Dataset Information

Network organization of the huntingtin proteomic interactome in mammalian brain.

ABSTRACT: We used affinity-purification mass spectrometry to identify 747 candidate proteins that are complexed with Huntingtin (Htt) in distinct brain regions and ages in Huntington's disease (HD) and wild-type mouse brains. To gain a systems-level view of the Htt interactome, we applied Weighted Correlation Network Analysis to the entire proteomic data set to unveil a verifiable rank of Htt-correlated proteins and a network of Htt-interacting protein modules, with each module highlighting distinct aspects of Htt biology. Importantly, the Htt-containing module is highly enriched with proteins involved in 14-3-3 signaling, microtubule-based transport, and proteostasis. Top-ranked proteins in this module were validated as Htt interactors and genetic modifiers in an HD Drosophila model. Our study provides a compendium of spatiotemporal Htt-interacting proteins in the mammalian brain and presents an approach for analyzing proteomic interactome data sets to build in vivo protein networks in complex tissues, such as the brain.

SUBMITTER: Shirasaki DI

PROVIDER: S-EPMC3432264 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Network organization of the huntingtin proteomic interactome in mammalian brain.

Shirasaki Dyna I DI Greiner Erin R ER Al-Ramahi Ismael I Gray Michelle M Boontheung Pinmanee P Geschwind Daniel H DH Botas Juan J Coppola Giovanni G Horvath Steve S Loo Joseph A JA Yang X William XW

Neuron 20120701 1

We used affinity-purification mass spectrometry to identify 747 candidate proteins that are complexed with Huntingtin (Htt) in distinct brain regions and ages in Huntington's disease (HD) and wild-type mouse brains. To gain a systems-level view of the Htt interactome, we applied Weighted Correlation Network Analysis to the entire proteomic data set to unveil a verifiable rank of Htt-correlated proteins and a network of Htt-interacting protein modules, with each module highlighting distinct aspec ...[more]

PMID: 22794259

Similar Datasets

Project description:Recordings of ongoing neural activity with EEG and MEG exhibit oscillations of specific frequencies over a non-oscillatory background. The oscillations appear in the power spectrum as a collection of frequency bands that are evenly spaced on a logarithmic scale, thereby preventing mutual entrainment and cross-talk. Over the last few years, experimental, computational and theoretical studies have made substantial progress on our understanding of the biophysical mechanisms underlying the generation of network oscillations and their interactions, with emphasis on the role of neuronal synchronization. In this paper we ask a very different question. Rather than investigating how brain rhythms emerge, or whether they are necessary for neural function, we focus on what they tell us about functional brain connectivity. We hypothesized that if we were able to construct abstract networks, or "virtual brains", whose dynamics were similar to EEG/MEG recordings, those networks would share structural features among themselves, and also with real brains. Applying mathematical techniques for inverse problems, we have reverse-engineered network architectures that generate characteristic dynamics of actual brains, including spindles and sharp waves, which appear in the power spectrum as frequency bands superimposed on a non-oscillatory background dominated by low frequencies. We show that all reconstructed networks display similar topological features (e.g. structural motifs) and dynamics. We have also reverse-engineered putative diseased brains (epileptic and schizophrenic), in which the oscillatory activity is altered in different ways, as reported in clinical studies. These reconstructed networks show consistent alterations of functional connectivity and dynamics. In particular, we show that the complexity of the network, quantified as proposed by Tononi, Sporns and Edelman, is a good indicator of brain fitness, since virtual brains modeling diseased states display lower complexity than virtual brains modeling normal neural function. We finally discuss the implications of our results for the neurobiology of health and disease.

Project description:Abnormal neuroanatomic brain networks have been reported in schizophrenia, but their characterization across patients with psychotic disorders, and their potential alterations in nonpsychotic relatives, remain to be clarified. Participants recruited by the Bipolar and Schizophrenia Network for Intermediate Phenotypes consortium included 326 probands with psychotic disorders (107 with schizophrenia (SZ), 87 with schizoaffective disorder (SAD), 132 with psychotic bipolar disorder (BD)), 315 of their nonpsychotic first-degree relatives and 202 healthy controls. Single-subject gray matter graphs were extracted from structural MRI scans, and whole-brain neuroanatomic organization was compared across the participant groups. Compared with healthy controls, psychotic probands showed decreased nodal efficiency mainly in bilateral superior temporal regions. These regions had altered morphological relationships primarily with frontal lobe regions, and their network-level alterations were associated with positive symptoms of psychosis. Nonpsychotic relatives showed lower nodal centrality metrics in the prefrontal cortex and subcortical regions, and higher nodal centrality metrics in the left cingulate cortex and left thalamus. Diagnosis-specific analysis indicated that individuals with SZ had lower nodal efficiency in bilateral superior temporal regions than controls, probands with SAD only exhibited lower nodal efficiency in the left superior and middle temporal gyrus, and individuals with psychotic BD did not show significant differences from healthy controls. Our findings provide novel evidence of clinically relevant disruptions in the anatomic association of the superior temporal lobe with other regions of whole-brain networks in patients with psychotic disorders, but not in their unaffected relatives, suggesting that it is a disease-related trait. Network disorganization primarily involving frontal lobe and subcortical regions in nonpsychotic relatives may be related to familial illness risk.

Project description:Radiation therapy (RT) plays a vital role in the treatment of brain cancers, but it frequently results in cognitive decline in the patients who receive it. Because the underlying mechanisms for this decline remain poorly understood, the brain is typically treated as a single, uniform volume when evaluating the toxic effects of RT plans. This ignorance represents a significant deficit in the field of radiation oncology, as the technology exists to manipulate dose distributions to spare regions of the brain, but there exists no body of knowledge regarding what is critical to spare. This deficit exists due to the numerous confounding factors that are frequently associated with radiotherapy, including the tumors themselves, other treatments such as surgery and chemotherapy, and dose gradients across the brain. Here, we present a case in which a 57-year-old male patient received a uniform dose of radiation across the whole brain, did not receive concurrent chemotherapy, had minimal surgical intervention and a small tumor burden, and received resting-state functional magnetic resonance imaging (fMRI) scans both before and after RT. To our knowledge, this is the first study on the effects of whole-brain radiotherapy on functional network organization, and this patient's treatment regimen represents a rare and non-replicable opportunity to isolate the effects of radiation on functional connectivity. We observed substantial changes in the subject's behavior and functional network organization over a 12-month timeframe. Interestingly, the homogenous radiation dose to the brain had a heterogeneous effect on cortical networks, and the functional networks most affected correspond with observed cognitive behavioral deficits. This novel study suggests that the cognitive decline that occurs after whole-brain radiation therapy may be network specific and related to the disruption of large-scale distributed functional systems, and it indicates that fMRI is a promising avenue of study for optimizing cognitive outcomes after RT.

Dataset Information

Network organization of the huntingtin proteomic interactome in mammalian brain.

Publications

Network organization of the huntingtin proteomic interactome in mammalian brain.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets