Budding Yeast Dma Proteins Control Septin Dynamics and the Spindle Position Checkpoint by Promoting the Recruitment of the Elm1 Kinase to the Bud Neck

The first step towards cytokinesis in budding yeast is the assembly of a septin ring at the future site of bud emergence. Integrity of this ring is crucial for cytokinesis, proper spindle positioning, and the spindle position checkpoint (SPOC). This checkpoint delays mitotic exit and cytokinesis as long as the anaphase spindle does not properly align with the division axis. SPOC signalling requires the Kin4 protein kinase and the Kin4-regulating Elm1 kinase, which also controls septin dynamics. Here, we show that the two redundant ubiquitin-ligases Dma1 and Dma2 control septin dynamics and the SPOC by promoting the efficient recruitment of Elm1 to the bud neck. Indeed, dma1 dma2 mutant cells show reduced levels of Elm1 at the bud neck and Elm1-dependent activation of Kin4. Artificial recruitment of Elm1 to the bud neck of the same cells is sufficient to re-establish a normal septin ring, proper spindle positioning, and a proficient SPOC response in dma1 dma2 cells. Altogether, our data indicate that septin dynamics and SPOC function are intimately linked and support the idea that integrity of the bud neck is crucial for SPOC signalling

MOB1A

The accuracy of cell division is fundamental for the maintenance of cell ploidy and genomic stability. During cell division, many events, like DNA replication, chromosome segregation, mitosis completion, and cytokinesis, must be tightly controlled. The deregulation of these events is closely associated with severe pathology. Among other factors, the accuracy of cell division relies on the correct placement of the division plane which is dependent on the polarity axis. Both in unicellular organisms and in metazoan, the cell spindle position is regulated to be perpendicular or planar to the division plane, allowing this way to equally segregate the chromosomes between the two daughter cells.info:eu-repo/semantics/publishedVersio

Asymmetric Localization of Components and Regulators of the Mitotic Exit Network at Spindle Pole Bodies.

International audienceMost proteins of the Mitotic Exit Network (MEN) and their upstream regulators localize at spindle pole bodies (SPBs) at least in some stages of the cell cycle. Studying the SPB localization of MEN factors has been extremely useful to elucidate their biological roles, organize them in a hierarchical pathway, and define their dynamics under different conditions.Recruitment to SPBs of the small GTPase Tem1 and the downstream kinases Cdc15 and Mob1/Dbf2 is thought to be essential for Cdc14 activation and mitotic exit, while that of the upstream Tem1 regulators (the Kin4 kinase and the GTPase activating protein Bub2-Bfa1) is important for MEN inhibition upon spindle mispositioning. Here, we describe the detailed fluorescence microscopy procedures that we use in our lab to analyze the localization at SPBs of Mitotic Exit Network (MEN) components tagged with GFP or HA epitopes

A Large-Scale Assessment of Exact Model Reduction in the BioModels Repository

Chemical reaction networks are a popular formalism for modeling biological processes which supports both a deterministic and a stochastic interpretation based on ordinary differential equations and continuous-time Markov chains, respectively. In most cases, these models do not enjoy analytical solution, thus typically requiring expensive computational methods based on numerical solvers or stochastic simulations. Exact model reduction techniques can be used as an aid to lower the analysis cost by providing reduced networks that preserve the dynamics of interest to the modeler. We hereby consider a family of techniques for both deterministic and stochastic networks which are based on equivalence relations over the species in the network, leading to a coarse graining which provides the exact aggregate time-course evolution for each equivalence class. We present a large-scale empirical assessment on the BioModels repository by measuring their compression capability over 667 models. Through a number of selected case studies, we also show their ability in yielding physically interpretable reductions that can reveal dynamical patterns of the bio-molecular processes under consideration