scholarly journals Transcriptional Profiles of Cell Fate Transitions Reveal Early Drivers of Neuronal Apoptosis and Survival

Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3238
Author(s):  
Giovanna Morello ◽  
Ambra Villari ◽  
Antonio Gianmaria Spampinato ◽  
Valentina La Cognata ◽  
Maria Guarnaccia ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Cell Fate ◽  
Drug Targets ◽  
Regulatory Networks ◽  
Neuronal Apoptosis ◽  
Drug Repurposing ◽  
Transcriptional Level ◽  
Functional Annotations ◽  
Drug Candidates ◽  
Core Set

Neuronal apoptosis and survival are regulated at the transcriptional level. To identify key genes and upstream regulators primarily responsible for these processes, we overlayed the temporal transcriptome of cerebellar granule neurons following induction of apoptosis and their rescue by three different neurotrophic factors. We identified a core set of 175 genes showing opposite expression trends at the intersection of apoptosis and survival. Their functional annotations and expression signatures significantly correlated to neurological, psychiatric and oncological disorders. Transcription regulatory network analysis revealed the action of nine upstream transcription factors, converging pro-apoptosis and pro-survival-inducing signals in a highly interconnected functionally and temporally ordered manner. Five of these transcription factors are potential drug targets. Transcriptome-based computational drug repurposing produced a list of drug candidates that may revert the apoptotic core set signature. Besides elucidating early drivers of neuronal apoptosis and survival, our systems biology-based perspective paves the way to innovative pharmacology focused on upstream targets and regulatory networks.

scholarly journals Leveraging high-powered RNA-Seq datasets to improve inference of regulatory activity in single-cell RNA-Seq data

2019 ◽  
Author(s):  
Ning Wang ◽  
Andrew E. Teschendorff
Keyword(s):  
Transcription Factors ◽  
Single Cell ◽  
Cell Fate ◽  
Regulatory Networks ◽  
Large Scale ◽  
Single Cells ◽  
Differential Expression Analysis ◽  
Dropout Rate ◽  
Rna Seq ◽  
Regulatory Activity

AbstractInferring the activity of transcription factors in single cells is a key task to improve our understanding of development and complex genetic diseases. This task is, however, challenging due to the relatively large dropout rate and noisy nature of single-cell RNA-Seq data. Here we present a novel statistical inference framework called SCIRA (Single Cell Inference of Regulatory Activity), which leverages the power of large-scale bulk RNA-Seq datasets to infer high-quality tissue-specific regulatory networks, from which regulatory activity estimates in single cells can be subsequently obtained. We show that SCIRA can correctly infer regulatory activity of transcription factors affected by high technical dropouts. In particular, SCIRA can improve sensitivity by as much as 70% compared to differential expression analysis and current state-of-the-art methods. Importantly, SCIRA can reveal novel regulators of cell-fate in tissue-development, even for cell-types that only make up 5% of the tissue, and can identify key novel tumor suppressor genes in cancer at single cell resolution. In summary, SCIRA will be an invaluable tool for single-cell studies aiming to accurately map activity patterns of key transcription factors during development, and how these are altered in disease.

scholarly journals Translational and Clinical Pharmacology Considerations in Drug Repurposing for X-linked Adrenoleukodystrophy-A Rare Peroxisomal Disorder

2021 ◽  
Author(s):  
Julianne Tieu ◽  
Siddhee Sahasrabudhe ◽  
Paul Orchard ◽  
James Cloyd ◽  
Reena Kartha
Keyword(s):  
Drug Target ◽  
Drug Targets ◽  
Drug Repurposing ◽  
Pharmacokinetics And Pharmacodynamics ◽  
Drug Candidates ◽  
Target Patient Population ◽  
Site Of Action ◽  
Repurposed Drugs ◽  
Gait Disturbances ◽  
Spastic Quadriparesis

X-linked adrenoleukodystrophy (X-ALD) is an inherited, neurodegenerative rare disease that can result in devastating symptoms of blindness, gait disturbances, and spastic quadriparesis due to progressive demyelination. Typically, the disease progresses rapidly, causing death within the first decade of life. With limited treatments available, efforts to determine an effective therapy that can alter disease progression or mitigate symptoms have been undertaken for many years, particularly through drug repurposing. Repurposing has generally been guided through clinical experience and small trials. At this time, none of the drug candidates have been approved for use, which may be due, in part, to the lack of pharmacokinetic/pharmacodynamic (PK/PD) information on the repurposed medications in the target patient population. Greater consideration for the disease pathophysiology, drug pharmacology, and potential drug-target interactions, specifically at the site of action, would improve drug repurposing and facilitate development. Although there is a good understanding of X-ALD pathophysiology, the absence of information on drug targets, pharmacokinetics, and pharmacodynamics hinders the repurposing of drugs for this condition. Incorporating advanced translational and clinical pharmacological approaches in preclinical studies and early stages clinical trials will improve the success of repurposed drugs for X-ALD as well as other rare diseases.

scholarly journals Molecular Logic of Hypothalamus Development

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A507-A507
Author(s):  
Thomas Kim
Keyword(s):  
Transcription Factors ◽  
Cell Fate ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Developmental Time ◽  
Specific Gene ◽  
Molecular Logic ◽  
Hypothalamic Nuclei ◽  
Physiological Homeostasis ◽  
Mutant Lines

Abstract The hypothalamus is a central regulator of physiological homeostasis. During development, multiple transcription factors coordinate the patterning and specification of hypothalamic nuclei. However, the molecular mechanisms controlling hypothalamic patterning and cell fate specification are poorly understood. To identify genes that control these processes, we have previously used single-cell RNA sequencing (scRNA-Seq) to profile mouse hypothalamic gene expression across multiple developmental time points and established database HyDD (Hypothalamus Developmental Database). We next used HyDD to characterize multiple mutant lines targetting key transcription factors that came out from our scRNA-Seq database (Nkx2.2, Dlx1/2, Isl1, Foxd1, Lhx2), and was able to comprehensively characterize mutants that have altered hypothalamic patterning. Our phenotype result supports a modified columnar model of organization for the diencephalon, where prethalamus and hypothalamus are situated in adjacent dorsal and ventral domains of the anterior diencephalon. Furthermore, using our mouse hypothalamus as a guideline, we are comparing scRNA-Seq dataset of developing chicken, zebrafish and human hypothalamus, to identify evolutionarily conserved and divergent region-specific gene regulatory networks. Lastly, we are improving mouse HyDD, in order to characterize adult hypothalamus neuronal subtypes.

scholarly journals Computational guided approach for drug repurposing against SARS-CoV-2

2021 ◽  
Author(s):  
Jigisha Anand ◽  
Tanmay Ghildiyal ◽  
Aakanksha Madhwal ◽  
Rishabh Bhatt ◽  
Devvret Verma ◽  
...  
Keyword(s):  
Drug Targets ◽  
De Novo ◽  
Drug Repositioning ◽  
Drug Repurposing ◽  
Computational Docking ◽  
Drug Candidates ◽  
Docking Tool ◽  
Inhibitory Potential ◽  
Approved Drugs ◽  
Tract Infections

Background: In the current SARS-CoV-2 outbreak, drug repositioning emerges as a promising approach to develop efficient therapeutics in comparison to de novo drug development. The present investigation screened 130 US FDA-approved drugs including hypertension, cardiovascular diseases, respiratory tract infections (RTI), antibiotics and antiviral drugs for their inhibitory potential against SARS-CoV-2. Materials & methods: The molecular drug targets against SARS-CoV-2 proteins were determined by the iGEMDOCK computational docking tool. The protein homology models were generated through SWISS Model workspace. The pharmacokinetics of all the ligands was determined by ADMET analysis. Results: The study identified 15 potent drugs exhibiting significant inhibitory potential against SARS-CoV-2. Conclusion: Our investigation has identified possible repurposed drug candidates to improve the current modus operandi of the treatment given to COVID-19 patients.

scholarly journals Quantifying the Stability of Coupled Genetic and Epigenetic Switches With Variational Methods

2021 ◽  
Vol 11 ◽  
Author(s):  
Amogh Sood ◽  
Bin Zhang
Keyword(s):  
Gene Regulation ◽  
Transcription Factors ◽  
Cell Fate ◽  
Histone Modifications ◽  
Regulatory Networks ◽  
Variational Principles ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Fate Decisions ◽  
The Impact

The Waddington landscape provides an intuitive metaphor to view development as a ball rolling down the hill, with distinct phenotypes as basins and differentiation pathways as valleys. Since, at a molecular level, cell differentiation arises from interactions among the genes, a mathematical definition for the Waddington landscape can, in principle, be obtained by studying the gene regulatory networks. For eukaryotes, gene regulation is inextricably and intimately linked to histone modifications. However, the impact of such modifications on both landscape topography and stability of attractor states is not fully understood. In this work, we introduced a minimal kinetic model for gene regulation that combines the impact of both histone modifications and transcription factors. We further developed an approximation scheme based on variational principles to solve the corresponding master equation in a second quantized framework. By analyzing the steady-state solutions at various parameter regimes, we found that histone modification kinetics can significantly alter the behavior of a genetic network, resulting in qualitative changes in gene expression profiles. The emerging epigenetic landscape captures the delicate interplay between transcription factors and histone modifications in driving cell-fate decisions.

scholarly journals Recent Advances in In Silico Target Fishing

Molecules ◽  
2021 ◽  
Vol 26 (17) ◽  
pp. 5124 ◽  
Author(s):  
Salvatore Galati ◽  
Miriana Di Stefano ◽  
Elisa Martinelli ◽  
Giulio Poli ◽  
Tiziano Tuccinardi
Keyword(s):  
Drug Discovery ◽  
In Silico ◽  
Drug Targets ◽  
Biological Activities ◽  
Protein Structures ◽  
Drug Repurposing ◽  
Specific Protein ◽  
Protein Targets ◽  
Drug Candidates ◽  
Target Fishing

In silico target fishing, whose aim is to identify possible protein targets for a query molecule, is an emerging approach used in drug discovery due its wide variety of applications. This strategy allows the clarification of mechanism of action and biological activities of compounds whose target is still unknown. Moreover, target fishing can be employed for the identification of off targets of drug candidates, thus recognizing and preventing their possible adverse effects. For these reasons, target fishing has increasingly become a key approach for polypharmacology, drug repurposing, and the identification of new drug targets. While experimental target fishing can be lengthy and difficult to implement, due to the plethora of interactions that may occur for a single small-molecule with different protein targets, an in silico approach can be quicker, less expensive, more efficient for specific protein structures, and thus easier to employ. Moreover, the possibility to use it in combination with docking and virtual screening studies, as well as the increasing number of web-based tools that have been recently developed, make target fishing a more appealing method for drug discovery. It is especially worth underlining the increasing implementation of machine learning in this field, both as a main target fishing approach and as a further development of already applied strategies. This review reports on the main in silico target fishing strategies, belonging to both ligand-based and receptor-based approaches, developed and applied in the last years, with a particular attention to the different web tools freely accessible by the scientific community for performing target fishing studies.

scholarly journals Identifying potential novel insights for COVID-19 pathogenesis and therapeutics using an integrated bioinformatics analysis of host transcriptome

2021 ◽  
Author(s):  
Salem El-aarag ◽  
Amal Mahmoud ◽  
Mahmoud ElHefnawi
Keyword(s):  
Transcription Factors ◽  
Drug Targets ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Hub Genes ◽  
Drug Candidates ◽  
Protein Protein Interaction ◽  
Target Network ◽  
Novel Drug

Abstract The molecular mechanisms underlying the pathogenesis of COVID-19 has not been fully discovered. This study aims to decipher potentially hidden parts of the pathogenesis of COVID-19, potential novel drug targets, and to identify potential drug candidates. Two gene expression profiles (GSE147507-GSE153970) were analyzed and overlapping differentially expressed genes (DEGs) were selected for which top enriched transcription factors and kinases were identified and pathway analysis was performed. Protein-protein interaction (PPI) of DEGs was constructed, hub genes were identified and module analysis was also performed. DGIdb database was used to identify drugs for the potential targets (hub genes and the most enriched transcription factors and kinases for DEGs). A drug-potential target network was constructed and drugs are ranked according to the degree. L1000FDW web-based utility was used to identify drugs that can reverse transcriptional profiles of COVID-19. We identified drugs currently in clinical trials and novel potential 8 drugs. Besides the well-known pathogenic pathways, It was found that axon guidance is a potential pathogenic pathway. Sema7A, which may exacerbate hypercytokinemia, is considered a potential novel drug target. Another potential novel pathway is related to TINF2 overexpression which may induce potential telomere dysfunction and hence DNA damage that may exacerbate lung fibrosis.

scholarly journals Transcriptome Analysis of Insulin Signaling-Associated Transcription Factors in C. elegans Reveal Their Genome-Wide Target Genes Specificity and Complexity

2021 ◽  
Vol 22 (22) ◽  
pp. 12462
Author(s):  
Neha Kaushik ◽  
Soumya Rastogi ◽  
Sonia Verma ◽  
Deepak Pandey ◽  
Ashutosh Halder ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Insulin Signaling ◽  
Regulatory Networks ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Large Set ◽  
Sequencing Analysis ◽  
Experimental Conditions ◽  
Functional Annotations ◽  
C Elegans

Insulin/IGF-1-like signaling (IIS) plays a crucial, conserved role in development, growth, reproduction, stress tolerance, and longevity. In Caenorhabditis elegans, the enhanced longevity under reduced insulin signaling (rIIS) is primarily regulated by the transcription factors (TFs) DAF-16/FOXO, SKN-1/Nrf-1, and HSF1/HSF-1. The specific and coordinated regulation of gene expression by these TFs under rIIS has not been comprehensively elucidated. Here, using RNA-sequencing analysis, we report a systematic study of the complexity of TF-dependent target gene interactions during rIIS under analogous genetic and experimental conditions. We found that DAF-16 regulates only a fraction of the C. elegans transcriptome but controls a large set of genes under rIIS; SKN-1 and HSF-1 show the opposite trend. Both of the latter TFs function as activators and repressors to a similar extent, while DAF-16 is predominantly an activator. For expression of the genes commonly regulated by TFs under rIIS conditions, DAF-16 is the principal determining factor, dominating over the other two TFs, irrespective of whether they activate or repress these genes. The functional annotations and regulatory networks presented in this study provide novel insights into the complexity of the gene regulatory networks downstream of the IIS pathway that controls diverse phenotypes, including longevity.

II. Genetic approaches to pain therapy

2000 ◽  
Vol 278 (4) ◽  
pp. G507-G512 ◽  
Author(s):  
John N. Wood
Keyword(s):  
Transcription Factors ◽  
Ion Channels ◽  
Cell Fate ◽  
Sensory Neuron ◽  
Sensory Neurons ◽  
Drug Targets ◽  
Pain Perception ◽  
Na Channel ◽  
Analgesic Drug ◽  
Null Mutant Mice

New analgesic drugs are necessary because a number of pain states are untreatable. Genetic approaches to the identification of analgesic drug targets include mapping genes involved in human pain perception (e.g., trkA involved in hereditary neuropathies), identifying regulators of sensory neuron function in simple multicellular organisms and then investigating the activity of their mammalian homologs (e.g., POU domain transcription factors that specify sensory cell fate), as well as difference, expression, and homology cloning of receptors, ion channels, and transcription factors present in sensory neurons. After target validation through the construction of null mutant mice, high-throughput cell-based screens can be used to identify potential drug candidates. As a result of these approaches, a number of receptors and ion channels present in sensory neurons such as voltage-gated sodium channels [sensory neuron specific (SNS) and Na channel novel] and ATP-gated (P2X3), capsaicin-gated [vanilloid receptor 1(VR1)], and proton-gated [acid-sensing ion channel (ASIC)] channels are now under investigation as potential new analgesic drug targets.

scholarly journals Molecular targets and system biology approaches for drug repurposing against SARS-CoV-2

2020 ◽  
Vol 44 (1) ◽  
Author(s):  
Rahul Kunwar Singh ◽  
Brijesh Singh Yadav ◽  
Tribhuvan Mohan Mohapatra
Keyword(s):  
Network Analysis ◽  
Drug Targets ◽  
Drug Repurposing ◽  
Main Body ◽  
Surface Receptors ◽  
Drug Candidates ◽  
Analysis Tools ◽  
Host Cell Surface ◽  
Almost All ◽  
Novel Drug

Abstract Background COVID-19, a pandemic declared by WHO, has infected about 39.5 million and killed about 1.1 million people throughout the world. There is the urgent need of more studies to identify the novel drug targets and the drug candidates against it to handle the situation. Main body To virtually screen various drugs against SARS-CoV-2, the scientists need the detail information about the various drug targets identified till date. The present review provides the information about almost all the drug targets, including structural and non-structural proteins of virus as well as host cell surface receptors, that can be used for virtual screening of drugs. Moreover, this review also focuses on the different network analysis tools that have been used for the identification of new drug targets and candidate repurposable drugs against SARS-CoV-2. Conclusion This review provides important insights of various drug targets and the network analysis tools to young bioinformaticians and will help in creating pace to the drug repurposing strategy for COVID-19 disease.

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