AMBIENT: Active Modules for Bipartite Networks - using high-throughput transcriptomic data to dissect metabolic response

BACKGROUND: With the continued proliferation of high-throughput biological experiments, there is a pressing need for tools to integrate the data produced in ways that produce biologically meaningful conclusions. Many microarray studies have analysed transcriptomic data from a pathway perspective, for instance by testing for KEGG pathway enrichment in sets of upregulated genes. However, the increasing availability of species-specific metabolic models provides the opportunity to analyse these data in a more objective, system-wide manner. RESULTS: Here we introduce ambient (Active Modules for Bipartite Networks), a simulated annealing approach to the discovery of metabolic subnetworks (modules) that are significantly affected by a given genetic or environmental change. The metabolic modules returned by ambient are connected parts of the bipartite network that change coherently between conditions, providing a more detailed view of metabolic changes than standard approaches based on pathway enrichment. CONCLUSIONS: ambient is an effective and flexible tool for the analysis of high-throughput data in a metabolic context. The same approach can be applied to any system in which reactions (or metabolites) can be assigned a score based on some biological observation, without the limitation of predefined pathways. A Python implementation of ambient is available at http://www.theosysbio.bio.ic.ac.uk/ambient

Deciphering the response of Mycobacterium smegmatis to nitrogen stress using bipartite active modules.

Background The ability to adapt to environments with fluctuating nutrient availability is vital for bacterial survival. Although essential for growth, few nitrogen metabolism genes have been identified or fully characterised in mycobacteria and nitrogen stress survival mechanisms are unknown. Results A global transcriptional analysis of the mycobacterial response to nitrogen stress, showed a significant change in the differential expression of 16% of the Mycobacterium smegmatis genome. Gene expression changes were mapped onto the metabolic network using Active Modules for Bipartite Networks (AMBIENT) to identify metabolic pathways showing coordinated transcriptional responses to the stress. AMBIENT revealed several key features of the metabolic response not identified by KEGG enrichment alone. Down regulated reactions were associated with the general reduction in cellular metabolism as a consequence of reduced growth rate. Up-regulated modules highlighted metabolic changes in nitrogen assimilation and scavenging, as well as reactions involved in hydrogen peroxide metabolism, carbon scavenging and energy generation. Conclusions Application of an Active Modules algorithm to transcriptomic data identified key metabolic reactions and pathways altered in response to nitrogen stress, which are central to survival under nitrogen limiting environments

Psychological impact of injuries sustained in motor vehicle crashes: Systematic review and meta-analysis

Objective: The aim of this meta-analysis was to determine the psychological impact associated with motor vehicle crash (MVC)-related physical injuries. Design: Systematic review and meta-analysis. Data sources: Multiple search engines included MEDLINE (via OVID), PsycINFO and Embase, and studies were sourced from scientific journals, conference papers and doctoral theses. Study selection: A high-yield search strategy was employed. Terms like 'psychological distress', 'depression', 'PTSD' and 'motor vehicle accident' were employed. These key words were run primarily and secondary searches were then conducted in association with the major injury types. Studies needed to compare psychological distress in people injured in an MVC with uninjured controls who had not recently experienced an MVC. Data extraction: Searches resulted in the identification of 2537 articles, and after eliminating duplicates and studies not meeting inclusion criteria, 24 studies were selected involving 4502 injured participants. These studies were entered into separate meta-analyses for mild to moderate traumatic brain injury (mTBI), whiplash-associated disorder (WAD) and spinal cord injury (SCI). Results: Elevated psychological distress was associated with MVC-related injuries with a large summary effect size in WAD (0.90), medium to large effect size in SCI (0.69) and small to medium effect size in mTBI (0.23). No studies meeting inclusion criteria were found for burns, fractures and low back injury. Increased psychological distress remains elevated in SCI, mTBI and WAD for at least 3 years post-MVC. Conclusions: Rehabilitation strategies are needed to minimise distress subsequent to MVC-related physical injuries and the scientific robustness of studies requires improvement

Improved Understanding of the Ball-Pen Probe through Particle-In-Cell Simulations

Ball-pen probes (BPP)have been deployed in the SOL of numerous tokamak experiments and low-temperature magnetised plasmas to make direct measurements of the plasma potential and electron temperature. Despite strong empirical evidence for the success of the BPP it lacks a theoretical underpinning of its collection mechanism. In this paper we investigate the capability of the probe to measure the plasma potential by means of particle-in-cell simulations. The BPP is found to float at a potential offset from the plasma potential by a factor TₑαBPP. By simulating BPPs and Langmuir probes, excellent agreement has been found between the measured electron temperature and the specified source temperature. The transport mechanism for both ions and electrons has been determined.E×B drifts are observed to drive electrons and ions down the tunnel. This mechanism is sensitive to the diameter of the prob

Modeling Bacterial DNA: Simulation of Self-avoiding Supercoiled Worm-Like Chains Including Structural Transitions of the Helix

Under supercoiling constraints, naked DNA, such as a large part of bacterial DNA, folds into braided structures called plectonemes. The double-helix can also undergo local structural transitions, leading to the formation of denaturation bubbles and other alternative structures. Various polymer models have been developed to capture these properties, with Monte-Carlo (MC) approaches dedicated to the inference of thermodynamic properties. In this chapter, we explain how to perform such Monte-Carlo simulations, following two objectives. On one hand, we present the self-avoiding supercoiled Worm-Like Chain (ssWLC) model, which is known to capture the folding properties of supercoiled DNA, and provide a detailed explanation of a standard MC simulation method. On the other hand, we explain how to extend this ssWLC model to include structural transitions of the helix.Comment: Book chapter to appear in The Bacterial Nucleoid, Methods and Protocols, Springer serie

Identification of possible virulence marker from Campylobacter jejuni isolates

This is the final version of the article. Available from the publisher via the DOI in this record.A novel protein translocation system, the type-6 secretion system (T6SS), may play a role in virulence of Campylobacter jejuni. We investigated 181 C. jejuni isolates from humans, chickens, and environmental sources in Vietnam, Thailand, Pakistan, and the United Kingdom for T6SS. The marker was most prevalent in human and chicken isolates from Vietnam.The work was partly supported by the UK Biotechnology and Biological Sciences Research Council, award BB/1024631/1 to R.T., D.S., and O.C.; by a Wellcome Trust Institutional Strategic Support Award (WT097835MF); and by a studentship awarded to J.H. Mr Harrison is a PhD student at the University of Exeter under the supervision of D.S. His research focuses on using bioinformatic methods to investigate the comparative genomics of emerging diseases and plant-associated microbes

Neurospora from natural populations: Population genomics insights into the Life history of a model microbial Eukaryote

The ascomycete filamentous fungus Neurospora crassa played a historic role in experimental biology and became a model system for genetic research. Stimulated by a systematic effort to collect wild strains initiated by Stanford geneticist David Perkins, the genus Neurospora has also become a basic model for the study of evolutionary processes, speciation, and population biology. In this chapter, we will first trace the history that brought Neurospora into the era of population genomics. We will then cover the major contributions of population genomic investigations using Neurospora to our understanding of microbial biogeography and speciation, and review recent work using population genomics and genome-wide association mapping that illustrates the unique potential of Neurospora as a model for identifying the genetic basis of (potentially adaptive) phenotypes in filamentous fungi. The advent of population genomics has contributed to firmly establish Neurospora as a complete model system and we hope our review will entice biologists to include Neurospora in their research

A fresh look at the evolution and diversification of photochemical reaction centers

In this review, I reexamine the origin and diversification of photochemical reaction centers based on the known phylogenetic relations of the core subunits, and with the aid of sequence and structural alignments. I show, for example, that the protein folds at the C-terminus of the D1 and D2 subunits of Photosystem II, which are essential for the coordination of the water-oxidizing complex, were already in place in the most ancestral Type II reaction center subunit. I then evaluate the evolution of reaction centers in the context of the rise and expansion of the different groups of bacteria based on recent large-scale phylogenetic analyses. I find that the Heliobacteriaceae family of Firmicutes appears to be the earliest branching of the known groups of phototrophic bacteria; however, the origin of photochemical reaction centers and chlorophyll synthesis cannot be placed in this group. Moreover, it becomes evident that the Acidobacteria and the Proteobacteria shared a more recent common phototrophic ancestor, and this is also likely for the Chloroflexi and the Cyanobacteria. Finally, I argue that the discrepancies among the phylogenies of the reaction center proteins, chlorophyll synthesis enzymes, and the species tree of bacteria are best explained if both types of photochemical reaction centers evolved before the diversification of the known phyla of phototrophic bacteria. The primordial phototrophic ancestor must have had both Type I and Type II reaction centers

Changes in circulating microRNA levels associated with prostate cancer

BACKGROUND: The aim of this study was to investigate the hypothesis that changes in circulating microRNAs (miRs) represent potentially useful biomarkers for the diagnosis, staging and prediction of outcome in prostate cancer. METHODS: Real-time polymerase chain reaction analysis of 742 miRs was performed using plasma-derived circulating microvesicles of 78 prostate cancer patients and 28 normal control individuals to identify differentially quantified miRs. RESULTS: A total of 12 miRs were differentially quantified in prostate cancer patients compared with controls, including 9 in patients without metastases. In all, 11 miRs were present in significantly greater amounts in prostate cancer patients with metastases compared with those without metastases. The association of miR-141 and miR-375 with metastatic prostate cancer was confirmed using serum-derived exosomes and microvesicles in a separate cohort of patients with recurrent or non-recurrent disease following radical prostatectomy. An analysis of five selected miRs in urine samples found that miR-107 and miR-574-3p were quantified at significantly higher concentrations in the urine of men with prostate cancer compared with controls. CONCLUSION: These observations suggest that changes in miR concentration in prostate cancer patients may be identified by analysing various body fluids. Moreover, circulating miRs may be used to diagnose and stage prostate cance