Guanru Zhou’s research while affiliated with Hubei University of Chinese Medicine and other places

Mentha is a commonly used spice worldwide, which possesses medicinal properties and fragrance. These characteristics are conferred, at least partially, by essential oils such as menthol. In this study, a gap-free assembly with a genome size of 414.3 Mb and 31,251 coding genes was obtained for Mentha suaveolens ‘Variegata’. Based on its high heterozygosity (1.5%), two complete haplotypic assemblies were resolved, with genome sizes of 401.9 Mb and 405.7 Mb, respectively. The telomeres and centromeres of each haplotype were almost fully annotated. In addition, we detected a total of 41,135 structural variations. Enrichment analysis demonstrated that genes involved in terpenoid biosynthesis were affected by these structural variations. Analysis of volatile metabolites showed that Mentha suaveolens mainly produces piperitenone oxide rather than menthol. We identified three genes in the Mentha suaveolens genome which encode isopiperitenone reductase (ISPR), a key rate-limiting enzyme in menthol biosynthesis. However, the transcription levels of ISPR were low. Given that other terpenoid biosynthesis genes were expressed, Mentha suaveolens ISPRs may account for the accumulation of piperitenone oxide in this species. The findings of this study may provide a valuable resource for improving the detection rate and accuracy of genetic variants, thereby enhancing our understanding of their impact on gene function and expression. Moreover, our haplotype-resolved gap-free genome assembly offers novel insights into molecular marker-assisted breeding of Mentha.

Animal bile is an important component of natural medicine and is widely used in clinical treatment. However, it is easy to cause mixed applications during processing, resulting in uneven quality, which seriously affects and harms the interests and health of consumers. Bile acids are the major bioactive constituents of bile and contain a variety of isomeric constituents. Although the components are structurally similar, they exhibit different pharmacological activities. Identifying the characteristics of each animal bile is particularly important for processing and reuse. It is necessary to establish an accurate analysis method to distinguish different types of animal bile. We evaluated the biological activity of key feature markers from various animal bile samples. In this study, a strategy combining metabolomics and machine learning was used to compare the bile of three different animals, and four key markers were screened. Quantitative analysis of the key markers showed that the levels of Glycochenodeoxycholic acid (GCDCA) and Taurodeoxycholic acid (TDCA) were highest in pig bile; Glycocholic acid (GCA) and Cholic acid (CA) were the most abundant in bovine and sheep bile, respectively. In addition, four key feature markers significantly inhibited the production of NO in LPS-stimulated RAW264.7 macrophage cells. These findings will contribute to the targeted development of bile in various animals and provide a basis for its rational application.

In the clinical application of Traditional Chinese Medicine (TCM) substitutes, the consistency evaluation of TCM substitutes from different sources is recognized as the main bottleneck. As the most widely used analytical method in TCM consistency evaluation, fingerprint similarity evaluation suffers from insufficient method sensitivity and poor conformity with the actual characteristics of TCM, which is difficult to adapt to the analytical needs of complex substance systems of TCM. This work aims to develop an effective and more accurate method for consistency evaluation using omics strategy and machine learning algorithms. The natural calculus bovis (NCB) were graded into three groups according to the similarity to in vitro cultured bovis (IVCB), and chemical markers between samples of each grade were screened out. Support vector machine (SVM) models with different kernels were then constructed by using the chemical markers as feature variables. The results showed that the classification accuracy of the SVM classifier of NCB and the consistency evaluation SVM model classifier were 95.47% and 100% respectively. The approach demonstrated in the study presented a good analytical performance with higher sensitivity, accuracy for consistency evaluation of TCM.

Genomic data have demonstrated considerable traction in accelerating contemporary studies in traditional medicine. However, the lack of a uniform format and dispersed storage limits the full potential of herb genomic data. In this study, we developed a Global Pharmacopoeia Genome Database (GPGD). The database contains 34,346 records for 903 herb species from eight global pharmacopoeias (Brazilian, Egyptian, European, Indian, Japanese, Korean, the Pharmacopoeia of the People’s Republic of China, and U.S. Pharmacopoeia’s Herbal Medicines Compendium). In particular, the GPGD contains 21,872 DNA barcodes from 867 species, 2,203 organelle genomes from 674 species, 55 whole genomes from 49 species, 534 genomic sequencing datasets from 366 species, and 9,682 transcriptome datasets from 350 species. Among the organelle genomes, 534 genomes from 366 species were newly generated in this study. Whole genomes, organelle genomes, genomic fragments, transcriptomes, and DNA barcodes were uniformly formatted and arranged by species. The GPGD is publicly accessible at http://www.gpgenome.com and serves as an essential resource for species identification, decomposition of biosynthetic pathways, and molecular-assisted breeding analysis. Thus, the database is an invaluable resource for future studies on herbal medicine safety, drug discovery, and the protection and rational use of herbal resources.

Background Brazil is exceptionally abundant in traditional medicinal plant resources and has a rich ethnopharmacological history. Brazilian Pharmacopoeia (BP) acts as a national standard regulating drugs’ quality and has six published editions. Recent genomic approaches have led to a resurgence of interest in herbal drugs. Plants’ genomic data have been used for pharmaceutical applications, protecting natural resources, and efficiently regulating the market. However, there are few genomic databases specifically on medicinal plants, and establishing one focusing on the herbs of BP is urgently needed. Methods The BP editions’ medicinal plant species were analyzed to understand the evolution of the herbal drugs in Brazil. A new database, BPGD (Brazilian Pharmacopoeia Genomic Database), was constructed based on a typical web server architecture. A BLAST server for species identification and sequence searching with internal transcribed spacer 2 (ITS2), intergenic region ( psb A- trn H), and chloroplast genome (cp-G) of Brazilian traditional medicinal plants was also embedded in BPGD. Data of 82 plants in BP were collected and categorized into four parts: DNA barcodes, super-barcodes, genomes, and sequencing data. Further, the cp-Gs of Aloe genus in the database were analyzed as an illustration.ResultsBPGD (V1.0) has been tested and opened for public users. The database provides a comprehensive set of data, including the description and identification criteria of medicinal plants, and allows sequence-based search using BLAST. The database has 753 ITS2 of 76 species, 553 psb A -trn H and 190 genomes (whole genome and chloroplast genome) of 57 species, and 37 genome sequence data sets of 24 species and 616 transcriptome sequence data sets of 34 species. The data includes 187 cp-Gs representing 57 medicinal species in BP. Analysis of the six cp-Gs of three Aloe species identified the variable regions in cp-Gs, which could be used to identify species and understand the intraspecific relationship. Conclusions This study presents the first genomic database for traditional medicinal plants listed in the latest BP. It serves as an efficient platform to obtain genomic data, specifically on medical plants listed in the BP (http://bpgenome.com/).