Dataset Information

Regulatory Targets of the Response Regulator RR_1586 from Clostridioides difficile Identified Using a Bacterial One-Hybrid Screen.

ABSTRACT: The Clostridioides difficile R20291 genome encodes 57 response regulator proteins that, as part of two-component signaling pathways, regulate adaptation to environmental conditions. Genomic and transcriptomic studies in C. difficile have been limited, due to technical challenges, to the analysis of either high-throughput screens or high-priority targets, such as primary regulators of toxins or spore biology. We present the use of several technically accessible and generally applicable techniques to elucidate the putative regulatory targets of a response regulator, RR_1586, involved in sporulation of the hypervirulent C. difficile strain R20291. A DNA-binding specificity motif for RR_1586 was determined using a bacterial one-hybrid assay originally developed for Drosophila transcription factors. Comparative bioinformatics approaches identified and in vitro experiments confirmed RR_1586 binding sites upstream of putative target genes, including those that encode phosphate ion transporters, spermidine/putrescine biosynthesis and transport pathways, ABC type transport systems, known regulators of sporulation, and genes encoding spore structural proteins. Representative examples of these regulatory interactions have been tested and confirmed in Escherichia coli-based reporter assays. Finally, evidence of possible regulatory mechanisms is also presented. A working model includes self-regulation by RR_1586 and phosphorylation-dependent and -independent DNA binding at low- and high-fidelity binding sites, respectively. Broad application of this and similar approaches is anticipated to be an important catalyst for the study of gene regulation by two-component systems from pathogenic or technically challenging bacteria.IMPORTANCE Clostridioides difficile spores survive under harsh conditions and can germinate into actively dividing cells capable of causing disease. An understanding of the regulatory networks controlling sporulation and germination in C. difficile could be exploited for therapeutic advantage. However, such studies are hindered by the challenges of working with an anaerobic pathogen recalcitrant to genetic manipulation. Although two-component response regulators can be identified from genetic sequences, identification of their downstream regulatory networks requires further development. This work integrates experimental and bioinformatic approaches, which provide practical advantages over traditional transcriptomic analyses, to identify the putative regulon of the C. difficile response regulator RR_1586 by first screening for protein-DNA interactions in E. coli and then predicting regulatory outputs in C. difficile.

SUBMITTER: Hebdon SD

PROVIDER: S-EPMC6222199 | biostudies-other | 2018 Dec

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Regulatory Targets of the Response Regulator RR_1586 from Clostridioides difficile Identified Using a Bacterial One-Hybrid Screen.

Hebdon Skyler D SD Menon Smita K SK Richter-Addo George B GB Karr Elizabeth A EA West Ann H AH

Journal of bacteriology 20181106 23

The <i>Clostridioides difficile</i> R20291 genome encodes 57 response regulator proteins that, as part of two-component signaling pathways, regulate adaptation to environmental conditions. Genomic and transcriptomic studies in <i>C. difficile</i> have been limited, due to technical challenges, to the analysis of either high-throughput screens or high-priority targets, such as primary regulators of toxins or spore biology. We present the use of several technically accessible and generally applica ...[more]

PMID: 30201779

Similar Datasets

Project description:BACKGROUND:Better understanding of the signaling pathways that regulate human bone marrow stromal stem cell (hBMSC) differentiation into bone-forming osteoblasts is crucial for their clinical use in regenerative medicine. Chemical biology approaches using small molecules targeting specific signaling pathways are increasingly employed to manipulate stem cell differentiation fate. METHODS:We employed alkaline phosphatase activity and staining assays to assess osteoblast differentiation and Alizarin R staining to assess mineralized matrix formation of cultured hBMSCs. Changes in gene expression were assessed using an Agilent microarray platform, and data normalization and bioinformatics were performed using GeneSpring software. For in vivo ectopic bone formation experiments, hMSCs were mixed with hydroxyapatite-tricalcium phosphate granules and implanted subcutaneously into the dorsal surface of 8-week-old female nude mice. Hematoxylin and eosin staining and Sirius Red staining were used to detect bone formation in vivo. RESULTS:We identified several compounds which inhibited osteoblastic differentiation of hMSCs. In particular, we identified ruxolitinib (INCB018424) (3 ?M), an inhibitor of JAK-STAT signaling that inhibited osteoblastic differentiation and matrix mineralization of hMSCs in vitro and reduced ectopic bone formation in vivo. Global gene expression profiling of ruxolitinib-treated cells identified 847 upregulated and 822 downregulated mRNA transcripts, compared to vehicle-treated control cells. Bioinformatic analysis revealed differential regulation of multiple genetic pathways, including TGF? and insulin signaling, endochondral ossification, and focal adhesion. CONCLUSIONS:We identified ruxolitinib as an important regulator of osteoblast differentiation of hMSCs. It is plausible that inhibition of osteoblast differentiation by ruxolitinib may represent a novel therapeutic strategy for the treatment of pathological conditions caused by accelerated osteoblast differentiation and mineralization.

Project description:We examine the use of high-throughput sequencing on binding sites recovered using a bacterial one-hybrid (B1H) system and find that improved models of transcription factor (TF) binding specificity can be obtained compared to standard methods of sequencing a small subset of the selected clones. We can obtain even more accurate binding models using a modified version of B1H selection method with constrained variation (CV-B1H). However, achieving these improved models using CV-B1H data required the development of a new method of analysis - GRaMS (Growth Rate Modeling of Specificity) - that estimates bacterial growth rates as a function of the quality of the recognition sequence. We benchmark these different methods of motif discovery using Zif268, a well characterized C2H2 zinc finger transcription factor on both a 28bp randomized library for the standard B1H method and on 6bp randomized library for the CV-B1H method for which forty-five different experimental conditions were tested: 5 time points and three different IPTG and 3-AT concentrations. We find that GRaMS analysis is robust to the different experimental parameters whereas other analysis methods give widely varying results depending on the conditions of the experiment. Finally, we demonstrate that the CV-B1H assay can be performed in liquid media, which produces recognition models that are similar in quality to sequences recovered from selection on solid media. All selections were performed using the bait transcription factor Zif268. 45 different B1H selections were performed on plates and the selected sites were multiplexed and sequenced in a single lane. A single selection was performed in liquid media and sequenced along with other multiplexed sets of sites in a separate lane. For the experiments performed on plates, the of the selections assays was varied (4, 8, 12, 18, 24 hours). The stringency of the selections was also varied by changing the concentration of IPTG (0, 10, 50 uM) and 3-AT (0.5, 1, 2 mM). The initial randomized library used for all selections was also sequenced in a single lane. The randomized portion of each transcription factor binding site is 6bp long and is immediately 5' of the constant sequence, GCGG, which is the consensus binding site for finger 1 of Zif268. Upstream of the randomized binding site is a 4bp randomized region referred to as the key region. The purpose of the key region is to detect possible PCR 'jackpotting.' The single liquid media experiment was run for 4 hours using 50uM IPTG and 5mM 3-AT. Four selections were performed using a prey library with a 28bp long randomized region and not fixed consensus site region. These selections were performed at either 36 or 48 hours using 10uM IPTG and 0, 2, or 5 mM 3-AT.

Dataset Information

Regulatory Targets of the Response Regulator RR_1586 from Clostridioides difficile Identified Using a Bacterial One-Hybrid Screen.

Publications

Regulatory Targets of the Response Regulator RR_1586 from Clostridioides difficile Identified Using a Bacterial One-Hybrid Screen.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets