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Propidium monoazide (PMA) is a highly selective dye that penetrates only membrane-compromised, dead microbial cells and inhibits both DNA extraction and amplification. PMA has been widely used for discrimination between living and dead microbial cells; however, the application of PMA in phytoplankton studies has been limited. In this study, we attempted to evaluate its applicability for the discrimination of viable phytoplankton. We tested PMA on seven phytoplankton species, Microcystis aeruginosa, Anabaena sp., Aphanizomenon sp., Synechocystis sp., Cryptomonas ovata, Scenedesmus obliquus, and Nitzschia apiculata as representatives of the major phytoplankton taxa Cyanobacteria (first four species), Chlorophyta, Cryptophyta, and Bacillariophyta, respectively. Our results showed that application of PMA to phytoplankton living in freshwater has the potential to distinguish viable from dead cells as in microbial studies. Particularly, PMA differentiated viable from dead cells in cyanobacterial species rather than in other phytoplankton taxa under our experimental conditions. However, our results also showed that it may be necessary to adjust various conditions affecting PMA treatment efficiency to expand its applicability to other phytoplankton. Although all factors contributing to the effects of PMA could not be evaluated, our study showed the applicability of PMA-based molecular approaches, which can be convenient quantitative methods for distinguishing living from dead phytoplankton in freshwater ecosystems. Setting optimal treatment conditions for other phytoplankton species may increase the efficacy of PMA-based molecular approaches.

To efficiently investigate the forage preference of Svalbard reindeer (Rangifer tarandus platyrhynchus), we applied length-heterogeneity polymerase chain reaction (LH-PCR) based on length differences of internal transcribed spacer (ITS) regions of ribosomal RNA (rRNA) to fecal samples from R. tarandus platyrhynchus. A length-heterogeneity (LH) database was constructed using both collected potential food sources of Svalbard reindeer and fecal samples, followed by PCR, cloning and sequencing. In total, eighteen fecal samples were collected between 2011 and 2012 from 2 geographic regions and 15 samples were successfully amplified by PCR. The LH-PCR analysis detected abundant peaks, 18.6 peaks on an average per sample, ranging from 100 to 500 bp in size and showing distinct patterns associated with both regions and years of sample collection. Principal component analysis (PCA) resulted in clustering of 15 fecal samples into 3 groups by the year of collection and region with a statistically significant difference at 99.9% level. The first 2 principal components (PCs) explained 71.1% of the total variation among the samples. Through comparison with LH database and identification by cloning and sequencing, lichens (Stereocaulon sp. and Ochrolechia sp.) and plant species (Salix polaris and Saxifraga oppositifolia) were detected as the food sources that contributed most to the Svalbard reindeer diet. Our results suggest that the use of LH-PCR analysis would be a non-invasive and efficient monitoring tool for characterizing the foraging strategy of Svalbard reindeer. Additionally, combining sequence information would increase its resolving power in identification of foraged diet components.