The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Search algorithms as a framework for the optimization of drug combinations

Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms, originally developed for digital communication, modified to optimize combinations of therapeutic interventions. In biological experiments measuring the restoration of the decline with age in heart function and exercise capacity in Drosophila melanogaster, we found that search algorithms correctly identified optimal combinations of four drugs with only one third of the tests performed in a fully factorial search. In experiments identifying combinations of three doses of up to six drugs for selective killing of human cancer cells, search algorithms resulted in a highly significant enrichment of selective combinations compared with random searches. In simulations using a network model of cell death, we found that the search algorithms identified the optimal combinations of 6-9 interventions in 80-90% of tests, compared with 15-30% for an equivalent random search. These findings suggest that modified search algorithms from information theory have the potential to enhance the discovery of novel therapeutic drug combinations. This report also helps to frame a biomedical problem that will benefit from an interdisciplinary effort and suggests a general strategy for its solution.Comment: 36 pages, 10 figures, revised versio

Comparative genomics of isolates of a pseudomonas aeruginosa epidemic strain associated with chronic lung infections of cystic fibrosis patients

Pseudomonas aeruginosa is the main cause of fatal chronic lung infections among individuals suffering from cystic fibrosis (CF). During the past 15 years, particularly aggressive strains transmitted among CF patients have been identified, initially in Europe and more recently in Canada. The aim of this study was to generate high-quality genome sequences for 7 isolates of the Liverpool epidemic strain (LES) from the United Kingdom and Canada representing different virulence characteristics in order to: (1) associate comparative genomics results with virulence factor variability and (2) identify genomic and/or phenotypic divergence between the two geographical locations. We performed phenotypic characterization of pyoverdine, pyocyanin, motility, biofilm formation, and proteolytic activity. We also assessed the degree of virulence using the Dictyostelium discoideum amoeba model. Comparative genomics analysis revealed at least one large deletion (40-50 kb) in 6 out of the 7 isolates compared to the reference genome of LESB58. These deletions correspond to prophages, which are known to increase the competitiveness of LESB58 in chronic lung infection. We also identified 308 non-synonymous polymorphisms, of which 28 were associated with virulence determinants and 52 with regulatory proteins. At the phenotypic level, isolates showed extensive variability in production of pyocyanin, pyoverdine, proteases and biofilm as well as in swimming motility, while being predominantly avirulent in the amoeba model. Isolates from the two continents were phylogenetically and phenotypically undistinguishable. Most regulatory mutations were isolate-specific and 29% of them were predicted to have high functional impact. Therefore, polymorphism in regulatory genes is likely to be an important basis for phenotypic diversity among LES isolates, which in turn might contribute to this strain's adaptability to varying conditions in the CF lung

The impact of a supplementary medication review and counselling service within the oncology outpatient setting

The impact on the care of breast cancer patients, of a pharmacy technician-led medication review and counselling clinic, provided in an outpatient setting, was investigated using a controlled randomised study. Compared to the controls, clinic patients showed a significantly improved level of understanding of their chemotherapy support medication (95% CI for difference in mean knowledge rating scores=2.165–2.826, P<0.001) and a significant reduction in the median number of support items required (two compared to five in the control, P<0.001). This resulted in a significant reduction in mean medication expenditure per patient (£26.70 vs £10.20, 95% CI for the mean difference in cost £6.72–£26.26, P<0.001). The clinic was also associated with significant reductions in chemotherapy delays (P<0.001) and dose reductions due to side effects (P=0.003). Other benefits from the clinic were a reduction in pharmacy dispensing time and a highly significant reduction in pharmacy time spent resolving post-clinic prescription queries (P<0.001). Taking into account the initial technician training cost, the scheme represented an annual saving to the Trust of over £15 000. The clinic serves as a model for those wishing to improve outpatient services to breast cancer patients

Is dietary pattern of schizophrenia patients different from healthy subjects?

<p>Abstract</p> <p>Background</p> <p>There are limited findings about dietary patterns and food preferences among patients suffering from schizophrenia. The main objective of this study was therefore to compare the nutritional pattern of schizophrenia patients with that of matched healthy subjects.</p> <p>Methods</p> <p>The dietary pattern of 30 hospitalized 16–67 years old schizophrenic patients (11 female) was compared with that of 30 healthy age and sex matched individuals as control group. Subjects' anthropometric measurements including weight, height and body mass index (BMI), semi-quantitative food frequency (FFQ), medical and food history questionnaires were also collected and FFQs were then scored using Food Guide Pyramid to obtain the dietary scores. Percent body fat (%BF) was measured using bioelectrical impedance analysis (BIA) method.</p> <p>Results</p> <p>Female patients had more %BF and lower dietary pattern scores than that of their controls (32 ± 3.6 vs 27.7 ± 4.6 percent and 43.2 ± 11.9 vs 54.5 ± 10.7 points; respectively, p < 0.05 for both). They also consumed less milk and dairy products, fresh vegetables, fruits, chicken, and nuts compared with the female controls (p < 0.03). However, these patients used to eat more full-fat cream and carbonated drinks (p < 0.05). Male patients had lower BMI (22 ± 4.7 vs 25.6 ± 4.4; p < 0.05) than their counterpart controls but there was no significant difference between their %BFs. Moreover, they used to have more full-fat cream, hydrogenated fats, less red meat and nuts compared with the male controls (p < 0.05).</p> <p>Conclusion</p> <p>Schizophrenia patients have poor nutritional patterns. In particular, female patients have more percent body fat and lower dietary pattern scores compared with their healthy controls. All patients used to consume more fats and sweet drinks frequently. The findings of this study suggest that schizophrenia patients need specific medical nutrition therapies through limiting dietary fats and sugars intakes and weight control. Whether obesity is the consequence of disease, dietary preference or medications used remains to be cleared.</p

Deficiency in origin licensing proteins impairs cilia formation: implications for the aetiology of meier-gorlin syndrome

Mutations in ORC1, ORC4, ORC6, CDT1, and CDC6, which encode proteins required for DNA replication origin licensing, cause Meier-Gorlin syndrome (MGS), a disorder conferring microcephaly, primordial dwarfism, underdeveloped ears, and skeletal abnormalities. Mutations in ATR, which also functions during replication, can cause Seckel syndrome, a clinically related disorder. These findings suggest that impaired DNA replication could underlie the developmental defects characteristic of these disorders. Here, we show that although origin licensing capacity is impaired in all patient cells with mutations in origin licensing component proteins, this does not correlate with the rate of progression through S phase. Thus, the replicative capacity in MGS patient cells does not correlate with clinical manifestation. However, ORC1-deficient cells from MGS patients and siRNA-mediated depletion of origin licensing proteins also have impaired centrosome and centriole copy number. As a novel and unexpected finding, we show that they also display a striking defect in the rate of formation of primary cilia. We demonstrate that this impacts sonic hedgehog signalling in ORC1-deficient primary fibroblasts. Additionally, reduced growth factor-dependent signaling via primary cilia affects the kinetics of cell cycle progression following cell cycle exit and re-entry, highlighting an unexpected mechanism whereby origin licensing components can influence cell cycle progression. Finally, using a cell-based model, we show that defects in cilia function impair chondroinduction. Our findings raise the possibility that a reduced efficiency in forming cilia could contribute to the clinical features of MGS, particularly the bone development abnormalities, and could provide a new dimension for considering developmental impacts of licensing deficiency

The Prevalence and Psychopathological Correlates of Sibling Bullying in Children with and without Autism Spectrum Disorder

Using data from a prospective population based study, the prevalence and psychopathological correlates of sibling bullying in children with and without autism spectrum disorder (ASD) were estimated. There were 475 children with ASD and 13,702 children without ASD aged 11 years. Children with ASD were more likely to be bullied by their siblings compared to those without ASD. They were also more likely than those without ASD to both bully and be bullied by their siblings, which was associated with lower prosocial skills as well as more internalizing and externalizing problems compared to those not involved in any sibling bullying. Interventions to improve social and emotional outcomes in children with ASD should focus on both the affected and the unaffected sibling

The endothelial-specific regulatory mutation, Mvwf1, is a common mouse founder allele

Mvwf1 is a cis-regulatory mutation previously identified in the RIIIS/J mouse strain that causes a unique tissue-specific switch in the expression of an N-acetylgalactosaminyltransferase, B4GALNT2, from intestinal epithelium to vascular endothelium. Vascular B4galnt2 expression results in aberrant glycosylation of von Willebrand Factor (VWF) and accelerated VWF clearance from plasma. We now report that 13 inbred mouse strains share the Mvwf1 tissue-specific switch and low VWF phenotype, including five wild-derived strains. Genomic sequencing identified a highly conserved 97-kb Mvwf1 haplotype block shared by these strains that encompasses a 30-kb region of high nucleotide sequence divergence from C57BL6/J flanking B4galnt2 exon 1. The analysis of a series of bacterial artificial chromosome (BAC) transgenes containing B4galnt2 derived from the RIIIS/J or C57BL6/J inbred mouse strains demonstrates that the corresponding sequences are sufficient to confer the vessel (RIIIS/J) or intestine (C57BL6/J)-specific expression patterns. Taken together, our data suggest that the region responsible for the Mvwf1 regulatory switch lies within an approximately 30-kb genomic interval upstream of the B4galnt2 gene. The observation that Mvwf1 is present in multiple wild-derived strains suggests that this locus may be retained in wild mouse populations due to positive selection. Similar selective pressures could contribute to the high prevalence of von Willebrand disease in humans

Surface and Temporal Biosignatures

Recent discoveries of potentially habitable exoplanets have ignited the prospect of spectroscopic investigations of exoplanet surfaces and atmospheres for signs of life. This chapter provides an overview of potential surface and temporal exoplanet biosignatures, reviewing Earth analogues and proposed applications based on observations and models. The vegetation red-edge (VRE) remains the most well-studied surface biosignature. Extensions of the VRE, spectral "edges" produced in part by photosynthetic or nonphotosynthetic pigments, may likewise present potential evidence of life. Polarization signatures have the capacity to discriminate between biotic and abiotic "edge" features in the face of false positives from band-gap generating material. Temporal biosignatures -- modulations in measurable quantities such as gas abundances (e.g., CO2), surface features, or emission of light (e.g., fluorescence, bioluminescence) that can be directly linked to the actions of a biosphere -- are in general less well studied than surface or gaseous biosignatures. However, remote observations of Earth's biosphere nonetheless provide proofs of concept for these techniques and are reviewed here. Surface and temporal biosignatures provide complementary information to gaseous biosignatures, and while likely more challenging to observe, would contribute information inaccessible from study of the time-averaged atmospheric composition alone.Comment: 26 pages, 9 figures, review to appear in Handbook of Exoplanets. Fixed figure conversion error