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十种碳纳米材料效应的多组学分析突出了细胞类型特异性的分子调控和适应模式。

Multi-omics analysis of ten carbon nanomaterials effects highlights cell type specific patterns of molecular regulation and adaptation.

作者信息

Scala Giovanni, Kinaret Pia, Marwah Veer, Sund Jukka, Fortino Vittorio, Greco Dario

机构信息

Faculty of Medicine and Life Sciences, University of Tampere, Finland.

Institute of Biosciences and Medical Technologies (BioMediTech), University of Tampere, Finland.

出版信息

NanoImpact. 2018 Jul;11:99-108. doi: 10.1016/j.impact.2018.05.003.

Abstract

New strategies to characterize the effects of engineered nanomaterials (ENMs) based on omics technologies are emerging. However, given the intricate interplay of multiple regulatory layers, the study of a single molecular species in exposed biological systems might not allow the needed granularity to successfully identify the pathways of toxicity (PoT) and, hence, portraying adverse outcome pathways (AOPs). Moreover, the intrinsic diversity of different cell types composing the exposed organs and tissues in living organisms poses a problem when transferring experimentation into cell-based systems. To overcome these limitations, we have profiled genome-wide DNA methylation, mRNA and microRNA expression in three human cell lines representative of relevant cell types of the respiratory system, A549, BEAS-2B and THP-1, exposed to a low dose of ten carbon nanomaterials (CNMs) for 48 h. We applied advanced data integration and modelling techniques in order to build comprehensive regulatory and functional maps of the CNM effects in each cell type. We observed that different cell types respond differently to the same CNM exposure even at concentrations exerting similar phenotypic effects. Furthermore, we linked patterns of genomic and epigenomic regulation to intrinsic properties of CNM. Interestingly, DNA methylation and microRNA expression only partially explain the mechanism of action (MOA) of CNMs. Taken together, our results strongly support the implementation of approaches based on multi-omics screenings on multiple tissues/cell types, along with systems biology-based multi-variate data modelling, in order to build more accurate AOPs.

摘要

基于组学技术来表征工程纳米材料(ENMs)效应的新策略正在兴起。然而,鉴于多个调控层面之间复杂的相互作用,在暴露的生物系统中研究单一分子种类可能无法提供成功识别毒性途径(PoT)所需的精细程度,因此也无法描绘出不良结局途径(AOPs)。此外,构成生物体中暴露器官和组织的不同细胞类型的内在多样性,在将实验转移到基于细胞的系统时会带来问题。为了克服这些限制,我们对三种代表呼吸系统相关细胞类型的人类细胞系A549、BEAS - 2B和THP - 1进行了全基因组DNA甲基化、mRNA和微小RNA表达分析,这些细胞系暴露于低剂量的十种碳纳米材料(CNMs)48小时。我们应用了先进的数据整合和建模技术,以便构建每种细胞类型中CNM效应的全面调控和功能图谱。我们观察到,即使在施加相似表型效应的浓度下,不同细胞类型对相同的CNM暴露的反应也不同。此外,我们将基因组和表观基因组调控模式与CNM的内在特性联系起来。有趣的是,DNA甲基化和微小RNA表达仅部分解释了CNMs的作用机制(MOA)。综上所述,我们的结果有力地支持了基于对多种组织/细胞类型进行多组学筛选以及基于系统生物学的多变量数据建模的方法的实施,以便构建更准确的AOPs。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/caa3/7043328/70d21a614d37/fx1.jpg

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