scholarly journals Design trade-offs and robust architectures for combined transcriptional and translational resource allocation controllers

2020 ◽  
Author(s):  
Alexander P.S. Darlington ◽  
Declan G. Bates
Keyword(s):  
Gene Expression ◽  
Resource Allocation ◽  
Control System ◽  
Robust Control ◽  
Specific Gene ◽  
Circuit Performance ◽  
Regulatory Interactions ◽  
Trade Offs ◽  
The Impact ◽  
Shared Gene

AbstractRecent work on engineering synthetic cellular circuitry has shown that non-regulatory interactions brought about through competition for shared gene expression resources, such as RNA polymerase and ribosomes, can result in degraded performance or even circuit failure. Transcriptional and translational resource allocation controllers based on orthogonal ‘circuit-specific’ gene expression machineries have previously been separately designed to enforce modularity and improve circuit performance. Here we investigate the potential advantages, challenges, and design trade-offs involved in combining transcriptional and translational resource allocation into one overarching centralised control system. We design a number of biologically feasible controllers that reduce coupling at both the transcriptional and translational levels simultaneously, and identify some key performance tradeoffs. We apply tools from robust control theory to rigorously quantify the impact of uncertainty/variability arising due to experimental implementations on the operation of such controllers. Based on these results, we identify promising architectures for the construction of robust dual transcriptional–translational resource allocation controllers.

scholarly journals Modulation of Human Mesenchymal Stem Cells by Electrical Stimulation Using an Enzymatic Biofuel Cell

Catalysts ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 62
Author(s):  
Won-Yong Jeon ◽  
Seyoung Mun ◽  
Wei Beng Ng ◽  
Keunsoo Kang ◽  
Kyudong Han ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Mesenchymal Stem Cells ◽  
Electrical Stimulation ◽  
Regenerative Medicine ◽  
Cell Morphology ◽  
Electrical Current ◽  
Specific Gene ◽  
Next Generation ◽  
The Impact

Enzymatic biofuel cells (EBFCs) have excellent potential as components in bioelectronic devices, especially as active biointerfaces to regulate stem cell behavior for regenerative medicine applications. However, it remains unclear to what extent EBFC-generated electrical stimulation can regulate the functional behavior of human adipose-derived mesenchymal stem cells (hAD-MSCs) at the morphological and gene expression levels. Herein, we investigated the effect of EBFC-generated electrical stimulation on hAD-MSC cell morphology and gene expression using next-generation RNA sequencing. We tested three different electrical currents, 127 ± 9, 248 ± 15, and 598 ± 75 nA/cm2, in mesenchymal stem cells. We performed transcriptome profiling to analyze the impact of EBFC-derived electrical current on gene expression using next generation sequencing (NGS). We also observed changes in cytoskeleton arrangement and analyzed gene expression that depends on the electrical stimulation. The electrical stimulation of EBFC changes cell morphology through cytoskeleton re-arrangement. In particular, the results of whole transcriptome NGS showed that specific gene clusters were up- or down-regulated depending on the magnitude of applied electrical current of EBFC. In conclusion, this study demonstrates that EBFC-generated electrical stimulation can influence the morphological and gene expression properties of stem cells; such capabilities can be useful for regenerative medicine applications such as bioelectronic devices.

scholarly journals Starvation resistance and tissue-specific gene expression of stress-related genes in a naturally inbred ant population

2016 ◽  
Vol 3 (4) ◽  
pp. 160062 ◽  
Author(s):  
Nick Bos ◽  
Unni Pulliainen ◽  
Liselotte Sundström ◽  
Dalial Freitak
Keyword(s):  
Gene Expression ◽  
Stress Responses ◽  
Specific Gene ◽  
Starvation Resistance ◽  
Specific Expression ◽  
Tissue Specific ◽  
Trade Offs ◽  
Stress Related Genes ◽  
The Individual ◽  
Different Tissues

Starvation is one of the most common and severe stressors in nature. Not only does it lead to death if not alleviated, it also forces the starved individual to allocate resources only to the most essential processes. This creates energetic trade-offs which can lead to many secondary challenges for the individual. These energetic trade-offs could be exacerbated in inbred individuals, which have been suggested to have a less efficient metabolism. Here, we studied the effect of inbreeding on starvation resistance in a natural population of Formica exsecta ants, with a focus on survival and tissue-specific expression of stress, metabolism and immunity-related genes. Starvation led to large tissue-specific changes in gene expression, but inbreeding had little effect on most of the genes studied. Our results illustrate the importance of studying stress responses in different tissues instead of entire organisms.

scholarly journals Patient ancestry significantly contributes to molecular heterogeneity of systemic lupus erythematosus

2020 ◽  
Author(s):  
Michelle D. Catalina ◽  
Prathyusha Bachali ◽  
Anthony E. Yeo ◽  
Nicholas S. Geraci ◽  
Michelle A. Petri ◽  
...  
Keyword(s):  
Gene Expression ◽  
Systemic Lupus Erythematosus ◽  
Native American ◽  
Lupus Erythematosus ◽  
Gene Signature ◽  
Specific Gene ◽  
Molecular Heterogeneity ◽  
Systemic Lupus ◽  
Gene Expression Signatures ◽  
The Impact

AbstractGene expression signatures can stratify patients with heterogeneous diseases, such as Systemic Lupus Erythematosus (SLE), yet understanding the contributions of ancestral background to this heterogeneity is not well elucidated. We hypothesized that ancestry would significantly influence gene expression signatures and measured 34 gene modules in 1566 SLE patients of african (AA), european (EA) or native american (NAA) ancestry to determine the impact of ancestry on gene expression. Healthy subject ancestry-specific gene expression provided the transcriptomic background upon which the SLE patient signatures were built. Although standard therapy affected every gene signature, and significantly increased myeloid cell signatures, logistic regression analysis determined that ancestral background significantly changed 23/34 gene signatures. Additionally, the strongest association to gene expression changes was autoantibodies and this also had etiology in ancestry; the AA predisposition to have both RNP and dsDNA autoantibodies compared to EA predisposition to have only antidsDNA. A machine learning approach was used to determine a gene signature characteristic to distinguish AA SLE and was most influenced by genes characteristic of the perturbed B cell axis in AA SLE patients.

scholarly journals Predicting genotype-specific gene regulatory networks

2021 ◽  
Author(s):  
Deborah Weighill ◽  
Marouen Ben Guebila ◽  
Kimberly Glass ◽  
John Quackenbush ◽  
John Platig
Keyword(s):  
Gene Expression ◽  
Gene Regulatory Network ◽  
Gene Regulatory Networks ◽  
Genetic Variants ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Specific Gene ◽  
Disease Etiology ◽  
Gene Regulatory ◽  
The Impact

AbstractThe majority of disease-associated genetic variants are thought to have regulatory effects, including the disruption of transcription factor (TF) binding and the alteration of downstream gene expression. Identifying how a person’s genotype affects their individual gene regulatory network has the potential to provide important insights into disease etiology and to enable improved genotype-specific disease risk assessments and treatments. However, the impact of genetic variants is generally not considered when constructing gene regulatory networks. To address this unmet need, we developed EGRET (Estimating the Genetic Regulatory Effect on TFs), which infers a genotype-specific gene regulatory network (GRN) for each individual in a study population by using message passing to integrate genotype-informed TF motif predictions - derived from individual genotype data, the predicted effects of variants on TF binding and gene expression, and TF motif predictions - with TF protein-protein interactions and gene expression. Comparing EGRET networks for two blood-derived cell lines identified genotype-associated cell-line specific regulatory differences which were subsequently validated using allele-specific expression, chromatin accessibility QTLs, and differential TF binding from ChIP-seq. In addition, EGRET GRNs for three cell types across 119 individuals captured regulatory differences associated with disease in a cell-type-specific manner. Our analyses demonstrate that EGRET networks can capture the impact of genetic variants on complex phenotypes, supporting a novel fine-scale stratification of individuals based on their genetic background. EGRET is available through the Network Zoo R package (netZooR v0.9; netzoo.github.io).

scholarly journals Mitochondrial acetyl-CoA reversibly regulates locus-specific histone acetylation and gene expression

2018 ◽  
Author(s):  
Oswaldo A. Lozoya ◽  
Tianyuan Wang ◽  
Dagoberto Grenet ◽  
Taylor C. Wolfgang ◽  
Mack Sobhany ◽  
...  
Keyword(s):  
Gene Expression ◽  
Specific Gene ◽  
Atp Citrate Lyase ◽  
Acetyl Coa ◽  
Mtdna Depletion ◽  
Citrate Lyase ◽  
Environmental Agents ◽  
Physiological Outcomes ◽  
The Impact ◽  
Histone Hypoacetylation

AbstractThe impact of mitochondria in epigenetics is emerging but our understanding of this relationship and its impact on gene expression remain incomplete. We previously showed that acute mitochondrial DNA (mtDNA) loss leads to histone hypoacetylation. It remains to be defined if these changes are maintained when mitochondrial dysfunction is chronic and, importantly, if they are sufficient to alter gene expression. To fill these gaps, we here studied both a progressive and a chronic model of mtDNA depletion using biochemical, pharmacological, genomics and genetic assays. We show that histones are hypoacetylated in both models. We link these effects to decreased histone acetyltransferase (HAT) activity independent of changes in ATP citrate lyase function, which can be reversibly modulated by altering specifically the mitochondrial pool of acetyl-CoA. Also, we determined that these changes regulate locus-specific gene expression and physiological outcomes, including the production of prostaglandins. These results may be relevant to the pathophysiology of mtDNA depletion syndromes and to understanding the effects of environmental agents, such as AZT or antibiotics, that lead to physical or functional mtDNA loss.

scholarly journals Growth-Rate Dependent And Nutrient-Specific Gene Expression Resource Allocation In Fission Yeast

2021 ◽  
Author(s):  
Istvan T. Kleijn ◽  
Amalia Martínez-Segura ◽  
François Bertaux ◽  
Malika Saint ◽  
Holger Kramer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Growth Rate ◽  
Resource Allocation ◽  
Fission Yeast ◽  
Metabolic Enzymes ◽  
Specific Gene ◽  
Specific Gene Expression ◽  
Rate Dependent ◽  
Specific Regulation ◽  
Yeast Genes

Cellular resources are limited and their relative allocation to gene expression programmes determines physiological states and global properties such as the growth rate. Quantitative studies using various growth conditions have singled out growth rate as a major physiological variable explaining relative protein abundances. Here, we used the simple eukaryote Schizosaccharomyces pombe to determine the importance of growth rate in explaining relative changes in protein and mRNA levels during growth on a series of non-limiting nitrogen sources. Although half of fission yeast genes were significantly correlated with the growth rate, this came alongside wide-spread nutrient-specific regulation. Proteome and transcriptome often showed coordinated regulation but with notable exceptions, such as metabolic enzymes. Genes positively correlated with growth rate participated in every level of protein production with the notable exception of RNA polymerase II, whereas those negatively correlated mainly belonged to the environmental stress response programme. Critically, metabolic enzymes, which represent ~55-70% of the proteome by mass, showed mainly condition-specific regulation. Specifically, many enzymes involved in glycolysis and NAD-dependent metabolism as well as the fermentative and respiratory pathways were condition-dependent and not consistently correlated with growth. In summary, we provide a rich account of resource allocation to gene expression in a simple eukaryote, advancing our basic understanding of the interplay between growth-rate dependent and nutrient-specific gene expression.

scholarly journals dynDeepDRIM: a dynamic deep learning model to infer direct regulatory interactions using single cell time-course gene expression data

2021 ◽  
Author(s):  
Yu Xu ◽  
Jiaxing Chen ◽  
Aiping Lyu ◽  
William K Cheung ◽  
Lu Zhang
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Gene Expression Data ◽  
Time Course ◽  
Target Genes ◽  
Neighborhood Context ◽  
Specific Gene ◽  
Expression Data ◽  
Regulatory Interactions ◽  
Gene Functions

Time-course single-cell RNA sequencing (scRNA-seq) data have been widely applied to reconstruct the cell-type-specific gene regulatory networks by exploring the dynamic changes of gene expression between transcription factors (TFs) and their target genes. The existing algorithms were commonly designed to analyze bulk gene expression data and could not deal with the dropouts and cell heterogeneity in scRNA-seq data. In this paper, we developed dynDeepDRIM that represents gene pair joint expression as images and considers the neighborhood context to eliminate the transitive interactions. dynDeepDRIM integrated the primary image, neighbor images with time-course into a four-dimensional tensor and trained a convolutional neural network to predict the direct regulatory interactions between TFs and genes. We evaluated the performance of dynDeepDRIM on five time-course gene expression datasets. dynDeepDRIM outperformed the state-of-the-art methods for predicting TF-gene direct interactions and gene functions. We also observed gene functions could be better performed if more neighbor images were involved.

scholarly journals Stress responses upon starvation and exposure to bacteria in the antFormica exsecta

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6428 ◽  
Author(s):  
Dimitri Stucki ◽  
Dalial Freitak ◽  
Nick Bos ◽  
Liselotte Sundström
Keyword(s):  
Gene Expression ◽  
Escherichia Coli ◽  
Stress Responses ◽  
Nutritional State ◽  
Oral Exposure ◽  
Starvation Resistance ◽  
Immune Defenses ◽  
Trade Offs ◽  
Induced Changes ◽  
The Impact

Organisms are simultaneously exposed to multiple stresses, which requires regulation of the resistance to each stress. Starvation is one of the most severe stresses organisms encounter, yet nutritional state is also one of the most crucial conditions on which other stress resistances depend. Concomitantly, organisms often deploy lower immune defenses when deprived of resources. This indicates that the investment into starvation resistance and immune defenses is likely to be subject to trade-offs. Here, we investigated the impact of starvation and oral exposure to bacteria on survival and gene expression in the antFormica exsecta. Of the three bacteria used in this study, onlySerratia marcescensincreased the mortality of the ants, whereas exposure toEscherichia coliandPseudomonas entomophilaalleviated the effects of starvation. Both exposure to bacteria and starvation induced changes in gene expression, but in different directions depending on the species of bacteria used, as well as on the nutritional state of the ants.

Genetically Engineered Mice: Tools To Understand Craniofacial Development

1995 ◽  
Vol 6 (3) ◽  
pp. 181-201 ◽  
Author(s):  
Michael A. Ignelzi ◽  
Yi-Hsin Liu ◽  
Robert E. Maxson ◽  
Malcolm L. Snead
Keyword(s):  
Gene Expression ◽  
Mouse Model ◽  
Craniofacial Development ◽  
Genetically Engineered ◽  
Specific Gene ◽  
Regulatory Interactions ◽  
Genetically Engineered Mice ◽  
Experimental Approaches ◽  
Insight Into ◽  
Craniofacial Complex

In this review, we provide a survey of the experimental approaches used to generate genetically engineered mice. Two specific examples are presented that demonstrate the applicability of these approaches to craniofacial development. In the first, a promoter analysis of the Msx2 gene is presented which illustrates the cis regulatory interactions that define cell-specific gene expression. In the second, a mouse model of the human disease craniosynostosis, Boston type, has been created by misregulation of the Msx2 gene product. Finally, we present a formulary of spontaneously occurring and genetically engineered mice that exhibit defects in developmental processes affecting the craniofacial complex. The purpose of this review is to provide insight into the experimental approaches that are used to create genetically engineered mice and to impress upon the reader that genetically engineered mice are well-suited to address fundamental questions pertaining to the development, maintenance, and regeneration of tissues and organs.

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