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A variety of new analytical approaches have been proposed in order to develop fast and reliable pollen identification using specific molecular information. The combination of the obtained patterns of pollen mass spectra (MADLI-TOF MS (Autoflex III, Bruker)) and multivariate statistics provide a powerful tool for the investigation of structural correlations within pollen grain mixtures.
Both commercially available lyophilized pollen (Sigma, Germany) and fresh pollen acquired from biological samples collected in parks and in the Botanic Garden Berlin-Dahlem, were utilized. The samples were extracted based on a modified biotyper protocol (Bruker) by formic acid extraction in the gas phase and spotted with HCCA matrix. This presentation show results from the newly developed MALDI target setup, with conductive tape. The spectral data were investigated by principal component analysis (PCA).
The common characterization and identification of pollen is a time-consuming task that mainly relies on microscopic determination of the genus-specific pollen morphology. A variety of spectroscopic and spectrometric approaches have been proposed to develop a fast and reliable pollen identification using specific molecular information. Amongst them, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) shows a high potential for the successful investigation of such complex biological samples. Based on optimized MALDI sample preparation using conductive carbon tape, the application of multivariate statistics (e.g. principal components analysis, PCA) yields an enormous improvement concerning taxonomic classification of pollen species compared to common microscopic techniques.
Since multivariate evaluation of the recorded mass spectra is of vital importance for classification, it’s helpful to implement the applied sequence of standard Matlab functions into a graphical user interface (GUI). In this presentation, a stand-alone application (GUI) is shown, which provides multiple functions to perform fast multivariate analysis on multiple datasets. The use of a GUI enables a first overview on the measured dataset, conducts spectral pretreatment and can give classification information based on HCA and PCA evaluation. Moreover, it can be used to improve fast spectral classification and supports the development of a simple routine method to identify pollen based on mass spectrometry.
Anemophilous plants produce pollen grains, which have to be monitored to provide an information network for persons suffering from an allergy. The current conventional characterization and identification of pollen is performed by time-consuming microscopic examinations on the basis of the genus-specific pollen shape and size. These examinations are in need of proficient researchers, are not statistically validated, and additionally rely on relatively inaccurate observations of the pollination process. A variety of new analytical approaches have been proposed in order to develop a fast and reliable pollen identification using specific molecular information. Recently, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was initially applied for the rapid investigation of such complex biological samples. The combination of the obtained patterns of pollen mass spectra and multivariate statistics provide a powerful tool for identifying taxonomic relationships. Here promising results obtained by the reduction and optimization of sample preparation prior to MALDI-TOF MS mapping are presented. Based on a novel application of conductive carbon tape as target, the signal information of the species-specific mass peak patterns of pollen was enhanced. This leads to a clear separation in a subsequent pattern analysis, which is important when analyzing pollen grains in natural species mixtures. As a proof-of-concept, artificial pollen mixtures were investigated by MALDI imaging and evaluated by innovative multivariate data analysis strategies, to assign individual pollen species in the mixtures. Our results can be used to improve the taxonomic differentiation and identification of pollen species and might be useful for the development of a routine method to identify pollen based on mass spectrometry.
About one in seven German citizens is suffering from respiratory allergies, which are mainly caused by anemophilous plant pollen. These pollen grains are monitored to provide a national information network. Their conventional identification is performed by time-consuming microscopic examinations based on the genus-specific pollen morphology. A variety of spectroscopic and spectrometric approaches have been proposed to develop a fast and reliable pollen identification using specific molecular information. Amongst them, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) showed a high potential for the successful investigation of such complex biological samples. The evaluation of the obtained peak patterns from pollen mass spectra with multivariate statistics enables a consistent and rapid identification of the taxonomic relationships.