MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

Abstract Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw.http://deepblue.lib.umich.edu/bitstream/2027.42/78256/1/1471-2105-11-504.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/2/1471-2105-11-504-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/3/1471-2105-11-504-S2.ZIPhttp://deepblue.lib.umich.edu/bitstream/2027.42/78256/4/1471-2105-11-504.pdfPeer Reviewe

Cough quality in children: a comparison of subjective vs. bronchoscopic findings

BACKGROUND: Cough is the most common symptom presenting to doctors. The quality of cough (productive or wet vs dry) is used clinically as well as in epidemiology and clinical research. There is however no data on the validity of cough quality descriptors. The study aims were to compare (1) cough quality (wet/dry and brassy/non-brassy) to bronchoscopic findings of secretions and tracheomalacia respectively and, (2) parent's vs clinician's evaluation of the cough quality (wet/dry). METHODS: Cough quality of children (without a known underlying respiratory disease) undergoing elective bronchoscopy was independently evaluated by clinicians and parents. A 'blinded' clinician scored the secretions seen at bronchoscopy on pre-determined criteria and graded (1 to 6). Kappa (K) statistics was used for agreement, and inter-rater and intra-rater agreement examined on digitally recorded cough. A receiver operating characteristic (ROC) curve was used to determine if cough quality related to amount of airway secretions present at bronchoscopy. RESULTS: Median age of the 106 children (62 boys, 44 girls) enrolled was 2.6 years (IQR 5.7). Parent's assessment of cough quality (wet/dry) agreed with clinicians' (K = 0.75, 95%CI 0.58–0.93). When compared to bronchoscopy (bronchoscopic secretion grade 4), clinicians' cough assessment had the highest sensitivity (0.75) and specificity (0.79) and were marginally better than parent(s). The area under the ROC curve was 0.85 (95%CI 0.77–0.92). Intra-observer (K = 1.0) and inter-clinician agreement for wet/dry cough (K = 0.88, 95%CI 0.82–0.94) was very good. Weighted K for inter-rater agreement for bronchoscopic secretion grades was 0.95 (95%CI 0.87–1). Sensitivity and specificity for brassy cough (for tracheomalacia) were 0.57 and 0.81 respectively. K for both intra and inter-observer clinician agreement for brassy cough was 0.79 (95%CI 0.73–0.86). CONCLUSIONS: Dry and wet cough in children, as determined by clinicians and parents has good clinical validity. Clinicians should however be cognisant that children with dry cough may have minimal to mild airway secretions. Brassy cough determined by respiratory physicians is highly specific for tracheomalacia

Treatment course and outcomes following drug and alcohol-related traumatic injuries

Both authors are with the NeuroTexas Institute at St. David's HealthCare, St. David's Medical Center, 1015 East 32nd Street, Suite 404, Austin, Texas 78705, USA -- Matthew C. Cowperthwaite is with the Center for Systems and Synthetic Biology, The University of Texas at Austin, 1 University Station, A4800, Austin, Texas 78712, USABackground: Alcohol and drug use is known to be a major factor affecting the incidence of traumatic injury. However, the ways in which immediate pre-injury substance use affects patients' clinical care and outcomes remains unclear. The goal of the present study is to determine the associations between pre-injury use of alcohol or drugs and patient injury severity, hospital course, and clinical outcome. Materials and methods: This study used more than 200,000 records from the National Trauma Data Bank (NTDB), which is the largest trauma registry in the United States. Incidents in the NTDB were placed into one of four classes: alcohol related, drug related, alcohol-and-drug related, and substance negative. Logistic regression models were used to determine comorbid conditions or treatment complications that were significantly associated with pre-injury substance use. Hospital charges were associated with the presence or absence of drugs and alcohol, and patient outcomes were assessed using discharge disposition as delimited by the NTDB. Results: The rates of complications arising during treatment were 8.3, 10.9, 9.9 and 8.6 per one hundred incidents in the alcohol related, drug related, alcohol-and-drug related, and substance-negative classes, respectively. Regression models suggested that pre-injury alcohol use is associated with a 15% higher risk of infection, whereas pre-injury drug use is associated with a 30% higher risk of infection. Pre-injury substance use did not appear to significantly impact clinical outcomes following treatment for traumatic injury, however. Conclusion: This study suggests that pre-injury drug use is associated with a significantly higher complication rate. In particular, infection during hospitalization is a significant risk for both alcohol and drug related trauma visits, and drug-related trauma incidents are associated with increased risk for additional circulatory complications. Although drug and alcohol related trauma incidents are not associated with appreciably worse clinical outcomes, patients experiencing such complications are associated with significantly greater length of stay and higher hospitalization costs. Therefore significant benefits to trauma patients could be gained with enhanced surveillance for pre-injury substance use upon admission to the ED, and closer monitoring for infection or circulatory complications during their period of hospitalization.Center for Systems and Synthetic [email protected]

AMP-Activated Kinase Restricts Rift Valley Fever Virus Infection by Inhibiting Fatty Acid Synthesis

The cell intrinsic innate immune responses provide a first line of defense against viral infection, and often function by targeting cellular pathways usurped by the virus during infection. In particular, many viruses manipulate cellular lipids to form complex structures required for viral replication, many of which are dependent on de novo fatty acid synthesis. We found that the energy regulator AMPK, which potently inhibits fatty acid synthesis, restricts infection of the Bunyavirus, Rift Valley Fever Virus (RVFV), an important re-emerging arthropod-borne human pathogen for which there are no effective vaccines or therapeutics. We show restriction of RVFV both by AMPK and its upstream activator LKB1, indicating an antiviral role for this signaling pathway. Furthermore, we found that AMPK is activated during RVFV infection, leading to the phosphorylation and inhibition of acetyl-CoA carboxylase, the first rate-limiting enzyme in fatty acid synthesis. Activating AMPK pharmacologically both restricted infection and reduced lipid levels. This restriction could be bypassed by treatment with the fatty acid palmitate, demonstrating that AMPK restricts RVFV infection through its inhibition of fatty acid biosynthesis. Lastly, we found that this pathway plays a broad role in antiviral defense since additional viruses from disparate families were also restricted by AMPK and LKB1. Therefore, AMPK is an important component of the cell intrinsic immune response that restricts infection through a novel mechanism involving the inhibition of fatty acid metabolism

Ibudilast, a Pharmacologic Phosphodiesterase Inhibitor, Prevents Human Immunodeficiency Virus-1 Tat-Mediated Activation of Microglial Cells

Human Immunodeficiency Virus-1 (HIV-1)-associated neurocognitive disorders (HAND) occur, in part, due to the inflammatory response to viral proteins, such as the HIV-1 transactivator of transcription (Tat), in the central nervous system (CNS). Given the need for novel adjunctive therapies for HAND, we hypothesized that ibudilast would inhibit Tat-induced excess production of pro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNFα) in microglial cells. Ibudilast is a non-selective cyclic AMP phosphodiesterase inhibitor that has recently shown promise as a treatment for neuropathic pain via its ability to attenuate glial cell activation. Accordingly, here we demonstrate that pre-treatment of both human and mouse microglial cells with increasing doses of ibudilast inhibited Tat-induced synthesis of TNFα by microglial cells in a manner dependent on serine/threonine protein phosphatase activity. Ibudilast had no effect on Tat-induced p38 MAP kinase activation, and blockade of adenosine A2A receptor activation did not reverse ibudilast's inhibition of Tat-induced TNFα production. Interestingly, ibudilast reduced Tat-mediated transcription of TNFα, via modulation of nuclear factor-kappa B (NF-κB) signaling, as shown by transcriptional activity of NF-κB and analysis of inhibitor of kappa B alpha (IκBα) stability. Together, our findings shed light on the mechanism of ibudilast's inhibition of Tat-induced TNFα production in microglial cells and may implicate ibudilast as a potential novel adjunctive therapy for the management of HAND

Hierarchical Modeling of Activation Mechanisms in the ABL and EGFR Kinase Domains: Thermodynamic and Mechanistic Catalysts of Kinase Activation by Cancer Mutations

Structural and functional studies of the ABL and EGFR kinase domains have recently suggested a common mechanism of activation by cancer-causing mutations. However, dynamics and mechanistic aspects of kinase activation by cancer mutations that stimulate conformational transitions and thermodynamic stabilization of the constitutively active kinase form remain elusive. We present a large-scale computational investigation of activation mechanisms in the ABL and EGFR kinase domains by a panel of clinically important cancer mutants ABL-T315I, ABL-L387M, EGFR-T790M, and EGFR-L858R. We have also simulated the activating effect of the gatekeeper mutation on conformational dynamics and allosteric interactions in functional states of the ABL-SH2-SH3 regulatory complexes. A comprehensive analysis was conducted using a hierarchy of computational approaches that included homology modeling, molecular dynamics simulations, protein stability analysis, targeted molecular dynamics, and molecular docking. Collectively, the results of this study have revealed thermodynamic and mechanistic catalysts of kinase activation by major cancer-causing mutations in the ABL and EGFR kinase domains. By using multiple crystallographic states of ABL and EGFR, computer simulations have allowed one to map dynamics of conformational fluctuations and transitions in the normal (wild-type) and oncogenic kinase forms. A proposed multi-stage mechanistic model of activation involves a series of cooperative transitions between different conformational states, including assembly of the hydrophobic spine, the formation of the Src-like intermediate structure, and a cooperative breakage and formation of characteristic salt bridges, which signify transition to the active kinase form. We suggest that molecular mechanisms of activation by cancer mutations could mimic the activation process of the normal kinase, yet exploiting conserved structural catalysts to accelerate a conformational transition and the enhanced stabilization of the active kinase form. The results of this study reconcile current experimental data with insights from theoretical approaches, pointing to general mechanistic aspects of activating transitions in protein kinases

Variations in Stress Sensitivity and Genomic Expression in Diverse S. cerevisiae Isolates

Interactions between an organism and its environment can significantly influence phenotypic evolution. A first step toward understanding this process is to characterize phenotypic diversity within and between populations. We explored the phenotypic variation in stress sensitivity and genomic expression in a large panel of Saccharomyces strains collected from diverse environments. We measured the sensitivity of 52 strains to 14 environmental conditions, compared genomic expression in 18 strains, and identified gene copy-number variations in six of these isolates. Our results demonstrate a large degree of phenotypic variation in stress sensitivity and gene expression. Analysis of these datasets reveals relationships between strains from similar niches, suggests common and unique features of yeast habitats, and implicates genes whose variable expression is linked to stress resistance. Using a simple metric to suggest cases of selection, we found that strains collected from oak exudates are phenotypically more similar than expected based on their genetic diversity, while sake and vineyard isolates display more diverse phenotypes than expected under a neutral model. We also show that the laboratory strain S288c is phenotypically distinct from all of the other strains studied here, in terms of stress sensitivity, gene expression, Ty copy number, mitochondrial content, and gene-dosage control. These results highlight the value of understanding the genetic basis of phenotypic variation and raise caution about using laboratory strains for comparative genomics

Sequence and Structure Signatures of Cancer Mutation Hotspots in Protein Kinases

Protein kinases are the most common protein domains implicated in cancer, where somatically acquired mutations are known to be functionally linked to a variety of cancers. Resequencing studies of protein kinase coding regions have emphasized the importance of sequence and structure determinants of cancer-causing kinase mutations in understanding of the mutation-dependent activation process. We have developed an integrated bioinformatics resource, which consolidated and mapped all currently available information on genetic modifications in protein kinase genes with sequence, structure and functional data. The integration of diverse data types provided a convenient framework for kinome-wide study of sequence-based and structure-based signatures of cancer mutations. The database-driven analysis has revealed a differential enrichment of SNPs categories in functional regions of the kinase domain, demonstrating that a significant number of cancer mutations could fall at structurally equivalent positions (mutational hotspots) within the catalytic core. We have also found that structurally conserved mutational hotspots can be shared by multiple kinase genes and are often enriched by cancer driver mutations with high oncogenic activity. Structural modeling and energetic analysis of the mutational hotspots have suggested a common molecular mechanism of kinase activation by cancer mutations, and have allowed to reconcile the experimental data. According to a proposed mechanism, structural effect of kinase mutations with a high oncogenic potential may manifest in a significant destabilization of the autoinhibited kinase form, which is likely to drive tumorigenesis at some level. Structure-based functional annotation and prediction of cancer mutation effects in protein kinases can facilitate an understanding of the mutation-dependent activation process and inform experimental studies exploring molecular pathology of tumorigenesis