scholarly journals A Persistence Detector for Metabolic Network Rewiring in an Animal

2018 ◽  
Author(s):  
Jote T. Bulcha ◽  
Gabrielle E. Giese ◽  
Md. Zulfikar Ali ◽  
Yong-Uk Lee ◽  
Melissa D. Walker ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Logic Gates ◽  
Environmental Signals ◽  
Shunt Pathway ◽  
E Coli ◽  
Gene Regulatory ◽  
Multicellular Organisms ◽  
Network Rewiring ◽  
Target Activation

ABSTRACTBiological systems must possess mechanisms that prevent inappropriate responses to spurious environmental signals. Gene regulatory network circuitries known as coherent type 1 feed-forward loops (FFLs) with AND-logic gates have been proposed to function as a persistence detector because it generates a delay in target activation and prevents target induction unless the input signal is sustained. While such a circuit has been found for the L-arabinose utilization system in E. coli, their existence and relevance multicellular organisms has remained unclear. Here, we identify the first persistence detector in an animal that redirects propionate breakdown to a shunt pathway when flux through the canonical propionate breakdown pathway is perturbed. We propose that this mechanism has evolved to ensure the shunt pathway stays off unless propionate accumulation is persistent because the shunt pathway generates highly toxic acrylate. Our study uniquely connects persistence detector circuitry to a physiological response in an animal.

scholarly journals Developmental transcriptomics of the brittle star Amphiura filiformis reveals gene regulatory network rewiring in echinoderm larval skeleton evolution

2017 ◽  
Author(s):  
David Dylus ◽  
Liisa M. Blowes ◽  
Anna Czarkwiani ◽  
Maurice R. Elphick ◽  
Paola Oliveri
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
De Novo ◽  
Sea Urchins ◽  
Brittle Star ◽  
Stages Of Development ◽  
Sequence Alignments ◽  
Amphiura Filiformis ◽  
Gene Regulatory ◽  
Network Rewiring

ABSTRACTAmongst the echinoderms the class Ophiuroidea is of particular interest for its phylogenetic position, ecological importance, developmental and regenerative biology. However, compared to other echinoderms, notably echinoids (sea urchins), relatively little is known about developmental changes in gene expression in ophiuroids. To address this issue we have generated and assembled a large RNAseq data set of four key stages of development in the brittle star Amphiura filiformis and a de novo reference transcriptome of comparable quality to that of a model echinoderm - the sea urchin Strongyloncentrotus purpuratus. Furthermore, we provide access to the new data via a web interface: http://www.echinonet.eu/shiny/Amphiura_filiformis/. With a focus on skeleton development, we have identified highly conserved genes associated with the development of a biomineralized skeleton. We also identify important class-specific characters, including the independent duplication of the msp130 class of genes in different echinoderm classes and the unique occurrence of spicule matrix (sm) genes in echinoids. Using a new quantification pipeline for our de novo transcriptome, validated with other methodologies, we find major differences between brittle stars and sea urchins in the temporal expression of many transcription factor genes. This divergence in developmental regulatory states is more evident in early stages of development when cell specification begins, than when cells initiate differentiation. Our findings indicate that there has been a high degree of gene regulatory network rewiring in the evolution of echinoderm larval development.Data DepositionsAll sequence reads are available at Genbank SRR4436669 - SRR4436674. Any sequence alignments used are available by the corresponding author upon request.

scholarly journals A simple test to infer mode of selection in metagenomics time series of evolving asexual populations

2020 ◽  
Author(s):  
Rohan Maddamsetti ◽  
Nkrumah A. Grant
Keyword(s):  
Time Series ◽  
Positive Selection ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Fine Tuning ◽  
Simple Test ◽  
Regulatory Regions ◽  
E Coli ◽  
Gene Regulatory ◽  
Asexual Populations

ABSTRACTWe introduce a simple test to infer mode of selection (STIMS) in metagenomic time series of evolving asexual populations. STIMS compares the tempo of molecular evolution for a gene set of interest against a null distribution that is bootstrapped on random gene sets. We test STIMS on metagenomic data spanning 62,750 generations of Lenski’s long-term evolution experiment with E. coli (LTEE). Our method successfully recovers signals of purifying selection and positive selection on gold standard sets of genes. We then use STIMS to study the evolution of genetic modules in the LTEE. We find strong evidence of ongoing positive selection on key regulators of the E. coli gene regulatory network. Key regulatory genes show evidence of positive selection over the entire time series, even in some hypermutator populations. By contrast, we found no signal of selection on the genetic modules that show the strongest transcriptional responses to changes in growth conditions. In addition, the cis-regulatory regions of key regulators are evolving faster than the cis-regulatory regions of their downstream regulatory targets. These results indicate that one mechanistic cause for ongoing fitness gains in the LTEE is ongoing fine-tuning of the gene regulatory network.

scholarly journals Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis

2021 ◽  
Author(s):  
Basavaraj Mallikarjunayya Vastrad ◽  
Chanabasayya Mallikarjunayya Vastrad
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Ppi Network ◽  
Hub Genes ◽  
Hub Gene ◽  
Network Modules ◽  
Gene Regulatory

Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were then performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway. The top hub genes such as MYC, EGFR, LNX1, YBX1, HSP90AA1, ESR1, FN1, TK1, ANLN and SMAD9 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Receiver operating characteristic curve (ROC) analysis and RT-PCR confirmed that these genes were significantly associated with T1DM. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the advancement and progression of T1DM, and certain genes might be used as candidate target molecules to diagnose, monitor and treat T1DM.

scholarly journals Enterohaemorrhagic E. coli utilizes an AND-OR logic gate to regulate expression of an outer membrane haem receptor

2021 ◽  
Author(s):  
Brandon M Sy ◽  
Jai Justin Tree
Keyword(s):  
High Temperature ◽  
Transcription Initiation ◽  
Logic Gate ◽  
Logic Gates ◽  
Local Environment ◽  
Transcriptional Terminator ◽  
Environmental Signals ◽  
E Coli ◽  
Regulatory Circuit ◽  
Transcript Elongation

To sense the transition from environment to host, bacteria use a range of environmental cues to control expression of virulence genes. Iron is tightly sequestered in host tissues and in the human pathogen enterohaemorrhagic E. coli (EHEC) iron-limitation induces transcription of the outermembrane haem transporter encoded by chuAS. ChuA expression is post-transcriptionally activated at 37oC by a FourU RNA thermometer ensuring that the haem receptor is only expressed under low iron, high temperature conditions that indicate the host. Here we demonstrate that expression of chuA is also independently regulated by the cAMP-responsive sRNA CyaR and transcriptional terminator Rho. These results indicate that chuA expression is regulated at the transcription initiation, transcript elongation, and translational level. The natural dependence of these processes creates a hierarchy of regulatory AND and OR logic gates that integrate information about the local environment. We show that the logic of the chuA regulatory circuit is activated under conditions that satisfy low iron AND (low glucose OR high temperature). We speculate that additional sensing of a gluconeogenic environment allows further precision in determining when EHEC is at the gastrointestinal epithelium of the host. With previous studies, it appears that the chuA transcript is controlled by eight regulatory inputs that control expression through six different transcriptional and post-transcriptional mechanisms. The results highlight the ability of regulatory sRNAs to integrate multiple environmental signals into a conditional hierarchy of signal input.

scholarly journals Gene Regulatory Network Rewiring in the Immune Cells Associated with Cancer

Genes ◽  
2017 ◽  
Vol 8 (11) ◽  
pp. 308 ◽  
Author(s):  
Pengyong Han ◽  
Chandrasekhar Gopalakrishnan ◽  
Haiquan Yu ◽  
Edwin Wang
Keyword(s):  
Gene Regulatory Network ◽  
Immune Cells ◽  
Regulatory Network ◽  
Gene Regulatory ◽  
Network Rewiring

scholarly journals Exploring the effect of network topology, mRNA and protein dynamics on gene regulatory network stability

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yipei Guo ◽  
Ariel Amir
Keyword(s):  
Regulatory Network ◽  
Biological Network ◽  
Structural Features ◽  
Network Stability ◽  
Transcription Network ◽  
Factors Affecting ◽  
E Coli ◽  
Growing Cell ◽  
Gene Regulatory ◽  
Mrna Degradation Rate

AbstractHomeostasis of protein concentrations in cells is crucial for their proper functioning, requiring steady-state concentrations to be stable to fluctuations. Since gene expression is regulated by proteins such as transcription factors (TFs), the full set of proteins within the cell constitutes a large system of interacting components, which can become unstable. We explore factors affecting stability by coupling the dynamics of mRNAs and proteins in a growing cell. We find that mRNA degradation rate does not affect stability, contrary to previous claims. However, global structural features of the network can dramatically enhance stability. Importantly, a network resembling a bipartite graph with a lower fraction of interactions that target TFs has a higher chance of being stable. Scrambling the E. coli transcription network, we find that the biological network is significantly more stable than its randomized counterpart, suggesting that stability constraints may have shaped network structure during the course of evolution.

scholarly journals Intracellular and Intercellular Gene Regulatory Network Inference From Time-Course Individual RNA-Seq

2021 ◽  
Vol 1 ◽  
Author(s):  
Makoto Kashima ◽  
Yuki Shida ◽  
Takashi Yamashiro ◽  
Hiromi Hirata ◽  
Hiroshi Kurosaka
Keyword(s):  
Transcription Factors ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Time Course ◽  
Network Inference ◽  
Molecular Mechanisms ◽  
Rna Seq ◽  
Gene Regulatory Network Inference ◽  
Gene Regulatory ◽  
Multicellular Organisms

Gene regulatory network (GRN) inference is an effective approach to understand the molecular mechanisms underlying biological events. Generally, GRN inference mainly targets intracellular regulatory relationships such as transcription factors and their associated targets. In multicellular organisms, there are both intracellular and intercellular regulatory mechanisms. Thus, we hypothesize that GRNs inferred from time-course individual (whole embryo) RNA-Seq during development can reveal intercellular regulatory relationships (signaling pathways) underlying the development. Here, we conducted time-course bulk RNA-Seq of individual mouse embryos during early development, followed by pseudo-time analysis and GRN inference. The results demonstrated that GRN inference from RNA-Seq with pseudo-time can be applied for individual bulk RNA-Seq similar to scRNA-Seq. Validation using an experimental-source-based database showed that our approach could significantly infer GRN for all transcription factors in the database. Furthermore, the inferred ligand-related and receptor-related downstream genes were significantly overlapped. Thus, the inferred GRN based on whole organism could include intercellular regulatory relationships, which cannot be inferred from scRNA-Seq based only on gene expression data. Overall, inferring GRN from time-course bulk RNA-Seq is an effective approach to understand the regulatory relationships underlying biological events in multicellular organisms.

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