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Wang L, He H, Wang J, Meng Z, Wang L, Jin X, Zhang J, Du P, Zhang L, Wang F, Li H, Xie Q. Genome-Wide Identification of the Geranylgeranyl Pyrophosphate Synthase (GGPS) Gene Family Associated with Natural Rubber Synthesis in Taraxacum kok-saghyz L. Rodin. PLANTS (BASEL, SWITZERLAND) 2024; 13:2788. [PMID: 39409658 PMCID: PMC11478434 DOI: 10.3390/plants13192788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Revised: 10/02/2024] [Accepted: 10/02/2024] [Indexed: 10/20/2024]
Abstract
Taraxacum kok-saghyz Rodin (TKS) is a recognized alternative source of natural rubber comparable to the rubber tree. The geranylgeranyl pyrophosphate synthase (GGPS) catalyzed the synthesis of geranylgeranyl pyrophosphate (GGPP), which is an important enzyme in the secondary metabolism pathway. In this study, we present the first analysis of the GGPS gene family in TKS, where a total of seven TkGGPS family members were identified. Their core motifs, conserved structural domains, gene structures, and cis-acting elements were described. In addition, two phylogenetic trees were constructed based on the Neighbor-Joining and Maximum-Likelihood methods, and the TkGGPSs were highly conserved and exhibited good collinearity with the other species. Transcriptome data showed that seven TkGGPS gene members were expressed in all the 12 tissues measured, and TkGGPS1, TkGGPS3, and TkGGPS6 were highly expressed in latex, suggesting that they may be associated with natural rubber synthesis. Meanwhile, quantitative real-time PCR (qRT-PCR) showed that the expression levels of the TkGGPS genes were regulated by the ethylene and methyl jasmonate (MeJA) pathways. Subcellular localization results indicated that all the TkGGPS proteins were also located in chloroplasts involved in photosynthesis in plants. This study will provide valuable insights into the selection of candidate genes for molecular breeding and natural rubber biosynthesis in TKS.
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Affiliation(s)
- Lili Wang
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, Xinjiang Production and Construction Corps Key Laboratory of Oasis Town and Mountain-basin System Ecology, College of Life Sciences, Shihezi University, Shihezi 832003, China; (L.W.); (H.H.); (J.W.); (Z.M.); (L.W.); (J.Z.); (P.D.); (L.Z.)
| | - Huan He
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, Xinjiang Production and Construction Corps Key Laboratory of Oasis Town and Mountain-basin System Ecology, College of Life Sciences, Shihezi University, Shihezi 832003, China; (L.W.); (H.H.); (J.W.); (Z.M.); (L.W.); (J.Z.); (P.D.); (L.Z.)
| | - Jiayin Wang
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, Xinjiang Production and Construction Corps Key Laboratory of Oasis Town and Mountain-basin System Ecology, College of Life Sciences, Shihezi University, Shihezi 832003, China; (L.W.); (H.H.); (J.W.); (Z.M.); (L.W.); (J.Z.); (P.D.); (L.Z.)
| | - Zhuang Meng
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, Xinjiang Production and Construction Corps Key Laboratory of Oasis Town and Mountain-basin System Ecology, College of Life Sciences, Shihezi University, Shihezi 832003, China; (L.W.); (H.H.); (J.W.); (Z.M.); (L.W.); (J.Z.); (P.D.); (L.Z.)
| | - Lei Wang
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, Xinjiang Production and Construction Corps Key Laboratory of Oasis Town and Mountain-basin System Ecology, College of Life Sciences, Shihezi University, Shihezi 832003, China; (L.W.); (H.H.); (J.W.); (Z.M.); (L.W.); (J.Z.); (P.D.); (L.Z.)
| | - Xiang Jin
- Ministry of Education Key Laboratory for Ecology of Tropical Islands, Key Laboratory of Tropical Animal and Plant Ecology of Hainan Province, College of Life Sciences, Hainan Normal University, Haikou 571158, China;
| | - Jianhang Zhang
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, Xinjiang Production and Construction Corps Key Laboratory of Oasis Town and Mountain-basin System Ecology, College of Life Sciences, Shihezi University, Shihezi 832003, China; (L.W.); (H.H.); (J.W.); (Z.M.); (L.W.); (J.Z.); (P.D.); (L.Z.)
| | - Pingping Du
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, Xinjiang Production and Construction Corps Key Laboratory of Oasis Town and Mountain-basin System Ecology, College of Life Sciences, Shihezi University, Shihezi 832003, China; (L.W.); (H.H.); (J.W.); (Z.M.); (L.W.); (J.Z.); (P.D.); (L.Z.)
| | - Liyu Zhang
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, Xinjiang Production and Construction Corps Key Laboratory of Oasis Town and Mountain-basin System Ecology, College of Life Sciences, Shihezi University, Shihezi 832003, China; (L.W.); (H.H.); (J.W.); (Z.M.); (L.W.); (J.Z.); (P.D.); (L.Z.)
| | - Fei Wang
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, Xinjiang Production and Construction Corps Key Laboratory of Oasis Town and Mountain-basin System Ecology, College of Life Sciences, Shihezi University, Shihezi 832003, China; (L.W.); (H.H.); (J.W.); (Z.M.); (L.W.); (J.Z.); (P.D.); (L.Z.)
| | - Hongbin Li
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, Xinjiang Production and Construction Corps Key Laboratory of Oasis Town and Mountain-basin System Ecology, College of Life Sciences, Shihezi University, Shihezi 832003, China; (L.W.); (H.H.); (J.W.); (Z.M.); (L.W.); (J.Z.); (P.D.); (L.Z.)
| | - Quanliang Xie
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, Xinjiang Production and Construction Corps Key Laboratory of Oasis Town and Mountain-basin System Ecology, College of Life Sciences, Shihezi University, Shihezi 832003, China; (L.W.); (H.H.); (J.W.); (Z.M.); (L.W.); (J.Z.); (P.D.); (L.Z.)
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Bai Y, Zhang H. The cluster analysis of traditional Chinese medicine authenticity identification technique assisted by chemometrics. Heliyon 2024; 10:e37479. [PMID: 39309934 PMCID: PMC11416282 DOI: 10.1016/j.heliyon.2024.e37479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 09/02/2024] [Accepted: 09/04/2024] [Indexed: 09/25/2024] Open
Abstract
This study explore the authenticity identification technique of traditional Chinese medicine (TCM) using chemometrics in conjunction with cluster analysis. A clustering Gaussian mixture model was constructed and applied for the data clustering analysis of four types of TCM. Chemical measurements combined with discrete wavelet transform (DWT), Fourier transform infrared spectroscopy (FTIR), and Fourier self-deconvolution (FSD) were utilized for the detailed differentiation of Bupleurum scorzonerifolium, Bupleurum yinchowense, Bupleurum marginatum, and Bupleurum smithii Wolff var. parvifolium. Differences in the attenuated total reflection-FTIR (ATR-FTIR) spectra among the four TCMs were observed. Utilizing clustering algorithms, the one-dimensional DWT of the infrared spectra of samples was employed for the authentication of Chinese herbal medicines. The model demonstrates optimal performance throughout 2000 rounds of network training. The accuracy (88.6 %), sensitivity (86.5 %), and specificity (82.7 %) of the model constructed in this study significantly surpassed those of the CNN model: accuracy (67.7 %), sensitivity (70.4 %), and specificity (68.5 %) (P < 0.05). By setting the cluster size K = 5 and the number of Gaussian mixture model components to 5, the model effectively fits the actual number of categories within the dataset. Infrared spectroscopy analysis revealed distinct carbon-oxygen stretching vibration absorption peaks between 1025 and 1200 cm-1 for Bupleurum scorzonerifolium, Bupleurum yinchowense, Bupleurum marginatum, and Bupleurum smithii Wolff var. parvifolium, indicating strong absorption peaks of carbohydrates. A comprehensive structural information analysis revealed a similarity of above 0.982 among the four types of TCM. Combined with chemometrics and intelligent algorithm-based cluster analysis, successful and accurate authentication of TCM authenticity was achieved, providing an effective methodology for quality control in TCM.
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Affiliation(s)
- Yunxia Bai
- College of Computer Science and Technology, Baotou Medical College, Baotou, 014040, China
| | - Huiwen Zhang
- College of Pharmacy, Inner Mongolia Medical University, Hohhot, 010110, China
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Rezayatmand H, Golestani N, Haghighat Hoseini AS, Mousavialmaleki E, Alem M, Farzane Yegane D. Gene expression profile of Campylobacter jejuni in response to macrolide antibiotics. Arch Microbiol 2024; 206:117. [PMID: 38393387 DOI: 10.1007/s00203-024-03849-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 01/06/2024] [Accepted: 01/16/2024] [Indexed: 02/25/2024]
Abstract
Campylobacter jejuni is a foodborne pathogen that causes gastroenteritis in humans and has developed resistance to various antibiotics. The primary objective of this research was to examine the network of antibiotic resistance in C. jejuni. The study involved the wild and antibiotic-resistant strains placed in the presence and absence of antibiotics to review their gene expression profiles in response to ciprofloxacin via microarray. Differentially expressed genes (DEGs) analysis and Protein-Protein Interaction (PPI) Network studies were performed for these genes. The results showed that the resistance network of C. jejuni is modular, with different genes involved in bacterial motility, capsule synthesis, efflux, and amino acid and sugar synthesis. Antibiotic treatment resulted in the down-regulation of cluster genes related to translation, flagellum formation, and chemotaxis. In contrast, cluster genes involved in homeostasis, capsule formation, and cation efflux were up-regulated. The study also found that macrolide antibiotics inhibit the progression of C. jejuni infection by inactivating topoisomerase enzymes and increasing the activity of epimerase enzymes, trying to compensate for the effect of DNA twisting. Then, the bacterium limits the movement to conserve energy. Identifying the antibiotic resistance network in C. jejuni can aid in developing drugs to combat these bacteria. Genes involved in cell division, capsule formation, and substance transport may be potential targets for inhibitory drugs. Future research must be directed toward comprehending the underlying mechanisms contributing to the modularity of antibiotic resistance and developing strategies to disrupt and mitigate the growing threat of antibiotic resistance effectively.
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Affiliation(s)
- Hamed Rezayatmand
- Department of Pharmacy and Technology of Organic Substances, Industrial Pharmacy, Ukrainian State Chemical Technology University, Dnipro, Ukraine
| | - Nafiseh Golestani
- Department of Biochemistry, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
| | | | - Elaheh Mousavialmaleki
- Pharmaceutical Science Research Center, Medicinal Chemistry Department, Faculty of Pharmacy, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
| | - Mahsa Alem
- Department of Microbiology, Faculty of Veterinary Medicine, Urmia University, Urmia, Iran.
| | - Donya Farzane Yegane
- Department of Pharmacognosy and Pharmaceutical Biotechnology, Faculty of Pharmacy, Lorestan University of Medical Sciences, Khorramabad, Iran
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Wang S, Deng P, Sun X, Han J, Yang S, Chen Z. Global research trends and hotspots analysis of hallux valgus: A bibliometric analysis from 2004 to 2021. Front Surg 2023; 10:1093000. [PMID: 36998596 PMCID: PMC10044137 DOI: 10.3389/fsurg.2023.1093000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 02/13/2023] [Indexed: 03/09/2023] Open
Abstract
BackgroundHallux valgus (HV) is a common foot and ankle surgery disease. The correction of HV deformity relies on a highly challenging surgical treatment. Thus, widely adopted evidence-based clinical guidelines are still needed to guide the selection of the most appropriate interventions. Recently, the study of HV has been growing and scholars are increasingly paying particular attention to this area. However, bibliometric literature remains lacking. Therefore, this study aims to reveal the hotspots and future research trends in HV via bibliometric analysis to fill this knowledge gap.MethodsLiterature related to HV from 2004 to 2021 was retrieved from the Science Citation Index Expanded (SCI-expanded) of the Web of Science Core Collection (WoSCC). Quantitative and qualitative analyses of scientific data are performed using software such as CiteSpace, R-bibliometrix, and VOSviewer.ResultsA total of 1,904 records were identified for analysis. The United States had the most number of published articles and total citations. Thus, the United States has made an essential contribution to the field of HV. Meanwhile, La Trobe University in Australia was the most productive institution. Menz HB and Foot & Ankle International were the most influential authors and the most popular journals among researchers, respectively. In addition, “older people,” “chevron osteotomy,” “Lapidus,” and “hallux rigidus” have always been the hotspots of attention. Changes and developments in the surgery of HV have gained researchers' interest. Future research trends are more focused on “radiographic measurement,” “recurrence,” “outcome,” “rotation,” “pronation,” and “minimally invasive surgery.” Thus, focusing on these subject directions can facilitate academic progress and provide the possibility of better treatments for HV.ConclusionThis study summarizes the hotspots and trends in the field of HV from 2004 to 2021, which will provide researchers with an updated view of essential information and somehow guide future research.
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Affiliation(s)
- Shulong Wang
- School of Graduates, Beijing University of Chinese Medicine, Beijing, China
- Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
| | - Ping Deng
- School of Graduates, Beijing University of Chinese Medicine, Beijing, China
- Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
| | - Xiaojie Sun
- School of Graduates, Beijing University of Chinese Medicine, Beijing, China
- Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
| | - Jinglu Han
- School of Graduates, Beijing University of Chinese Medicine, Beijing, China
- Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
| | - Shanshan Yang
- School of Graduates, Beijing University of Chinese Medicine, Beijing, China
| | - Zhaojun Chen
- Department of Hand and Foot Surgery, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, China
- Correspondence: Zhaojun Chen
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Wang X, Zhang X, Li J, Hu B, Zhang J, Zhang W, Weng W, Li Q. Analysis of prescription medication rules of traditional Chinese medicine for bradyarrhythmia treatment based on data mining. Medicine (Baltimore) 2022; 101:e31436. [PMID: 36343087 PMCID: PMC9646641 DOI: 10.1097/md.0000000000031436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 09/30/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Multiple studies have revealed that Traditional Chinese Medicine (TCM) prescriptions can provide protective effect on the cardiovascular system, increase the heart rate and relieve the symptoms of patients with bradyarrhythmia. In China, the TCM treatment of bradyarrhythmia is very common, which is also an effective complementary therapy. In order to further understand the application of Chinese medicines in bradyarrhythmia, we analyzed the medication rules of TCM prescriptions for bradyarrhythmia by data mining methods based on previous clinical studies. METHODS We searched studies reporting the clinical effect of TCM on bradyarrhythmia in the PubMed and Chinese databases China National Knowledge Infrastructure database, and estimated publication bias by risk of bias tools ROB 2. Descriptive analysis, hierarchical clustering analysis and association rule analysis based on Apriori algorithm were carried out by Microsoft Excel, SPSS Modeler, SPSS Statistics and Rstidio, respectively. Association rules, co-occurrence and clustering among Chinese medicines were found. RESULTS A total of 48 studies were included in our study. Among the total 99 kinds of Chinese medicines, 22 high-frequency herbs were included. Four new prescriptions were obtained by hierarchical cluster analysis. 81 association rules were found based on association rule analysis, and a core prescription was intuitively based on the grouping matrix of the top 15 association rules (based on confidence level), of which Guizhi, Zhigancao, Wuweizi, Chuanxiong, Danshen, Danggui, Huangqi, Maidong, Dangshen, Rougui were the most strongly correlated herbs and in the core position. CONCLUSION In this study, data mining strategy was applied to explore the TCM prescription for the treatment of bradyarrhythmia, and high-frequency herbs and core prescription were found. The core prescription was in line with the treatment ideas of TCM for bradyarrhythmia, which could intervene the disease from different aspects and adjust the patient's Qi, blood, Yin and Yang, so as to achieve the purpose of treatment.
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Affiliation(s)
- Xujie Wang
- Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
- NMPA Key Laboratory for Clinical Research and Evaluation of Traditional Chinese Medicine, Beijing, China
- National Clinical Research Center for Chinese Medicine Cardiology, Beijing, China
| | - Xuexue Zhang
- Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Jiaxi Li
- Shanxi University of Chinese Medicine, Taiyuan, China
| | | | - Jiwei Zhang
- Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Wantong Zhang
- Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
- NMPA Key Laboratory for Clinical Research and Evaluation of Traditional Chinese Medicine, Beijing, China
- National Clinical Research Center for Chinese Medicine Cardiology, Beijing, China
| | - Weiliang Weng
- Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
- NMPA Key Laboratory for Clinical Research and Evaluation of Traditional Chinese Medicine, Beijing, China
- National Clinical Research Center for Chinese Medicine Cardiology, Beijing, China
| | - Qiuyan Li
- Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
- National Clinical Research Center for Chinese Medicine Cardiology, Beijing, China
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Poulain P, Camadro JM. AutoClassWeb: a simple web interface for Bayesian clustering of omics data. BMC Res Notes 2022; 15:241. [PMID: 35799281 PMCID: PMC9264669 DOI: 10.1186/s13104-022-06129-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 06/21/2022] [Indexed: 11/10/2022] Open
Abstract
Objective Data clustering is a common exploration step in the omics era, notably in genomics and proteomics where many genes or proteins can be quantified from one or more experiments. Bayesian clustering is a powerful unsupervised algorithm that can classify several thousands of genes or proteins. AutoClass C, its original implementation, handles missing data, automatically determines the best number of clusters but is not user-friendly. Results We developed an online tool called AutoClassWeb, which provides an easy-to-use and simple web interface for Bayesian clustering with AutoClass. Input data are entered as TSV files and quality controlled. Results are provided in formats that ease further analyses with spreadsheet programs or with programming languages, such as Python or R. AutoClassWeb is implemented in Python and is published under the 3-Clauses BSD license. The source code is available at https://github.com/pierrepo/autoclassweb along with a detailed documentation.
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Affiliation(s)
- Pierre Poulain
- Université Paris Cité, CNRS, Institut Jacques Monod, Paris, F-75013, France.
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