Quantitative profiling of comprehensive composition in compound herbal injections: An NMR approach applied on Shenmai injection

LAMAIS: A library-aided approach for efficient 1D 1H NMR qualitative analysis in plant metabolomics

BACKGROUND

One-dimensional proton nuclear magnetic resonance (1D 1H NMR) spectroscopy is a non-destructive, non-targeted analytical technique providing both qualitative and quantitative insights, particularly beneficial for mixture analysis. However, the qualitative analysis of 1D 1H NMR spectra for mixture samples is laborious and time-consuming, involving extensive database searches and verification experiments like spiking. This process heavily relies on the analyst's expertise, leading to efficiency discrepancies. There is a pressing need for a reliable method to streamline operations and enhance the efficiency of qualitative analysis in complex mixtures.

RESULTS

We introduce a library-aided method for spectral profiling, named LAMAIS. This method achieves compound identification through similarity assessment between samples and template data, allowing rapid, automatic compound identification and full-spectrum peak assignment without the need for fitting. LAMAIS correctly identifies over 90 % of components in synthetic mixtures and more than 75 % in experimental mixtures, surpassing other representative methods with a higher F2 score. Our reference library, which currently includes 71 compounds, is tailored to capture the commonality of primary metabolites across diverse plant species. The analysis of real-world samples yielded encouraging results, underscoring LAMAIS's versatility as an auxiliary tool suitable for a variety of botanical sources. For analyst convenience, interactive graphics are utilized as the output format.

SIGNIFICANCE

LAMAIS excels, demonstrating competitiveness and reliability. The approach minimizes repetitive tasks and sample wastage, improving the efficiency of 1D 1H NMR qualitative analysis. Constructing a reference library effectively preserves knowledge, mitigates reliance on human experience, and addresses gaps in the analysis of plant source samples.

Characterisation and critical processes identification for production of herbal preparations using 1H-NMR and chemometrics: A case study of Trichosanthis Pericarpium injection

INTRODUCTION

Herbal preparations are extensively utilised for the treatment of diseases in Asian countries. However, the variations in origin, climate, and production processes can lead to inconsistencies in the quality of herbal preparations. Existing quality control methods only target a few components in the finished product but ignore the control in the pharmaceutical process. Therefore, this study intends to develop a comprehensive component analysis method for intermediates in the pharmaceutical process to reveal the change patterns of substances and deepen the process understanding.

OBJECTIVE

This study aims to develop a rapid and comprehensive process characterisation and critical process identification method for herbal preparations.

METHODS

Six batches of Trichosanthis Pericarpium injection (TPI) intermediates were collected from the production process. Proton nuclear magnetic resonance (1H-NMR) spectra were acquired for qualitative and quantitative analysis of the se intermediates. Subsequently, chemometrics were used to identify critical processes and potential chemical markers.

RESULTS

A total of 39 components in intermediates were identified, and the transfer of 25 components during the production process was investigated. Column chromatography was determined as the critical process. Nine components were identified as chemical markers.

CONCLUSION

The application of 1H-NMR facilitated a comprehensive reflection of the chemical composition information of process intermediates, enabling investigations into the transfer of multi-component substances and accurate identification of critical processes and chemical markers.

Exploring metabolic responses and pathway changes in CHO-K1 cells under varied aeration conditions and copper supplementations using 1 H NMR-based metabolomics

The optimization of bioprocess for CHO cell culture involves careful consideration of factors such as nutrient consumption, metabolic byproduct accumulation, cell growth, and monoclonal antibody (mAb) production. Valuable insights can be obtained by understanding cellular physiology to ensure robust and efficient bioprocess. This study aims to improve our understanding of the CHO-K1 cell metabolism using 1 H NMR-based metabolomics. Initially, the variations in culture performance and metabolic profiles under varied aeration conditions and copper supplementations were thoroughly examined. Furthermore, a comprehensive metabolic pathway analysis was performed to assess the impact of these conditions on the implicated pathways. The results revealed substantial alterations in the pyruvate metabolism, histidine metabolism, as well as phenylalanine, tyrosine and tryptophan biosynthesis, which were especially evident in cultures subjected to copper deficiency conditions. Conclusively, significant metabolites governing cell growth and mAb titer were identified through orthogonal partial least square-discriminant analysis (OPLS-DA). Metabolites, including glycerol, alanine, formate, glutamate, phenylalanine, and valine, exhibited strong associations with distinct cell growth phases. Additionally, glycerol, acetate, lactate, formate, glycine, histidine, and aspartate emerged as metabolites influencing cell productivity. This study demonstrates the potential of employing 1 H NMR-based metabolomics technology in bioprocess research. It provides valuable guidance for feed medium development, feeding strategy design, bioprocess parameter adjustments, and ultimately the enhancement of cell proliferation and mAb yield.

Machine learning integration of multi-modal analytical data for distinguishing abnormal botanical drugs and its application in Guhong injection

BACKGROUND

Determination of batch-to-batch consistency of botanical drugs (BDs) has long been the bottleneck in quality evaluation primarily due to the chemical diversity inherent in BDs. This diversity presents an obstacle to achieving comprehensive standardization for BDs. Basically, a single detection mode likely leads to substandard analysis results as different classes of structures always possess distinct physicochemical properties. Whereas representing a workaround for multi-target standardization using multi-modal data, data processing for information from diverse sources is of great importance for the accuracy of classification.

METHODS

In this research, multi-modal data of 78 batches of Guhong injections (GHIs) consisting of 52 normal and 26 abnormal samples were acquired by employing HPLC-UV, -ELSD, and quantitative 1H NMR (q1HNMR), of which data obtained was then individually used for Pearson correlation coefficient (PCC) calculation and partial least square-discriminant analysis (PLS-DA). Then, a mid-level data fusion method with data containing qualitative and quantitative information to establish a support vector machine (SVM) model for evaluating the batch-to-batch consistency of GHIs.

RESULTS

The resulting outcomes showed that datasets from one detection mode (e.g., data from UV detectors only) are inadequate for accurately assessing the product's quality. The mid-level data fusion strategy for the quality evaluation enabled the classification of normal and abnormal batches of GHIs at 100% accuracy.

CONCLUSIONS

A quality assessment strategy was successfully developed by leveraging a mid-level data fusion method for the batch-to-batch consistency evaluation of GHIs. This study highlights the promising utility of data from different detection modes for the quality evaluation of BDs. It also reminds manufacturers and researchers about the advantages of involving data fusion to handle multi-modal data. Especially when done jointly, this strategy can significantly increase the accuracy of product classification and serve as a capable tool for studies of other BDs.

The immediate adverse drug reactions induced by ShenMai Injection are mediated by thymus-derived T cells and associated with RhoA/ROCK signaling pathway

Introduction

The mechanism of the immediate adverse drug reactions (ADRs) induced by ShenMai injection (SMI) has not been completely elucidated. Within 30 minutes, the ears and lungs of mice injected with SMI for the first time showed edema and exudation reactions. These reactions were different from the IV hypersensitivity. The theory of pharmacological interaction with immune receptor (p-i) offered a new insight into the mechanisms of immediate ADRs induced by SMI.

Methods

In this study, we determined that the ADRs were mediated by thymus-derived T cells through the different reactions of BALB/c mice (thymus-derived T cell normal) and BALB/c nude mice (thymus-derived T cell deficient) after injecting SMI. The flow cytometric analysis, cytokine bead array (CBA) assay and untargeted metabolomics were used to explain the mechanisms of the immediate ADRs. Moreover, the activation of the RhoA/ROCK signaling pathway was detected by western blot analysis.

Results

In BALB/c mice, the vascular leakage and histopathology results showed the occurrence of the immediate ADRs induced by SMI. The flow cytometric analysis revealed that CD4⁺ T cell subsets (Th1/Th2, Th17/Treg) were imbalanced. And the levels of cytokines such as IL-2, IL-4, IL12P70 and INF-γ increased significantly. However, in BALB/c nude mice, all the indicators mentioned above have not changed significantly. The metabolic profile of both BALB/c mice and BALB/c nude mice was significantly changed after injecting SMI, and the notable increase in lysolecithin level might have a greater association with the immediate ADRs induced by SMI. The Spearman correlation analysis revealed that LysoPC (18:3(6Z,9Z,12Z)/0:0) showed a significant positive correlation with cytokines. After injecting SMI, the levels of RhoA/ROCK signaling pathway-related protein increased significantly in BALB/c mice. Protein-protein interaction (PPI) showed that the increased lysolecithin levels might be related to the activation of the RhoA/ROCK signaling pathway.

Discussion

Together, the results of our study revealed that the immediate ADRs induced by SMI were mediated by thymus-derived T cells, and elucidated the mechanisms of such ADRs. This study provided new insights into the underlying mechanism of immediate ADRs induced by SMI.

A multivariate curve resolution-alternating least squares (MCR-ALS) technology assisted 1 H-NMR methodology for multi-component quantitation of Trichosanthis Pericarpium injection

INTRODUCTION

Trichosanthis Pericarpium injection (TPI) is a traditional Chinese medicine preparation obtained from Trichosanthis Pericarpium by extraction, purification and sterilisation. It contains amino acids, alkaloids, nucleotides and other components. Existing quantitative methods only analyse a few components in injections, so this study intends to develop a method for comprehensive analysis of TPI components.

OBJECTIVE

To develop a method for quantification of components in TPI by multivariate curve resolution-alternating least squares (MCR-ALS) assisted proton nuclear magnetic resonance (¹ H-NMR).

METHODS

A ¹ H-NMR method was developed for the quantification of components in TPI. For components with independent signals, 3-(trimethylsilyl) propionic-2,2,3,3-d₄ acid sodium salt (TSP) was used as an internal standard to calculate the component contents. For components with overlapping signals, the method of MCR-ALS was used.

RESULTS

A total of 36 components were identified in TPI, of which 33 were quantified. Methodological validation results showed that the developed ¹ H-NMR method has good linearity, accuracy, precision, robustness and specificity.

CONCLUSION

The use of ¹ H-NMR provides a reliable and universal method for the TPI components identification and quantification. Also, it can be used as a powerful tool for analysing the contents in a complex mixture as a quality control measure.