Gibbs Lab
Deciphering self versus non-self recognition in bacteria
University of California, Berkeley
Cells from two different populations of Proteus mirabilis meeting as they migrate as a swarm along the rigid surface.
In the Gibbs research group, our goal is to identify molecular mechanisms that contribute to collective behaviors of single-celled organisms. In many of these systems, molecular components enable distinct responses between self and nonself. Indeed, self (or kin) recognition is observed at many levels of biological complexity ranging from immune cells to bacteria. In our model system, migrating colonies of independent Proteus mirabilis isolates recognize each other as foreign. The colonies do not merge when they intersect, whereas colonies of clonal isolates do merge, indicating that this bacterium is capable of self/nonself recognition (see the movie). P. mirabilis is broadly found in animal and human intestines and can cause bladder and kidney infections.
We strive to harness this bacterium’s relative genetic simplicity and tractability to discern the molecular mechanisms underlying its self/nonself recognition process. We leverage its sophisticated synthesis of sensing, signaling, and motility to advance understanding of the basic phenomena that give rise to behaviors, such as cell-cell communication, collective migration, competition, and pathogenesis.
Colonies of P. mirabilis migrate as swarms on top of a rigid nutrient surface. The pattern of concentric circles is characteristic of a P. mirabilis swarm.
Left: Each colony was isolated from a different person. A visible line forms between the two colonies and is apparent at the end of the time-lapse movie.
Right: Each colony was isolated from the same person. The two colonies form a single, coherent colony at the end of the time-lapse movie.
Movies taken by J. Austerman.
Interested in joining our group for graduate school, a postdoctoral fellowship or research internship? Contact Dr. Gibbs directly at kagibbs@berkeley.edu.
A list of recent publications can be found at https://orcid.org/0000-0002-1246-6401.