DROP Met
DROP Met is a repository and distribution site of the dataset obtained from our multiple MS-based metabolome analyses. Various kinds of datasets, ranging from raw fundamental data on analytical conditions to metabolic profiles of biological samples, are available to the public. We release some datasets in the raw, hoping that users in bioinformatics and metabolomics fields will develop novel algorithms and methodologies of metabolomics using our datasets. Please read Terms of Use carefully before using DROP Met.
DM0056. Characterization of Entamoeba fatty acid elongases; validation as targets and provision of promising leads for new drugs against amebiasis
| Author | Fumika Mi-ichi, Hiroshi Tsugawa, Vo Kha Tam, Yuto Kurizaki, Hiroki Yoshida, and Makoto Arita |
| Abstract | The LC-MS/MS-based lipidomics raw data for Entamoeba histolytica are available. It includes the experiments of E. histolytica transformants for fatty acid elongase (FAE) over-expression, stable isotope labeling, and drug administration of FAE inhibitors. |
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DM0054. MS-DIAL 5 multimodal mass spectrometry data mining unveils lipidome complexities
| Author | Hiroaki Takeda, Yuki Matsuzawa, Manami Takeuchi, Mikiko Takahashi, Kozo Nishida, Takeshi Harayama, Yoshimasa Todoroki, Kuniyoshi Shimizu, Nami Sakamoto, Takaki Oka, Masashi Maekawa, Mi Hwa Chung, Yuto Kurizaki, Saki Kiuchi, Kanako Tokiyoshi, Bujinlkham Buyantogtokh, Misaki Kurata, Aleš Kvasnička, Ushio Takeda, Haruki Uchino, Mayu Hasegawa, Junki Miyamoto, Kana Tanabe, Shigenori Takeda, Tetsuya Mori, Ryota Kumakubo, Tsuyoshi Tanaka, Tomoko Yoshino, Makoto Arita, Hiroshi Tsugawa |
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DM0053. Using variable data independent acquisition for capillary electrophoresis-based untargeted metabolomics
| Author | Saki Kiuchi, Yasuhiro Otoguro, Tomoaki Nitta, Mi Hwa Chung, Taiki Nakaya, Yuki Matsuzawa, Katsuya Oobuchi, Kazunori Sasaki, Hiroyuki Yamamoto, Hiroshi Tsugawa |
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DM0052. The phosphorylated pathway of serine biosynthesis affects sperm, embryo, and sporophyte development, and metabolism in Marchantia polymorpha
| Author | Mengyao Wang, Hiromitsu Tabeta, Kinuka Ohtaka, Ayuko Kuwahara, Ryuichi Nishihama, Toshiki Ishikawa, Kiminori Toyooka, Mayuko Sato, Mayumi Wakazaki, Hiromichi Akashi, Hiroshi Tsugawa, Tsubasa Shoji, Yozo Okazaki, Keisuke Yoshida, Ryoichi Sato, Ali Ferjani, Takayuki Kohchi, Masami Yokota Hirai |
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GC-QqQ-MS data (Metabolome)
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DM0051. A procedure for solid phase extractions using metal oxide coated silica column in lipidomics
| Author | Hiroaki Takeda, Manami Takeuchi, Mayu Hasegawa, Junki Miyamoto, Hiroshi Tsugawa |
| Abstract | The LC-MS/MS raw data sets which were obtained for the method optimization of solid phase extractions in lipidomics were uploaded. |
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DM0050. Using data-dependent and independent hybrid acquisitions for fast liquid chromatography-based untargeted lipidomics
| Author | Kanako Tokiyoshi, Yuki Matsuzawa, Mikiko Takahashi, Hiroaki Takeda, Mayu Hasegawa, Junki Miyamoto, Hiroshi Tsugawa |
| Please cite | https://www.biorxiv.org/content/10.1101/2023.10.12.562117v1 |
| Abstract | While a fast LC gradient of less than 10 minutes is used for lipid rapid screening in a population-scale study, the lipid annotation rate decreases due to the lower coverage of MS/MS spectra caused by the narrow peak width. To overcome the drawback, we propose a procedure to achieve a high annotation rate in fast LC-based untargeted lipidomics by integrating data-dependent acquisition (DDA) and SWATH (sequential window acquisition of all theoretical mass spectra) data-independent acquisition (DIA) techniques. The uploaded files contain (1) DDA analysis files for plasma (2) SWATH-DIA analysis files for plasma (3) DDA for feces (4) SWATH-DIA for feces and (5) SWATH-DIA for feces which were used to optimize the precursor window range. |
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DM0049. Very-long-chain fatty acids (VLCFAs) are Crucial to Neuronal Polarity by Providing Sphingolipids to Lipid-Rafts
| Author | Atsuko Honda, Motohiro Nozumi, Yasuyuki Ito, Rie Natsume, Asami Kawasaki, Fubito Nakatsu, Manabu Abe, Haruki Uchino, Natsuki Matsushita, Kazutaka Ikeda, Makoto Arita, Kenji Sakimura, Michihiro Igarashi |
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DM0048. ACSL6 facilitates the local distribution of di-DHA- and ULC-PUFA-containing phospholipids in the retina to support normal visual function in mice
| Author | Sayoko Kuroha, Yusaku Katada, Yosuke Isobe, Haruki Uchino, Kyosuke Shishikura, Takashi Nirasawa, Kazuo Tsubota, Kazuno Negishi, Toshihide Kurihara, and Makoto Arita |
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DM0047. Targeted Metabolome Profiling of Indonesian Shallots and Japanese Long-Day/Short-Day Bulb Onions
| Author | Matsuse, Kanako, Mostafa Abdelrahman, Nur Aeni Ariyanti, Fumitada Tsuji, Sho Hirata, Tetsuya Nakajima, Muneo Sato, Masami Yokota Hirai, Benya Manochai, and Masayoshi Shigyo |
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DM0046. Sterol-O acyltransferase inhibition ameliorates high-fat diet-induced renal fibrosis and tertiary lymphoid tissue maturation after ischemic reperfusion injury
| Author | Yuki Ariyasu, Yuki Sato, Yosuke Isobe, Keisuke Taniguchi, Motoko Yanagita, Makoto Arita |
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Untargeted lipidomics data used in this study.
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DM0045. Pleiotropic roles of cholesteryl sulfate during Entamoeba encystation: involvement in cell rounding and development of membrane impermeability
| Author | Fumika Mi-ichi, Hiroshi Tsugawa, Makoto Arita, Hiroki Yoshida |
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LC-QTOF/MS data for untargeted lipidomics
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DM0044. A lipidome landscape of aging in mice
| Author | Hiroshi Tsugawa, Tomoaki Ishihara, Kota Ogasa, Seigo Iwanami, Aya Hori, Mikiko Takahashi, Yutaka Yamada, Aki Minoda, Makoto Arita |
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DM0043. A liquid chromatography-mass spectrometry-based metabolomics strategy to explore plant metabolite diversity
| Author | Tetsuya Mori, Amit Rai, Hiroshi Tsugawa, Yutaka Yamada, Kazuki Saito |
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DM0042. Fecal metabolome data of COVID-19 patients and control subjects
| Author | Naoyoshi Nagata, Tadashi Takeuchi, Hiroaki Masuoka, Ryo Aoki, Masahiro Ishikane, Noriko Iwamoto, Masaya Sugiyama, Wataru Suda, Yumiko Nakanishi, Junko Terada-Hirashima, Moto Kimura, Tomohiko Nishijima, Hiroshi Inooka, Tohru Miyoshi-Akiyama, Yasushi Kojima, Chikako Shimokawa, Hajime Hisaeda, Fen Zhang, Yun Kit Yeoh, Siew C. Ng, Naomi Uemura, Takao Itoi, Masashi Mizokami, Takashi Kawai, Haruhito Sugiyama, Norio Ohmagari, and Hiroshi Ohno |
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DM0041. Assessment of greenhouse tomato anthesis rate through metabolomics using LASSO regularized linear regression model
| Author | Ratklao Siriwach, Jun Matsuzaki, Takeshi Saito, Hiroshi Nishimura, Masahide Isozaki, Yosuke Isoyama, Muneo Sato, Masanori Arita, Shotaro Akaho, Tadahisa Higashide, Kentaro Yano, Masami Yokota Hirai |
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DM0040. Computational mass spectrometry accelerates C=C position-resolved untargeted lipidomics using oxygen attachment dissociation
| Author | Haruki Uchino, Hiroshi Tsugawa, Hidenori Takahashi, Makoto Arita |
| Please cite | Communications Chemistry volume 5, Article number: 162 (2022) |
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The LC-CID-MS/MS and LC-OAD-MS/MS data of HEK293 cells, mouse tissues, and human plasma can be downloaded.
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DM0039. A multimodal metabolomics approach using imaging mass spectrometry and liquid chromatography-tandem mass spectrometry for spatially characterizing monoterpene indole alkaloids secreted from roots
| Author | Ryo Nakabayashi, Noriko Takeda-Kamiya, Yutaka Yamada, Tetsuya Mori, Mai Uzaki, Takashi Nirasawa, Kiminori Toyooka, Kazuki Saito |
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DM0038. Spatial metabolomics using imaging mass spectrometry to identify the localization of asparaptine in Asparagus officinalis
| Author | Ryo Nakabayashi, Kei Hashimoto, Tetsuya Mori, Kiminori Toyooka, Hiroshi Sudo, Kazuki Saito |
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DM0037. Multi-omics reveals the impact of accelerated gut microbiota carbohydrate fermentation on insulin resistance
| Author | Tadashi Takeuchi, Tetsuya Kubota, Yumiko Nakanishi, Hiroshi Tsugawa, Wataru Suda, Andrew Tae-Jun Kwon, Junshi Yazaki, Kazutaka Ikeda, Yoshiki Mochizuki, Toshimori Kitami, Katsuyuki Yugi, Yoshiko Mizuno, Nobutake Yamamichi, Tsutomu Yamazaki, Iseki Takamoto, Naoto Kubota, Takashi Kadowaki, Erik Arner, Piero Carninci, Osamu Ohara, Makoto Arita, Masahira Hattori, Shigeo Koyasu, Hiroshi Ohno |
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DM0036. Stage-Specific De Novo Synthesis of Very-Long-Chain Dihydroceramides Confers Dormancy to Entamoeba Parasites
| Author | Fumika Mi-ichi, Kazutaka Ikeda, Hiroshi Tsugawa, Sharmina Deloer, Hiroki Yoshida and Makoto Arita |
| Citation | https://msphere.asm.org/content/6/2/e00174-21/article-info |
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DM0035. Tandem mass spectrum similarity-based network analysis using 13C-labeled and non-labeled metabolome data to identify the biosynthesis pathway of blood pressure-lowering asparagus metabolite asparaptine A
| Author | Ryo Nakabayashi, Yutaka Yamada, Tomoko Nishizawa, Tetsuya Mori, Takashi Asano, Masanari Kuwabara, Kazuki Saito |
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DM0034. Food lipidomics for 155 agricultural plant products
| Author | Yuki Matsuzawa, Yasuhiro Higashi, Kouji Takano, Mikiko Takahashi, Yutaka Yamada, Yozo Okazaki, Ryo Nakabayashi, Kazuki Saito, Hiroshi Tsugawa |
| Citation | https://pubs.acs.org/doi/abs/10.1021/acs.jafc.0c07356 |
| Link to metadata | RPMM0066 |
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DM0033. Metabolome-Based Discrimination Analysis of Shallot Landraces and Bulb Onion Cultivars Associated with Differences in the Amino Acid and Flavonoid Profiles.
| Author | Mostafa Abdelrahman, Nur Aeni Ariyanti, Yuji Sawada, Fumitada Tsuji, Sho Hirata, Tran Thi Minh Hang, Mami Okamoto, Yutaka Yamada, Hiroshi Tsugawa, Masami Yokota Hirai and Masayoshi Shigyo |
| Citation | https://www.mdpi.com/1420-3049/25/22/5300 |
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DM0032. Elucidation of gut microbiota-associated lipids using LC-MS/MS and 16S rRNA sequence analyses
| Author | Shu Yasuda, Nobuyuki Okahashi, Hiroshi Tsugawa, Yusuke Ogata, Kazutaka Ikeda, Wataru Suda, Hiroyuki Arai, Masahira Hattori, Makoto Arita |
| Citation | https://www.sciencedirect.com/science/article/pii/S2589004220310385 |
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DM0031. A lipidome atlas in MS-DIAL 4
| Author | Hiroshi Tsugawa, Kazutaka Ikeda, Mikiko Takahashi, Aya Satoh, Yoshifumi Mori, Haruki Uchino, Nobuyuki Okahashi, Yutaka Yamada, Ipputa Tada, Paolo Bonini, Yasuhiro Higashi, Yozo Okazaki, Zhiwei Zhou, Zheng-Jiang Zhu, Jeremy Koelmel, Tomas Cajka, Oliver Fiehn, Kazuki Saito, Masanori Arita, and Makoto Arita |
| Citation | https://www.nature.com/articles/s41587-020-0531-2 |
| Link to metadata | SE196 (Metabolonote) |
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DM0030. Characterization of Lipid Profiles after Dietary Intake of Polyunsaturated Fatty Acids Using Integrated Untargeted and Targeted Lipidomics
| Author | Satoko Naoe, Hiroshi Tsugawa, Mikiko Takahashi, Kazutaka Ikeda, Makoto Arita |
| Please cite | Metabolites 2019, 9(10), 241 |
| Summary | Illuminating comprehensive lipid profiles after dietary intakes of polyunsaturated fatty acid (PUFA) is crucial to reveal the tissue distribution of dietary PUFAs in living organisms as well as to provide novel insights in lipid metabolisms. In this study, we performed the lipidomics analyses for mouse plasma and nine tissues, which include liver, kidney, brain, white adipose, lung, small intestine, skeletal muscle, and spleen, in the dietary intake condition of arachidonic acid (ARA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA). |
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DM0029. Genetic Variation for Seed Metabolite Levels in Brachypodium distachyon
| About | Yoshihiko Onda, Komaki, Inoue,Yuji Sawada, Minami Shimizu, Kotaro Takahagi, Yukiko Uehara-Yamaguchi, Masami Y. Hirai, David F. |
| Please cite | International Journal of Molecular Sciences (Accepted) |
| Link to metadata | RPMM0056 |
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Metadata.xlsx for datasets
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DM0028. Metabolome-based discrimination of chrysanthemum cultivars for the efficient generation of flower color variations in mutation breeding
| About | Yuji Sawada, Muneo Sato, Mami Okamoto, Junichi Masuda, Satoshi Yamaki, Mitsuo Tamari, Yuki Tanokashira, Sanae Kishimoto, Akemi Ohmiya, Tomoko Abe, Masami Yokota Hirai |
| Please cite | Metabolomics (Submitted) |
| Link to metadata | RPMM0055 |
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Metadata.xlsx for datasets
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DM0027. Data resource for fully 13C labelled plants
| About | LC-MS/MS data files of fully 13C labelled- and 12C plant tissues, which is utilized to determine the carbon element count for metabolite characterizations. |
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A cheminformatics approach to characterize metabolomes in stable-isotope-labeled organisms. Hiroshi Tsugawa, Ryo Nakabayashi, Tetsuya Mori, Yutaka Yamada, Mikiko Takahashi, Amit Rai, Ryosuke Sugiyama, Hiroyuki Yamamoto, Taiki Nakaya, Mami Yamazaki, Rik Kooke, Johanna A. Bac-Molenaar, Nihal Oztolan-Erol, Joost J. B. Keurentjes, Masanori Arita & Kazuki Saito Nature Methods 16, 295?298 (2019) |
| Link to metadata | RPMM0030 |
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Waters Raw data can be downloaded for 31 plant tissues of 12 plant species. These data can be converted to ABF- or mzML file format to be imported in MS-DIAL.
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DM0026. Arabidopsis thaliana 25 accessions
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LC-MS/MS data files of Arabidopsis thaliana 25 accessions. |
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A cheminformatics approach to characterize metabolomes in stable-isotope-labeled organisms. Hiroshi Tsugawa, Ryo Nakabayashi, Tetsuya Mori, Yutaka Yamada, Mikiko Takahashi, Amit Rai, Ryosuke Sugiyama, Hiroyuki Yamamoto, Taiki Nakaya, Mami Yamazaki, Rik Kooke, Johanna A. Bac-Molenaar, Nihal Oztolan-Erol, Joost J. B. Keurentjes, Masanori Arita & Kazuki Saito Nature Methods 16, 295?298 (2019) |
| Link to metadata | RPMM0030 |
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Waters Raw data can be downloaded for shoot- and root parts of Arabidopsis thaliana accessions. These data can be converted to ABF- or mzML file format to be imported in MS-DIAL. |
DM0025. Integrated strategy for unknown EI-MS identification using quality control calibration curve, multivariate analysis, EI-MS spectral database, and retention index prediction
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GC-MS data files analyzing six types of Chinese medicine Senkyu can be downloaded. This repository also includes pooled QC (quality control) data files used for QC curve filtering. |
| Please cite |
Integrated strategy for unknown EI-MS identification using quality control calibration curve, multivariate analysis, EI-MS spectral database, and retention index prediction Teruko Matsuo, Hiroshi Tsugawa, Hiromi Miyagawa, Eiichiro Fukusaki Anal. Chem. 2017,89,12,6766-6773 |
| Link to metadata | RPMM0031 |
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NetCDF files (six different origins of Senkyu, n = 6; seven concentration ranges of QC samples, n = 4)
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DM0024. A novel method for single-grain-based metabolic profiling of Arabidopsis seed
| About | Yuji Sawada, Hirokazu Tsukaya, Yimeng Li, Muneo Sato, Kensuke Kawade, Masami Yokota Hirai |
| Please cite | Metabolomics (Minor revision) |
| Link to metadata | RPMM0049 |
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Metadata.xlsx for datasets
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DM0023. Test dataset for MS-DIAL 2.0 and MS-FINDER 2.0
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Three validation kits are prepared for the evaluation of MS-DIAL 2.0 and MS-FINDER 2.0. (1) The validation of MS-DIAL chromatogram deconvolution for GC/MS data was performed by six raw data files from five major MS vendors. (2) Software comparison of MS-DIAL against other alternative programs was performed by four raw data files. (3) Software comparison of MS-FINDER against other alternative programs was performed by five EI-MS spectra. The raw files except for Bruker Daltonics and Thermo Fisher Scientific (because of their contracts) can be downloaded. |
| Please cite |
Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics Zijuan Lai, Hiroshi Tsugawa, Gert Wohlgemuth, Sajjan Mehta, Matthew Mueller, Yuxuan Zheng, Atsushi Ogiwara, John Meissen, Megan Showalter, Kohei Takeuchi, Tobias Kind, Peter Beal, Masanori Arita & Oliver Fiehn Nature Methods 15,53-56 (2018) |
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1. Dataset for the validation of MS-DIAL chromatogram deconvolution
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DM0022. Raw LC/MS/MS data of nine algal species
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We performed a lipidomic analysis of nine algal species in our paper (Nature Methods 12, 523-526, 2015). Total 188 LC/MS/MS data sets including data independent acquisition, data dependent acquisition, positive ion mode, negative ion mode, blank samples, and quality controls, can be downloaded from this repository. A part of these files is also managed in our DropMet as 'MS-DIAL demo files'. |
| Please cite |
MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis Hiroshi Tsugawa, Tomas Cajka, Tobias Kind, Yan Ma, Brendan Higgins, Kazutaka Ikeda, Mitsuhiro Kanazawa, Jean VanderGheynst, Oliver Fiehn & Masanori Arita Nature Methods 12,523-526 (2015) |
| Link to metadata | RPMM0033 |
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AB Sciex raw data (.wiff & .wiff.scan), SWATH, Negative ion mode.
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DM0021. Test dataset for the regular expression of MS/MS spectra data
| About | A regular expression of tandem mass spectrometry (MS/MS) data was developed to search structurally similar metabolites and to describe spectral motifs for partial annotation and characterization of metabolite structure (See project homepage .) |
| Please cite | Regular expressions of MS/MS spectra for partial annotation of metabolite features (Submitted) |
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MS/MS strings of MassBank dataset (Supplementary Data 1) and MS/MS strings of Arabidopsis (ATH) and rice (OSA) MS/MS spectra data.
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DM0020. Metabolome data across different growth stages and across under different stress conditions in Brachypodium distachyon and wheat
| About | Widely targeted metabolome analysis was performed at different growth stages (BBCH00 seed, BBCH03 seed, BBCH10 seed, BBCH10 leaf, BBCH11 leaf, and BBCH13 leaf) by using B. distachyon accessions (Bd21 and Bd3-1) and Chinese Spring wheat. Furthermore, another metabolome analysis was also conducted under stress conditions (2℃, 12℃, 32℃, 42℃, 100 mM NaCl and 500 mM NaCl) using plants at the BBCH15 stage. |
| Please cite |
Determination of growth stages and metabolic profiles in Brachypodium distachyon for comparison of developmental context with Triticeae crops Yoshihiko Onda, Kei Hashimoto, Takuhiro Yoshida, Tetsuya Sakurai, Yuji Sawada, Masami Yokota Hirai, Kiminori Toyooka, Keiichi Mochida, and Kazuo Shinozaki Proceedings of the Royal Society B (provisionally accepted) |
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DM0019. MS-DIAL demo files
| About | Both data independent MS/MS acquisition (SWATH) and data dependent MS/MS acquisition (IDA) data sets is downloaded as the demo files of MS-DIAL. In order to use MS-DIAL program, the user has to convert the vendor's raw data to ABF file format. The demonstration for file convert can be performed via AB Sciex raw data sets (.wiff and .wiff.scan). The file converter is available at http://www.reifycs.com/english/AbfConverter/ . If you want to demonstrate MS-DIAL itself, please use the converted files (.abf) from the below link. Also see MSDIAL quick start |
| Please cite | Tsugawa et al. (2015) https://www.ncbi.nlm.nih.gov/pubmed/25938372 |
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AB Sciex raw data (.wiff & .wiff.scan), SWATH, Negative ion mode.
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DM0018. Japanese rice 188 cultivars LC-MS dataset
| About | The metabolome data (NetCDF format, 188 cultivars * 4 replicates = 752 files) were obtained from 188 accessions of Japanese rice collection by liquid chromatography-tandem mass spectrometry (LC-MS/MS). |
| Please cite | Matsuda et al. Submitted. |
| Link to metadata | RPMM0054 |
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DM0017. Untargeted metabolome data during drought stress in Arabidopsis thaliana
| About | The MS and MS/MS data of A. thaliana (Col-0) were acquired in positive mode of LC-QTOF-MS. The raw files were converted to netCDF and text files stored here. |
| Please cite |
Alternation of flavonoid accumulation under drought stress in Arabidopsis thaliana. Ryo Nakabayashi, Tetsuya Mori, Kazuki Saito Plant Signaling & Behavior |
| Link to metadata | RPMM0050 |
| Contents | DAD 0 DAD 3 DAD 5 |
DM0016. Metabolome data in Oryza sativa L. cultivar Habataki and MS/MS spectra of isolated compounds from rice leaves
| About | The MS/MS raw data were acquired in positive and negative mode of LC-QTOF-MS. |
| Please cite |
Toward better annotation in plant metabolomics: Isolation and structure elucidation of 36 specialized metabolites from Oryza sativa (rice) by using MS/MS and NMR analyses Zhigang Yang, Ryo Nakabayashi, Yozo Okazaki, Tetsuya Mori, Satoshi Takamatsu, Susumu Kitanaka, Jun Kikuchi, Kazuki Saito Metabolomics |
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DM0015. High resolution MS/MS spectra from health-promoting crops
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We collected MS/MS spectra from health-promoting crops by LC-QTOF-MS. All data and metadata are freely available. |
| Contact person | Ryo Nakabayashi |
| Acknowledgements | This project was supported by Japan Advanced Plant Science Network and Strategic International Research Cooperative Program (SICP), JST. |
| Contents | Allium cepa from Hokkaido Pref Allium cepa from Saga Pref Allium cepa (Early Red) Allium sativum Allium fistulosum (Bannounegi) Asparagus officinalis Brassica oleracea Brassica rapa Lactuca sativa Raphanus sativus (peel of root) Raphanus sativus (root) Solanum tuberosum (peel of bulb) Solanum tuberosum (bulb) Wasabia japonica (root) Wasabia japonica (leaf and stem) |
DM0014. Development of Metabolite Profiling Database for Knock-Out Mutants in Arabidopsis (MeKO)
| About |
We chose 50 Arabidopsis mutants including a set of characterized and uncharacterized mutants, which resemble wild-type plants. We performed metabolite profiling of the plants using gas chromatography-mass spectrometry (GC-MS). All data are available for download in netCDF format. MetaboLights ID: MTBLS47 . |
| Please cite |
Metabolomic Characterization of Knock-Out Mutants in Arabidopsis - Development of a Metabolite Profiling Database for Knock-Out Mutants in Arabidopsis (MeKO) Atsushi Fukushima, Miyako Kusano, Ramon Francisco Mejia, Mami Iwasa,Makoto Kobayashi, Naomi Hayashi, Akiko Watanabe-Takahashi, Tomoko Narisawa, Takayuki Tohge, Manhoi Hur, Eve Syrkin Wurtele, Basil J.Nikolau, Kazuki Saito Plant Physiology |
| Link to metadata | RPMM0002 |
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DM0013. Metabolome data in Allium plants and MS/MS spectra of S-containing compounds
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The MS raw data were acquired in the positive mode of LC-FTICR-MS. The raw files were converted to netCDF files stored here. |
| Please cite | Submitted. |
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DM0012. Metabolome data in Arabidopsis mutants overaccumulating and lacking flavonoids
| About |
The MS raw data of the Arabidopsis mutants were acquired in positive mode of LC-QTOF-MS. The raw files were converted to netCDF files stored here. |
| Please cite |
Enhancement of oxidative and drought tolerance in Arabidopsis by overaccumulation of antioxidant flavonoids Ryo Nakabayashi, Keiko Yonekura-Sakakibara, Kaoru Urano, Makoto Suzuki, Yutaka Yamada, Tomoko Nishizawa, Fumio Matsuda, Mikiko Kojima, Hitoshi Sakakibara, Kazuo Shinozaki, Anthony J. Michael, Takayuki Tohge, Mami Yamazaki, Kazuki Saito The Plant Journal |
| Link to metadata | RPMM0047 |
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Unstress condition
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DM0011. Metabolic profile data of RILs of G. max and G. soja
| About | LC-ESI-QqQ-MS (UPLC-TQS, Waters) data derived from 93 Soybean RILs with excel file. |
| Please cite |
Computational and Structural Biotechnology Journal 2013 Yuji Sawada, Masami Yokota Hirai Integrated LC-MS/MS system for plant metabolomics |
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DM0010. 12C- & 13C-based metabolome data in onion bulb
| About |
The MS and MS/MS raw data were acquired in the positive mode of LC-FT-ICR-MS. The raw files were converted to netCDF files stored here. |
| Please cite |
Combination of Liquid Chromatography-Fourier Transform-Ion Cyclotron Resonance-Mass Spectrometry with 13C labeling for Chemical Assignment of Sulfur-containing Metabolites in Onion Bulbs Ryo Nakabayashi, Yuji Sawada, Yutaka Yamada, Makoto Suzuki, Masami Yokota Hirai, Tetsuya Sakurai, and Kazuki Saito Analytical Chemistry |
| Link to metadata | RPMM0048 |
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DM0009. Metabolic profile data of LjMG RILines
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Total 88 metabolites of raw LC-ESI-QqQ-MS (UPLC-TQS, Waters) data derived from 132 LjMG RILines with excel file. Metabolic profile data of LjMG RILines |
| Please cite |
RIKEN tandem mass spectral database (ReSpect) for phytochemicals: A plant-specific MS/MS-based data resource and database. Phytochemistry |
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DM0008. AtMetExpress 20 ecotypes raw LC-ESI-TOF-MS dataset
| About | Total 200 raw LC-ESI-TOF-MS chromatogram data derived from 20 Arabidopsis accession recorded with NetCDF format. These are part of the AtMetExpress metabolite accumulation atlas. Detailed information of each data files are described in the meta information (.txt) by following Metabolome Standard Initiative (MSI) recommendation. |
| Please cite |
Mass spectra-based framework for automated structural elucidation of metabolome data to explore phytochemical diversity. Front. Plant Sci. 2:40 (2011). doi: 10.3389/fpls.2011.00040 |
| Link to metadata | RPMM0053 |
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DM0007. Exploring matrix effects and quantification performance in metabolomics experiments using artificial biological gradients
| About | Aritifical biological gradients between leaft and fruit samples from tomato for broad evaluation of quantification performance. |
| Please cite |
Exploring matrix effects and quantification performance in metabolomics experiments using artificial biological gradients. Redestig H, Kobayashi M, Saito K, Kusano M. Anal Chem. 2011 Jun 1. |
| Link to metadata | RPMM0017 |
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DM0006. Covering chemical diversity of genetically-modified tomatoes using metabolomics for objective substantial equivalence assessment
| About | Metabolic profile data of miraculin over-expressing tomatoes grown on hydroponics (HC) and soil. |
| Please cite |
Covering chemical diversity of genetically-modified tomatoes using metabolomics for objective substantial equivalence assessment. Kusano M, Redestig H, Hirai T, Oikawa A, Matsuda F, Fukushima A, Arita M, Watanabe S, Yano M, Hiwasa-Tanas K, Ezura H & Saito K. PLoS ONE, 2011 |
| Link to metadata | RPMM0018 |
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DM0005. Metabolite accumulation in seeds of Arabidopsis transposon-tagged mutants and accessions
| About | Metabolic profiles in seeds of 2,656 Arabidopsis transposon-tagged mutants and 225 Arabidopsis accessions. Peak areas were measured by UPLC-ZQMS analysis for 36 metabolites and recorded with Tab Separated Variables format. |
| Please cite |
Toward genome-wide metabolotyping and elucidation of metabolic system: metabolic profiling of large-scale bioresources. Journal of Plant Research. (2010) 123, 291–298 |
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DM0004. AtMetExpress Development raw LC-ESI-TOF-MS dataset
| About | Total 288 raw LC-ESI-TOF-MS chromatogram data derived from 36 Arabidopsis tissues recorded with NetCDF format. These are part of the AtMetExpress metabolite accumulation atlas. Detailed information of each data files are described in the meta information (.txt) by following Metabolome Standard Initiative (MSI) recommendation. |
| Please cite |
AtMetExpress Development: A phytochemical Atlas of Arabidopsis Develpment Plant Physiol. (2010) in press. |
| Link to metadata | RPMM0052 |
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DM0003. Mixture Dilution Series for Pre-processing Validation
| About | Total of 27 chromatograms with replicates of three different standard mixtures. Provided for validation of the Bioconductor package TargetSearch |
| Please cite |
TargetSearch - a Bioconductor package for the efficient preprocessing of GC-MS metabolite profiling data. BMC Bioinformatics. (2009) 10:428 |
| Link to metadata | RPMM0025 |
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DM0002. Metabolic profile data of Arabidopsis four aerial tissues
| About | Total 32 raw LC-ESI-MS chromatogram data derived from four Arabidopsis tissues (flower, rosette leaf, cauline leaf, and internode, eight replicates) recorded with NetCDF and ASCII format. Detailed information of each data files are described in the meta information (.txt) by following Metabolome Standard Initiative (MSI) recommendation. For details, please refer LC-MS branch. |
| Please cite |
MS/MS spectral tag-based annotation of non-targeted profile of plant secondary metabolites. Plant J (2009) 57,555–577 |
| Link to metadata | RPMM0051 |
| Contents |
DM0001. Widely targeted metabolomics datasets ver 1.0
| About | We optimized multiple reaction monitoring (MRM) conditions to detect each of the 860 compounds (as of Mar 2009) by means of widely targeted metabolomics. All datasets useful to condition your measurement system are released here. ESI-MS/MS spectra are also available in ReSpect for Phytochemicals. A dataset of the metabolite accumulation patterns in 14 plants from Brassicaceae, Gramineae and Fabaceae is also released here. |
| Please cite |
Widely targeted metabolomics based on large-scale MS/MS data for elucidating metabolite accumulation patterns in plants. Plant Cell Physiol. (2009) 50, 37–47 [PubMed] |
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