Biology subjects

Tsuji, S.

Publications and source records attributed to Tsuji, S..

26 records · Page 2Linked to original sources

bioRxiv2022

Differences in the genetic structure between and within two landlocked Ayu groups with different migration patterns in Lake Biwa revealed by environmental DNA analysis

Ayu, Plecoglossus altivelis, is largely an annual amphidromous fish, although a landlocked population lives in Lake Biwa, the largest lake in Japan. The landlocked population comprises two migrant groups, spring migrants and autumn migrants, which run to inlet rivers from the lake at different seasons. We used environmental DNA (eDNA) analysis, which is reported to be more sensitive and cost-effective than capture surveys, to clarify the genetic structure of this landlocked Ayu population with different migration patterns in Lake Biwa. We took water samples in 11 inlet rivers in the spring and autumn for two years in a row and quantitatively detected a total of 265 haplotypes of the mitochondrial D-loop region. The pairwise fixation index (FST) value and haplotype diversity indicated that there were genetic differences between the two migrant groups in their respective rivers, and the FST values were negatively related to latitude and the presence of artificial fish release. Additionally, the isolation by distance within each migrant group was observed when the lake was divided into the east and west sides. These findings show that the landlocked Ayu population in Lake Biwa has the genetic structure associated with migration patterns and geographical distance. This study demonstrates that the eDNA approach will be effective for conducting a large-scale investigation of genetic structure beyond simple presence/absence tests.

ecology↗

bioRxiv2022

Analysis of the persistence and particle size distributional shift of sperm-derived environmental DNA to monitor Jack Mackerel spawning activity

Environmental DNA (eDNA) analysis holds great promises as an efficient and noninvasive method to monitor not only the presence and biomass of organisms but also their spawning activity. In eDNA analysis-based monitoring of spawning activity, the detection of sperm-derived eDNA is a key point; however, its characteristics and dynamics are completely unknown. The present study focuses on the persistence and particle size distribution (PSD) of eDNA derived from the sperm of Japanese jack mackerel. First, we investigated the time-dependent degradation and the PSD of sperm-derived eDNA by artificially adding sperm to fish eDNA-free seawater. Next, we kept fish in tanks and examined the changes in DNA concentration and PSD before and after spawning. The data obtained from the two experiments showed that the degradation of sperm-derived eDNA proceeded rapidly, with PSD shifting to a smaller size, regardless of the DNA region (Cyt b or ITS1). Additionally, it was shown that the nuclei and mitochondria released from sperm through degradation had a size distribution that was not simply dependent on each organelle size. The results of this study will contribute to elucidating the characteristics and dynamics of eDNA specifically during the spawning season and to further developing eDNA analysis as a powerful tool for the monitoring of spawning activity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/483695v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@15a91e8org.highwire.dtl.DTLVardef@1212566org.highwire.dtl.DTLVardef@11e5e95org.highwire.dtl.DTLVardef@d39a36_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2021

Aerobic glycolysis in cancer cells supplies ATP while preventing excess metabolic thermogenesis

Adenosine triphosphate (ATP) regeneration by substrate-level phosphorylation is a general feature of cancer metabolism, even under normoxic conditions (aerobic glycolysis). However, it is unclear why cancer cells prefer inefficient aerobic glycolysis over the highly efficient process of oxidative phosphorylation for ATP regeneration. To investigate the metabolic principles underlying aerobic glycolysis, we performed 13C-metabolic flux analysis of 12 cultured cancer cell lines and explored the metabolic constraints required to reproduce the results using in silico metabolic simulations. We found that the measured flux distribution can be reproduced by maximizing the ATP consumption in the flux balance analysis considering a limitation of metabolic heat dissipation (enthalpy change). It suggests that aerobic glycolysis may be preferable because metabolic heat production during one mol of ATP regeneration by aerobic glycolysis was less than that produced by oxidative phosphorylation (OXPHOS). Consistent with the simulation, OXPHOS inhibition induced metabolic redirection to aerobic glycolysis while maintaining the intracellular temperature. Furthermore, the dependency on aerobic glycolysis was partly alleviated upon culturing at low temperatures. Our data suggest that metabolic thermogenesis is an important factor in understanding aerobic glycolysis in cancer cells and that an advantage of aerobic glycolysis is the reduction in metabolic heat generation during ATP regeneration.

cancer biology↗

bioRxiv2020

Artificial intelligence based computational framework for drug-target prioritization and inference of novel repositionable drugs for Alzheimer's disease

BackgroundIdentification of novel therapeutic targets is a key for successful drug development. However, the cost to experimentally identify therapeutic targets is huge and only 400 genes are targets for FDA-approved drugs. Therefore, it is inevitable to develop powerful computational tools to identify potential novel therapeutic targets. Because proteins make their functions together with their interacting partners, a protein-protein interaction network (PIN) in human could be a useful resource to build computational tools to investigate potential targets for therapeutic drugs. Network embedding methods, especially deep-learning based methods would be useful tools to extract an informative low-dimensional latent space that contains enough information required to fully represent original high-dimensional non-linear data of PINs. ResultsIn this study, we developed a deep learning based computational framework that extracts low-dimensional latent space embedded in high-dimensional data of the human PIN and uses the features in the latent space (latent features) to infer potential novel targets for therapeutic drugs. We examined the relationships between the latent features and the representative network metrics and found that the network metrics can explain a large number of the latent features, while several latent features do not correlate with all the network metrics. The results indicate that the features are likely to capture information that the representative network metrics can not capture, while the latent features also can capture information obtained from the network metrics. Our computational framework uses the latent features together with state-of-the-art machine learning techniques to infer potential drug target genes. We applied our computational framework to prioritized novel putative target genes for Alzheimers disease and successfully identified key genes for potential novel therapeutic targets (e.g., DLG4, EGFR, RAC1, SYK, PTK2B, SOCS1). Furthermore, based on these putative targets, we inferred repositionable candidate-compounds for the disease (e.g., Tamoxifen, Bosutinib, and Dasatinib) DiscussionsOur computational framework could be powerful computational tools to efficiently prioritize new therapeutic targets and drug repositioning. It is pertinent to note here that our computational platform is easily applicable to investigate novel potential targets and repositionable compounds for any diseases, especially for rare diseases.

bioinformatics↗

bioRxiv2020

Identifying spawning activity in aquatic species based on environmental DNA spikes

An understanding of the reproductive biology of aquatic organisms is crucial for the efficient conservation and management of species and/or populations. Nevertheless, conventional spawning surveys such as visual- and capture-based monitoring generally require laborious, time-consuming work and are subject to monitoring biases such as observer bias, as well as miscounts due to false spawning. In addition, direct capture often damages eggs or individuals. Thus, an efficient non-invasive approach for monitoring spawning activity on aquatic species would be a valuable tool to understand their reproductive biology and conserving biodiversity. Here, we proposed an environmental DNA (eDNA)-based approach for monitoring and understanding spawning activity by observing spikes in eDNA concentration after spawning activity. We found in cross experiments using two medaka species (Oryzias latipes and O. sakaizumii, 1:1 individual per tank) that an eDNA spike occurred in only male species after spawning activity. In addition, the magnitude of the eDNA spike was dependent on the number of spawning activities with egg and sperm release. In the field survey during the reproductive season, eDNA concentration after spawning were 3-25 times higher than before spawning. On the other hand, there was no increase in eDNA concentration during the non-reproductive season. Therefore, our results demonstrated that spikes in the eDNA concentration are mainly caused by the release of sperm during spawning activity, and it can be used as evidence of spawning in field survey. The presented approach could be a practical tool for studying reproductive biology and provides an opportunity to design effective conservation and environmental management actions.

molecular biology↗

bioRxiv2019

Enhanced emotional memory retrieval by chemogenetic activation of locus coeruleus norepinephrine neurons

The ability to retrieve memory store in response to the environment is essential for animal behavioral adaptation. Norepinephrine (NE)-containing neurons in the brain play a key role in the modulation of synaptic plasticity underlying various processes of memory formation. However, the role of the central NE system in memory retrieval remains unclear. In this study, we developed a neural chemogenetic activation strategy using insect olfactory Ionotropic Receptors (IRs), and used it for selective stimulation of NE neurons in the locus coeruleus (LC) in transgenic mice. Ligand-induced activation of LC NE neurons resulted in enhancement of the retrieval process of conditioned taste aversion, which was mediated through at least partly adrenergic receptors in the amygdala. Pharmacological blockade of LC activity confirmed the facilitative role of these neurons in memory retrieval. Our findings indicate that the LC-amygdalar pathway is required and sufficient for enhancing the recall of taste associative memory.

neuroscience↗

bioRxiv2019

Environmental DNA analysis shows high potential as a tool for estimating intraspecific genetic diversity in a wild fish population

Environmental DNA (eDNA) analysis has recently been used as a new tool for estimating intraspecific diversity. However, whether known haplotypes contained in a sample can be detected correctly using eDNA-based methods has been examined only by an aquarium experiment. Here, we tested whether the haplotypes of Ayu fish (Plecoglossus altivelis altivelis) detected in a capture survey could also be detected from an eDNA sample derived from the field that contained various haplotypes with low concentrations and foreign substances. A water sample and Ayu specimens collected from a river on the same day were analysed by eDNA analysis and Sanger sequencing, respectively. The 10 L water sample was divided into 20 filters for each of which 15 PCR replications were performed. After high-throughput sequencing, denoising was performed using two of the most widely used denoising packages, UNOISE3 and DADA2. Of the 42 haplotypes obtained from the Sanger sequencing of 96 specimens, 38 (UNOISE3) and 41 (DADA2) haplotypes were detected by eDNA analysis. When DADA2 was used, except for one haplotype, haplotypes owned by at least two specimens were detected from all the filter replications. This study showed that the eDNA analysis for evaluating intraspecific genetic diversity provides comparable results for large-scale capture-based conventional methods, suggesting that it could become a more efficient survey method for investigating intraspecific genetic diversity in the field.

molecular biology↗

bioRxiv2018

Evaluating intraspecific diversity of a fish population using environmental DNA: An approach to distinguish true haplotypes from erroneous sequences

Recent advances in environmental DNA (eDNA) analysis using high-throughput sequencing (HTS) provide a non-invasive way to evaluate the intraspecific genetic diversity of aquatic macroorganisms. However, erroneous sequences present in HTS data can result in false positive haplotypes; therefore, reliable strategies are necessary to eliminate such erroneous sequences when evaluating intraspecific genetic diversity using eDNA metabarcoding. In this study, we propose an approach combining denoising using amplicon sequence variant (ASV) method and the removal of haplotypes with low detection rates. A mixture of rearing water of Ayu (Plecoglossus altivelis altivelis) was used as an eDNA sample. In total, nine haplotypes of Ayu mitochondrial D-loop region were contained in the sample and amplified by two-step tailed PCR. The 15 PCR replicates indexed different tags were prepared from the eDNA sample to compare the detection rates between true haplotypes and false positive haplotypes. All PCR replications were sequenced by HTS, and the total number of detected true haplotypes and false positive haplotypes were compared with and without denoising using the two types of ASV methods, Divisive Amplicon Denoising Algorithm 2 (DADA2) and UNOISE3. The use of both ASV methods considerably reduced the number of false positive haplotypes. Moreover, all true haplotypes were detected in all 15 PCR, whereas false positive haplotypes had detection rates varying from 1/15 to 15/15. Thus, by removing haplotypes with lower detection rates than 15/15, the number of false positive haplotypes were further reduced. The approach proposed in this study successfully eliminated most of false positive haplotypes in the HTS data obtained from eDNA samples, which allowed us to improve the detection accuracy for evaluating intraspecific genetic diversity using eDNA analysis.

molecular biology↗