Our cells and in particular our neurons are too large for thermal-driven diffusion to be an effective means of transport of proteins, organelles and other cargoes. Instead, eukaryotic organisms have evolved motor proteins that drive unidirectional motion over relatively long distances while consuming chemical energy in the form of ATP. Over the last two decades, important insights into the molecular mechanisms of several key motor proteins of the kinesin, myosin and dynein families have been obtained, among others by the application of advanced single-molecule methods. Over the last five years in my laboratory, the focus has shifted from studying the behavior of single motor proteins, working on their own in vitro, to studying motor proteins in their cellular environment. In our cells, motor proteins do not work on their own: cargoes are often transported by multiple motors, of the same type, but often also of opposite directionality. In addition, our cells are a very crowded environment, with many proteins bound to the motors’ tracks, which might hamper their motion and could lead to ‘traffic jams’.
To study these kinds of problems, we have focused on a particular transport mechanism, intraflagellar transport (IFT), which takes place in cilia and flagella and is essential for the assembly and maintenance of these organelles. As a model system we use IFT in the chemosensory cilia of the nematode C. elegans. In these organisms, IFT is driven by groups of tens of three different motor proteins: 2 kinesin-2’s (the slow kinesin-II and the fast OSM-3) that drive transport of cargo trains from base to tip of the cilium, and IFT dynein that drives transport back to the base. In order to visualize IFT components with fluorescence microscopy, we generate mutant-nematodes expressing fluorescent versions of the IFT component of interest. Our fluorescence and image analysis approaches allow us to visualize, track and quantify trains of IFT components moving together as well as individual motor or IFT proteins. Together, bulk and single-molecule data provide new, deep insights into the mechanisms of motor cooperation, which we try to capture in quantitative models.