A subcellular atlas ofToxoplasmareveals the functional context of the proteome

Abstract

Apicomplexan parasites cause major human disease and food insecurity. They owe their considerable success to novel, highly specialized cell compartments and structures. These adaptations drive their recognition and nondestructive penetration of host's cells and the elaborate reengineering of these cells to promote growth, dissemination, and the countering of host defenses. The evolution of unique apicomplexan cellular compartments is concomitant with vast proteomic novelty that defines these new cell organizations and their functions. Consequently, half of apicomplexan proteins are unique and uncharacterized, and these cells are, therefore, very poorly understood. Here, we determine the steadystate subcellular location of thousands of proteins simultaneously within the globally prevalent apicomplexan parasite Toxoplasma gondii. This provides unprecedented comprehensive molecular definition to these cells and their novel compartments, and these data reveal the spatial organizations of protein expression and function, adaptation to hosts, and the underlying evolutionary trajectories of these pathogens.

Proteomic Insights into the Biology of the Most Important Foodborne Parasites in Europe

“…The most comprehensive description of the proteomic organization of a T. gondii cell (tachyzoite) was recently presented by Barylyuk et al [ 177 ] by applying relatively new proteomic method of subcellular localization of thousands of proteins per experiment by isotope tagging (hyperLOPIT). The hyperLOPIT method utilizes a unique abundance distribution map, which is formed during the organelles and subcellular structures biochemical fractionation, e.g., density gradient centrifugation.…”

“…In addition, these three data sets have a total of 3832 proteins, which can provide complete abundance distribution overview information of 30 fractions. Using the hyperLOPIT approach, Barylyuk et al assigned thousands of proteins to their subcellular niches [ 177 ].…”

A single master regulator controls asexual cell cycle division patterns inToxoplasma gondii

“…In the list of downregulated transcripts, we were struck by the number of annotated genes corresponding to proteins targeted to the IMC and to the apical complex both structures that are the first to appear when the daughters bud within the mother cell. To better assess the potential localization of the proteins that correspond to downregulated transcripts, we used a HyperLopit proteomic dataset that predicts with high confidence the localization of proteins in the parasite [25]. We showed that a high proportion of the downregulated transcripts present in the dataset (331 genes) encode proteins predicted to localize to the IMC or to the apical complex (a total of 30% of the downregulated transcripts present in the HyperLopit dataset; Figure S7B).…”

A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection

“…Novelty detection can also prove useful in validating experimental design, either by demonstrating that contaminants have been removed or that increased resolution of organelle classes has been achieved by the experimental approach. For most non-model organisms, we have little a priori knowledge of their sub-cellular proteome organisation, making it challenging to curate the marker set (training dataset) from the literature (Barylyuk et al, 2020). In these cases, novelty detection can assist in annotating the spatial proteome.…”

“…The proposed T-Augmented Gaussian Mixture (TAGM) model was shown to achieve state-of-the-art predictive performance against other commonly used machine learning algorithms (Crook et al, 2018). Furthermore, the model has been successfully applied to reveal unrivalled insight into the spatial organisation of Toxoplasma gondii (Barylyuk et al, 2020) and identify cargo of the Golgins of the trans-Golgi network (Shin et al, 2019).…”