Genome-level analyses of Mycobacterium bovis lineages reveal the role of SNPs and antisense transcription in differential gene expression

BACKGROUND: Bovine tuberculosis (bTB) is a disease with major implications for animal welfare and productivity, as well as having the potential for zoonotic transmission. In Great Britain (GB) alone, controlling bTB costs in the region of £100 million annually, with the current control scheme seemingly unable to stop the inexorable spread of infection. One aspect that may be driving the epidemic is evolution of the causative pathogen, Mycobacterium bovis. To understand the underlying genetic changes that may be responsible for this evolution, we performed a comprehensive genome-level analyses of 4 M. bovis strains that encompass the main molecular types of the pathogen circulating in GB. RESULTS: We have used a combination of genome sequencing, transcriptome analyses, and recombinant DNA technology to define genetic differences across the major M. bovis lineages circulating in GB that may give rise to phenotypic differences of practical importance. The genomes of three M. bovis field isolates were sequenced using Illumina sequencing technology and strain specific differences in gene expression were measured during in vitro growth and in ex vivo bovine alveolar macrophages using a whole genome amplicon microarray and a whole genome tiled oligonucleotide microarray. SNP/small base pair insertion and deletions and gene expression data were overlaid onto the genomic sequence of the fully sequenced strain of M. bovis 2122/97 to link observed strain specific genomic differences with differences in RNA expression. CONCLUSIONS: We show that while these strains show extensive similarities in their genetic make-up and gene expression profiles, they exhibit distinct expression of a subset of genes. We provide genomic, transcriptomic and functional data to show that synonymous point mutations (sSNPs) on the coding strand can lead to the expression of antisense transcripts on the opposing strand, a finding with implications for how we define a 'silent’ nucleotide change. Furthermore, we show that transcriptomic data based solely on amplicon arrays can generate spurious results in terms of gene expression profiles due to hybridisation of antisense transcripts. Overall our data suggest that subtle genetic differences, such as sSNPS, may have important consequences for gene expression and subsequent phenotype

TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance

We propose a geometric deep-learning-based framework, TractGeoNet, for performing regression using diffusion magnetic resonance imaging (dMRI) tractography and associated pointwise tissue microstructure measurements. By employing a point cloud representation, TractGeoNet can directly utilize pointwise tissue microstructure and positional information from all points within a fiber tract. To improve regression performance, we propose a novel loss function, the Paired-Siamese Regression loss, which encourages the model to focus on accurately predicting the relative differences between regression label scores rather than just their absolute values. In addition, we propose a Critical Region Localization algorithm to identify highly predictive anatomical regions within the white matter fiber tracts for the regression task. We evaluate the effectiveness of the proposed method by predicting individual performance on two neuropsychological assessments of language using a dataset of 20 association white matter fiber tracts from 806 subjects from the Human Connectome Project. The results demonstrate superior prediction performance of TractGeoNet compared to several popular regression models. Of the twenty tracts studied, we find that the left arcuate fasciculus tract is the most highly predictive of the two studied language performance assessments. The localized critical regions are widespread and distributed across both hemispheres and all cerebral lobes, including areas of the brain considered important for language function such as superior and anterior temporal regions, pars opercularis, and precentral gyrus. Overall, TractGeoNet demonstrates the potential of geometric deep learning to enhance the study of the brain's white matter fiber tracts and to relate their structure to human traits such as language performance.Comment: 28 pages, 7 figure

Comparison of Mental Toughness and Power Test Performances in High-Level Kickboxers by Competitive Success

Background Kickboxing is a high-intensity intermittent striking combat sport, which is characterized by complex skills and tactical key actions with short duration. Objectives The present study compared and verified the relationship between mental toughness (MT), countermovement jump (CMJ) and medicine ball throw (MBT) power tests by outcomes of high-level kickboxers during National Championship. Materials and Methods Thirty two high-level male kickboxers (winner = 16 and loser = 16: 21.2 ± 3.1 years, 1.73 ± 0.07 m, and 70.2 ± 9.4 kg) were analyzed using the CMJ, MBT tests and sports mental toughness questionnaire (SMTQ; based in confidence, constancy and control subscales), before the fights of the 2015 national championship (16 bouts). In statistical analysis, Mann-Withney test and a multiple linear regression were used to compare groups and to observe relationships, respectively, P ≤ 0.05. Results The present results showed significant differences between losers vs. winners, respectively, of total MT (7(7;8) vs. 11(10.2;11), confidence (3(3;3) vs. 4(4;4)), constancy (2(2;2) vs. 3(3;3)), control (2(2;3) vs. 4(4;4)) subscales and MBT (4.1(4;4.3) vs. 4.6(4.4;4.8)). The multiple linear regression showed a strong associations between MT results and outcome (r = 0.89), MBT (r = 0.84) and CMJ (r = 0.73). Conclusions The findings suggest that MT will be more predictive of performance in those sports and in the outcome of competition.Ministry of Higher Teaching and Scientific Research, Tunisi

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

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

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

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

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