Covid-19 acute responses and possible long term consequences: what nanotoxicology can teach us

Non peer reviewe

Profiling Non-Coding RNA Changes Associated with 16 Different Engineered Nanomaterials in a Mouse Airway Exposure Model

Perturbations in cellular molecular events and their associated biological processes provide opportunities for hazard assessment based on toxicogenomic profiling. Long non-coding RNAs (lncRNAs) are transcribed from DNA but are typically not translated into full-length proteins. Via epigenetic regulation, they play important roles in organismal response to environmental stress. The effects of nanoparticles on this important part of the epigenome are understudied. In this study, we investigated changes in lncRNA associated with hazardous inhalatory exposure of mice to 16 engineered nanomaterials (ENM)–4 ENM (copper oxide, multi-walled carbon nanotubes, spherical titanium dioxide, and rod-like titanium dioxide particles) with 4 different surface chemistries (pristine, COOH, NH2, and PEG). Mice were exposed to 10 µg of ENM by oropharyngeal aspiration for 4 consecutive days, followed by cytological analyses and transcriptomic characterization of whole lung tissues. The number of significantly altered non-coding RNA transcripts, suggestive of their degrees of toxicity, was different for each ENM type. Particle surface chemistry and shape also had varying effects on lncRNA expression. NH2 and PEG caused the strongest and weakest responses, respectively. Via correlational analyses to mRNA expression from the same samples, we could deduce that significantly altered lncRNAs are potential regulators of genes involved in mitotic cell division and DNA damage response. This study sheds more light on epigenetic mechanisms of ENM toxicity and also emphasizes the importance of the lncRNA superfamily as toxicogenomic markers of adverse ENM exposure

Profiling Non-Coding RNA Changes Associated with 16 Different Engineered Nanomaterials in a Mouse Airway Exposure Model

Perturbations in cellular molecular events and their associated biological processes provide opportunities for hazard assessment based on toxicogenomic profiling. Long non-coding RNAs (lncRNAs) are transcribed from DNA but are typically not translated into full-length proteins. Via epigenetic regulation, they play important roles in organismal response to environmental stress. The effects of nanoparticles on this important part of the epigenome are understudied. In this study, we investigated changes in lncRNA associated with hazardous inhalatory exposure of mice to 16 engineered nanomaterials (ENM)-4 ENM (copper oxide, multi-walled carbon nanotubes, spherical titanium dioxide, and rod-like titanium dioxide particles) with 4 different surface chemistries (pristine, COOH, NH2, and PEG). Mice were exposed to 10 mu g of ENM by oropharyngeal aspiration for 4 consecutive days, followed by cytological analyses and transcriptomic characterization of whole lung tissues. The number of significantly altered non-coding RNA transcripts, suggestive of their degrees of toxicity, was different for each ENM type. Particle surface chemistry and shape also had varying effects on lncRNA expression. NH2 and PEG caused the strongest and weakest responses, respectively. Via correlational analyses to mRNA expression from the same samples, we could deduce that significantly altered lncRNAs are potential regulators of genes involved in mitotic cell division and DNA damage response. This study sheds more light on epigenetic mechanisms of ENM toxicity and also emphasizes the importance of the lncRNA superfamily as toxicogenomic markers of adverse ENM exposure.Peer reviewe

Profiling Non-Coding RNA Changes Associated with 16 Different Engineered Nanomaterials in a Mouse Airway Exposure Model

Perturbations in cellular molecular events and their associated biological processes provide opportunities for hazard assessment based on toxicogenomic profiling. Long non-coding RNAs (lncRNAs) are transcribed from DNA but are typically not translated into full-length proteins. Via epigenetic regulation, they play important roles in organismal response to environmental stress. The effects of nanoparticles on this important part of the epigenome are understudied. In this study, we investigated changes in lncRNA associated with hazardous inhalatory exposure of mice to 16 engineered nanomaterials (ENM)–4 ENM (copper oxide, multi-walled carbon nanotubes, spherical titanium dioxide, and rod-like titanium dioxide particles) with 4 different surface chemistries (pristine, COOH, NH2, and PEG). Mice were exposed to 10 µg of ENM by oropharyngeal aspiration for 4 consecutive days, followed by cytological analyses and transcriptomic characterization of whole lung tissues. The number of significantly altered non-coding RNA transcripts, suggestive of their degrees of toxicity, was different for each ENM type. Particle surface chemistry and shape also had varying effects on lncRNA expression. NH2 and PEG caused the strongest and weakest responses, respectively. Via correlational analyses to mRNA expression from the same samples, we could deduce that significantly altered lncRNAs are potential regulators of genes involved in mitotic cell division and DNA damage response. This study sheds more light on epigenetic mechanisms of ENM toxicity and also emphasizes the importance of the lncRNA superfamily as toxicogenomic markers of adverse ENM exposure

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

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 in vivo experimentation into cell-based in vitro 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.Peer reviewe

Supervised Methods for Biomarker Detection from Microarray Experiments

Biomarkers are valuable indicators of the state of a biological system. Microarray technology has been extensively used to identify biomarkers and build computational predictive models for disease prognosis, drug sensitivity and toxicity evaluations. Activation biomarkers can be used to understand the underlying signaling cascades, mechanisms of action and biological cross talk. Biomarker detection from microarray data requires several considerations both from the biological and computational points of view. In this chapter, we describe the main methodology used in biomarkers discovery and predictive modeling and we address some of the related challenges. Moreover, we discuss biomarker validation and give some insights into multiomics strategies for biomarker detection.Non peer reviewe

Toxicogenomics analysis of dynamic dose-response in macrophages highlights molecular alterations relevant for multi-walled carbon nanotube-induced lung fibrosis

Toxicogenomics approaches are increasingly used to gain mechanistic insight into the toxicity of engineered nanomaterials (ENMs). These emerging technologies have been shown to aid the translation of in vitro experimentation into relevant information on real-life exposures. Furthermore, integrating multiple layers of molecular alteration can provide a broader understanding of the toxicological insult. While there is growing evidence of the immunotoxic effects of several ENMs, the mechanisms are less characterized, and the dynamics of the molecular adaptation of the immune cells are still largely unknown. Here, we hypothesized that a multi-omics investigation of dynamic dose-dependent (DDD) molecular alterations could be used to retrieve relevant information concerning possible long-term consequences of the exposure. To this end, we applied this approach on a model of human macrophages to investigate the effects of rigid multi-walled carbon nanotubes (rCNTs). THP-1 macrophages were exposed to increasing concentrations of rCNTs and the genome-wide transcription and gene promoter methylation were assessed at three consecutive time points. The results suggest dynamic molecular adaptation with a rapid response in the gene expression and contribution of DNA methylation in the long-term adaptation. Moreover, our analytical approach is able to highlight patterns of molecular alteration in vitro that are relevant for the pathogenesis of pulmonary fibrosis, a known long-term effect of rCNTs exposure in vivo.Peer reviewe

Microarray Data Preprocessing: From Experimental Design to Differential Analysis

DNA microarray data preprocessing is of utmost importance in the analytical path starting from the experimental design and leading to a reliable biological interpretation. In fact, when all relevant aspects regarding the experimental plan have been considered, the following steps from data quality check to differential analysis will lead to robust, trustworthy results. In this chapter, all the relevant aspects and considerations about microarray preprocessing will be discussed. Preprocessing steps are organized in an orderly manner, from experimental design to quality check and batch effect removal, including the most common visualization methods. Furthermore, we will discuss data representation and differential testing methods with a focus on the most common microarray technologies, such as gene expression and DNA methylation.Peer reviewe

Integrated network analysis reveals new genes suggesting COVID-19 chronic effects and treatment

The COVID-19 disease led to an unprecedented health emergency, still ongoing worldwide. Given the lack of a vaccine or a clear therapeutic strategy to counteract the infection as well as its secondary effects, there is currently a pressing need to generate new insights into the SARS-CoV-2 induced host response. Biomedical data can help to investigate new aspects of the COVID-19 pathogenesis, but source heterogeneity represents a major drawback and limitation. In this work, we applied data integration methods to develop a Unified Knowledge Space (UKS) and used it to identify a new set of genes associated with SARS-CoV-2 host response, both in vitro and in vivo. Functional analysis of these genes reveals possible long-term systemic effects of the infection, such as vascular remodelling and fibrosis. Finally, we identified a set of potentially relevant drugs targeting proteins involved in multiple steps of the host response to the virus.Peer reviewe

Integration of genome-wide mRNA and miRNA expression, and DNA methylation data of three cell lines exposed to ten carbon nanomaterials

We present data derived from an exposure experiment in which three cell-lines representative of cell types of the respiratory tissue (epithelial type-I A549, epithelial type-II BEAS-2B, and macrophage THP-1) have been exposed to ten different carbon-based nanomaterials for 48 h. In particular, we provide: genome-wide mRNA and miRNA expression, and DNA methylation; gene tables, containing information on the aberrations induced in these three genomic data layers at the gene level; mechanism of action (MOA) maps representing the comparative functional alteration induced in each cell line and each exposure. (C) 2018 Published by Elsevier Inc.Peer reviewe