1H NMR spectroscopy-based metabolomics analysis for the diagnosis of symptomatic E. coli-associated urinary tract infection (UTI).

BACKGROUND: Urinary tract infection (UTI) is one of the most common diagnoses in girls and women, and to a lesser extent in boys and men younger than 50 years. Escherichia coli, followed by Klebsiella spp. and Proteus spp., cause 75-90% of all infections. Infection of the urinary tract is identified by growth of a significant number of a single species in the urine, in the presence of symptoms. Urinary culture is an accurate diagnostic method but takes several hours or days to be carried out. Metabolomics analysis aims to identify biomarkers that are capable of speeding up diagnosis. METHODS: Urine samples from 51 patients with a prior diagnosis of Escherichia coli-associated UTI, from 21 patients with UTI caused by other pathogens (bacteria and fungi), and from 61 healthy controls were analyzed. The 1H-NMR spectra were acquired and processed. Multivariate statistical models were applied and their performance was validated using permutation test and ROC curve. RESULTS: Orthogonal Partial Least Squares-discriminant Analysis (OPLS-DA) showed good separation (R2Y = 0.76, Q2=0.45, p < 0.001) between UTI caused by Escherichia coli and healthy controls. Acetate and trimethylamine were identified as discriminant metabolites. The concentrations of both metabolites were calculated and used to build the ROC curves. The discriminant metabolites identified were also evaluated in urine samples from patients with other pathogens infections to test their specificity. CONCLUSIONS: Acetate and trimethylamine were identified as optimal candidates for biomarkers for UTI diagnosis. The conclusions support the possibility of a fast diagnostic test for Escherichia coli-associated UTI using acetate and trimethylamine concentrations

Proteome analsyis of Translocation phenomenon

Escherichia coli is the most widely used bacterial model organism and is the most commonly used host for the expression of recombinant proteins. Here we describe an unexpected protein translocation phenomenon in E. coli, whereby over-expression of recombinant proteins leads to high-level lysis-independent, mechanosensitive channel (MscL) dependent release of recombinant protein into the periplasmic space. Protein accumulation in the periplasm leads to protein release into the extracellular environment, independent of outer membrane vesicle formation. The translocated proteins retain their corresponding biological activity, and can be isolated directly from the extracellular medium with high purity and yield. Condition-specific metabolomic and proteomic analyses combined with statistical enrichment analysis indicate a role of both osmotic and translational stress responses in the regulation of the MscL-dependent translocation phenomenon. We suggest a model coupling translational stress to the regulation of MscL via the action of both osmotic stress and the Alternative ribosome-rescue factor A (ArfA) to explain this potentially very useful phenomenon

Baseline Proteomics Characterisation of Biomanufacturing Organism Halomonas Bluephagenesis

Biomanufacturing remains financially uncompetitive with the lower cost but higher carbon emitting hydrocarbon based chemical industry. Novel chassis organisms may enable cost reductions with respect to traditional chassis such as E. coli and so open an economic rout to low emission biomanufacturing. Extremophile bacteria exemplify that potential. Salt tolerant halomonas species thrive in conditions inimical to other organisms. Their adoption would eliminate the cost of sterilising equipment. Novel chassis are inevitably poorly understood in comparison to established organisms. Rapid characterisation and community data sharing will facilitate organisms’ adoption for biomanufacturing. This paper describes baseline proteomics data set for Halomonas bluephagenesis TD01 under active development for biomanufactoring. The data record comprises a newly sequenced genome for the organism; evidence for expression of 1150 proteins (30% of the proteome) including baseline quantification of 1050 proteins (27% of the proteome) and a spectral library enabling re-use for targeted proteomics assays. Protein data is annotated with KEGG Orthology enabling rapid matching of quantitative data to pathways of interest to biomanufacturing

Ligand docking models of vanillic acid decarboxylase (VdcCD)

Files used for, and generated by, Autodock Vina ligand dockin

Development and validation of an updated computational model of Streptomyces coelicolor primary and secondary metabolism

Abstract Background Streptomyces species produce a vast diversity of secondary metabolites of clinical and biotechnological importance, in particular antibiotics. Recent developments in metabolic engineering, synthetic and systems biology have opened new opportunities to exploit Streptomyces secondary metabolism, but achieving industry-level production without time-consuming optimization has remained challenging. Genome-scale metabolic modelling has been shown to be a powerful tool to guide metabolic engineering strategies for accelerated strain optimization, and several generations of models of Streptomyces metabolism have been developed for this purpose. Results Here, we present the most recent update of a genome-scale stoichiometric constraint-based model of the metabolism of Streptomyces coelicolor, the major model organism for the production of antibiotics in the genus. We show that the updated model enables better metabolic flux and biomass predictions and facilitates the integrative analysis of multi-omics data such as transcriptomics, proteomics and metabolomics. Conclusions The updated model presented here provides an enhanced basis for the next generation of metabolic engineering attempts in Streptomyces

CCDC 840438: Experimental Crystal Structure Determination

Related Article: A.March-Cortijos, T.J.Snape, N.J.Turner|2012|Synlett|23|1511|doi:10.1055/s-0031-129101

CCDC 840439: Experimental Crystal Structure Determination

Related Article: A.March-Cortijos, T.J.Snape, N.J.Turner|2012|Synlett|23|1511|doi:10.1055/s-0031-129101

Molecular structures enumeration and virtual screening in the chemical space with RetroPath2.0

Abstract Background Network generation tools coupled with chemical reaction rules have been mainly developed for synthesis planning and more recently for metabolic engineering. Using the same core algorithm, these tools apply a set of rules to a source set of compounds, stopping when a sink set of compounds has been produced. When using the appropriate sink, source and rules, this core algorithm can be used for a variety of applications beyond those it has been developed for. Results Here, we showcase the use of the open source workflow RetroPath2.0. First, we mathematically prove that we can generate all structural isomers of a molecule using a reduced set of reaction rules. We then use this enumeration strategy to screen the chemical space around a set of monomers and predict their glass transition temperatures, as well as around aminoglycosides to search structures maximizing antibacterial activity. We also perform a screening around aminoglycosides with enzymatic reaction rules to ensure biosynthetic accessibility. We finally use our workflow on an E. coli model to complete E. coli metabolome, with novel molecules generated using promiscuous enzymatic reaction rules. These novel molecules are searched on the MS spectra of an E. coli cell lysate interfacing our workflow with OpenMS through the KNIME Analytics Platform. Conclusion We provide an easy to use and modify, modular, and open-source workflow. We demonstrate its versatility through a variety of use cases including molecular structure enumeration, virtual screening in the chemical space, and metabolome completion. Because it is open source and freely available on MyExperiment.org, workflow community contributions should likely expand further the features of the tool, even beyond the use cases presented in the paper

Discovery of a new metal and NAD⁺-dependent formate dehydrogenase from Clostridium ljungdahlii

Over the next decades, with the growing concern of rising atmospheric carbon dioxide (CO2) levels, the importance of investigating new approaches for its reduction becomes crucial. Reclamation of CO2 for conversion into biofuels represents an alternative and attractive production method that has been studied in recent years, now with enzymatic methods gaining more attention. Formate dehydrogenases (FDHs) are NAD(P)H-dependent oxidoreductases that catalyze the conversion of formate into CO2 and have been extensively used for cofactor recycling in chemoenzymatic processes. A new FDH from Clostridium ljungdahlii (ClFDH) has been recently shown to possess activity in the reverse reaction: the mineralization of CO2 into formate. In this study, we show the successful homologous expression of ClFDH in Escherichia coli. Biochemical and kinetic characterization of the enzyme revealed that this homologue also demonstrates activity toward CO2 reduction. Structural analysis of the enzyme through homology modeling is also presented

CCDC 755434: Experimental Crystal Structure Determination

Related Article: V.Kohler, K.R.Bailey, A.Znabet, J.Raftery, M.Helliwell, N.J.Turner|2010|Angew.Chem.,Int.Ed.|49|2182|doi:10.1002/anie.20090665