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"Chromatography - methods"
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A Review: Sample Preparation and Chromatographic Technologies for Detection of Aflatoxins in Foods
As a class of mycotoxins with regulatory and public health significance, aflatoxins (e.g., aflatoxin B1, B2, G1 and G2) have attracted unparalleled attention from government, academia and industry due to their chronic and acute toxicity. Aflatoxins are secondary metabolites of various Aspergillus species, which are ubiquitous in the environment and can grow on a variety of crops whereby accumulation is impacted by climate influences. Consumption of foods and feeds contaminated by aflatoxins are hazardous to human and animal health, hence the detection and quantification of aflatoxins in foods and feeds is a priority from the viewpoint of food safety. Since the first purification and identification of aflatoxins from feeds in the 1960s, there have been continuous efforts to develop sensitive and rapid methods for the determination of aflatoxins. This review aims to provide a comprehensive overview on advances in aflatoxins analysis and highlights the importance of sample pretreatments, homogenization and various cleanup strategies used in the determination of aflatoxins. The use of liquid-liquid extraction (LLE), supercritical fluid extraction (SFE), solid phase extraction (SPE) and immunoaffinity column clean-up (IAC) and dilute and shoot for enhancing extraction efficiency and clean-up are discussed. Furthermore, the analytical techniques such as gas chromatography (GC), liquid chromatography (LC), mass spectrometry (MS), capillary electrophoresis (CE) and thin-layer chromatography (TLC) are compared in terms of identification, quantitation and throughput. Lastly, with the emergence of new techniques, the review culminates with prospects of promising technologies for aflatoxin analysis in the foreseeable future.
Journal Article
A guide to large-scale RNA sample preparation
RNA is becoming more important as an increasing number of functions, both regulatory and enzymatic, are being discovered on a daily basis. As the RNA boom has just begun, most techniques are still in development and changes occur frequently. To understand RNA functions, revealing the structure of RNA is of utmost importance, which requires sample preparation. We review the latest methods to produce and purify a variation of RNA molecules for different purposes with the main focus on structural biology and biophysics. We present a guide aimed at identifying the most suitable method for your RNA and your biological question and highlighting the advantages of different methods.
Journal Article
Quantitative Structure Retention-Relationship Modeling: Towards an Innovative General-Purpose Strategy
Reversed-Phase Liquid Chromatography (RPLC) is a common liquid chromatographic mode used for the control of pharmaceutical compounds during their drug life cycle. Nevertheless, determining the optimal chromatographic conditions that enable this separation is time consuming and requires a lot of lab work. Quantitative Structure Retention Relationship models (QSRR) are helpful for doing this job with minimal time and cost expenditures by predicting retention times of known compounds without performing experiments. In the current work, several QSRR models were built and compared for their adequacy in predicting the retention times. The regression models were based on a combination of linear and non-linear algorithms such as Multiple Linear Regression, Support Vector Regression, Least Absolute Shrinkage and Selection Operator, Random Forest, and Gradient Boosted Regression. Models were built for five pH conditions, i.e., at pH 2.7, 3.5, 6.5, and 8.0. In the end, the model predictions were combined using stacking and the performances of all models were compared. The k-nearest neighbor-based application domain filter was established to assess the reliability of the prediction for further compound prioritization. Altogether, this study can be insightful for analytical chemists working with RPLC to begin with the computational prediction modeling such as QSRR to predict the separation of small molecules.
Journal Article
Antibody Aggregate Removal by Multimodal Chromatography
The growing demand for therapeutic monoclonal antibodies (mAbs) has heightened the need for efficient and scalable purification strategies. A major challenge in downstream processing is the removal of antibody aggregates, which can compromise drug safety, efficacy, and regulatory compliance. This review explores the use of multimodal chromatography for aggregate separation, providing an in-depth analysis of commercially available resins and emerging adsorbent prototypes. It also examines the mechanisms of aggregate formation during bioprocessing. A comparative evaluation of conventional single-mode chromatography techniques—affinity, ion exchange, and hydrophobic interaction—is presented alongside multimodal chromatography, which integrates ion-exchange, hydrophobic, and other non-covalent interactions for enhanced aggregate clearance and process flexibility. The review primarily assesses commercial multimodal resins in terms of aggregate removal efficiency, binding capacity, and scalability. Additionally, advancements in prototype resins and multimodal membranes are discussed. Finally, the advantages, limitations, and future directions of multimodal chromatography in mAb aggregate removal are outlined. As purification demands continue to evolve, multimodal chromatography is poised to play an increasingly critical role in achieving the high purity standards required for therapeutic antibodies.
Journal Article
Multiplatform metabolomic interlaboratory study of a whole human stool candidate reference material from omnivore and vegan donors
IntroductionHuman metabolomics has made significant strides in understanding metabolic changes and their implications for human health, with promising applications in diagnostics and treatment, particularly regarding the gut microbiome. However, progress is hampered by issues with data comparability and reproducibility across studies, limiting the translation of these discoveries into practical applications.ObjectivesThis study aims to evaluate the fit-for-purpose of a suite of human stool samples as potential candidate reference materials (RMs) and assess the state of the field regarding harmonizing gut metabolomics measurements.MethodsAn interlaboratory study was conducted with 18 participating institutions. The study allowed for the use of preferred analytical techniques, including liquid chromatography-mass spectrometry (LC–MS), gas chromatography-mass spectrometry (GC–MS), and nuclear magnetic resonance (NMR).ResultsDifferent laboratories used various methods and analytical platforms to identify the metabolites present in human stool RM samples. The study found a 40% to 70% recurrence in the reported top 20 most abundant metabolites across the four materials. In the full annotation list, the percentage of metabolites reported multiple times after nomenclature standardization was 36% (LC–MS), 58% (GC–MS) and 76% (NMR). Out of 9,300 unique metabolites, only 37 were reported across all three measurement techniques.ConclusionThis collaborative exercise emphasized the broad chemical survey possible with multi-technique approaches. Community engagement is essential for the evaluation and characterization of common materials designed to facilitate comparability and ensure data quality underscoring the value of determining current practices, challenges, and progress of a field through interlaboratory studies.
Journal Article
Exploring extra dimensions to capture saliva metabolite fingerprints from metabolically healthy and unhealthy obese patients by comprehensive two-dimensional gas chromatography featuring Tandem Ionization mass spectrometry
This study examines the information potential of comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC×GC-TOF MS) and variable ionization energy (i.e., Tandem Ionization™) to study changes in saliva metabolic signatures from a small group of obese individuals. The study presents a proof of concept for an effective exploitation of the complementary nature of tandem ionization data. Samples are taken from two sub-populations of severely obese (BMI > 40 kg/m2) patients, named metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO). Untargeted fingerprinting, based on pattern recognition by template matching, is applied on single data streams and on fused data, obtained by combining raw signals from the two ionization energies (12 and 70 eV). Results indicate that at lower energy (i.e., 12 eV), the total signal intensity is one order of magnitude lower compared to the reference signal at 70 eV, but the ranges of variations for 2D peak responses is larger, extending the dynamic range. Fused data combine benefits from 70 eV and 12 eV resulting in more comprehensive coverage by sample fingerprints. Multivariate statistics, principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA) show quite good patient clustering, with total explained variance by the first two principal components (PCs) that increases from 54% at 70 eV to 59% at 12 eV and up to 71% for fused data. With PLS-DA, discriminant components are highlighted and putatively identified by comparing retention data and 70 eV spectral signatures. Within the most informative analytes, lactose is present in higher relative amount in saliva from MHO patients, whereas N-acetyl-D-glucosamine, urea, glucuronic acid γ-lactone, 2-deoxyribose, N-acetylneuraminic acid methyl ester, and 5-aminovaleric acid are more abundant in MUO patients. Visual feature fingerprinting is combined with pattern recognition algorithms to highlight metabolite variations between composite per-class images obtained by combining raw data from individuals belonging to different classes, i.e., MUO vs. MHO.Graphical abstract
Journal Article
LC-MS/MS versus TLC plus GC methods: Consistency of glycerolipid and fatty acid profiles in microalgae and higher plant cells and effect of a nitrogen starvation
Methods to analyze lipidomes have considerably evolved, more and more based on massspectrometry technics (LC-MS/MS). However, accurate quantifications using these methodsrequire 13C-labeled standards for each lipid, which is not feasible because of the verylarge number of molecules. Thus, quantifications rely on standard molecules representativeof a whole class of lipids, which might lead to false estimations of some molecular species.Here, we determined and compared glycerolipid distributions from three different types ofcells, two microalgae (Phaeodactylum tricornutum, Nannochloropsis gaditana) and onehigher plant (Arabidopsis thaliana), using either LC-MS/MS or Thin Layer Chromatographycoupled with Gas Chromatography (TLC-GC), this last approach relying on the precisequantification of the fatty acids present in each glycerolipid class. Our results showed thatthe glycerolipid distribution was significantly different depending on the method used. Howcan one reconcile these two analytical methods? Here we propose that the possible biaswith MS data can be circumvented by systematically running in tandem with the sample tobe analyzed a lipid extract from a qualified control (QC) of each type of cells, previously analyzedby TLC-GC, and used as an external standard to quantify the MS results. As a casestudy, we applied this method to compare the impact of a nitrogen deficiency on the threetypes of cells.
Journal Article
Native Liquid Chromatography and Mass Spectrometry to Structurally and Functionally Characterize Endo-Xylanase Proteoforms
Xylanases are of great value in various industries, including paper, food, and biorefinery. Due to their biotechnological production, these enzymes can contain a variety of post-translational modifications, which may have a profound effect on protein function. Understanding the structure–function relationship can guide the development of products with optimal performance. We have developed a workflow for the structural and functional characterization of an endo-1,4-β-xylanase (ENDO-I) produced by Aspergillus niger with and without applying thermal stress. This workflow relies on orthogonal native separation techniques to resolve proteoforms. Mass spectrometry and activity assays of separated proteoforms permitted the establishment of structure–function relationships. The separation conditions were focus on balancing efficient separation and protein functionality. We employed size exclusion chromatography (SEC) to separate ENDO-I from other co-expressed proteins. Charge variants were investigated with ion exchange chromatography (IEX) and revealed the presence of low abundant glycated variants in the temperature-stressed material. To obtain better insights into the effect on glycation on function, we enriched for these species using boronate affinity chromatography (BAC). The activity measurements showed lower activity of glycated species compared to the non-modified enzyme. Altogether, this workflow allowed in-depth structural and functional characterization of ENDO-I proteoforms.
Journal Article
Evaluation of coverage, retention patterns, and selectivity of seven liquid chromatographic methods for metabolomics
Liquid chromatography–mass spectrometry-based metabolomics studies require highly selective and efficient chromatographic techniques. Typically employed reversed-phase (RP) methods fail to target polar metabolites, but the introduction of hydrophilic interaction liquid chromatography (HILIC) is slow due to perceived issues of reproducibility and ruggedness and a limited understanding of the complex retention mechanisms. In this study, we present a comparison of the chromatographic performance of a traditional RP-C18 column with zwitterionic, amide-, alkyl diol-, and aminoalkyl-based HILIC and mixed-mode columns. Our metabolite library represents one of the largest analyte sets available and consists of 764 authentic metabolite standards, including amino acids, nucleotides, sugars, and other metabolites, representing all major biological pathways and commonly observed exogenous metabolites (drugs). The coverage, retention patterns, and selectivity of the individual methods are highly diverse even between conceptually related HILIC methods. Furthermore, we show that HILIC sorbents having highly orthogonal selectivity and specificity enhance the coverage of major metabolite groups in (semi-) targeted applications compared to RP. Finally, we discuss issues encountered in the analysis of biological samples based on the results obtained with human plasma extracts. Our results demonstrate that fast and highly reproducible separations on zwitterionic columns are feasible, but knowledge of analyte properties is essential to avoid chromatographic bias and exclusion of key analytes in metabolomics studies.
Graphical Abstract
The chromatographic parameters of 764 authentic metabolite standards provide the basis for a comparison of coverage, selectivity and orthogonality of 7 reversed-phase (RP), mixed-mode (MM) and hydrophilic interaction liquid chromatography (HILIC) methods
Journal Article