Incorporating Metabolic Competence into High-Throughput Profiling Assays

High-throughput profiling assays such as high-throughput phenotypic profiling (HTPP) with Cell Painting and high-throughput transcriptomics (HTTr) with TempO-Seq have been used to characterize the bioactivity and potential hazards associated with large inventories of chemicals. Although both methods offer broad coverage of molecular targets, a limitation is that the cell types used in these in vitro assays typically lack the xenobiotic metabolism capabilities of humans or laboratory animals used for in vivo testing. To address this limitation, this proof-of-concept study coupled the Alginate Immobilization of Metabolic Enzymes (AIME) platform to both assays and evaluated the impact of metabolism on chemical bioactivity in a breast cancer cell line, VM7Luc4E2. HTPP detected concentration-dependent increases in chemical bioactivity corresponding to increased estrogen receptor (ER) activation measured using an ER transactivation assay (ERTA) that had been previously coupled to the AIME platform in VM7Luc4E2 cells. Additionally, HTTr detected a greater number of active genes in the metabolic condition associated with increased ER activation. This corresponded to a greater number of active ER high-confidence (ERHC) gene signatures and/or metabolism-induced shifts in ERHC signature enrichment as a transcriptomic readout of ER activity. This study demonstrates that the high-throughput profiling assays can detect changes in chemical bioactivity between parent compounds and metabolites generated using the AIME platform in a reproducible way. Incorporating metabolic competence into high-throughput profiling assays will better inform next-generation risk assessment by capturing potential metabolite-based changes in bioactivity of test chemicals that may be missed by current screening approaches.