9 research outputs found
Structural movements of RIG1 and MDA5 receptors during MD simulation.
<p>Porcupine plots showing structural movements of (A) RIG1 and (B) MDA5 receptors during MD simulations. The structural movements are shown for both RNA-bound and free proteins. The docked dsRNA molecule has been colored in violet color. Arrow heads indicate direction of motion and length of the arrows specifies the extent of displacement. The figure also shows the schematic representation of intermolecular interactions (C) RIG1 and (D) MDA5 with dsRNA after MD simulations.</p
Insight into Buffalo (<i>Bubalus bubalis</i>) RIG1 and MDA5 Receptors: A Comparative Study on dsRNA Recognition and <i>In-Vitro</i> Antiviral Response
<div><p>RIG1 and MDA5 have emerged as important intracellular innate pattern recognition receptors that recognize viral RNA and mediate cellular signals controlling Type I interferon (IFN-I) response. Buffalo RIG1 and MDA5 genes were investigated to understand the mechanism of receptor induced antiviral response. Sequence analysis revealed that RIG1 and MDA5 maintain a domain arrangement that is common in mammals. Critical binding site residues of the receptors are evolutionary conserved among mammals. Molecular dynamics simulations suggested that RIG1 and MDA5 follow a similar, if not identical, dsRNA binding pattern that has been previously reported in human. Moreover, binding free energy calculation revealed that MDA5 had a greater affinity towards dsRNA compared to RIG1. Constitutive expressions of RLR genes were ubiquitous in different tissues without being specific to immune organs. Poly I:C stimulation induced elevated expressions of IFN-β and IFN-stimulated genes (ISGs) through interferon regulatory factors (IRFs) mediated pathway in buffalo foetal fibroblast cells. The present study provides crucial insights into the structure and function of RIG1 and MDA5 receptors in buffalo.</p></div
Primers used for amplification of buffalo RIG1 and MDA5 genes.
<p>Primers used for amplification of buffalo RIG1 and MDA5 genes.</p
Constitutive protein expression levels of buffalo RIG1 and MDA5 in different tissues.
<p>Imuunohistochemical localization of RIG1 and MDA5 were detected in thin tissue sections using specific antibodies with DAB (3,3′-Diaminobenzidine) as substrate. Counterstaining was performed with Mayer’s haematoxylin.</p
Primers used for mRNA quantitation of different genes by Real time PCR (qRT-PCR).
<p>Primers used for mRNA quantitation of different genes by Real time PCR (qRT-PCR).</p
MM/PBSA binding free energies (kJ/mol) of RIG1/dsRNA and MDA5/dsRNA complexes.
<p>*Standard errors are indicated in parenthesis.</p><p>ΔG<sub>coul</sub> = Electrostatic energy.</p><p>ΔG<sub>ps</sub> = Polar solvation energy.</p><p>ΔG<sub>polar</sub> = Polar contribution (ΔG<sub>coul</sub>+ΔG<sub>ps</sub>).</p><p>ΔG<sub>vdW</sub> = van der Waals energy.</p><p>ΔG<sub>nps</sub> = Nonpolar solvation energy.</p><p>ΔG<sub>nonpolar</sub> = Nonpolar contribution (ΔG<sub>nps</sub>+ΔG<sub>vdW</sub>).</p><p>ΔG<sub>bind</sub> = Overall binding energy.</p
Poly I:C induced expression levels of IFN-β and ISGs in buffalo foetal fibroblast cells over different time intervals.
<p>Relative fold change in mRNA of (A) IFN-β (B) ISG15 (C) ISG54 and (D) ISG56 over control has been shown.</p
Constitutive mRNA expression levels of buffalo RLR (<i>RIG1, MDA5</i> and <i>LGP2</i>) genes in different tissues.
<p>Relative abundance of mRNA was measured by qRT-PCR using <i>RPS-18</i> as housekeeping control.</p
Amino acid sequence analysis of RIG1 and MDA5 receptors.
<p>(A) Sequence comparison of functional domains and binding residues of RIG1 and MDA5. Multiple sequence alignment was performed by MAFFT web server and binding site residues (highlighted) were identified by DELTA-BLAST and CDD database of NCBI. (B) The evolutionary history was inferred by using the Maximum Likelihood method of MEGA5 based on the JTT matrix-based model. The trees with the highest log likelihood are shown. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using a JTT model, and then selecting the topology with superior log likelihood value. Sequences used for analysis are provided in Table S2 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089788#pone.0089788.s001" target="_blank">File S1</a>.</p