Reliable transfer of transcriptional gene regulatory networks between taxonomically related organisms

Baumbach J, Rahmann S, Tauch A. Reliable transfer of transcriptional gene regulatory networks between taxonomically related organisms. BMC Systems Biology. 2009;3(1):8.Background: Transcriptional regulation of gene activity is essential for any living organism. Transcription factors therefore recognize specific binding sites within the DNA to regulate the expression of particular target genes. The genome-scale reconstruction of the emerging regulatory networks is important for biotechnology and human medicine but cost-intensive, time-consuming, and impossible to perform for any species separately. By using bioinformatics methods one can partially transfer networks from well-studied model organisms to closely related species. However, the prediction quality is limited by the low level of evolutionary conservation of the transcription factor binding sites, even within organisms of the same genus. Results: Here we present an integrated bioinformatics workflow that assures the reliability of transferred gene regulatory networks. Our approach combines three methods that can be applied on a large-scale: re-assessment of annotated binding sites, subsequent binding site prediction, and homology detection. A gene regulatory interaction is considered to be conserved if (1) the transcription factor, (2) the adjusted binding site, and (3) the target gene are conserved. The power of the approach is demonstrated by transferring gene regulations from the model organism Corynebacterium glutamicum to the human pathogens C. diphtheriae, C. jeikeium, and the biotechnologically relevant C. efficiens. For these three organisms we identified reliable transcriptional regulations for similar to 40% of the common transcription factors, compared to similar to 5% for which knowledge was available before. Conclusion: Our results suggest that trustworthy genome-scale transfer of gene regulatory networks between organisms is feasible in general but still limited by the level of evolutionary conservation

Transcription factor site dependencies in human, mouse and rat genomes

<p>Abstract</p> <p>Background</p> <p>It is known that transcription factors frequently act together to regulate gene expression in eukaryotes. In this paper we describe a computational analysis of transcription factor site dependencies in human, mouse and rat genomes.</p> <p>Results</p> <p>Our approach for quantifying tendencies of transcription factor binding sites to co-occur is based on a binding site scoring function which incorporates dependencies between positions, the use of information about the structural class of each transcription factor (major/minor groove binder), and also considered the possible implications of varying GC content of the sequences. Significant tendencies (dependencies) have been detected by non-parametric statistical methodology (permutation tests). Evaluation of obtained results has been performed in several ways: reports from literature (many of the significant dependencies between transcription factors have previously been confirmed experimentally); dependencies between transcription factors are not biased due to similarities in their DNA-binding sites; the number of dependent transcription factors that belong to the same functional and structural class is significantly higher than would be expected by chance; supporting evidence from GO clustering of targeting genes. Based on dependencies between two transcription factor binding sites (second-order dependencies), it is possible to construct higher-order dependencies (networks). Moreover results about transcription factor binding sites dependencies can be used for prediction of groups of dependent transcription factors on a given promoter sequence. Our results, as well as a scanning tool for predicting groups of dependent transcription factors binding sites are available on the Internet.</p> <p>Conclusion</p> <p>We show that the computational analysis of transcription factor site dependencies is a valuable complement to experimental approaches for discovering transcription regulatory interactions and networks. Scanning promoter sequences with dependent groups of transcription factor binding sites improve the quality of transcription factor predictions.</p

Statistical significance of cis-regulatory modules

BACKGROUND: It is becoming increasingly important for researchers to be able to scan through large genomic regions for transcription factor binding sites or clusters of binding sites forming cis-regulatory modules. Correspondingly, there has been a push to develop algorithms for the rapid detection and assessment of cis-regulatory modules. While various algorithms for this purpose have been introduced, most are not well suited for rapid, genome scale scanning. RESULTS: We introduce methods designed for the detection and statistical evaluation of cis-regulatory modules, modeled as either clusters of individual binding sites or as combinations of sites with constrained organization. In order to determine the statistical significance of module sites, we first need a method to determine the statistical significance of single transcription factor binding site matches. We introduce a straightforward method of estimating the statistical significance of single site matches using a database of known promoters to produce data structures that can be used to estimate p-values for binding site matches. We next introduce a technique to calculate the statistical significance of the arrangement of binding sites within a module using a max-gap model. If the module scanned for has defined organizational parameters, the probability of the module is corrected to account for organizational constraints. The statistical significance of single site matches and the architecture of sites within the module can be combined to provide an overall estimation of statistical significance of cis-regulatory module sites. CONCLUSION: The methods introduced in this paper allow for the detection and statistical evaluation of single transcription factor binding sites and cis-regulatory modules. The features described are implemented in the Search Tool for Occurrences of Regulatory Motifs (STORM) and MODSTORM software

Predicting tissue specific cis-regulatory modules in the human genome using pairs of co-occurring motifs

<p>Abstract</p> <p>Background</p> <p>Researchers seeking to unlock the genetic basis of human physiology and diseases have been studying gene transcription regulation. The temporal and spatial patterns of gene expression are controlled by mainly non-coding elements known as cis-regulatory modules (CRMs) and epigenetic factors. CRMs modulating related genes share the regulatory signature which consists of transcription factor (TF) binding sites (TFBSs). Identifying such CRMs is a challenging problem due to the prohibitive number of sequence sets that need to be analyzed.</p> <p>Results</p> <p>We formulated the challenge as a supervised classification problem even though experimentally validated CRMs were not required. Our efforts resulted in a software system named CrmMiner. The system mines for CRMs in the vicinity of related genes. CrmMiner requires two sets of sequences: a mixed set and a control set. Sequences in the vicinity of the related genes comprise the mixed set, whereas the control set includes random genomic sequences. CrmMiner assumes that a large percentage of the mixed set is made of background sequences that do not include CRMs. The system identifies pairs of closely located motifs representing vertebrate TFBSs that are enriched in the training mixed set consisting of 50% of the gene loci. In addition, CrmMiner selects a group of the enriched pairs to represent the tissue-specific regulatory signature. The mixed and the control sets are searched for candidate sequences that include any of the selected pairs. Next, an optimal Bayesian classifier is used to distinguish candidates found in the mixed set from their control counterparts. Our study proposes 62 tissue-specific regulatory signatures and putative CRMs for different human tissues and cell types. These signatures consist of assortments of ubiquitously expressed TFs and tissue-specific TFs. Under controlled settings, CrmMiner identified known CRMs in noisy sets up to 1:25 signal-to-noise ratio. CrmMiner was 21-75% more precise than a related CRM predictor. The sensitivity of the system to locate known human heart enhancers reached up to 83%. CrmMiner precision reached 82% while mining for CRMs specific to the human CD4⁺T cells. On several data sets, the system achieved 99% specificity.</p> <p>Conclusion</p> <p>These results suggest that CrmMiner predictions are accurate and likely to be tissue-specific CRMs. We expect that the predicted tissue-specific CRMs and the regulatory signatures broaden our knowledge of gene transcription regulation.</p

A Novel Secretion Pathway of Salmonella enterica Acts as an Antivirulence Modulator during Salmonellosis

Salmonella spp. are Gram-negative enteropathogenic bacteria that infect a variety of vertebrate hosts. Like any other living organism, protein secretion is a fundamental process essential for various aspects of Salmonella biology. Herein we report the identification and characterization of a horizontally acquired, autonomous and previously unreported secretion pathway. In Salmonella enterica serovar Typhimurium, this novel secretion pathway is encoded by STM1669 and STM1668, designated zirT and zirS, respectively. We show that ZirT is localized to the bacterial outer membrane, expected to adopt a compact β-barrel conformation, and functions as a translocator for ZirS. ZirS is an exoprotein, which is secreted into the extracellular environment in a ZirT-dependent manner. The ZirTS secretion pathway was found to share several important features with two-partner secretion (TPS) systems and members of the intimin/invasin family of adhesions. We show that zirTS expression is affected by zinc; and that in vivo, induction of zirT occurs distinctively in Salmonella colonizing the small intestine, but not in systemic sites. Additionally, strong expression of zirT takes place in Salmonella shed in fecal pellets during acute and persistent infections of mice. Inactivation of ZirTS results in a hypervirulence phenotype of Salmonella during oral infection of mice. Cumulatively, these results indicate that the ZirTS pathway plays a unique role as an antivirulence modulator during systemic disease and is involved in fine-tuning a host–pathogen balance during salmonellosis

Validation of Skeletal Muscle cis-Regulatory Module Predictions Reveals Nucleotide Composition Bias in Functional Enhancers

We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs) using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions

Automated telephone communication systems for preventive healthcare and management of long-term conditions

Background Automated telephone communication systems (ATCS) can deliver voice messages and collect health-related information from patients using either their telephone’s touch-tone keypad or voice recognition software. ATCS can supplement or replace telephone contact between health professionals and patients. There are four different types of ATCS: unidirectional (one-way, non-interactive voice communication), interactive voice response (IVR) systems, ATCS with additional functions such as access to an expert to request advice (ATCS Plus) and multimodal ATCS, where the calls are delivered as part of a multicomponent intervention. Objectives To assess the effects of ATCS for preventing disease and managing long-term conditions on behavioural change, clinical, process, cognitive, patient-centred and adverse outcomes. Search methods We searched 10 electronic databases (the Cochrane Central Register of Controlled Trials; MEDLINE; Embase; PsycINFO; CINAHL; Global Health; WHOLIS; LILACS; Web of Science; and ASSIA); three grey literature sources (Dissertation Abstracts, Index to Theses, Australasian Digital Theses); and two trial registries (www.controlled-trials.com; www.clinicaltrials.gov) for papers published between 1980 and June 2015. Selection criteria Randomised, cluster- and quasi-randomised trials, interrupted time series and controlled before-and-after studies comparing ATCS interventions, with any control or another ATCS type were eligible for inclusion. Studies in all settings, for all consumers/carers, in any preventive healthcare or long term condition management role were eligible. Data collection and analysis We used standard Cochrane methods to select and extract data and to appraise eligible studies. Main results We included 132 trials (N = 4,669,689). Studies spanned across several clinical areas, assessing many comparisons based on evaluation of different ATCS types and variable comparison groups. Forty-one studies evaluated ATCS for delivering preventive healthcare, 84 for managing long-term conditions, and seven studies for appointment reminders. We downgraded our certainty in the evidence primarily because of the risk of bias for many outcomes. We judged the risk of bias arising from allocation processes to be low for just over half the studies and unclear for the remainder. We considered most studies to be at unclear risk of performance or detection bias due to blinding, while only 16% of studies were at low risk. We generally judged the risk of bias due to missing data and selective outcome reporting to be unclear. For preventive healthcare, ATCS (ATCS Plus, IVR, unidirectional) probably increase immunisation uptake in children (risk ratio (RR) 1.25, 95% confidence interval (CI) 1.18 to 1.32; 5 studies, N = 10,454; moderate certainty) and to a lesser extent in adolescents (RR 1.06, 95% CI 1.02 to 1.11; 2 studies, N = 5725; moderate certainty). The effects of ATCS in adults are unclear (RR 2.18, 95% CI 0.53 to 9.02; 2 studies, N = 1743; very low certainty). For screening, multimodal ATCS increase uptake of screening for breast cancer (RR 2.17, 95% CI 1.55 to 3.04; 2 studies, N = 462; high certainty) and colorectal cancer (CRC) (RR 2.19, 95% CI 1.88 to 2.55; 3 studies, N = 1013; high certainty) versus usual care. It may also increase osteoporosis screening. ATCS Plus interventions probably slightly increase cervical cancer screening (moderate certainty), but effects on osteoporosis screening are uncertain. IVR systems probably increase CRC screening at 6 months (RR 1.36, 95% CI 1.25 to 1.48; 2 studies, N = 16,915; moderate certainty) but not at 9 to 12 months, with probably little or no effect of IVR (RR 1.05, 95% CI 0.99, 1.11; 2 studies, 2599 participants; moderate certainty) or unidirectional ATCS on breast cancer screening. Appointment reminders delivered through IVR or unidirectional ATCS may improve attendance rates compared with no calls (low certainty). For long-term management, medication or laboratory test adherence provided the most general evidence across conditions (25 studies, data not combined). Multimodal ATCS versus usual care showed conflicting effects (positive and uncertain) on medication adherence. ATCS Plus probably slightly (versus control; moderate certainty) or probably (versus usual care; moderate certainty) improves medication adherence but may have little effect on adherence to tests (versus control). IVR probably slightly improves medication adherence versus control (moderate certainty). Compared with usual care, IVR probably improves test adherence and slightly increases medication adherence up to six months but has little or no effect at longer time points (moderate certainty). Unidirectional ATCS, compared with control, may have little effect or slightly improve medication adherence (low certainty). The evidence suggested little or no consistent effect of any ATCS type on clinical outcomes (blood pressure control, blood lipids, asthma control, therapeutic coverage) related to adherence, but only a small number of studies contributed clinical outcome data. The above results focus on areas with the most general findings across conditions. In condition-specific areas, the effects of ATCS varied, including by the type of ATCS intervention in use. Multimodal ATCS probably decrease both cancer pain and chronic pain as well as depression (moderate certainty), but other ATCS types were less effective. Depending on the type of intervention, ATCS may have small effects on outcomes for physical activity, weight management, alcohol consumption, and diabetes mellitus. ATCS have little or no effect on outcomes related to heart failure, hypertension, mental health or smoking cessation, and there is insufficient evidence to determine their effects for preventing alcohol/ substance misuse or managing illicit drug addiction, asthma, chronic obstructive pulmonary disease, HIV/AIDS, hypercholesterolaemia, obstructive sleep apnoea, spinal cord dysfunction or psychological stress in carers. Only four trials (3%) reported adverse events, and it was unclear whether these were related to the intervention