Abstract
RegulonDB, first published 20 years ago, is a comprehensive electronic resource about regulation of transcription initiation of Escherichia coli K-12 with decades of knowledge from classic ...molecular biology experiments, and recently also from high-throughput genomic methodologies. We curated the literature to keep RegulonDB up to date, and initiated curation of ChIP and gSELEX experiments. We estimate that current knowledge describes between 10% and 30% of the expected total number of transcription factor- gene regulatory interactions in E. coli. RegulonDB provides datasets for interactions for which there is no evidence that they affect expression, as well as expression datasets. We developed a proof of concept pipeline to merge binding and expression evidence to identify regulatory interactions. These datasets can be visualized in the RegulonDB JBrowse. We developed the Microbial Conditions Ontology with a controlled vocabulary for the minimal properties to reproduce an experiment, which contributes to integrate data from high throughput and classic literature. At a higher level of integration, we report Genetic Sensory-Response Units for 200 transcription factors, including their regulation at the metabolic level, and include summaries for 70 of them. Finally, we summarize our research with Natural language processing strategies to enhance our biocuration work.
Abstract
RegulonDB is a database that contains the most comprehensive corpus of knowledge of the regulation of transcription initiation of Escherichia coli K-12, including data from both classical ...molecular biology and high-throughput methodologies. Here, we describe biological advances since our last NAR paper of 2019. We explain the changes to satisfy FAIR requirements. We also present a full reconstruction of the RegulonDB computational infrastructure, which has significantly improved data storage, retrieval and accessibility and thus supports a more intuitive and user-friendly experience. The integration of graphical tools provides clear visual representations of genetic regulation data, facilitating data interpretation and knowledge integration. RegulonDB version 12.0 can be accessed at https://regulondb.ccg.unam.mx.
Graphical Abstract
Graphical Abstract
Genomics has set the basis for a variety of methodologies that produce high-throughput datasets identifying the different players that define gene regulation, particularly regulation of transcription ...initiation and operon organization. These datasets are available in public repositories, such as the Gene Expression Omnibus, or ArrayExpress. However, accessing and navigating such a wealth of data is not straightforward. No resource currently exists that offers all available high and low-throughput data on transcriptional regulation in
K-12 to easily use both as whole datasets, or as individual interactions and regulatory elements. RegulonDB (https://regulondb.ccg.unam.mx) began gathering high-throughput dataset collections in 2009, starting with transcription start sites, then adding ChIP-seq and gSELEX in 2012, with up to 99 different experimental high-throughput datasets available in 2019. In this paper we present a radical upgrade to more than 2000 high-throughput datasets, processed to facilitate their comparison, introducing up-to-date collections of transcription termination sites, transcription units, as well as transcription factor binding interactions derived from ChIP-seq, ChIP-exo, gSELEX and DAP-seq experiments, besides expression profiles derived from RNA-seq experiments. For ChIP-seq experiments we offer both the data as presented by the authors, as well as data uniformly processed in-house, enhancing their comparability, as well as the traceability of the methods and reproducibility of the results. Furthermore, we have expanded the tools available for browsing and visualization across and within datasets. We include comparisons against previously existing knowledge in RegulonDB from classic experiments, a nucleotide-resolution genome viewer, and an interface that enables users to browse datasets by querying their metadata. A particular effort was made to automatically extract detailed experimental growth conditions by implementing an assisted curation strategy applying Natural language processing and machine learning. We provide summaries with the total number of interactions found in each experiment, as well as tools to identify common results among different experiments. This is a long-awaited resource to make use of such wealth of knowledge and advance our understanding of the biology of the model bacterium
K-12.
Bartter syndrome (BS) is a salt-losing hereditary tubulopathy characterized by hypokalemic metabolic alkalosis with secondary hyperaldosteronism. Confirmatory molecular diagnosis may be difficult due ...to genetic heterogeneity and overlapping of clinical symptoms. The aim of our study was to describe the different molecular findings in patients with a clinical diagnosis of classic BS. We included 27 patients (26 families) with no identified pathogenic variants in CLCNKB. We used a customized Ion AmpliSeq Next-Generation Sequencing panel including 44 genes related to renal tubulopathies. We detected pathogenic or likely pathogenic variants in 12 patients (44%), reaching a conclusive genetic diagnosis. Variants in SLC12A3 were found in 6 (Gitelman syndrome). Median age at diagnosis was 14.6 years (range 0.1-31), with no history of prematurity or polyhydramnios. Serum magnesium level was low in 2 patients (33%) but urinary calcium excretion was normal or low in all, with no nephrocalcinosis. Variants in SLC12A1 were found in 3 (BS type 1); and in KCNJ1 in 1 (BS type 2). These patients had a history of polyhydramnios in 3 (75%), and the mean gestational age was 34.2 weeks (SD 1.7). The median age at diagnosis was 1.8 years (range 0.1-6). Chronic kidney disease and nephrocalcinosis were present in 1 (25%) and 3 (75%) patients, respectively. A variant in CLCN5 was found in one patient (Dent disease), and in NR3C2 in another patient (Geller syndrome). Genetic diagnosis of BS is heterogeneous as different tubulopathies can present with a similar clinical picture. The use of gene panels in these diseases becomes more efficient than the study gene by gene with Sanger sequencing.
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