Relating gene expression data on two-component systems to functional annotations in Escherichia coli

<p>Abstract</p> <p>Background</p> <p>Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionally, this has been done in two consecutive steps. The first step identifies important genes through clustering or statistical techniques, while the second step assigns biological functions to the identified groups. Recently, techniques have been developed that identify such relationships in a single step.</p> <p>Results</p> <p>We have developed an algorithm that relates patterns of gene expression in a set of microarray experiments to functional groups in one step. Our only assumption is that patterns co-occur frequently. The effectiveness of the algorithm is demonstrated as part of a study of regulation by two-component systems in <it>Escherichia coli</it>. The significance of the relationships between expression data and functional annotations is evaluated based on density histograms that are constructed using product similarity among expression vectors. We present a biological analysis of three of the resulting functional groups of proteins, develop hypotheses for further biological studies, and test one of these hypotheses experimentally. A comparison with other algorithms and a different data set is presented.</p> <p>Conclusion</p> <p>Our new algorithm is able to find interesting and biologically meaningful relationships, not found by other algorithms, in previously analyzed data sets. Scaling of the algorithm to large data sets can be achieved based on a theoretical model.</p

Stringent response of Escherichia coli: revisiting the bibliome using literature mining

Understanding the mechanisms responsible for cellular responses depends on the systematic collection and analysis of information on the main biological concepts involved. Indeed, the identification of biologically relevant concepts in free text, namely genes, tRNAs, mRNAs, gene products and small molecules, is crucial to capture the structure and functioning of different responses. Results In this work, we review literature reports on the study of the stringent response in Escherichia coli. Rather than undertaking the development of a highly specialised literature mining approach, we investigate the suitability of concept recognition and statistical analysis of concept occurrence as means to highlight the concepts that are most likely to be biologically engaged during this response. The co-occurrence analysis of core concepts in this stringent response, i.e. the (p)ppGpp nucleotides with gene products was also inspected and suggest that besides the enzymes RelA and SpoT that control the basal levels of (p)ppGpp nucleotides, many other proteins have a key role in this response. Functional enrichment analysis revealed that basic cellular processes such as metabolism, transcriptional and translational regulation are central, but other stress-associated responses might be elicited during the stringent response. In addition, the identification of less annotated concepts revealed that some (p)ppGpp-induced functional activities are still overlooked in most reviews. Conclusions In this paper we applied a literature mining approach that offers a more comprehensive analysis of the stringent response in E. coli. The compilation of relevant biological entities to this stress response and the assessment of their functional roles provided a more systematic understanding of this cellular response. Overlooked regulatory entities, such as transcriptional regulators, were found to play a role in this stress response. Moreover, the involvement of other stress-associated concepts demonstrates the complexity of this cellular response

The Global Regulators GacA and ς(S) Form Part of a Cascade That Controls Alginate Production in Azotobacter vinelandii

Transcription of the Azotobacter vinelandii algD gene, which encodes GDP-mannose dehydrogenase (the rate-limiting enzyme of alginate synthesis), starts from three sites: p1, p2, and p3. The sensor kinase GacS, a member of the two-component regulatory system, is required for transcription of algD from its three sites during the stationary phase. Here we show that algD is expressed constitutively throughout the growth cycle from the p2 and p3 sites and that transcription from p1 started at the transition between the exponential growth phase and stationary phase. We constructed A. vinelandii strains that carried mutations in gacA encoding the cognate response regulator of GacS and in rpoS coding for the stationary-phase ς(S) factor. The gacA mutation impaired alginate production and transcription of algD from its three promoters. Transcription of rpoS was also abolished by the gacA mutation. The rpoS mutation impaired transcription of algD from the p1 promoter and increased it from the p2 ς(E) promoter. The results of this study provide evidence for the predominant role of GacA in a regulatory cascade controlling alginate production and gene expression during the stationary phase in A. vinelandii

Biological control of soil-borne pathogens by fluorescent pseudomonads.

Particular bacterial strains in certain natural environments prevent infectious diseases of plant roots. How these bacteria achieve this protection from pathogenic fungi has been analysed in detail in biocontrol strains of fluorescent pseudomonads. During root colonization, these bacteria produce antifungal antibiotics, elicit induced systemic resistance in the host plant or interfere specifically with fungal pathogenicity factors. Before engaging in these activities, biocontrol bacteria go through several regulatory processes at the transcriptional and post-transcriptional levels

Small RNAs as regulators of primary and secondary metabolism in Pseudomonas species.

Small RNAs (sRNAs) exert important functions in pseudomonads. Classical sRNAs comprise the 4.5S, 6S, 10Sa and 10Sb RNAs, which are known in enteric bacteria as part of the signal recognition particle, a regulatory component of RNA polymerase, transfer-messenger RNA (tmRNA) and the RNA component of RNase P, respectively. Their homologues in pseudomonads are presumed to have analogous functions. Other sRNAs of pseudomonads generally have little or no sequence similarity with sRNAs of enteric bacteria. Numerous sRNAs repress or activate the translation of target mRNAs by a base-pairing mechanism. Examples of this group in Pseudomonas aeruginosa are the iron-repressible PrrF1 and PrrF2 sRNAs, which repress the translation of genes encoding iron-containing proteins, and PhrS, an anaerobically inducible sRNA, which activates the expression of PqsR, a regulator of the Pseudomonas quinolone signal. Other sRNAs sequester RNA-binding proteins that act as translational repressors. Examples of this group in P. aeruginosa include RsmY and RsmZ, which are central regulatory elements in the GacS/GacA signal transduction pathway, and CrcZ, which is a key regulator in the CbrA/CbrB signal transduction pathway. These pathways largely control the extracellular activities (including virulence traits) and the selection of the energetically most favourable carbon sources, respectively, in pseudomonads