Application of a robust MALDI mass spectrometry approach for bee pollen investigation

Pollen collected by pollinators can be used as a marker of the foraging behavior as well as indicate the botanical species present in each environment. Pollen intake is essential for pollinators’ health and survival. During the foraging activity, some pollinators, such as honeybees, manipulate the collected pollen mixing it with salivary secretions and nectar (corbicular pollen) changing the pollen chemical profile. Different tools have been developed for the identification of the botanical origin of pollen, based on microscopy, spectrometry, or molecular markers. However, up to date, corbicular pollen has never been investigated. In our work, corbicular pollen from 5 regions with different climate conditions was collected during spring. Pollens were identified with microscopy-based techniques, and then analyzed in MALDI-MS. Four different chemical extraction solutions and two physical disruption methods were tested to achieve a MALDI-MS effective protocol. The best performance was obtained using a sonication disruption method after extraction with acetic acid or trifluoroacetic acid. Therefore, we propose a new rapid and reliable methodology for the identification of the botanical origin of the corbicular pollens using MALDI-MS. This new approach opens to a wide range of environmental studies spanning from plant biodiversity to ecosystem trophic interactions. Graphical Abstract Supplementary Information The online version contains supplementary material available at 10.1007/s00216-024-05368-9.


Supplementary results on the pollen extraction methods
Our experiment included bee pollen grains from five different Italian regions.In order to define the best experimental conditions to record robust and the most representative and distinguishable spectra for a pollen species, different conditions of extraction were tested, four different solutions: (1) 2M acetic acid 2M (2M AA) and 50% acetonitrile (50% ACN); (2) AA 2M; (3) 2% ACN and 0.1% trifluoroacetic acid (0.1% TFA); and (4) a solution of 1% TFA) and two mechanical extraction methods (stirring and ultrasonication).Moreover, 10-fold serial dilutions of the crude extracted material from the different bee pollen balls were evaluated (10, 100 and 1,000 times) to respect the most appropriate sample to matrix ratio.The 10-fold dilution was only efficient after sonication despite low peaks intensity, while the 1000fold dilution did not provide readable spectra, as well as direct positioned grains on steel plate and extracted with formic acid.Excluding the two best extraction methods results, the only other method that produced satisfying results was the 100-fold dilution after mechanical agitation (1h, 4°C) in 1% TFA, with 195 ions at m/z recorded at a significant relative intensity (Fig. S1g).Spectra were cut between range m/z 600-7000 to highlight peaks of interest.Dilution 1:1000 did not provide useful spectra and were not reported in the figure.a) spectra of pollen extracted in AA 2M/ ACN 50% and stirred (1h, 4°C).b) spectra of pollen extracted in AA 2M/ ACN 50% and sonicated.c) spectra of pollen extracted in AA 2M and stirred (1h, 4°C).d) spectra of pollen extracted in AA 2M and sonicated; e) spectra of pollen extracted in ACN 2%/ TFA 0.1% and stirred (1h, 4°C).f) spectra of pollen extracted in ACN 2%/ TFA 0.1% and sonicated.g) spectra of pollen extracted in TFA 1% and stirred (1h, 4°C).h) spectra of pollen extracted in TFA 1% and sonicated.[a.u.] stand for arbitrary unit

Code Grains morphology Botanical classification Code Grains morphology Botanical classification P11
Cistus incanus Table S3.

Fig. S1
Fig. S1 Mass spectra obtained from the different extraction conditions and according to the dilution factor of the crude extracts.Spectra were cut between range m/z 600-7000 to highlight peaks of interest.Dilution 1:1000 did not provide useful spectra and were not reported in the figure.a) spectra of pollen extracted in AA 2M/ ACN 50% and stirred (1h, 4°C).b) spectra of pollen extracted in AA 2M/ ACN 50% and sonicated.c) spectra of pollen extracted in AA 2M and stirred (1h, 4°C).d) spectra of pollen extracted in AA 2M and sonicated; e) spectra of pollen extracted in ACN 2%/ TFA 0.1% and stirred (1h, 4°C).f) spectra of pollen extracted in ACN 2%/ TFA 0.1% and sonicated.g) spectra of pollen extracted in TFA 1% and stirred (1h, 4°C).h) spectra of pollen extracted in TFA 1% and sonicated.[a.u.] stand for arbitrary unit

Fig. S2
Fig. S2 (a) Comparison between Quercus sp.(Fagaceae) and (b) between Rubus sp.bee pollen balls from different Italian region origin (flexAnalysis tool visualization).Visualization of the comparisons were done using the ClinProTools was used.[arb.u.] and [a.u.] stand for arbitrary unit

Figure S1 .
Figure S1.In blue, peaks considered for the PCA analysis and SNN Algorithm.In red, automatically assigned peaks from SNN Algorithm used for model generation.

Table S2 .
Botanical classification for each pollen tested in each different experiment.

value Appendix 1: Specifications for the genetic algorithm ClinProt Model Model Generation Classes Cross Validation Recognition Capability
Table shows mass average intensity, standard deviation ad p-value for each considered peak.Averages in bold indicate the Class where the intensity is higher.