A Novel Glucose 6-Phosphate Isomerase from Listeria monocytogenes

d-Arabinose 5-phosphate isomerases (APIs) catalyze the interconversion of d-ribulose 5-phosphate and d-arabinose 5-phosphate (A5P). A5P is an intermediate in the biosynthesis of 3-deoxy-d-manno-octulosonate (Kdo), an essential component of lipopolysaccharide, the lipopolysaccharide found in the outer membrane of Gram-negative bacteria. The genome of the Gram-positive pathogen Listeria monocytogenes contains a gene encoding a putative sugar isomerase domain API, Q723E8, with significant similarity to c3406, the only one of four APIs from Escherichia coli CFT073 that lacks a cystathionine-β-synthase domain. However, L. monocytogenes lacks genes encoding any of the other enzymes of the Kdo biosynthesis pathway. Realizing that the discovery of an API in a Gram-positive bacterium could provide insight into an alternate physiological role of A5P in the cell, we prepared and purified recombinant Q723E8. We found that Q723E8 does not possess API activity, but instead is a novel GPI (d-glucose 6-phosphate isomerase). However, the GPI activity of Q723E8 is weak compared with previously described GPIs. L. monocytogenes contains an ortholog of the well-studied two-domain bacterial GPI, so this maybe redundant. Based on this evidence glucose utilization is likely not the primary physiological role of Q723E8.     

How well can post-traumatic stress disorder be predicted from pre-trauma risk factors? An exploratory study in the WHO World Mental Health Surveys

Post‐traumatic stress disorder (PTSD) should be one of the most preventable mental disorders, since many people exposed to traumatic experiences (TEs) could be targeted in first response settings in the immediate aftermath of exposure for preventive intervention. However, these interventions are costly and the proportion of TE‐exposed people who develop PTSD is small. To be cost‐effective, risk prediction rules are needed to target high‐risk people in the immediate aftermath of a TE. Although a number of studies have been carried out to examine prospective predictors of PTSD among people recently exposed to TEs, most were either small or focused on a narrow sample, making it unclear how well PTSD can be predicted in the total population of people exposed to TEs. The current report investigates this issue in a large sample based on the World Health Organization (WHO)'s World Mental Health Surveys. Retrospective reports were obtained on the predictors of PTSD associated with 47,466 TE exposures in representative community surveys carried out in 24 countries. Machine learning methods (random forests, penalized regression, super learner) were used to develop a model predicting PTSD from information about TE type, socio‐demographics, and prior histories of cumulative TE exposure and DSM‐IV disorders. DSM‐IV PTSD prevalence was 4.0% across the 47,466 TE exposures. 95.6% of these PTSD cases were associated with the 10.0% of exposures (i.e., 4,747) classified by machine learning algorithm as having highest predicted PTSD risk. The 47,466 exposures were divided into 20 ventiles (20 groups of equal size) ranked by predicted PTSD risk. PTSD occurred after 56.3% of the TEs in the highest‐risk ventile, 20.0% of the TEs in the second highest ventile, and 0.0‐1.3% of the TEs in the 18 remaining ventiles. These patterns of differential risk were quite stable across demographic‐geographic sub‐samples. These results demonstrate that a sensitive risk algorithm can be created using data collected in the immediate aftermath of TE exposure to target people at highest risk of PTSD. However, validation of the algorithm is needed in prospective samples, and additional work is warranted to refine the algorithm both in terms of determining a minimum required predictor set and developing a practical administration and scoring protocol that can be used in routine clinical practice.     

Temperature explains variable spread rates of the invasive woodwasp Sirex noctilio in the Southern Hemisphere

The frequency of introductions of non-indigenous forest insects into new habitats is increasing worldwide, often with profoundly adverse consequences on natural and plantation forest ecosystems. Understanding rates and patterns of spread of invasive forest insects is important for predicting when and where these species will expand their geographical range, with the potential to improve mitigation strategies. The woodwasp Sirex noctilio is a damaging invasive forest insect that kills numerous species of Pinus. Despite encountering highly variable eco-climatic conditions, S. noctilio has arrived and established in exotic pine forest production areas throughout the Southern Hemisphere. In this study, we compiled historical records of S. noctilio invasion to compare spread rates among eight contrasting eco-climatic regions in the Southern Hemisphere and to explore how spread rate is predicted by landscape variation in climate, habitat characteristics and anthropogenic effects. Spread rates for S. noctilio varied considerably among the invaded regions, ranging from 12 to 82 km per year. Among regions, spread rates of S. noctilio increased with increasing mean annual temperature and isothermality. We hypothesize that temperature may directly or indirectly influence S. noctilio population growth and dispersal, thereby influencing spread rates.     

In situ visualization of newly synthesized proteins in environmental microbes using amino acid tagging and click chemistry

Here we describe the application of a new click chemistry method for fluorescent tracking of protein synthesis in individual microorganisms within environmental samples. This technique, termed bioorthogonal non‐canonical amino acid tagging (BONCAT), is based on the in vivo incorporation of the non‐canonical amino acid L‐azidohomoalanine (AHA), a surrogate for l ‐methionine, followed by fluorescent labelling of AHA‐containing cellular proteins by azide‐alkyne click chemistry. BONCAT was evaluated with a range of phylogenetically and physiologically diverse archaeal and bacterial pure cultures and enrichments, and used to visualize translationally active cells within complex environmental samples including an oral biofilm, freshwater and anoxic sediment. We also developed combined assays that couple BONCAT with ribosomal RNA (rRNA)‐targeted fluorescence in situ hybridization (FISH), enabling a direct link between taxonomic identity and translational activity. Using a methanotrophic enrichment culture incubated under different conditions, we demonstrate the potential of BONCAT‐FISH to study microbial physiology in situ. A direct comparison of anabolic activity using BONCAT and stable isotope labelling by nano‐scale secondary ion mass spectrometry (¹⁵NH₃ assimilation) for individual cells within a sediment‐sourced enrichment culture showed concordance between AHA‐positive cells and ¹⁵N enrichment. BONCAT‐FISH offers a fast, inexpensive and straightforward fluorescence microscopy method for studying the in situ activity of environmental microbes on a single‐cell level.     

The Natural Antimicrobial Carvacrol Inhibits Quorum Sensing in Chromobacterium violaceum and Reduces Bacterial Biofilm Formation at Sub-Lethal Concentrations

The formation of biofilm by bacteria confers resistance to biocides and presents problems in medical and veterinary clinical settings. Here we report the effect of carvacrol, one of the major antimicrobial components of oregano oil, on the formation of biofilms and its activity on existing biofilms. Assays were carried out in polystyrene microplates to observe (a) the effect of 0–0.8 mM carvacrol on the formation of biofilms by selected bacterial pathogens over 24 h and (b) the effect of 0–8 mM carvacrol on the stability of pre-formed biofilms. Carvacrol was able to inhibit the formation of biofilms of Chromobacterium violaceum ATCC 12472, Salmonella enterica subsp. Typhimurium DT104, and Staphylococcus aureus 0074, while it showed no effect on formation of Pseudomonas aeruginosa (field isolate) biofilms. This inhibitory effect of carvacrol was observed at sub-lethal concentrations (<0.5 mM) where no effect was seen on total bacterial numbers, indicating that carvacrol''s bactericidal effect was not causing the observed inhibition of biofilm formation. In contrast, carvacrol had (up to 8 mM) very little or no activity against existing biofilms of the bacteria described, showing that formation of the biofilm also confers protection against this compound. Since quorum sensing is an essential part of biofilm formation, the effect of carvacrol on quorum sensing of C. violaceum was also studied. Sub-MIC concentrations of carvacrol reduced expression of cviI (a gene coding for the N-acyl-L-homoserine lactone synthase), production of violacein (pigmentation) and chitinase activity (both regulated by quorum sensing) at concentrations coinciding with carvacrol''s inhibiting effect on biofilm formation. These results indicate that carvacrol''s activity in inhibition of biofilm formation may be related to the disruption of quorum sensing.     

Bioinformatics Pipelines for Targeted Resequencing and Whole-Exome Sequencing of Human and Mouse Genomes: A Virtual Appliance Approach for Instant Deployment

Targeted resequencing by massively parallel sequencing has become an effective and affordable way to survey small to large portions of the genome for genetic variation. Despite the rapid development in open source software for analysis of such data, the practical implementation of these tools through construction of sequencing analysis pipelines still remains a challenging and laborious activity, and a major hurdle for many small research and clinical laboratories. We developed TREVA (Targeted REsequencing Virtual Appliance), making pre-built pipelines immediately available as a virtual appliance. Based on virtual machine technologies, TREVA is a solution for rapid and efficient deployment of complex bioinformatics pipelines to laboratories of all sizes, enabling reproducible results. The analyses that are supported in TREVA include: somatic and germline single-nucleotide and insertion/deletion variant calling, copy number analysis, and cohort-based analyses such as pathway and significantly mutated genes analyses. TREVA is flexible and easy to use, and can be customised by Linux-based extensions if required. TREVA can also be deployed on the cloud (cloud computing), enabling instant access without investment overheads for additional hardware. TREVA is available at http://bioinformatics.petermac.org/treva/.