HECTAR: A method to predict subcellular targeting in heterokonts

Abstract

BackgroundThe heterokonts are a particularly interesting group of eukaryotic organisms; they include many key species of planktonic and coastal algae and several important pathogens. To understand the biology of these organisms, it is necessary to be able to predict the subcellular localisation of their proteins but this is not straightforward, particularly in photosynthetic heterokonts which possess a complex chloroplast, acquired as the result of a secondary endosymbiosis. This is because the bipartite target peptides that deliver proteins to these chloroplasts can be easily confused with the signal peptides of secreted proteins, causing currently available algorithms to make erroneous predictions. HECTAR, a subcellular targeting prediction method which takes into account the specific properties of heterokont proteins, has been developed to address this problem.ResultsHECTAR is a statistical prediction method designed to assign proteins to five different categories of subcellular targeting: Signal peptides, type II signal anchors, chloroplast transit peptides, mitochondrion transit peptides and proteins which do not possess any N-terminal target peptide. The recognition rate of HECTAR is 96.3%, with Matthews correlation coefficients ranging from 0.67 to 0.95. The method is based on a hierarchical architecture which implements the divide and conquer approach to identify the different possible target peptides one at a time. At each node of the hierarchy, the most relevant outputs of various existing subcellular prediction methods are combined by a Support Vector Machine.ConclusionThe HECTAR method is able to predict the subcellular localisation of heterokont proteins with high accuracy. It also efficiently predicts the subcellular localisation of proteins from cryptophytes, a group that is phylogenetically close to the heterokonts. A variant of HECTAR, called HECTARSEC, can be used to identify signal peptide and type II signal anchor sequences in proteins from any eukaryotic organism. Both HECTAR and HECTARSEC are available as a web application at the following address: .

Evidence for glycoprotein transport into complex plastids

“…S4). This observation is supported by in silico analyses performed with homologs of a set of 48 verified heterokont stromal proteins (33) revealing that 10.4% have high confidence predictions for N-glycosylation (Table S1). …”

Choreography of Transcriptomes and Lipidomes ofNannochloropsisReveals the Mechanisms of Oil Synthesis in Microalgae

“…To determine possible compartmentalization of TAG synthesis in this organism, SignalP (Petersen et al, 2011), ChloroP (Emanuelsson et al, 1999), Mitoprot (Claros, 1995), and HECTAR (Gschloessl et al, 2008) were used to predict subcellular localization of the 13 DGAT genes. A Type II signal anchor was detected in DGAT-2A, 2H, and 2K (Supplemental Data Set 6).…”

“…A Type II signal anchor was detected in DGAT-2A, 2H, and 2K (Supplemental Data Set 6). The Type II signal anchors are signal peptides with an extended N-terminal transmembrane region; thus, the proteins with type II signal anchors are presumed to be located in ER membranes (Gschloessl et al, 2008). These ER-associated DGAT-2 proteins seemed to play differential physiological roles in TAG synthesis under the various environmental conditions: The most abundant ER-associated isoform (encoded by DGAT-2A) and a minor isoform (2H) were induced under N deprivation (Figures 4C and 5), whereas 2K was upregulated in the lag and early exponential growth phases under N+ conditions (Figures 4A and 5).…”

“…For Nannochloropsis and other heterokonts derived from secondary endosymbiosis, an ER signal peptide is required in addition to the plastid transit peptide for targeting proteins to the plastid because those plastids are surrounded by a cisterna of ER membrane called the plastid ER (Gibbs, 1979;Gschloessl et al, 2008). In IMET1, the plastid transit peptides were identified in DGAT-1B and 2C proteins (Supplemental Data Set 6), but the ER signal peptide was absent.…”

Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions

“…Information regarding transport proteins was obtained from TransportDB and TCDB (Ren and Paulsen, 2007). Subcellular protein localization was predicted using SignalP, ChloroP, HECTAR, and WolF PSORT (Emanuelsson et al, 1999;Horton et al, 2007;Gschloessl et al, 2008;Petersen et al, 2011; Table I). …”