Determining a new alignment scoring matrix for disordered proteins

Intrinsically disordered proteins (IDPs) are polypeptide sequences that do not form a rigid three dimensional structure when isolated in the cytosol of the cell. These sequences are very common in most genomes, and usually are involved in many protein-protein interactions. IDPs also play a key role in many diseases, including cancer and Huntington\u27s disease. However, IDPs are difficult to study because of their amorphous shape, high mutation rate, and unique amino acid composition. These obstacles make homology studies especially difficult. This study focused on generating a new substitution matrix designed to aid in homology studies of IDPs. The matrix was generated using a genetic algorithm (GA). GAs are alternative hill-climbing methods for finding solutions in complex problem spaces. To achieve this goal, a GA models the evolutionary process found in nature by breeding solutions to the problem until one of sufficient quality is produced. The GA implemented in this study produced a substitution matrix for use in differentiation between homologous and non-homologous proteins containing disordered regions. The matrix showed some correlation to the patterns of evolution found in disordered proteins and their general sequence makeup. However, when compared to a commonly used substitution matrix, BLOSUM, the GA\u27s solution did not show significant improvement. But the results here do show a general proof of concept, and that given modifications to the GA, more time, or more resources, a substitution matrix capable of out-performing BLOSUM is potentially possible

Mycobacterium tuberculosis and Clostridium difficille interactomes: demonstration of rapid development of computational system for bacterial interactome prediction

Background\ud Protein-protein interaction (PPI) networks (interactomes) of most organisms, except for some model organisms, are largely unknown. Experimental methods including high-throughput techniques are highly resource intensive. Therefore, computational discovery of PPIs can accelerate biological discovery by presenting "most-promising" pairs of proteins that are likely to interact. For many bacteria, genome sequence, and thereby genomic context of proteomes, is readily available; additionally, for some of these proteomes, localization and functional annotations are also available, but interactomes are not available. We present here a method for rapid development of computational system to predict interactome of bacterial proteomes. While other studies have presented methods to transfer interologs across species, here, we propose transfer of computational models to benefit from cross-species annotations, thereby predicting many more novel interactions even in the absence of interologs. Mycobacterium tuberculosis (Mtb) and Clostridium difficile (CD) have been used to demonstrate the work.\ud \ud Results\ud We developed a random forest classifier over features derived from Gene Ontology annotations and genetic context scores provided by STRING database for predicting Mtb and CD interactions independently. The Mtb classifier gave a precision of 94% and a recall of 23% on a held out test set. The Mtb model was then run on all the 8 million protein pairs of the Mtb proteome, resulting in 708 new interactions (at 94% expected precision) or 1,595 new interactions at 80% expected precision. The CD classifier gave a precision of 90% and a recall of 16% on a held out test set. The CD model was run on all the 8 million protein pairs of the CD proteome, resulting in 143 new interactions (at 90% expected precision) or 580 new interactions (at 80% expected precision). We also compared the overlap of predictions of our method with STRING database interactions for CD and Mtb and also with interactions identified recently by a bacterial 2-hybrid system for Mtb. To demonstrate the utility of transfer of computational models, we made use of the developed Mtb model and used it to predict CD protein-pairs. The cross species model thus developed yielded a precision of 88% at a recall of 8%. To demonstrate transfer of features from other organisms in the absence of feature-based and interaction-based information, we transferred missing feature values from Mtb orthologs into the CD data. In transferring this data from orthologs (not interologs), we showed that a large number of interactions can be predicted.\ud \ud Conclusions\ud Rapid discovery of (partial) bacterial interactome can be made by using existing set of GO and STRING features associated with the organisms. We can make use of cross-species interactome development, when there are not even sufficient known interactions to develop a computational prediction system. Computational model of well-studied organism(s) can be employed to make the initial interactome prediction for the target organism. We have also demonstrated successfully, that annotations can be transferred from orthologs in well-studied organisms enabling accurate predictions for organisms with no annotations. These approaches can serve as building blocks to address the challenges associated with feature coverage, missing interactions towards rapid interactome discovery for bacterial organisms.\ud \ud Availability\ud The predictions for all Mtb and CD proteins are made available at: http://severus.dbmi.pitt.edu/TB and http://severus.dbmi.pitt.edu/CD respectively for browsing as well as for download

The Alzheimer's Biomarker Consortium-Down Syndrome: Rationale and methodology.

INTRODUCTION: Adults with Down syndrome (DS) are at exceptionally high risk for Alzheimer's disease (AD), with virtually all individuals developing key neuropathological features by age 40. Identifying biomarkers of AD progression in DS can provide valuable insights into pathogenesis and suggest targets for disease modifying treatments. METHODS: We describe the development of a multi-center, longitudinal study of biomarkers of AD in DS. The protocol includes longitudinal examination of clinical, cognitive, blood and cerebrospinal fluid-based biomarkers, magnetic resonance imaging and positron emission tomography measures (at 16-month intervals), as well as genetic modifiers of AD risk and progression. RESULTS: Approximately 400 individuals will be enrolled in the study (more than 370 to date). The methodological approach from the administrative, clinical, neuroimaging, omics, neuropathology, and statistical cores is provided. DISCUSSION: This represents the largest U.S.-based, multi-site, biomarker initiative of AD in DS. Findings can inform other multidisciplinary networks studying AD in the general population

Frataxin deficiency promotes endothelial senescence in pulmonary hypertension

The dynamic regulation of endothelial pathophenotypes in pulmonary hypertension (PH) remains undefined. Cellular senescence is linked to PH with intracardiac shunts; however, its regulation across PH subtypes is unknown. Since endothelial deficiency of iron-sulfur (Fe-S) clusters is pathogenic in PH, we hypothesized that a Fe-S biogenesis protein, frataxin (FXN), controls endothelial senescence. An endothelial subpopulation in rodent and patient lungs across PH subtypes exhibited reduced FXN and elevated senescence. In vitro, hypoxic and inflammatory FXN deficiency abrogated activity of endothelial Fe-S–containing polymerases, promoting replication stress, DNA damage response, and senescence. This was also observed in stem cell–derived endothelial cells from Friedreich’s ataxia (FRDA), a genetic disease of FXN deficiency, ataxia, and cardiomyopathy, often with PH. In vivo, FXN deficiency–dependent senescence drove vessel inflammation, remodeling, and PH, whereas pharmacologic removal of senescent cells in Fxn-deficient rodents ameliorated PH. These data offer a model of endothelial biology in PH, where FXN deficiency generates a senescent endothelial subpopulation, promoting vascular inflammatory and proliferative signals in other cells to drive disease. These findings also establish an endothelial etiology for PH in FRDA and left heart disease and support therapeutic development of senolytic drugs, reversing effects of Fe-S deficiency across PH subtypes

Factors Associated with Heritable Pulmonary Arterial Hypertension Exert Convergent Actions on the miR-130/301-Vascular Matrix Feedback Loop

Pulmonary arterial hypertension (PAH) is characterized by occlusion of lung arterioles, leading to marked increases in pulmonary vascular resistance. Although heritable forms of PAH are known to be driven by genetic mutations that share some commonality of function, the extent to which these effectors converge to regulate shared processes in this disease is unknown. We have causally connected extracellular matrix (ECM) remodeling and mechanotransduction to the miR-130/301 family in a feedback loop that drives vascular activation and downstream PAH. However, the molecular interconnections between factors genetically associated with PAH and this mechano-driven feedback loop remain undefined. We performed systematic manipulation of matrix stiffness, the miR-130/301 family, and factors genetically associated with PAH in primary human pulmonary arterial cells and assessed downstream and reciprocal consequences on their expression. We found that a network of factors linked to heritable PAH converges upon the matrix stiffening-miR-130/301-PPARγ-LRP8 axis in order to remodel the ECM. Furthermore, we leveraged a computational network biology approach to predict a number of additional molecular circuits functionally linking this axis to the ECM. These results demonstrate that multiple genes associated with heritable PAH converge to control the miR-130/301 circuit, triggering a self-amplifying feedback process central to pulmonary vascular stiffening and disease

How can we improve Science, Technology, Engineering, and Math education to encourage careers in Biomedical and Pathology Informatics?

The Computer Science, Biology, and Biomedical Informatics (CoSBBI) program was initiated in 2011 to expose the critical role of informatics in biomedicine to talented high school students.[1] By involving them in Science, Technology, Engineering, and Math (STEM) training at the high school level and providing mentorship and research opportunities throughout the formative years of their education, CoSBBI creates a research infrastructure designed to develop young informaticians. Our central premise is that the trajectory necessary to be an expert in the emerging fields of biomedical informatics and pathology informatics requires accelerated learning at an early age.In our 4th year of CoSBBI as a part of the University of Pittsburgh Cancer Institute (UPCI) Academy (http://www.upci.upmc.edu/summeracademy/), and our 2nd year of CoSBBI as an independent informatics-based academy, we enhanced our classroom curriculum, added hands-on computer science instruction, and expanded research projects to include clinical informatics. We also conducted a qualitative evaluation of the program to identify areas that need improvement in order to achieve our goal of creating a pipeline of exceptionally well-trained applicants for both the disciplines of pathology informatics and biomedical informatics in the era of big data and personalized medicine

Systems Analysis of the Human Pulmonary Arterial Hypertension Lung Transcriptome

Pulmonary arterial hypertension (PAH) is characterized by increased pulmonary artery pressure and vascular resistance, typically leading to right heart failure and death. Current therapies improve quality of life of the patients but have a modest effect on long-term survival. A detailed transcriptomics and systems biology view of the PAH lung is expected to provide new testable hypotheses for exploring novel treatments. We completed transcriptomics analysis of PAH and control lung tissue to develop disease-specific and clinical data/tissue pathology gene expression classifiers from expression datasets. Gene expression data were integrated into pathway analyses. Gene expression microarray data were collected from 58 PAH and 25 control lung tissues. The strength of the dataset and its derived disease classifier was validated using multiple approaches. Pathways and upstream regulators analyses was completed with standard and novel graphical approaches. The PAH lung dataset identified expression patterns specific to PAH subtypes, clinical parameters, and lung pathology variables. Pathway analyses indicate the important global role of TNF and transforming growth factor signaling pathways. In addition, novel upstream regulators and insight into the cellular and innate immune responses driving PAH were identified. Finally, WNT-signaling pathways may be a major determinant underlying the observed sex differences in PAH. This study provides a transcriptional framework for the PAH-diseased lung, supported by previously reported findings, and will be a valuable resource to the PAH research community. Our investigation revealed novel potential targets and pathways amenable to further study in a variety of experimental systems

Outcomes of Pulmonary Arterial Hypertension Are Improved in a Specialty Care Center

BackgroundPulmonary arterial hypertension (PAH) is characterized by elevated pulmonary arterial pressures and is managed by vasodilator therapies. Current guidelines encourage PAH management in specialty care centers (SCCs), but evidence is sparse regarding improvement in clinical outcomes and correlation to vasodilator use with referral.Research questionIs PAH management at SCCs associated with improved clinical outcomes?Study designand methodsA single-center, retrospective study was performed at the University of Pittsburgh Medical Center (UPMC; overseeing 40 hospitals). Patients with PAH were identified between 2008 and 2018 and classified into an SCC or non-SCC cohort. Cox proportional hazard modeling was done to compare for all-cause mortality, as was negative binomial regression modeling for hospitalizations. Vasodilator therapy was included to adjust outcomes.ResultsOf 580 patients with PAH at UPMC, 455 (78%) were treated at the SCC, comprising a younger (58.8 vs 64.8 years; P < .001) and more often female (68.4% vs 51.2%; P < .001) population with more comorbidities without differences in race or income. SCC patients demonstrated improved survival (hazard ratio, 0.68; P = .012) and fewer hospitalizations (incidence ratio, 0.54; P < .001), and provided more frequent disease monitoring. Early patient referral to SCC (< 6 months from time of diagnosis) was associated with improved outcomes compared with non-SCC patients. SCC patients were more frequently prescribed vasodilators (P < .001) and carried more diagnostic PAH coding (P < .001). Vasodilators were associated with improved outcomes irrespective of location but without statistical significance when comparing between locations (P > .05).InterpretationThe UPMC SCC demonstrated improved outcomes in mortality and hospitalizations. The SCC benefit was multifactorial, with more frequent vasodilator therapy and disease monitoring. These findings provide robust evidence for early and regular referral of patients with PAH to SCCs

Cerebrovascular disease emerges with age and Alzheimer’s disease in adults with Down syndrome

Adults with Down syndrome have a genetic form of Alzheimer's disease (AD) and evidence of cerebrovascular disease across the AD continuum, despite few systemic vascular risk factors. The onset and progression of AD in Down syndrome is highly age-dependent, but it is unknown at what age cerebrovascular disease emerges and what factors influence its severity. In the Alzheimer's Biomarker Consortium-Down Syndrome study (ABC-DS; n = 242; age = 25-72), we estimated the age inflection point at which MRI-based white matter hyperintensities (WMH), enlarged perivascular spaces (PVS), microbleeds, and infarcts emerge in relation to demographic data, risk factors, amyloid and tau, and AD diagnosis. Enlarged PVS and infarcts appear to develop in the early 30s, while microbleeds, WMH, amyloid, and tau emerge in the mid to late 30s. Age-residualized WMH were higher in women, in individuals with dementia, and with lower body mass index. Participants with hypertension and APOE-ε4 had higher age-residualized PVS and microbleeds, respectively. Lifespan trajectories demonstrate a dramatic cerebrovascular profile in adults with Down syndrome that appears to evolve developmentally in parallel with AD pathophysiology approximately two decades prior to dementia symptoms