Tools for drug discovery and molecular bioprocessing
Nature owes its unparalleled structural and functional diversity to the power of enzymes and multi-enzyme pathways that comprise the synthetic machinery of biological systems. Mankind has only been able to tap into a small part of this biocatalytic repertoire, yet this has resulted in a vast array of natural products for use as pharmaceuticals, agrochemicals, chemical intermediates, and biomaterials. Nevertheless, a significantly larger and more diverse universe of natural compounds, as well as the enzymes and metabolic pathways that generate such molecules, remains untapped. We are combining the fields of biocatalysis, bioinformatics, metabolic engineering, and high-throughput combinatorial biosynthesis with microsystems engineering to form a new area of fundamental and applied research. This new area, called "molecular bioprocessing" enables us to join the technologies of combinatorial biosynthesis with high-throughput biocatalytic technologies, which allow access to nature's "warehouse" of structures and functions, and to be able to manipulate the synthesis of these molecules to yield novel compounds and materials for use in the pharmaceutical, chemical, and agrochemical industries.
Drug Toxicity Screening Platform
We have developed new tools to interrogate the effects of small molecules on biological function (Figure DD-1). These include cell- and protein-based high-throughput screening1-4, on chip immunoassays3-6 and high-throughput biocatalysis on a microarray platform7. With respect to the cell-based screening platform, we have developed (in collaboration with Doug Clark’s group at UC Berkeley) a miniaturized three-dimensional (3D) cellular array chip (the DataChip, Figure DD-2) that has been used for in vitro toxicological assessment of drug candidates and other chemicals in high-throughput. Although recent emphasis has been placed on understanding cellular metabolism in 3D, relatively little effort has been spent using 3D cultures to study cytotoxicity, particularly at very small volumes consistent with high-throughput screening. Furthermore, we have recently begun to investigate the toxicity of compounds on human stem and progenitor cells in comparison to their differentiated progeny3-5.
Figure DD-1. New high-throughput tools being developed. Upper left is the DataChip (Data Analysis Toxicology Assay Chip) for high throughput 3D cell culture screens. Upper right is the MetaChip (Metabolizing Enzyme Assay Chip for high-throughput interrogation of enzyme function. In this case, CYP450 inhibition assays7. Lower left is a modification of the DataChip to enable on-chip, in-cell immunofluorescence assays and quantitative analysis of protein expression levels within cells6. Lower right is a schematic of an Artificial Golgi, which includes an image of a digital microfluidic device.
Figure DD-2. The DataChip. Upper left represents the hemispherical spots generated by microarray spotting of cells in alginate solution, which upon contact with poly-L-lysine and BaCl2 results in nearly immediate gelation. The cells grow well up to 5 days in culture (upper right). Lower left shows an actual image of a stained DataChip (live-dead assay) and representative dose response curves for drug candidates and chemicals in the presence or absence of metabolizing enzymes contained within a MetaChip and stamped on top of the DataChip. Lower right is the output of the on-chip, in-cell immunofluorescence assay. The dose response to an activator of Hif-1α in a pancreatic tumor cell line (triangles represent standard Western blotting analysis on mL scale and open squares represent the on-chip immunofluorescence assay in volumes as low as 30-nL).
Most recently, we have developed a novel chip design that enables interrogation of differential expression of various drug-metabolizing enzymes (DMEs) in the human liver. Such information is relevant to inter-individual variability in drug pharmacokinetic profiles, drug efficacy and toxicity. Specifically, we developed the “Transfected Enzyme and Metabolism Chip” (TeamChip), which predicts potential metabolism-induced drug or drug-candidate toxicity8. The TeamChip is prepared by delivering genes into miniaturized three-dimensional cellular microarrays on a micropillar chip using recombinant adenoviruses in a complementary microwell chip (Figure DD-3). The device enables users to manipulate the expression of individual and multiple human metabolizing-enzyme genes (such as CYP3A4, CYP2D6, CYP2C9, CP1A2, CYP2E1, and UGT1A4) in THLE-2 cell microarrays. To identify specific enzymes involved in drug detoxification, we created 84 combinations of metabolic-gene expressions in a combinatorial fashion on a single microarray (Figure DD-4). Thus, the TeamChip platform can provide critical information necessary for evaluating metabolism-induced toxicity in a high-throughput manner.
Figure DD-3. TeamChip schematics and photographs. (a) Micropillar/microwell chip components in relation to a standard glass microscope slide. (b) The micropillar chip containing THLE-2 cells encapsulated in matrigel droplets. (c) The microwell chip containing recombinant adenoviruses carrying genes for drug-metabolizing enzymes (the red color indicates the no-virus control and the two colors represent different viruses). (d) Stamping of the micropillar/microwell chips for drug-metabolizing gene expression. (e) Experimental procedure for use of the TeamChip.
Figure DD-4. Effects of combinatorial expression of human drug-metabolizing enzymes on the toxicity of tamoxifen. (a) Layout of the microwell chip containing 84 combinations of multiple recombinant adenoviruses (three sets of recombinant adenoviruses dispensed sequentially) to prepare the TeamChip for high-throughput gene transduction, and an additional microwell chip containing 200 mM tamoxifen for metabolism-induced toxicity screening. (b) Scanned image of THLE-2 cells expressing 84 combinations of multiple drug-metabolizing enzymes on the chip exposed to 200 mM tamoxifen for 48 h (top) and normalized THLE-2 cell viability at different drug-metabolizing enzyme expression levels (bottom). The viability of multiple drug-metabolizing enzyme-expressing THLE-2 cells exposed to tamoxifen was normalized by the fluorescent intensity of THLE-2 cells incubated in the absence of compound. The least toxic region in the scanned image is highlighted in a yellow box, and the red circle in the graph designates normalized THLE-2 cell viability calculated from the least toxic region that involved the combination of CYP1A2 and UGT1A4.
- M.-Y. Lee, R.A. Kumar, S.M. Sukumaran, M.G. Hogg, D.S. Clark, and J.S. Dordick (2008), “Three-dimensional cellular microarray for high-throughput toxicology assays”, Proc. Natl. Acad. Sci. USA 105, 59-63.
- M.-Y. Lee, C.-B. Park, J.S. Dordick, and D.S. Clark (2005), “Metabolizing enzyme toxicology assay chip (MetaChip) for high-throughput microscale toxicity analyses”, Proc. Natl. Acad. Sci. USA 102, 983-987. Cover Article.
- L. Meli, H.S.C. Barbosa, A. M. Hickey, L. Gasimli, G. Nierode, M. M. Diogo, R. J. Linhardt, J. M. S. Cabral, and J. S. Dordick. (2014), “Three-dimensional cellular microarray platform for human neural stem cell differentiation and toxicology,” Stem Cell Res. 13, 36-47.
- G. J. Nierode, B. C. Perea, S. K. McFarland, J. F. Pascoal, D. S. Clark, D. V. Schaffer, and J. S. Dordick. (2016), “High-throughput toxicity and phenotypic screening of 3D human neural progenitor cell cultures on a microarray chip platform,” Stem Cell Rep. 7, 970-982.
- T.G. Fernandes, S.-J. Kwon, M.-Y. Lee, M.M. Diogo, D.S. Clark, J.M.S. Cabral, and J.S. Dordick (2010), “Three-dimensional cell culture microarrays for high-throughput studies of stem cell fate”, Biotechnol. Bioeng. 106, 106-118.
- T.G. Fernandes, S.-J. Kwon, M.-Y. Lee, D.S. Clark, J.M.S. Cabral, and J.S. Dordick (2008), “An on-chip, cell-based microarray immunofluorescence assay for high-throughput analysis of target proteins”, Anal. Chem. 80, 6633-6639.
- S.M. Sukumaran, B. Potsaid, M.-Y. Lee, D.S. Clark, and J.S. Dordick (2009), “Development of a fluorescence based, ultra high-throughput screening platform for nanoliter-scale cytochrome P450 microarrays”, J. Biomol. Screen. 14, 668-678.
- S.J. Kwon, D.W. Lee, D.A. Shah, B. Ku, S.Y. Joon, K. Solanki, J.D. Ryan, D.S. Clark, J.S. Dordick, and M.Y. Lee (2014), "High-throughput and combinatorial gene expression on a chip for metabolism-induced toxicology screening", Nat. Commun. 5, 3739.