Enhancing Escherichia coli abiotic stress resistance through ornithine lipid formation.

Escherichia coli is a common host for biotechnology and synthetic biology applications. During growth and fermentation, the microbes are often exposed to stress conditions, such as variations in pH or solvent concentrations. Bacterial membranes play a key role in response to abiotic stresses. Ornithine lipids (OLs) are a group of membrane lipids whose presence and synthesis have been related to stress resistance in bacteria. We wondered if this stress resistance could be transferred to bacteria not encoding the capacity to form OLs in their genome, such as E. coli. In this study, we engineered different E. coli strains to produce unmodified OLs and hydroxylated OLs by expressing the synthetic operon olsFC. Our results showed that OL formation improved pH resistance and increased biomass under phosphate limitation. Transcriptome analysis revealed that OL-forming strains differentially expressed stress- and membrane-related genes. OL-producing strains also showed better growth in the presence of the ionophore carbonyl cyanide 3-chlorophenylhydrazone (CCCP), suggesting reduced proton leakiness in OL-producing strains. Furthermore, our engineered strains showed improved heterologous violacein production at phosphate limitation and also at low pH. Overall, this study demonstrates the potential of engineering the E. coli membrane composition for constructing robust hosts with an increased abiotic stress resistance for biotechnology and synthetic biology applications. KEY POINTS: • Ornithine lipid production in E. coli increases biomass yield under phosphate limitation. • Engineered strains show an enhanced production phenotype under low pH stress. • Transcriptome analysis and CCCP experiments revealed reduced proton leakage.

Predicting synchronized gene coexpression patterns from fibration symmetries in gene regulatory networks in bacteria.

BACKGROUND: Gene regulatory networks coordinate the expression of genes across physiological states and ensure a synchronized expression of genes in cellular subsystems, critical for the coherent functioning of cells. Here we address the question whether it is possible to predict gene synchronization from network structure alone. We have recently shown that synchronized gene expression can be predicted from symmetries in the gene regulatory networks described by the concept of symmetry fibrations. We showed that symmetry fibrations partition the genes into groups called fibers based on the symmetries of their 'input trees', the set of paths in the network through which signals can reach a gene. In idealized dynamic gene expression models, all genes in a fiber are perfectly synchronized, while less idealized models-with gene input functions differencing between genes-predict symmetry breaking and desynchronization. RESULTS: To study the functional role of gene fibers and to test whether some of the fiber-induced coexpression remains in reality, we analyze gene fibrations for the gene regulatory networks of E. coli and B. subtilis and confront them with expression data. We find approximate gene coexpression patterns consistent with symmetry fibrations with idealized gene expression dynamics. This shows that network structure alone provides useful information about gene synchronization, and suggest that gene input functions within fibers may be further streamlined by evolutionary pressures to realize a coexpression of genes. CONCLUSIONS: Thus, gene fibrations provide a sound conceptual tool to describe tunable coexpression induced by network topology and shaped by mechanistic details of gene expression.

Pseudocrossidium replicatum (Taylor) R.H. Zander is a fully desiccation-tolerant moss that expresses an inducible molecular mechanism in response to severe abiotic stress.

KEY MESSAGE: The moss Pseudocrossidium replicatum is a desiccation-tolerant species that uses an inducible system to withstand severe abiotic stress in both protonemal and gametophore tissues. Desiccation tolerance (DT) is the ability of cells to recover from an air-dried state. Here, the moss Pseudocrossidium replicatum was identified as a fully desiccation-tolerant (FDT) species. Its gametophores rapidly lost more than 90% of their water content when exposed to a low-humidity atmosphere [23% relative humidity (RH)], but abscisic acid (ABA) pretreatment diminished the final water loss after equilibrium was reached. P. replicatum gametophores maintained good maximum photosystem II (PSII) efficiency (Fv/Fm) for up to two hours during slow dehydration; however, ABA pretreatment induced a faster decrease in the Fv/Fm. ABA also induced a faster recovery of the Fv/Fm after rehydration. Protein synthesis inhibitor treatment before dehydration hampered the recovery of the Fv/Fm when the gametophores were rehydrated after desiccation, suggesting the presence of an inducible protective mechanism that is activated in response to abiotic stress. This observation was also supported by accumulation of soluble sugars in gametophores exposed to ABA or NaCl. Exogenous ABA treatment delayed the germination of P. replicatum spores and induced morphological changes in protonemal cells that resembled brachycytes. Transcriptome analyses revealed the presence of an inducible molecular mechanism in P. replicatum protonemata that was activated in response to dehydration. This study is the first RNA-Seq study of the protonemal tissues of an FDT moss. Our results suggest that P. replicatum is an FDT moss equipped with an inducible molecular response that prepares this species for severe abiotic stress and that ABA plays an important role in this response.

A Novel OmpR-Type Response Regulator Controls Multiple Stages of the Rhizobium etli - Phaseolus vulgaris N2-Fixing Symbiosis.

OmpR, is one of the best characterized response regulators families, which includes transcriptional regulators with a variety of physiological roles including the control of symbiotic nitrogen fixation (SNF). The Rhizobium etli CE3 genome encodes 18 OmpR-type regulators; the function of the majority of these regulators during the SNF in common bean, remains elusive. In this work, we demonstrated that a R. etli mutant strain lacking the OmpR-type regulator RetPC57 (ΔRetPC57), formed less nodules when used as inoculum for common bean. Furthermore, we observed reduced expression level of bacterial genes involved in Nod Factors production (nodA and nodB) and of plant early-nodulation genes (NSP2, NIN, NF-YA and ENOD40), in plants inoculated with ΔRetPC57. RetPC57 also contributes to the appropriate expression of genes which products are part of the multidrug efflux pumps family (MDR). Interestingly, nodules elicited by ΔRetPC57 showed increased expression of genes relevant for Carbon/Nitrogen nodule metabolism (PEPC and GOGAT) and ΔRetPC57 bacteroids showed higher nitrogen fixation activity as well as increased expression of key genes directly involved in SNF (hfixL, fixKf, fnrN, fixN, nifA and nifH). Taken together, our data show that the previously uncharacterized regulator RetPC57 is a key player in the development of the R. etli - P. vulgaris symbiosis.

RegulonDB v 10.5: tackling challenges to unify classic and high throughput knowledge of gene regulation in E. coli K-12.

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.

A unified resource for transcriptional regulation in Escherichia coli K-12 incorporating high-throughput-generated binding data into RegulonDB version 10.0.

BACKGROUND: Our understanding of the regulation of gene expression has benefited from the availability of high-throughput technologies that interrogate the whole genome for the binding of specific transcription factors and gene expression profiles. In the case of widely used model organisms, such as Escherichia coli K-12, the new knowledge gained from these approaches needs to be integrated with the legacy of accumulated knowledge from genetic and molecular biology experiments conducted in the pre-genomic era in order to attain the deepest level of understanding possible based on the available data. RESULTS: In this paper, we describe an expansion of RegulonDB, the database containing the rich legacy of decades of classic molecular biology experiments supporting what we know about gene regulation and operon organization in E. coli K-12, to include the genome-wide dataset collections from 32 ChIP and 19 gSELEX publications, in addition to around 60 genome-wide expression profiles relevant to the functional significance of these datasets and used in their curation. Three essential features for the integration of this information coming from different methodological approaches are: first, a controlled vocabulary within an ontology for precisely defining growth conditions; second, the criteria to separate elements with enough evidence to consider them involved in gene regulation from isolated transcription factor binding sites without such support; and third, an expanded computational model supporting this knowledge. Altogether, this constitutes the basis for adequately gathering and enabling the comparisons and integration needed to manage and access such wealth of knowledge. CONCLUSIONS: This version 10.0 of RegulonDB is a first step toward what should become the unifying access point for current and future knowledge on gene regulation in E. coli K-12. Furthermore, this model platform and associated methodologies and criteria can be emulated for gathering knowledge on other microbial organisms.

Improving biocuration of microRNAs in diseases: a case study in idiopathic pulmonary fibrosis.

MicroRNAs (miRNAs) are small and non-coding RNA molecules that inhibit gene expression posttranscriptionally. They play important roles in several biological processes, and in recent years there has been an interest in studying how they are related to the pathogenesis of diseases. Although there are already some databases that contain information for miRNAs and their relation with illnesses, their curation represents a significant challenge due to the amount of information that is being generated every day. In particular, respiratory diseases are poorly documented in databases, despite the fact that they are of increasing concern regarding morbidity, mortality and economic impacts. In this work, we present the results that we obtained in the BioCreative Interactive Track (IAT), using a semiautomatic approach for improving biocuration of miRNAs related to diseases. Our procedures will be useful to complement databases that contain this type of information. We adapted the OntoGene text mining pipeline and the ODIN curation system in a full-text corpus of scientific publications concerning one specific respiratory disease: idiopathic pulmonary fibrosis, the most common and aggressive of the idiopathic interstitial cases of pneumonia. We curated 823 miRNA text snippets and found a total of 246 miRNAs related to this disease based on our semiautomatic approach with the system OntoGene/ODIN. The biocuration throughput improved by a factor of 12 compared with traditional manual biocuration. A significant advantage of our semiautomatic pipeline is that it can be applied to obtain the miRNAs of all the respiratory diseases and offers the possibility to be used for other illnesses. Database URL: http://odin.ccg.unam.mx/ODIN/bc2015-miRNA/.

In silico clustering of Salmonella global gene expression data reveals novel genes co-regulated with the SPI-1 virulence genes through HilD.

A wide variety of Salmonella enterica serovars cause intestinal and systemic infections to humans and animals. Salmonella Patogenicity Island 1 (SPI-1) is a chromosomal region containing 39 genes that have crucial virulence roles. The AraC-like transcriptional regulator HilD, encoded in SPI-1, positively controls the expression of the SPI-1 genes, as well as of several other virulence genes located outside SPI-1. In this study, we applied a clustering method to the global gene expression data of S. enterica serovar Typhimurium from the COLOMBOS database; thus genes that show an expression pattern similar to that of SPI-1 genes were selected. This analysis revealed nine novel genes that are co-expressed with SPI-1, which are located in different chromosomal regions. Expression analyses and protein-DNA interaction assays showed regulation by HilD for six of these genes: gtgE, phoH, sinR, SL1263 (lpxR) and SL4247 were regulated directly, whereas SL1896 was regulated indirectly. Interestingly, phoH is an ancestral gene conserved in most of bacteria, whereas the other genes show characteristics of genes acquired by Salmonella. A role in virulence has been previously demonstrated for gtgE, lpxR and sinR. Our results further expand the regulon of HilD and thus identify novel possible Salmonella virulence genes.

Chaotic multiquenching annealing applied to the protein folding problem.

The Chaotic Multiquenching Annealing algorithm (CMQA) is proposed. CMQA is a new algorithm, which is applied to protein folding problem (PFP). This algorithm is divided into three phases: (i) multiquenching phase (MQP), (ii) annealing phase (AP), and (iii) dynamical equilibrium phase (DEP). MQP enforces several stages of quick quenching processes that include chaotic functions. The chaotic functions can increase the exploration potential of solutions space of PFP. AP phase implements a simulated annealing algorithm (SA) with an exponential cooling function. MQP and AP are delimited by different ranges of temperatures; MQP is applied for a range of temperatures which goes from extremely high values to very high values; AP searches for solutions in a range of temperatures from high values to extremely low values. DEP phase finds the equilibrium in a dynamic way by applying least squares method. CMQA is tested with several instances of PFP.