From molecular noise to behavioral variability in a single bacterium
"From molecular noise to behavioural variability in a single bacterium"
Ekaterina Korobkova, Thierry Emonet, Jose M.G. Vilar, Thomas S. Shimizu, & Philippe Cluzel
Nature 428 574-578 (2004)
Soft Matter Keywords
bacteria, E. coli, chemotaxis, signaling pathway
The authors present primarily experimental work regarding a study of the chemotaxis network governing the motion of Escherichia coli. In the past, experiments and models for this system have assumed that network properties can be inferred from population measurements, which has the unfortunately effect of masking temporal fluctuations of intracellular signaling events. Korobkova, et al. study a noise analysis of behavioral variations in individual bacteria as a route to inferring fundamental properties of the chemotaxis network. They observe some properties established by population measurements to not be conserved at the single-cell level and find behavior of non-stimulated bacteria displaying temporal variations much larger than expected statistical fluctuation. The authors have also found that the temporal behavioral variablity is strong dependent on the concentration of a key network component.
Practical Application of Research
Though not immediately applicable in its own right, this research helps elucidate some of the features of the biological network and feedback that governs the motion of E. coli. Understanding this network could allow for precise genetic design of mutant strains of E. coli with particular locomotion controls. This is also a nice example of the overlap between physics and biology in which standard physical analyses are extended to biological systems to yield new isights.
Noise Analysis of Individual Bacterium
The authors study how the behavior of an individual bacterium in a homogeneous environment fluctuates with time. Their primary question is whether there are specific molecular events that could cause temporal behavioral variability in an individual bacterium. To perform this study, bacteria were immobilized onto microscope slides and their flagella marked with micro-beads to visualize the rotation with dark-field microscopy. The output from these observations was converted to a binary time series showing the direction of rotation (see Figure 1a)
written by Donald Aubrecht