Network analysis for complex neurodegenerative diseases

Purpose of Review Biomedicine is witnessing a paradigm shift in the way complex disorders are investigated. In particular, the need for big data interpretation has led to the development of pipelines that require the cooperation of different fields of expertise, including medicine, functional biology, informatics, mathematics and systems biology. This review sits at the crossroad of different disciplines and surveys the recent developments in the use of graph theory (in the form of network analysis) to interpret large and different datasets in the context of complex neurodegenerative diseases. It aims at a professional audience with different backgrounds. Recent Findings Biomedicine has entered the era of big data, and this is actively changing the way we approach and perform research. The increase in size and power of biomedical studies has led to the establishment of multi-centre, international working groups coordinating open access platforms for data generation, storage and analysis. Particularly, pipelines for data interpretation are under development, and network analysis is gaining momentum since it represents a versatile approach to study complex systems made of interconnected multiple players. Summary We will describe the era of big data in biomedicine and survey the major freely accessible multi-omics datasets. We will then introduce the principles of graph theory and provide examples of network analysis applied to the interpretation of complex neurodegenerative disorders

Protein network analysis links the NSL complex to Parkinson's disease via mitochondrial and nuclear biology

Whilst the majority of Parkinson's Disease (PD) cases are sporadic, much of our understanding of the pathophysiological basis of the disease can be traced back to the study of rare, monogenic forms of PD. In the past decade, the availability of genome-wide association studies (GWAS) has facilitated a shift in focus, toward identifying common risk variants conferring increased risk of developing PD across the population. A recent mitophagy screening assay of GWAS candidates has functionally implicated the non-specific lethal (NSL) complex in the regulation of PINK1-mitophagy. Here, a bioinformatics approach has been taken to investigate the proteome of the NSL complex, to unpick its relevance to PD pathogenesis. The NSL interactome has been built, using 3 online tools: PINOT, HIPPIE and MIST, to mine curated, literature-derived protein-protein interaction (PPI) data. We built (i) the 'mitochondrial' NSL interactome exploring its relevance to PD genetics and (ii) the PD-oriented NSL interactome to uncover biological pathways underpinning the NSL/PD association. In this study, we find the mitochondrial NSL interactome to be significantly enriched for the protein products of PD-associated genes, including the Mendelian PD genes LRRK2 and VPS35. In addition, we find nuclear processes to be amongst those most significantly enriched within the PD-associated NSL interactome. These findings strengthen the role of the NSL complex in sporadic and familial PD, mediated by both its mitochondrial and nuclear functions

Measuring lactase enzymatic activity in the teaching lab

Understanding how enzymes work, and relating this to real life examples, is critical to a wide range of undergraduate degrees in the biological and biomedical sciences. This easy to follow protocol was developed for first year undergraduate pharmacy students and provides an entry-level introduction to enzyme reactions and analytical procedures for enzyme analysis. The enzyme of choice is lactase, as this represents an example of a commercially available enzyme relevant to human disease/pharmaceutical practice. Lactase is extracted from dietary supplement tablets, and assessed using a colorimetric assay based upon hydrolysis of an artificial substrate for lactase (ortho-nitrophenol-beta-D-galactopyranoside, ONPG). Release of ortho-nitrophenol following the hydrolytic cleavage of ONPG by lactase is measured by a change in absorbance at 420 nm, and the effect of the temperature on the enzymatic reaction is evaluated by carrying out the reaction on ice, at room temperature and at 37 °C. More advanced analysis can be implemented using this protocol by assessing the enzyme activity under different conditions and using different reagents

Weighted protein interaction network analysis of frontotemporal dementia

The genetic analysis of complex disorders has undoubtedly led to the identification of a wealth of associations between genes and specific traits. However, moving from genetics to biochemistry one gene at a time has, to date, rather proved inefficient and under-powered to comprehensively explain the molecular basis of phenotypes. Here we present a novel approach, weighted protein−protein interaction network analysis (W-PPI-NA), to highlight key functional players within relevant biological processes associated with a given trait. This is exemplified in the current study by applying W-PPI-NA to frontotemporal dementia (FTD): We first built the state of the art FTD protein network (FTD-PN) and then analyzed both its topological and functional features. The FTD-PN resulted from the sum of the individual interactomes built around FTD-spectrum genes, leading to a total of 4198 nodes. Twenty nine of 4198 nodes, called inter-interactome hubs (IIHs), represented those interactors able to bridge over 60% of the individual interactomes. Functional annotation analysis not only reiterated and reinforced previous findings from single genes and gene-coexpression analyses but also indicated a number of novel potential disease related mechanisms, including DNA damage response, gene expression regulation, and cell waste disposal and potential biomarkers or therapeutic targets including EP300. These processes and targets likely represent the functional core impacted in FTD, reflecting the underlying genetic architecture contributing to disease. The approach presented in this study can be applied to other complex traits for which risk-causative genes are known as it provides a promising tool for setting the foundations for collating genomics and wet laboratory data in a bidirectional manner. This is and will be critical to accelerate molecular target prioritization and drug discovery

FORMAÇÃO ESPECIAL DE PROFESSORES: AVALIAÇÃO DE RESULTADOS EM UMA UNIVERSIDADE FEDERAL

A discussão sobre a formação de professores vem se ampliando em decorrência de variados problemas constatados no desempenho das redes escolares e na diminuição da procura pela carreira docente. Nesse contexto, o presente artigo tem como objetivo identificar no âmbito da Universidade Federal de Santa Maria (UFSM) os egressos do Curso Especial de Graduação para Formação de Professores para a Educação Profissional (PEG) que estão atuando como docente e analisar se os conhecimentos adquiridos no PEG contribuíram para encarar a realidade de uma sala de aula. Para tal investigação utilizou-se uma pesquisa descritiva, exploratória do tipo estudo de caso, utilizando-se como instrumento de coleta de dados a aplicação de um questionário enviado por e-mail com as informações para acesso e preenchimento do mesmo. O acesso ao questionário foi por meio do link da página da UFSM, sendo necessário utilizar o usuário e a senha do portal do professor. Neste contexto, o presente estudo foi realizado juntamente aos alunos egressos do PEG – UFSM. Como resultado constatou-se a importância e a necessidade dos cursos de formação e que poucos docentes sentiram problemas na formação de professores, nos levando a acreditar que esta constatação esteja ligada ao fato que a maioria já exercia a função de docente

DIFFERENT SHADING INTENSITIES INTERFERE WITH THE GROWTH OF Myrocarpus frondosus ALLEMÃO SEEDLINGS IN THE NURSERY?

Native tree species present different responses depending on their adaptability to varying degrees of sunlight. The objective of this study was to evaluate the growth of Myrocarpus frondosus seedlings under different shade conditions in a nursery. The experimental design included randomized blocks in a factorial scheme, corresponding to treatments of full sun (0%), or one of three shading intensities (30%, 50%, and 70%), with evaluation times of 30, 90, 150, 210, 270, 330, and 390 days after emergence – d.a.e. The evaluation of the morphological attributes height (H) and stem diameter (SD) were determined every 60 days, and H/SD ratio were calculated. At 390 d.a.e, the following attributes were evaluated: aerial dry matter, (ADM), root dry matter (RDM), total dry matter, (TDM), Dickson quality index (DQI), leaf area (LA), root volume (RV), and root length. The pigment contents of chlorophyll a, chlorophyll b, and chlorophyll a/b ratio were also identified, along with carotenoid content, maximum quantum yield PSII (Fv/Fm), and electron transport rate (ETR). Myrocarpus frondosus requires shading in its initial stage of growth, at an ideal intensity of 50% or 70% for producing seedlings.

Integrating protein networks and machine learning for disease stratification in the Hereditary Spastic Paraplegias.

The Hereditary Spastic Paraplegias are a group of neurodegenerative diseases characterized by spasticity and weakness in the lower body. Owing to the combination of genetic diversity and variable clinical presentation, the Hereditary Spastic Paraplegias are a strong candidate for protein-protein interaction network analysis as a tool to understand disease mechanism(s) and to aid functional stratification of phenotypes. In this study, experimentally validated human data were used to create a protein-protein interaction network based on the causative genes. Network evaluation as a combination of topological analysis and functional annotation led to the identification of core proteins in putative shared biological processes, such as intracellular transport and vesicle trafficking. The application of machine learning techniques suggested a functional dichotomy linked with distinct sets of clinical presentations, indicating that there is scope to further classify conditions currently described under the same umbrella-term of Hereditary Spastic Paraplegias based on specific molecular mechanisms of disease

Protein interaction network analysis reveals genetic enrichment of immune system genes in frontotemporal dementia

To further unravel the complex genetic etiology of frontotemporal dementia (FTD), we hypothesized that interactors of the protein products of known FTD genes might be involved in the molecular pathways towards disease. We therefore applied protein interaction network (PIN) analysis to prioritize candidate genes for rare variant association. We created an FTD-PIN starting from known FTD genes downloading their physical interactors and performed functional enrichment analyses. We identified overrepresented processes in FTD and selected genes (n=440) belonging to the FTD processes for rare variant analysis in a Belgian cohort of 228 FTD patients and 345 controls. SKAT-O analysis suggested TNFAIP3 as the top gene (P = 0.7 × 10−3) reaching near test-wide significance (P = 2.5 × 10−4). We then analyzed the TNFAIP3-subnetwork within the FTD-PIN which indicated enrichment of several immune signaling networks, suggesting that disrupted immune signaling may be implicated in TNFAIP3-related FTD. Our study demonstrates that integration of PINs with genetic data is a useful approach to increase the power for rare variant association analysis. Furthermore, we present a computational pipeline for identifying potential novel therapeutic targets and risk-modifying variants

The LRRK2-macroautophagy axis and its relevance to Parkinson's Disease

A wide variety of different functions and an impressive array of interactors have been associated with leucine-rich repeat kinase 2 (LRRK2) over the years. Here, I discuss the hypothesis that LRRK2 may be capable of interacting with different proteins at different times and places, therefore, controlling a plethora of diverse functions based on the different complexes formed. Among these, I will then focus on macroautophagy in the general context of the endolysosomal system. First, the relevance of autophagy in Parkinson's disease will be evaluated giving a brief overview of all the relevant Parkinson's disease genes; then, the association of LRRK2 with macroautophagy and the endolysosomal pathway will be analyzed based on the supporting literature