Transcriptomic analysis identifies key genes associated with nutrient deprivation responses in infectious bursal disease virus infection

Infectious bursal disease virus (IBDV) causes a highly contagious and immunosuppressive disease that severely impacts the poultry industry. However, the molecular basis of IBDV-induced immunosuppression remains poorly understood. In this study, we investigate key genes implicated in this process, focusing on the interplay between metabolism and immune regulation. IBDV infection enhanced glucose and glutamine uptake in HD11 cells. Transcriptome analysis across glucose-starved, amino acid-starved, IBDV-infected, and control groups identified key differentially expressed genes (DEGs) linked to immune and metabolic pathways. Specifically, 612 DEGs were associated with glucose starvation, 998 with amino acid starvation, and 496 shared between both conditions. Enrichment analysis revealed involvement in cytokine signalling, amino acid biosynthesis, and antiviral responses. qPCR validated ENO2 and MAT1A expression changes, and a regulatory network analysis highlighted their potential roles in nutrient stress and IBDV pathogenesis. This study presents a novel strategy to identify genes involved in nutrient deprivation during IBDV infection, highlighting ENO2 and MAT1A as key contributors to immune cell dysfunction.

Authors

Institutions

Publication Details

Journal
BMC Genomics
Published
2025-08-16
DOI
https://doi.org/10.1186/s12864-025-11918-x
Primary Topic
Virology and Viral Diseases
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Transcriptomic analysis identifies key genes associated with nutrient deprivation responses in infectious bursal disease virus infection

Zongping Liu, Qiangzhou Wang, Shihao Chen, Xuan Huang et al.
BMC Genomics
Virology and Viral Diseases
article

Transcriptomic analysis identifies key genes associated with nutrient deprivation responses in infectious bursal disease virus infection

Zongping Liu, Qiangzhou Wang, Shihao Chen, Xuan Huang, Hao Bai, Guobin Chang, Jiaxing Wang, Yuyu Ping, Ting Yang
article en

Abstract

Infectious bursal disease virus (IBDV) causes a highly contagious and immunosuppressive disease that severely impacts the poultry industry. However, the molecular basis of IBDV-induced immunosuppression remains poorly understood. In this study, we investigate key genes implicated in this process, focusing on the interplay between metabolism and immune regulation. IBDV infection enhanced glucose and glutamine uptake in HD11 cells. Transcriptome analysis across glucose-starved, amino acid-starved, IBDV-infected, and control groups identified key differentially expressed genes (DEGs) linked to immune and metabolic pathways. Specifically, 612 DEGs were associated with glucose starvation, 998 with amino acid starvation, and 496 shared between both conditions. Enrichment analysis revealed involvement in cytokine signalling, amino acid biosynthesis, and antiviral responses. qPCR validated ENO2 and MAT1A expression changes, and a regulatory network analysis highlighted their potential roles in nutrient stress and IBDV pathogenesis. This study presents a novel strategy to identify genes involved in nutrient deprivation during IBDV infection, highlighting ENO2 and MAT1A as key contributors to immune cell dysfunction.

BMC GenomicsVol. 26(1)
Ministry of Education (MV), Yangzhou University (CN)
Government of Jiangsu Province, Yangzhou University, National Key Research and Development Program of China
Zero hunger
Openalex Percentile: Top 71%
Virology and Viral Diseases
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.