scholarly journals Entangled gene regulatory networks with cooperative expression endow robust adaptive responses to unforeseen environmental changes

2020 ◽  
Author(s):  
Masayo Inoue ◽  
Kunihiko Kaneko

Living organisms must respond to environmental changes. Generally, accurate and rapid responses are provided by simple, unidirectional networks that connect inputs with outputs. Besides accuracy and speed, however, biological responses should also be robust to environmental or intracellular noise and mutations. Furthermore, cells must also respond to unforeseen environmental changes that have not previously been experienced, to avoid extinction prior to the evolutionary rewiring of their networks, which takes numerous generations. To address the question how cells can make robust adaptation even to unforeseen challenges, we have investigated gene regulatory networks that mutually activate or inhibit, and have demonstrated that complex entangled networks can make appropriate input-output relationships that satisfy such adaptive responses. Such entangled networks function when the expression of each gene shows sloppy and unreliable responses with low Hill coefficient reactions. To compensate for such sloppiness, several detours in the regulatory network exist. By taking advantage of the averaging over such detours, the network shows a higher robustness to environmental and intracellular noise as well as to mutations in the network, when compared to simple unidirectional circuits. Furthermore, it is demonstrated that the appropriate response to unforeseen environmental changes, allowing for functional outputs, is achieved as many genes exhibit similar dynamic expression responses, irrespective of inputs including unforeseen inputs. The similarity of the responses is statistically confirmed by applying dynamic time warping and dynamic mode decomposition methods. As complex entangled networks are commonly observed in the data in gene regulatory networks whereas global gene expression responses are measured in transcriptome analysis in microbial experiments, the present results give an answer how cells make adaptive responses and also provide a novel design principle for cellular networks.Author summaryRecent experimental advances have demonstrated that cells often have appropriate, robust responses to environmental changes, including those that have not previously been experienced. It is known that accurate and rapid responses can be achieved by simple unidirectional networks that connect straightforwardly input and outputs. However, such responses were not robust to perturbations. Here we have made numerical evolution of gene regulatory networks with mutual activation and inhibitions, and uncovered that complex entangled networks including many feedforward and feedback paths can make robust input-output responses, when each gene expression is not accurate. Remarkably, they make appropriate responses even to unforeseen environmental changes, as are supported by global, correlated responses across genes that are similar for all input signals. The results explain why cells adopt complex gene regulatory networks and exhibit global expression changes, even though they may not be advantageous in terms of their energy cost or response speed. The present results are consistent with the recent experiments on microbial gene expression changes and network analyses. This investigation provides insights into how cells survive fluctuating and unforeseen unpredictable environmental changes, and gives a universal conceptual framework to go beyond the standard picture based on a combination of network motifs.

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Mika J. Välimäki ◽  
Robert S. Leigh ◽  
Sini M. Kinnunen ◽  
Alexander R. March ◽  
Ana Hernández de Sande ◽  
...  

AbstractBackgroundPharmacological modulation of cell fate decisions and developmental gene regulatory networks holds promise for the treatment of heart failure. Compounds that target tissue-specific transcription factors could overcome non-specific effects of small molecules and lead to the regeneration of heart muscle following myocardial infarction. Due to cellular heterogeneity in the heart, the activation of gene programs representing specific atrial and ventricular cardiomyocyte subtypes would be highly desirable. Chemical compounds that modulate atrial and ventricular cell fate could be used to improve subtype-specific differentiation of endogenous or exogenously delivered progenitor cells in order to promote cardiac regeneration.MethodsTranscription factor GATA4-targeted compounds that have previously shown in vivo efficacy in cardiac injury models were tested for stage-specific activation of atrial and ventricular reporter genes in differentiating pluripotent stem cells using a dual reporter assay. Chemically induced gene expression changes were characterized by qRT-PCR, global run-on sequencing (GRO-seq) and immunoblotting, and the network of cooperative proteins of GATA4 and NKX2-5 were further explored by the examination of the GATA4 and NKX2-5 interactome by BioID. Reporter gene assays were conducted to examine combinatorial effects of GATA-targeted compounds and bromodomain and extraterminal domain (BET) inhibition on chamber-specific gene expression.ResultsGATA4-targeted compounds 3i-1000 and 3i-1103 were identified as differential modulators of atrial and ventricular gene expression. More detailed structure-function analysis revealed a distinct subclass of GATA4/NKX2-5 inhibitory compounds with an acetyl lysine-like domain that contributed to ventricular cells (%Myl2-eGFP+). Additionally, BioID analysis indicated broad interaction between GATA4 and BET family of proteins, such as BRD4. This indicated the involvement of epigenetic modulators in the regulation of GATA-dependent transcription. In this line, reporter gene assays with combinatorial treatment of 3i-1000 and the BET bromodomain inhibitor (+)-JQ1 demonstrated the cooperative role of GATA4 and BRD4 in the modulation of chamber-specific cardiac gene expression.ConclusionsCollectively, these results indicate the potential for therapeutic alteration of cell fate decisions and pathological gene regulatory networks by GATA4-targeted compounds modulating chamber-specific transcriptional programs in multipotent cardiac progenitor cells and cardiomyocytes. The compound scaffolds described within this study could be used to develop regenerative strategies for myocardial regeneration.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Neel Patel ◽  
William S. Bush

Abstract Background Transcriptional regulation is complex, requiring multiple cis (local) and trans acting mechanisms working in concert to drive gene expression, with disruption of these processes linked to multiple diseases. Previous computational attempts to understand the influence of regulatory mechanisms on gene expression have used prediction models containing input features derived from cis regulatory factors. However, local chromatin looping and trans-acting mechanisms are known to also influence transcriptional regulation, and their inclusion may improve model accuracy and interpretation. In this study, we create a general model of transcription factor influence on gene expression by incorporating both cis and trans gene regulatory features. Results We describe a computational framework to model gene expression for GM12878 and K562 cell lines. This framework weights the impact of transcription factor-based regulatory data using multi-omics gene regulatory networks to account for both cis and trans acting mechanisms, and measures of the local chromatin context. These prediction models perform significantly better compared to models containing cis-regulatory features alone. Models that additionally integrate long distance chromatin interactions (or chromatin looping) between distal transcription factor binding regions and gene promoters also show improved accuracy. As a demonstration of their utility, effect estimates from these models were used to weight cis-regulatory rare variants for sequence kernel association test analyses of gene expression. Conclusions Our models generate refined effect estimates for the influence of individual transcription factors on gene expression, allowing characterization of their roles across the genome. This work also provides a framework for integrating multiple data types into a single model of transcriptional regulation.


Sign in / Sign up

Export Citation Format

Share Document