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Evaluating biological activity of compounds by transcription factor activity profiling.

ABSTRACT: Assessing the biological activity of compounds is an essential objective of biomedical research. We show that one can infer the bioactivity of compounds by assessing the activity of transcription factors (TFs) that regulate gene expression. Using a multiplex reporter system, the FACTORIAL, we characterized cell response to a compound by a quantitative signature, the TF activity profile (TFAP). We found that perturbagens of biological pathways elicited distinct TFAP signatures in human cells. Unexpectedly, perturbagens of the same pathway all produced identical TFAPs, regardless of where or how they interfered. We found invariant TFAPs for mitochondrial, histone deacetylase, and ubiquitin/proteasome pathway inhibitors; cytoskeleton disruptors; and DNA-damaging agents. Using these invariant signatures permitted straightforward identification of compounds with specified bioactivities among uncharacterized chemicals. Furthermore, this approach allowed us to assess the multiple bioactivities of polypharmacological drugs. Thus, TF activity profiling affords straightforward assessment of the bioactivity of compounds through the identification of perturbed biological pathways.

SUBMITTER: Medvedev A

PROVIDER: S-EPMC6157966 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Evaluating biological activity of compounds by transcription factor activity profiling.

Medvedev Alexander A Moeser Matt M Medvedeva Liubov L Martsen Elena E Granick Alexander A Raines Lydia L Zeng Ming M Makarov Sergei S Houck Keith A KA Makarov Sergei S SS

Science advances 20180926 9

Assessing the biological activity of compounds is an essential objective of biomedical research. We show that one can infer the bioactivity of compounds by assessing the activity of transcription factors (TFs) that regulate gene expression. Using a multiplex reporter system, the FACTORIAL, we characterized cell response to a compound by a quantitative signature, the TF activity profile (TFAP). We found that perturbagens of biological pathways elicited distinct TFAP signatures in human cells. Une ...[more]

PMID: 30263952

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Project description:BackgroundExtracellular 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 findingsTF-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 ?-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/significanceThis 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.

Project description:Mentha species are widely used as food, medicine, spices, and flavoring agents. Thus, chemical composition is an important parameter for assessing the quality of mints. In general, the contents of menthol, menthone, eucalyptol, and limonene comprise one of the major parameters for assessing the quality of commercially important mints. Building further on the phytochemical characterization of the quality of Mentha species, this work was focused on the composition of phenolic compounds in methanolic extracts. Thirteen Mentha species were grown under the same environmental conditions, and their methanolic extracts were subjected to the LC-MS/MS (liquid chromatography-tandem mass spectrometry) profiling of phenolics and the testing their biological activities, i.e., antioxidant and tyrosinase inhibition activities, which are important features for the cosmetic industry. The total phenolic content (TPC) ranged from 14.81 ± 1.09 mg GAE (gallic acid equivalents)/g for Mentha cervina to 58.93. ± 8.39 mg GAE/g for Mentha suaveolens. The antioxidant activity of examined Mentha related with the content of the phenolic compounds and ranged from 22.79 ± 1.85 to 106.04 ± 3.26 mg TE (Trolox equivalents)/g for M. cervina and Mentha x villosa, respectively. Additionally, Mentha pulegium (123.89 ± 5.64 mg KAE (kojic acid equivalents)/g) and Mentha x piperita (102.82 ± 15.16 mg KAE/g) showed a strong inhibition of the enzyme tyrosinase, which is related to skin hyperpigmentation. The most abundant compound in all samples was rosmarinic acid, ranging from 1363.38 ± 8323 to 2557.08 ± 64.21 μg/g. In general, the levels of phenolic acids in all examined mint extracts did not significantly differ. On the contrary, the levels of flavonoids varied within the species, especially in the case of hesperidin (from 0.73 ± 0.02 to 109. 39 ± 2.01 μg/g), luteolin (from 1.84 ± 0.11 to 31.03 ± 0.16 μg/g), and kaempferol (from 1.30 ± 0.17 to 33.68 ± 0.81 μg/g). Overall results indicated that all examined mints possess significant amounts of phenolic compounds that are responsible for antioxidant activity and, to some extent, for tyrosinase inhibition activity. Phenolics also proved to be adequate compounds, together with terpenoids, for the characterization of Mentha sp. Additionally, citrus-scented Mentha x villosa could be selected as a good candidate for the food and pharmaceutical industry, especially due its chemical composition and easy cultivation, even in winter continental conditions.

Project description:BackgroundAn important goal in post-genomic research is discovering the network of interactions between transcription factors (TFs) and the genes they regulate. We have previously reported the development of a supervised-learning approach to TF target identification, and used it to predict targets of 104 transcription factors in yeast. We now include a new sequence conservation measure, expand our predictions to include 59 new TFs, introduce a web-server, and implement an improved ranking method to reveal the biological features contributing to regulation. The classifiers combine 8 genomic datasets covering a broad range of measurements including sequence conservation, sequence overrepresentation, gene expression, and DNA structural properties.Principal findings(1) Application of the method yields an amplification of information about yeast regulators. The ratio of total targets to previously known targets is greater than 2 for 11 TFs, with several having larger gains: Ash1(4), Ino2(2.6), Yaf1(2.4), and Yap6(2.4). (2) Many predicted targets for TFs match well with the known biology of their regulators. As a case study we discuss the regulator Swi6, presenting evidence that it may be important in the DNA damage response, and that the previously uncharacterized gene YMR279C plays a role in DNA damage response and perhaps in cell-cycle progression. (3) A procedure based on recursive-feature-elimination is able to uncover from the large initial data sets those features that best distinguish targets for any TF, providing clues relevant to its biology. An analysis of Swi6 suggests a possible role in lipid metabolism, and more specifically in metabolism of ceramide, a bioactive lipid currently being investigated for anti-cancer properties. (4) An analysis of global network properties highlights the transcriptional network hubs; the factors which control the most genes and the genes which are bound by the largest set of regulators. Cell-cycle and growth related regulators dominate the former; genes involved in carbon metabolism and energy generation dominate the latter.ConclusionPostprocessing of regulatory-classifier results can provide high quality predictions, and feature ranking strategies can deliver insight into the regulatory functions of TFs. Predictions are available at an online web-server, including the full transcriptional network, which can be analyzed using VisAnt network analysis suite.

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Evaluating biological activity of compounds by transcription factor activity profiling.

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Evaluating biological activity of compounds by transcription factor activity profiling.

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