Bibliographic Details
| Title: |
Collective bacterial condensation is fundamentally constrained by the emergence of active turbulence. |
| Authors: |
Livne, Nir1, Vaknin, Ady1 avaknin@mail.huji.ac.il |
| Source: |
Proceedings of the National Academy of Sciences of the United States of America. 3/17/2026, Vol. 123 Issue 11, p1-9. 25p. |
| Subjects: |
Chemotaxis, Microbial aggregation, Fluid mechanics, Turbulence, Motility of bacteria, Porous materials, Concentration gradient |
| Abstract: |
Collective bacterial condensation arises from positive feedback between the ability of bacteria to generate chemical gradients in their environment and their chemotactic ability to follow those gradients. This feedback drives the spontaneous formation of local cell accumulations, characterized by sharp cell-density gradients, even in the absence of physical boundaries. By following the dynamics of bacterial condensation in uniform acidic environments, we show that condensation is critically constrained by the spontaneous emergence of correlated bacterial swimming and the associated active turbulence. These collective behaviors generate vortex-like cell motion with a pronounced radial component directed down the cell-density gradient. This, in turn, induces local fluid motion that broadens the condensate and expels nonchemotactic bacteria. When condensates are strongly confined in thin layers, the radial component of fluid motion diminishes and condensation is enhanced. Moreover, in porous environments, correlated bacterial motion is strongly suppressed, allowing spontaneous condensation to progress even further until it reaches the limits imposed by the nonlocal nature of bacterial chemotaxis. Overall, these findings highlight the fundamental interplay between self-generated bacterial condensation and correlated swimming. [ABSTRACT FROM AUTHOR] |
|
Copyright of Proceedings of the National Academy of Sciences of the United States of America is the property of National Academy of Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |