scholarly journals Time-resolved genome-scale profiling reveals a causal expression network

2019 ◽  
Author(s):  
Sean R. Hackett ◽  
Edward A. Baltz ◽  
Marc Coram ◽  
Bernd J. Wranik ◽  
Griffin Kim ◽  
...  
Keyword(s):  
Indirect Effects ◽  
Causal Attribution ◽  
Model Potential ◽  
Dynamic Responses ◽  
Time Resolved ◽  
Genome Wide ◽  
Yeast Dataset ◽  
Regulatory Cascades ◽  
Genome Scale ◽  
Entire Dataset

AbstractWe present an approach for inferring genome-wide regulatory causality and demonstrate its application on a yeast dataset constructed by independently inducing hundreds of transcription factors and measuring timecourses of the resulting gene expression responses. We discuss the regulatory cascades in detail for a single transcription factor, Aft1; however, we have 201 TF induction timecourses that include >100,000 signal-containing dynamic responses. From a single TF induction timecourse we can often discriminate the direct from the indirect effects of the induced TF. Across our entire dataset, however, we find that the majority of expression changes are indirectly driven by unknown regulators. By integrating all timecourses into a single whole-cell transcriptional model, potential regulators of each gene can be predicted without incorporating prior information. In doing so, the indirect effects of a TF are understood as a series of direct regulatory predictions that capture how regulation propagates over time to create a causal regulatory network. This approach, which we call CANDID (Causal Attribution Networks Driven by Induction Dynamics), resulted in the prediction of multiple transcriptional regulators that were validated experimentally.

A genome-wide screen uncovers multiple roles for mitochondrial nucleoside diphosphate kinase D in inflammasome activation

2021 ◽  
Vol 14 (694) ◽  
pp. eabe0387
Author(s):  
Orna Ernst ◽  
Jing Sun ◽  
Bin Lin ◽  
Balaji Banoth ◽  
Michael G. Dorrington ◽  
...  
Keyword(s):  
Nucleoside Diphosphate Kinase ◽  
Multiple Roles ◽  
Metabolic Reprogramming ◽  
Inflammasome Activation ◽  
Ros Production ◽  
Genome Wide ◽  
A Genome ◽  
Mouse Macrophages ◽  
Genome Scale ◽  
Mitochondrial Dna Synthesis

Noncanonical inflammasome activation by cytosolic lipopolysaccharide (LPS) is a critical component of the host response to Gram-negative bacteria. Cytosolic LPS recognition in macrophages is preceded by a Toll-like receptor (TLR) priming signal required to induce transcription of inflammasome components and facilitate the metabolic reprograming that fuels the inflammatory response. Using a genome-scale arrayed siRNA screen to find inflammasome regulators in mouse macrophages, we identified the mitochondrial enzyme nucleoside diphosphate kinase D (NDPK-D) as a regulator of both noncanonical and canonical inflammasomes. NDPK-D was required for both mitochondrial DNA synthesis and cardiolipin exposure on the mitochondrial surface in response to inflammasome priming signals mediated by TLRs, and macrophages deficient in NDPK-D had multiple defects in LPS-induced inflammasome activation. In addition, NDPK-D was required for the recruitment of TNF receptor–associated factor 6 (TRAF6) to mitochondria, which was critical for reactive oxygen species (ROS) production and the metabolic reprogramming that supported the TLR-induced gene program. NDPK-D knockout mice were protected from LPS-induced shock, consistent with decreased ROS production and attenuated glycolytic commitment during priming. Our findings suggest that, in response to microbial challenge, NDPK-D–dependent TRAF6 mitochondrial recruitment triggers an energetic fitness checkpoint required to engage and maintain the transcriptional program necessary for inflammasome activation.

scholarly journals Modular Dynamic Biomolecular Modelling: The Unification of Stoichiometry, Thermodynamics, Kinetics and Data

2021 ◽  
Author(s):  
Peter J. Gawthrop ◽  
Michael Pan ◽  
Edmund J. Crampin
Keyword(s):  
Dynamic Models ◽  
System Development ◽  
Kinetic Modelling ◽  
Simulation Models ◽  
Bond Graph ◽  
Model Parameters ◽  
Biomolecular Systems ◽  
Genome Wide ◽  
Estimation Of Model Parameters ◽  
Genome Scale

AbstractRenewed interest in dynamic simulation models of biomolecular systems has arisen from advances in genome-wide measurement and applications of such models in biotechnology and synthetic biology. In particular, genome-scale models of cellular metabolism beyond the steady state are required in order to represent transient and dynamic regulatory properties of the system. Development of such whole-cell models requires new modelling approaches. Here we propose the energy-based bond graph methodology, which integrates stoichiometric models with thermo-dynamic principles and kinetic modelling. We demonstrate how the bond graph approach intrinsically enforces thermodynamic constraints, provides a modular approach to modelling, and gives a basis for estimation of model parameters leading to dynamic models of biomolecular systems. The approach is illustrated using a well-established stoichiometric model of E. coli and published experimental data.

scholarly journals Photoemission time versus streaking delay in attosecond time-resolved solid state photo-emission

2019 ◽  
Vol 205 ◽  
pp. 02019
Author(s):  
Andreas Gebauer ◽  
Sergej Neb ◽  
Walter Enns ◽  
Ulrich Heinzmann ◽  
Andrey K. Kazansky ◽  
...  
Keyword(s):  
Solid State ◽  
Schrödinger Equation ◽  
Schrodinger Equation ◽  
Model Potential ◽  
Time Dependent ◽  
Dimensional Model ◽  
Time Resolved ◽  
One Dimensional

Time-dependent Schrodinger equation simulations for a one-dimensional model potential reveal that the delay extracted from a streaking spectrogram does not reflect the photoemission time if the streaking field inside the solid cannot be neglected.

scholarly journals Rational Discovery of Dual-Action Multi-Target Kinase Inhibitor for Precision Anti-Cancer Therapy Using Structural Systems Pharmacology

2018 ◽  
Author(s):  
Hansaim Lim ◽  
Di He ◽  
Yue Qiu ◽  
Patrycja Krawczuk ◽  
Xiaoru Sun ◽  
...  
Keyword(s):  
Machine Learning ◽  
Heart Failure ◽  
Drug Resistance ◽  
Drug Repurposing ◽  
Target Drug ◽  
Genome Wide ◽  
Anti Cancer ◽  
Dual Action ◽  
Target Screening ◽  
Genome Scale

AbstractAlthough remarkable progresses have been made in the cancer treatment, existing anti-cancer drugs are associated with increasing risk of heart failure, variable drug response, and acquired drug resistance. To address these challenges, for the first time, we develop a novel genome-scale multi-target screening platform 3D-REMAP that integrates data from structural genomics and chemical genomics as well as synthesize methods from structural bioinformatics, biophysics, and machine learning. 3D-REMAP enables us to discover marked drugs for dual-action agents that can both reduce the risk of heart failure and present anti-cancer activity. 3D-REMAP predicts that levosimendan, a drug for heart failure, inhibits serine/threonine-protein kinase RIOK1 and other kinases. Subsequent experiments confirm this prediction, and suggest that levosimendan is active against multiple cancers, notably lymphoma, through the direct inhibition of RIOK1 and RNA processing pathway. We further develop machine learning models to identify cancer cell-lines and patients that may respond to levosimendan. Our findings suggest that levosimendan can be a promising novel lead compound for the development of safe and effective multi-targeted cancer therapy, and demonstrate the potential of genome-wide multi-target screening in designing polypharmacology and drug repurposing for precision medicine.Author SummaryMulti-target drug design (a.k.a targeted polypharmacology) has emerged as a new strategy for discovering novel therapeutics that can enhance therapeutic efficacy and overcome drug resistance in tackling multi-genic diseases such as cancer. However, it is extremely challenging for conventional computational tools that are either receptor-based or ligand-based to screen compounds for selectively targeting multiple receptors. Existing multi-target drug design mainly focuses on compound screening against receptors within the same gene family but not across different gene families. Here, we develop a new computational tool 3D-REMAP that enables us to identify chemical-protein interactions across fold space on a genome scale. The genome-scale chemical-protein interaction network allows us to discover dual-action drugs that can bind to two types of targets simultaneously, one for mitigating side effect and another for enhancing the therapeutic effect. Using 3D-REMAP, we predict and subsequently experiments validate that levosimendan, a drug for heart failure, is active against multiple cancers, notably, lymphoma. This study demonstrates the potential of genome-wide multi-target screening in designing polypharmacology and drug repurposing for precision medicine.

scholarly journals Identification of pathways modulating vemurafenib resistance in melanoma cells via a genome-wide CRISPR/Cas9 screen

2021 ◽  
Vol 11 (2) ◽  
Author(s):  
Corinna Jie Hui Goh ◽  
Jin Huei Wong ◽  
Chadi El Farran ◽  
Ban Xiong Tan ◽  
Cynthia R Coffill ◽  
...  
Keyword(s):  
Kinase Inhibitor ◽  
Mapk Pathway ◽  
Enrichment Analysis ◽  
Melanoma Cells ◽  
Mitogen Activated Protein Kinase ◽  
Braf V600e ◽  
Genome Wide ◽  
A Genome ◽  
Mitogen Activated Protein ◽  
Genome Scale

Abstract Vemurafenib is a BRAF kinase inhibitor (BRAFi) that is used to treat melanoma patients harboring the constitutively active BRAF-V600E mutation. However, after a few months of treatment patients often develop resistance to vemurafenib leading to disease progression. Sequence analysis of drug-resistant tumor cells and functional genomic screens has identified several genes that regulate vemurafenib resistance. Reactivation of mitogen-activated protein kinase (MAPK) pathway is a recurrent feature of cells that develop resistance to vemurafenib. We performed a genome-scale CRISPR-based knockout screen to identify modulators of vemurafenib resistance in melanoma cells with a highly improved CRISPR sgRNA library called Brunello. We identified 33 genes that regulate resistance to vemurafenib out of which 14 genes have not been reported before. Gene ontology enrichment analysis showed that the hit genes regulate histone modification, transcription and cell cycle. We discuss how inactivation of hit genes might confer resistance to vemurafenib and provide a framework for follow-up investigations.

scholarly journals Genome-scale phylogeny and contrasting modes of genome evolution in the fungal phylum Ascomycota

2020 ◽  
Vol 6 (45) ◽  
pp. eabd0079
Author(s):  
Xing-Xing Shen ◽  
Jacob L. Steenwyk ◽  
Abigail L. LaBella ◽  
Dana A. Opulente ◽  
Xiaofan Zhou ◽  
...  
Keyword(s):  
Genome Evolution ◽  
Filamentous Fungi ◽  
Common Ancestor ◽  
Evolutionary Change ◽  
Sequence Evolution ◽  
Last Common Ancestor ◽  
Molecular Sequence ◽  
Genome Wide ◽  
Similarities And Differences ◽  
Genome Scale

Ascomycota, the largest and most well-studied phylum of fungi, contains three subphyla: Saccharomycotina (budding yeasts), Pezizomycotina (filamentous fungi), and Taphrinomycotina (fission yeasts). Despite its importance, we lack a comprehensive genome-scale phylogeny or understanding of the similarities and differences in the mode of genome evolution within this phylum. By examining 1107 genomes from Saccharomycotina (332), Pezizomycotina (761), and Taphrinomycotina (14) species, we inferred a robust genome-wide phylogeny that resolves several contentious relationships and estimated that the Ascomycota last common ancestor likely originated in the Ediacaran period. Comparisons of genomic properties revealed that Saccharomycotina and Pezizomycotina differ greatly in their genome properties and enabled inference of the direction of evolutionary change. The Saccharomycotina typically have smaller genomes, lower guanine-cytosine contents, lower numbers of genes, and higher rates of molecular sequence evolution compared with Pezizomycotina. These results provide a robust evolutionary framework for understanding the diversity and ecological lifestyles of the largest fungal phylum.

scholarly journals Metabolic Responses of Carotenoid and Cordycepin Biosynthetic Pathways in Cordyceps militaris under Light-Programming Exposure through Genome-Wide Transcriptional Analysis

Biology ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 242
Author(s):  
Roypim Thananusak ◽  
Kobkul Laoteng ◽  
Nachon Raethong ◽  
Yu Zhang ◽  
Wanwipa Vongsangnak
Keyword(s):  
Process Development ◽  
Light Exposure ◽  
Carotenoid Biosynthesis ◽  
Cordyceps Militaris ◽  
Transcriptional Analysis ◽  
Metabolic Responses ◽  
Abiotic Factor ◽  
Metabolic Genes ◽  
Genome Wide ◽  
Genome Scale

Cordyceps militaris is currently exploited for commercial production of specialty products as its biomass constituents are enriched in bioactive compounds, such as cordycepin. The rational process development is important for economically feasible production of high quality bioproducts. Light is an abiotic factor affecting the cultivation process of this entomopathogenic fungus, particularly in its carotenoid formation. To uncover the cell response to light exposure, this study aimed to systematically investigate the metabolic responses of C. militaris strain TBRC6039 using integrative genome-wide transcriptome and genome-scale metabolic network (GSMN)-driven analysis. The genome-wide transcriptome analysis showed 8747 expressed genes in the glucose and sucrose cultures grown under light-programming and dark conditions. Of them, 689 differentially expressed genes were significant in response to the light-programming exposure. Through integration with the GSMN-driven analysis using the improved network (iRT1467), the reporter metabolites, e.g., adenosine-5′-monophosphate (AMP) and 2-oxoglutarate, were identified when cultivated under the carotenoid-producing condition controlled by light-programming exposure, linking to up-regulations of the metabolic genes involved in glyoxalase system, as well as cordycepin and carotenoid biosynthesis. These results indicated that C. militaris had a metabolic control in acclimatization to light exposure through transcriptional co-regulation, which supported the cell growth and cordycepin production in addition to the accumulation of carotenoid as a photo-protective bio-pigment. This study provides a perspective in manipulating the metabolic fluxes towards the target metabolites through either genetic or physiological approaches.

scholarly journals Genome-Wide Classification of Type I, Type II and Type III Interferon-Stimulated Genes in Chicken Fibroblasts

Vaccines ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 160 ◽  
Author(s):  
Santhakumar ◽  
Rohaim ◽  
Munir
Keyword(s):  
Differential Expression Analysis ◽  
Type I ◽  
Public Health Importance ◽  
Interferon Stimulated Genes ◽  
Dynamic Expression ◽  
Genome Wide ◽  
Unique Nature ◽  
Genome Scale ◽  
Multiple Pathogens ◽  
Type Iii Interferon

Interferons (IFNs) play central roles in establishing innate immunity and mediating adaptive immunity against multiple pathogens. Three known types of IFNs identify their cognate receptors, initiate cascades of signalling events and eventually result in the induction of a myriad of IFN-stimulated genes (ISGs). These ISGs perform a multitude of functions and cumulatively corroborate a bespoke antiviral state to safeguard hosts against invading viruses. Owing to the unique nature of a chicken’s immune system and the lack of foundational profiling information on the nature and dynamic expression of IFN-specific ISGs at the genome scale, we performed a systematic and extensive analysis of type I, II and III IFN-induced genes in chicken. Employing pan-IFN responsive chicken fibroblasts coupled with transcriptomics, we observed an over-representation of up-regulated ISGs compared to down-regulated ISGs by all types of IFNs. Intriguingly, prediction of IFN-stimulated response element (ISRE) and gamma-IFN activation sequence (GAS) revealed a substantial number of GAS motifs in selective and significantly induced ISGs in chicken. Extensive comparative, genome-wide and differential expression analysis of ISGs under equivalent signalling input catalogue a set of genes that were either IFN-specific or independent of types of IFNs used to prime fibroblasts. These comprehensive datasets, first of their kinds in chicken, will establish foundations to elucidate the mechanisms of actions and breadth of antiviral action of ISGs, which may propose alternative avenues for targeted antiviral therapy against viruses of poultry of public health importance.

scholarly journals Delineating the early transcriptional specification of the mammalian trachea and esophagus

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Akela Kuwahara ◽  
Ace E Lewis ◽  
Coohleen Coombes ◽  
Fang-Shiuan Leung ◽  
Michelle Percharde ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Mouse Embryos ◽  
Transcriptional Program ◽  
Chip Sequencing ◽  
Fate Specification ◽  
Master Regulators ◽  
Genome Wide ◽  
Single Cell Rna Sequencing ◽  
Genome Scale ◽  
New Framework

The genome-scale transcriptional programs that specify the mammalian trachea and esophagus are unknown. Though NKX2-1 and SOX2 are hypothesized to be co-repressive master regulators of tracheoesophageal fates, this is untested at a whole transcriptomic scale and their downstream networks remain unidentified. By combining single-cell RNA-sequencing with bulk RNA-sequencing of Nkx2-1 mutants and NKX2-1 ChIP-sequencing in mouse embryos, we delineate the NKX2-1 transcriptional program in tracheoesophageal specification, and discover that the majority of the tracheal and esophageal transcriptome is NKX2-1 independent. To decouple the NKX2-1 transcriptional program from regulation by SOX2, we interrogate the expression of newly-identified tracheal and esophageal markers in Sox2/Nkx2-1 compound mutants. Finally, we discover that NKX2-1 binds directly to Shh and Wnt7b and regulates their expression to control mesenchymal specification to cartilage and smooth muscle, coupling epithelial identity with mesenchymal specification. These findings create a new framework for understanding early tracheoesophageal fate specification at the genome-wide level.

Sign in / Sign up

Export Citation Format

Share Document