Aerial dissemination of Clostridium difficile spores

Background: Clostridium difficile-associated diarrhoea (CDAD) is a frequently occurring healthcare-associated infection, which is responsible for significant morbidity and mortality amongst elderly patients in healthcare facilities. Environmental contamination is known to play an important contributory role in the spread of CDAD and it is suspected that contamination might be occurring as a result of aerial dissemination of C. difficile spores. However previous studies have failed to isolate C. difficile from air in hospitals. In an attempt to clarify this issue we undertook a short controlled pilot study in an elderly care ward with the aim of culturing C. difficile from the air. Methods: In a survey undertaken during February (two days) 2006 and March (two days) 2007, air samples were collected using a portable cyclone sampler and surface samples collected using contact plates in a UK hospital. Sampling took place in a six bedded elderly care bay (Study) during February 2006 and in March 2007 both the study bay and a four bedded orthopaedic bay (Control). Particulate material from the air was collected in Ringer's solution, alcohol shocked and plated out in triplicate onto Brazier's CCEY agar without egg yolk, but supplemented with 5 mg/L of lysozyme. After incubation, the identity of isolates was confirmed by standard techniques. Ribotyping and REP-PCR fingerprinting were used to further characterise isolates. Results: On both days in February 2006, C. difficile was cultured from the air with 23 samples yielding the bacterium (mean counts 53 – 426 cfu/m3 of air). One representative isolate from each of these was characterized further. Of the 23 isolates, 22 were ribotype 001 and were indistinguishable on REP-PCR typing. C. difficile was not cultured from the air or surfaces of either hospital bay during the two days in March 2007. Conclusion: This pilot study produced clear evidence of sporadic aerial dissemination of spores of a clone of C. difficile, a finding which may help to explain why CDAD is so persistent within hospitals and difficult to eradicate. Although preliminary, the findings reinforce concerns that current C. difficile control measures may be inadequate and suggest that improved ward ventilation may help to reduce the spread of CDAD in healthcare facilities

NIBBS-Search for Fast and Accurate Prediction of Phenotype-Biased Metabolic Systems

Understanding of genotype-phenotype associations is important not only for furthering our knowledge on internal cellular processes, but also essential for providing the foundation necessary for genetic engineering of microorganisms for industrial use (e.g., production of bioenergy or biofuels). However, genotype-phenotype associations alone do not provide enough information to alter an organism's genome to either suppress or exhibit a phenotype. It is important to look at the phenotype-related genes in the context of the genome-scale network to understand how the genes interact with other genes in the organism. Identification of metabolic subsystems involved in the expression of the phenotype is one way of placing the phenotype-related genes in the context of the entire network. A metabolic system refers to a metabolic network subgraph; nodes are compounds and edges labels are the enzymes that catalyze the reaction. The metabolic subsystem could be part of a single metabolic pathway or span parts of multiple pathways. Arguably, comparative genome-scale metabolic network analysis is a promising strategy to identify these phenotype-related metabolic subsystems. Network Instance-Based Biased Subgraph Search (NIBBS) is a graph-theoretic method for genome-scale metabolic network comparative analysis that can identify metabolic systems that are statistically biased toward phenotype-expressing organismal networks. We set up experiments with target phenotypes like hydrogen production, TCA expression, and acid-tolerance. We show via extensive literature search that some of the resulting metabolic subsystems are indeed phenotype-related and formulate hypotheses for other systems in terms of their role in phenotype expression. NIBBS is also orders of magnitude faster than MULE, one of the most efficient maximal frequent subgraph mining algorithms that could be adjusted for this problem. Also, the set of phenotype-biased metabolic systems output by NIBBS comes very close to the set of phenotype-biased subgraphs output by an exact maximally-biased subgraph enumeration algorithm ( MBS-Enum ). The code (NIBBS and the module to visualize the identified subsystems) is available at http://freescience.org/cs/NIBBS

Novel Small-Molecule Inhibitors of Hepatitis C Virus Entry Block Viral Spread and Promote Viral Clearance in Cell Culture

Combinations of direct-acting anti-virals offer the potential to improve the efficacy, tolerability and duration of the current treatment regimen for hepatitis C virus (HCV) infection. Viral entry represents a distinct therapeutic target that has been validated clinically for a number of pathogenic viruses. To discover novel inhibitors of HCV entry, we conducted a high throughput screen of a proprietary small-molecule compound library using HCV pseudoviral particle (HCVpp) technology. We independently discovered and optimized a series of 1,3,5-triazine compounds that are potent, selective and non-cytotoxic inhibitors of HCV entry. Representative compounds fully suppress both cell-free virus and cell-to-cell spread of HCV in vitro. We demonstrate, for the first time, that long term treatment of an HCV cell culture with a potent entry inhibitor promotes sustained viral clearance in vitro. We have confirmed that a single amino acid variant, V719G, in the transmembrane domain of E2 is sufficient to confer resistance to multiple compounds from the triazine series. Resistance studies were extended by evaluating both the fusogenic properties and growth kinetics of drug-induced and natural amino acid variants in the HCVpp and HCV cell culture assays. Our results indicate that amino acid variations at position 719 incur a significant fitness penalty. Introduction of I719 into a genotype 1b envelope sequence did not affect HCV entry; however, the overall level of HCV replication was reduced compared to the parental genotype 1b/2a HCV strain. Consistent with these findings, I719 represents a significant fraction of the naturally occurring genotype 1b sequences. Importantly, I719, the most relevant natural polymorphism, did not significantly alter the susceptibility of HCV to the triazine compounds. The preclinical properties of these triazine compounds support further investigation of entry inhibitors as a potential novel therapy for HCV infection

Patients' hands and healthcare-associated infection

NoNot availabl

Change-point models for identifying behavioral transitions in wild animals

Abstract Animal behavior can be difficult, time-consuming, and costly to observe in the field directly. Innovative modeling methods, such as hidden Markov models (HMMs), allow researchers to infer unobserved animal behaviors from movement data, and implementations often assume that transitions between states occur multiple times. However, some behavioral shifts of interest, such as parturition, migration initiation, and juvenile dispersal, may only occur once during an observation period, and HMMs may not be the best approach to identify these changes. We present two change-point models for identifying single transitions in movement behavior: a location-based change-point model and a movement metric-based change-point model. We first conducted a simulation study to determine the ability of these models to detect a behavioral transition given different amounts of data and the degree of behavioral shifts. We then applied our models to two ungulate species in central Pennsylvania that were fitted with global positioning system collars and vaginal implant transmitters to test hypotheses related to parturition behavior. We fit these models in a Bayesian framework and directly compared the ability of each model to describe the parturition behavior across species. Our simulation study demonstrated that successful change point estimation using either model was possible given at least 12 h of post-change observations and 15 min fix interval. However, our models received mixed support among deer and elk in Pennsylvania due to behavioral variation between species and among individuals. Our results demonstrate that when the behavior follows the dynamics proposed by the two models, researchers can identify the timing of a behavioral change. Although we refer to detecting parturition events, our results can be applied to any behavior that results in a single change in time

TCA and rTCA metabolic pathways.

<p>TCA cycle: gray arrows; rTCA: black arrows; EC numbers: white boxes; Pathway specific EC numbers: TCA-specific (gray), rTCA-specific (black).</p

List of top ranking pathways and their enrichment score for the phenotype dark fermentative hydrogen production.

<p>List of top ranking pathways and their enrichment score for the phenotype dark fermentative hydrogen production.</p

Approximation Accuracy: The negative log of the statistical significance of the approximation scores has been plotted.

<p>The for . Gray: ; black: .</p