42 research outputs found

    Predictive toxicology using systemic biology and liver microfluidic "on chip" approaches: Application to acetaminophen injury

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    International audienceWe have analyzed transcriptomic, proteomic and metabolomic profiles of hepatoma cells cultivated inside a microfluidic biochip with or without acetaminophen (APAP). Without APAP, the results show an adaptive cellular response to the microfluidic environment, leading to the induction of anti-oxidative stress and cytoprotective pathways. In presence of APAP, calcium homeostasis perturbation, lipid peroxidation and cell death are observed. These effects can be attributed to APAP metabolism into its highly reactive metabolite. N-acetyl-p-benzoquinone imine (NAPQI). That toxicity pathway was confirmed by the detection of GSH-APAP, the large production of 2-hydroxybutyrate and 3-hydroxybutyrate, and methionine, cystine, and histidine consumption in the treated biochips. Those metabolites have been reported as specific biomarkers of hepatotoxicity and glutathione depletion in the literature. In addition, the integration of the metabolomic, transcriptomic and proteomic collected profiles allowed a more complete reconstruction of the APAP injury pathways. To our knowledge, this work is the first example of a global integration of microfluidic biochip data in toxicity assessment. Our results demonstrate the potential of that new approach to predictive toxicology

    Drug discovery for remyelination and treatment of MS

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    Investigation of ifosfamide and chloroacetaldehyde renal toxicity through integration of in vitro liver–kidney microfluidic data and pharmacokinetic-system biology models

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    We have integrated in vitro and in silico data to describe the toxicity of chloroacetaldehyde (CAA) on renal cells via its production from the metabolism of ifosfamide (IFO) by hepatic cells. A pharmacokinetic (PK) model described the production of CAA by the hepatocytes and its transport to the renal cells. A system biology model was coupled to the PK model to describe the production of reactive oxygen species (ROS) induced by CAA in the renal cells. In response to the ROS production, the metabolism of glutathione (GSH) and its depletion were modeled by the action of an NFE2L2 gene-dependent pathway. The model parameters were estimated in a Bayesian context via Markov Chain Monte Carlo (MCMC) simulations based on microfluidic experiments and literature in vitro data. Hepatic IFO and CAA in vitro intrinsic clearances were estimated to be 1.85 x 10-9 μL s–1 cell–1 and 0.185 x 10-9 μL s–1 cell–1,respectively (corresponding to an in vivo intrinsic IFO clearance estimate of 1.23 l h–1, to be compared to IFO published values ranging from 3 to 10 l h–1). After model calibration, simulations made at therapeutic doses of IFO showed CAA renal intracellular concentrations ranging from 11 to 131 μM. Intracellular CAA concentrations above 70 μM induced intense ROS production and GSH depletion. Those responses were time and dose dependent, showing transient and non-linear kinetics. Those results are in agreement with literature data reporting that intracellular CAA toxic concentrations range from 35 to 320 μM, after therapeutic ifosfamide dosing. The results were also consistent with in vitro CAA renal cytotoxicity data

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    Metabolomics-on-a-chip of hepatotoxicity induced by anticancer drug flutamide and its active metabolite hydroxyflutamide using HepG2/C3a microfluidic biochips

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    International audienceWe used the recently introduced "metabolomics-on-a-chip" approach to test secondary drug toxicity in bioartificial organs. Bioartificial organs cultivated in microfluidic culture conditions provide a beneficial environment, in which the cellular cytoprotective mechanisms are enhanced, compared with Petri dish culture conditions. We investigated the metabolic response of HepG2/C3a cells exposed to flutamide, an anticancer prodrug, and hydroxyflutamide (HF), its active metabolite, in a microfluidic biochip. The cellular response was analyzed by (1)H nuclear magnetic resonance spectroscopy to identify cell-specific molecule-response markers. The metabolic response to flutamide results in a disruption of glucose homeostasis and in mitochondrial dysfunctions. This flutamide-specific metabolic response was illustrated by a reduction of the extracellular glucose and fructose consumptions and a general reduction of the tricarboxylic acid cycle activity leading to the reduction of the consumption of several amino acids. We also found a higher production of 3-hydroxybutyrate and lactate, and the reduction of the albumin production compared with controls. The toxic metabolic signature associated with the active metabolite HF was illustrated by a high-energy demand and an increase in several amino acid metabolism. Finally, for both molecules, the hepatotoxicity was correlated to the glutathione (GSH) metabolism illustrated by the levels of the 2-hydroxybutyrate and pyroglutamate productions and the increase of the glutamate and glycine productions. Thus, the entire set of results contributed to extract specific mechanistic toxic signatures and their relation to hepatotoxicity, which appeared consistent with literature reports. As new finding of HepG2/C3a cells hepatotoxicity, we propose a metabolic network with a related list of metabolite variations to describe the GSH depletion when followed by a cell death for the HepG2/C3a cells cultivated in our polydimethylsiloxane microfluidic biochips. Our findings illustrate the potential of metabolomics-on-a-chip as an in vitro alternative method for predictive toxicology

    Investigation of ifosfamide nephrotoxicity induced in a liver-kidney co-culture biochip.

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    International audienceIn this article, we present a liver-kidney co-culture model in a micro fluidic biochip. The liver was modeled using HepG2/C3a and HepaRG cell lines and the kidney using MDCK cell lines. To demonstrate the synergic interaction between both organs, we investigated the effect of ifosfamide, an anticancerous drug. Ifosfamide is a prodrug which is metabolized by the liver to isophosforamide mustard, an active metabolite. This metabolism process also leads to the formation of chloroacetaldehyde, a nephrotoxic metabolite and acrolein a urotoxic one. In the biochips of MDCK cultures, we did not detect any nephrotoxic effects after 72 h of 50 µM ifosfamide exposure. However, in the liver-kidney biochips, the same 72 h exposure leads to a nephrotoxicity illustrated by a reduction of the number of MDCK cells (up to 30% in the HepaRG-MDCK) when compared to untreated co-cultures or treated MDCK monocultures. The reduction of the MDCK cell number was not related to a modification of the cell cycle repartition in ifosfamide treated cases when compared to controls. The ifosfamide biotransformation into 3-dechloroethylifosfamide, an equimolar byproduct of the chloroacetaldehyde production, was detected by mass spectrometry at a rate of apparition of 0.3 ± 0.1 and 1.1 ± 0.3 pg/h/biochips in HepaRG monocultures and HepaRG-MDCK co-cultures respectively. Any metabolite was detected in HepG2/C3a cultures. Furthermore, the ifosfamide treatment in HepaRG-MDCK co-culture system triggered an increase in the intracellular calcium release in MDCK cells on contrary to the treatment on MDCK monocultures. As 3-dechloroethylifosfamide is not toxic, we have tested the effect of equimolar choloroacetaldehyde concentration onto the MDCK cells. At this concentration, we found a quite similar calcium perturbation and MDCK nephrotoxicity via a reduction of 30% of final cell numbers such as in the ifosfamide HepaRG-MDCK co-culture experiments. Our results suggest that ifosfamide nephrotoxicity in a liver-kidney micro fluidic co-culture model using HepaRG-MDCK cells is induced by the metabolism of ifosfamide into chloroacetaldehyde whereas this pathway is not functional in HepG2/C3a-MDCK model. This study demonstrates the interest in the development of systemic organ-organ interactions using micro fluidic biochips. It also illustrated their potential in future predictive toxicity model using in vitro models as alternative methods
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