Proteomics of secretory and endocytic organelles in Giardia lamblia

贾第鞭毛虫分泌和内吞细胞器的蛋白质组学

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作者:Petra B Wampfler, Vinko Tosevski, Paolo Nanni, Cornelia Spycher, Adrian B Hehl

Abstract

Giardia lamblia is a flagellated protozoan enteroparasite transmitted as an environmentally resistant cyst. Trophozoites attach to the small intestine of vertebrate hosts and proliferate by binary fission. They access nutrients directly via uptake of bulk fluid phase material into specialized endocytic organelles termed peripheral vesicles (PVs), mainly on the exposed dorsal side. When trophozoites reach the G2/M restriction point in the cell cycle they can begin another round of cell division or encyst if they encounter specific environmental cues. They induce neogenesis of Golgi-like organelles, encystation-specific vesicles (ESVs), for regulated secretion of cyst wall material. PVs and ESVs are highly simplified and thus evolutionary diverged endocytic and exocytic organelle systems with key roles in proliferation and transmission to a new host, respectively. Both organelle systems physically and functionally intersect at the endoplasmic reticulum (ER) which has catabolic as well as anabolic functions. However, the unusually high degree of sequence divergence in Giardia rapidly exhausts phylogenomic strategies to identify and characterize the molecular underpinnings of these streamlined organelles. To define the first proteome of ESVs and PVs we used a novel strategy combining flow cytometry-based organelle sorting with in silico filtration of mass spectrometry data. From the limited size datasets we retrieved many hypothetical but also known organelle-specific factors. In contrast to PVs, ESVs appear to maintain a strong physical and functional link to the ER including recruitment of ribosomes to organelle membranes. Overall the data provide further evidence for the formation of a cyst extracellular matrix with minimal complexity. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the dataset identifier PXD000694.

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