Abstract
Subcellular localization is a critical aspect of protein function and the potential application of proteins either as drugs or drug targets, or in industrial and domestic applications. However, the experimental determination of protein localization is time consuming and expensive. Therefore, various localization predictors have been developed for particular groups of species. Intriguingly, despite their major representation amongst biotechnological cell factories and pathogens, a meta-predictor based on sorting signals and specific for Gram-positive bacteria was still lacking. Here we present GP4, a protein subcellular localization meta-predictor mainly for Firmicutes, but also Actinobacteria, based on the combination of multiple tools, each specific for different sorting signals and compartments. Novelty elements include improved cell-wall protein prediction, including differentiation of the type of interaction, prediction of non-canonical secretion pathway target proteins, separate prediction of lipoproteins and better user experience in terms of parsability and interpretability of the results. GP4 aims at mimicking protein sorting as it would happen in a bacterial cell. As GP4 is not homology based, it has a broad applicability and does not depend on annotated databases with homologous proteins. Non-canonical usage may include little studied or novel species, synthetic and engineered organisms, and even re-use of the prediction data to develop custom prediction algorithms. Our benchmark analysis highlights the improved performance of GP4 compared to other widely used subcellular protein localization predictors. A webserver running GP4 is available at http://gp4.hpc.rug.nl/
Highlights
Subcellular localization (SCL) is a key element in the functional annotation of proteins, their use in biotechnology, and their potential as drug candidates or targets
We address the most relevant aspects that should be taken into account and present a new protein subcellular localization meta-predictor for Firmicutes, named GP4, which is suitable for Actinobacteria
The more the query sequence, or the species from which it is derived, is related to elements incorporated in the training set, the more precise the result returned by most tools will be. This bias is present in homology-based prediction tools that rely on the presence and correct annotation of proteins within the respective database
Summary
Subcellular localization (SCL) is a key element in the functional annotation of proteins, their use in biotechnology, and their potential as drug candidates or targets. This is time consuming, expensive and impractical due to the recent explosion in the numbers of whole-genome-sequenced organisms. Tjeerd van Rij is a senior scientist at the DSM Biotechnology Center in Delft, the Netherlands He obtained his PhD from Leiden University the Netherlands in 2006. His interests are in gene expression and protein secretion. Jan Maarten van Dijl is a professor of molecular bacteriology at the University of Groningen and the University Medical Center Groningen, the Netherlands, since 2004. He earned his PhD degree in 1990. Submitted: 29 July 2020; Received (in revised form): 8 October 2020
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