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ABSTRACTChronic Pseudomonas aeruginosa lung infections are a feature of cystic fibrosis (CF) that many patients experience even with the advent of highly effective modulator therapies. Identifying factors that impact P. aeruginosa in the CF lung could yield novel strategies to eradicate infection or otherwise improve outcomes. To complement published P. aeruginosa studies using laboratory models or RNA isolated from sputum, we analyzed transcripts of strain PAO1 after incubation in sputum from different CF donors prior to RNA extraction. We compared PAO1 gene expression in this “spike-in” sputum model to that for P. aeruginosa grown in synthetic cystic fibrosis sputum medium to determine key genes, which are among the most differentially expressed or most highly expressed. Using the key genes, gene sets with correlated expression were determined using the gene expression analysis tool eADAGE. Gene sets were used to analyze the activity of specific pathways in P. aeruginosa grown in sputum from different individuals. Gene sets that we found to be more active in sputum showed similar activation in published data that included P. aeruginosa RNA isolated from sputum relative to corresponding in vitro reference cultures. In the ex vivo samples, P. aeruginosa had increased levels of genes related to zinc and iron acquisition which were suppressed by metal amendment of sputum. We also found a significant correlation between expression of the H1-type VI secretion system and CFTR corrector use by the sputum donor. An ex vivo sputum model or synthetic sputum medium formulation that imposes metal restriction may enhance future CF-related studies.IMPORTANCEIdentifying the gene expression programs used by Pseudomonas aeruginosa to colonize the lungs of people with cystic fibrosis (CF) will illuminate new therapeutic strategies. To capture these transcriptional programs, we cultured the common P. aeruginosa laboratory strain PAO1 in expectorated sputum from CF patient donors. Through bioinformatic analysis, we defined sets of genes that are more transcriptionally active in real CF sputum compared to a synthetic cystic fibrosis sputum medium. Many of the most differentially active gene sets contained genes related to metal acquisition, suggesting that these gene sets play an active role in scavenging for metals in the CF lung environment which may be inadequately represented in some models. Future studies of P. aeruginosa transcript abundance in CF may benefit from the use of an expectorated sputum model or media supplemented with factors that induce metal restriction.

Prefiguration is a term borrowed from political science, describing the experimentation with alternative ways of living, doing and being together in the present as a form of activism. In this article I will argue that cinema can be a powerful tool that can be used to support prefigurative objectives. Arguably, the point of origin of this methodology is Man with a Movie Camera (??????? ? K???????????? 1929) by Dziga Vertov. Structurally this film can be described as 'database driven' and as prescient toward the digital age in which databases and hypertexts are common organising principles affecting daily life experiences. But more importantly, the film presages a different, more harmonious society in a style that simultaneously uses documentary, experimental and poetic elements. The purpose of this enquiry is to establish whether subsequent crowd-sourced and community driven documentaries can be seen as equally successful examples of prefiguration.

Genome-wide transcriptome profiling identifies genes that are prone to differential expression (DE) across contexts, as well as genes with changes specific to the experimental manipulation. Distinguishing genes that are specifically changed in a context of interest from common differentially expressed genes (DEGs) allows more efficient prediction of which genes are specific to a given biological process under scrutiny. Currently, common DEGs or pathways can only be identified through the laborious manual curation of experiments, an inordinately time-consuming endeavor. Here we pioneer an approach, Specific cOntext Pattern Highlighting In Expression data (SOPHIE), for distinguishing between common and specific transcriptional patterns using a generative neural network to create a background set of experiments from which a null distribution of gene and pathway changes can be generated. We apply SOPHIE to diverse datasets including those from human, human cancer, and bacterial pathogen Pseudomonas aeruginosa. SOPHIE identifies common DEGs in concordance with previously described, manually and systematically determined common DEGs. Further molecular validation indicates that SOPHIE detects highly specific but low-magnitude biologically relevant transcriptional changes. SOPHIE’s measure of specificity can complement log2 fold change values generated from traditional DE analyses. For example, by filtering the set of DEGs, one can identify genes that are specifically relevant to the experimental condition of interest. Consequently, these results can inform future research directions. All scripts used in these analyses are available at https://github.com/greenelab/generic-expression-patterns. Users can access https://github.com/greenelab/sophie to run SOPHIE on their own data.

Mendelian randomization can be used to mimic the effects of protein-targeting drugs in a population of individuals. Here, the authors have identified potential causal proteins for stroke in a two-sample Mendelian randomization framework, providing potential stroke therapeutic targets.

Abstract Researchers studying cystic fibrosis (CF) pathogens have produced numerous RNA-seq datasets which are available in the gene expression omnibus (GEO). Although these studies are publicly available, substantial computational expertise and manual effort are required to compare similar studies, visualize gene expression patterns within studies, and use published data to generate new experimental hypotheses. Furthermore, it is difficult to filter available studies by domain-relevant attributes such as strain, treatment, or media, or for a researcher to assess how a specific gene responds to various experimental conditions across studies. To reduce these barriers to data re-analysis, we have developed an R Shiny application called CF-Seq, which works with a compendium of 128 studies and 1,322 individual samples from 13 clinically relevant CF pathogens. The application allows users to filter studies by experimental factors and to view complex differential gene expression analyses at the click of a button. Here we present a series of use cases that demonstrate the application is a useful and efficient tool for new hypothesis generation. (CF-Seq: http://scangeo.dartmouth.edu/CFSeq/ )

ABSTRACT Thousands of Pseudomonas aeruginosa RNA sequencing (RNA-seq) gene expression profiles are publicly available via the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). In this work, the transcriptional profiles from hundreds of studies performed by over 75 research groups were reanalyzed in aggregate to create a powerful tool for hypothesis generation and testing. Raw sequence data were uniformly processed using the Salmon pseudoaligner, and this read mapping method was validated by comparison to a direct alignment method. We developed filtering criteria to exclude samples with aberrant levels of housekeeping gene expression or an unexpected number of genes with no reported values and normalized the filtered compendia using the ratio-of-medians method. The filtering and normalization steps greatly improved gene expression correlations for genes within the same operon or regulon across the 2,333 samples. Since the RNA-seq data were generated using diverse strains, we report the effects of mapping samples to noncognate reference genomes by separately analyzing all samples mapped to cDNA reference genomes for strains PAO1 and PA14, two divergent strains that were used to generate most of the samples. Finally, we developed an algorithm to incorporate new data as they are deposited into the SRA. Our processing and quality control methods provide a scalable framework for taking advantage of the troves of biological information hibernating in the depths of microbial gene expression data and yield useful tools for P. aeruginosa RNA-seq data to be leveraged for diverse research goals. IMPORTANCE Pseudomonas aeruginosa is a causative agent of a wide range of infections, including chronic infections associated with cystic fibrosis. These P. aeruginosa infections are difficult to treat and often have negative outcomes. To aid in the study of this problematic pathogen, we mapped, filtered for quality, and normalized thousands of P. aeruginosa RNA-seq gene expression profiles that were publicly available via the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA). The resulting compendia facilitate analyses across experiments, strains, and conditions. Ultimately, the workflow that we present could be applied to analyses of other microbial species.

ABSTRACT Pseudomonas aeruginosa is an opportunistic pathogen that causes difficult-to-treat infections. Two well-studied divergent P. aeruginosa strain types, PAO1 and PA14, have significant genomic heterogeneity, including diverse accessory genes present in only some strains. Genome content comparisons find core genes that are conserved across both PAO1 and PA14 strains and accessory genes that are present in only a subset of PAO1 and PA14 strains. Here, we use recently assembled transcriptome compendia of publicly available P. aeruginosa RNA sequencing (RNA-seq) samples to create two smaller compendia consisting of only strain PAO1 or strain PA14 samples with each aligned to their cognate reference genome. We confirmed strain annotations and identified other samples for inclusion by assessing each sample’s median expression of PAO1-only or PA14-only accessory genes. We then compared the patterns of core gene expression in each strain. To do so, we developed a method by which we analyzed genes in terms of which genes showed similar expression patterns across strain types. We found that some core genes had consistent correlated expression patterns across both compendia, while others were less stable in an interstrain comparison. For each accessory gene, we also determined core genes with correlated expression patterns. We found that stable core genes had fewer coexpressed neighbors that were accessory genes. Overall, this approach for analyzing expression patterns across strain types can be extended to other groups of genes, like phage genes, or applied for analyzing patterns beyond groups of strains, such as samples with different traits, to reveal a deeper understanding of regulation. IMPORTANCE Pseudomonas aeruginosa is a ubiquitous pathogen. There is much diversity among P. aeruginosa strains, including two divergent but well-studied strains, PAO1 and PA14. Understanding how these different strain-level traits manifest is important for identifying targets that regulate different traits of interest. With the availability of thousands of PAO1 and PA14 samples, we created two strain-specific RNA-seq compendia where each one contains hundreds of samples from PAO1 or PA14 strains and used them to compare the expression patterns of core genes that are conserved in both strain types and to determine which core genes have expression patterns that are similar to those of accessory genes that are unique to one strain or the other using an approach that we developed. We found a subset of core genes with different transcriptional patterns across PAO1 and PA14 strains and identified those core genes with expression patterns similar to those of strain-specific accessory genes.

Veprik et al. show that Acetyl-CoA-carboxylase 1 (ACC1), an enzyme that couples glucose metabolism to lipogenesis, is involved in glucagon secretion and regulates S-acylation of critical glucose-sensing proteins. Loss of ACC1 in pancreatic alpha-cells negatively affects both size and number, as well as glucagon content, while in gut enteroendocrine cells leads to reduced release of glucagon-like peptide 1.

A gene expression compendium is a heterogeneous collection of gene expression experiments assembled from data collected for diverse purposes. The widely varied experimental conditions and genetic backgrounds across samples creates a tremendous opportunity for gaining a systems level understanding of the transcriptional responses that influence phenotypes. Variety in experimental design is particularly important for studying microbes, where the transcriptional responses integrate many signals and demonstrate plasticity across strains including response to what nutrients are available and what microbes are present. Advances in high-throughput measurement technology have made it feasible to construct compendia for many microbes. In this review we discuss how these compendia are constructed and analyzed to reveal transcriptional patterns.

BACKGROUND:The prevalence, treatment and outcomes of balloon undilatable chronic total occlusions (CTOs) have received limited study. METHODS:We examined the prevalence, clinical and angiographic characteristics, and procedural outcomes of percutaneous coronary interventions (PCIs) for balloon undilatable CTOs in a contemporary multicenter US registry. RESULTS:Between 2012 and 2017 data on balloon undilatable lesions were available for 425 consecutive CTO PCIs in 415 patients in whom guidewire crossing was successful: 52 of 425 CTOs were balloon undilatable (12%). Mean patient age was 65 ± 10 years and most patients were men (84%). Patients with balloon undilatable CTOs were more likely to be diabetic (67 vs. 41%, P

Mitochondrial DNA (mtDNA) variants influence the risk of late-onset human diseases, but the reasons for this are poorly understood. Undertaking a hypothesis-free analysis of 5,689 blood-derived biomarkers with mtDNA variants in 16,220 healthy donors, here we show that variants defining mtDNA haplogroups Uk and H4 modulate the level of circulating N-formylmethionine (fMet), which initiates mitochondrial protein translation. In human cytoplasmic hybrid (cybrid) lines, fMet modulated both mitochondrial and cytosolic proteins on multiple levels, through transcription, post-translational modification and proteolysis by an N-degron pathway, abolishing known differences between mtDNA haplogroups. In a further 11,966 individuals, fMet levels contributed to all-cause mortality and the disease risk of several common cardiovascular disorders. Together, these findings indicate that fMet plays a key role in common age-related disease through pleiotropic effects on cell proteostasis. The association between certain mitochondrial DNA variants and increased risk of late-onset diseases in humans could be explained by a direct role of mitochondrial DNA in the regulation of cellular proteostasis., Author(s): Na Cai [sup.1] [sup.2] [sup.3] , Aurora Gomez-Duran [sup.4] [sup.5] [sup.6] , Ekaterina Yonova-Doing [sup.7] [sup.8] , Kousik Kundu [sup.1] , Annette I. Burgess [sup.9] , Zoe J. Golder [...]

AimTo examine the impact of diabetes mellitus on procedural outcomes of patients who underwent percutaneous coronary intervention for chronic total occlusion.MethodsWe assessed the impact of diabetes mellitus on the outcomes of percutaneous coronary intervention for chronic total occlusion among 1308 people who underwent such procedures at 11 US centres between 2012 and 2015.ResultsThe participants' mean ± sd age was 66 ± 10 years, 84% of the participants were men and 44.6% had diabetes. As compared with participants without diabetes, participants with diabetes were more likely to have undergone coronary artery bypass graft surgery (38 vs 31%; P = 0.006), and to have had previous heart failure (35 vs 22%; P = 0.0001) and peripheral arterial disease (19 vs 13%; P = 0.002). They also had a higher BMI (31 ± 6 kg/m2 vs 29 ± 6 kg/m2 ; P = 0.001), similar Japanese chronic total occlusion scores (2.6 ± 1.2 vs 2.5 ± 1.2; P = 0.82) and similar final successful crossing technique: antegrade wire escalation (46 vs 47%; P = 0.66), retrograde (30 vs 28%; P = 0.66) and antegrade dissection re-entry (24 vs 25%; P = 0.66). Technical (91 vs 90%; P = 0.80) and procedural (89 vs 89%; P = 0.93) success was similar in the two groups, as was the incidence of major adverse cardiac events (2.2 vs 2.5%; P = 0.61).ConclusionsIn a contemporary cohort of people undergoing percutaneous coronary intervention for chronic total occlusion, nearly one in two (45%) had diabetes mellitus. Procedural success and complication rates were similar in people with and without diabetes.

High success rates are achievable for chronic total occlusion (CTO) percutaneous coronary intervention (PCI) using the hybrid approach, but periprocedural complications remain of concern. Although scores estimating success and efficiency in CTO PCI have been developed, there is currently no available score for estimation of the risk for periprocedural complications. We sought to develop a scoring tool for prediction of periprocedural complications during CTO PCI. We analyzed data from 1569 CTO PCIs in the Prospective Global Registry for the Study of Chronic Total Occlusion Intervention (PROGRESS CTO) using a derivation and validation sampling ratio of 2:1. Variables independently associated with periprocedural complications in multivariable analysis in the derivation set were assigned points based on their respective odds ratios. Forty-four (2.8%) patients experienced complications. Three factors were independent predictors of complications and were included in the score: patient age >65 years, +3 points (odds ratio, OR=4.85, CI 1.82-16.77); lesion length ≥23 mm, +2 points (OR=3.22, CI 1.08-13.89); and use of the retrograde approach +1 point (OR=2.41, CI 1.04-6.05). The resulting score showed good calibration and discriminatory capacity in the derivation (Hosmer-Lemeshow χ2 6.271, P=0.281, receiver-operating characteristic [ROC] area=0.758) and validation (Hosmer-Lemeshow χ2 4.551, P=0.473, ROC area=0.793) sets. Score values of 0 to 2, 3 to 4, and ≥5 were defined as low, intermediate, and high risk of complications (derivation cohort 0.4%, 1.8%, 6.5%, P

Here, the authors report a multi-ethnic genome wide association meta-analysis of 12 studies from the International Cataract Genetics Consortium. They find six new loci associated with age-related nuclear cataract, in addition to replicating the association at CRYAA, and suggest a strong genetic link between age-related nuclear and congenital cataracts.

Intravascular imaging can facilitate chronic total occlusion (CTO) percutaneous coronary intervention. We examined the frequency of use and outcomes of intravascular imaging among 619 CTO percutaneous coronary interventions performed between 2012 and 2015 at 7 US centers. Mean age was 65.4±10 years and 85% of the patients were men. Intravascular imaging was used in 38%: intravascular ultrasound in 36%, optical coherence tomography in 3%, and both in 1.45%. Intravascular imaging was used for stent sizing (26.3%), stent optimization (38.0%), and CTO crossing (35.7%, antegrade in 27.9%, and retrograde in 7.8%). Intravascular imaging to facilitate crossing was used more frequently in lesions with proximal cap ambiguity (49% versus 26%, P

BackgroundAdministration of a large amount of contrast volume during chronic total occlusion (CTO) percutaneous coronary intervention (PCI) may lead to contrast-induced nephropathy.MethodsWe examined the association of clinical, angiographic and procedural variables with contrast volume administered during 1330 CTO-PCI procedures performed at 12 experienced United States centers.ResultsTechnical and procedural success was 90% and 88%, respectively, and mean contrast volume was 289 ± 138 mL. Approximately 33% of patients received >320 mL of contrast (high contrast utilization group). On univariable analysis, male gender (P=.01), smoking (P=.01), prior coronary artery bypass graft surgery (P=.04), moderate or severe calcification (P=.01), moderate or severe tortuosity (P=.04), proximal cap ambiguity (P=.01), distal cap at a bifurcation (P

Stroke risk is influenced by genetic and lifestyle factors and previously a genomic risk score (GRS) for stroke was proposed, albeit with limited predictive power. Here, Abraham et al. develop a metaGRS that is composed of several stroke-related GRSs and demonstrate improved predictive power compared with individual GRS or classic risk factors.