Genome-wide phylogenetic analysis of the pathogenic potential of Vibrio furnissii

This is the final version of the article. Available from Frontiers Media via the DOI in this record.We recently reported the genome sequence of a free-living strain of Vibrio furnissii (NCTC 11218) harvested from an estuarine environment. V. furnissii is a widespread, free-living proteobacterium and emerging pathogen that can cause acute gastroenteritis in humans and lethal zoonoses in aquatic invertebrates, including farmed crustaceans and molluscs. Here we present the analyses to assess the potential pathogenic impact of V. furnissii. We compared the complete genome of V. furnissii with 8 other emerging and pathogenic Vibrio species. We selected and analyzed more deeply 10 genomic regions based upon unique or common features, and used 3 of these regions to construct a phylogenetic tree. Thus, we positioned V. furnissii more accurately than before and revealed a closer relationship between V. furnissii and V. cholerae than previously thought. However, V. furnissii lacks several important features normally associated with virulence in the human pathogens V. cholera and V. vulnificus. A striking feature of the V. furnissii genome is the hugely increased Super Integron, compared to the other Vibrio. Analyses of predicted genomic islands resulted in the discovery of a protein sequence that is present only in Vibrio associated with diseases in aquatic animals. We also discovered evidence of high levels horizontal gene transfer in V. furnissii. V. furnissii seems therefore to have a dynamic and fluid genome that could quickly adapt to environmental perturbation or increase its pathogenicity. Taken together, these analyses confirm the potential of V. furnissii as an emerging marine and possible human pathogen, especially in the developing, tropical, coastal regions that are most at risk from climate change.This research was funded by a grant from Shell Research Ltd

Complete genome sequence of a free-living Vibrio furnissii sp. nov. strain (NCTC 11218)

This is the final version. Available from American Society for Microbiology via the DOI in this record. Shell Research Limited

Mining for diagnostic information in body surface potential maps: A comparison of feature selection techniques

BACKGROUND: In body surface potential mapping, increased spatial sampling is used to allow more accurate detection of a cardiac abnormality. Although diagnostically superior to more conventional electrocardiographic techniques, the perceived complexity of the Body Surface Potential Map (BSPM) acquisition process has prohibited its acceptance in clinical practice. For this reason there is an interest in striking a compromise between the minimum number of electrocardiographic recording sites required to sample the maximum electrocardiographic information. METHODS: In the current study, several techniques widely used in the domains of data mining and knowledge discovery have been employed to mine for diagnostic information in 192 lead BSPMs. In particular, the Single Variable Classifier (SVC) based filter and Sequential Forward Selection (SFS) based wrapper approaches to feature selection have been implemented and evaluated. Using a set of recordings from 116 subjects, the diagnostic ability of subsets of 3, 6, 9, 12, 24 and 32 electrocardiographic recording sites have been evaluated based on their ability to correctly asses the presence or absence of Myocardial Infarction (MI). RESULTS: It was observed that the wrapper approach, using sequential forward selection and a 5 nearest neighbour classifier, was capable of choosing a set of 24 recording sites that could correctly classify 82.8% of BSPMs. Although the filter method performed slightly less favourably, the performance was comparable with a classification accuracy of 79.3%. In addition, experiments were conducted to show how (a) features chosen using the wrapper approach were specific to the classifier used in the selection model, and (b) lead subsets chosen were not necessarily unique. CONCLUSION: It was concluded that both the filter and wrapper approaches adopted were suitable for guiding the choice of recording sites useful for determining the presence of MI. It should be noted however that in this study recording sites have been suggested on their ability to detect disease and such sites may not be optimal for estimating body surface potential distributions

Palaeogenomics of the Hydrocarbon Producing Microalga Botryococcus braunii.

Botryococcus braunii is a colonial microalga that appears early in the fossil record and is a sensitive proxy of environmental and hydroclimatic conditions. Palaeozoic Botryococcus fossils which contribute up to 90% of oil shales and approximately 1% of crude oil, co-localise with diagnostic geolipids from the degradation of source-signature hydrocarbons. However more recent Holocene sediments demonstrate no such association. Consequently, Botryococcus are identified in younger sediments by morphology alone, where potential misclassifications could lead to inaccurate paleoenvironmental reconstructions. Here we show that a combination of flow cytometry and ancient DNA (aDNA) sequencing can unambiguously identify Botryococcus microfossils in Holocene sediments with hitherto unparalleled accuracy and rapidity. The application of aDNA sequencing to microfossils offers a far-reaching opportunity for understanding environmental change in the recent geological record. When allied with other high-resolution palaeoenvironmental information such as aDNA sequencing of humans and megafauna, aDNA from microfossils may allow a deeper and more precise understanding of past environments, ecologies and migrations

Decoding the regulatory network of early blood development from single-cell gene expression measurements.

Reconstruction of the molecular pathways controlling organ development has been hampered by a lack of methods to resolve embryonic progenitor cells. Here we describe a strategy to address this problem that combines gene expression profiling of large numbers of single cells with data analysis based on diffusion maps for dimensionality reduction and network synthesis from state transition graphs. Applying the approach to hematopoietic development in the mouse embryo, we map the progression of mesoderm toward blood using single-cell gene expression analysis of 3,934 cells with blood-forming potential captured at four time points between E7.0 and E8.5. Transitions between individual cellular states are then used as input to develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model of blood development. Several model predictions concerning the roles of Sox and Hox factors are validated experimentally. Our results demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that underpin organogenesis.We thank J. Downing (St. Jude Children's Research Hospital, Memphis, TN, USA) for the Runx1-ires-GFP mouse. Research in the authors' laboratory is supported by the Medical Research Council, Biotechnology and Biological Sciences Research Council, Leukaemia and Lymphoma Research, the Leukemia and Lymphoma Society, Microsoft Research and core support grants by the Wellcome Trust to the Cambridge Institute for Medical Research and Wellcome Trust - MRC Cambridge Stem Cell Institute. V.M. is supported by a Medical Research Council Studentship and Centenary Award and S.W. by a Microsoft Research PhD Scholarship.This is the accepted manuscript for a paper published in Nature Biotechnology 33, 269–276 (2015) doi:10.1038/nbt.315

Conductive Cellulose Composites with Low Percolation Threshold for 3D Printed Electronics

We are reporting a 3D printable composite paste having strong thixotropic rheology. The composite has been designed and investigated with highly conductive silver nanowires. The optimized electrical percolation threshold from both simulation and experiment is shown from 0.7 vol. % of silver nanowires which is significantly lower than other composites using conductive nano-materials. Reliable conductivity of 1.19 × 102 S/cm has been achieved from the demonstrated 3D printable composite with 1.9 vol. % loading of silver nanowires. Utilizing the high conductivity of the printable composites, 3D printing of designed battery electrode pastes is demonstrated. Rheology study shows superior printability of the electrode pastes aided by the cellulose\u27s strong thixotropic rheology. The designed anode, electrolyte, and cathode pastes are sequentially printed to form a three-layered lithium battery for the demonstration of a charging profile. This study opens opportunities of 3D printable conductive materials to create printed electronics with the next generation additive manufacturing process

Phenotypic Complexity, Measurement Bias, and Poor Phenotypic Resolution Contribute to the Missing Heritability Problem in Genetic Association Studies

Background The variance explained by genetic variants as identified in (genome-wide) genetic association studies is typically small compared to family-based heritability estimates. Explanations of this ‘missing heritability’ have been mainly genetic, such as genetic heterogeneity and complex (epi-)genetic mechanisms. Methodology We used comprehensive simulation studies to show that three phenotypic measurement issues also provide viable explanations of the missing heritability: phenotypic complexity, measurement bias, and phenotypic resolution. We identify the circumstances in which the use of phenotypic sum-scores and the presence of measurement bias lower the power to detect genetic variants. In addition, we show how the differential resolution of psychometric instruments (i.e., whether the instrument includes items that resolve individual differences in the normal range or in the clinical range of a phenotype) affects the power to detect genetic variants. Conclusion We conclude that careful phenotypic data modelling can improve the genetic signal, and thus the statistical power to identify genetic variants by 20-99

Plasma Apolipoprotein Levels Are Associated with Cognitive Status and Decline in a Community Cohort of Older Individuals

<div><h3>Objectives</h3><p>Apolipoproteins have recently been implicated in the etiology of Alzheimer’s disease (AD). In particular, Apolipoprotein J (ApoJ or clusterin) has been proposed as a biomarker of the disease at the pre-dementia stage. We examined a group of apolipoproteins, including ApoA1, ApoA2, ApoB, ApoC3, ApoE, ApoH and ApoJ, in the plasma of a longitudinal community based cohort.</p> <h3>Methods</h3><p>664 subjects (257 with Mild Cognitive Impairment [MCI] and 407 with normal cognition), mean age 78 years, from the Sydney Memory and Aging Study (MAS) were followed up over two years. Plasma apolipoprotein levels at baseline (Wave 1) were measured using a multiplex bead fluorescence immunoassay technique.</p> <h3>Results</h3><p>At Wave 1, MCI subjects had lower levels of ApoA1, ApoA2 and ApoH, and higher levels of ApoE and ApoJ, and a higher ApoB/ApoA1 ratio. Carriers of the apolipoprotein E ε4 allele had significantly lower levels of plasma ApoE, ApoC3 and ApoH and a significantly higher level of ApoB. Global cognitive scores were correlated positively with ApoH and negatively with ApoJ levels. ApoJ and ApoE levels were correlated negatively with grey matter volume and positively with cerebrospinal fluid (CSF) volume on MRI. Lower ApoA1, ApoA2 and ApoH levels, and higher ApoB/ApoA1 ratio, increased the risk of cognitive decline over two years in cognitively normal individuals. ApoA1 was the most significant predictor of decline. These associations remained after statistically controlling for lipid profile. Higher ApoJ levels predicted white matter atrophy over two years.</p> <h3>Conclusions</h3><p>Elderly individuals with MCI have abnormal apolipoprotein levels, which are related to cognitive function and volumetric MRI measures cross-sectionally and are predictive of cognitive impairment in cognitively normal subjects. ApoA1, ApoH and ApoJ are potential plasma biomarkers of cognitive decline in non-demented elderly individuals.</p> </div