Bioscience Evidence 2024, Vol.14, No.2, 44-55 http://bioscipublisher.com/index.php/be 51 Figure 4 Effects of cell-free supernatants (CFSs) of bacteria on the growth of R. solani AG8 (Adopted from Yin et al., 2022) Image caption: CK: AG8 only; CK1: ddH2O; B5: CFSs of Pseudomonas sp. B5; B6: CFSs of Streptomyces sp. B6; B7: CFSs of Chryseobacteriumsp. B7; B11: CFSs of Pseudomonas sp. B11; B12: CFSs of Pseudomonas sp. B12; B17: CFSs of Sphingomonas sp. B17; B20: CFSs of Cupriavidus campinensis B20; B27: CFSs of Asticcacaulis sp. B27; B43: CFSs of Rhodococcus erythropolis B43; BJ: CFSs of Janthinobacterium lividumBJ; P25: CFSs of Pseudomonas sp. P25; P38: CFSs of Chryseobacterium soldanellicola P38; P43: CFSs of Chryseobacteriumsp. P43; P44: CFSs of Pedobacter sp. P44; C1: CFSs of SynCom 1; C2: CFSs of SynCom 2; C3: CFSs of SynCom 3; C4: CFSs of SynCom 4; C5: CFSs of SynCom 5; C6: CFSs of SynCom 6; C7: CFSs of SynCom 7; C8: CFSs of SynCom 8; C9: CFSs of SynCom 9; C10: CFSs of SynCom 10 (Adopted from Yin et al., 2022) 6.3 Limitations and areas for improvement Despite the promising outcomes, there are several limitations and areas for improvement in the application of SynComs for climate-resilient agriculture. One major limitation is that SynComs were not more effective than single strains in some cases, such as in the reduction of wheat root rot disease (Yin et al., 2022). This suggests that further research is needed to understand the interactions between different microbial strains and their collective impact on plant health. Additionally, while computational methods have advanced the design of SynComs, there is still a need for more robust and comprehensive models that can accurately predict the best microbial combinations for various crops and environmental conditions (Souza et al., 2020). Future research should focus on refining these models and exploring the synergistic effects of different microbial strains to enhance the overall efficacy of SynComs in field applications. 7 Challenges and Limitations 7.1 Technical challenges in engineering and deploying SynComs Engineering and deploying synthetic microbial communities (SynComs) for agricultural applications face several technical challenges. One significant issue is the reproducibility of SynComs in different field conditions. The performance of SynComs can vary widely due to differences in crops, soil types, and environmental conditions, which complicates their consistent application (Sai et al., 2022; Shayanthan et al., 2022). Additionally, the complexity of designing stable and effective SynComs that can robustly colonize and persist in the plant microbiome is a major hurdle (Song et al., 2024). Computational methods, including machine learning
RkJQdWJsaXNoZXIy MjQ4ODYzMg==