Biology subjects

Kanamori, Y.

Publications and source records attributed to Kanamori, Y..

4 recordsLinked to original sources

bioRxiv2024

Integrated hepatic ferroptosis gene signature dictates pathogenic features of ferroptosis

Background & AimsFerroptosis, a distinctive form of cell death induced by iron-dependent lipid peroxidation, is implicated in various biological processes, including liver diseases. Establishing an iron overload-induced ferroptosis model and identifying hepatic gene signatures associated with ferroptosis are crucial for understanding its role in liver pathogenesis. MethodsF-box and leucine-rich repeat protein 5 (FBXL5) is a substrate-recognition component of the SCF E3 ligase complex that restricts intracellular iron levels. In this study, we used liver-specific Fbxl5-null mice to establish an iron overload-induced ferroptosis model. Transcriptome analysis identified genes involved in hepatic ferroptosis. Integrating these gene signatures with another ferroptosis model enabled the assessment of ferroptosis-related pathology in murine liver injury models and in 174 patients undergoing liver resection surgery. ResultsIron overload induced severe liver damage in liver-specific Fbxl5-null mice, characterized by elevated liver enzymes, histopathological changes, and lipid peroxidation. Transcriptome analysis revealed a distinct set of genes associated with hepatic ferroptosis response. Generating a gene signature for evaluating ferroptosis enhanced the understanding of ferroptosis-related pathologies in liver diseases. Iron overload exacerbated liver damage in murine ischemia-reperfusion injury models via ferroptosis induction. In human patients, elevated serum iron levels correlated with sustained post-operative liver damage, indicating heightened susceptibility to ferroptosis. ConclusionHere, a murine model of iron overload-induced hepatic ferroptosis was established, and a gene signature indicative of hepatic ferroptosis response in both mice and humans was identified. These findings underscore the role of ferroptosis in liver injury progression and suggest potential therapeutic targets for liver disease intervention. HIGHLIGHTSO_LILiver-specific Fbxl5 knockout mice provide an iron-induced ferroptotic injury model C_LIO_LIIntegrated gene signature of iron- and acetaminophen-induced liver injury dictates ferroptosis C_LIO_LIIron overload aggravates hepatic ischemia-reperfusion injury in mice C_LIO_LIPatients with high iron levels show delayed post-operative liver damage recovery C_LI IMPACT AND IMPLICATIONSOur study elucidated the critical role of iron in liver disease pathogenesis and ischemia-reperfusion injury (IRI). By establishing a murine model of iron overload-induced ferroptosis, we confirmed that iron overload exacerbated hepatic IRI, underscoring the importance of ferroptosis in liver damage. Additionally, the development of an integrated gene signature for hepatic ferroptosis response provides a valuable tool for evaluating ferroptosis in liver diseases. Via analysis of patient data, we also highlighted the clinical relevance of ferroptosis in post-operative liver damage, offering insights into potential therapeutic strategies targeting iron and ferroptosis to improve outcomes in patients with liver diseases.

molecular biology↗

bioRxiv2024

Distributional shifts change the biodiversity-ecosystem stability relationship under climate change

Distributional shifts under climate change are increasingly recognized as a biotic change worldwide. However, the effects of distributional shifts on ecosystem variability through changes in biodiversity remain to be clari[fi]ed. In this study, to elucidate the impact of population-level distributional shifts under climate change on community structure and ecosystem function through ecological hierarchy, we investigated the temporal changes in alpha and beta diversity, the contribution of individual species to the observed changes in biodiversity, and the changes in the relationship between biodiversity and ecosystem variability, using over 25 years of data on about 700 species. We found that ecosystem variability was largely stabilized by beta diversity, especially in the present period (2012 to 2021), because beta diversity increased due to the invasion of species that were distributed mainly in tropic and subtropic areas. Despite the effect of beta diversity, ecosystem variability increased in the present period. This increase in ecosystem variability was caused by the spatially synchronized temporal variation in sea-bottom temperature, which resulted in synchronized temporal variation in species abundance among local communities, as well as the increased impact of alpha variability on ecosystem variability. These results indicate that the impact of alpha diversity on ecosystem variability is more changeable than the impact of beta diversity on ecosystem variability under climate change, suggesting the importance of focusing on changes in alpha diversity resulting from local colonization from other habitats and local extinction in existing habitats.

ecology↗

bioRxiv2022

Spatio-temporal model and machine learning method reveal process of phenological shift under climate change of North Pacific spiny dogfish

Climate change has disrupted natural phenological patterns, including migration. Despite extensive studies of phenological shifts in migration by climate change and driving factors of migration, a few issues remain unresolved. In particular, little is known about the complex effects of driving factors on migration with interactions and nonlinearity, and partitioning of the effects of factors into spatial, temporal, and spatio-temporal effects. The Pacific spiny dogfish Squalus suckleyi (hereafter "spiny dogfish") is a coastal elasmobranchii that migrates southward for parturition and northward for feeding in the western North Pacific. Here, to elucidate the migration patterns as well as the driving factors under climate change, we first examined long-term changes in the timing and geographic location of migration by applying a spatio-temporal model to ca. 5-decade time series data for the presence/absence of spiny dogfish in the western North Pacific. We then evaluated the spatial, temporal, and spatio-temporal effects of driving factors (sea surface temperature [SST], depth, productivity, and magnetic fields) on seasonal occurrence patterns using a machine learning model. We found that the migration area did not change over ca. 5 decades, whereas the migration timing advanced by a month after 2000. The spatial effects of magnetic fields and depth were consistently large and the spatial and spatio-temporal effects of SST increased in the migration season, even though temporal effect of SST was always weak. These results suggest that the migration area of spiny dogfish was stable over time because their spatial distribution was determined by geographic features, whereas the migration timing advanced by tracking a suitable SST location which increased steeply after 2000. Therefore, temperature as well as other factors influence migration simultaneously under climate change and underline the importance of paying attention biotic/abiotic factors including temperature and process-based understanding to predict future impacts of climate change on phenological shifts.

ecology↗

bioRxiv2020

Spatio-temporal model reduces species misidentification bias of spawning eggs in stock assessment of spotted mackerel in the western North Pacific

Species identification based on morphological characteristics includes species misidentification, leading to estimation bias of population size. The eggs of spotted mackerel Scomber australicus and chub mackerel S. japonicus in the western North Pacific has been identified based on egg diameter. Recent density of spotted mackerel was considerably high despite its low stock biomass. A possibility of this phenomenon is due to overestimation because the difference in egg diameter has become ambiguous between two species. However, we cannot test this possibility using DNA analysis because the eggs are fixed with formalin. Here, we estimated the index of egg density of spotted mackerel using a spatio-temporal model that incorporates the effect of egg density of chub mackerel on the catchability of spotted mackerel, using 15 years data of spawning eggs. We then examined how retrospective biases in estimated stock abundance were reduced when using the index from the model. The index estimated from the model decreased temporal fluctuation and showed smooth patterns. Especially, the recent index was considerably revised down rather than the nominal index. Additionally, the retrospective bias decreased ca. half compared with the nominal index. Therefore, incorporating species misidentification bias should be an essential process for improving stock assessment.

ecology↗