Led by researchers at Sorbonne Université, the study published in the journal Nature Microbiology provides a new perspective on how bacteria sense their environment and could guide the development of treatments for bacterial infections, including antibiotic-resistant infections.
Bacteria are constantly exposed to a vast array of molecules in their environment, and many use specialised proteins called 'sensor domains' to detect and respond to these molecules. These proteins can act like switches that turn on or off specific genes in the bacterial cell in response to the sensed molecule, controlling everything from metabolism to virulence.
Despite their critical importance, the precise molecules detected by many sensor domains were unknown. To address this, the researchers developed a new method called SEnSoR, which involves modifying the sensor domain so that it binds to a synthetic molecule instead of its natural ligand. This synthetic molecule can then be used to 'fish out' the sensor domain from a mixture of proteins and identify its binding partner.
The team used SEnSoR to identify the binding partners of several sensor domains from the opportunistic human pathogen Pseudomonas aeruginosa, which is responsible for a variety of infections, including pneumonia and sepsis. They found that these sensor domains detect a diverse array of molecules, including sugars, amino acids, and lipids, and that these molecules are essential for the survival of P. aeruginosa in different environments, such as the human respiratory tract.
"We believe that this method can be applied to other bacteria besides Pseudomonas aeruginosa, potentially revealing the molecular targets of a wide range of sensor domains and providing new insights into how bacteria interact with their environment," said study lead author Dr. William Vizcarra-Ortega.
"This information could be exploited for antimicrobial drug design and the development of new antibiotics that target sensor domains and disrupt bacterial signalling pathways.”
The researchers believe that the method could also help identify new ways to prevent and treat bacterial infections. For example, by identifying the molecules that are essential for bacterial survival in certain environments, it may be possible to develop strategies to block their detection or interfere with their function, thereby inhibiting the growth of the bacteria.
Going forward, the researchers aim to further explore the potential applications of their method and investigate the role of sensor domains in antibiotic resistance. They also plan to use the method to study other types of bacteria and identify new drug targets for the treatment of bacterial infections.
