Objective Gene expression changes have been reported in the brains of suicide completers. More recently, differences in promoter DNA methylation between suicide completers and comparison subjects in specific genes have been associated with these changes in gene expression patterns, implicating DNA methylation alterations as a plausible component of the pathophysiology of suicide. The authors used a genome-wide approach to investigate the extent of DNA methylation alterations in the brains of suicide completers. Method Promoter DNA methylation was profiled using methylated DNA immunoprecipitation (MeDIP) followed by microarray hybridization in hippocampal tissue from 62 men (46 suicide completers and 16 comparison subjects). The correlation between promoter methylation and expression was investigated by comparing the MeDIP data with gene expression profiles generated through mRNA microarray. Methylation differences between groups were validated on neuronal and nonneuronal DNA fractions isolated by fluorescence-assisted cell sorting. Results The authors identified 366 promoters that were differentially methylated in suicide completers relative to comparison subjects (273 hypermethylated and 93 hypomethylated). Overall, promoter methylation differences were inversely correlated with gene expression differences. Functional annotation analyses revealed an enrichment of differential methylation in the promoters of genes involved, among other functions, in cognitive processes. Validation was performed on the top genes from this category, and these differences were found to occur mainly in the neuronal cell fraction. Conclusions These results suggest broad reprogramming of promoter DNA methylation patterns in the hippocampus of suicide completers. This may help explain gene expression alterations associated with suicide and possibly behavioral changes increasing suicide risk.
Abstract Quantifying changes in DNA and RNA levels is essential in numerous molecular biology protocols. Quantitative real time PCR (qPCR) techniques have evolved to become commonplace, however, data analysis includes many time-consuming and cumbersome steps, which can lead to mistakes and misinterpretation of data. To address these bottlenecks, we have developed an open-source Python software to automate processing of result spreadsheets from qPCR machines, employing calculations usually performed manually. Auto-qPCR is a tool that saves time when computing qPCR data, helping to ensure reproducibility of qPCR experiment analyses. Our web-based app ( https://auto-q-pcr.com/ ) is easy to use and does not require programming knowledge or software installation. Using Auto-qPCR, we provide examples of data treatment, display and statistical analyses for four different data processing modes within one program: (1) DNA quantification to identify genomic deletion or duplication events; (2) assessment of gene expression levels using an absolute model, and relative quantification (3) with or (4) without a reference sample. Our open access Auto-qPCR software saves the time of manual data analysis and provides a more systematic workflow, minimizing the risk of errors. Our program constitutes a new tool that can be incorporated into bioinformatic and molecular biology pipelines in clinical and research labs.
Abstract Quantifying changes in DNA and RNA levels is essential in numerous molecular biology protocols. Quantitative real time PCR (qPCR) techniques have evolved to become commonplace, however, data analysis includes many time-consuming and cumbersome steps, which can lead to mistakes and misinterpretation of data. To address these bottlenecks, we have developed an open-source Python software to automate processing of result spreadsheets from qPCR machines, employing calculations usually performed manually. Auto-qPCR is a tool that saves time when computing qPCR data, helping to ensure reproducibility of qPCR experiment analyses. Our web-based app ( https://auto-q-pcr.com/ ) is easy to use and does not require programming knowledge or software installation. Using Auto-qPCR, we provide examples of data treatment, display and statistical analyses for four different data processing modes within one program: (1) DNA quantification to identify genomic deletion or duplication events; (2) assessment of gene expression levels using an absolute model, and relative quantification (3) with or (4) without a reference sample. Our open access Auto-qPCR software saves the time of manual data analysis and provides a more systematic workflow, minimizing the risk of errors. Our program constitutes a new tool that can be incorporated into bioinformatic and molecular biology pipelines in clinical and research labs.
Abstract A growing body of knowledge implicates perturbed RNA homeostasis in amyotrophic lateral sclerosis (ALS), a neurodegenerative disease that currently has no cure and few available treatments. Dysregulation of the multifunctional RNA-binding protein TDP-43 is increasingly regarded as a convergent feature of this disease, evidenced at the neuropathological level by the detection of TDP-43 pathology in most patient tissues, and at the genetic level by the identification of disease-associated mutations in its coding gene TARDBP. To characterize the transcriptional landscape induced by TARDBP mutations, we performed whole-transcriptome profiling of motor neurons differentiated from two knock-in iPSC lines expressing the ALS-linked TDP-43 variants p.A382T or p.G348C. Our results show that the TARDBP mutations significantly altered the expression profiles of mRNAs and microRNAs of the 14q32 cluster in MNs. Using mutation-induced gene signatures and the Connectivity Map database, we identified compounds predicted to restore gene expression toward wild-type levels. Among top-scoring compounds selected for further investigation, the NEDD8-activating enzyme inhibitor MLN4924 effectively improved cell viability and neuronal activity, highlighting a possible role for protein post-translational modification via NEDDylation in the pathobiology of TDP-43 in ALS.
Abstract The development of targeted therapeutics for rare neurodevelopmental disorders (NDDs) faces significant challenges due to the scarcity of subjects and the difficulty of obtaining human neural cells. Here, we illustrate a rapid, simple protocol by which patient derived cells can be reprogrammed to induced pluripotent stem cells (iPSCs) using an episomal vector and differentiated into neurons. Using this platform enables patient somatic cells to be converted to physiologically active neurons in less than two months with minimal labor. This platform includes a method to combine somatic cell reprogramming with CRISPR/Cas9 gene editing at single cell resolution, which enables the concurrent development of clonal knockout or knock-in models that can be used as isogenic control lines. This platform reduces the logistical barrier for using iPSC technology, allows for the development of appropriate control lines for use in rare neurodevelopmental disease research, and establishes a fundamental component to targeted therapeutics and precision medicine.
Anorexia Nervosa (AN) is a dramatic psychiatric disorder characterized by dysregulations in food intake and reward processing, involving molecular and cellular changes in several peripheral cell types and central neuronal networks. Genomic and epigenomic analyses have allowed the identification of multiple genetic and epigenetic modifications highlighting the complex pathophysiology of AN. Behavioural and genetic rodent models have been used to recapitulate and investigate, with some limitations, the cellular and molecular changes that potentially underlie eating disorders. In the last five years, the use of induced-pluripotent stem cells, combined with CRISPR-Cas9 technology has led to the generation of specific neuronal cell sub-types engineered from human somatic samples, representing a powerful tool to complement observations made in human samples and data collected from animal models. Systems biology using induced-pluripotent stem cells has indeed proved to be a valuable approach for the study of metabolic disorders, in addition to neurodevelopmental and psychiatric disorders. The manuscript while reviewing the main findings related to the genetic, epigenetic and cellular bases of AN, will present how new studies published, or to be performed, in the field of IPSC-derived cells should improve our current understanding of the pathophysiology of AN, and provide potential therapeutic strategies addressing specific endophenotypes.
