RegulonDB version 9.0: high-level integration of gene regulation, coexpression, motif clustering and beyond

Abstract

RegulonDB (http://regulondb.ccg.unam.mx) is one of the most useful and important resources on bacterial gene regulation,as it integrates the scattered scientific knowledge of the best-characterized organism, Escherichia coli K-12, in a database that organizes large amounts of data. Its electronic format enables researchers to compare their results with the legacy of previous knowledge and supports bioinformatics tools and model building. Here, we summarize our progress with RegulonDB since our last Nucleic Acids Research publication describing RegulonDB, in 2013. In addition to maintaining curation up-to-date, we report a collection of 232 interactions with small RNAs affecting 192 genes, and the complete repertoire of 189 Elementary Genetic Sensory-Response units (GENSOR units), integrating the signal, regulatory interactions, and metabolic pathways they govern. These additions represent major progress to a higher level of understanding of regulated processes. We have updated the computationally predicted transcription factors, which total 304 (184 with experimental evidence and 120 from computational predictions); we updated our position-weight matrices and have included tools for clustering them in evolutionary families. We describe our semiautomatic strategy to accelerate curation, including datasets from high-throughput experiments, a novel coexpression distance to search for 'neighborhood' genes to known operons and regulons, and computational developments.

Figure 1.

The BetI GENSOR unit. The signal and signal processing, in this case transport of choline through the membrane, are shown in blue. The genetic switch, i.e., repression of betT and betIBA transcription units, is shown in yellow. The response is shown in green: production of BetT, a choline transporter, and BetA and BetB, enzymes responsible for the utilization of choline.

Figure 2.

Circular Browser. Transcription factors (TF) classified in their evolutionary families, based on PFAM, CDD and Superfamily annotations.

Figure 3.

Impact of RegulonDB. Accumulated citations for each RegulonDB paper by year and the concomitant expansion of domains of the biology that we curate.

Figure 4.

Schema of types of methods and content in RegulonDB.