Phytochemical Markers Of Different Types Of Red Propolis.

Propolis is a resin that bees collect from different plant sources and use in the defense of the bee community. The intricate composition of propolis varies depending on plant sources from different geographic regions and many types have been reported. Red coloured propolis found in several states in Brazil and in other countries has known antimicrobial and antioxidant activity. Different analytical methods have been applied to studies regarding the chemical composition and plant origins of red propolis. In this study samples of red propolis from different regions have been characterised using direct infusion electrospray ionisation mass spectrometry (ESI(-)-MS) fingerprinting. Data from the fingerprints was extracted and analysed by multivariate analysis to group the samples according to their composition and marker compounds. Despite similar colour, the red coloured propolis samples were divided into three groups due to contrasting chemical composition, confirming the need to properly characterise the chemical composition of propolis.

A Metabolomic Protocol For Plant Systematics By Matrix-assisted Laser-desorption/ionization Time-of Flight Mass Spectrometry.

Matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF MS) has been widely used for the identification and classification of microorganisms based on their proteomic fingerprints. However, the use of MALDI-TOF MS in plant research has been very limited. In the present study, a first protocol is proposed for metabolic fingerprinting by MALDI-TOF MS using three different MALDI matrices with subsequent multivariate data analysis by in-house algorithms implemented in the R environment for the taxonomic classification of plants from different genera, families and orders. By merging the data acquired with different matrices, different ionization modes and using careful algorithms and parameter selection, we demonstrate that a close taxonomic classification can be achieved based on plant metabolic fingerprints, with 92% similarity to the taxonomic classifications found in literature. The present work therefore highlights the great potential of applying MALDI-TOF MS for the taxonomic classification of plants and, furthermore, provides a preliminary foundation for future research.