Molecular Soil Biology 2025, Vol.16, No.1, 16-26 http://bioscipublisher.com/index.php/msb 18 2.2 Techniques for engineering SynComs The engineering of SynComs involves several advanced techniques, including synthetic biology, genetic modification, and metabolic modeling. Synthetic biology allows for the precise manipulation of microbial genomes to enhance their bioremediation capabilities. This can involve the insertion of new genes, the deletion of non-essential genes, or the modification of existing genes to optimize metabolic pathways (Sharma and Shukla, 2020). Genetic modification techniques, such as CRISPR-Cas9, enable targeted alterations in microbial DNA, facilitating the creation of strains with enhanced pollutant-degrading abilities (Sharma and Shukla, 2020). Metabolic modeling, particularly genome-scale metabolic models (GEMs), plays a crucial role in the design of SynComs. GEMs provide a mathematical representation of microbial metabolism, allowing researchers to simulate and predict the metabolic interactions within a community under various environmental conditions. This helps in the rational design of SynComs by identifying optimal combinations of microbial strains that can work synergistically to degrade pollutants (Wang et al., 2023). Additionally, in silico tools and databases are used to analyze experimental data and predict the behavior of SynComs, further aiding in their design and optimization (Sharma and Shukla, 2020; Wang et al., 2023). 2.3 Advantages of SynComs over natural microbial communities for bioremediation SynComs offer several advantages over natural microbial communities for bioremediation. Firstly, they can be tailored to target specific pollutants, making them more efficient in degrading contaminants compared to natural communities, which may not possess the necessary metabolic pathways (Sharma and Shukla, 2020). Secondly, SynComs can be designed to function under a wide range of environmental conditions, including extreme environments such as saline-alkali soils, where natural microbial communities may struggle to survive and function effectively (Shi et al., 2019; Sharma and Shukla, 2020). Moreover, SynComs can be engineered to have enhanced stability and resilience, ensuring consistent performance in bioremediation applications. This is achieved by selecting microbial strains that can withstand environmental stresses and by engineering metabolic pathways that are robust to fluctuations in environmental conditions (Sharma and Shukla, 2020; Wang et al., 2023). Additionally, the use of SynComs allows for the combination of multiple microbial strains with complementary metabolic capabilities, enabling the simultaneous degradation of a wide range of pollutants, which is often not possible with natural microbial communities (Sharma and Shukla, 2020). 3 Mechanisms of SynComs in Bioremediation 3.1 Biological pathways involved in the degradation and neutralization of soil salinity and alkalinity Synthetic microbial communities (SynComs) play a crucial role in the bioremediation of saline-alkali soils through various biological pathways. These pathways include the degradation of pollutants and the neutralization of soil salinity and alkalinity. For instance, microbial biofilm formation and the production of secondary metabolites are essential traits that enhance the stability and functionality of SynComs under environmental stressors (Martins et al., 2023). Additionally, halophilic bacteria, arbuscular mycorrhizal fungi, and plant growth-promoting rhizobacteria have been documented to promote plant growth under salt-stress conditions by maintaining and enhancing soil health (Table 1) (Kumawat et al., 2022). The microbial degradation of hydrocarbons in saline soils, facilitated by salinity-tolerant hydrocarbon-degrading bacteria, further exemplifies the potential of SynComs in bioremediation (Ebadi et al., 2018). 3.2 Genetic engineering approaches to enhance SynCom efficiency Genetic engineering approaches are pivotal in enhancing the efficiency of SynComs for bioremediation. Systems biology tools help identify new genes, proteins, and metabolic pathways involved in bioremediation, which can be used to design SynComs capable of degrading multiple recalcitrant pollutants simultaneously (Sharma and Shukla, 2020). Computational methods, including machine learning and artificial intelligence, are employed to screen and identify beneficial microbes, improving the process of determining the best combination of microbes for a desired plant phenotype (Souza et al., 2020). These approaches enable the creation of SynComs with robust colonization traits and specific beneficial functions, thereby enhancing crop resiliency against stressful conditions (Souza et al., 2020; Marín et al., 2021).
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