Bulk RNAseq Analysis of Cardiac Myosin-Specific CD4+ and CD8+ T Cells Reveals Distinct Transcriptomic Profiles Between Myocarditis-Resistant and Susceptible Mice

<b>Background</b>: We recently generated T cell receptor (TCR) transgenic (Tg) mice specific to cardiac myosin heavy chain-α (Myhc-α 334-352) on both myocarditis-resistant (C57BL/6) and susceptible (A/J) genetic backgrounds. We noted that the antigen-specific TCRs were expressed in CD4<sup>+</sup> and CD8<sup>+</sup> T cells in both strains, but their responses differed. While the T cells from naïve Tg C57BL/6 mice do not respond to Myhc-α 334-352, whereas those from A/J mice spontaneously respond to the antigen, suggesting their underlying molecular mechanisms might differ. <b>Methods</b>: To investigate the mechanisms of differences in the antigen-responsiveness between the Tg C57BL/6 and A/J mice, we performed bulk RNA sequencing on CD4⁺ and CD8⁺ T cells sorted by flow cytometry. Differentially expressed genes, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, gene set enrichment analysis (GSEA) of GO and KEGG, and transcription factor (TF) network analyses were performed to identify pathways and regulators of immune responses. <b>Results</b>: First, the principal component analysis of the transcriptomic profiles distinguished CD4<sup>+</sup> from CD8<sup>+</sup> T cells, which also differed between the two strains. Second, the differentially expressed cytokine and cytotoxicity genes revealed similar patterns between CD4<sup>+</sup> and CD8<sup>+</sup> T cells. Importantly, KEGG enrichment analysis revealed downregulated pathways in both CD4<sup>+</sup> and CD8<sup>+</sup> T cells that are associated with viral myocarditis, and various autoimmune conditions in C57BL/6 as compared to A/J mice. Similarly, the GSEA of GO revealed negative regulation of heart contraction and positive regulation of cardiac muscle hypertrophy processes were negatively enriched in CD4<sup>+</sup> T cells of C57BL/6 mice. Finally, by generating the transcription factor (TF) networks, 22 TFs were found common to both CD4<sup>+</sup> and CD8<sup>+</sup> T cells, whereas eight TFs were unique to CD4<sup>+</sup> or CD8<sup>+</sup> T cells that have a role in T cell activation, tolerance, and T regulatory cells. <b>Conclusions</b>: Our data provide new insights into the transcriptomic profiles that may contribute to the genetic resistance mechanisms for developing cardiac autoimmunity.

Authors

Institutions

Publication Details

Journal
Biomedicines
Published
2025-11-06
DOI
https://doi.org/10.3390/biomedicines13112725
Primary Topic
Viral Infections and Immunology Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bulk RNAseq Analysis of Cardiac Myosin-Specific CD4+ and CD8+ T Cells Reveals Distinct Transcriptomic Profiles Between Myocarditis-Resistant and Susceptible Mice

Kiruthiga Mone, Shraddha Singh, Meghna Sur, Jay Reddy et al.
Biomedicines
Viral Infections and Immunology Research
article

Bulk RNAseq Analysis of Cardiac Myosin-Specific CD4+ and CD8+ T Cells Reveals Distinct Transcriptomic Profiles Between Myocarditis-Resistant and Susceptible Mice

Kiruthiga Mone, Shraddha Singh, Meghna Sur, Jay Reddy, Arunakumar Gangaplara, Chandirasegaran Massilamany, Celia Wafa Ayad
article en

Abstract

<b>Background</b>: We recently generated T cell receptor (TCR) transgenic (Tg) mice specific to cardiac myosin heavy chain-α (Myhc-α 334-352) on both myocarditis-resistant (C57BL/6) and susceptible (A/J) genetic backgrounds. We noted that the antigen-specific TCRs were expressed in CD4<sup>+</sup> and CD8<sup>+</sup> T cells in both strains, but their responses differed. While the T cells from naïve Tg C57BL/6 mice do not respond to Myhc-α 334-352, whereas those from A/J mice spontaneously respond to the antigen, suggesting their underlying molecular mechanisms might differ. <b>Methods</b>: To investigate the mechanisms of differences in the antigen-responsiveness between the Tg C57BL/6 and A/J mice, we performed bulk RNA sequencing on CD4⁺ and CD8⁺ T cells sorted by flow cytometry. Differentially expressed genes, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, gene set enrichment analysis (GSEA) of GO and KEGG, and transcription factor (TF) network analyses were performed to identify pathways and regulators of immune responses. <b>Results</b>: First, the principal component analysis of the transcriptomic profiles distinguished CD4<sup>+</sup> from CD8<sup>+</sup> T cells, which also differed between the two strains. Second, the differentially expressed cytokine and cytotoxicity genes revealed similar patterns between CD4<sup>+</sup> and CD8<sup>+</sup> T cells. Importantly, KEGG enrichment analysis revealed downregulated pathways in both CD4<sup>+</sup> and CD8<sup>+</sup> T cells that are associated with viral myocarditis, and various autoimmune conditions in C57BL/6 as compared to A/J mice. Similarly, the GSEA of GO revealed negative regulation of heart contraction and positive regulation of cardiac muscle hypertrophy processes were negatively enriched in CD4<sup>+</sup> T cells of C57BL/6 mice. Finally, by generating the transcription factor (TF) networks, 22 TFs were found common to both CD4<sup>+</sup> and CD8<sup>+</sup> T cells, whereas eight TFs were unique to CD4<sup>+</sup> or CD8<sup>+</sup> T cells that have a role in T cell activation, tolerance, and T regulatory cells. <b>Conclusions</b>: Our data provide new insights into the transcriptomic profiles that may contribute to the genetic resistance mechanisms for developing cardiac autoimmunity.

BiomedicinesVol. 13(11)
University of Nebraska–Lincoln (US), City Of Hope National Medical Center (US), Beth Israel Deaconess Medical Center (US), City of Hope (US), Lentigen Technology (United States) (US), Stealth BioTherapeutics (United States) (US)
Openalex Percentile: Top 50%
Viral Infections and Immunology Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.