Identification of velvet antler and its mixed varieties by UPLC-QTOF-MS combined with principal component analysis

Digital identification of Aucklandiae radix, Vladimiriae radix, and Inulae radix based on multivariate algorithms and UHPLC-QTOF-MS analysis

INTRODUCTION

The identification of Aucklandiae Radix (AR), Vladimiriae Radix (VR), and Inulae Radix (IR) based on traits and microscopic features is susceptible to the state of samples and the subjective awareness of personnel, and the identification based on a few or single chemical compositions is a cumbersome and time-consuming procedure and fails to rationally and effectively utilize the information of unknown components and is not specificity enough.

OBJECTIVES

This study aimed to improve the identification efficiency, strengthen supervision, and realize digital identification of three Chinese medicines. Ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) combined with multivariate algorithms was used to explore the digital identification of AR, VR, and IR.

MATERIALS AND METHODS

UHPLC-QTOF-MS was used to analyze AR, VR, and IR. The MS data combined with multivariate algorithms such as partial least squares discrimination analysis (PLS-DA) and artificial neural networks (ANNs) was used to filter important variables and data modeling. Finally, the optimal model was selected for the digital identification of three herbs.

RESULTS

The results showed that three herbs can be distinguished on the whole level, and through feature screening, 591 characteristic variables combined with multivariate algorithms to construct data models. The ANN model was the best with accuracy = 0.983, precision = 0.984, and external verification showed the reliability and practicability of ANN model.

CONCLUSION

ANN model combined with MS data is of great significance for tdigital identification of AR, VR, and IR. It is an important reference for developing the digital identification of traditional Chinese medicines at the individual level based on UHPLC-QTOF-MS and multivariate algorithms.

Comprehensive immune cell spectral library for large-scale human primary T, B, and NK cell proteomics

Although proteomics is extensively used in immune research, there is currently no publicly accessible spectral assay library for the comprehensive proteome of immune cells. This study generated spectral assay libraries for five human immune cell lines and four primary immune cells: CD4 T, CD8 T, natural killer (NK) cells, and B cells. This was achieved by utilizing data-dependent acquisition (DDA) and employing fractionated samples from over 100 µg of proteins, which was applied to acquire the highest-quality MS/MS spectral data. In addition, Data-indedendent acquisition (DIA) was used to obtain sufficient data points for analyzing proteins from 10,000 primary CD4 T, CD8 T, NK, and B cells. The immune cell spectral assay library generated included 10,544 protein groups and 127,106 peptides. The proteomic profiles of 10,000 primary human immune cells obtained from 15 healthy volunteers analyzed using DIA revealed the highest heterogeneity of B cells among other immune cell types and the similarity between CD4 T and CD8 T cells. All data and spectral library are deposited in ProteomeXchange (PXD047742).

Development and Validation of UPLC-MS/MS Analysis for Sphingolipids Isolated from Velvet Antlers of Cervus elaphus

Deer velvet antlers, known as tonics, have created a large market as dietary supplements and have been consumed worldwide. Despite the high consumption of velvet antlers as dietary supplements, analytical methods for their identification and standardization remain limited. Quantitative analysis for gangliosides, considered quality indexes for velvet antlers, was developed to indirectly analyze the sialic acid obtained from chemical degradation. Owing to the complex and time-consuming chemical derivatization of gangliosides, a simple and rapid quality evaluation method for velvet antlers must be developed. For the first time, this study reports the isolation and structural elucidation of two new sphingomyelins (1 and 2), two known sphingomyelins (3 and 4), and four ceramides (5-8) as chemical markers from the velvet antlers of Cervus elaphus. To expedite and simplify the quality control of velvet antlers, advanced quantitative analysis of sphingolipids has been developed using ultra-performance liquid chromatography-mass spectroscopy.

Discovery of species-specific peptide markers and development of quality-evaluation strategies for deer horn gelatin using liquid chromatography-tandem mass spectrometry and a label-free methodology

Deer horn gelatin (DHG) is a valuable nutritional dietary supplement. Due to the significant variation in the price of DHG from different sources, it is important to assess its quality and to clarify the species of its raw material. However, due to the similarity in appearance and physicochemical properties, as well as the destruction of genetic material during the manufacturing process, it is difficult to distinguish DHG from gelatin derived from other sources. Furthermore, current methods are unable to evaluate the overall quality of DHG. Using Nano LC-Orbitrap MS and data analysis software, DHG samples from five deer species were analyzed to identify peptide markers specific to alpha-2-HS-glycoprotein (AHSG) and collagen. The peptide markers were validated using HPLC-Triple Quadrupole MS, and strategies for assessing the quality of DHG were developed. Eighteen peptide markers were discovered, comprising peptides with differing specificities. Three strategies for the identification, characteristic mapping, and content determination of DHG were developed. These strategies can be used to assess the quality of deer gelatin.

Application of digital-intelligence technology in the processing of Chinese materia medica

Processing of Chinese Materia Medica (PCMM) is the concentrated embodiment, which is the core of Chinese unique traditional pharmaceutical technology. The processing includes the preparation steps such as cleansing, cutting and stir-frying, to make certain impacts on the quality and efficacy of Chinese botanical drugs. The rapid development of new computer digital technologies, such as big data analysis, Internet of Things (IoT), blockchain and cloud computing artificial intelligence, has promoted the rapid development of traditional pharmaceutical manufacturing industry with digitalization and intellectualization. In this review, the application of digital intelligence technology in the PCMM was analyzed and discussed, which hopefully promoted the standardization of the process and secured the quality of botanical drugs decoction pieces. Through the intellectualization and the digitization of production, safety and effectiveness of clinical use of traditional Chinese medicine (TCM) decoction pieces were ensured. This review also provided a theoretical basis for further technical upgrading and high-quality development of TCM industry.

Application of digital-intelligence technology in the processing of Chinese materia medica

Processing of Chinese Materia Medica (PCMM) is the concentrated embodiment, which is the core of Chinese unique traditional pharmaceutical technology. The processing includes the preparation steps such as cleansing, cutting and stir-frying, to make certain impacts on the quality and efficacy of Chinese botanical drugs. The rapid development of new computer digital technologies, such as big data analysis, Internet of Things (IoT), blockchain and cloud computing artificial intelligence, has promoted the rapid development of traditional pharmaceutical manufacturing industry with digitalization and intellectualization. In this review, the application of digital intelligence technology in the PCMM was analyzed and discussed, which hopefully promoted the standardization of the process and secured the quality of botanical drugs decoction pieces. Through the intellectualization and the digitization of production, safety and effectiveness of clinical use of traditional Chinese medicine (TCM) decoction pieces were ensured. This review also provided a theoretical basis for further technical upgrading and high-quality development of TCM industry.

Identification and Quality Evaluation of Velvet Antler by DNA Barcoding and Stable Isotope Techniques Combined with Chemometrics

This study aimed to identify Velvet antler and its counterfeits and to further evaluate their quality. Mitochondrial cytochrome b (Cytb) was used as a target gene to identify Velvet antler samples, and a DNA barcoding method was established for species origin identification in Velvet antlers. After identification, the stable isotope contents and ratios were adopted to evaluate the quality of different specifications of authentic Velvet antler in combination with chemometrics. Two stable isotope contents (C % and N %) and ratios (δ¹³C and δ¹⁵N) in three kinds of Velvet antler slices of different specifications, namely, wax slices, powder slices, and bone slices, were determined. Nine Velvet antler samples sold in the market were identified for label conformity. Only two samples were consistent with the labeled species, and the others were counterfeits. The three slices of Velvet antler of different specifications were clearly distinguished by principal component analysis and hierarchical cluster analysis. Then, the discriminant model of partial least squares discriminant analysis was established, and 100% discrimination accuracy was observed in this model. All the Velvet antler slice samples of different specification samples were grouped clearly according to their sources. In summary, it is feasible for the identification and quality grade evaluation of Velvet antler by DNA barcoding based on mitochondrial Cytb and stable isotope techniques combined with chemometric analysis. The establishment of this method also provided a reference for the evaluation of other animal-derived medicinal materials.

Species-specific identification of donkey-hide gelatin and its adulterants using marker peptides

Donkey-hide gelatin is an important traditional Chinese medicine made from donkey skin. Despite decades of effort, identifying the animal materials (donkeys, horses, cattle and pigs) in donkey-hide gelatin remains challenging. In our study, we aimed to identify marker peptides of donkey-hide gelatin and its adulterants and develop a liquid chromatography–tandem mass spectrometry method to identify them. Theoretical marker peptides of four animals (donkeys, horses, cattle and pigs) were predicted and verified by proteomic experiments, and 12 species-specific marker peptides from donkey-hide gelatin and its adulterants were identified. One marker peptide for each gelatin was selected to develop the liquid chromatography–tandem mass spectrometry method. The applicability of the method was evaluated by investigating homemade mixed gelatin samples and commercial donkey-hide gelatin products. Using the liquid chromatography–tandem mass spectrometry method, the addition of cattle-hide gelatin and pig-hide gelatin to donkey-hide gelatin could be detected at a level of 0.1%. Horse-hide gelatin was detected when added at a level of 0.5%. Among 18 batches of donkey-hide gelatin products, nine were identified as authentic, and eight of the remaining samples were suspected to be adulterated with horse materials. These results provide both a practical method to control the quality of donkey-hide gelatin and a good reference for quality evaluations of other medicinal materials and foods containing protein components.

Peptide Biomarkers Discovery for Seven Species of Deer Antler Using LC-MS/MS and Label-Free Approach

Deer antler is a globally widely used precious natural medicine and the material of deer horn gelatin. However, identification of deer antler species based on traditional approaches are problematic because of their similarity in appearance and physical-chemical properties. In this study, we performed a comprehensive antler peptidome analysis using a label-free approach: nano LC-Orbitrap MS was applied to discover peptide biomarkers in deer adult beta-globin (HBB_A), and HPLC-Triple Quadrupole MS was used to verify their specificity. Nineteen peptide biomarkers were found, on which foundation a strategy for antlers and a strategy for antler mixtures such as flakes or powder are provided to identify seven species of deer antler including Eurasian elk (Alces alces), reindeer (Rangifer tarandus), white-tailed deer (Odocoileus viginianus), white-lipped deer (Przewalskium albirostris), fallow deer (Dama dama), sika deer (Cervus nippon), and red deer (Cervus elaphus) simultaneously. It is worth noting that our search found that the HBB_A gene of sika deer, red deer, and North American wapiti (Cervus canadensis) in China may have undergone severe genetic drifts.

The Application of UHPLC-HRMS for Quality Control of Traditional Chinese Medicine

UHPLC-HRMS (ultra-high-performance liquid chromatography-high resolution mass spectrometry) is a new technique that unifies the application of UHPLC with HRMS. Because of the high sensitivity and good separation ability of UHPLC and the sensitivity of HRMS, this technique has been widely used for structure identification, quantitative determination, fingerprint analysis, and elucidation of the mechanisms of action of traditional Chinese medicines (TCMs) in recent years. This review mainly outlines the advantages of using UHPLC-HRMS and provides a survey of the research advances on UHPLC-HRMS for the quality control of TCMs.

Development of 16 novel EST-SSR markers for species identification and cross-genus amplification in sambar, sika, and red deer

Deer genera around the globe are threatened by anthropogenic interference. The translocation of alien species and their subsequent genetic introgression into indigenous deer populations is particularly harmful to the species of greatest conservation concern. Products derived from deer, including venison and antler velvet, are also at risk of fraudulent labeling. The current molecular markers used to genetically identify deer species were developed from genome sequences and have limited applicability for cross-species amplification. The absence of efficacious diagnostic techniques for identifying deer species has hampered conservation and wildlife crime investigation efforts. Expressed sequence tag-simple sequence repeat (EST-SSR) markers are reliable tools for individual and species identification, especially in terms of cross-species genotyping. We conducted transcriptome sequencing of sambar (Rusa unicolor) antler velvet and acquired 11,190 EST-SSRs from 65,074 newly assembled unigenes. We identified a total of 55 unambiguous amplicons in sambar (n = 45), which were selected as markers to evaluate cross-species genotyping in sika deer (Cervus nippon, n = 30) and red deer (Cervus elaphus, n = 46), resulting in cross-species amplification rates of 94.5% and 89.1%, respectively. Based on polymorphic information content (>0.25) and genotyping fidelity, we selected 16 of these EST-SSRs for species identification. This marker set revealed significant genetic differentiation based on the fixation index and genetic distance values. Principal coordinate analysis and STRUCTURE analysis revealed distinct clusters of species and clearly identified red-sika hybrids. These markers showed applicability across different genera and proved suitable for identification and phylogenetic analyses across deer species.

Analysis of the characteristic compounds of Citri Sarcodactylis Fructus from different geographical origins

INTRODUCTION

Citri Sarcodactylis Fructus (CSF) is widely used as a food ingredient and a traditional Chinese medicine. In China, CSF is cultivated in many places, including Sichuan, Guangdong, Zhejiang, and Fujian provinces. The types and chemical contents of CSF from different origins may vary greatly due to the difference in climate and environmental conditions. Therefore, comparing the chemical composition of CSF from various places is vital.

OBJECTIVE

To rapidly select potential characteristic compounds for differentiating CSF from different origins.

MATERIAL AND METHODS

Thirty-one batches of CSF samples from different regions were analysed using ultra-performance liquid chromatography with hybrid quadrupole-orbitrap high-resolution mass spectrometry. Thereafter, chemometric methods, including principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA), were employed to find differential metabolites among the CSF samples from various origins.

RESULTS

PCA revealed 77.9% of the total variance and divided all CSF samples into three categories corresponding to their origins. OPLS-DA displayed better discrimination of CSF from different sources, with R² X, R² Y, and Q² of 0.801, 0.985, and 0.849, respectively. Finally, 203 differential metabolites were obtained from CSF from different origins using the variable importance in projection of the OPLS-DA model, 30 of which were identified, and five coumarin compounds were selected as marker compounds discriminating CSF from different origins.

CONCLUSION

This work provides a practical strategy for classifying CSF from different origins and offers a research foundation for the quality control of CSF.

Bioactive Molecular Discovery Using Deer Antlers as a Model of Mammalian Regeneration

The ability to activate and regulate stem cells during wound healing and tissue regeneration is a promising field that is resulting in innovative approaches in the field of regenerative medicine. The regenerative capacity of invertebrates has been well documented; however, in mammals, stem cells that drive organ regeneration are rare. Deer antlers are the only known mammalian structure that can annually regenerate to produce a tissue containing dermis, blood vessels, nerves, cartilage, and bone. The neural crest derived stem cells that drive this process result in antlers growing at up to 2 cm/day. Deer antlers thus provide superior attributes compared to lower-order animal models, when investigating the regulation of stem cell-based regeneration. Antler stem cells can therefore be used as a model to investigate the bioactive molecules, biological processes, and pathways involved in the maintenance of a stem cell niche, and their activation and differentiation during organ formation. This review examines stem cell-based regeneration with a focus on deer antlers, a neural crest stem cell-based mammalian regenerative structure. It then discusses the omics technical platforms highlighting the proteomics approaches used for investigating the molecular mechanisms underlying stem cell regulation in antler tissues.

Quantitative Detection of Donkey Hide Gelatin (Colla corii asini) Adulteration by Real-Time PCR on the Basis of Single-Copy Nuclear Genes

ABSTRACT

Donkey hide gelatin (Colla corii asini) is well-known for its high nutritional value, especially for medicinal purposes. However, it is also a potential candidate for adulteration because of its low yield and high price. To quantitatively detect adulterated donkey hide gelatin with all possible mixed animal species, a real-time PCR approach on the basis of single-copy housekeeping nuclear reference primers was proposed in this study. For the system establishment, mixtures containing designated contents of pig hide with donkey hide were used to generate a calibration curve on the basis of the ratio of cycle threshold, CT (specificity/reference) with reasonable linearity (5 to 100%). Then, a set of experiments were performed on commercially available samples. The proposed PCR approach could specifically identify donkey hide from mixed animal products and quantify the content of donkey hide gelatin, thus facilitating control over this novel form of donkey hide gelatin adulteration.

HIGHLIGHTS

Development of novel EST microsatellite markers for genetic diversity analysis and correlation analysis of velvet antler growth characteristics in Sika deer

BACKGROUND

Sika deer is one of the most popular and valued animals in China. However, few studies have been conducted on the microsatellite of Sika deer, which has hampered the progress of genetic selection breeding. To develop and characterize a set of microsatellites for Sika deer which provide helpful information for protection of Sika deer natural resources and effectively increase the yield and quantity of velvet antler.

RESULTS

We conducted a transcriptome survey of Sika deer using next-generation sequencing technology. One hundred eighty-two thousand two hundred ninety-five microsatellite markers were identified in the transcriptome, 170 of 200 loci were successfully amplified across panels of 140 individuals from Shuangyang Sika deer population. And 29 loci were found to be obvious polymorphic. Number of alleles is from 3 to 14. The expected heterozygosity ranged from 0.3087 to 0.7644. The observed heterozygosity ranged from 0 to 0.7698. The polymorphism information content values of those microsatellites varied ranged from 0.2602 to 0.7507. The marker-trait association was tested for 6 important and kernel characteristics of two-branched velvet antler in Shuangyang Sika deer through one-way analysis of variance. The results showed that marker-trait associations were identified with 8 different markers, especially M009 and M027.

CONCLUSIONS

This study not only provided a large scale of microsatellites which were valuable for future genetic mapping and trait association in Sika deer, but also offers available information for molecular breeding in Sika deer.

Identification of Calculus Bovis and its mixed varieties by ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-Q/TOF-MS) combined with the principal component analysis (PCA) method

The method of ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC-Q/TOF-MS) was established and combined with principal component analysis (PCA) to identify natural Calculus Bovis, in vitro cultured Calculus Bovis and artificial Calculus Bovis. PCA, which was particularly powerful in dealing with multicollinearity and variables that outnumber the samples, was used to analyze the UHPLC-MS data of the processed samples, and potential markers were analyzed and described based on orthogonal partial least-squares discriminant analysis. According to the results in this study, the approach of combining UHPLC-QTOF-MS with PCA was proven to be credible and could be used to identify Calculus Bovis from in vitro cultured Calculus Bovis and artificial Calculus Bovis and to determine if there is Calculus Bovis in patented Chinese medicines that should contained Calculus Bovis medicinal materials.

Establishment and comparative analysis of HPLC fingerprints of deer tissues

Context With the increasing use of velvet antlers (VA) as functional food or traditional Chinese medicine, the quality control has become more and more important. Aims Establish an effective method to provide a way of distinguishing VA from other types of deer tissue. Methods In the present study, 18 samples from three types of deer tissue were analysed on the basis of high-performance liquid chromatography, and a chromatogram of each sample was obtained. Then, these chromatograms were processed using the similarity evaluation system for chromatographic fingerprints of traditional Chinese medicine, to give the fingerprints of three deer tissues. The chemometric methods were used to analyse the fingerprint results, so as to identify the three types of deer tissue. Key results Shared peaks of VA, venison and deer bone were identified using similarity evaluation system. The results showed that, in total, 19 peaks were identified among these three types of deer tissue. Compared with venison, VA lacked three peaks (Numbers 3, 4 and 17); compared with deer bone, VA had six extra peaks (Numbers 2, 5, 8, 9, 14 and 19). The results of chemometric methods showed that different tissue samples could be classified into three categories by using both cluster analysis and principal component analysis. After principal component analysis and partial least-square discrimination analysis, seven peaks were selected, which had significant influence on the classification of VA, venison and deer bone. Conclusions The high-performance liquid-chromatography fingerprints in combination with chemometric methods can be used to effectively distinguish three deer tissue types, namely, VA, venison and deer bone. Implications We believe the method offers a useful tool much needed in the current Chinese velvet market.