A practical, bioinformatic workflow system for large data sets generated by next-generation sequencing

Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic workflow system, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This workflow system provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This system is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism

A practical, bioinformatic workflow system for large data sets generated by next-generation sequencing

Transcriptomics (at the level of single cells, tissues and/or whole organisms) underpins many fields of biomedical science, from understanding the basic cellular function in model organisms, to the elucidation of the biological events that govern the development and progression of human diseases, and the exploration of the mechanisms of survival, drug-resistance and virulence of pathogens. Next-generation sequencing (NGS) technologies are contributing to a massive expansion of transcriptomics in all fields and are reducing the cost, time and performance barriers presented by conventional approaches. However, bioinformatic tools for the analysis of the sequence data sets produced by these technologies can be daunting to researchers with limited or no expertise in bioinformatics. Here, we constructed a semi-automated, bioinformatic workflow system, and critically evaluated it for the analysis and annotation of large-scale sequence data sets generated by NGS. We demonstrated its utility for the exploration of differences in the transcriptomes among various stages and both sexes of an economically important parasitic worm (Oesophagostomum dentatum) as well as the prediction and prioritization of essential molecules (including GTPases, protein kinases and phosphatases) as novel drug target candidates. This workflow system provides a practical tool for the assembly, annotation and analysis of NGS data sets, also to researchers with a limited bioinformatic expertise. The custom-written Perl, Python and Unix shell computer scripts used can be readily modified or adapted to suit many different applications. This system is now utilized routinely for the analysis of data sets from pathogens of major socio-economic importance and can, in principle, be applied to transcriptomics data sets from any organism

Medication Underuse in Aging Outpatients with Cardiovascular Disease: Prevalence, Determinants, and Outcomes in a Prospective Cohort Study.

Cardiovascular disease is a leading cause of death in older people, and the impact of being exposed or not exposed to preventive cardiovascular medicines is accordingly high. Underutilization of beneficial drugs is common, but prevalence estimates differ across settings, knowledge on predictors is limited, and clinical consequences are rarely investigated.Using data from a prospective population-based cohort study, we assessed the prevalence, determinants, and outcomes of medication underuse based on cardiovascular criteria from Screening Tool To Alert to Right Treatment (START).Medication underuse was present in 69.1% of 1454 included participants (mean age 71.1 ± 6.1 years) and was significantly associated with frailty (odds ratio: 2.11 [95% confidence interval: 1.24-3.63]), body mass index (1.03 [1.01-1.07] per kg/m2), and inversely with the number of prescribed drugs (0.84 [0.79-0.88] per drug). Using this information for adjustment in a follow-up evaluation (mean follow-up time 2.24 years) on cardiovascular and competing outcomes, we found no association of medication underuse with cardiovascular events (fatal and non-fatal) (hazard ratio: 1.00 [0.65-1.56]), but observed a significant association of medication underuse with competing deaths from non-cardiovascular causes (2.52 [1.01-6.30]).Medication underuse was associated with frailty and adverse non-cardiovascular clinical outcomes. This may suggest that cardiovascular drugs were withheld because of serious co-morbidity or that concurrent illness can preclude benefit from cardiovascular prevention. In the latter case, adapted prescribing criteria should be developed and evaluated in those patients

Vaccination of calves with yeast- and bacterial-expressed paramyosin from the bovine lungworm Dictyocaulus viviparus

Previously, vaccination of cattle with Escherichia coli-expressed bovine lungworm paramyosin (EcPMY) adjuvanted with Quil A resulted in considerable reduction in worm burden and larvae shedding (Strube et al., 2015). To further evaluate the protective potential of PMY, cattle vaccination trials were performed using either E. coli- (EcPMY) or Pichia pastoris-expressed PMY (PpPMY) with different adjuvants (Matrix-Q(™) or Quil A). Combinations EcPMY+Matrix-Q(™) (trial 1), PpPMY+Matrix-Q(™) (trial 2) and PpPMY+Quil A (trial 3) were tested against challenge infections with 2000 Dictyocaulus viviparus larvae. Even though GM worm burden and larvae shedding was lower in almost all vaccinated groups, there were high variations between individuals hampering significant differences. However, in all vaccinated groups, lungworms were significantly shorter compared to those in controls. In vitro stimulation of peripheral blood mononuclear cells (PBMC) with recombinant (r)PMY revealed no significant proliferation following vaccinations or challenge infection. All vaccinated cattle showed a significant rise in specific antibodies, particularly IgG and its subclass IgG1, and detected the native lungworm PMY in immunoblots starting two weeks after the first vaccination. The use of a different rPMY-adjuvant combination or combined vaccination with additional recombinant antigens might be a promising future approach towards a new vaccine against lungworms in cattle

Presence of medication underuse was associated with frailty, BMI, and the number of drugs.

<p>Selected model variables and their association with medication underuse in a multivariate logistic regression model (*** < 0.001; ** < 0.01; and * < 0.05).</p

Medication underuse did not affect cardiovascular outcomes, but rather deaths due to non-cardiovascular causes.

<p>(A) Kaplan-Meier plot of relevant cardiovascular events for appropriate use and medication underuse (<i>P</i> value calculated by the log-rank test). (B) cumulative incidence functions of relevant (black) and competing events (gray) according to status of medication underuse (<i>P</i> value calculated by the Gray test) (solid line: appropriate use; dotted line: underuse).</p

Adapted START criteria for determination of cardiovascular medication underuse.

<p>^a a documented history of atherosclerotic coronary, cerebral, or peripheral vascular disease included previous myocardial infarction, stroke, coronary intervention (bypass surgery or balloon catheterization of the coronary arteries), pulmonary embolism, and deep vein thrombosis.</p><p>^b hypertension, hypercholesterolemia, and smoking history</p><p>Adapted START criteria for determination of cardiovascular medication underuse.</p