A four-dimensional separation approach by offline 2D-LC/IM-TOF-MS in combination with database-driven computational peak annotation facilitating the in-depth characterization of the multicomponents from Atractylodis Macrocephalae Rhizoma (Atractylodes macrocephala)

Integration of non-targeted multicomponent profiling, targeted characteristic chromatograms and quantitative to accomplish systematic quality evaluation strategy of Huo-Xiang-Zheng-Qi oral liquid

Huo-Xiang-Zheng-Qi oral liquid (HXZQOL) is a well-known traditional Chinese medicine formula for the treatment of gastrointestinal diseases, with the pharmacologic effects of antiinflammatory, immune protection and gastrointestinal motility regulation. More significantly, HXZQOL is recommended for the treatment of COVID-19 patients with gastrointestinal symptoms, and it has been clinically proven to reduce the inflammatory response in patients with COVID-19. However, the effective and overall quality control of HXZQOL is currently limited due to its complex composition, especially the large amount of volatile and non-volatile active components involved. In this study, aimed to fully develop a comprehensive strategy based on non-targeted multicomponent identification, targeted authentication and quantitative analysis for quality evaluation of HXZQOL from different batches. Firstly, the non-targeted high-definition MSE (HDMSE) approach is established based on UHPLC/IM-QTOF-MS, utilized for multicomponent comprehensive characterization of HXZQOL. Combined with in house library-driven automated peak annotation and comparison of 47 reference compounds, 195 components were initially identified. In addition, HS-SPME-GC-MS was employed to analyze the volatile organic compounds (VOCs) in HXZQOL, and a total of 61 components were identified by comparison to the NIST database, reference compounds as well as retention indices. Secondly, based on the selective ion monitoring (SIM) of 24 "identity markers" (involving each herbal medicine), characteristic chromatograms (CCs) were established on LC-MS and GC-MS respectively, to authenticate 15 batches of HXZQOL samples. The targeted-SIM CCs showed that all marker compounds in 15 batches of samples could be accurately monitored, which could indicate preparations authenticity. Finally, a parallel reaction monitoring (PRM) method was established and validated to quantify the nine compounds in 15 batches of HXZQOL. Conclusively, this study first reports chemical-material basis, SIM CCs and quality evaluation of HXZQOL, which is of great implication to quality control and ensuring the authenticity of the preparation.

A compounds annotation strategy using targeted molecular networking for offline two-dimensional liquid chromatography-mass spectrometry analysis: Yupingfeng as a case study

Component overlapping and long-time consumption hinder the data processing of offline two-dimensional liquid chromatography mass spectrometry (offline 2D-LC MS) system. Although molecular networking has been commonly employed in data processing of liquid chromatography mass spectrometry (LC-MS), its application in offline 2D-LC MS is challenged by voluminous and redundant data. In light of this, for the first time, a data deduplication and visualization strategy combining hand-in-hand alignment with targeted molecular networking (TMN) for compounds annotation of offline 2D-LC MS data was developed and applied to the chemical profile of Yupingfeng (YPF), a classical traditional Chinese medicine (TCM) prescription, as a case study. Firstly, an offline 2D-LC MS system was constructed for the separation and data acquisition of YPF extract. Then the data of 12 fractions derived from YPF were deconvoluted and aligned as a whole data file by hand-in-hand alignment, resulting in a 49.2% reduction in component overlapping (from 17951 to 9112 ions) and an improvement in the MS² spectrum quality of precursor ions. Subsequently, the MS²-similarity adjacency matrix of focused parent ions was computed by a self-building Python script, which realized the construction of an innovative TMN. Interestingly, the TMN was found to be able to efficiently distinguish and visualize the co-elution, in-source fragmentations and multi-type adduct ions in a clustering network. Consequently, a total of 497 compounds were successfully identified depending on only seven TMN analysis guided by product ions filtering (PIF) and neutral loss filtering (NLF) for the targeted compounds in YPF. This integrated strategy improved the efficiency of targeted compound discovery in offline 2D-LC MS data, also shown a huge scalability in accurate compound annotation of complex samples. In conclusion, our study developed available concepts and tools while providing a research paradigm for efficient and rapid compound annotation in complex samples such as TCM prescriptions, with YPF as an example.

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.

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.

Combining multidimensional chromatography-mass spectrometry and feature-based molecular networking methods for the systematic characterization of compounds in the supercritical fluid extract of Tripterygium wilfordii Hook F

Tripterygium wilfordii Hook F from the family Celastraceae is a traditional Chinese medicine (TCM) whose principal chemical constituents are terpenoids, including sesquiterpene alkaloids and diterpenoids, which have unique and diverse structures and remarkable biological activities. In order to advance pharmacological research and guide the preparation of monomer compounds derived from T. wilfordii, a systematic approach to efficiently discover new compounds or their derivatives is needed. Herein, compound separation and identification were performed by offline reversed-phase × supercritical fluid chromatography coupled mass spectrometry (RP × SFC-Q-TOF-MS/MS) and Global Natural Product Social (GNPS) molecular networking. The 2D chromatography system exhibited a high degree of orthogonality and significant peak capacity, and SFC has an advantage during the separation of sesquiterpene alkaloid isomers. Feature-based molecular networking offers the great advantage of quickly detecting and clustering unknown compounds, which greatly assists in intuitively judging the type of compound, and this networking technique has the potential to dramatically accelerate the identification and characterization of compounds from natural sources. A total of 324 compounds were identified and quantitated, including 284 alkaloids, 22 diterpenoids and 18 triterpenoids, which means that there are numerous potential new compounds with novel structures to be further explored. Overall, feature-based molecular networking provides an effective method for discovering and characterizing novel compounds and guides the separation and preparation of targeted natural products.

An off-line three-dimensional liquid chromatography/Q-Orbitrap mass spectrometry approach enabling the discovery of 1561 potentially unknown ginsenosides from the flower buds of Panax ginseng, Panax quinquefolius and Panax notoginseng

To comprehensively elucidate the herbal metabolites is crucial in natural products research to discover new lead compounds. Ginsenosides are an important class of bioactive components from the Panax plants exerting the significant tonifying effects. However, to identify new ginsenosides by the conventional strategies trends to be more and more difficult because of the large spans of acid-base property (the neutral and acidic saponins), molecular mass (400-1400 Da), and rather low content. Herein, an off-line multidimensional chromatography/high-resolution mass spectrometry approach was presented: ion exchange chromatography (IEC) as the first dimension of separation, hydrophilic interaction chromatography (HILIC) in the second dimension, and reversed-phase chromatography (RPC) for the third dimension which was hyphenated to a Q Exactive Q-Orbitrap mass spectrometer. By applying to the flower buds of P. ginseng (PGF), P. quinquefolius (PQF), and P. notoginseng (PNF), IEC using a PhenoSphere^TM SAX column could fractionate the total extracts into the neutral (unretained) and acidic (retained) fractions, while HILIC (an XBridge Amide column) and RPC (BEH Shield RP18 column) achieved the hydrophilic interaction and hydrophobic interaction separations, respectively. Q-Orbitrap mass spectrometry offered rich structural information and complementary resolution to the co-eluting components, particular to those minor ones by including precursor ion lists in data-dependent acquisition. We could characterize 803 ginsenosides from PGF, 795 from PQF, and 833 from PNF, and 1561 thereof are potentially unknown. These results can indicate the great potential of this multidimensional approach in the ultra-deep characterization of complex herbal samples supporting the efficient discovery of potentially novel natural compounds.

Quality evaluation of Atractylodis macrocephalae rhizoma through fingerprint qualitative analysis and quantitative analysis of multi-components by single marker

A comprehensive strategy for quality evaluation of Atractylodis macrocephalae rhizoma by combining quantitative analysis of multi-components by single marker and HPLC fingerprint qualitative analysis was developed and validated in this paper. By analyzing chromatograms of 18 batches of Atractylodis macrocephalae rhizoma, the reference fingerprint of Atractylodis macrocephalae rhizoma was generated and 10 common peaks were identified, of which Atractylenolide I, atractylenolide II, atractylenolide III and atractylone were identified with chemical references. With atractylenolide III as an internal reference substance, the contents of the other three components in 18 batches of Atractylodis macrocephalae rhizoma samples were simultaneously determined by quantitative analysis of multi-components by single marker which were not significantly different from the results determined by external standard method (t test, P>0.839). The accuracy, precision, reproducibility and stability of this method were validated which exhibited satisfactory results, indicating that quantitative analysis of multi-components by single marker could be used for quantitative analysis of Atractylodis macrocephalae rhizoma instead of external standard method. The content of each component in 18 batches of Atractylodis macrocephalae rhizoma was significantly different from each other. There is no Assay specified in the quality standard of Atractylodis macrocephalae rhizoma in Chinese Pharmacopoeia (volume I) (2020 edition). This method combining quantitative analysis of multi-components by single marker and HPLC fingerprint can evaluate quality of Atractylodis macrocephalae rhizoma samples more comprehensively which is beneficial to the application of Atractylodis macrocephalae rhizoma.

Comprehensive multicomponent characterization and fingerprinting analysis of Lanqin Oral Liquid by ultra-high-performance liquid chromatography coupled with ion mobility-quadrupole time-of-flight mass spectrometry

Comprehensive characterization of the chemical constituents of Chinese patent medicine poses a great challenge due to the frustrating complexity resulting from superposition of multiple drugs. Lanqin Oral Liquid is a five-component Chinese patent medicine widely applied to treat pharyngeal inflammation in clinic. Here, we streamline a universal three-dimensional separation approach to efficiently identify the multicomponents from Lanqin Oral Liquid by ultra-high-performance liquid chromatography/ion mobility quadrupole time-of-flight mass spectrometry and UNIFI/in-house library-driven automatic peak annotation. Because of the systematic optimization, the use of an HSS T3 column enabled good separation of the multiple components within 42 min, while high-definition MS^E in both the negative and positive modes could characterize more classes of herbal components, thus providing the retention, collision cross-section, and MS information for each component. Benefiting from the ion mobility separation, cleaner MS¹ and MS² spectra were acquired. Aided by comparison and analysis of the fragmentation pathways of 49 reference compounds, we could characterize 175 compounds from Lanqin Oral Liquid. A validated high-performance liquid chromatography fingerprinting approach unveiled good similarity (0.985-1.000) among 22 batches of commercial samples. Conclusively, we demonstrated a practical solution to elucidating the chemical composition of Chinese patent medicines, with the potential of popularization.