First Line Research Data Management for Life Sciences: a Case Study

Modern life sciences studies depend on the collection, management and analysis of comprehensive datasets in what has become data-intensive research. Life science research is also characterised by having relatively small groups of researchers. This combination of data-intensive research performed by a few people has led to an increasing bottleneck in research data management (RDM). Parallel to this, there has been an urgent call by initiatives like FAIR and Open Science to openly publish research data which has put additional pressure on improving the quality of RDM. Here, we reflect on the lessons learnt by DataHub Maastricht, a RDM support group of the Maastricht University Medical Centre (MUMC+) in Maastricht, the Netherlands, in providing first-line RDM support for life sciences. DataHub Maastricht operates with a small core team, and is complemented with disciplinary data stewards, many of whom have joint positions with DataHub and a research group. This organisational model helps creating shared knowledge between DataHub and the data stewards, including insights how to focus support on the most reusable datasets. This model has shown to be very beneficial given limited time and personnel. We found that co-hosting tailored platforms for specific domains, reducing storage costs by implementing tiered storage and promoting cross-institutional collaboration through federated authentication were all effective features to stimulate researchers to initiate RDM. Overall, utilising the expertise and communication channel of the embedded data stewards was also instrumental in our RDM success. Looking into the future, we foresee the need to further embed the role of data stewards into the lifeblood of the research organisation, along with policies on how to finance long-term storage of research data. The latter, to remain feasible, needs to be combined with a further formalising of appraisal and reappraisal of archived research data

MagiCMicroRna: a web implementation of AgiMicroRna using shiny

BACKGROUND: MicroRNA expression can be quantified using sequencing techniques or commercial microRNA-expression arrays. Recently, the AgiMicroRna R-package was published that enabled systematic preprocessing and statistical analysis for Agilent microRNA arrays. Here we describe MagiCMicroRna, which is a user-friendly web interface for this package, together with a new filtering approach. RESULTS: We used MagiCMicroRna to normalize and filter an Agilent miRNA microarray dataset of cancerous and normal tissues from 14 different patients. With the standard filtering procedure, 250 out of 817 microRNAs remained, whereas the new group-specific filtering approach resulted in broader datasets for further analysis in most groups (>279 microRNAs remaining). CONCLUSIONS: The user-friendly web interface of MagiCMicroRna enables researchers to normalize and filter Agilent microarrays by the click of one button. Furthermore, MagiCMicroRna provides flexibility in choosing the filtering method. The new group-specific filtering approach lead to an increased number and additional tissue-specific microRNAs remaining for subsequent analysis compared to the standard procedure. The MagiCMicroRna web interface and source code can be downloaded from https://bitbucket.org/mutgx/magicmicrorna.git. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13029-015-0035-5) contains supplementary material, which is available to authorized users

Regulation of skeletal muscle lipolysis and oxidative metabolism by the co-lipase CGI-58.

International audienceWe investigated here the specific role of CGI-58 in the regulation of energy metabolism in skeletal muscle. We first examined CGI-58 protein expression in various muscle types in mice, and next modulated CGI-58 expression during overexpression and knockdown studies in human primary myotubes and evaluated the consequences on oxidative metabolism. We observed a preferential expression of CGI-58 in oxidative muscles in mice consistent with triacylglycerol hydrolase activity. We next showed by pulse-chase that CGI-58 overexpression increased by more than 2-fold the rate of triacylglycerol (TAG) hydrolysis, as well as TAG-derived fatty acid (FA) release and oxidation. Oppositely, CGI-58 silencing reduced TAG hydrolysis and TAG-derived FA release and oxidation (-77%, P < 0.001), whereas it increased glucose oxidation and glycogen synthesis. Interestingly, modulations of CGI-58 expression and FA release are reflected by changes in pyruvate dehydrogenase kinase 4 gene expression. This regulation involves the activation of the peroxisome proliferator activating receptor-δ (PPARδ) by lipolysis products. Altogether, these data reveal that CGI-58 plays a limiting role in the control of oxidative metabolism by modulating FA availability and the expression of PPARδ-target genes, and highlight an important metabolic function of CGI-58 in skeletal muscle

Evaluating microRNA profiles reveals discriminative responses following genotoxic or non-genotoxic carcinogen exposure in primary mouse hepatocytes

Chemical carcinogenesis can be induced by genotoxic (GTX) or non-genotoxic (NGTX) carcinogens. GTX carcinogens have a well-described mode of action. However, the complex mechanisms by which NGTX carcinogens act are less clear and may result in conflicting results between species [e.g. Wy-14,643 (Wy)]. We hypothesise that common microRNA response pathways exist for each class of carcinogenic agents. Therefore, this study compares and integrates mRNA and microRNA expression profiles following short term acute exposure (24 and 48h) to three GTX [aflatoxin B1 (AFB1), benzo[a]pyrene (BaP) and cisplatin (CisPl)] or three NGTX (2,3,7,8-tetrachloordibenzodioxine (TCDD), cyclosporine A (CsA) and Wy) carcinogens in primary mouse hepatocytes. Discriminative gene sets, microRNAs (not for 24h) and processes were identified following 24 and 48h of exposure. From the three discriminative microRNAs found following 48h of exposure, mmu-miR-503-5p revealed to have an interaction with mRNA target gene cyclin D2 (Ccnd2 - 12444) which was involved in the discriminative process of p53 signalling and metabolism. Following exposure to NGTX carcinogens Mmu-miR-503-5p may have an oncogenic function by stimulating Ccnd2 possibly leading to a tumourigenic cell cycle progression. By contrast, after GTX carcinogen exposure it may have a tumour-suppressive function (repressing Ccnd2) leading to cell cycle arrest and to increased DNA repair activities. In addition, compound-specific microRNA-mRNA interactions [mmu-miR-301b-3p-Papss2 (for AFB1), as well as mmu-miR-29b-3p-Col4a2 and mmu-miR-24-3p-Flna (for BaP)] were found to contribute to a better understanding of microRNAs in cell cycle arrest and the impairment of the DNA damage repair, an important hallmark of GTX-induced carcinogenesis. Overall, our results indicate that microRNAs represent yet another relevant intracellular regulatory level in chemical carcinogenesis

Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity

The well-defined battery of in vitro systems applied within chemical cancer risk assessment is often characterised by a high false-positive rate, thus repeatedly failing to correctly predict the in vivo genotoxic and carcinogenic properties of test compounds. Toxicogenomics, i.e. mRNA-profiling, has been proven successful in improving the prediction of genotoxicity in vivo and the understanding of underlying mechanisms. Recently, microRNAs have been discovered as post-transcriptional regulators of mRNAs. It is thus hypothesised that using microRNA response-patterns may further improve current prediction methods. This study aimed at predicting genotoxicity and non-genotoxic carcinogenicity in vivo, by comparing microRNA-and mRNA-based profiles, using a frequently applied in vitro liver model and exposing this to a range of well-chosen prototypical carcinogens. Primary mouse hepatocytes (PMH) were treated for 24 and 48 h with 21 chemical compounds [genotoxins (GTX) vs. non-genotoxins (NGTX) and non-genotoxic carcinogens (NGTX-C) versus non-carcinogens (NC)]. MicroRNA and mRNA expression changes were analysed by means of Exiqon and Affymetrix microarray-platforms, respectively. Classification was performed by using Prediction Analysis for Microarrays (PAM). Compounds were randomly assigned to training and validation sets (repeated 10 times). Before prediction analysis, pre-selection of microRNAs and mRNAs was performed by using a leave-one-out t-test. No microRNAs could be identified that accurately predicted genotoxicity or non-genotoxic carcinogenicity in vivo. However, mRNAs could be detected which appeared reliable in predicting genotoxicity in vivo after 24 h (7 genes) and 48 h (2 genes) of exposure (accuracy: 90% and 93%, sensitivity: 65% and 75%, specificity: 100% and 100%). Tributylinoxide and para-Cresidine were misclassified. Also, mRNAs were identified capable of classifying NGTX-C after 24 h (5 genes) as well as after 48 h (3 genes) of treatment (accuracy: 78% and 88%, sensitivity: 83% and 83%, specificity: 75% and 93%). Wy-14,643, phenobarbital and ampicillin trihydrate were misclassified. We conclude that genotoxicity and non-genotoxic carcinogenicity probably cannot be accurately predicted based on microRNA profiles. Overall, transcript-based prediction analyses appeared to clearly outperform microRNA-based analyses

Integrating multiple omics to unravel mechanisms of Cyclosporin A induced hepatotoxicity in vitro

In order to improve attrition rates of candidate-drugs there is a need for a better understanding of the mechanisms underlying drug-induced hepatotoxicity. We aim to further unravel the toxicological response of hepatocytes to a prototypical cholestatic compound by integrating transcriptomic and metabonomic profiling of HepG2 cells exposed to Cyclosporin A. Cyclosporin A exposure induced intracellular cholesterol accumulation and diminished intracellular bile acid levels. Performing pathway analyses of significant mRNAs and metabolites separately and integrated, resulted in more relevant pathways for the latter. Integrated analyses showed pathways involved in cell cycle and cellular metabolism to be significantly changed. Moreover, pathways involved in protein processing of the endoplasmic reticulum, bile acid biosynthesis and cholesterol metabolism were significantly affected. Our findings indicate that an integrated approach combining metabonomics and transcriptomics data derived from representative in vitro models, with bioinformatics can improve our understanding of the mechanisms of action underlying drug-induced hepatotoxicity. Furthermore, we showed that integrating multiple omics and thereby analyzing genes, microRNAs and metabolites of the opposed model for drug-induced cholestasis can give valuable information about mechanisms of drug-induced cholestasis in vitro and therefore could be used in toxicity screening of new drug candidates at an early stage of drug discovery

Hepatotoxicity Screening on In Vitro Models and the Role of 'Omics

The liver is one of the five most common target organs of toxicity, both during acute and chronic (repeated dose) toxicity, not only for drugs but also for cosmetic ingredients. Chemical entities can trigger liver damage in humans, and hepatotoxicity is the leading cause of withdrawal of drugs from the market, accounting for 40% of withdrawals worldwide. It has been estimated that only 50% of human liver toxicities could be predicted using animal models, and there is a clear need for accurately predictive toxicity and safety testing methods. Hepatocellular injury can manifest in a number of ways, including hepatitis, steatosis, cirrhosis, inflammation, phospholipidosis, and cholestasis. Cholestasis and steatosis are among the most prominent and well-documented types of liver injury and are the focus of this chapter. Furthermore, attention is also paid to necrosis, a mode of cell death that is observed in most of the aforementioned types of hepatocellular injury