Biology subjects

Kume, M.

Publications and source records attributed to Kume, M..

3 recordsLinked to original sources

bioRxiv2020

Evaluation of biodiversity in estuaries using environmental DNA metabarcoding

Biodiversity is an important parameter for the evaluation of the extant environmental conditions. Here, we used environmental DNA (eDNA) metabarcoding to investigate fish biodiversity in five different estuaries in Japan. Water samples for eDNA were collected from river mouths and adjacent coastal areas of two estuaries with high degrees of development (the Tama and Miya Rivers) and three estuaries with relatively low degrees of development (the Aka, Takatsu, and Sendai Rivers). A total of 182 fish species across 67 families were detected. Among them, 11 species occurred in all the rivers studied. Rare fishes including endangered species were successfully detected in rich natural rivers. Biodiversity was the highest in the Sendai River and lowest in the Tama River, reflecting the degree of human development along each river. Even though nutrient concentration was low in both the Aka and Sendai Rivers, the latter exhibited greater diversity, including many tropical or subtropical species, owing to its more southern location. Species composition detected by eDNA varied among rivers, reflecting the distribution and migration of fishes. Our results are in accordance with the ecology of each fish species and environmental conditions of each river, suggesting the potential of eDNA for non-invasive assessment of aquatic biodiversity.

ecology↗

bioRxiv2020

The cellular basis of protease activated receptor type 2 (PAR2) evoked mechanical and affective pain

Protease-activated receptor type-2 (PAR2) has long been implicated in inflammatory and visceral pain, but the cellular basis of PAR2-evoked pain has not been delineated. While many studies have attributed PAR2-evoked pain to sensory neuron expression, RNA-sequencing experiments are ambiguous on detection of F2rl1 mRNA. Moreover, many pharmacological tools for PAR2 have been shown to be non-specific as they also act on the Mas-related (Mrg) family of g-protein coupled receptors (GPCRs) that are highly enriched in sensory neurons. We sought to bring clarity to the cellular basis of PAR2 pain. We developed a PAR2 conditional mutant mouse by loxp targeting of exon 2 of the F2rl1 gene and specifically deleted PAR2 in all sensory neurons using the PirtCre mouse line. Our behavioral findings show that PAR2 agonist-evoked mechanical hyperalgesia and facial grimacing, but not thermal hyperalgesia, is completely dependent on PAR2 expression in sensory neurons that project to the hindpaw in male and female mice. F2rl1 mRNA is expressed in a discrete population (~4%) of sensory neurons that also express the Nppb and IL31ra genes. This cell population has previously been implicated in itch, but our work shows that PAR2 activation in these cells causes clear pain-related behaviors from the skin. Our findings clarify the mechanism through which proteases, like tryptase and elastase, cause pain via PAR2 activation in a small subset of nociceptors.

neuroscience↗

bioRxiv2019

A molecular logic of sensory coding revealed by optical tagging of physiologically-defined neuronal types

Neural circuit analysis relies on having molecular markers for specific cell types. However, for a cell type identified only by its circuit function, the process of identifying markers remains laborious. Here, we report physiological optical tagging sequencing (PhOTseq), a technique for tagging and expression-profiling cells based on their functional properties. We demonstrate that PhOTseq is capable of selecting rare cell types and enriching them by nearly one hundred-fold. We applied PhOTseq to the challenge of mapping receptor-ligand pairings among vomeronasal pheromone-sensing neurons in mice. Together with in vivo ectopic expression of vomeronasal chemoreceptors, PhOTseq identified the complete combinatorial receptor code for a specific set of ligands, and revealed that the primary sequence of a chemoreceptor was an unexpectedly strong predictor of functional similarity.

neuroscience↗