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Non-rhizobial endophytes (NREs) are active colonizers inhabiting the root nodules. Though their active role in the lentil agroecosystem is not well defined, here we observed that these NREs might promote the growth of lentils, modulate rhizospheric community structure and could be used as promising organisms for optimal use of rice fallow soil. NREs from root nodules of lentils were isolated and examined for plant growth-promoting traits, exopolysaccharide (EPS) and biofilm production, root metabolites, and the presence of nifH and nifK elements. The greenhouse experiment with the chosen NREs, i.e., Serratia plymuthica 33GS and Serratia sp. R6 significantly increased the germination rate, vigour index, development of nodules (in non-sterile soil) and fresh weight of nodules (33GS 94%, R6 61% growth) and length of the shoot (33GS 86%, R6 51.16%) as well as chlorophyll levels when compared to the uninoculated control. Scanning Electron Microscopy (SEM) revealed that both isolates could successfully colonize the roots and elicit root hair growth. The inoculation of the NREs resulted in specific changes in root exudation patterns. The plants with 33GS and R6 treatment significantly stimulated the exudation of triterpenes, fatty acids, and their methyl esters in comparison to the uninoculated plants, altering the rhizospheric microbial community structure. Proteobacteria dominated the rhizospheric microbiota in all the treatments. Treatment with 33GS or R6 also enhanced the relative abundance of other favourable microbes, including Rhizobium, Mesorhizobium, and Bradyrhizobium. The correlation network analysis of relative abundances resulted in numerous bacterial taxa, which were in cooperation with each other, having a possible role in plant growth promotion. The results indicate the significant role of NREs as plant growth promoters, which also includes their role in root exudation patterns, enhancement of soil nutrient status and modulation of rhizospheric microbiota, suggesting their prospects in sustainable, and bio-based agriculture.

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