A multi-dimensional liquid chromatography/high-resolution mass spectrometry approach combined with computational data processing for the comprehensive characterization of the multicomponents from Cuscuta chinensis

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry

Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.

Preliminary Exploration of Potential Active Ingredients and Molecular Mechanisms of Yanggan Yishui Granules for Treating Hypertensive Nephropathy Using UPLC-Q-TOF/MS Coupled with Network Pharmacology and Molecular Docking Strategy

Hypertensive nephropathy (HN) is a prevalent complication of hypertension and stands as the second primary reason for end-stage renal disease. Research in clinical settings has revealed that Yanggan Yishui Granule (YGYSG) has significant therapeutic effects on HN. However, the material basis and action mechanisms of YGYSG against HN remain unclear. Consequently, this study utilized a comprehensive method integrating ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS), network pharmacology, and molecular docking to delineate the active ingredients and potential therapeutic mechanisms of YGYSG for treating HN. Firstly, sixty distinct components were recognized in total as potential active ingredients in YGYSG by UPLC-Q-TOF/MS. Subsequently, the mechanisms of YGYSG against HN were revealed for the first time using network pharmacology. 23 ingredients played key roles in the complete network and were the key active ingredients, which could affect the renin-angiotensin system, fluid shear stress and atherosclerosis, HIF-1 signaling pathway, and AGE-RAGE signaling pathway in diabetic complications by regulating 29 key targets such as TNF, IL6, ALB, EGFR, ACE, and MMP2. YGYSG could treat HN through the suppression of inflammatory response and oxidative stress, attenuating the proliferation of renal vascular smooth muscle cells, lessening glomerular capillary systolic pressure, and ameliorating renal dysfunction and vascular damage through the aforementioned targets and pathways. Molecular docking results revealed that most key active ingredients exhibited a high affinity for binding to the key targets. This study pioneers in clarifying the bioactive compounds and molecular mechanisms of YGYSG against HN and offers scientific reference into the clinical application.

A powerful two-dimensional chromatography method for the non-target analysis of depolymerised lignin

BACKGROUND

Lignin is an abundant natural polymer obtained as a by-product from the fractionation of lignocellulosic biomass. In the name of a circular economy, lignin should be valorised into valuable chemicals or biomaterials and utilised instead of petrochemicals. For the development of efficient valorisation processes, the structural characterisation of lignin can be highly beneficial. However, this is an arduous task, as the isolated (and sometimes processed) lignin mainly consists of various neutral monomers but also oligomers. In addition, the material contains isomers, which can be especially problematic to separate and identify.

RESULTS

We present a powerful off-line comprehensive two-dimensional (2D) chromatography method combining liquid chromatography (LC), supercritical fluid chromatography (SFC), and high-resolution mass spectrometry for the non-target analysis of depolymerised lignin. The implementation of a 1-aminoanthracene column in the second dimension enabled a class separation of potential lignin monomers, dimers, trimers, and tetramers with an additional separation based on the number of hydroxyl groups and steric effects. The pentafluorophenyl column in the first dimension additionally improved the separation based on hydrophobicity. The comparison of off-line 2D LC × SFC to 1D SFC showed that besides the overall improved performance, the first method is also superior for the separation of isomers. Advanced data analysis methods (MS-DIAL, SIRIUS, and Feature-Based Molecular Network) were integrated into the non-target workflow to rapidly visualise and study the detected compounds, which proved to be especially beneficial for the characterisation of the separated isomers.

SIGNIFICANCE

The method yielded the first 2D LC plot demonstrating a classification of lignin compounds, which can be applied to compare various lignin sources and processing methods. In addition, the technique demonstrated improved separation of compounds, including isomers, which was especially beneficial as 77 % of the detected compounds had at least one isomer in the same lignin sample.

Composition analysis of Compound Shenhua Tablet, a seven-herb Chinese medicine for IgA nephropathy: evaluation of analyte-capacity of the assays

Compound Shenhua Tablet, a medicine comprising seven herbs, is employed in treating IgA nephropathy. This study aimed to meticulously analyze its chemical composition. Based on a list of candidate compounds, identified through extensive literature review pertinent to the tablet's herbal components, the composition analysis entailed the systematic identification, characterization, and quantification of the constituents. The analyte-capacity of LC/ESI-MS-based and GC/EI-MS-based assays was evaluated. The identified and characterized constituents were quantified to determine their content levels and were ranked based on the constituents' daily doses. A total of 283 constituents, classified into 12 distinct categories, were identified and characterized in the Compound Shenhua Tablet. These constituents exhibited content levels of 1-10 982 μg·g-1, with daily doses of 0.01-395 μmol·d-1. The predominant constituents, with daily doses of ≥ 10 μmol·d-1, include nine organic acids (citric acid, quinic acid, chlorogenic acid, cryptochlorogenic acid, gallic acid, neochlorogenic acid, isochlorogenic acid C, isochlorogenic acid B, and linoleic acid), five iridoids (specnuezhenide, nuezhenoside G13, nuezhenidic acid, secoxyloganin, and secologanoside), two monoterpene glycosides (paeoniflorin and albiflorin), a sesquiterpenoid (curzerenone), a triterpenoid (oleanolic acid), and a phenylethanoid (salidroside). Additionally, there were 83, 126, and 55 constituents detected in the medicine with daily doses of 1-10, 0.1-1, and 0.01-0.1 μmol·d-1, respectively. The combination of the LC/ESI-MS-based and GC/EI-MS-based assays demonstrated a complementary relationship in their analyte-capacity for detecting the constituents present in the medicine. This comprehensive composition analysis establishes a solid foundation for further pharmacological research on Compound Shenhua Tablet and facilitates the quality evaluation of this complex herbal medicine.

Two Multidimensional Chromatography/High-Resolution Mass Spectrometry Approaches Enabling the In-Depth Metabolite Characterization Simultaneously from Three Glycyrrhiza Species: Method Development, Comparison, and Integration

Two offline multidimensional chromatography/high-resolution mass spectrometry systems (method 1: fractionation and online two-dimensional liquid chromatography, 2D-LC; method 2: fractionation and offline 2D-LC) were established to characterize the metabolites simultaneously from three Glycyrrhiza species. Ion exchange chromatography in the first-dimensional (1D) separation was well fractionated between the acidic (mainly triterpenoids) and weakly acidic components (flavonoids). These obtained subsamples got sophisticated separation by the second (2D) and third dimension (3D) of chromatography either by online reversed-phase chromatography × reversed-phase chromatography (RPC × RPC) or offline hydrophilic interaction chromatography × RPC (HILIC × RPC). Orthogonality for the 2D/3D separations reached 0.73 for method 1 and 0.81 for method 2, respectively. We could characterize 1097 compounds from three Glycyrrhiza species based on an in-house library and 33 reference standards, involving 618 by method 1 and 668 by method 2, respectively. They exhibited a differentiated performance and complementarity in identifying the multiple subclasses of Glycyrrhiza components.

Gain deeper insights into traditional Chinese medicines using multidimensional chromatography combined with chemometric approaches

Traditional Chinese medicines (TCMs) possess a rich historical background, unique theoretical framework, remarkable therapeutic efficacy, and abundant resources. However, the modernization and internationalization of TCMs have faced significant obstacles due to their diverse ingredients and unknown mechanisms. To gain deeper insights into the phytochemicals and ensure the quality control of TCMs, there is an urgent need to enhance analytical techniques. Currently, two-dimensional (2D) chromatography, which incorporates two independent separation mechanisms, demonstrates superior separation capabilities compared to the traditional one-dimensional (1D) separation system when analyzing TCMs samples. Over the past decade, new techniques have been continuously developed to gain actionable insights from complex samples. This review presents the recent advancements in the application of multidimensional chromatography for the quality evaluation of TCMs, encompassing 2D-gas chromatography (GC), 2D-liquid chromatography (LC), as well as emerging three-dimensional (3D)-GC, 3D-LC, and their associated data-processing approaches. These studies highlight the promising potential of multidimensional chromatographic separation for future phytochemical analysis. Nevertheless, the increased separation capability has resulted in higher-order data sets and greater demands for data-processing tools. Considering that multidimensional chromatography is still a relatively nascent research field, further hardware enhancements and the implementation of chemometric methods are necessary to foster its robust development.

Phytochemical profile and anti-inflammatory activity of the hull of γ-irradiated wheat mutant lines (Triticum aestivum L.)

Wheat (Triticum aestivum Linn.; Poaceae) is the second most cultivated food crop among all global cereal crop production. The high carbohydrate content of its grains provides energy, multiple nutrients, and dietary fiber. After threshing, a substantial amount of wheat hull is produced, which serves as the non-food component of wheat. For the valorization of these by-products as a new resource from which functional components can be extracted, the hull from the seeds of cultivated wheat mutant lines bred after γ-irradiation were collected. Untargeted metabolite analysis of the hull of the original cultivar (a crossbreeding cultivar., Woori-mil × D-7) and its 983 mutant lines were conducted using ultra-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry technique. A total of 55 molecules were tentatively identified, including 21 compounds found in the Triticum species for the first time and 13 compounds not previously described. Among them, seven flavonolignans with a diastereomeric structure, isolated as a single compound from the hull of T. aestivum in our previous study, were used as the standards in the metabolite analysis. The differences in their collision cross-section values were shown to contribute to the clear distinction between tricine-lignan stereoisomers. To select functionally active agents with anti-inflammatory activity among the identified compounds, the wheat hull samples were evaluated for their inhibitory effect on nitric oxide production in lipopolysaccharide-stimulated RAW 264.7 cells. As a result of multivariate analysis based on the results of chemical and biological profiles of the wheat hull samples, 10 metabolites were identified as key markers, contributing to the distinction between active and inactive mutant lines. Considering that one of the four key markers attributed to anti-inflammatory activity has been identified to be a flavonolignan, the wheat hull could be a valuable source of diverse tricin-lignan type compounds and used as a natural health-promoting product in food supplements.

Two-dimensional liquid chromatography and ion mobility-mass spectrometry for the multicomponent characterization of different parts of the medicinal plant Gynostemma longipes

Herba Gynostemma (Jiaogulan) is an herbaceous plant of the genus Gynostemma in the family Cucurbitaceae. Gynostemma longipes has lipid-lowering activity, thus, it is used as a medicinal material. However, its medicinal using parts have been recorded as whole plants or aerial parts in different provincial quality standards; therefore, it is necessary to conduct a comprehensive compositional analysis of the different parts of G. longipes (rhizomes, stems, and leaves) used in traditional medicine. In this study, offline two-dimensional liquid chromatography-ion mobility-quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS) was used to analyze the different parts of G. longipes obtained from Shaanxi province, China. By combining the retention times, mass fragments, collision cross-section values, reference standards, and information concerning literature compounds, 396 components were identified from the three parts of the plant, including 94 groups of isomers, and 217 components were identified or tentatively identified as new compounds. In the rhizomes, leaves, and stems, 240, 220, and 168 compounds, respectively, were identified. Differential analysis of the compounds in the rhizomes and aerial parts was also carried out, and 36 differential components were identified, of which 32 had higher contents in the rhizomes. Therefore, these findings indicate that the number of chemical components and the content of major differential components are higher in the rhizomes than the leaves and stems of G. longipes from the Maobaling Planting Base in Pingli county, Shaanxi province. Thus, the rhizomes of G. longipes are also an important part for medicinal use. These results will contribute to the establishment of quality control methods for G. longipes.

Collision cross section measurement and prediction methods in omics

Omics studies such as metabolomics, lipidomics, and proteomics have become important for understanding the mechanisms in living organisms. However, the compounds detected are structurally different and contain isomers, with each structure or isomer leading to a different result in terms of the role they play in the cell or tissue in the organism. Therefore, it is important to detect, characterize, and elucidate the structures of these compounds. Liquid chromatography and mass spectrometry have been utilized for decades in the structure elucidation of key compounds. While prediction models of parameters (such as retention time and fragmentation pattern) have also been developed for these separation techniques, they have some limitations. Moreover, ion mobility has become one of the most promising techniques to give a fingerprint to these compounds by determining their collision cross section (CCS) values, which reflect their shape and size. Obtaining accurate CCS enables its use as a filter for potential analyte structures. These CCS values can be measured experimentally using calibrant-independent and calibrant-dependent approaches. Identification of compounds based on experimental CCS values in untargeted analysis typically requires CCS references from standards, which are currently limited and, if available, would require a large amount of time for experimental measurements. Therefore, researchers use theoretical tools to predict CCS values for untargeted and targeted analysis. In this review, an overview of the different methods for the experimental and theoretical estimation of CCS values is given where theoretical prediction tools include computational and machine modeling type approaches. Moreover, the limitations of the current experimental and theoretical approaches and their potential mitigation methods were discussed.

Collision Cross Section Prediction Based on Machine Learning

Ion mobility-mass spectrometry (IM-MS) is a powerful separation technique providing an additional dimension of separation to support the enhanced separation and characterization of complex components from the tissue metabolome and medicinal herbs. The integration of machine learning (ML) with IM-MS can overcome the barrier to the lack of reference standards, promoting the creation of a large number of proprietary collision cross section (CCS) databases, which help to achieve the rapid, comprehensive, and accurate characterization of the contained chemical components. In this review, advances in CCS prediction using ML in the past 2 decades are summarized. The advantages of ion mobility-mass spectrometers and the commercially available ion mobility technologies with different principles (e.g., time dispersive, confinement and selective release, and space dispersive) are introduced and compared. The general procedures involved in CCS prediction based on ML (acquisition and optimization of the independent and dependent variables, model construction and evaluation, etc.) are highlighted. In addition, quantum chemistry, molecular dynamics, and CCS theoretical calculations are also described. Finally, the applications of CCS prediction in metabolomics, natural products, foods, and the other research fields are reflected.

Systematical characterization of gypenosides in Gynostemma pentaphyllum and the chemical composition variation of different origins

Gynostemma pentaphyllum (Thunb.) Makino is an herbaceous plant of Cucurbitaceae family, which has been widely used as an herbal tea and traditional Chinese medicine. Since its saponins are similar to ginsenosides and have a wide range of activities, it has attracted wide interest. However, there are still a large number of unknown saponins that have not been isolated, especially some trace gypenosides. In the present study, a HILIC × RP offline two-dimensional liquid separation combined with a multimode data acquisition was developed for the systematical characterization of gypenosides. On top of the negative mode information, considering that saponins are prone to in-source fragmentations in positive ion mode, a precursor ion list data acquisition method was used for the targeted acquisition of multistage positive data. Reference herbal drug was taken as a golden sample to probe the chemical composition of G. pentaphyllum. The mixed sample of commercially available samples were also analyzed in parallel. Furthermore, the chemical compositions of commercially available samples from different sources were compared. In total, 1108 saponins were characterized, among which 588 were accurately characterized, with 574 identified in the reference herbal drug and 700 in the mixed commercially available samples. The commercially available samples showed great composition variation. These findings clarified the material basis and provided clues for quality control of G. pentaphyllum.

Multicomponent Characterization of the Flower Bud of Panax notoginseng and Its Metabolites in Rat Plasma by Ultra-High Performance Liquid Chromatography/Ion Mobility Quadrupole Time-of-Flight Mass Spectrometry

The flower bud of Panax notoginseng (PNF) consumed as a tonic shows potential in the prevention and treatment of cardiovascular diseases. To identify the contained multi-components and, in particular, to clarify which components can be absorbed and what metabolites are transformed, unveiling the effective substances of PNF is of vital significance. A unique ultrahigh-performance liquid chromatography/ion mobility quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS) profiling approach and efficient data processing by the UNIFI^TM bioinformatics platform were employed to comprehensively identify the multi-components of PNF and the related metabolites in the plasma of rats after oral administration (at a dose of 3.6 g/kg). Two MS² data acquisition modes operating in the negative electrospray ionization mode, involving high-definition MS^E (HDMS^E) and data-dependent acquisition (DDA), were utilized aimed to extend the coverage and simultaneously ensure the quality of the MS² spectra. As a result, 219 components from PNF were identified or tentatively characterized, and 40 thereof could be absorbed. Moreover, 11 metabolites were characterized from the rat plasma. The metabolic pathways mainly included the phase I (deglycosylation and oxidation). To the best of our knowledge, this is the first report that systematically studies the in vivo metabolites of PNF, which can assist in better understanding its tonifying effects and benefit its further development.

Integrating Enhanced Profiling and Chemometrics to Unveil the Potential Markers for Differentiating among the Leaves of Panax ginseng, P. quinquefolius, and P. notoginseng by Ultra-High Performance Liquid Chromatography/Ion Mobility-Quadrupole Time-of-Flight Mass Spectrometry

The leaves of Panax species (e.g., Panax ginseng-PGL, P. quinquefolius-PQL, and P. notoginseng-PNL) can serve as a source for healthcare products. Comprehensive characterization and unveiling of the metabolomic difference among PGL, PQL, and PNL are critical to ensure their correct use. For this purpose, enhanced profiling and chemometrics were integrated to probe into the ginsenoside markers for PGL/PQL/PNL by ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS). A hybrid scan approach (HDMS^E-HDDDA) was established achieving the dimension-enhanced metabolic profiling, with 342 saponins identified or tentatively characterized from PGL/PQL/PNL. Multivariate statistical analysis (33 batches of leaf samples) could unveil 42 marker saponins, and the characteristic ginsenosides diagnostic for differentiating among PGL/PQL/PNL were primarily established. Compared with the single DDA or DIA, the HDMS^E-HDDDA hybrid scan approach could balance between the metabolome coverage and spectral reliability, leading to high-definition MS spectra and the additional collision-cross section (CCS) useful to differentiate isomers.