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1. Fourier transform infrared (FTIR) spectroscopy enables chemical analysis of pollen samples for plant phenotyping to study plant–environment interactions, such as influence of climate change or pathogens.However, current approach, such as microspectroscopy and attenuated total reflection spectroscopy, does not allow for highthroughput protocols. This study at hand suggests a new spectroscopic method for high-throughput characterization of pollen.
2. Samples were measured as thin films of pollen fragments using a Bruker FTIR spectrometer with a highthroughput eXTension (HTS-XT) unit employing 384-well plates. In total, 146 pollen samples, belonging to 31 different pollen species of Fagaceae and Betulaceae and collected during three consecutive years (2012–2014) at locations in Croatia, Germany and Norway, were analysed. Critical steps in the sample preparation and measurement, such as variabilities between technical replicates, between microplates and between spectrometers, were studied.
3. Measurement variations due to sample preparation, microplate holders and instrumentation were low, and thus allowed differentiation of samples with respect to phylogeny and biogeography. The spectral variability for a range of Fagales species (Fagus, Quercus, Betula, Corylus, Alnus and Ostrya) showed high-species-specific differences in pollen’s chemical composition due to either location or year. Statistically significant inter-annual and locational differences in the pollen spectra indicate that pollen chemical composition has high phenotypic plasticity and is influenced by local climate conditions. The variations in composition are connected to lipids, proteins, carbohydrates and sporopollenins that play crucial roles in cold and desiccation tolerance, protection against UVradiation and asmaterial and energy reserves.
4. The results of this study demonstrate the value of high-throughput FTIR approach for the systematic collection of data on ecosystems. The novel FTIR approach offers fast, reliable and economical screening of large number of samples by semi-automated methodology. The high-throughput approach could provide crucial understanding on plant–climate interactions with respect to biochemical variation within genera, species and populations.
1. Fourier transform infrar ed (FTIR) spectroscopy enables chemical analysis of pollen samples for plant phenotyping to stud y plant–environment interactions, such as influence of climate change or pathogens. However, current approach, such as microspectrosc opy and attenuated total refle ction spectrosco py, doe s not allow fo r high-throughput protocols. This st udy at hand suggests a new sp ectroscopic method for high-throughp ut characterization of pollen.
2. Samples were measured as thin films of pollen fragments using a Bruker FTIR spe ctrometer with a high-throughput eXTension (HTS-XT) unit employing 384-well plates. In total, 146 pollen samples, belonging to 31 different pollen species of Fagaceae and Betulaceae and collected during three consecutive years (2012–2014) at locations in Croatia, Germany and Norway, were analysed. Critical steps in the sample preparation and measurement, such as variabilities between technical replicates, between microplates and between spectrometers, were studied.
3. Measurement variations due to sample preparation, microplate holders and instrumentation were low, and thus allowed differentiation of samples with respect to phylogeny and biogeography. The spectral variability for a ran ge of Fagales spec ies (Fagus, Quercus, Betula, Corylus, Alnus and Ostrya) showed high-species-specific differences in pollen’s chemical composition due to eithe r location or year. Statistically significant inter-annual and locational differences in the pollen spectra indicate that pollen chemical composition has high phenotypic plasticity and is influenced by local climate conditions. The variations in composition are connected to lipids, proteins, carbohydrates and sporopollenins that play crucial ro les in cold and desiccation tolerance, protection against UV radiation and as material and energy reserves.
4. The results of this study demonstrate the value of high-throughput FTIR approach for the systematic collection of data on ecosystems. The novel FTIR approach offers fast, reliable and economical screening of large number of samples by semi-automated methodology. The high-throughput approach could provide crucial understanding on plant–climate interactions with respect to biochemical variation within genera, species and populations.
The analysis of pollen chemical composition is important to many fields, including agriculture, plant physiology, ecology, allergology, and climate studies. Here, the potential of a combination of different spectroscopic and spectrometric methods regarding the characterization of small biochemical differences between pollen samples was evaluated using multivariate statistical approaches. Pollen samples, collected from three populations of the grass Poa alpina, were analyzed using Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, surface enhanced Raman scattering (SERS), and matrix assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS). The variation in the sample set can be described in a hierarchical framework comprising three populations of the same grass species and four different growth conditions of the parent plants for each of the populations. Therefore, the data set can work here as a model system to evaluate the classification and characterization ability of the different spectroscopic and spectrometric methods. ANOVA Simultaneous Component Analysis (ASCA) was applied to achieve a separation of different sources of variance in the complex sample set. Since the chosen methods and sample preparations probe different parts and/or molecular constituents of the pollen grains, complementary information about the chemical composition of the pollen can be obtained. By using consensus principal component analysis (CPCA), data from the different methods are linked together. This enables an investigation of the underlying global information, since complementary chemical data are combined. The molecular information from four spectroscopies was combined with phenotypical information gathered from the parent plants, thereby helping to potentially link pollen chemistry to other biotic and abiotic parameters.
MALDI time-of-flight mass spectrometry (MALDI-TOF MS) has become a widely used tool for the classification of biological samples. The complex chemical composition of pollen grains leads to highly specific, fingerprint-like mass spectra, with respect to the pollen species. Beyond the species-specific composition, the variances in pollen chemistry can be hierarchically structured, including the level of different populations, of environmental conditions or different genotypes. We demonstrate here the sensitivity of MALDI-TOF MS regarding the adaption of the chemical composition of three Poaceae (grass) pollen for different populations of parent plants by analyzing the mass spectra with partial least squares discriminant analysis (PLS-DA) and principal component analysis (PCA). Thereby, variances in species, population and specific growth conditions of the plants were observed simultaneously. In particular, the chemical pattern revealed by the MALDI spectra enabled discrimination of the different populations of one species. Specifically, the role of environmental changes and their effect on the pollen chemistry of three different grass species is discussed. Analysis of the Group formation within the respective populations showed a varying influence of plant genotype on the classification, depending on the species, and permits conclusions regarding the respective rigidity or plasticity towards environmental changes.
The chemical characterization and discrimination of allergy-relevant pollen (common ragweed (Ambrosia artemisiifolia), white birch (Betula pendula), English oak (Quercus robur), and European linden (Tilia cordata)) has been studied by Raman microscopy. Spectra were obtained at different excitation wavelengths (514, 633, and 780 nm) and various methods were examined to minimize the strong fluorescence background. The use of a HeNe laser (633 nm) for excitation yields high-quality single pollen Raman spectra, which contain multiple bands due to pollen components such as carotenoids, proteins, nucleic acids, carbohydrates, and lipids. Multivariate classification, i.e. principal component analysis (PCA) and hierarchical cluster analysis, demonstrated the validity of the approach for discrimination between different pollen species.
RATIONALE
A fast and reliable online identification of pollen is not yet available. The identification of pollen is based mainly on the evaluation of morphological data obtained by microscopic methods.
METHODS
Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS) was applied to the analysis of extracts and milled pollen samples. The obtained MALDI data were explored for characteristic peak patterns which could be subjected to a multivariate statistical analysis.
RESULTS
Two sample preparation methods are presented, which require only minimal or no chemical extraction of the pollen. MALDI pollen spectra could be recorded showing various peak patterns. A multivariate statistics approach allowed the classification of pollen into clusters indicating similarities and differences between various species.
CONCLUSIONS
These results demonstrate the potential and the reliability of MALDI-TOF MS for the identification and, in combination with multivariate statistics, also for the classification of pollen.
Matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) is a well-implemented analytical technique for the investigation of complex biological samples. In MS, the sample preparation strategy is decisive for the success of the measurements. Here, sample preparation processes and target materials for the investigation of different pollen grains are compared. A reduced and optimized sample preparation process prior to MALDI-TOF measurement is presented using conductive carbon tape as target. The application of conductive tape yields in enhanced absolute signal intensities and mass spectral pattern information, which leads to a clear separation in subsequent pattern analysis. The results will be used to improve the taxonomic differentiation and identification, and might be useful for the development of a simple routine method to identify pollen based on mass spectrometry.
Matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) is a well-implemented analytical technique for the investigation of complex biological samples. In MS, the sample preparation strategy is decisive for the success of the measurements. Here, sample preparation processes and target materials for the investigation of different pollen grains are compared. A reduced and optimized sample preparation process prior to MALDI-TOF measurement is presented using conductive carbon tape as target. The application of conductive tape yields in enhanced absolute signal intensities and mass spectral pattern information, which leads to a clear separation in subsequent pattern analysis. The results will be used to improve the taxonomic differentiation and identification, and might be useful for the development of a simple routine method to identify pollen based on mass spectrometry.
The allergenic potential of airborne proteins may be enhanced via post-translational modification induced by air pollutants like ozone (O3) and nitrogen dioxide (NO2). The molecular mechanisms and kinetics of the chemical modifications that enhance the allergenicity of proteins, however, are still not fully understood. Here, protein tyrosine nitration and oligomerization upon simultaneous exposure of O3 and NO2 were studied in coated-wall flow-tube and bulk solution experiments under varying atmospherically relevant conditions (5–200 ppb O3, 5–200 ppb NO2, 45–96% RH), using bovine serum albumin as a model protein. Generally, more tyrosine residues were found to react via the nitration pathway than via the oligomerization pathway. Depending on reaction conditions, oligomer mass fractions and nitration degrees were in the ranges of 2.5–25% and 0.5–7%, respectively. The experimental results were well reproduced by the kinetic multilayer model of aerosol surface and bulk chemistry (KM-SUB). The extent of nitration and oligomerization strongly depends on relative humidity (RH) due to moisture-induced phase transition of proteins, highlighting the importance of cloud processing conditions for accelerated protein chemistry. Dimeric and nitrated species were major products in the liquid phase, while protein oligomerization was observed to a greater extent for the solid and semi-solid phase states of proteins. Our results show that the rate of both processes was sensitive towards ambient ozone concentration but rather insensitive towards different NO2 levels. An increase of tropospheric ozone concentrations in the Anthropocene may thus promote pro-allergic protein modifications and contribute to the observed increase of allergies over the past decades.
Aqueous pollen extracts of varying taxonomic relations were analyzed with surface enhanced Raman scattering (SERS) by using gold nanoparticles in aqueous suspensions as SERS substrate. This enables a selective vibrational characterization of the pollen water soluble fraction (mostly cellular components) devoid of the spectral contributions from the insoluble sporopollenin outer layer. The spectra of the pollen extracts are species-specific, and the chemical fingerprints can be exploited to achieve a classification that can distinguish between different species of the same genus. In the simple experimental procedure, several thousands of spectra per species are generated. Using an artificial neural network (ANN), it is demonstrated that analysis of the intrinsic biochemical information of the pollen cells in the SERS data enables the identification of pollen from different plant species at high accuracy. The ANN extracts the taxonomically-relevant information from the data in spite of high intra-species spectral variation caused by signal fluctuations and preparation specifics. The results show that SERS can be used for the reliable characterization and identification of pollen samples. They have implications for improved investigation of pollen physiology and for allergy warning.