Understanding the Link between Inflammasome and Apoptosis through the Response of THP-1 Cells against Drugs Using Droplet-Based Microfluidics.

Droplet-based microfluidic devices are used to investigate monocytic THP-1 cells in response to drug administration. Consistent and reproducible droplets are created, each of which acts as a bioreactor to carry out single cell experiments with minimized contamination and live cell tracking under an inverted fluorescence microscope for more than 2 days. Here, the effects of three different drugs (temsirolimus, rifabutin, and BAY 11-7082) on THP-1 are examined and the results are analyzed in the context of the inflammasome and apoptosis relationship. The ASC adaptor gene tagged with GFP is monitored as the inflammasome reporter. Thus, a systematic way is presented for deciphering cell-to-cell heterogeneity, which is an important issue in cancer treatment. The drug temsirolimus, which has effects of disrupting the mTOR pathway and triggering apoptosis in tumor cells, causes THP-1 cells to express ASC and to be involved in apoptosis. Treatment with rifabutin, which inhibits proliferation and initiates apoptosis in cells, affects ASC expression by first increasing and then decreasing it. CASP-3, which has a role in apoptosis and is directly related to ASC, has an increasing level in inflammasome conditioning. Thus, the cell under the effect of rifabutin might be faced with programmed cell death faster. The drug BAY 11-7082, which is responsible for NFκB inhibition, shows similar results to temsirolimus with more than 60% of cells having high fluorescence intensity (ASC expression). The microfluidic platform presented here offers strong potential for studying newly developed small-molecule inhibitors for personalized/precision medicine.

Real-Time Single-Cell Monitoring of Drug Effects Using Droplet-Based Microfluidic Technology: A Proof-of-Concept Study.

Drugs that act on ribosome biogenesis and cell proliferation play important roles in treatment of human diseases. Moreover, measurement of drug effects at a single-cell level would create vast opportunities for pharmaceutical innovation. We present in this study an original proof-of-concept study of single-cell measurement of drug effects with a focus on inhibition of ribosome biogenesis and cell proliferation, and using yeast (Saccharomyces cerevisiae) as a model eukaryotic organism. We employed a droplet-based microfluidic technology and nucleolar protein-tagged strain of the yeast for real-time monitoring of the cells. We report a comprehensive account of the ways in which interrelated pathways are impacted by drug treatment in a single-cell level. Self-organizing maps, transcription factor, and Gene Ontology enrichment analyses were utilized to these ends. This article makes a contribution to advance single-cell measurement of drug effects. We anticipate the microfluidic technology platform presented herein is well poised for future applications in personalized/precision medicine research as well as in industrial settings for drug discovery and clinical development. In addition, the study offers new insights on ribosome biogenesis and cell proliferation that should prove useful in cancer research and other complex human diseases impacted by these key cellular processes.

A Drug Repurposing and Protein-Protein Interaction Network Study of Ribosomopathies Using Yeast as a Model System.

Ribosomopathies result in various cancers, neurodegenerative and viral diseases, and other pathologies such as Diamond-Blackfan anemia and Shwachman-Diamond syndrome. Their pathophysiology at a proteome and functional level remains to be determined. Protein networks and highly connected hub proteins for ribosome biogenesis in Saccharomyces cerevisiae offer a potential as a model system to inform future therapeutic innovation in ribosomopathies. In this context, we report a ribosome biogenesis protein-protein interaction network in S. cerevisiae, created with 1772 proteins and 22,185 physical interactions connecting them. Moreover, by network decomposition analysis, we determined the linear pathways between the transcription factors and target proteins with a view to drug repurposing. While considering only the paths containing the three C/D box proteins (Nop56, Nop58, and Nop1), the most frequently encountered proteins were Aft1, Htz1, Ssa1, Ssb1, Ssb2, Gcn5, Cka1, Tef1, Nop1, Cdc28, Act1, Krr1, Rpl8B, and Tor1, which were then identified as potential drug targets. For drug repurposing, these candidate proteins were further searched in the DrugBank to find other diseases associated with them, as well as the drugs used to treat these diseases. To support the computational results, an experimental study was conducted using in-house manufactured microfluidic bioreactor platform, while the effect of the drug temsirolimus, Tor1 inhibitor, on yeast cells was investigated by following Nop56 protein expression. In conclusion, these results inform the ways in which ribosomopathies and associated common complex human diseases materialize and how drug repurposing might accelerate therapeutic innovation through bioinformatic studies of yeast.