Identifying molecular mechanisms or therapeutic targets is typically based on large-scale cellular analysis that measures the abundance of mRNA or protein; however, abundance does not necessarily correlate with activity. We report a method for direct large-scale quantification of active pathways that employs a cellular array with parallel gene delivery of constructs that report pathway activity. The reporter constructs encode luciferase, whose expression is influenced by binding of transcription factors (TFs), which are the downstream targets of signaling pathways. Luciferase levels are quantified by bioluminescence imaging (BLI), which allows for rapid, noninvasive measurements. Activity profiles by BLI of 32 TFs were robust, consistent, and reproducible, and correlated with standard cell lysis techniques. The array identified five TFs with differential activity during phorbol-12-myristate-13-acetate (PMA)-induced differentiation of breast cancer cells. A system for rapid, large-scale, BLI quantification of pathway activity provides an enabling technology for mechanistic studies of cellular responses and processes.

Dynamic systems biology aims to identify the molecular mechanisms governing cell fate decisions through the analysis of living cells. Large scale molecular information from living cells can be obtained from reporter constructs that provide activities for either individual transcription factors or multiple factors binding to the full promoter following CRISPR/Cas9 directed insertion of luciferase. In this report, we investigated the design criteria to obtain reporters that are specific and responsive to transcription factor (TF) binding and the integration of TF binding activity with genetic reporter activity. The design of TF reporters was investigated for the impact of consensus binding site spacing sequence and off-target binding on the reporter sensitivity using a library of 25 SMAD3 activity reporters with spacers of random composition and length. A spacer was necessary to quantify activity changes after TGFβ stimulation. TF binding site prediction algorithms (BEEML, FIMO and DeepBind) were used to predict off-target binding, and nonresponsiveness to a SMAD3 reporter was correlated with a predicted competitive binding of constitutively active p53. The network of activity of the SMAD3 reporter was inferred from measurements of TF reporter library, and connected with large-scale genetic reporter activity measurements. The integration of TF and genetic reporters identified the major hubs directing responses to TGFβ, and this method provided a systems-level algorithm to investigate cell signaling.