Bacteria move in the fluid by means of flagella. The flagellar geometry is a hollow tube which outer diameter is about 20 nanometers and the inner diameter is about 2 nanometers to form a helical propeller that produces a thrust force in the fluid. The formation of a flagellum is a one-dimensional self-assembly system. This system uses the ion electromotive force and ATP hydrolysis as the energy sources for the secretion of flagellin subunits. During flagella growth, flagellar monomer delivery to the distal end of the filament and folded into the flagella.
To study this self-assembly system, we developed a fast flagella labeling method and constructed an image processing protocol to track flagella automatically. For E. coli, there is a flagella labeling method using amino acid-specific dye (amino-specific dye). But, this dye spent about half to one hour to loading if you want to get a good signal to noise ratio. Therefore, we choose Vibrio alginolyticus as our system because they have sheathed flagella which are covered by a layer membrane-like structure. Therefore, we developed a flagella labeling protocol using lipophilic dye FM4-64 to monitor flagellar growth in real-time. This labeling protocol is greatly shortened to stain fluorescent dye, so that the time-resolution is greatly improved. Hence, we can obtain the accuracy measurement and observation for the self-assembly system. Besides, in the past, analysis is not based on a fixed algorithm resulting in the measurement accompanied by human error. But, the lipophilic dye also can stain the cell membrane. So, we cannot use define a threshold to pick out flagella. Then, based on the principle of optical imaging, we remove a halo effect between the cell and flagellum to make the bacterial flagella analysis data more reliable.
Further, we measured the flagellum self-assembly system of Vibrio alginolyticus, showing that the growth rate of flagellum is length dependent. From our experimental result, we compared the flagellar growth rate in different mutants. And then, we set up the Injection-diffusion model and use Brownian Dynamics simulation to fit the model. The main idea of the model is that both injection and diffusion mechanisms compete with each other to cause the rate of self-assembly to have different rate-limiting in different duration. In the early stages of flagellation, because the flagellin molecules are at low occupancy in the channel, so the export apparatus can smoothly pump the subunits into the channel. Hence, the secretion force dominates the flagellar growth rate at short flagellation. However, when the flagellar length becomes longer, the number of protein molecules are jammed in the flagellum tube. The secretion force cannot be successfully loaded into the new protein molecules into channel. Until the protein molecules in the channel are diffused, the new protein molecules have the opportunity to enter. Therefore, this time would be dominated by diffusion resulting in the flagellar self-assembly rate decay.
Our fluorescent labeling protocol, image process, experimental results, and the injection-diffusion model shed the light of understanding bacterial flagella self-assembly mechanisms.
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