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PubMed · 42748794

Long-term saline-alkaline selection rewires the growth-survival trade-off in Priestia megaterium.

Abstract

Saline-alkaline soils impose persistent osmotic, ionic, pH, and nutrient stress on soil microorganisms, but the evolutionary routes by which beneficial bacteria adapt to such conditions remain poorly resolved. We performed adaptive laboratory evolution to examine the adaption of the plant growth-promoting rhizobacterium Priestia megaterium HA22 to long-term oligotrophic saline-alkaline selection. After 175 serial transfers, the evolved lineage proliferated stably at 40 g L-1 Na2SO4 at pH 10.0, whereas the wild-type strain failed to proliferate. Genome resequencing and allelic replacement revealed a 5-bp insertion in spo0A, the master sporulation regulator, as a major adaptive mutation. This mutation abolished sporulation; shortened the lag phase; and enhanced vegetative growth, nutrient uptake, and expression of tricarboxylic acid cycle and nitrogen metabolism gene under saline-alkaline stress. According to untargeted metabolomics, adaptation was accompanied by increased amino acid metabolism and aminoacyl-tRNA biosynthesis, with proline, isoleucine and pantothenic acid functionally promoting growth. A point mutation in ugpB enhanced glycerol-3-phosphate uptake, increased peptidoglycan and wall teichoic acid levels, and partially rescued the survival cost of the spo0A mutation. In greenhouse assays under combined saline-alkaline stress, the evolved strain increased soybean shoot dry weight and root dry weight by 56.08% and 27.02%, respectively. These results indicate that prolonged, predictable saline-alkaline selection can favor active growth rather than dormancy when compensatory cell envelope reinforcement buffers survival costs.

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BibTeXRIS

Luming Ma, Liang Liu, Dongmei Li, Hongwen Zhao, Chunting Zhang, Jinshui Yang, Hongli Yuan. 2026-09-14. Long-term saline-alkaline selection rewires the growth-survival trade-off in Priestia megaterium.. https://doi.org/10.1016/j.micres.2026.128707

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Adaptive laboratory evolution