Literature DB >> 26819889

Application of Metabolomics for High Resolution Phenotype Analysis.

Eiichiro Fukusaki1.   

Abstract

Metabolome, a total profile of whole metabolites, is placed on downstream of proteome. Metabolome is thought to be results of implementation of genomic information. In other words, metabolome can be called as high resolution phenotype. The easiest operation of metabolomics is the integration to the upstream ome information including transcriptome and/or proteome. Those trials have been reported at a certain scientific level. In addition, metabolomics can be operated in stand-alone mode without any other ome information. Among metabolomics tactics, the author's group is particularly focusing on metabolic fingerprinting, in which metabolome information is employed as explanatory variant to evaluate response variant. Metabolic fingerprinting technique is expected not only for analyzing slight difference depending on genotype difference but also for expressing dynamic variation of living organisms. The author introduces several good examples which he performed. Those are useful for easy understanding of the power of metabolomics. In addition, the author mentions the latest technology for analysis of metabolic dynamism. The author's group developed a facile analytical method for semi-quantitative metabolic dynamism. The author introduces the novel method that uses time dependent variation of isotope distribution based on stable isotope dilution.

Keywords:  metabolic fingerprinting; metabolomics; multi variate analysis; quantitative phenotype

Year:  2015        PMID: 26819889      PMCID: PMC4541153          DOI: 10.5702/massspectrometry.S0045

Source DB:  PubMed          Journal:  Mass Spectrom (Tokyo)        ISSN: 2186-5116


  36 in total

1.  Metabolite profiling of soy sauce using gas chromatography with time-of-flight mass spectrometry and analysis of correlation with quantitative descriptive analysis.

Authors:  Shinya Yamamoto; Takeshi Bamba; Atsushi Sano; Yukako Kodama; Miho Imamura; Akio Obata; Eiichiro Fukusaki
Journal:  J Biosci Bioeng       Date:  2012-05-19       Impact factor: 2.894

2.  Metabolic profiling of Angelica acutiloba roots utilizing gas chromatography-time-of-flight-mass spectrometry for quality assessment based on cultivation area and cultivar via multivariate pattern recognition.

Authors:  Sukanda Tianniam; Lucksanaporn Tarachiwin; Takeshi Bamba; Akio Kobayashi; Eiichiro Fukusaki
Journal:  J Biosci Bioeng       Date:  2008-06       Impact factor: 2.894

3.  High-throughput technique for comprehensive analysis of Japanese green tea quality assessment using ultra-performance liquid chromatography with time-of-flight mass spectrometry (UPLC/TOF MS).

Authors:  Wipawee Pongsuwan; Takeshi Bamba; Kazuo Harada; Tsutomu Yonetani; Akio Kobayashi; Eiichiro Fukusaki
Journal:  J Agric Food Chem       Date:  2008-11-26       Impact factor: 5.279

4.  Different-batch metabolome analysis of Saccharomyces cerevisiae based on gas chromatography/mass spectrometry.

Authors:  Naoki Kawase; Hiroshi Tsugawa; Takeshi Bamba; Eiichiro Fukusaki
Journal:  J Biosci Bioeng       Date:  2013-08-19       Impact factor: 2.894

5.  Monitoring the ripening process of Cheddar cheese based on hydrophilic component profiling using gas chromatography-mass spectrometry.

Authors:  H Ochi; Y Sakai; H Koishihara; F Abe; T Bamba; E Fukusaki
Journal:  J Dairy Sci       Date:  2013-10-17       Impact factor: 4.034

6.  Non-targeted metabolite fingerprinting of oriental folk medicine Angelica acutiloba roots by ultra performance liquid chromatography time-of-flight mass spectrometry.

Authors:  Sukanda Tianniam; Takeshi Bamba; Eiichiro Fukusaki
Journal:  J Sep Sci       Date:  2009-07       Impact factor: 3.645

Review 7.  Current metabolomics: technological advances.

Authors:  Sastia P Putri; Shinya Yamamoto; Hiroshi Tsugawa; Eiichiro Fukusaki
Journal:  J Biosci Bioeng       Date:  2013-03-07       Impact factor: 2.894

8.  In vivo 15N-enrichment of metabolites in suspension cultured cells and its application to metabolomics.

Authors:  Kazuo Harada; Eiichiro Fukusaki; Takeshi Bamba; Fumihiko Sato; Akio Kobayashi
Journal:  Biotechnol Prog       Date:  2006 Jul-Aug

9.  GC/MS based metabolomics: development of a data mining system for metabolite identification by using soft independent modeling of class analogy (SIMCA).

Authors:  Hiroshi Tsugawa; Yuki Tsujimoto; Masanori Arita; Takeshi Bamba; Eiichiro Fukusaki
Journal:  BMC Bioinformatics       Date:  2011-05-04       Impact factor: 3.169

10.  Molar-based targeted metabolic profiling of cyanobacterial strains with potential for biological production.

Authors:  Yudai Dempo; Erika Ohta; Yasumune Nakayama; Takeshi Bamba; Eiichiro Fukusaki
Journal:  Metabolites       Date:  2014-06-20
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  6 in total

Review 1.  Metabolomics Signatures of Aging: Recent Advances.

Authors:  Sunil S Adav; Yulan Wang
Journal:  Aging Dis       Date:  2021-04-01       Impact factor: 6.745

2.  Integration of metabolomics and transcriptomics in nanotoxicity studies.

Authors:  Tae Hwan Shin; Da Yeon Lee; Hyeon-Seong Lee; Hyung Jin Park; Moon Suk Jin; Man-Jeong Paik; Balachandran Manavalan; Jung-Soon Mo; Gwang Lee
Journal:  BMB Rep       Date:  2018-01       Impact factor: 4.778

3.  Uncovering sperm metabolome to discover biomarkers for bull fertility.

Authors:  E B Menezes; A L C Velho; F Santos; T Dinh; A Kaya; E Topper; A A Moura; E Memili
Journal:  BMC Genomics       Date:  2019-09-18       Impact factor: 3.969

Review 4.  Metabolic Fingerprinting of Fabry Disease: Diagnostic and Prognostic Aspects.

Authors:  Maria Teresa Rocchetti; Federica Spadaccino; Valeria Catalano; Gianluigi Zaza; Giovanni Stallone; Daniela Fiocco; Giuseppe Stefano Netti; Elena Ranieri
Journal:  Metabolites       Date:  2022-07-28

Review 5.  Sperm Functional Genome Associated With Bull Fertility.

Authors:  Memmet Özbek; Mustafa Hitit; Abdullah Kaya; Frank Dean Jousan; Erdogan Memili
Journal:  Front Vet Sci       Date:  2021-06-22

Review 6.  Metabolome-based biomarkers: their potential role in the early detection of lung cancer.

Authors:  Karol Jelonek; Piotr Widłak
Journal:  Contemp Oncol (Pozn)       Date:  2018-09-30
  6 in total

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