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A yeast one-hybrid and microfluidics-based pipeline to map mammalian gene regulatory networks.

ABSTRACT: The comprehensive mapping of gene promoters and enhancers has significantly improved our understanding of how the mammalian regulatory genome is organized. An important challenge is to elucidate how these regulatory elements contribute to gene expression by identifying their trans-regulatory inputs. Here, we present the generation of a mouse-specific transcription factor (TF) open-reading frame clone library and its implementation in yeast one-hybrid assays to enable large-scale protein-DNA interaction detection with mouse regulatory elements. Once specific interactions are identified, we then use a microfluidics-based method to validate and precisely map them within the respective DNA sequences. Using well-described regulatory elements as well as orphan enhancers, we show that this cross-platform pipeline characterizes known and uncovers many novel TF-DNA interactions. In addition, we provide evidence that several of these novel interactions are relevant in vivo and aid in elucidating the regulatory architecture of enhancers.

SUBMITTER: Gubelmann C

PROVIDER: S-EPMC3779800 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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A yeast one-hybrid and microfluidics-based pipeline to map mammalian gene regulatory networks.

Gubelmann Carine C Waszak Sebastian M SM Isakova Alina A Holcombe Wiebke W Hens Korneel K Iagovitina Antonina A Feuz Jean-Daniel JD Raghav Sunil K SK Simicevic Jovan J Deplancke Bart B

Molecular systems biology 20130806

The comprehensive mapping of gene promoters and enhancers has significantly improved our understanding of how the mammalian regulatory genome is organized. An important challenge is to elucidate how these regulatory elements contribute to gene expression by identifying their trans-regulatory inputs. Here, we present the generation of a mouse-specific transcription factor (TF) open-reading frame clone library and its implementation in yeast one-hybrid assays to enable large-scale protein-DNA inte ...[more]

PMID: 23917988

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Project description:BackgroundSeveral human pathologies, including neoplasia and ischemic cardiovascular diseases, course with an unbalance between oxygen supply and demand (hypoxia). Cells within hypoxic regions respond with the induction of a specific genetic program, under the control of the Hypoxia Inducible Factor (HIF), that mediates their adaptation to the lack of oxygen. The activity of HIF is mainly regulated by the EGL-nine homolog (EGLN) enzymes that hydroxylate the alpha subunit of this transcription factor in an oxygen-dependent reaction. Hydroxylated HIF is then recognized and ubiquitinilated by the product of the tumor suppressor gene, pVHL, leading to its proteosomal degradation. Under hypoxia, the hydroxylation of HIF by the EGLNs is compromised due to the lack of oxygen, which is a reaction cosubstrate. Thus, HIF escapes degradation and drives the transcription of its target genes. Since the progression of the aforementioned pathologies might be influenced by activation of HIF-target genes, development of small molecules with the ability to interfere with the HIF-regulatory machinery is of great interest.ResultsHerein we describe a yeast three-hybrid system that reconstitutes mammalian HIF regulation by the EGLNs and VHL. In this system, yeast growth, under specific nutrient restrictions, is driven by the interaction between the beta domain of VHL and a hydroxyproline-containing HIFalpha peptide. In turn, this interaction is strictly dependent on EGLN activity that hydroxylates the HIFalpha peptide. Importantly, this system accurately preserves the specificity of the hydroxylation reaction toward specific substrates. We propose that this system, in combination with a matched control, can be used as a simple and inexpensive assay to identify molecules that specifically modulate EGLN activity. As a proof of principle we show that two known EGLN inhibitors, dimethyloxaloylglycine (DMOG) and 6-chlor-3-hydroxychinolin-2-carbonic acid-N-carboxymethylamide (S956711), have a profound and specific effect on the yeast HIF/EGLN/VHL system.ConclusionThe system described in this work accurately reconstitutes HIF regulation while preserving EGLN substrate specificity. Thus, it is a valuable tool to study HIF regulation, and particularly EGLN biochemistry, in a cellular context. In addition, we demonstrate that this system can be used to identify specific inhibitors of the EGLN enzymes.

Project description:Gene regulatory networks (GRNs) play a central role in systems biology, especially in the study of mammalian organ development. One key question remains largely unanswered: Is it possible to infer mammalian causal GRNs using observable gene co-expression patterns alone? We assembled two mouse GRN datasets (embryonic tooth and heart) and matching microarray gene expression profiles to systematically investigate the difficulties of mammalian causal GRN inference. The GRNs were assembled based on > 2,000 pieces of experimental genetic perturbation evidence from manually reading > 150 primary research articles. Each piece of perturbation evidence records the qualitative change of the expression of one gene following knock-down or over-expression of another gene. Our data have thorough annotation of tissue types and embryonic stages, as well as the type of regulation (activation, inhibition and no effect), which uniquely allows us to estimate both sensitivity and specificity of the inference of tissue specific causal GRN edges. Using these unprecedented datasets, we found that gene co-expression does not reliably distinguish true positive from false positive interactions, making inference of GRN in mammalian development very difficult. Nonetheless, if we have expression profiling data from genetic or molecular perturbation experiments, such as gene knock-out or signalling stimulation, it is possible to use the set of differentially expressed genes to recover causal regulatory relationships with good sensitivity and specificity. Our result supports the importance of using perturbation experimental data in causal network reconstruction. Furthermore, we showed that causal gene regulatory relationship can be highly cell type or developmental stage specific, suggesting the importance of employing expression profiles from homogeneous cell populations. This study provides essential datasets and empirical evidence to guide the development of new GRN inference methods for mammalian organ development.

Dataset Information

A yeast one-hybrid and microfluidics-based pipeline to map mammalian gene regulatory networks.

Publications

A yeast one-hybrid and microfluidics-based pipeline to map mammalian gene regulatory networks.

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