Computational Molecular Biology 2016, Vol.6, No.4, 1-12
1
Research Article Open Access
ProtSecKB: The Protist Secretome and Subcellular Proteome Knowledgebase
Brian Powell
1
, Vamshi Amerishetty
2
, John Meinken
2,3
, Geneva Knott
4
, Feng Yu
1
, Chester Cooper
2,4
, Xiang Jia Min
2,4
1 Department of Computer Science & Information Systems, Youngstown State University, Youngstown, OH 44555, USA
2 Center for Applied Chemical Biology, Youngstown State University, Youngstown, OH 44555, USA
3 Center for Health Informatics, University of Cincinnati, Cincinnati, OH 45267-0840, USA
4 Department of Biological Sciences, Youngstown State University, Youngstown, OH 44555, USA
Corresponding author email:
Computational Molecular Biology, 2016, Vol.6, No.4 doi: 10.5376/cmb.2016.06.0004
Received: 19 Aug., 2016
Accepted: 01 Nov., 2016
Published: 14 Dec., 2016
Copyright © 2016
Powell et al., This is an open access article published under the terms of the Creative Commons Attribution License, which
permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
Preferred citation for this article
:
Powell B., Amerishetty V., Meinken J., Knott G., Feng Y., Cooper C., and Min X.M., 2016, ProtSecKB: the protist secretome and subcellular proteome
knowledgebase, Computational Molecular Biology, 6(4): 1-12 (doi: 10.5376/cmb.2016.06.0004)
Abstract
Kingdom Protista contains a large group of eukaryotic organisms with diverse lifestyles. We developed the Protist
Secretome and Subcellular Proteome Knowledgebase (ProtSecKB) to host information of curated and predicted subcellular locations
of all protist proteins. The protist protein sequences were retrieved from UniProtKB, consisting of 1.97 million entries generated
from 7,024 species with 101 species including 127 organisms having complete proteomes. The protein subcellular locations were
based on curated information and predictions using a set of well evaluated computational tools. The database can be searched using
several different types of identifiers, gene names or keyword(s). Secretomes and other subcellular proteomes can be searched or
downloaded. BLAST searching against the complete set of protist proteins or secretomes is available. Protein family analysis of
secretomes from representing protist species, including
Dictyostelium discoideum
,
Phytophthora infestans
, and
Trypanosoma cruzi
,
showed that species with different lifestyles had drastic differences of protein families in their secretomes, which may determine their
lifestyles. The database provides an important resource for the protist and biomedical research community. The database is available
at
.
Keywords
Computational Prediction; Protest; Protista; Secreted Protein; Secretome; Signal Peptide; Subcellular Location;
Subcellular Proteome; Lifestyle
1 Introduction
Protists consist of a large number of diverse eukaryotic organisms that are not classified into the kingdoms of
Fungi, Plantae, or Animalia (Foissner, 1999, 2006; Slapeta et al., 2005). Some protists are parasites of animals and
humans, such as
Plasmodium falciparum
causing malaria, and many others cause similar diseases in other
vertebrates (D'Acremont et al., 2010). The oomycete
Phytophthora infestans
causes late blight in potato and
tomato plants (Nowicki et al., 2012). Understanding the metabolism of these protists and their roles in ecology
may allow these diseases to be treated more efficiently.
In eukaryotes, proteins are synthesized within a cell and then transported to different subcellular locations
including extracellular space or matrix to perform their biological functions. Identification and analysis of protein
subcellular locations in eukaryotes is one of the important subjects for annotating a proteome. The term secretome
is often used to describe the set of proteins secreted outside of a cell (Lum and Min, 2011). The parasite
P.
falciparum
causes malaria by replicating inside red blood cells of infected individuals. Secreted proteins of
P.
falciparum
were identified and experimentally examined (Przyborski and Lanzer, 2004; Hiller et al., 2004; Van
Ooij et al., 2008). These secreted proteins are potential targets for drug treatment of the malaria disease (Bhatt,
2012).
Classical eukaryotic secreted proteins contain a secretory signal peptide at the N-terminus (von Heijne, 1990).
Classical secreted proteins of eukaryotes can be computationally predicted accurately with our developed
computational protocols of combining multiple prediction tools (Min, 2010). Thus we have made efforts to
