mini-Complexome Profiling (mCP), an FDR-controlled workflow for global targeted detection of protein complexes

IntroductionCo-fractionation mass spectrometry couples native-like separations of protein-protein complexes with mass spectrometric proteome analysis for global characterization of protein networks. The technique allows for both de novo detection of complexes and for the detection of subtle changes in their protein composition. The typical requirement for fine-grained fractionation of >80 fractions, however, translates into significant demands on sample quantity and mass spectrometric instrument time, and represents a significant barrier to experimental replication and the use of scarce sample material (ex. patient biopsies).MethodsWe developed mini-Complexome Profiling (mCP), a streamlined workflow with reduced requirements for fractionation and, thus, biological material and laboratory and instrument time. Soluble and membrane-associated protein complexes are extracted from biological material under mild conditions, and fractionated by Blue Native electrophoresis using commercial equipment. Each fraction is analysed by data-independent acquisition mass spectrometry, and known protein complexes are detected based on the coelution of known components using a novel R package with a controlled false discovery rate approach. The tool is available to the community on a GitHub repository.ResultsmCP was benchmarked using HEK293 cell lysate and exhibited performance similar to established workflows, but from a significantly reduced number of fractions. We then challenged mCP by performing comparative complexome analysis of cardiomyocytes isolated from different chambers from a single mouse heart, where we identified subtle chamber-specific changes in mitochondrial OxPhos complexes.DiscussionThe reduced sample and instrument time requirements open up new applications of co-fractionation mass spectrometry, specifically for the analysis of sparse samples such as human patient biopsies. The ability to identify subtle changes between similar tissue types (left/right ventricular and atrial cardiomyocytes) serves as a proof of principle for comparative analysis of mild/asymptomatic disease states

Ninein is essential for apico-basal microtubule formation and CLIP-170 facilitates its redeployment to non-centrosomal microtubule organizing centres.

Differentiation of columnar epithelial cells involves a dramatic reorganization of the microtubules (MTs) and centrosomal components into an apico-basal array no longer anchored at the centrosome. Instead, the minus-ends of the MTs become anchored at apical non-centrosomal microtubule organizing centres (n-MTOCs). Formation of n-MTOCs is critical as they determine the spatial organization of MTs, which in turn influences cell shape and function. However, how they are formed is poorly understood. We have previously shown that the centrosomal anchoring protein ninein is released from the centrosome, moves in a microtubule-dependent manner and accumulates at n-MTOCs during epithelial differentiation. Here, we report using depletion and knockout (KO) approaches that ninein expression is essential for apico-basal array formation and epithelial elongation and that CLIP-170 is required for its redeployment to n-MTOCs. Functional inhibition also revealed that IQGAP1 and active Rac1 coordinate with CLIP-170 to facilitate microtubule plus-end cortical targeting and ninein redeployment. Intestinal tissue and in vitro organoids from the Clip1/Clip2 double KO mouse with deletions in the genes encoding CLIP-170 and CLIP-115, respectively, confirmed requirement of CLIP-170 for ninein recruitment to n-MTOCs, with possible compensation by other anchoring factors such as p150Glued and CAMSAP2 ensuring apico-basal microtubule formation despite loss of ninein at n-MTOCs

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Personality Traits, Self-Employment, and Professions

We investigate the effect of broad personality traits' - the Big Five - on an individua's decision to become self-employed. In particular, we test an overall indicator of the entrepreneurial personality. Since we find that the level of self-employment varies considerably across professions, we also perform the analysis for different types of professions, namely, those classified as being in the 'creative class' as compared to the noncreative class. The analysis is based on micro data for individuals of the German Socio Economic Panel (SOEP). We find a significant association between personality traits and the propensity be become self-employed. However, the strength of this link is fairly weak and differs across professions, indicating an important effect of an individual's profession on his or her decision to run an own business

Network-based atrophy modelling in the common epilepsies: a worldwide ENIGMA study

SUMMARY Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional mega-analysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1,021 adults with epilepsy compared to 1,564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy co-localized with highly interconnected cortical hub regions, whereas idiopathic generalized epilepsy showed preferential subcortical hub involvement. These morphological abnormalities were anchored to the connectivity profiles of distinct disease epicenters, pointing to temporo-limbic cortices in temporal lobe epilepsy and fronto-central cortices in idiopathic generalized epilepsy. Indices of progressive atrophy further revealed a strong influence of connectome architecture on disease progression in temporal lobe, but not idiopathic generalized, epilepsy. Our findings were reproduced across individual sites and single patients, and were robust across different analytical methods. Through worldwide collaboration in ENIGMA-Epilepsy, we provided novel insights into the macroscale features that shape the pathophysiology of common epilepsies

The ENIGMA-Epilepsy working group: Mapping disease from large data sets

Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller‐scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well‐established by the ENIGMA Consortium, ENIGMA‐Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event‐based modeling analysis. We explore age of onset‐ and duration‐related features, as well as phenomena‐specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA‐Epilepsy