Liver-Kidney-on-Chip To Study Toxicity of Drug Metabolites.

Advances in organ-on-chip technologies for the application in in vitro drug development provide an attractive alternative approach to replace ethically controversial animal testing and to establish a basis for accelerated drug development. In recent years, various chip-based tissue culture systems have been developed, which are mostly optimized for cultivation of one single cell type or organoid structure and lack the representation of multi organ interactions. Here we present an optimized microfluidic chip design consisting of interconnected compartments, which provides the possibility to mimic the exchange between different organ specific cell types and enables to study interdependent cellular responses between organs and demonstrate that such tandem system can greatly improve the reproducibility and efficiency of toxicity studies. In a simplified liver-kidney-on-chip model, we showed that hepatic cells that grow in microfluidic conditions abundantly and stably expressed metabolism-related biomarkers. Moreover, we applied this system for investigating the biotransformation and toxicity of Aflatoxin B1 (AFB1) and Benzoalphapyrene (BαP), as well as the interaction with other chemicals. The results clearly demonstrate that the toxicity and metabolic response to drugs can be evaluated in a flow-dependent manner within our system, supporting the importance of advanced interconnected multiorgans in microfluidic devices for application in in vitro toxicity testing and as optimized tissue culture systems for in vitro drug screening.

Molecular insights into reprogramming-initiation events mediated by the OSKM gene regulatory network.

Somatic cells can be reprogrammed to induced pluripotent stem cells by over-expression of OCT4, SOX2, KLF4 and c-MYC (OSKM). With the aim of unveiling the early mechanisms underlying the induction of pluripotency, we have analyzed transcriptional profiles at 24, 48 and 72 hours post-transduction of OSKM into human foreskin fibroblasts. Experiments confirmed that upon viral transduction, the immediate response is innate immunity, which induces free radical generation, oxidative DNA damage, p53 activation, senescence, and apoptosis, ultimately leading to a reduction in the reprogramming efficiency. Conversely, nucleofection of OSKM plasmids does not elicit the same cellular stress, suggesting viral response as an early reprogramming roadblock. Additional initiation events include the activation of surface markers associated with pluripotency and the suppression of epithelial-to-mesenchymal transition. Furthermore, reconstruction of an OSKM interaction network highlights intermediate path nodes as candidates for improvement intervention. Overall, the results suggest three strategies to improve reprogramming efficiency employing: 1) anti-inflammatory modulation of innate immune response, 2) pre-selection of cells expressing pluripotency-associated surface antigens, 3) activation of specific interaction paths that amplify the pluripotency signal.

LitInspector: literature and signal transduction pathway mining in PubMed abstracts.

LitInspector is a literature search tool providing gene and signal transduction pathway mining within NCBI's PubMed database. The automatic gene recognition and color coding increases the readability of abstracts and significantly speeds up literature research. A main challenge in gene recognition is the resolution of homonyms and rejection of identical abbreviations used in a 'non-gene' context. LitInspector uses automatically generated and manually refined filtering lists for this purpose. The quality of the LitInspector results was assessed with a published dataset of 181 PubMed sentences. LitInspector achieved a precision of 96.8%, a recall of 86.6% and an F-measure of 91.4%. To further demonstrate the homonym resolution qualities, LitInspector was compared to three other literature search tools using some challenging examples. The homonym MIZ-1 (gene IDs 7709 and 9063) was correctly resolved in 87% of the abstracts by LitInspector, whereas the other tools achieved recognition rates between 35% and 67%. The LitInspector signal transduction pathway mining is based on a manually curated database of pathway names (e.g. wingless type), pathway components (e.g. WNT1, FZD1), and general pathway keywords (e.g. signaling cascade). The performance was checked for 10 randomly selected genes. Eighty-two per cent of the 38 predicted pathway associations were correct. LitInspector is freely available at http://www.litinspector.org/.