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

Madness decolonized?: Madness as transnational identity in Gail Hornstein’s Agnes’s Jacket

The US psychologist Gail Hornstein’s monograph Agnes’s Jacket: A Psychologist’s Search for the Meanings of Madness (2009) is an important intervention in the identity politics of the mad movement. Hornstein offers a resignified vision of mad identity that embroiders the central trope of an “anti-colonial” struggle to reclaim the experiential world “colonized” by psychiatry. A series of literal and figurative appeals make recourse to the inner world and (corresponding) cultural world of the mad, as well as to the ethno-symbolic cultural materials of dormant nationhood. This rhetoric is augmented by a model in which the mad comprise a diaspora without an origin, coalescing into a single transnational community. The mad are also depicted as persons displaced from their metaphorical homeland, the “inner” world “colonized” by the psychiatric regime. There are a number of difficulties with Hornstein’s rhetoric, however. Her “ethnicity-and-rights” response to the oppression of the mad is symptomatic of Western parochialism, while her proposed transmutation of putative psychopathology from limit upon identity to parameter of successful identity is open to contestation. Moreover, unless one accepts Hornstein’s porous vision of mad identity, her self-ascribed insider status in relation to the mad community may present a problematic “re-colonization” of mad experience

Widespread somatic L1 retrotransposition occurs early during gastrointestinal cancer evolution

Somatic L1 retrotransposition events have been shown to occur in epithelial cancers. Here, we attempted to determine how early somatic L1 insertions occurred during the development of gastrointestinal (GI) cancers. Using L1-targeted resequencing (L1-seq), we studied different stages of four colorectal cancers arising from colonic polyps, seven pancreatic carcinomas, as well as seven gastric cancers. Surprisingly, we found somatic L1 insertions not only in all cancer types and metastases but also in colonic adenomas, well-known cancer precursors. Some insertions were also present in low quantities in normal GI tissues, occasionally caught in the act of being clonally fixed in the adjacent tumors. Insertions in adenomas and cancers numbered in the hundreds, and many were present in multiple tumor sections, implying clonal distribution. Our results demonstrate that extensive somatic insertional mutagenesis occurs very early during the development of GI tumors, probably before dysplastic growth

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Effects of selective serotonin reuptake inhibitor treatment on plasma oxytocin and cortisol in major depressive disorder

Background: Oxytocin is known for its capacity to facilitate social bonding, reduce anxiety and for its actions on the stress hypothalamopituitary adrenal (HPA) axis. Since oxytocin can physiologically suppress activity of the HPA axis, clinical applications of this neuropeptide have been proposed in conditions where the function of the HPA axis is dysregulated. One such condition is major depressive disorder (MDD). Dysregulation of the HPA system is the most prominent endocrine change seen with MDD, and normalizing the HPA axis is one of the major targets of recent treatments. The potential clinical application of oxytocin in MDD requires improved understanding of its relationship to the symptoms and underlying pathophysiology of MDD. Previous research has investigated potential correlations between oxytocin and symptoms of MDD, including a link between oxytocin and treatment related symptom reduction. The outcomes of studies investigating whether antidepressive treatment (pharmacological and non-pharmacological) influences oxytocin concentrations in MDD, have produced conflicting outcomes. These outcomes suggest the need for an investigation of the influence of a single treatment class on oxytocin concentrations, to determine whether there is a relationship between oxytocin, the HPA axis (e.g., oxytocin and cortisol) and MDD. Our objective was to measure oxytocin and cortisol in patients with MDD before and following treatment with selective serotonin reuptake inhibitors, SSRI. Method: We sampled blood from arterial plasma. Patients with MDD were studied at the same time twice; pre- and post- 12 weeks treatment, in an unblinded sequential design (clinicaltrials.govNCT00168493). Results: Results did not reveal differences in oxytocin or cortisol concentrations before relative to following SSRI treatment, and there were no significant relationships between oxytocin and cortisol, or these two physiological variables and psychological symptom scores, before or after treatment. Conclusions: These outcomes demonstrate that symptoms of MDD were reduced following effective treatment with an SSRI, and further, stress physiology was unlikely to be a key factor in this outcome. Further research is required to discriminate potential differences in underlying stress physiology for individuals with MDD who respond to antidepressant treatment, relative to those who experience treatment resistance.Charlotte Keating, Tye Dawood, David A Barton, Gavin W Lambert and Alan J Tilbroo

Reinvestigation of aminoacyl-TRNA synthetase core complex by affinity purification-mass spectrometry reveals TARSL2 as a potential member of the complex

10.1371/journal.pone.0081734PLoS ONE812-POLN

Comparative genomics reveals high biological diversity and specific adaptations in the industrially and medically important fungal genus Aspergillus

Peer reviewe