Quantification of global transcription patterns in prokaryotes using spotted microarrays

We describe an analysis, applicable to any spotted microarray dataset produced using genomic DNA as a reference, that quantifies prokaryotic levels of mRNA on a genome-wide scale. Applying this to Mycobacterium tuberculosis, we validate the technique, show a correlation between level of expression and biological importance, define the complement of invariant genes and analyze absolute levels of expression by functional class to develop ways of understanding an organism's biology without comparison to another growth condition

Mycobacterium tuberculosis Responds to Chloride and pH as Synergistic Cues to the Immune Status of its Host Cell

PubMed ID: 23592993This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Metabolomic and transcriptomic stress response of Escherichia coli

GC-MS-based analysis of the metabolic response of Escherichia coli exposed to four different stress conditions reveals reduction of energy expensive pathways.Time-resolved response of E. coli to changing environmental conditions is more specific on the metabolite as compared with the transcript level.Cease of growth during stress response as compared with stationary phase response invokes similar transcript but dissimilar metabolite responses.Condition-dependent associations between metabolites and transcripts are revealed applying co-clustering and canonical correlation analysis

Global analyses of TetR family transcriptional regulators in mycobacteria indicates conservation across species and diversity in regulated functions

BACKGROUND: Mycobacteria inhabit diverse niches and display high metabolic versatility. They can colonise both humans and animals and are also able to survive in the environment. In order to succeed, response to environmental cues via transcriptional regulation is required. In this study we focused on the TetR family of transcriptional regulators (TFTRs) in mycobacteria. RESULTS: We used InterPro to classify the entire complement of transcriptional regulators in 10 mycobacterial species and these analyses showed that TFTRs are the most abundant family of regulators in all species. We identified those TFTRs that are conserved across all species analysed and those that are unique to the pathogens included in the analysis. We examined genomic contexts of 663 of the conserved TFTRs and observed that the majority of TFTRs are separated by 200 bp or less from divergently oriented genes. Analyses of divergent genes indicated that the TFTRs control diverse biochemical functions not limited to efflux pumps. TFTRs typically bind to palindromic motifs and we identified 11 highly significant novel motifs in the upstream regions of divergently oriented TFTRs. The C-terminal ligand binding domain from the TFTR complement in M. tuberculosis showed great diversity in amino acid sequence but with an overall architecture common to other TFTRs. CONCLUSION: This study suggests that mycobacteria depend on TFTRs for the transcriptional control of a number of metabolic functions yet the physiological role of the majority of these regulators remain unknown. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1696-9) contains supplementary material, which is available to authorized users

Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound

Lung ultrasound (LUS) is an important imaging modality used by emergency physicians to assess pulmonary congestion at the patient bedside. B-line artifacts in LUS videos are key findings associated with pulmonary congestion. Not only can the interpretation of LUS be challenging for novice operators, but visual quantification of B-lines remains subject to observer variability. In this work, we investigate the strengths and weaknesses of multiple deep learning approaches for automated B-line detection and localization in LUS videos. We curate and publish, BEDLUS, a new ultrasound dataset comprising 1,419 videos from 113 patients with a total of 15,755 expert-annotated B-lines. Based on this dataset, we present a benchmark of established deep learning methods applied to the task of B-line detection. To pave the way for interpretable quantification of B-lines, we propose a novel "single-point" approach to B-line localization using only the point of origin. Our results show that (a) the area under the receiver operating characteristic curve ranges from 0.864 to 0.955 for the benchmarked detection methods, (b) within this range, the best performance is achieved by models that leverage multiple successive frames as input, and (c) the proposed single-point approach for B-line localization reaches an F1-score of 0.65, performing on par with the inter-observer agreement. The dataset and developed methods can facilitate further biomedical research on automated interpretation of lung ultrasound with the potential to expand the clinical utility.Comment: 10 pages, 4 figure

β-Adrenoceptor blockade modulates fusiform gyrus activity to black versus white faces.

INTRODUCTION: The beta-adrenoceptor antagonist propranolol is known to reduce peripheral and central activity of noradrenaline. A recent study found that intervention with propranolol diminished negative implicit racial bias. MATERIALS AND METHOD: The current study used functional magnetic resonance imaging (fMRI) in order to determine the neural correlates of this effect. Healthy volunteers (N = 40) of white ethnic origin received a single oral dose (40 mg) of propranolol, in a randomised, double-blind, parallel group, placebo-controlled design, before viewing unfamiliar faces of same and other race. RESULTS AND DISCUSSION: We found significantly reduced activity in the fusiform gyrus and thalamus following propranolol to out-group faces only. Additionally, propranolol lowered the implicit attitude score, without affecting explicit prejudice measure. CONCLUSION: These findings suggest that noradrenaline pathways might modulate racial bias by acting on the processing of categorisation in the fusiform gyrus

Evidence for Escherichia coli DcuD carrier dependent FOF1-ATPase activity during fermentation of glycerol

During fermentation Escherichia coli excrete succinate mainly via Dcu family carriers. Current work reveals the total and N,N’-dicyclohexylcarbodiimide (DCCD) inhibited ATPase activity at pH 7.5 and 5.5 in E. coli wild type and dcu mutants upon glycerol fermentation. The overall ATPase activity was highest at pH 7.5 in dcuABCD mutant. In wild type cells 50% of the activity came from the FOF1-ATPase but in dcuD mutant it reached ~80%. K+ (100 mM) stimulate total but not DCCD inhibited ATPase activity 40% and 20% in wild type and dcuD mutant, respectively. 90% of overall ATPase activity was inhibited by DCCD at pH 5.5 only in dcuABC mutant. At pH 7.5 the H+ fluxes in E. coli wild type, dcuD and dcuABCD mutants was similar but in dcuABC triple mutant the H+ flux decreased 1.4 fold reaching 1.15 mM/min when glycerol was supplemented. In succinate assays the H+ flux was higher in the strains where DcuD is absent. No significant differences were determined in wild type and mutants specific growth rate except dcuD strain. Taken together it is suggested that during glycerol fermentation DcuD has impact on H+ fluxes, FOF1-ATPase activity and depends on potassium ions

Comparative molecular biological analysis of membrane transport genes in organisms

Comparative analyses of membrane transport genes revealed many differences in the features of transport homeostasis in eight diverse organisms, ranging from bacteria to animals and plants. In bacteria, membrane-transport systems depend mainly on single genes encoding proteins involved in an ATP-dependent pump and secondary transport proteins that use H+ as a co-transport molecule. Animals are especially divergent in their channel genes, and plants have larger numbers of P-type ATPase and secondary active transporters than do other organisms. The secondary transporter genes have diverged evolutionarily in both animals and plants for different co-transporter molecules. Animals use Na+ ions for the formation of concentration gradients across plasma membranes, dependent on secondary active transporters and on membrane voltages that in turn are dependent on ion transport regulation systems. Plants use H+ ions pooled in vacuoles and the apoplast to transport various substances; these proton gradients are also dependent on secondary active transporters. We also compared the numbers of membrane transporter genes in Arabidopsis and rice. Although many transporter genes are similar in these plants, Arabidopsis has a more diverse array of genes for multi-efflux transport and for response to stress signals, and rice has more secondary transporter genes for carbohydrate and nutrient transport