Computational Molecular Biology 2025, Vol.15, No.6, 282-290 http://bioscipublisher.com/index.php/cmb 282 Research Insight Open Access Computational Modeling of Metabolic Networks in Rice Under Salt Stress Xingzhu Feng Hainan Institute of Biotechnology, Haikou, 570206, Hainan, China Corresponding author: zhongqi.wu@jicat.org Computational Molecular Biology, 2025, Vol.15, No.6 doi: 10.5376/cmb.2025.15.0028 Received: 30 Sep., 2025 Accepted: 10 Nov., 2025 Published: 29 Nov., 2025 Copyright © 2025 Feng, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Feng X.Z., 2025, Computational modeling of metabolic networks in rice under salt stress, Computational Molecular Biology, 15(6): 282-290 (doi: 10.5376/cmb.2025.15.0028) Abstract Salt stress is one of the main abiotic stresses affecting the growth and yield of rice, and it can significantly disrupt the ionic homeostasis and metabolic activities within cells. A thorough understanding of the metabolic regulation mechanism of rice under salt stress is of great significance for enhancing the salt tolerance of crops and achieving precise breeding. This study reviews the typical physiological and metabolic responses of rice to salt stress, including osmotic regulation, ion balance mechanisms, antioxidant metabolism, and dynamic reprogramming of primary and secondary metabolism. Based on metabolic network modeling methods such as flux balance analysis (FBA), combined with transcriptome and metabolome data, a specific metabolic model under salt stress conditions was constructed. And network mapping and throughput estimation are carried out by using databases such as KEGG and MetaCyc, as well as tools like COBRA and CellDesigner. In the case analysis, this study focused on the simulation and functional verification of central carbon metabolism and amino acid metabolism (such as proline and GABA), revealing the modular reconstruction process of the metabolic network under stress, identifying key nodes and restricted pathways, and predicting possible metabolic engineering modification strategies. This study provides a systems biology perspective for analyzing the metabolic regulation of rice under adverse conditions, and at the same time offers theoretical basis and computational support for the molecular design of salt-tolerant varieties. Keywords Rice; Salt stress; Metabolic network; Computational modeling; Flux balance analysis 1 Introduction Not all abiotic stresses are as troublesome as salt stress, especially for rice (Oryza sativa L.). The high-salt environment in coastal and saline-alkali areas often leads to a sharp decline in yield. Ion imbalance is just the beginning; the subsequent changes in osmotic pressure and oxidative pressure are even more difficult to deal with. Sometimes, a sudden drop in photosynthetic efficiency or a slower absorption of nutrients by the root system may also be related to these factors (Luo et al., 2024). Inside the cells, the metabolic network also has to be adjusted accordingly. Amino acids, sugars, organic acids, and even some secondary metabolites start to be redistributed, most of which come into play to combat water loss or eliminate free radicals. In fact, there is a considerable difference in the accumulation of such metabolites between salt-tolerant varieties and sensitive varieties, and the gene expression patterns are also different. All these indicate from the side that metabolic regulation is indeed involved in the salt-tolerant process (Kong et al., 2019; Rajkumari et al., 2023; Deng et al., 2025). However, when looking at the data, sometimes it can be quite confusing. The transcriptome and metabolome can each be seen in parts, but they tell fragmented stories. To "piece together" all this information, relying solely on data from a single dimension is often insufficient. This is also why people are increasingly beginning to use metabolic network models to string together these scattered pieces of information. By simulating the flux distribution and tracking how molecules "move", you can see which pathways become particularly active under salt stress, such as photosynthesis, the respiratory chain, antioxidant pathways, and sometimes even hormone metabolism. Such modeling results repeatedly remind us that some metabolic nodes are frequent "alerts", indicating that they play a key role in salt responses (Wanichthanarak et al., 2020). This study will construct and apply a metabolic network model of rice under salt stress to reveal its systematic metabolic adaptation mechanism, identify potential targets for improving salt tolerance, review the relevant background and modeling methods, introduce model construction and validation, analyze metabolic responses,
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