Toxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely... Show moreToxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely disease-specific observational models into target-specific predictive models. Traditionally, toxicology has strong links with other fields such as biology, chemistry, pharmacology and medicine. With the rise of synthetic and new engineered materials, alongside ongoing prioritisation needs in chemical risk assessment for existing chemicals, early predictive evaluations are becoming of utmost importance to both scientific and regulatory purposes. ELIXIR is an intergovernmental organisation that brings together life science resources from across Europe. To coordinate the linkage of various life science efforts around modern predictive toxicology, the establishment of a new ELIXIR Community is seen as instrumental. In the past few years, joint efforts, building on incidental overlap, have been piloted in the context of ELIXIR. For example, the EU-ToxRisk, diXa, HeCaToS, transQST, and the nanotoxicology community have worked with the ELIXIR TeSS, Bioschemas, and Compute Platforms and activities. In 2018, a core group of interested parties wrote a proposal, outlining a sketch of what this new ELIXIR Toxicology Community would look like. A recent workshop (held September 30th to October 1st, 2020) extended this into an ELIXIR Toxicology roadmap and a shortlist of limited investment-high gain collaborations to give body to this new community. This Whitepaper outlines the results of these efforts and defines our vision of the ELIXIR Toxicology Community and how it complements other ELIXIR activities. Show less
The liver plays an important role in xenobiotic metabolism and represents a primary target for toxic substances. Many different in vitro cell models have been developed in the past decades. In this... Show moreThe liver plays an important role in xenobiotic metabolism and represents a primary target for toxic substances. Many different in vitro cell models have been developed in the past decades. In this study, we used RNA-sequencing (RNA-Seq) to analyze the following human in vitro liver cell models in comparison to human liver tissue: cancer-derived cell lines (HepG2, HepaRG 3D), induced pluripotent stem cell-derived hepatocyte-like cells (iPSC-HLCs), cancerous human liver-derived assays (hPCLiS, human precision cut liver slices), non-cancerous human liver-derived assays (PHH, primary human hepatocytes) and 3D liver microtissues. First, using CellNet, we analyzed whether these liver in vitro cell models were indeed classified as liver, based on their baseline expression profile and gene regulatory networks (GRN). More comprehensive analyses using non-differentially expressed genes (non-DEGs) and differential transcript usage (DTU) were applied to assess the coverage for important liver pathways. Through different analyses, we noticed that 3D liver microtissues exhibited a high similarity with in vivo liver, in terms of CellNet (C/T score: 0.98), non-DEGs (10,363) and pathway coverage (highest for 19 out of 20 liver specific pathways shown) at the beginning of the incubation period (0 h) followed by a decrease during long-term incubation for 168 and 336 h. PHH also showed a high degree of similarity with human liver tissue and allowed stable conditions for a short-term cultivation period of 24 h. Using the same metrics, HepG2 cells illustrated the lowest similarity (C/T: 0.51, non-DEGs: 5623, and pathways coverage: least for 7 out of 20) with human liver tissue. The HepG2 are widely used in hepatotoxicity studies, however, due to their lower similarity, they should be used with caution. HepaRG models, iPSC-HLCs, and hPCLiS ranged clearly behind microtissues and PHH but showed higher similarity to human liver tissue than HepG2 cells. In conclusion, this study offers a resource of RNA-Seq data of several biological replicates of human liver cell models in vitro compared to human liver tissue. Show less
Sillivan, S.E.; Jamieson, S.; Nijs, L. de; Jones, M.; Snijders, C.; Klengel, T.; ... ; Miller, C.A. 2020
Disruption of persistent, stress-associated memories is relevant for treating posttraumatic stress disorder (PTSD) and related syndromes, which develop in a subset of individuals following a... Show moreDisruption of persistent, stress-associated memories is relevant for treating posttraumatic stress disorder (PTSD) and related syndromes, which develop in a subset of individuals following a traumatic event. We previously developed a stress-enhanced fear learning (SEFL) paradigm in inbred mice that produces PTSD-like characteristics in a subset of mice, including persistently enhanced memory and heightened cFos in the basolateral amygdala complex (BLC) with retrieval of the remote (30-day-old) stress memory. Here, the contribution of BLC microRNAs (miRNAs) to stress-enhanced memory was investigated because of the molecular complexity they achieve through their ability to regulate multiple targets simultaneously. We performed small-RNA sequencing (smRNA-Seq) and quantitative proteomics on BLC tissue collected from mice 1 month after SEFL and identified persistently changed microRNAs, including mir-135b-5p, and proteins associated with PTSD-like heightened fear expression. Viral-mediated overexpression of mir-135b-5p in the BLC of stress-resilient animals enhanced remote fear memory expression and promoted spontaneous renewal 14 days after extinction. Conversely, inhibition of BLC mir-135b-5p in stress-susceptible animals had the opposite effect, promoting a resilient-like phenotype. mir-135b-5p is highly conserved across mammals and was detected in post mortem human amygdala, as well as human serum samples. The mir-135b passenger strand, mir-135b-3p, was significantly elevated in serum from PTSD military veterans, relative to combat-exposed control subjects. Thus, miR-135b-5p may be an important therapeutic target for dampening persistent, stress-enhanced memory and its passenger strand a potential biomarker for responsivity to a mir-135-based therapeutic. Show less
Sillivan, S.E.; Jamieson, S.; Nijs, L. de; Jones, M.; Snijders, C.; Klengel, T.; ... ; Miller, C.A. 2020
Posttraumatic stress disorder (PTSD) is a psychiatric disorder that can develop upon exposure to a traumatic event. While most people are able to recover promptly, others are at increased risk of... Show morePosttraumatic stress disorder (PTSD) is a psychiatric disorder that can develop upon exposure to a traumatic event. While most people are able to recover promptly, others are at increased risk of developing PTSD. However, the exact underlying biological mechanisms of differential susceptibility are unknown. Identifying biomarkers of PTSD could assist in its diagnosis and facilitate treatment planning. Here, we identified serum microRNAs (miRNAs) of subjects that underwent a traumatic event and aimed to assess their potential to serve as diagnostic biomarkers of PTSD. Next-generation sequencing was performed to examine circulating miRNA profiles of 24 members belonging to the Dutch military cohort Prospective Research in Stress-Related Military Operations (PRISMO). Three groups were selected: "susceptible" subjects who developed PTSD after combat exposure, "resilient" subjects without PTSD, and nonexposed control subjects (N = 8 per group). Differential expression analysis revealed 22 differentially expressed miRNAs in PTSD subjects compared to controls and 1 in PTSD subjects compared to resilient individuals (after multiple testing correction and a log2 fold-change cutoff of >=|1|). Weighted Gene Coexpression Network Analysis (WGCNA) identified a module of coexpressed miRNAs which could distinguish between the three groups. In addition, receiver operating characteristic curve analyses suggest that the miRNAs with the highest module memberships could have a strong diagnostic accuracy as reflected by high areas under the curves. Overall, the results of our pilot study suggest that serum miRNAs could potentially serve as diagnostic biomarkers of PTSD, both individually or grouped within a cluster of coexpressed miRNAs. Larger studies are now needed to validate and build upon these preliminary findings. Show less
Nijs, L. de; Krauskopf, J.; Snijders, C.; Kleinjans, J.; Machiels, B.; Smeets, B.; ... ; Rutten, B. 2017
Background: Previously, we developed a combined dictionary dubbed Chemlist for the identification of small molecules and drugs in text based on a number of publicly available databases and tested... Show moreBackground: Previously, we developed a combined dictionary dubbed Chemlist for the identification of small molecules and drugs in text based on a number of publicly available databases and tested it on an annotated corpus. To achieve an acceptable recall and precision we used a number of automatic and semi-automatic processing steps together with disambiguation rules. However, it remained to be investigated which impact an extensive manual curation of a multi-source chemical dictionary would have on chemical term identification in text. ChemSpider is a chemical database that has undergone extensive manual curation aimed at establishing valid chemical name-to-structure relationships.Results: We acquired the component of ChemSpider containing only manually curated names and synonyms. Rule-based term filtering, semi-automatic manual curation, and disambiguation rules were applied. We tested the dictionary from ChemSpider on an annotated corpus and compared the results with those for the Chemlist dictionary. The ChemSpider dictionary of ca. 80 k names was only a 1/3 to a 1/4 the size of Chemlist at around 300 k. The ChemSpider dictionary had a precision of 0.43 and a recall of 0.19 before the application of filtering and disambiguation and a precision of 0.87 and a recall of 0.19 after filtering and disambiguation. The Chemlist dictionary had a precision of 0.20 and a recall of 0.47 before the application of filtering and disambiguation and a precision of 0.67 and a recall of 0.40 after filtering and disambiguation.Conclusions: We conclude the following: (1) The ChemSpider dictionary achieved the best precision but the Chemlist dictionary had a higher recall and the best F-score; (2) Rule-based filtering and disambiguation is necessary to achieve a high precision for both the automatically generated and the manually curated dictionary. ChemSpider is available as a web service at http://www.chemspider.com/ and the Chemlist dictionary is freely available as an XML file in Simple Knowledge Organization System format on the web at http://www.biosemantics.org/chemlist. Show less
