scholarly journals Assessment of brain reference genes for RT-qPCR studies in neurodegenerative diseases

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Rasmus Rydbirk ◽  
Jonas Folke ◽  
Kristian Winge ◽  
Susana Aznar ◽  
Bente Pakkenberg ◽  
...  
Keyword(s):  
Neurodegenerative Diseases ◽  
Reference Genes ◽  
Target Gene ◽  
Structural Changes ◽  
A Priori ◽  
Brain Regions ◽  
Quantitative Real Time Pcr ◽  
Human Brain Tissue ◽  
Web Based ◽  
Gene Expression Levels

Abstract Evaluation of gene expression levels by reverse transcription quantitative real-time PCR (RT-qPCR) has for many years been the favourite approach for discovering disease-associated alterations. Normalization of results to stably expressed reference genes (RGs) is pivotal to obtain reliable results. This is especially important in relation to neurodegenerative diseases where disease-related structural changes may affect the most commonly used RGs. We analysed 15 candidate RGs in 98 brain samples from two brain regions from Alzheimer’s disease (AD), Parkinson’s disease (PD), Multiple System Atrophy, and Progressive Supranuclear Palsy patients. Using RefFinder, a web-based tool for evaluating RG stability, we identified the most stable RGs to be UBE2D2, CYC1, and RPL13 which we recommend for future RT-qPCR studies on human brain tissue from these patients. None of the investigated genes were affected by experimental variables such as RIN, PMI, or age. Findings were further validated by expression analyses of a target gene GSK3B, known to be affected by AD and PD. We obtained high variations in GSK3B levels when contrasting the results using different sets of common RG underlining the importance of a priori validation of RGs for RT-qPCR studies.

scholarly journals Co-Cultures ofPseudomonas aeruginosaandRoseobacter denitrificansReveal Shifts in Gene Expression Levels Compared to Solo Cultures

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Crystal A. Conway ◽  
Nwadiuto Esiobu ◽  
Jose V. Lopez
Keyword(s):  
Gene Expression ◽  
Target Gene ◽  
Beta Lactamase ◽  
Interspecies Interactions ◽  
Quantitative Real Time Pcr ◽  
Bacterial Strains ◽  
Microbial Cultures ◽  
Culturing Conditions ◽  
Gene Expression Levels

Consistent biosynthesis of desired secondary metabolites (SMs) from pure microbial cultures is often unreliable. In a proof-of-principle study to induce SM gene expression and production, we describe mixed “co-culturing” conditions and monitoring of messages via quantitative real-time PCR (qPCR). Gene expression of model bacterial strains (Pseudomonas aeruginosaPAO1 andRoseobacter denitrificansOch114) was analyzed in pure solo and mixed cocultures to infer the effects of interspecies interactions on gene expressionin vitro, TwoP. aeruginosagenes (PhzHcoding for portions of the phenazine antibiotic pathway leading to pyocyanin (PCN) and theRhdAgene for thiosulfate: cyanide sulfurtransferase (Rhodanese)) and twoR. denitrificansgenes (BetaLactfor metallo-beta-lactamase and theDMSPgene for dimethylpropiothetin dethiomethylase) were assessed for differential expression. Results showed thatR. denitrificansDMSPandBetaLactgene expression became elevated in a mixed culture. In contrast,P. aeruginosaco-cultures withR. denitrificansor a third species did not increase target gene expression above control levels. This paper provides insight for better control of target SM gene expressionin vitroand bypass complex genetic engineering manipulations.

Web-based Tools for Drug Repurposing: Successful Examples of Collaborative Research

2020 ◽  
Vol 28 (1) ◽  
pp. 181-195
Author(s):  
Quentin Vanhaelen
Keyword(s):  
User Interfaces ◽  
Collaborative Research ◽  
Meta Analysis ◽  
A Priori ◽  
Drug Repurposing ◽  
Data Access ◽  
Estimation Methods ◽  
Large Set ◽  
Computational Tools ◽  
Web Based

: Computational approaches have been proven to be complementary tools of interest in identifying potential candidates for drug repurposing. However, although the methods developed so far offer interesting opportunities and could contribute to solving issues faced by the pharmaceutical sector, they also come with their constraints. Indeed, specific challenges ranging from data access, standardization and integration to the implementation of reliable and coherent validation methods must be addressed to allow systematic use at a larger scale. In this mini-review, we cover computational tools recently developed for addressing some of these challenges. This includes specific databases providing accessibility to a large set of curated data with standardized annotations, web-based tools integrating flexible user interfaces to perform fast computational repurposing experiments and standardized datasets specifically annotated and balanced for validating new computational drug repurposing methods. Interestingly, these new databases combined with the increasing number of information about the outcomes of drug repurposing studies can be used to perform a meta-analysis to identify key properties associated with successful drug repurposing cases. This information could further be used to design estimation methods to compute a priori assessment of the repurposing possibilities.

scholarly journals ccNetViz: a WebGL-based JavaScript library for visualization of large networks

2020 ◽  
Vol 36 (16) ◽  
pp. 4527-4529
Author(s):  
Ales Saska ◽  
David Tichy ◽  
Robert Moore ◽  
Achilles Rasquinha ◽  
Caner Akdas ◽  
...  
Keyword(s):  
Systems Biology ◽  
Complex Networks ◽  
Open Source ◽  
High Speed ◽  
A Priori ◽  
Supplementary Information ◽  
Network Visualization ◽  
Supplementary Data ◽  
Web Based ◽  
Flow Of Information

Abstract Summary Visualizing a network provides a concise and practical understanding of the information it represents. Open-source web-based libraries help accelerate the creation of biologically based networks and their use. ccNetViz is an open-source, high speed and lightweight JavaScript library for visualization of large and complex networks. It implements customization and analytical features for easy network interpretation. These features include edge and node animations, which illustrate the flow of information through a network as well as node statistics. Properties can be defined a priori or dynamically imported from models and simulations. ccNetViz is thus a network visualization library particularly suited for systems biology. Availability and implementation The ccNetViz library, demos and documentation are freely available at http://helikarlab.github.io/ccNetViz/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Gray-Matter Expansion of Social Brain Networks in Individuals High in Public Self-Consciousness

2021 ◽  
Vol 11 (3) ◽  
pp. 374
Author(s):  
Tomoyo Morita ◽  
Minoru Asada ◽  
Eiichi Naito
Keyword(s):  
Gray Matter ◽  
Structural Changes ◽  
Gray Matter Volume ◽  
Brain Networks ◽  
Japanese Version ◽  
Brain Regions ◽  
The Self ◽  
Social Brain ◽  
Default Mode ◽  
Public Self Consciousness

Self-consciousness is a personality trait associated with an individual’s concern regarding observable (public) and unobservable (private) aspects of self. Prompted by previous functional magnetic resonance imaging (MRI) studies, we examined possible gray-matter expansions in emotion-related and default mode networks in individuals with higher public or private self-consciousness. One hundred healthy young adults answered the Japanese version of the Self-Consciousness Scale (SCS) questionnaire and underwent structural MRI. A voxel-based morphometry analysis revealed that individuals scoring higher on the public SCS showed expansions of gray matter in the emotion-related regions of the cingulate and insular cortices and in the default mode network of the precuneus and medial prefrontal cortex. In addition, these gray-matter expansions were particularly related to the trait of “concern about being evaluated by others”, which was one of the subfactors constituting public self-consciousness. Conversely, no relationship was observed between gray-matter volume in any brain regions and the private SCS scores. This is the first study showing that the personal trait of concern regarding public aspects of the self may cause long-term substantial structural changes in social brain networks.

scholarly journals Cortical structural differences in major depressive disorder correlate with cell type-specific transcriptional signatures

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jiao Li ◽  
Jakob Seidlitz ◽  
John Suckling ◽  
Feiyang Fan ◽  
Gong-Jun Ji ◽  
...  
Keyword(s):  
Gene Expression ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Structural Changes ◽  
Brain Regions ◽  
Cell Type ◽  
Major Depressive ◽  
Structural Differences ◽  
Neuroimaging Data ◽  
Cell Type Specific

AbstractMajor depressive disorder (MDD) has been shown to be associated with structural abnormalities in a variety of spatially diverse brain regions. However, the correlation between brain structural changes in MDD and gene expression is unclear. Here, we examine the link between brain-wide gene expression and morphometric changes in individuals with MDD, using neuroimaging data from two independent cohorts and a publicly available transcriptomic dataset. Morphometric similarity network (MSN) analysis shows replicable cortical structural differences in individuals with MDD compared to control subjects. Using human brain gene expression data, we observe that the expression of MDD-associated genes spatially correlates with MSN differences. Analysis of cell type-specific signature genes suggests that microglia and neuronal specific transcriptional changes account for most of the observed correlation with MDD-specific MSN differences. Collectively, our findings link molecular and structural changes relevant for MDD.

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