Background Genome-wide identification of transcription factor binding sites (TFBSs) is essential for reconstructing regulatory networks and understanding how gene expression patterns shape bacterial physiology. Although the number of experimentally characterized binding motifs has increased substantially in recent years, currently available TFBS-scanning web tools often lack interactivity, flexible threshold adjustment, reliability assessment, and functional interpretation of predicted regulons. Results We present PREDetector v4.0, an updated web-based platform for position weight matrix (PWM)-driven prediction of transcription factor regulons in bacterial genomes. The platform provides access to more than 9,000 bacterial genomes and over 2,000 curated PWMs from multiple public databases, while also allowing users to upload their own genomes and customized PWMs. PREDetector integrates dynamic PWM score threshold adjustment, enables assessment of the prediction reliability based on the genomic distribution of predicted TFBSs, includes predicted co-transcribed genes, and displays the results in an interactive genomic mapping viewer. Finally, each predicted target gene is directly linked to external annotation resources, including the KEGG pathway database and the UniProt knowledgebase, enabling immediate functional interpretation of the inferred regulon. Conclusions PREDetector v4.0 provides a comprehensive and user-friendly framework for genome-wide regulon prediction in bacteria and their functional analysis. By combining flexible motif scanning with interactive visualization and pathway interpretation, the platform facilitates hypothesis generation and supports both exploratory and targeted studies of bacterial transcriptional regulation. The web server is freely accessible at https://www.predetector.uliege.be.
Mechanisms regulating oligodendrocyte differentiation, developmental myelination and myelin maintenance in adulthood are complex and still not completely described. Their understanding is crucial for the development of new protective or therapeutic strategies in demyelinating pathologies such as multiple sclerosis. In this perspective, we have investigated the role of Cyclin-dependent kinase 7 (Cdk7), a kinase involved in cell-cycle progression and transcription regulation, in the oligodendroglial lineage. We generated a conditional knock-out mouse model in which Cdk7 is invalidated in post-mitotic oligodendrocytes. At the end of developmental myelination, the number and diameter of myelinated axons, as well as the myelin structure, thickness and protein composition, were normal. However, in young adult and in aged mice, there was a higher number of small caliber myelinated axons associated with a decreased mean axonal diameter, myelin sheaths of large caliber axons were thinner, and the level of some major myelin-associated proteins was reduced. These defects were accompanied by the appearance of an abnormal clasping phenotype. We also used an in vitro oligodendroglial model and showed that Cdk7 pharmacological inhibition led to an altered myelination-associated morphological modification combined with a decreased expression of myelin-specific genes. Altogether, we identified novel functions for Cdk7 in CNS myelination.
BACKGROUND:The increasing demand for local food production is fueling high interest in the development of controlled environment agriculture. In particular, LED technology brings energy-saving advantages together with the possibility of manipulating plant phenotypes through light quality control. However, optimizing light quality is required for each cultivated plant and specific purpose.FINDINGS:This article shows that the combination of LED gradient set-ups with imaging-based non-destructive plant phenotyping constitutes an interesting new screening tool with the potential to improve speed, logistics, and information output. To validate this concept, an experiment was performed to evaluate the effects of a complete range of red:blue ratios on 7 plant species: Arabidopsis thaliana, Brachypodium distachyon, Euphorbia peplus, Ocimum basilicum, Oryza sativa, Solanum lycopersicum, and Setaria viridis. Plants were exposed during 30 days to the light gradient and showed significant, but species-dependent, responses in terms of dimension, shape, and color. A time-series analysis of phenotypic descriptors highlighted growth changes but also transient responses of plant shapes to the red:blue ratio.CONCLUSION:This approach, which generated a large reusable dataset, can be adapted for addressing specific needs in crop production or fundamental questions in photobiology.
Transcriptional regulation is key in bacteria for providing an adequate response in time and space to changing environmental conditions. However, despite decades of research, the binding sites and therefore the target genes and the function of most transcription factors (TFs) remain unknown. Filling this gap in knowledge through conventional methods represents a colossal task which we demonstrate here can be significantly facilitated by a widespread feature in transcriptional control: the autoregulation of TFs implying that the yet unknown tran-scription factor binding site (TFBS) is neighboring the TF itself. In this work, we describe the "AURTHO" methodology (AUtoregulation of oRTHOlogous transcription factors), consisting of analyzing upstream regions of orthologous TFs in order to uncover their associated TFBSs. AURTHO enabled the de novo identification of novel TFBSs with an unprecedented improvement in terms of quantity and reliability. DNA-protein interaction studies on a selection of candidate cis-acting elements yielded an >90 % success rate, demonstrating the efficacy of AURTHO at highlighting true TF-TFBS couples and confirming the identification in a near future of a plethora of TFBSs across all bacterial species.
Euphorbia peplus images used in the paper entitled "Led Color Gradient As A New Screening Tool For Rapid Phenotyping Of Plant Responses To Light Quality" by Pierre LEJEUNE, Anthony FRATAMICO, Frédéric BOUCHÉ, Samuel HUERGA-FERNÁNDEZ, Pierre TOCQUIN, Claire PÉRILLEUX
Current developments in light-emitting diodes (LEDs) technologies have opened new perspectives for sustainable and highly efficient indoor cultivation. The introduction of LEDs not only allows a reduction in the production costs on a quantitative level, it also offers opportunities to manipulate and optimise qualitative traits. Indeed, while plants respond strongest to red and blue lights for photosynthesis, the whole light spectrum has an effect on plant shape, development, and chemical composition. In order to evaluate LEDs as an alternative to traditional lighting sources, the species-specific plant responses to distinct wavelengths need to be evaluated under controlled conditions. Here, we tested the possibility to use light composition gradients in combination with semi-automated phenotyping to rapidly explore the phenotypic responses of different species to variations in the light spectrum provided by LED sources. Plants of seven different species ( Arabidopsis thaliana, Ocimum basilicum, Solanum lycopersicum, Brachypodium distachyon, Oryza sativa, Euphorbia peplus, Setaria viridis ) were grown under standard white fluorescent light for 30 days, then transferred to a Red:Blue gradient for another 30 days and finally returned to white light. In all species, differences in terms of dimension, shape, and color were rapidly observed across the gradient and the overall response was widely species-dependent. The experiment yielded large amounts of imaging-based phenotypic data and we suggest simple data analysis methods to aggregate the results and facilitate comparisons between species. Similar experimental setups will help achieve rapid environmental optimization, screen new crop species and genotypes, or develop new gene discovery strategies.
SUMMARY:To support small and large-scale genome mining projects, we present Post-processing Analysis tooLbox for ANTIsmash Reports (Palantir), a dedicated software suite for handling and refining secondary metabolite biosynthetic gene cluster (BGC) data annotated with the popular antiSMASH pipeline. Palantir provides new functionalities building on NRPS/PKS predictions from antiSMASH, such as improved BGC annotation, module delineation and easy access to sub-sequences at different levels (cluster, gene, module and domain). Moreover, it can parse user-provided antiSMASH reports and reformat them for direct use or storage in a relational database. AVAILABILITY AND IMPLEMENTATION:Palantir is released both as a Perl API available on CPAN (https://metacpan.org/release/Bio-Palantir) and as a web application (http://palantir.uliege.be). As a practical use case, the web interface also features a database built from the mining of 1616 cyanobacterial genomes, of which 1488 were predicted to encode at least one BGC. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.
Common scab disease on root and tuber plants is caused by Streptomyces scabies and related species which use the cellulose synthase inhibitor thaxtomin A as main phytotoxin. Thaxtomin production is primarily triggered by the import of cello-oligosaccharides. Once inside the cell, the fate of the cello-oligosaccharides is dichotomized into i) fueling glycolysis with glucose for the saprophytic lifestyle through the action of β-glucosidase(s) (BG), and ii) eliciting the pathogenic lifestyle by inhibiting the CebR-mediated transcriptional repression of thaxtomin biosynthetic genes. Here we investigated the role of scab57721 encoding a putative BG (BglC) in the onset of the pathogenicity of S. scabies. Enzymatic assays showed that BglC was able to release glucose from cellobiose, cellotriose and all other cello-oligosaccharides tested. Its inactivation resulted in a phenotype opposite to what was expected as we monitored reduced production of thaxtomin when the mutant was cultivated on media containing cello-oligosaccharides as unique carbon source. This unexpected phenotype could be attributed to the highly increased activity of alternative intracellular BGs, probably as a compensation of bglC inactivation, which then prevented cellobiose and cellotriose accumulation to reduce the activity of CebR. In contrast, when the bglC null mutant was cultivated on media devoid of cello-oligosaccharides it instead constitutively produced thaxtomin. This observed hypervirulent phenotype does not fit with the proposed model of the cello-oligosaccharide-mediated induction of thaxtomin production and suggests that the role of BglC in the route to the pathogenic lifestyle of S. scabies is more complex than currently presented.
Root system analysis is a complex task, often performed with fully automated image analysis pipelines. However, the outcome is rarely verified by ground-truth data, which might lead to underestimated biases. We have used a root model, ArchiSimple, to create a large and diverse library of ground-truth root system images (10,000). For each image, three levels of noise were created. This library was used to evaluate the accuracy and usefulness of several image descriptors classically used in root image analysis softwares. Our analysis highlighted that the accuracy of the different traits is strongly dependent on the quality of the images and the type, size, and complexity of the root systems analyzed. Our study also demonstrated that machine learning algorithms can be trained on a synthetic library to improve the estimation of several root system traits. Overall, our analysis is a call to caution when using automatic root image analysis tools. If a thorough calibration is not performed on the dataset of interest, unexpected errors might arise, especially for large and complex root images. To facilitate such calibration, both the image library and the different codes used in the study have been made available to the community.
This depository contains the images and associated RSML files used in the paper entitled "Using a structural root system model for an in-depth assessment of root image analysis pipeline" from the same authors. It contains: - 10.000 simulated root images; - 10.000 corresponding RSML files; - .csv files containing the ground-truth data for each modelled root system; - .csv files containing the image descriptors extracted using RIA-J; - .tps files containing the shape descriptors data. The codes used with this data is available here: https://zenodo.org/record/62063
Molecular data concerning the involvement of roots in the genetic pathways regulating floral transition are lacking. In this study, we performed global analyses of the root transcriptome in Arabidopsis in order to identify flowering time genes that are expressed in the roots and genes that are differentially expressed in the roots during the induction of flowering. Data mining of public microarray experiments uncovered that about 200 genes whose mutations are reported to alter flowering time are expressed in the roots (i.e. were detected in more than 50% of the microarrays). However, only a few flowering integrator genes passed the analysis cutoff. Comparison of root transcriptome in short days and during synchronized induction of flowering by a single 22-h long day revealed that 595 genes were differentially expressed. Enrichment analyses of differentially expressed genes in root tissues, gene ontology categories, and cis-regulatory elements converged towards sugar signaling. We concluded that roots are integrated in systemic signaling, whereby carbon supply coordinates growth at the whole plant level during the induction of flowering. This coordination could involve the root circadian clock and cytokinin biosynthesis as a feed forward loop towards the shoot.
ABSTRACT In the era that huge numbers of microbial genomes are being released in the databases, it becomes increasingly important to rapidly mine genes as well as predict the regulatory networks that control their expression. To this end, we have developed an improved and online version of the PREDetector software aimed at identifying putative transcription factor-binding sites (TFBS) in bacterial genomes. The original philosophy of PREDetector 1.0 is maintained, i.e. to allow users to freely fix the DNA-motif screening parameters, and to provide a statistical means to estimate the reliability of the prediction output. This new version offers an interactive table as well as graphics to dynamically alter the main screening parameters with automatic update of the list of identified putative TFBS. PREDetector 2.0 also has the following additional options: (i) access to genome sequences from different databases, (ii) access to weight matrices from public repositories, (iii) visualization of the predicted hits in their genomic context, (iv) grouping of hits identified in the same upstream region, (v) possibility to store the performed jobs, and (vi) automated export of the results in various formats. PREDetector 2.0 is available at http://predetector.fsc.ulg.ac.be/ .