Biology subjects

Mullers, E.

Publications and source records attributed to Mullers, E..

4 recordsLinked to original sources

bioRxiv2023

Diseased human pancreas and liver microphysiological system for preclinical diabetes research

Current research on metabolic disorders such as type 2 diabetes relies on animal models because multi-organ diseases cannot be well studied with the standard in vitro assays. Here, we connect models of key metabolism organs, pancreas and liver, on a microfluidic chip to enable diabetes research in a human-based preclinical system. Aided by mechanistic mathematical modelling, we developed a two-organ microphysiological system (MPS) that replicates clinically-relevant phenotypes of diabetic dysregulation both in the liver and pancreas compartments. Exposure to hyperglycemia and high cortisone created a diseased pancreas-liver MPS which displayed beta-cell dysfunction, steatosis, elevated ketone-body secretion, increased glycogen storage, and upregulated gluconeogenic machinery. In turn, normoglycemia and physiological cortisone concentration maintained glucose tolerance and stable liver and beta-cell functions. This method was evaluated for repeatability in two laboratories and was effective in multiple pancreatic islet donors. The model also provides a platform to identify new therapeutic targets as demonstrated with a liver-secreted IL-1R2 protein that induced islet proliferation.

cell biology↗

bioRxiv2023

Cell Painting-based bioactivity prediction boosts high-throughput screening hit-rates and compound diversity

Efficiently identifying bioactive compounds towards a target of interest remains a time- and resource-intensive task in early drug discovery. The ability to accurately predict bioactivity using morphological profiles has the potential to rationalize the process, enabling smaller screens of focused compound sets. Towards this goal, we explored the application of deep learning with Cell Painting, a high-content image-based assay, for compound bioactivity prediction in early drug screening. Combining Cell Painting data and unrefined single-concentration activity readouts from high-throughput screening (HTS) assays, we investigated to what degree morphological profiles could predict compound activity across a set of 140 unique assays. We evaluated the performance of our models across different target classes, assay technologies, and disease areas. The predictive performance of the models was high, with a tendency for better predictions on cell-based assays and kinase targets. The average ROC-AUC was 0.744 with 62% of assays reaching [≥]0.7, 30% reaching [≥]0.8 and 7% reaching [≥]0.9 average ROC-AUC, outperforming commonly used structure-based predictions in terms of predictive performance and compound structure diversity. In many cases, bioactivity prediction from Cell Painting data could be matched using brightfield images rather than multichannel fluorescence images. Experimental validation of our predictions in follow-up assays confirmed enrichment of active compounds. Our results suggest that models trained on Cell Painting data can predict compound activity in a range of high-throughput screening assays robustly, even with relatively noisy HTS assay data. With our approach, enriched screening sets with higher hit rates and higher hit diversity can be selected, which could reduce the size of HTS campaigns and enable primary screening with more complex assays.

bioinformatics↗

bioRxiv2022

Cell morphological profiling enables high-throughput screening for PROteolysis TArgeting Chimera (PROTAC) phenotypic signature

PROTACs (PROteolysis TArgeting Chimeras) use the ubiquitin-proteasome system to degrade a protein of interest for therapeutic benefit. Advances in targeted protein degradation technology have been remarkable with several molecules moving into clinical studies. However, robust routes to assess and better understand the safety risks of PROTACs need to be identified, which is an essential step towards delivering efficacious and safe compounds to patients. In this work, we used Cell Painting, an unbiased high content imaging method, to identify phenotypic signatures of PROTACs. Chemical clustering and model prediction allowed the identification of a mitotoxicity signature that could not be expected by screening the individual PROTAC components. The data highlighted the benefit of unbiased phenotypic methods for identifying toxic signatures and the potential to impact drug design. HighlightsO_LIMorphological profiling detects various PROTACs phenotypic signatures C_LIO_LIPhenotypic signatures can be attributed to diverse biological responses C_LIO_LIChemical clustering from phenotypic signatures separates on drug selection C_LIO_LITrained in-silico machine learning models to predict PROTACs mitochondrial toxicity C_LI

pharmacology and toxicology↗

bioRxiv2017

Cyclin A2 localises in the cytoplasm at the S/G2 transition to activate Plk1

Cyclin A2 is a key regulator of the cell cycle, implicated both in DNA replication and mitotic entry. Cyclin A2 participates in feedback loops that activate mitotic kinases in G2-phase, but why active Cyclin A2-CDK2 during S phase does not trigger mitotic kinase activation remains unclear. Here we describe a change in localisation of Cyclin A2 from being only nuclear to both nuclear and cytoplasmic at the S/G2 border. We find that Cyclin A2-CDK2 can activate the mitotic kinase PLK1 through phosphorylation of Bora, and that only cytoplasmic Cyclin A2 interacts with Bora and PLK1. Expression of predominately cytoplasmic Cyclin A2 or phospho-mimicking PLK1 T210D can partially rescue a G2 arrest caused by Cyclin A2 depletion. Cytoplasmic presence of Cyclin A2 is restricted by p21, in particular after DNA damage. Cyclin A2 chromatin association during DNA replication and additional mechanisms contribute to Cyclin A2 localisation change in G2 phase. We find no evidence that such mechanisms involve G2 feedback loops and suggest that cytoplasmic appearance of Cyclin A2 at the S/G2 transition functions as a trigger for mitotic kinase activation. SynopsisMain mitotic kinases as PLK1 are activated at the S/G2 transition. A change in Cyclin A2 localisation at the S/G2 transition enables activation of PLK1. Main points-Cyclin A2 appears in the cytoplasm at the S/G2 transition -Association with replicating chromatin and p21 restricts Cyclin A2 to the nucleus -DNA damage ensures nuclear Cyclin A2 through p21 -Cytoplasmic Cyclin A2 initiates PLK1 activation Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC="FIGDIR/small/191437v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@7e7e82org.highwire.dtl.DTLVardef@a3c9aforg.highwire.dtl.DTLVardef@10e11edorg.highwire.dtl.DTLVardef@baf6bd_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗