Български
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Phytochemistry 2003-Mar

Construction and application of a mass spectral and retention time index database generated from plant GC/EI-TOF-MS metabolite profiles.

Само регистрирани потребители могат да превеждат статии
Вход / Регистрация
Линкът е запазен в клипборда
Cornelia Wagner
Michael Sefkow
Joachim Kopka

Ключови думи

Резюме

The non-supervised construction of a mass spectral and retention time index data base (MS/RI library) from a set of plant metabolic profiles covering major organs of potato (Solanum tuberosum), tobacco (Nicotiana tabaccum), and Arabidopsis thaliana, was demonstrated. Typically 300-500 mass spectral components with a signal to noise ratio > or =75 were obtained from GC/EI-time-of-flight (TOF)-MS metabolite profiles of methoxyaminated and trimethylsilylated extracts. Profiles from non-sample controls contained approximately 100 mass spectral components. A MS/RI library of 6205 mass spectral components was accumulated and applied to automated identification of the model compounds galactonic acid, a primary metabolite, and 3-caffeoylquinic acid, a secondary metabolite. Neither MS nor RI alone were sufficient for unequivocal identification of unknown mass spectral components. However library searches with single bait mass spectra of the respective reference substance allowed clear identification by mass spectral match and RI window. Moreover, the hit lists of mass spectral searches were demonstrated to comprise candidate components of highly similar chemical nature. The search for the model compound galactonic acid allowed identification of gluconic and gulonic acid among the top scoring mass spectral components. Equally successful was the exemplary search for 3-caffeoylquinic acid, which led to the identification of quinic acid and of the positional isomers, 4-caffeoylquinic acid, 5-caffeoylquinic acid among other still non-identified conjugates of caffeic and quinic acid. All identifications were verified by co-analysis of reference substances. Finally we applied hierarchical clustering to a complete set of pair-wise mass spectral comparisons of unknown components and reference substances with known chemical structure. We demonstrated that the resulting clustering tree depicted the chemical nature of the reference substances and that most of the nearest neighbours represented either identical components, as judged by co-elution, or conformational isomers exhibiting differential retention behaviour. Unknown components could be classified automatically by grouping with the respective branches and sub-branches of the clustering tree.

Присъединете се към нашата
страница във facebook

Най-пълната база данни за лечебни билки, подкрепена от науката

  • Работи на 55 езика
  • Билкови лекове, подкрепени от науката
  • Разпознаване на билки по изображение
  • Интерактивна GPS карта - маркирайте билките на място (очаквайте скоро)
  • Прочетете научни публикации, свързани с вашето търсене
  • Търсете лечебни билки по техните ефекти
  • Организирайте вашите интереси и бъдете в крак с научните статии, клиничните изследвания и патентите

Въведете симптом или болест и прочетете за билките, които биха могли да помогнат, напишете билка и вижте болестите и симптомите, срещу които се използва.
* Цялата информация се базира на публикувани научни изследвания

Google Play badgeApp Store badge