Investigating Mitochondrial Gene Expression Patterns in Drosophila melanogaster Using Network Analysis to Understand Aging Mechanisms

被引:2
作者
Mangoni, Manuel [1 ,2 ]
Petrizzelli, Francesco [1 ]
Liorni, Niccolo [1 ,2 ]
Bianco, Salvatore Daniele [1 ,2 ]
Biagini, Tommaso [1 ]
Napoli, Alessandro [1 ]
Adinolfi, Marta [1 ]
Guzzi, Pietro Hiram [3 ]
Novelli, Antonio [4 ]
Caputo, Viviana [2 ]
Mazza, Tommaso [1 ]
机构
[1] Fdn IRCCS Casa Sollievo Sofferenza, Bioinformat Lab, I-71013 San Giovanni Rotondo, Italy
[2] Sapienza Univ Rome, Dept Expt Med, I-00161 Rome, Italy
[3] Magna Graecia Univ Catanzaro, Dept Surg & Med Sci, I-88100 Catanzaro, Italy
[4] Bambino Gesu Pediat Hosp, Med Genet Lab, I-00146 Rome, Italy
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 12期
关键词
Drosophila melanogaster; network analysis; mitochondrial DNA; aging; LIFE-SPAN; COMPLEXITY; PATHWAYS; MODEL;
D O I
10.3390/app13127342
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The process of aging is a complex phenomenon that involves a progressive decline in physiological functions required for survival and fertility. To better understand the mechanisms underlying this process, the scientific community has utilized several tools. Among them, mitochondrial DNA has emerged as a crucial factor in biological aging, given that mitochondrial dysfunction is thought to significantly contribute to this phenomenon. Additionally, Drosophila melanogaster has proven to be a valuable model organism for studying aging due to its low cost, capacity to generate large populations, and ease of genetic manipulation and tissue dissection. Moreover, graph theory has been employed to understand the dynamic changes in gene expression patterns associated with aging and to investigate the interactions between aging and aging-related diseases. In this study, we have integrated these approaches to examine the patterns of gene co-expression in Drosophila melanogaster at various stages of development. By applying graph-theory techniques, we have identified modules of co-expressing genes, highlighting those that contain a significantly high number of mitochondrial genes. We found important mitochondrial genes involved in aging and age-related diseases in Drosophila melanogaster, including UQCR-C1, ND-B17.2, ND-20, and Pdhb. Our findings shed light on the role of mitochondrial genes in the aging process and demonstrate the utility of Drosophila melanogaster as a model organism and graph theory in aging research.
引用
收藏
页数:15
相关论文
共 46 条
  • [41] Metabolic Flux Analysis of Embryonic Stem Cells Using Three Distinct Differentiation Protocols and Comparison to Gene Expression Patterns
    Sepulveda, Dario E.
    Andrews, Barbara A.
    Papoutsakis, Eleftherios Terry
    Asenjo, Juan A.
    BIOTECHNOLOGY PROGRESS, 2010, 26 (05) : 1222 - 1229
  • [42] Gene co-expression network analysis reveals mechanisms underlying ozone-induced carbamazepine toxicity in zebrafish (Danio rerio) embryos
    Pohl, Johannes
    Golovko, Oksana
    Carlsson, Gunnar
    Orn, Stefan
    Schmitz, Monika
    Ahi, Ehsan Pashay
    CHEMOSPHERE, 2021, 276
  • [43] Identifying the potential role of IL-1β in the molecular mechanisms of disc degeneration using gene expression profiling and bioinformatics analysis
    Fan, Ning
    Yuan, Shuo
    Hai, Yong
    Du, Peng
    Li, Jian
    Kong, Xiaochuan
    Zhu, Wenyi
    Liu, Yuzeng
    Zang, Lei
    JOURNAL OF ORTHOPAEDIC SURGERY, 2022, 30 (01)
  • [44] The Identification and Validation of Hub Genes Associated with Acute Myocardial Infarction Using Weighted Gene Co-Expression Network Analysis
    Xue, Junqiang
    Chen, Lu
    Cheng, Hao
    Song, Xiaoyue
    Shi, Yuekai
    Li, Linnan
    Xu, Rende
    Qin, Qing
    Ma, Jianying
    Ge, Junbo
    JOURNAL OF CARDIOVASCULAR DEVELOPMENT AND DISEASE, 2022, 9 (01)
  • [45] Incorporating prior biological knowledge for network-based differential gene expression analysis using differentially weighted graphical LASSO
    Zuo, Yiming
    Cui, Yi
    Yu, Guoqiang
    Li, Ruijiang
    Ressom, Habtom W.
    BMC BIOINFORMATICS, 2017, 18
  • [46] Gene regulatory network analysis identifies key genes and regulatory mechanisms involved in acute myocardial infarction using bulk and single cell RNA-seq data
    Luo, Jiaxin
    Wu, Lin
    Liu, Dinghui
    Xiong, Zhaojun
    Wang, Linli
    Qian, Xiaoxian
    Sun, Xiaoqiang
    MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2021, 18 (06) : 7774 - 7789