Back

Unusual Morphological Changes of Rugositalea oryzae, A Novel Wrinkled Bacterium Isolated from The Rice Rhizosphere, Under Nutrient Stress

Chung, Y. R.; Lee, J.-E.; Aslam, Z.; Chung, E. J.; Khan, A.; Lee, K. H.; Kang, B. H.; Niraula, S.; Chang, W.-S.

2022-08-30 microbiology
10.1101/2022.08.29.505124 bioRxiv
Show abstract

Bacterial cell morphology might result from natural selection to gain a competitive advantage under environmentally stressful conditions such as nutrient limitation. A bacterial strain YC6860T isolated from the rhizosphere of rice (Oryza sativa L.) showed pleomorphic behavior with smooth cell morphology and wrinkled surface rods depending upon nutritional conditions. Based on scanning and transmission electron microscopy studies, we hypothesized that the surface-to-volume ratio of cells increases with decreasing nutrient concentrations. The transition from smooth to wrinkled cell surface morphology could be one of the adaptation strategies by which YC6860T maximizes its ability to access available nutrients. To characterize the properties of the wrinkled strain, we performed taxonomic and phylogenetic analyses. 16S rRNA gene sequencing results showed that the strain represented a novel, deep-rooting lineage within the order Rhizobiales with the highest similarity of 94.2% to Pseudorhodoplanes sinuspersici RIPI 110T. Whole genome sequencing was also performed to characterize its genetic features. The strain YC6860T might belong to a new genus, named Rugositalea, and a new species, named Rugositalea oryzae, In addition, taxonomic analysis showed that YC6860T is Gram-negative, aerobic, and rod-shaped with large regular wrinkles resembling a delicate twist of fusilli, measuring 0.5-0.6 {micro}m in width and 1.5-1.6 {micro}m in length under nutrient-limiting conditions. This unique cell structure with regular rugosity could be the first finding that has not been reported in the existing bacterial morphology.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.