Spontaneous self-assembly of pathogenic huntingtin exon 1 protein into amyloid structures

PolyQ (polyglutamine) diseases such as HD (Huntington's disease) or SCA1 (spinocerebellar ataxia type 1) are neurodegenerative disorders caused by abnormally elongated polyQ tracts in human proteins. PolyQ expansions promote misfolding and aggregation of disease-causing proteins, leading to the appearance of nuclear and cytoplasmic inclusion bodies in patient neurons. Several lines of experimental evidence indicate that this process is critical for disease pathogenesis. However, the molecular mechanisms underlying spontaneous polyQ-containing aggregate formation and the perturbation of neuronal processes are still largely unclear. The present chapter reviews the current literature regarding misfolding and aggregation of polyQ-containing disease proteins. We specifically focus on studies that have investigated the amyloidogenesis of polyQ-containing HTTex1 (huntingtin exon 1) fragments. These protein fragments are disease-relevant and play a critical role in HD pathogenesis. We outline potential mechanisms behind mutant HTTex1 aggregation and toxicity, as well as proteins and small molecules that can modify HTTex1 amyloidogenesis in vitro and in vivo. The potential implications of such studies for the development of novel therapeutic strategies are discussed

Construction of antimicrobial peptide-drug combination networks from scientific literature based on a semi-automated curation workflow

Considerable research efforts are being invested in the development of novel antimicrobial therapies effective against the growing number of multi-drug resistant (MDR) pathogens. Notably, the combination of different agents is increasingly explored as means to exploit and improve individual agent actions while minimising microorganism resistance. Although there are several databases on antimicrobial agents, scientific literature is the primary source of information on experimental antimicrobial combination testing. This work presents a semi-automated database curation workflow that supports the mining of scientific literature and enables the reconstruction of recently documented antimicrobial combinations. Currently, the database contains data on antimicrobial combinations that have been experimentally tested against Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli, Listeria monocytogenes and Candida albicans, which are prominent pathogenic organisms and are well-known for their wide and growing resistance to conventional antimicrobials. Researchers are able to explore the experimental results for a single organism or across organisms. Likewise, researchers may look into indirect network associations and identify new potential combinations to be tested. The database is available without charges. Database URL: http://sing.ei.uvigo.es/antimicrobialCombination/This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145FEDER-006684), and support by FCT and the European Community fund FEDER, through the Programme COMPETE, under the scope of the Projects AntiPep PTDC/SAU-SAP/113196/2009 (FCOMP-01-0124-FEDER-016012) and RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462). Authors acknowledge the PhD Grant of Paula Jorge, funded by FCT Ref. SFRH/BD/ 88192/2012, and the PhD grants of Martin Pérez-Pérez and Gael Pe´rez-Rodriguez, funded by the University of Vigo. Finally, this study was partially funded by the [15VI013] Contract-Programme from the University of Vigo and the Agrupamento INBIOMED from DXPCTSUG-FEDER unha maneira de facer Europa (2012/273). This document reflects only the authors views and the European Union is not liable for any use that may be made of the information contained herein

Publisher, be damned! From price gouging to the open road

The economics and organization of academic publishing have been the subject of much controversy recently – within the UK and internationally. Both journalists (e.g. Monbiot, 2011) and academics (e.g. Gowers, 2012) have objected to publishers’ pricing practices and business models. The past few years have not only witnessed debate, but more energetic activity too. One publishing giant is currently boycotted by academics, and not for the first time. In a few instances, editorial boards have resigned en masse in protest at high subscription prices. We have seen the creation of numerous open-access initiatives and dozens of new open-access journals, including the über-respectable Public Library of Science (PLoS). In 2012, a group commissioned by the UK government published the results of its year-long study into the academic journal market and the feasibility of adopting open access (Finch Report, 2012). In this Proposition, we review some of these developments. [Taken from introduction

Systematic interaction network filtering identifies CRMP1 as a novel suppressor of huntingtin misfolding and neurotoxicity

Assemblies of huntingtin (HTT) fragments with expanded polyglutamine (polyQ) tracts are a pathological hallmark of Huntington's disease (HD). The molecular mechanisms by which these structures are formed and cause neuronal dysfunction and toxicity are poorly understood. Here, we utilized available gene expression data sets of selected brain regions of HD patients and controls for systematic interaction network filtering in order to predict disease-relevant, brain region-specific HTT interaction partners. Starting from a large protein-protein interaction (PPI) data set, a step-by-step computational filtering strategy facilitated the generation of a focused PPI network that directly or indirectly connects 13 proteins potentially dysregulated in HD with the disease protein HTT. This network enabled the discovery of the neuron-specific protein CRMP1 that targets aggregation-prone, N-terminal HTT fragments and suppresses their spontaneous self-assembly into proteotoxic structures in various models of HD. Experimental validation indicates that our network filtering procedure provides a simple but powerful strategy to identify disease-relevant proteins that influence misfolding and aggregation of polyQ disease proteins