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Multiple aspects of the local extracellular environment profoundly affect cell phenotype and function. Physical and chemical cues in the environment trigger intracellular signaling cascades that ultimately activate transcription factors (TFs) - powerful regulators of the cell phenotype. TRACER (TRanscriptional Activity CEll aRrays) was employed for large-scale, dynamic quantification of TF activity in human fibroblasts cultured on hydrogels with a controlled elastic modulus and integrin ligand density. We identified three groups of TFs: responders to alterations in ligand density alone, substrate stiffness or both. Dynamic networks of regulatory TFs were constructed computationally and revealed distinct TF activity levels, directionality (i.e., activation or inhibition), and dynamics for adhesive and mechanical cues. Moreover, TRACER networks predicted conserved hubs of TF activity across multiple cell types, which are significantly altered in clinical fibrotic tissues. Our approach captures the distinct and overlapping effects of adhesive and mechanical stimuli, identifying conserved signaling mechanisms in normal and disease states.

Tissue development and disease progression are multi-stage processes controlled by an evolving set of key regulatory factors, and identifying these factors necessitates a dynamic analysis spanning relevant time scales. Current omics approaches depend on incomplete biological databases to identify critical cellular processes. Herein, we present TRACER (TRanscriptional Activity CEll aRrays), which was employed to quantify the dynamic activity of numerous transcription factor (TFs) simultaneously in 3D and networks for TRACER (NTRACER), a computational algorithm that allows for cellular rewiring to establish dynamic regulatory networks based on activity of TF reporter constructs. We identified major hubs at various stages of culture associated with normal and abnormal tissue growth (i.e., ELK-1 and E2F1, respectively) and the mechanism of action for a targeted therapeutic, lapatinib, through GATA-1, which were confirmed in human ErbB2 positive breast cancer patients and human ErbB2 positive breast cancer cell lines that were either sensitive or resistant to lapatinib.

Live-cell assays to measure cellular function performed within 3D cultures have the potential to elucidate the underlying processes behind disease progression and tissue formation. Cells cultured in 3D interact and remodel their microenvironment and can develop into complex structures. We have developed a transcription factor (TF) activity array that uses bioluminescence imaging (BLI) of lentiviral delivered luminescent reporter constructs that allows for the non-invasive imaging of TF activity in both 2D and 3D culture. Imaging can be applied repeatedly throughout culture to capture dynamic TF activity, though appropriate normalization is necessary. We investigated in-well normalization using Gaussia or Renilla luciferase, and external well normalization using firefly luciferase. Gaussia and Renilla luciferase were each unable to provide consistent normalization for long-term measurement of TF activity. However, external well normalization provided low variability and accounted for changes in cellular dynamics. Using external normalization, dynamic TF activities were quantified for five TFs. The array captured expected changes in TF activity to stimuli, however the array also provided dynamic profiles within 2D and 3D that have not been previously characterized. The development of the technology to dynamically track TF activity within cells cultured in both 2D and 3D can provide greater understanding of complex cellular processes., (Copyright © 2012 Wiley Periodicals, Inc.)

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, non-invasive 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., (2010 Wiley Periodicals, Inc.)

Background: Extracellular activation of signal transduction pathways and their downstream target transcription factors (TFs) are critical regulators of cellular processes and tissue development. The intracellular signaling network is complex, and techniques that quantify the activities of numerous pathways and connect their activities to the resulting phenotype would identify the signals and mechanisms regulating tissue development. The ability to investigate tissue development should capture the dynamic pathway activity and requires an environment that supports cellular organization into structures that mimic in vivo phenotypes. Taken together, our objective was to develop cellular arrays for dynamic, large-scale quantification of TF activity as cells organized into spherical structures within 3D culture., Methodology/principal Findings: TF-specific and normalization reporter constructs were delivered in parallel to a cellular array containing a well-established breast cancer cell line cultured in Matrigel. Bioluminescence imaging provided a rapid, non-invasive, and sensitive method to quantify luciferase levels, and was applied repeatedly on each sample to monitor dynamic activity. Arrays measuring 28 TFs identified up to 19 active, with 13 factors changing significantly over time. Stimulation of cells with β-estradiol or activin A resulted in differential TF activity profiles evolving from initial stimulation of the ligand. Many TFs changed as expected based on previous reports, yet arrays were able to replicate these results in a single experiment. Additionally, arrays identified TFs that had not previously been linked with activin A., Conclusions/significance: This system provides a method for large-scale, non-invasive, and dynamic quantification of signaling pathway activity as cells organize into structures. The arrays may find utility for investigating mechanisms regulating normal and abnormal tissue growth, biomaterial design, or as a platform for screening therapeutics.