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鱼类连通性图谱:通过其作用机制驱动的转录组图谱连接化学应激源。

Fish connectivity mapping: linking chemical stressors by their mechanisms of action-driven transcriptomic profiles.

作者信息

Wang Rong-Lin, Biales Adam D, Garcia-Reyero Natalia, Perkins Edward J, Villeneuve Daniel L, Ankley Gerald T, Bencic David C

机构信息

Exposure Methods & Measurements Division, National Exposure Research Laboratory, US Environmental Protection Agency, 26 W Martin Luther King Dr., MS 587, Cincinnati, OH, 45268, USA.

Environmental Laboratory, US Army Engineer Research and Development Center, US Army Corps of Engineers, 3909 Halls Ferry Rd, Vicksburg, MS, 39180, USA.

出版信息

BMC Genomics. 2016 Jan 28;17:84. doi: 10.1186/s12864-016-2406-y.

Abstract

BACKGROUND

A very large and rapidly growing collection of transcriptomic profiles in public repositories is potentially of great value to developing data-driven bioinformatics applications for toxicology/ecotoxicology. Modeled on human connectivity mapping (Cmap) in biomedical research, this study was undertaken to investigate the utility of an analogous Cmap approach in ecotoxicology. Over 3500 zebrafish (Danio rerio) and fathead minnow (Pimephales promelas) transcriptomic profiles, each associated with one of several dozen chemical treatment conditions, were compiled into three distinct collections of rank-ordered gene lists (ROGLs) by species and microarray platforms. Individual query signatures, each consisting of multiple gene probes differentially expressed in a chemical condition, were used to interrogate the reference ROGLs.

RESULTS

Informative connections were established at high success rates within species when, as defined by their mechanisms of action (MOAs), both query signatures and ROGLs were associated with the same or similar chemicals. Thus, a simple query signature functioned effectively as an exposure biomarker without need for a time-consuming process of development and validation. More importantly, a large reference database of ROGLs also enabled a query signature to cross-interrogate other chemical conditions with overlapping MOAs, leading to novel groupings and subgroupings of seemingly unrelated chemicals at a finer resolution. This approach confirmed the identities of several estrogenic chemicals, as well as a polycyclic aromatic hydrocarbon and a neuro-toxin, in the largely uncharacterized water samples near several waste water treatment plants, and thus demonstrates its future potential utility in real world applications.

CONCLUSIONS

The power of Cmap should grow as chemical coverages of ROGLs increase, making it a framework easily scalable in the future. The feasibility of toxicity extrapolation across fish species using Cmap needs more study, however, as more gene expression profiles linked to chemical conditions common to multiple fish species are needed.

摘要

背景

公共数据库中大量且快速增长的转录组图谱集合对于开发数据驱动的毒理学/生态毒理学信息学应用可能具有巨大价值。本研究以生物医学研究中的人类连接图谱(Cmap)为模型,旨在探讨类似的Cmap方法在生态毒理学中的效用。超过3500个斑马鱼(Danio rerio)和黑头呆鱼(Pimephales promelas)的转录组图谱,每个图谱都与几十种化学处理条件之一相关联,按物种和微阵列平台被汇编成三个不同的有序基因列表(ROGLs)集合。每个由在化学条件下差异表达的多个基因探针组成的个体查询特征,被用于查询参考ROGLs。

结果

当查询特征和ROGLs根据其作用机制(MOAs)与相同或相似的化学物质相关联时,在物种内以高成功率建立了信息性联系。因此,一个简单查询特征可有效地作为暴露生物标志物,而无需耗时的开发和验证过程。更重要的是,一个大型的ROGLs参考数据库还使查询特征能够交叉查询具有重叠MOAs的其他化学条件,从而以更高分辨率对看似不相关的化学物质进行新的分组和子分组。这种方法确认了几个废水处理厂附近大量未表征水样中的几种雌激素化学物质、一种多环芳烃和一种神经毒素的身份,从而证明了其在实际应用中的未来潜在效用。

结论

随着ROGLs的化学覆盖范围增加,Cmap的能力应会增强,使其成为一个未来易于扩展的框架。然而,使用Cmap跨鱼类物种进行毒性外推的可行性需要更多研究,因为需要更多与多种鱼类共有的化学条件相关的基因表达谱。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5da2/4730593/aa8ad9987546/12864_2016_2406_Fig1_HTML.jpg

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