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Quantitative genome-scale analysis of protein localization in an asymmetric bacterium.

ABSTRACT: Despite the importance of subcellular localization for cellular activities, the lack of high-throughput, high-resolution imaging and quantitation methodologies has limited genomic localization analysis to a small number of archival studies focused on C-terminal fluorescent protein fusions. Here, we develop a high-throughput pipeline for generating, imaging, and quantitating fluorescent protein fusions that we use for the quantitative genomic assessment of the distributions of both N- and C-terminal fluorescent protein fusions. We identify nearly 300 localized Caulobacter crescentus proteins, up to 10-fold more than were previously characterized. The localized proteins tend to be involved in spatially or temporally dynamic processes and proteins that function together and often localize together as well. The distributions of the localized proteins were quantitated by using our recently described projected system of internal coordinates from interpolated contours (PSICIC) image analysis toolkit, leading to the identification of cellular regions that are over- or under-enriched in localized proteins and of potential differences in the mechanisms that target proteins to different subcellular destinations. The Caulobacter localizome data thus represent a resource for studying both global properties of protein localization and specific protein functions, whereas the localization analysis pipeline is a methodological resource that can be readily applied to other systems.

SUBMITTER: Werner JN

PROVIDER: S-EPMC2671984 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe prediction of protein subcellular localization is a key step of the big effort towards protein functional annotation. Many computational methods exist to identify high-level protein subcellular compartments such as nucleus, cytoplasm or organelles. However, many organelles, like mitochondria, have their own internal compartmentalization. Knowing the precise location of a protein inside mitochondria is crucial for its accurate functional characterization. We recently developed DeepMito, a new method based on a 1-Dimensional Convolutional Neural Network (1D-CNN) architecture outperforming other similar approaches available in literature.ResultsHere, we explore the adoption of DeepMito for the large-scale annotation of four sub-mitochondrial localizations on mitochondrial proteomes of five different species, including human, mouse, fly, yeast and Arabidopsis thaliana. A significant fraction of the proteins from these organisms lacked experimental information about sub-mitochondrial localization. We adopted DeepMito to fill the gap, providing complete characterization of protein localization at sub-mitochondrial level for each protein of the five proteomes. Moreover, we identified novel mitochondrial proteins fishing on the set of proteins lacking any subcellular localization annotation using available state-of-the-art subcellular localization predictors. We finally performed additional functional characterization of proteins predicted by DeepMito as localized into the four different sub-mitochondrial compartments using both available experimental and predicted GO terms. All data generated in this study were collected into a database called DeepMitoDB (available at http://busca.biocomp.unibo.it/deepmitodb ), providing complete functional characterization of 4307 mitochondrial proteins from the five species.ConclusionsDeepMitoDB offers a comprehensive view of mitochondrial proteins, including experimental and predicted fine-grain sub-cellular localization and annotated and predicted functional annotations. The database complements other similar resources providing characterization of new proteins. Furthermore, it is also unique in including localization information at the sub-mitochondrial level. For this reason, we believe that DeepMitoDB can be a valuable resource for mitochondrial research.

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Quantitative genome-scale analysis of protein localization in an asymmetric bacterium.

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