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Chandhiruthil Sathyan A, Yadav P, Gupta P, Mahapathra AK, Galib R. In Silico Approaches to Polyherbal Synergy: Protocol for a Scoping Review. JMIR Res Protoc 2024; 13:e56646. [PMID: 38857494 PMCID: PMC11196908 DOI: 10.2196/56646] [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: 01/22/2024] [Revised: 03/22/2024] [Accepted: 04/10/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND According to the World Health Organization, more than 80% of the world's population relies on traditional medicine. Traditional medicine is typically based on the use of single herbal drugs or polyherbal formulations (PHFs) to manage diseases. However, the probable mode of action of these formulations is not well studied or documented. Over the past few decades, computational methods have been used to study the molecular mechanism of phytochemicals in single herbal drugs. However, the in silico methods applied to study PHFs remain unclear. OBJECTIVE The aim of this protocol is to develop a search strategy for a scoping review to map the in silico approaches applied in understanding the activity of PHFs used as traditional medicines worldwide. METHODS The scoping review will be conducted based on the methodology developed by Arksey and O'Malley and the recommendations of the Joanna Briggs Institute (JBI). A set of predetermined keywords will be used to identify the relevant studies from five databases: PubMed, Embase, Science Direct, Web of Science, and Google Scholar. Two independent reviewers will conduct the search to yield a list of relevant studies based on the inclusion and exclusion criteria. Mendeley version 1.19.8 will be used to remove duplicate citations, and title and abstract screening will be performed with Rayyan software. The JBI System for the Unified Management, Assessment, and Review of Information tool will be used for data extraction. The scoping review will be reported based on the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. RESULTS Based on the core areas of the scoping review, a 3-step search strategy was developed. The initial search produced 3865 studies. After applying filters, 875 studies were short-listed for further review. Keywords were further refined to yield more relevant studies on the topic. CONCLUSIONS The findings are expected to determine the extent of the knowledge gap in the applications of computational methods in PHFs for any traditional medicine across the world. The study can provide answers to open research questions related to the phytochemical identification of PHFs, criteria for target identification, strategies applied for in silico studies, software used, and challenges in adopting in silico methods for understanding the mechanisms of action of PHFs. This study can thus provide a better understanding of the application and types of in silico methods for investigating PHFs. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) PRR1-10.2196/56646.
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Affiliation(s)
| | - Pramod Yadav
- Department of Rasa Shastra and Bhaishajya Kalpana, All India Institute of Ayurveda, Delhi, India
| | - Prashant Gupta
- Ayurinformatics Laboratory, Department of Kaumarbhritya, All India Institute of Ayurveda, Delhi, India
| | - Arun Kumar Mahapathra
- Ayurinformatics Laboratory, Department of Kaumarbhritya, All India Institute of Ayurveda, Delhi, India
| | - Ruknuddin Galib
- Department of Rasa Shastra and Bhaishajya Kalpana, All India Institute of Ayurveda, Delhi, India
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Wanichthanarak K, In-on A, Fan S, Fiehn O, Wangwiwatsin A, Khoomrung S. Data processing solutions to render metabolomics more quantitative: case studies in food and clinical metabolomics using Metabox 2.0. Gigascience 2024; 13:giae005. [PMID: 38488666 PMCID: PMC10941642 DOI: 10.1093/gigascience/giae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 12/22/2023] [Accepted: 02/02/2024] [Indexed: 03/18/2024] Open
Abstract
In classic semiquantitative metabolomics, metabolite intensities are affected by biological factors and other unwanted variations. A systematic evaluation of the data processing methods is crucial to identify adequate processing procedures for a given experimental setup. Current comparative studies are mostly focused on peak area data but not on absolute concentrations. In this study, we evaluated data processing methods to produce outputs that were most similar to the corresponding absolute quantified data. We examined the data distribution characteristics, fold difference patterns between 2 metabolites, and sample variance. We used 2 metabolomic datasets from a retail milk study and a lupus nephritis cohort as test cases. When studying the impact of data normalization, transformation, scaling, and combinations of these methods, we found that the cross-contribution compensating multiple standard normalization (ccmn) method, followed by square root data transformation, was most appropriate for a well-controlled study such as the milk study dataset. Regarding the lupus nephritis cohort study, only ccmn normalization could slightly improve the data quality of the noisy cohort. Since the assessment accounted for the resemblance between processed data and the corresponding absolute quantified data, our results denote a helpful guideline for processing metabolomic datasets within a similar context (food and clinical metabolomics). Finally, we introduce Metabox 2.0, which enables thorough analysis of metabolomic data, including data processing, biomarker analysis, integrative analysis, and data interpretation. It was successfully used to process and analyze the data in this study. An online web version is available at http://metsysbio.com/metabox.
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Affiliation(s)
- Kwanjeera Wanichthanarak
- Siriraj Center of Research Excellence in Metabolomics and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Ammarin In-on
- Siriraj Center of Research Excellence in Metabolomics and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Sili Fan
- Department of Biostatistics, University of California Davis, Davis, CA 95616, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis Genome Center, Davis, CA 95616, USA
| | - Arporn Wangwiwatsin
- Department of Systems Biosciences and Computational Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Sakda Khoomrung
- Siriraj Center of Research Excellence in Metabolomics and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Center of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok 10700, Thailand
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Vannabhum M, Mahajaroensiri S, Pattanapholkornsakul S, Tantiwongsekunakorn A, Thippayacharoentam T, Tripatara P, Akarasereenont P. Metabolomics of Personalized Body Elements in Thai Traditional Medicine Response to Herbal Medicine for Body Elements Balancing in Healthy Volunteers. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE : ECAM 2023; 2023:6684263. [PMID: 37954926 PMCID: PMC10640159 DOI: 10.1155/2023/6684263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 09/05/2023] [Accepted: 10/25/2023] [Indexed: 11/14/2023]
Abstract
Background In Thai traditional medicine (TTM), the dominant body element called "Dhat Chao Ruean" (DCR) is an integral part in the diagnostic process of Thai traditional medicine. TTM practitioners usually use Thai herbal Benjakul formula (BKF) for adjusting and balancing the body elements. However, the effects of BKF on metabolism and individual response to it have not been studied yet. Methods This study proposed to investigate the metabolic profiling in 24 volunteers categorized by their types of birth month DCR (bDCR) after the administration of BKF (450 mg, three tablets three times a day before meals) for seven days. Differences in metabolic profiling between bDCR groups were investigated by using liquid chromatography coupled with mass spectrometry for untargeted analysis, and in addition, the safety was assessed by testing the plasma biochemical level. Results This study identified 57 biomarkers in positive ESI and 12 in negative ESI. Piperine was found in varying amount among the participants but it was the highest in the earth group. In addition, this study found that elemicin, phenylpropionic acid, ricinoleic acid, and β-sitosterol are important substances in a single herb of BKF. Regarding biochemical tests, the results indicated that BKF can decrease the lipid profile and it has no toxic effects on liver and kidney functions. Conclusion The findings indicated that it is safe to use BKF which can help to improve health in chronic diseases by adjusting abnormality of the elements of the body. In addition, the information gathered from this study is valuable for further study in the field of Thai traditional medicine.
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Affiliation(s)
- Manmas Vannabhum
- Center of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Suthatip Mahajaroensiri
- Center of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Saracha Pattanapholkornsakul
- Center of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Athippat Tantiwongsekunakorn
- Center of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Thapthep Thippayacharoentam
- Center of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Pinpat Tripatara
- Pharmacology Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Pravit Akarasereenont
- Center of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Pharmacology Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
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4
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Jariyasopit N, Khoomrung S. Mass spectrometry-based analysis of gut microbial metabolites of aromatic amino acids. Comput Struct Biotechnol J 2023; 21:4777-4789. [PMID: 37841334 PMCID: PMC10570628 DOI: 10.1016/j.csbj.2023.09.032] [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: 05/04/2023] [Revised: 09/24/2023] [Accepted: 09/24/2023] [Indexed: 10/17/2023] Open
Abstract
Small molecules derived from gut microbiota have been increasingly investigated to better understand the functional roles of the human gut microbiome. Microbial metabolites of aromatic amino acids (AAA) have been linked to many diseases, such as metabolic disorders, chronic kidney diseases, inflammatory bowel disease, diabetes, and cancer. Important microbial AAA metabolites are often discovered via global metabolite profiling of biological specimens collected from humans or animal models. Subsequent metabolite identity confirmation and absolute quantification using targeted analysis enable comparisons across different studies, which can lead to the establishment of threshold concentrations of potential metabolite biomarkers. Owing to their excellent selectivity and sensitivity, hyphenated mass spectrometry (MS) techniques are often employed to identify and quantify AAA metabolites in various biological matrices. Here, we summarize the developments over the past five years in MS-based methodology for analyzing gut microbiota-derived AAA. Sample preparation, method validation, analytical performance, and statistical methods for correlation analysis are discussed, along with future perspectives.
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Affiliation(s)
- Narumol Jariyasopit
- Siriraj Center of Research Excellence in Metabolomics and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital Mahidol University, Bangkok 10700, Thailand
| | - Sakda Khoomrung
- Siriraj Center of Research Excellence in Metabolomics and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital Mahidol University, Bangkok 10700, Thailand
- Department of Biochemistry, Faculty of Medicine Siriraj Hospital Mahidol University, Bangkok 10700, Thailand
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Jariyasopit N, Limjiasahapong S, Kurilung A, Sartyoungkul S, Wisanpitayakorn P, Nuntasaen N, Kuhakarn C, Reutrakul V, Kittakoop P, Sirivatanauksorn Y, Khoomrung S. Traveling Wave Ion Mobility-Derived Collision Cross Section Database for Plant Specialized Metabolites: An Application to Ventilago harmandiana Pierre. J Proteome Res 2022; 21:2481-2492. [PMID: 36154058 PMCID: PMC9552781 DOI: 10.1021/acs.jproteome.2c00413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Indexed: 11/29/2022]
Abstract
The combination of ion mobility mass spectrometry (IM-MS) and chromatography is a valuable tool for identifying compounds in natural products. In this study, using an ultra-performance liquid chromatography system coupled to a high-resolution quadrupole/traveling wave ion mobility spectrometry/time-of-flight MS (UPLC-TWIMS-QTOF), we have established and validated a comprehensive TWCCSN2 and MS database for 112 plant specialized metabolites. The database included 15 compounds that were isolated and purified in-house and are not commercially available. We obtained accurate m/z, retention times, fragment ions, and TWIMS-derived CCS (TWCCSN2) values for 207 adducts (ESI+ and ESI-). The database included novel 158 TWCCSN2 values from 79 specialized metabolites. In the presence of plant matrix, the CCS measurement was reproducible and robust. Finally, we demonstrated the application of the database to extend the metabolite coverage of Ventilago harmandiana Pierre. In addition to pyranonaphthoquinones, a group of known specialized metabolites in V. harmandiana, we identified flavonoids, xanthone, naphthofuran, and protocatechuic acid for the first time through targeted analysis. Interestingly, further investigation using IM-MS of unknown features suggested the presence of organonitrogen compounds and lipid and lipid-like molecules, which is also reported for the first time. Data are available on the MassIVE (https://massive.ucsd.edu, data set identifier MSV000090213).
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Affiliation(s)
- Narumol Jariyasopit
- Metabolomics
and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj
Metabolomics and Phenomics Center, Faculty
of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Suphitcha Limjiasahapong
- Siriraj
Metabolomics and Phenomics Center, Faculty
of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Alongkorn Kurilung
- Metabolomics
and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Sitanan Sartyoungkul
- Metabolomics
and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Pattipong Wisanpitayakorn
- Metabolomics
and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj
Metabolomics and Phenomics Center, Faculty
of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Narong Nuntasaen
- Center
of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok 10400 Thailand
| | - Chutima Kuhakarn
- Center
of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok 10400 Thailand
| | - Vichai Reutrakul
- Center
of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok 10400 Thailand
| | - Prasat Kittakoop
- Chulabhorn
Graduate Institute, Program in Chemical Sciences, Chulabhorn Royal Academy, Laksi,
Bangkok 10210, Thailand
- Chulabhorn
Research Institute, Kamphaeng Phet 6 Road, Laksi, Bangkok 10210, Thailand
| | - Yongyut Sirivatanauksorn
- Siriraj
Metabolomics and Phenomics Center, Faculty
of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Sakda Khoomrung
- Metabolomics
and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj
Metabolomics and Phenomics Center, Faculty
of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Center
of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok 10400 Thailand
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Indrati N, Phonsatta N, Poungsombat P, Khoomrung S, Sumpavapol P, Panya A. Metabolic profiles alteration of Southern Thailand traditional sweet pickled mango during the production process. Front Nutr 2022; 9:934842. [PMID: 36159495 PMCID: PMC9493497 DOI: 10.3389/fnut.2022.934842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 08/15/2022] [Indexed: 11/21/2022] Open
Abstract
Sweet pickled mango named Ma-Muang Bao Chae-Im (MBC), a delicacy from the Southern part of Thailand, has a unique aroma and taste. The employed immersion processes (brining 1, brining 2, and immersion in a hypertonic sugar solution, sequentially) in the MBC production process bring changes to the unripe mango, which indicate the occurrence of metabolic profiles alteration during the production process. This occurrence was never been explored. Thus, this study investigated metabolic profile alteration during the MBC production process. The untargeted metabolomics profiling method was used to reveal the changes in volatile and non-volatile metabolites. Headspace solid-phase micro-extraction tandem with gas chromatography quadrupole time of flight (GC/QTOF) was employed for the volatile analysis, while metabolites derivatization for non-volatile analysis. In conclusion, a total of 82 volatile and 41 non-volatile metabolites were identified during the production process. Terpenes, terpenoids, several non-volatile organic acids, and sugars were the major mango metabolites that presented throughout the process. Gamma-aminobutyric acid (GABA) was only observed during the brining processes, which suggested the microorganism’s stress response mechanism to an acidic environment and high chloride ions in brine. Esters and alcohols were abundant during the last immersion process, which had an important role in MBC flavor characteristics. The knowledge of metabolites development during the MBC production process would be beneficial for product development and optimization.
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Affiliation(s)
- Niken Indrati
- Food Microbiology and Safety Laboratory, Food Science and Technology Program, Faculty of Agro-Industry, Prince of Songkla University, Songkhla, Thailand
| | - Natthaporn Phonsatta
- Food Biotechnology Research Team, Functional Ingredients and Food Innovation Research Group, National Center for Genetic Engineering and Biotechnology (BIOTEC), Thailand Science Park, Khlong Luang, Thailand
| | - Patcha Poungsombat
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Sakda Khoomrung
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Department of Chemistry and Center of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok, Thailand
| | - Punnanee Sumpavapol
- Food Microbiology and Safety Laboratory, Food Science and Technology Program, Faculty of Agro-Industry, Prince of Songkla University, Songkhla, Thailand
- *Correspondence: Punnanee Sumpavapol,
| | - Atikorn Panya
- Food Biotechnology Research Team, Functional Ingredients and Food Innovation Research Group, National Center for Genetic Engineering and Biotechnology (BIOTEC), Thailand Science Park, Khlong Luang, Thailand
- Atikorn Panya,
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7
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Shady NH, Mostafa NM, Fayez S, Abdel-Rahman IM, Maher SA, Zayed A, Saber EA, Khowdiary MM, Elrehany MA, Alzubaidi MA, Altemani FH, Shawky AM, Abdelmohsen UR. Mechanistic Wound Healing and Antioxidant Potential of Moringa oleifera Seeds Extract Supported by Metabolic Profiling, In Silico Network Design, Molecular Docking, and In Vivo Studies. Antioxidants (Basel) 2022; 11:antiox11091743. [PMID: 36139817 PMCID: PMC9495458 DOI: 10.3390/antiox11091743] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/25/2022] [Accepted: 08/26/2022] [Indexed: 11/16/2022] Open
Abstract
Moringa oleifera Lam. (Moringaceae) is an adaptable plant with promising phytoconstituents, interesting medicinal uses, and nutritional importance. Chemical profiling of M. oleifera seeds assisted by LC-HRMS (HPLC system coupled to a high resolution mass detector) led to the dereplication of 19 metabolites. Additionally, the wound healing potential of M. oleifera seed extract was investigated in male New Zealand Dutch strain albino rabbits and supported by histopathological examinations. Moreover, the molecular mechanisms were investigated via different in vitro investigations and through analyzing the relative gene and protein expression patterns. When compared to the untreated and MEBO®-treated groups, topical administration of M. oleifera extract on excision wounds resulted in a substantial increase in wound healing rate (p < 0.001), elevating TGF-β1, VEGF, Type I collagen relative expression, and reducing inflammatory markers such as IL-1β and TNF-α. In vitro antioxidant assays showed that the extract displayed strong scavenging effects to peroxides and superoxide free radicals. In silico studies using a molecular docking approach against TNF-α, TGFBR1, and IL-1β showed that some metabolites in M. oleifera seed extract can bind to the active sites of three wound-healing related proteins. Protein−protein interaction (PPI) and compound−protein interaction (CPI) networks were constructed as well. Quercetin, caffeic acid, and kaempferol showed the highest connectivity with the putative proteins. In silico drug likeness studies revealed that almost all compounds comply with both Lipinski’s and Veber’s rule. According to the previous findings, an in vitro study was carried out on the pure compounds, including quercetin, kaempferol, and caffeic acid (identified from M. oleifera) to validate the proposed approach and to verify their potential effectiveness. Their inhibitory potential was evaluated against the pro-inflammatory cytokine IL-6 and against the endopeptidase MMPs (matrix metalloproteinases) subtype I and II, with highest activity being observed for kaempferol. Hence, M. oleifera seeds could be a promising source of bioactive compounds with potential antioxidant and wound healing capabilities.
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Affiliation(s)
- Nourhan Hisham Shady
- Department of Pharmacognosy, Faculty of Pharmacy, Deraya University, Universities Zone, New Minia City 61111, Egypt
- Correspondence: (N.H.S.); (N.M.M.); (U.R.A.); Tel.: +20-1025666872 (N.M.M.); +20-01005867510 or +20-1111595772 (U.R.A.)
| | - Nada M. Mostafa
- Department of Pharmacognosy, Faculty of Pharmacy, Ain Shams University, Cairo 11566, Egypt
- Correspondence: (N.H.S.); (N.M.M.); (U.R.A.); Tel.: +20-1025666872 (N.M.M.); +20-01005867510 or +20-1111595772 (U.R.A.)
| | - Shaimaa Fayez
- Department of Pharmacognosy, Faculty of Pharmacy, Ain Shams University, Cairo 11566, Egypt
| | - Islam M. Abdel-Rahman
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Deraya University, Minia 61519, Egypt
| | - Sherif A. Maher
- Department of Biochemistry, Faculty of Pharmacy, Deraya University, Universities Zone, New Minia City 61111, Egypt
| | - Ahmed Zayed
- Pharmacognosy Department, College of Pharmacy, Tanta University, Elguish Street (Medical Campus), Tanta 31527, Egypt
- Institute of Bioprocess Engineering, Technical University of Kaiserslautern, Gottlieb-Daimler-Straβe 49, 67663 Kaiserslautern, Germany
| | - Entesar Ali Saber
- Department of Histology and Cell Biology, Faculty of Medicine, Minia University, Minia 61519, Egypt, Delegated to Deraya University, Universities Zone, New Minia City 61111, Egypt
| | - Manal M. Khowdiary
- Chemistry Department, Faculty of Applied Science, Umm Al-Qura University, Al-Lith Branch, Makkah 24211, Saudi Arabia
| | - Mahmoud A. Elrehany
- Department of Biochemistry, Faculty of Pharmacy, Deraya University, Universities Zone, New Minia City 61111, Egypt
- Department of Biochemistry, Faculty of Medicine, Minia University, Minia 61519, Egypt
| | - Mubarak A. Alzubaidi
- Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Faisal H. Altemani
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, University of Tabuk, Tabuk 71491, Saudi Arabia
| | - Ahmed M. Shawky
- Science and Technology Unit (STU), Umm Al-Qura University, Makkah 21955, Saudi Arabia
| | - Usama Ramadan Abdelmohsen
- Department of Pharmacognosy, Faculty of Pharmacy, Deraya University, Universities Zone, New Minia City 61111, Egypt
- Department of Pharmacognosy, Faculty of Pharmacy, Minia University, Minia 61519, Egypt
- Correspondence: (N.H.S.); (N.M.M.); (U.R.A.); Tel.: +20-1025666872 (N.M.M.); +20-01005867510 or +20-1111595772 (U.R.A.)
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Nurcahyanti ADR, Cokro F, Wulanjati MP, Mahmoud MF, Wink M, Sobeh M. Curcuminoids for Metabolic Syndrome: Meta-Analysis Evidences Toward Personalized Prevention and Treatment Management. Front Nutr 2022; 9:891339. [PMID: 35757255 PMCID: PMC9218575 DOI: 10.3389/fnut.2022.891339] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 04/21/2022] [Indexed: 12/22/2022] Open
Abstract
The metabolic syndrome (MS) is a multifactorial syndrome associated with a significant economic burden and healthcare costs. MS management often requires multiple treatments (polydrug) to ameliorate conditions such as diabetes mellitus, insulin resistance, obesity, cardiovascular diseases, hypertension, and non-alcoholic fatty liver disease (NAFLD). However, various therapeutics and possible drug-drug interactions may also increase the risk of MS by altering lipid and glucose metabolism and promoting weight gain. In addition, the medications cause side effects such as nausea, flatulence, bloating, insomnia, restlessness, asthenia, palpitations, cardiac arrhythmias, dizziness, and blurred vision. Therefore, is important to identify and develop new safe and effective agents based on a multi-target approach to treat and manage MS. Natural products, such as curcumin, have multi-modalities to simultaneously target several factors involved in the development of MS. This review discusses the recent preclinical and clinical findings, and up-to-date meta-analysis from Randomized Controlled Trials regarding the effects of curcumin on MS, as well as the metabonomics and a pharma-metabolomics outlook considering curcumin metabolites, the gut microbiome, and environment for a complementary personalized prevention and treatment for MS management.
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Affiliation(s)
- Agustina Dwi Retno Nurcahyanti
- Department of Pharmacy, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
| | - Fonny Cokro
- Department of Pharmacy, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
| | - Martha P Wulanjati
- Research Division for Natural Products Technology (BPTBA), National Research and Innovation Agency (BRIN), Yogyakarta, Indonesia
| | - Mona F Mahmoud
- Department of Pharmacology and Toxicology, Faculty of Pharmacy, Zagazig University, Zagazig, Egypt
| | - Michael Wink
- Institute of Pharmacy and Molecular Biotechnology (IPMB), Heidelberg University, Heidelberg, Germany
| | - Mansour Sobeh
- AgroBioSciences Department, Mohammed VI Polytechnic University, Ben-Guerir, Morocco
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Ouchene R, Stien D, Segret J, Kecha M, Rodrigues AMS, Veckerlé C, Suzuki MT. Integrated Metabolomic, Molecular Networking, and Genome Mining Analyses Uncover Novel Angucyclines From Streptomyces sp. RO-S4 Strain Isolated From Bejaia Bay, Algeria. Front Microbiol 2022; 13:906161. [PMID: 35814649 PMCID: PMC9260717 DOI: 10.3389/fmicb.2022.906161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 05/16/2022] [Indexed: 11/13/2022] Open
Abstract
Multi-omic approaches have recently made big strides toward the effective exploration of microorganisms, accelerating the discovery of new bioactive compounds. We combined metabolomic, molecular networking, and genomic-based approaches to investigate the metabolic potential of the Streptomyces sp. RO-S4 strain isolated from the polluted waters of Bejaia Bay in Algeria. Antagonistic assays against methicillin-resistant Staphylococcus aureus with RO-S4 organic extracts showed an inhibition zone of 20 mm by using the agar diffusion method, and its minimum inhibitory concentration was 16 μg/ml. A molecular network was created using GNPS and annotated through the comparison of MS/MS spectra against several databases. The predominant compounds in the RO-S4 extract belonged to the angucycline family. Three compounds were annotated as known metabolites, while all the others were putatively new to Science. Notably, all compounds had fridamycin-like aglycones, and several of them had a lactonized D ring analogous to that of urdamycin L. The whole genome of Streptomyces RO-S4 was sequenced to identify the biosynthetic gene cluster (BGC) linked to these angucyclines, which yielded a draft genome of 7,497,846 bp with 72.4% G+C content. Subsequently, a genome mining analysis revealed 19 putative biosynthetic gene clusters, including a grincamycin-like BGC with high similarity to that of Streptomyces sp. CZN-748, that was previously reported to also produce mostly open fridamycin-like aglycones. As the ring-opening process leading to these compounds is still not defined, we performed a comparative analysis with other angucycline BGCs and advanced some hypotheses to explain the ring-opening and lactonization, possibly linked to the uncoupling between the activity of GcnE and GcnM homologs in the RO-S4 strain. The combination of metabolomic and genomic approaches greatly improved the interpretation of the metabolic potential of the RO-S4 strain.
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Affiliation(s)
- Rima Ouchene
- Laboratoire de Microbiologie Appliquée (LMA), Faculté des Sciences de la Nature et de la Vie, Université de Bejaia, Bejaia, Algeria
- Sorbonne Université, CNRS, Laboratoire de Biodiversité et Biotechnologies Microbiennes, LBBM, F-66650, Banyuls-sur-mer, France
| | - Didier Stien
- Sorbonne Université, CNRS, Laboratoire de Biodiversité et Biotechnologies Microbiennes, LBBM, F-66650, Banyuls-sur-mer, France
- *Correspondence: Didier Stien
| | - Juliette Segret
- Sorbonne Université, CNRS, Laboratoire de Biodiversité et Biotechnologies Microbiennes, LBBM, F-66650, Banyuls-sur-mer, France
| | - Mouloud Kecha
- Laboratoire de Microbiologie Appliquée (LMA), Faculté des Sciences de la Nature et de la Vie, Université de Bejaia, Bejaia, Algeria
| | - Alice M. S. Rodrigues
- Sorbonne Université, CNRS, Laboratoire de Biodiversité et Biotechnologies Microbiennes, LBBM, F-66650, Banyuls-sur-mer, France
| | - Carole Veckerlé
- Sorbonne Université, CNRS, Laboratoire de Biodiversité et Biotechnologies Microbiennes, LBBM, F-66650, Banyuls-sur-mer, France
| | - Marcelino T. Suzuki
- Sorbonne Université, CNRS, Laboratoire de Biodiversité et Biotechnologies Microbiennes, LBBM, F-66650, Banyuls-sur-mer, France
- Marcelino T. Suzuki
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10
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Abstract
This research focuses on community development and ways in which community members can express their opinions and maintain well-being. However, in many contexts, these voices have been enfeebled through top-down approaches, lack of a concrete scenario, and attention to community problems, all of which are frequently associated with prejudices based on social status, education, or gender. For the first time within an urban context, the Ban Bu/Wat Suwannaram community in Bangkok, Thailand, has been given the opportunity to voice their opinions about the community, the direction it should take, and the overall improvement to be made, without the constriction of external authorities. This study applies design thinking, which despite being one of the major trends in business over the last couple of decades, is not generally used to address social issues. Since design thinking requires data collection and the creation of a model/prototype, two complementary procedures are employed. Firstly, the community is studied through observation and interviews, which helped creating a SWOT analysis to identify its potential and facilitate an informal discussion with members of the local community on the situation before urbanisation loosened community ties. After this initial stage, a prototype for various areas of community development is discussed in a community workshop to enable participants to offer their opinions on how the community could develop further. The results reveal the aspirations of the local community towards improving social and environmental issues.
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11
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Chen XL, Sun MC, Chong SL, Si JP, Wu LS. Transcriptomic and Metabolomic Approaches Deepen Our Knowledge of Plant-Endophyte Interactions. FRONTIERS IN PLANT SCIENCE 2022; 12:700200. [PMID: 35154169 PMCID: PMC8828500 DOI: 10.3389/fpls.2021.700200] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Accepted: 12/22/2021] [Indexed: 05/10/2023]
Abstract
In natural systems, plant-symbiont-pathogen interactions play important roles in mitigating abiotic and biotic stresses in plants. Symbionts have their own special recognition ways, but they may share some similar characteristics with pathogens based on studies of model microbes and plants. Multi-omics technologies could be applied to study plant-microbe interactions, especially plant-endophyte interactions. Endophytes are naturally occurring microbes that inhabit plants, but do not cause apparent symptoms in them, and arise as an advantageous source of novel metabolites, agriculturally important promoters, and stress resisters in their host plants. Although biochemical, physiological, and molecular investigations have demonstrated that endophytes confer benefits to their hosts, especially in terms of promoting plant growth, increasing metabolic capabilities, and enhancing stress resistance, plant-endophyte interactions consist of complex mechanisms between the two symbionts. Further knowledge of these mechanisms may be gained by adopting a multi-omics approach. The involved interaction, which can range from colonization to protection against adverse conditions, has been investigated by transcriptomics and metabolomics. This review aims to provide effective means and ways of applying multi-omics studies to solve the current problems in the characterization of plant-microbe interactions, involving recognition and colonization. The obtained results should be useful for identifying the key determinants in such interactions and would also provide a timely theoretical and material basis for the study of interaction mechanisms and their applications.
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Affiliation(s)
| | | | | | | | - Ling-shang Wu
- State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou, China
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12
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Anekthanakul K, Manocheewa S, Chienwichai K, Poungsombat P, Limjiasahapong S, Wanichthanarak K, Jariyasopit N, Mathema VB, Kuhakarn C, Reutrakul V, Phetcharaburanin J, Panya A, Phonsatta N, Visessanguan W, Pomyen Y, Sirivatanauksorn Y, Worawichawong S, Sathirapongsasuti N, Kitiyakara C, Khoomrung S. Predicting lupus membranous nephritis using reduced picolinic acid to tryptophan ratio as a urinary biomarker. iScience 2021; 24:103355. [PMID: 34805802 PMCID: PMC8590081 DOI: 10.1016/j.isci.2021.103355] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Revised: 10/01/2021] [Accepted: 10/22/2021] [Indexed: 12/14/2022] Open
Abstract
The current gold standard for classifying lupus nephritis (LN) progression is a renal biopsy, which is an invasive procedure. Undergoing a series of biopsies for monitoring disease progression and treatments is unlikely suitable for patients with LN. Thus, there is an urgent need for non-invasive alternative biomarkers that can facilitate LN class diagnosis. Such biomarkers will be very useful in guiding intervention strategies to mitigate or treat patients with LN. Urine samples were collected from two independent cohorts. Patients with LN were classified into proliferative (class III/IV) and membranous (class V) by kidney histopathology. Metabolomics was performed to identify potential metabolites, which could be specific for the classification of membranous LN. The ratio of picolinic acid (Pic) to tryptophan (Trp) ([Pic/Trp] ratio) was found to be a promising candidate for LN diagnostic and membranous classification. It has high potential as an alternative biomarker for the non-invasive diagnosis of LN.
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Affiliation(s)
- Krittima Anekthanakul
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Siriphan Manocheewa
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Kittiphan Chienwichai
- Department of Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand
- Hatyai hospital, Songkhla 90110, Thailand
| | - Patcha Poungsombat
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Suphitcha Limjiasahapong
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Kwanjeera Wanichthanarak
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Narumol Jariyasopit
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Vivek Bhakta Mathema
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Chutima Kuhakarn
- Department of Chemistry and Center of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - Vichai Reutrakul
- Department of Chemistry and Center of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok 10400, Thailand
| | - Jutarop Phetcharaburanin
- Department of Biochemistry, Faculty of Medicine, Khon Kaen University, Khon Kaen 40002, Thailand
- Cholangiocarcinoma Research Institute, Khon Kaen University, Khon Kaen 40002, Thailand
- Khon Kaen University International Phenome Laboratory, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Atikorn Panya
- Functional Ingredients and Food Biotechnology Research Unit, National Center for Genetic Engineering and Biotechnology (BIOTEC), Pathumthani 12120, Thailand
| | - Natthaporn Phonsatta
- Functional Ingredients and Food Biotechnology Research Unit, National Center for Genetic Engineering and Biotechnology (BIOTEC), Pathumthani 12120, Thailand
| | - Wonnop Visessanguan
- Functional Ingredients and Food Biotechnology Research Unit, National Center for Genetic Engineering and Biotechnology (BIOTEC), Pathumthani 12120, Thailand
| | - Yotsawat Pomyen
- Translational Research Unit, Chulabhorn Research Institute, Bangkok 10210, Thailand
| | - Yongyut Sirivatanauksorn
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Suchin Worawichawong
- Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand
| | - Nuankanya Sathirapongsasuti
- Section of Translational Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand
- Research Network of NANOTEC - MU Ramathibodi on Nanomedicine, Bangkok 10400, Thailand
| | - Chagriya Kitiyakara
- Department of Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand
- Research Network of NANOTEC - MU Ramathibodi on Nanomedicine, Bangkok 10400, Thailand
| | - Sakda Khoomrung
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Department of Chemistry and Center of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok 10400, Thailand
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13
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Kaewnarin K, Limjiasahapong S, Jariyasopit N, Anekthanakul K, Kurilung A, Wong SCC, Sirivatanauksorn Y, Visessanguan W, Khoomrung S. High-Resolution QTOF-MRM for Highly Accurate Identification and Quantification of Trace Levels of Triterpenoids in Ganoderma lucidum Mycelium. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:2451-2462. [PMID: 34412475 DOI: 10.1021/jasms.1c00175] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The accurate quantification of triterpenoids in Ganoderma lucidum mushroom in the mycelium stage is challenging due to their low concentrations, interference from other possible isomers, and the complex matrix. Here, a high-resolution quadrupole-time-of-flight mass spectrometry "multiple reaction monitoring" with target enhancement (HR-QTOF-MRM) method was developed to quantify seven target triterpenoids in G. lucidum. The performance of this method was compared against an optimized QQQ-MRM method. The HR-QTOF-MRM was shown to be capable of distinguishing target triterpenoids from interferent peaks in the presence of matrices. The HR-QTOF-MRM LOD and LLOQ values were found to be one to two times lower than those derived from the QQQ-MRM method. Intraday and interday variabilities of the HR-QTOF-MRM demonstrated better reproducibility than the QQQ-MRM. In addition, excellent recoveries of the analytes ranging from 80 to 117% were achieved. Spiking experiments were carried out to verify and compare the quantitative accuracy of the two methods. The HR-QTOF-MRM method provided better percent accuracy, ranging from 84% to 99% (<3% RSD), compared with the range of 69 to 114% (<4%RSD) given by the QQQ-MRM method. These results demonstrate that the new HR-QTOF-MRM mode is able to improve sensitivity, reproducibility, and accuracy of trace level analysis of triterpenoids in the complex biological samples. The triterpenoid concentrations were in the range of nondetect to 0.06-6.72 mg/g of dried weight in fruiting body and to 0.0009-0.01 mg/g of dried weight in mycelium.
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Affiliation(s)
- Khwanta Kaewnarin
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Suphitcha Limjiasahapong
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Narumol Jariyasopit
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Krittima Anekthanakul
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Alongkorn Kurilung
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | | | - Yongyut Sirivatanauksorn
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Wonnop Visessanguan
- National Center for Genetic Engineering and Biotechnology (BIOTEC), Thailand Science Park, Pathum Thani 12120, Thailand
| | - Sakda Khoomrung
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Center of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok 10700, Thailand
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14
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Crosstalk of Multi-Omics Platforms with Plants of Therapeutic Importance. Cells 2021; 10:cells10061296. [PMID: 34071113 PMCID: PMC8224614 DOI: 10.3390/cells10061296] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 04/25/2021] [Accepted: 05/10/2021] [Indexed: 02/06/2023] Open
Abstract
From time immemorial, humans have exploited plants as a source of food and medicines. The World Health Organization (WHO) has recorded 21,000 plants with medicinal value out of 300,000 species available worldwide. The promising modern "multi-omics" platforms and tools have been proven as functional platforms able to endow us with comprehensive knowledge of the proteome, genome, transcriptome, and metabolome of medicinal plant systems so as to reveal the novel connected genetic (gene) pathways, proteins, regulator sequences and secondary metabolite (molecule) biosynthetic pathways of various drug and protein molecules from a variety of plants with therapeutic significance. This review paper endeavors to abridge the contemporary advancements in research areas of multi-omics and the information involved in decoding its prospective relevance to the utilization of plants with medicinal value in the present global scenario. The crosstalk of medicinal plants with genomics, transcriptomics, proteomics, and metabolomics approaches will be discussed.
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15
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Fu J, Zhang Y, Liu J, Lian X, Tang J, Zhu F. Pharmacometabonomics: data processing and statistical analysis. Brief Bioinform 2021; 22:6236068. [PMID: 33866355 DOI: 10.1093/bib/bbab138] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Revised: 02/09/2021] [Accepted: 03/23/2021] [Indexed: 12/14/2022] Open
Abstract
Individual variations in drug efficacy, side effects and adverse drug reactions are still challenging that cannot be ignored in drug research and development. The aim of pharmacometabonomics is to better understand the pharmacokinetic properties of drugs and monitor the drug effects on specific metabolic pathways. Here, we systematically reviewed the recent technological advances in pharmacometabonomics for better understanding the pathophysiological mechanisms of diseases as well as the metabolic effects of drugs on bodies. First, the advantages and disadvantages of all mainstream analytical techniques were compared. Second, many data processing strategies including filtering, missing value imputation, quality control-based correction, transformation, normalization together with the methods implemented in each step were discussed. Third, various feature selection and feature extraction algorithms commonly applied in pharmacometabonomics were described. Finally, the databases that facilitate current pharmacometabonomics were collected and discussed. All in all, this review provided guidance for researchers engaged in pharmacometabonomics and metabolomics, and it would promote the wide application of metabolomics in drug research and personalized medicine.
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Affiliation(s)
- Jianbo Fu
- College of Pharmaceutical Sciences in Zhejiang University, China
| | - Ying Zhang
- College of Pharmaceutical Sciences in Zhejiang University, China
| | - Jin Liu
- College of Pharmaceutical Sciences in Zhejiang University, China
| | - Xichen Lian
- College of Pharmaceutical Sciences in Zhejiang University, China
| | - Jing Tang
- Department of Bioinformatics in Chongqing Medical University, China
| | - Feng Zhu
- College of Pharmaceutical Sciences in Zhejiang University, China
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16
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Jariyasopit N, Khamsaeng S, Panya A, Vinaisuratern P, Metem P, Asawalertpanich W, Visessanguan W, Sirivatanauksorn V, Khoomrung S. Quantitative analysis of nutrient metabolite compositions of retail cow’s milk and milk alternatives in Thailand using GC-MS. J Food Compost Anal 2021. [DOI: 10.1016/j.jfca.2020.103785] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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17
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Limjiasahapong S, Kaewnarin K, Jariyasopit N, Hongthong S, Nuntasaen N, Robinson JL, Nookaew I, Sirivatanauksorn Y, Kuhakarn C, Reutrakul V, Khoomrung S. UPLC-ESI-MRM/MS for Absolute Quantification and MS/MS Structural Elucidation of Six Specialized Pyranonaphthoquinone Metabolites From Ventilago harmandiana. FRONTIERS IN PLANT SCIENCE 2021; 11:602993. [PMID: 33505413 PMCID: PMC7830255 DOI: 10.3389/fpls.2020.602993] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 11/25/2020] [Indexed: 06/12/2023]
Abstract
Pyranonaphthoquinones (PNQs) are important structural scaffolds found in numerous natural products. Research interest in these specialized metabolites lies in their natural occurrence and therapeutic activities. Nonetheless, research progress has thus far been hindered by the lack of analytical standards and analytical methods for both qualitative and quantitative analysis. We report here that various parts of Ventilago harmandiana are rich sources of PNQs. We developed an ultraperformance liquid chromatography-electrospray ionization multiple reaction monitoring/mass spectrometry method to quantitatively determine six PNQs from leaves, root, bark, wood, and heartwood. The addition of standards in combination with a stable isotope of salicylic acid-D6 was used to overcome the matrix effect with average recovery of 82% ± 1% (n = 15). The highest concentration of the total PNQs was found in the root (11,902 μg/g dry weight), whereas the lowest concentration was found in the leaves (28 μg/g dry weight). Except for the root, PNQ-332 was found to be the major compound in all parts of V. harmandiana, accounting for ∼48% of the total PNQs quantified in this study. However, PNQ-318A was the most abundant PNQ in the root sample, accounting for 27% of the total PNQs. Finally, we provide novel MS/MS spectra of the PNQs at different collision induction energies: 10, 20, and 40 eV (POS and NEG). For structural elucidation purposes, we propose complete MS/MS fragmentation pathways of PNQs using MS/MS spectra at collision energies of 20 and 40 eV. The MS/MS spectra along with our discussion on structural elucidation of these PNQs should be very useful to the natural products community to further exploring PNQs in V. harmandiana and various other sources.
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Affiliation(s)
- Suphitcha Limjiasahapong
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Center of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok, Thailand
| | - Khwanta Kaewnarin
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Narumol Jariyasopit
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Sakchai Hongthong
- Center of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok, Thailand
- Division of Chemistry, Faculty of Science and Technology, Rajabhat Rajanagarindra University, Chachoengsao, Thailand
| | - Narong Nuntasaen
- The Forest Herbarium National Park, Wildlife and Plant Conservation Department, Ministry of Natural Resources and Environment, Bangkok, Thailand
| | - Jonathan L. Robinson
- National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Intawat Nookaew
- Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Yongyut Sirivatanauksorn
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Chutima Kuhakarn
- Center of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok, Thailand
| | - Vichai Reutrakul
- Center of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok, Thailand
| | - Sakda Khoomrung
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Center of Excellence for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Bangkok, Thailand
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Principle of Hot and Cold and Its Clinical Application in Latin American and Caribbean Medicines. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1343:57-83. [DOI: 10.1007/978-3-030-80983-6_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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19
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Pomyen Y, Wanichthanarak K, Poungsombat P, Fahrmann J, Grapov D, Khoomrung S. Deep metabolome: Applications of deep learning in metabolomics. Comput Struct Biotechnol J 2020; 18:2818-2825. [PMID: 33133423 PMCID: PMC7575644 DOI: 10.1016/j.csbj.2020.09.033] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 09/21/2020] [Accepted: 09/21/2020] [Indexed: 01/11/2023] Open
Abstract
In the past few years, deep learning has been successfully applied to various omics data. However, the applications of deep learning in metabolomics are still relatively low compared to others omics. Currently, data pre-processing using convolutional neural network architecture appears to benefit the most from deep learning. Compound/structure identification and quantification using artificial neural network/deep learning performed relatively better than traditional machine learning techniques, whereas only marginally better results are observed in biological interpretations. Before deep learning can be effectively applied to metabolomics, several challenges should be addressed, including metabolome-specific deep learning architectures, dimensionality problems, and model evaluation regimes.
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Key Words
- AI, Artificial Intelligence
- ANN, Artificial Neural Network
- AUC, Area Under the receiver-operating characteristic Curve
- Artificial neural network
- CCS value, Collision Cross Section value
- CFM-EI, Competitive Fragmentation Modeling-Electron Ionization
- CNN, Convolutional Neural Network
- DL, Deep Learning
- DNN, Deep Neural Network
- Deep learning
- ECFP, Extended Circular Fingerprint
- ER, Estrogen Receptor
- FID, Free Induction Decay
- FP score, Fingerprint correlation score
- FTIR, Fourier Transform Infrared
- GC–MS, Gas Chromatography-Mass Spectrometry
- HDLSS data, High Dimensional Low Sample Size data
- IST, Iterative Soft Thresholding
- LC-MS, Liquid Chromatography-Mass Spectrometry
- LSTM, Long Short-Term Memory
- ML, Machine Learning
- MLP, Multi-layered Perceptron
- MS, Mass Spectrometry
- Mass spectrometry
- Metabolomics
- NEIMS, Neural Electron-Ionization Mass Spectrometry
- NMR
- NMR, Nuclear Magnetic Resonance
- NUS, Non-Uniformly Sampling
- PARAFAC2, Parallel Factor Analysis 2
- RF, Random Forest
- RNN, Recurrent Neural Network
- ReLU, Rectified Linear Unit
- SMARTS, SMILES arbitrary target specification
- SMILE, Sparse Multidimensional Iterative Lineshape-enhanced
- SMILES, Simplified Molecular-Input Line-Entry System
- SRA, Sequence Read Archive
- VAE, Variational Autoencoder
- istHMS, Implementation of IST at Harvard Medical School
- m/z, mass/charge ratio
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Affiliation(s)
- Yotsawat Pomyen
- Translational Research Unit, Chulabhorn Research Institute, Bangkok, Thailand
| | - Kwanjeera Wanichthanarak
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Patcha Poungsombat
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Center for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Rama 6 Road, Bangkok 10400, Thailand
| | - Johannes Fahrmann
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX 77030, USA
| | - Dmitry Grapov
- CDS- Creative Data Solutions LLC, https://creative-data.solutions, USA
| | - Sakda Khoomrung
- Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Center for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Rama 6 Road, Bangkok 10400, Thailand
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1H-NMR-based metabolomics to investigate the effects of Phoenix dactylifera seed extracts in LPS-IFN-γ-induced RAW 264.7 cells. Food Res Int 2019; 125:108565. [PMID: 31554083 DOI: 10.1016/j.foodres.2019.108565] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 06/24/2019] [Accepted: 07/14/2019] [Indexed: 12/13/2022]
Abstract
Inflammation has been revealed to play a central role in the onset and progression of many illnesses. Nuclear magnetic resonance (NMR) based metabolomics method was adopted to evaluate the effects of Phoenix dactylifera seeds, in particular the Algerian date variety of Deglet on the metabolome of the LPS-IFN-γ-induced RAW 264.7 cells. Variations in the extracellular and intracellular profiles emphasized the differences in the presence of tyrosine, phenylalanine, alanine, proline, asparagine, isocitrate, inosine and lysine. Principal component analysis (PCA) revealed noticeable clustering patterns between the treated and induced RAW cells based on the metabolic profile of the extracellular metabolites. However, the effects of treatment on the intracellular metabolites appears to be less distinct as suggested by the PCA and heatmap analyses. A clear group segregation was observed for the intracellular metabolites from the treated and induced cells based on the orthogonal partial least squares-discriminant analysis (OPLS-DA) score plot. Likewise, 11 of the metabolites in the treated cells were significantly different from those in the induced groups, including amino acids and succinate. The enrichment analysis demonstrated that treatment with Deglet seed extracts interfered with the energy and of amino acids metabolism. Overall, the obtained data reinforced the possible application of Deglet seeds as a functional food with anti-inflammatory properties.
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Wanichthanarak K, Jeamsripong S, Pornputtapong N, Khoomrung S. Accounting for biological variation with linear mixed-effects modelling improves the quality of clinical metabolomics data. Comput Struct Biotechnol J 2019; 17:611-618. [PMID: 31110642 PMCID: PMC6506811 DOI: 10.1016/j.csbj.2019.04.009] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 04/16/2019] [Accepted: 04/17/2019] [Indexed: 11/16/2022] Open
Abstract
Metabolite profiles from biological samples suffer from both technical variations and subject-specific variants. To improve the quality of metabolomics data, conventional data processing methods can be employed to remove technical variations. These methods do not consider sources of subject variation as separate factors from biological factors of interest. This can be a significant issue when performing quantitative metabolomics in clinical trials or screening for a potential biomarker in early-stage disease, because changes in metabolism or a desired-metabolite signal are small compared to the total metabolite signals. As a result, inter-individual variability can interfere subsequent statistical analyses. Here, we propose an additional data processing step using linear mixed-effects modelling to readjust an individual metabolite signal prior to multivariate analyses. Published clinical metabolomics data was used to demonstrate and evaluate the proposed method. We observed a substantial reduction in variation of each metabolite signal after model fitting. A comparison with other strategies showed that our proposed method contributed to improved classification accuracy, precision, sensitivity and specificity. Moreover, we highlight the importance of patient metadata as it contains rich information of subject characteristics, which can be used to model and normalize metabolite abundances. The proposed method is available as an R package lmm2met.
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Affiliation(s)
- Kwanjeera Wanichthanarak
- Department of Biochemistry and Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkok Noi, Bangkok 10700, Thailand.,Data Management and Statistical Analysis Center, Faculty of Public Health, Khon Kaen University, Khon Kaen 40002, Thailand
| | - Saharuetai Jeamsripong
- Research Unit in Microbial Food Safety and Antimicrobial Resistance, Department of Veterinary Public Health, Faculty of Veterinary Science, Chulalongkorn University, 39 Henri-Dunant Road, Pathumwan, Bangkok 10330, Thailand
| | - Natapol Pornputtapong
- Department of Biochemistry and Microbiology, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, 10330, Thailand.,Center of Excellence in Systems Biology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
| | - Sakda Khoomrung
- Department of Biochemistry and Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, 2 Wanglang Road, Bangkok Noi, Bangkok 10700, Thailand.,Center for Innovation in Chemistry (PERCH-CIC), Faculty of Science, Mahidol University, Rama 6 Road, Bangkok 10400, Thailand
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