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Cep192, a Novel Missing Link between the Centrosomal Core and Corona in Dictyostelium Amoebae.

ABSTRACT: The Dictyostelium centrosome is a nucleus-associated body with a diameter of approx. 500 nm. It contains no centrioles but consists of a cylindrical layered core structure surrounded by a microtubule-nucleating corona. At the onset of mitosis, the corona disassembles and the core structure duplicates through growth, splitting, and reorganization of the outer core layers. During the last decades our research group has characterized the majority of the 42 known centrosomal proteins. In this work we focus on the conserved, previously uncharacterized Cep192 protein. We use superresolution expansion microscopy (ExM) to show that Cep192 is a component of the outer core layers. Furthermore, ExM with centrosomal marker proteins nicely mirrored all ultrastructurally known centrosomal substructures. Furthermore, we improved the proximity-dependent biotin identification assay (BioID) by adapting the biotinylase BioID2 for expression in Dictyostelium and applying a knock-in strategy for the expression of BioID2-tagged centrosomal fusion proteins. Thus, we were able to identify various centrosomal Cep192 interaction partners, including CDK5RAP2, which was previously allocated to the inner corona structure, and several core components. Studies employing overexpression of GFP-Cep192 as well as depletion of endogenous Cep192 revealed that Cep192 is a key protein for the recruitment of corona components during centrosome biogenesis and is required to maintain a stable corona structure.

SUBMITTER: Pitzen V

PROVIDER: S-EPMC8467581 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundFunctional traits are the primary biotic component driving organism influence on ecosystem functions; in consequence, traits are widely used in ecological research. However, most animal trait-based studies use easy-to-measure characteristics of species that are at best only weakly associated with functions. Animal-mediated pollination is a key ecosystem function and is likely to be influenced by pollinator traits, but to date no one has identified functional traits that are simple to measure and have good predictive power.MethodsHere, we show that a simple, easy to measure trait (hairiness) can predict pollinator effectiveness with high accuracy. We used a novel image analysis method to calculate entropy values for insect body surfaces as a measure of hairiness. We evaluated the power of our method for predicting pollinator effectiveness by regressing pollinator hairiness (entropy) against single visit pollen deposition (SVD) and pollen loads on insects. We used linear models and AICC model selection to determine which body regions were the best predictors of SVD and pollen load.ResultsWe found that hairiness can be used as a robust proxy of SVD. The best models for predicting SVD for the flower species Brassica rapa and Actinidia deliciosa were hairiness on the face and thorax as predictors (R2 = 0.98 and 0.91 respectively). The best model for predicting pollen load for B. rapa was hairiness on the face (R2 = 0.81).DiscussionWe suggest that the match between pollinator body region hairiness and plant reproductive structure morphology is a powerful predictor of pollinator effectiveness. We show that pollinator hairiness is strongly linked to pollination-an important ecosystem function, and provide a rigorous and time-efficient method for measuring hairiness. Identifying and accurately measuring key traits that drive ecosystem processes is critical as global change increasingly alters ecological communities, and subsequently, ecosystem functions worldwide.

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Cep192, a Novel Missing Link between the Centrosomal Core and Corona in Dictyostelium Amoebae.

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