Data-Mining Bioinformatics: Connecting Adenylate Transport and Metabolic Responses to Stress

• Published in: Trends in plant science 2018-11, Vol.23 (11), p.961-974
• Main Authors: da Fonseca-Pereira, Paula, Neri-Silva, Roberto, Cavalcanti, João Henrique F., Brito, Danielle S., Weber, Andreas P.M., Araújo, Wagner L., Nunes-Nesi, Adriano
• Format: Article
• Language: English
• Subjects: Adenine; Adenosine triphosphate; adenylate carriers; Bioinformatics; Chloroplasts; Data mining; Data processing; Energy metabolism; Environmental conditions; expression analysis; Gene expression; Metabolism; Mitochondria; Nucleotides; Organelles; Oxidative phosphorylation; Phosphorylation; Photophosphorylation; Plants (botany); Stress; stress response; systems biology; Transport
• ISSN: 1360-1385; 1878-4372
• DOI: 10.1016/j.tplants.2018.09.002

Adenine nucleotides are essential in countless processes within the cellular metabolism. In plants, ATP is mainly produced in chloroplasts and mitochondria through photophosphorylation and oxidative phosphorylation, respectively. Thus, efficient adenylate transport systems are required for intracellular energy partitioning between the cell organelles. Adenylate carriers present in different subcellular compartments have been previously identified and biochemically characterized in plants. Here, by using data-mining bioinformatics tools, we propose how, and to what extent, these carriers integrate energy metabolism within a plant cell under different environmental conditions. We demonstrate that the expression pattern of the corresponding genes is variable under different environmental conditions, suggesting that specific adenylate carriers have distinct and nonredundant functions in plants. ATP is mainly produced inside the chloroplast and mitochondrion, and efficient adenylate transport systems are required for intracellular energy partitioning. Several adenine nucleotides carriers have been identified and their biochemical functions determined. However, their physiological roles under optimal and suboptimal conditions remain poorly investigated and, thus, poorly understood. The large amount of publicly available transcriptomic data coupled with improvements in high-quality microarray data in databases has emerged together with myriad tools to identify candidate genes not previously associated with a given biological question. The in silico survey of the expression pattern of adenine nucleotide carriers demonstrated that their expression is variable under different conditions, suggesting that specific adenylate carriers have distinct and nonredundant functions.