of C. elegans, mostly due to challenges preparing samples that maintain the native distribution of the elements. In this study, we developed an embedding, quantitation and imaging workflow that preserves C. elegans using 3D-printed uniform layer media application tools (ULMATs). Multiple embedding media were evaluated, and petrolatum, commercially known as Vaseline, stood out for its performance in preserving C. elegans for imaging applications. Worms were subjected to microscopy and LA-ICP-TOF-MS imaging where we achieved a 2-m spatial resolution by over-sampling laser shots during ablation. Quantitative elemental maps were obtained using a series of gelatin standards that were sectioned at a 40-m thickness to closely mimic the average tissue ablation depth of a Day 1 gravid adult C. elegans. Our results establish a new workflow for comprehensive elemental profiling of C. elegans using LA-ICP-TOF-MS, which holds high potential for future spatial metal biology research with C. elegans. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/698490v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@7c66c5org.highwire.dtl.DTLVardef@13f4934org.highwire.dtl.DTLVardef@1df3215org.highwire.dtl.DTLVardef@512fd2_HPS_FORMAT_FIGEXP M_FIG C_FIG

Digital polymerase chain reaction (PCR) is a fast-developed technology, which makes it possible to provide absolute quantitative results. However, this technology has not been widely used in research field or clinical diagnostics. Although digital PCR has been born for two decades, the products on this subject still suffer from either high cost or cumbersome user experience, hence very few labs have the willingness or budget to routinely use such product; On the other hand, the unique sensitivity of dPCR over traditional qPCR shows great potential applications. Here, a cost-effective digital PCR method based on a microfluidic printing system was introduced, trying to overcome those shortcomings. The microfluidic droplet printing technology was utilized in this study to directly generate droplet array containing PCR reaction solution onto the simple glass substrate for the subsequent PCR and imaging, which could be done with any regular flat-panel PCR machine and microscope. The method introduces a new perspective in droplet-based digital PCR in that the droplets generated with this method aligns well in an array without touch with each other, therefore the regular glass and oil could be used without any special surfactant. With simple analysis, the data generated with this method showed reliable quality, which followed the Poisson distribution trend. Compared with other expensive digital PCR methods, this system is more affordable and simpler to integrate, especially for those biological or medical labs which are in need for the digital PCR options but short in budget. Therefore, this method is believed to have the great potential in the future market application.

The identification of xenobiotics in nontargeted metabolomic analyses is a vital step in understanding human exposure. Xenobiotic metabolism, excretion, and co-existence with other endogenous molecules however greatly complicate nontargeted studies. While mass spectrometry (MS)-based platforms are commonly used in metabolomic measurements, deconvoluting endogenous metabolites and xenobiotics is often challenged by the lack of xenobiotic parent and metabolite standards as well as the numerous isomers possible for each small molecule m/z feature. Here, we evaluate the use of ion mobility spectrometry coupled with MS (IMS-MS) and mass defect filtering in a xenobiotic structural annotation workflow to reduce large metabolomic feature lists and uncover potential xenobiotic classes and species detected in the metabolomic studies. To evaluate the workflow, xenobiotics having known high toxicities including per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) were examined. Initially, to address the lack of available IMS collision cross section (CCS) values for per- and polyfluoroalkyl substances (PFAS), 88 PFAS standards were evaluated with IMS-MS to both develop a targeted PFAS CCS library and for use in machine learning predictions. The CCS values for biomolecules and xenobiotics were then plotted versus m/z, clearly distinguishing the biomolecules and halogenated xenobiotics. The xenobiotic structural annotation workflow was then used to annotate potential PFAS features in NIST human serum. The workflow reduced the 2,423 detected LC-IMS-MS features to 80 possible PFAS with 17 confidently identified through targeted analyses and 48 additional features correlating with possible CompTox entries.