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Paddy ecosystems are among the most biodiversity-rich ecosystems, but they can be degraded by field consolidation or the abandonment of rice cultivation. Snakes are the top predators in paddy ecosystems; therefore, understanding the distribution of snakes is important for the conservation of paddy biodiversity. Traditionally, surveys of snakes have been primarily conducted by sighting and trapping, but such methods require encountering snakes during surveys and require expertise in species identification. In this study, we developed environmental DNA (eDNA) detection assays for snakes as a method for surveying a wide area relatively easily. We designed species-specific assays for three common snake species in Japanese paddy ecosystems: Elaphe quadrivirgata, Rhabdophis tigrinus, and Gloydius blomhoffii. After confirming the detection of target species DNA from the rearing environment, the assays were applied to field samples. Eighty-seven and 51 samples were collected from paddy fields, reservoirs, and ditches in summer and autumn, respectively. We collected eDNA samples from eight traditional paddy areas that had not been consolidated, eight consolidated paddy areas, and two abandoned paddy areas in southeastern Hyogo Prefecture, Japan. We attempted to detect the DNA of the three target species in these samples using our eDNA assays and succeeded in identifying the DNA of R. tigrinus and G. blomhoffii in three areas and one area, respectively. Statistical analysis suggested that land-use type affected the detection of R. tigrinus eDNA. This study is the first attempt to survey snakes in paddy ecosystems using eDNA analysis and will contribute to the development of paddy ecosystem monitoring.

The combination of high-throughput sequencing technology and environmental DNA (eDNA) analysis has the potential to be a powerful tool for comprehensive, non-invasive monitoring of species in the environment. To understand the correlation between the abundance of eDNA and that of species in natural environments, we have to obtain quantitative eDNA data, usually via individual assays for each species. The recently developed quantitative sequencing (qSeq) technique enables simultaneous phylogenetic identification and quantification of individual species by counting random tags added to the 5′ end of the target sequence during the first DNA synthesis. Here, we applied qSeq to eDNA analysis to test its effectiveness in biodiversity monitoring. eDNA was extracted from water samples taken over 4 days from aquaria containing five fish species (Hemigrammocypris neglectus, Candidia temminckii, Oryzias latipes, Rhinogobius flumineus, and Misgurnus anguillicaudatus), and quantified by qSeq and microfluidic digital PCR (dPCR) using a TaqMan probe. The eDNA abundance quantified by qSeq was consistent with that quantified by dPCR for each fish species at each sampling time. The correlation coefficients between qSeq and dPCR were 0.643, 0.859, and 0.786 for H. neglectus, O. latipes, and M. anguillicaudatus, respectively, indicating that qSeq accurately quantifies fish eDNA.

The global outbreak of the SARS-CoV-2 pandemic has increased the focus of Wastewater-based epidemiology (WBE) studies as a tool for understanding the epidemic and risk management. A highly sensitive and rapid method for the virus concentration from wastewater is needed to obtain the accurate information for early detection of SARS-CoV-2 outbreak and epidemic. In this study, we evaluated the efficiency of the direct capture method provided from Promega, based on column adsorption using the wastewater from actual infectious diseases ward. The efficiency of the nucleic acid extraction-purification process was also evaluated by Maxwell® RSC instrument (fully automated extraction) and QIAamp Viral RNA mini kit (manual extraction). The obtained SARS-CoV-2 data from wastewater were analyzed with the number of inpatients which is the consideration of the severity and the days of onset. The combination of direct capture and Maxwell’s method (DC-MW) was suggested to be a highly sensitive and simple method with better concentration efficiency and quantification than other methods. Moreover, the inpatient conditions (severity and days of after onset) should be considered to accurately understand the actual status of the correlation between the number of inpatients and SARS-CoV-2 concentration in wastewater. The highly sensitive method of DC-MW was suggested to assess more actual situation of SARS-CoV-2 shedding into the wastewater.

Palaemon paucidens has a large population and is an important food source for fish in Lake Biwa, Japan. They are abundant in shallow waters from spring to summer, after which most individuals migrate to offshore deep areas where they remain during autumn and winter. However, some individuals are nonmigratory, remaining in shallow waters over winter. It has been reported that P. paucidens individuals have declined in recent years; a better understanding of its seasonal distribution is needed to manage this species, and basic information on its seasonal distribution is indispensable. We tracked the environmental DNA (eDNA) distribution of P. paucidens in Lake Biwa over a year using a quantitative real‐time polymerase chain reaction method. We collected water samples from offshore (both from the surface and from the benthic) and from shallow shore sites adjacent to the shorelines of the main lake and connecting freshwater lagoons. Offshore sampling took place in summer and winter, and shallow shore and lagoon sampling in all four seasons. During summer, eDNA concentrations were significantly higher in shallow and lagoon areas than offshore bottom sites. Conversely, during winter, eDNA concentrations were higher in offshore bottom sites, and relatively high and low eDNA concentrations in lagoons and shallow shore, respectively. These results most likely reflect the spatial and temporal distribution of this species in Lake Biwa. The eDNA concentrations peaked in early August at shallow shore sites in the main lake, with a significant decline in mid‐October, while low eDNA concentrations were recorded at offshore bottom sites in late August. These results suggest that P. paucidens migrates from shallow waters to offshore bottom sites between early August and mid‐October. These results provide important information for the management of this species.

The Ayu Plecoglossus altivelis altivelis is an amphidromous fish that is not only the most important commercial fishery species in Japanese rivers but also has a high economic value in recreational fishing. However, the degradation of its spawning grounds has caused a decrease in its abundance. In this study, we used environmental DNA (eDNA) to monitor the Ayu in the Takatsu River in Japan to (1) identify the spawning season in three known spawning grounds, (2) clarify changes in the main spawning grounds during the spawning season, and (3) discover unknown spawning grounds. We collected 1 L of the surface river water at three known spawning grounds nine times in 2018 and seven times in 2019 in the lower reaches of the Takatsu River. We also collected samples from seven unknown sites in 2018. The water samples were filtered through glass fiber filters. Total eDNA was extracted from each filtered sample and a Real-time quantitative PCR was performed with the specific primers and probe for Ayu. The results of the eDNA analyses showed that (1) the spawning season was in November in 2018 and in September in 2019. (2) One site was used as a spawning ground in both the early and the late spawning season, depending on the year. At the second site, the frequency of use changed year by year. The third site was the main spawning ground in the middle to late spawning season every year. From these results, we elucidated that some spawning grounds are used regularly every year, while the use of others varies year by year. (3) In five of the seven unknown sites, the nighttime eDNA concentrations were high at least once during the four surveys, suggesting that these sites may have functioned as spawning grounds. In particular, one site could be an important new spawning ground.

Environmental DNA (eDNA) analysis is a method of detecting DNA from environmental samples and is used as a biomonitoring tool. In recent studies, Illumina MiSeq has been the most extensively used tool for eDNA metabarcoding. The Illumina iSeq 100 (hereafter, iSeq), one of the high-throughput sequencers (HTS), has a relatively simple workflow and is potentially more affordable than other HTS. However, its utility in eDNA metabarcoding has still not been investigated. In the present study, we applied fish eDNA metabarcoding to 40 water samples from river and lake ecosystems to assess the difference in species detectability and composition between iSeq and MiSeq. To check differences in sequence quality and errors, we also assessed differences in read changes between the two HTS. There were similar sequence qualities between iSeq and MiSeq. Significant difference was observed in the number of species between two HTS, but no difference was observed in species composition between the two HTS. Additionally, the species compositions in common with the conventional method were the same between the two HTS. According to the results, using the same amplicon library for sequencing, two HTS would exhibit a similar performance of fish species detection using eDNA metabarcoding.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

In order to maximize the performance of lithium ion batteries, we have developed a new method for detecting the status of hybrid electric vehicle (HEV) batteries. The method obtains an accurate state of charge (SOC) by combining the SOC based on open circuit voltage (OCV) and the SOC based on current integration. In addition to that, our method has an auto-tuning function, which is realized by relatively simple processing, for the characteristic parameter of batteries. Our method can also obtain the state of health (SOH) by watching the tuned characteristic parameter. We perform simulation evaluations of our method with a battery model, and we confirm that the SOC error is less than 5% even if SOH set in the battery model and in our method are under mismatched condition. We also confirm that the SOH gradually converges to the true value and SOC error is improved by performing simulation evaluation repeatedly.