Biology subjects

Hiki, K.

Publications and source records attributed to Hiki, K..

3 recordsLinked to original sources

bioRxiv2025

Statistical Causal Discovery in Developing and Refining Adverse Outcome Pathway (AOP)

Statistical causal discovery (SCD) has the potential to advance the development and evaluation of Adverse Outcome Pathways (AOPs) by inferring causal relationships directly from data. However, ecotoxicology data often has challenges for SCD applications, such as missing data and violation of SCD algorithm assumptions. As a proof-of-concept, we applied a linear non-Gaussian acyclic model (LiNGAM), a representative SCD method, to three types of ecotoxicology datasets: (1) bivariate dose-response relationships, (2) bivariate response- response relationships, and (3) a multivariate dataset with a known causal structure. Missing data were addressed through multiple imputation followed by causal estimation using DirectLiNGAM, a direct method for estimating LiNGAM. DirectLiNGAM identified correct causal directions with high statistical reliabilities in three of four bivariate dose-response cases, even when assumptions such as linearity and non-Gaussianity were partially violated. In contrast, response-response cases did not yield a single dominant direction, likely due to the limited number of replicates. In the multivariate case, the inferred graphs closely resembled the expert-curated causal graph, achieving high recall (0.50-0.75), despite relatively low precision (0.31-0.40). These results demonstrate the utility of SCD, combined with multiple imputation, in identifying relevant key events, revealing missing links, and refining existing AOP and quantitative AOP (qAOP) models, under realistic ecotoxicological constraints. SynopsisStatistical causal discovery can advance the development of adverse outcome pathways in a data-driven manner, enabling efficient chemical risk assessment. TOC Art O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC="FIGDIR/small/672289v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@117bd64org.highwire.dtl.DTLVardef@19318cdorg.highwire.dtl.DTLVardef@414aecorg.highwire.dtl.DTLVardef@9e068e_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

Comprehensive Sequencing of Environmental RNA from Japanese Medaka at Various Size Fractions and Comparison with Skin RNA

Environmental RNA (eRNA) is emerging as a non-invasive tool for assessing the health of macro-organisms, but key information on its origin and particle sizes remains unclear. In this study, we performed comprehensive RNA-sequencing of eRNA (> 13 Gb/sample) collected from tank water containing Japanese medaka (Oryzias latipes), using sequential filtration through filters with pore sizes of 10, 3, and 0.4 m. Fish skin RNA was also sequenced to reveal the origin of eRNA. Our results showed that the 3-10 m fraction contained the lowest relative abundance of microbial RNA, the highest amount of medaka eRNA, and the largest number of detected medaka genes (5398 genes), while the 0.4-3 m fraction had the fewest (972 genes). Only a small number of genes (42 genes) were unique to the 0.4-3 m fraction. These findings suggest that a 3 m filter is optimal for eRNA analysis, as it allows for larger filtration volumes while maintaining the relative abundance of macro-organism eRNA. Furthermore, 81% of the genes detected in eRNA overlapped with skin RNA, indicating skin is a major source of fish eRNA. SynopsisThe 3 {micro}m filter is recommended to maximize the detection of eRNA from macro-organisms while reducing the relative abundance of microbial RNA. TOC Art O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/614187v2_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1702cc9org.highwire.dtl.DTLVardef@18c4d2borg.highwire.dtl.DTLVardef@1e4c13org.highwire.dtl.DTLVardef@114a4b1_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2023

Environmental RNA as a non-invasive tool for assessing toxic effects in fish: a proof-of-concept study using Japanese medaka exposed to pyrene

Although environmental RNA (eRNA) is emerging as a non-invasive tool to assess the health status of aquatic macro-organisms, the potential of eRNA remains largely untested. In this study, we investigated the ability of eRNA to detect changes in gene expression in Japanese medaka fish (Oryzias latipes) in response to sub-lethal pyrene exposure, as a model toxic chemical. We performed standardized acute toxicity tests and collected eRNA from tank water and RNA from fish tissue after 96 h of exposure. Our results showed that over 1000 genes were detected in eRNA and the sequenced read counts of these genes correlated with those in fish tissue (r = 0.50). Moreover, eRNA detected 86 differentially expressed genes in response to pyrene, some of which were shared by fish RNA, including suppression of collagen fiber genes. These results suggest that eRNA has the potential to detect changes in gene expression in fish in response to environmental stressors without the need for sacrificing or causing pain to fish. However, we also found that the majority of sequenced reads of eRNA (> 99%) were not mapped to the reference medaka genome and they originated from bacteria and fungi, resulting in low sequencing-depth. In addition, eRNA, in particular nuclear genes, was highly degraded with a median transcript integrity number (TIN) of < 20. These limitations highlight the need for future studies to improve the analytical methods of eRNA application. TOC Art O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=92 SRC="FIGDIR/small/538202v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@98c437org.highwire.dtl.DTLVardef@17a1f31org.highwire.dtl.DTLVardef@95d1e7org.highwire.dtl.DTLVardef@7a253_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗