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Rationale: From allergies to plant reproduction, pollens have important impacts on the health of human and plant populations, yet identification of pollen grains remains difficult and time-consuming. Low-volatility flavonoids generated from pollens cannot be easily characterized and quantified with current analytical techniques., Methods: Here we present the novel use of atmospheric solids analysis probe mass spectrometry (ASAP-MS) for the characterization of flavonoids in pollens. Flavonoid patterns were generated for pollens collected from different plant types (trees and bushes) in addition to bee pollens from distinct geographic regions. Standard flavonoids (kaempferol and rhamnazin) and those produced from pollens were compared and assessed with ASAP-MS using low-energy collision MS/MS. Results for a semi-quantitative method for assessing the amount of a flavonoid in pollens are also presented., Results: Flavonoid patterns for pollen samples were distinct with variability in the number and relative abundance of flavonoids in each sample. Pollens contained 2-5 flavonoids, and all but Kochia scoparia contained kaempferol or kaempferol isomers. We establish this method as a reliable and applicable technique for analyzing low-volatility compounds with minimal sample preparation. Standard curves were generated using 0.2-5 μg of kaempferol; from these experiments, it was estimated that there is approximately 2 mg of kaempferol present in 1 g of P. nigra italica pollen., Conclusions: Pollens can be characterized with a simple flavonoid pattern rather than analyzing the whole product pattern or the products-temperature profiles. ASAP-MS is a rapid analytical technique that can be used to distinguish between plant pollens and between bee pollens originating from different regions. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

We report a comprehensive multi-year study of thermophilic fungi at the Sevilleta National Wildlife Refuge in central New Mexico. Recovery of thermophilic fungi from soils showed seasonal fluctuations, with greater abundance correlating with spring and summer precipitation peaks. In addition to grassland soils, we obtained and characterized isolates from grassland and riparian litter, herbivore dung and biological soil crusts. All strains belonged to either the Eurotiales or Sordariales (Chaetomiaceae). No particular substrate or microhabitat associations were detected. Molecular typing of strains revealed substantial phylogenetic diversity, eight ad hoc phylogroups across the two orders were identified and genetic diversity was present within each phylogroup. Growth tests over a range of temperatures showed substantial variation in maximum growth rates among strains and across phylogroups but consistency within phylogroups. Results demonstrated that 45-50 C represents the optimal temperature for growth of most isolates, with a dramatic decline at 60 C. Most strains grew at 60 C, albeit slowly, whereas none grew at 65 C, providing empirical confirmation that 60 C presents an evolutionary threshold for fungal growth. Our results support the hypothesis that fungal thermophily is an adaptation to transient seasonal and diurnal high temperatures, rather than simply an adaptation to specialized high-temperature environments. We note that the diversity observed among strains and the frequently confused taxonomy within these groups highlight the need for comprehensive biosystematic revision of thermophilic taxa in both orders.

Algal biomass compositional analysis data form the basis of a large number of techno-economic process analysis models that are used to investigate and compare different processes in algal biofuels production. However, the analytical methods used to generate these data are far from standardized. This work investigated the applicability of common methods for rapid chemical analysis of biomass samples with respect to accuracy and precision. This study measured lipids, protein, carbohydrates, ash, and moisture of a single algal biomass sample at 3 institutions by 8 independent researchers over 12 separate workdays. Results show statistically significant differences in the results from a given analytical method among laboratories but not between analysts at individual laboratories, suggesting consistent training is a critical issue for empirical analytical methods. Significantly different results from multiple lipid and protein measurements were found to be due to different measurement chemistries. We identified a set of compositional analysis procedures that are in best agreement with data obtained by more advanced analytical procedures. The methods described here and used for the round robin experiment do not require specialized instrumentation, and with detailed analytical documentation, the differences between laboratories can be markedly reduced.