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Genome Res. 15:321-329, 2005 ©2005 by Cold Spring Harbor Laboratory Press; ISSN 1088-9051/05 $5.00
Methods Genome-wide identification of Pseudomonas aeruginosa exported proteins using a consensus computational strategy combined with a laboratory-based PhoA fusion screen1 Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, V6T 1Z4, Canada 2 Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, V5A 1S6, Canada
The Gram-negative pathogen Pseudomonas aeruginosa encodes multiple protein export systems, the substrates of which contain export signals such as N-terminal signal peptides. Here we report the first genome-wide computational and laboratory screen for N-terminal signal peptides in this important opportunistic pathogen. The computational identification of signal peptides was based on a consensus between multiple predictive tools and showed that 38% of the P. aeruginosa PAO1 proteome was predicted to encode exported proteins, most of which utilize cleavable type I signal peptides or uncleavable transmembrane helices. In addition, known and novel lipoproteins (type II), twin arginine transporter (TAT), and prepilin peptidase substrates (type IV) were also identified. A laboratory-based screen using the alkaline phosphatase (PhoA) fusion method was then used to test our predictions. In total, 310 nonredundant PhoA fusions were successfully identified, 296 of which possess a predicted export signal. Analysis of the PhoA fusion proteins lacking an export signal revealed that three proteins have alternate translation start sites that encode signal peptides, two proteins may use an unknown export signal, and the remaining nine proteins are likely cytoplasmic proteins and represent false positives associated with the PhoA screen. Our approach to identify exported proteins illustrates how computational and laboratory-based methods are complementary, where computational analyses provide a large number of accurate predictions while laboratory methods both confirm predictions and reveal unique cases meriting further analysis.
The completion of the Pseudomonas aeruginosa PAO1 genome sequence has provided many insights into the biology and pathogenesis of this organism and serves as the starting point for genome-wide studies of this important opportunistic pathogen (Stover et al. 2000  ). P. aeruginosa is the primary cause of chronic lung infections and mortality in patients with cystic fibrosis and is also the third most frequently isolated nosocomial pathogen, causing 10% of all hospital-acquired infections (Govan and Deretic 1996; Fridkin and Gaynes 1999; Hancock and Speert 2000). Pseudomonas infections are difficult to treat due to the high intrinsic antibiotic resistance of this organism, which is attributed to low outer membrane permeability coupled with additional resistance mechanisms such as active drug efflux and antibiotic modification (Hancock and Speert 2000).
A major subset of the P. aeruginosa proteome is dedicated to proteins that are exported out of the cytoplasm to the cell envelope (the cytoplasmic membrane, the periplasm, and the outer membrane) or that are secreted out of the cell to the extracellular environment (Nouwens et al. 2000
P. aeruginosa proteins destined to noncytoplasmic subcellular localizations utilize various protein export systems, as recently reviewed in Ma et al. (2003
Proteins utilizing the Sec or TAT machinery are recognized by their N-terminal signal peptides. These are typically short sequences with a tripartite positive-hydrophobic-polar character suitable for partitioning into lipid bilayers. The N region is positively charged, the hydrophobic H region is a minimum of eight hydrophobic residues in length and forms a membrane-spanning helix, and the C region often contains a signal peptidase recognition site (von Heijne 1985 The availability of the P. aeruginosa PAO1 genome sequence, combined with knowledge of the defined structures and motifs found in most N-terminal signal peptides, permitted us to perform a genome-wide computational survey of proteins that use N-terminal signal peptides for export out of the cytoplasm. Our definition of "exported protein" includes all proteins exported out of the cytoplasm, including those incorporated into the cytoplasmic membrane through the presence of transmembrane helices.
Laboratory-based surveys of signal peptide-encoding genes are possible through the use of the alkaline phosphatase (PhoA) fusion technique (Bina et al. 1997 In this report, we describe a combined computational and laboratory survey of P. aeruginosa signal peptide-encoding genes. We first screened the P. aeruginosa PAO1 genome for potential export candidates using computational techniques, and then performed a random cloning PhoA fusion screen to test our predictions. This study represents the most comprehensive analysis of exported proteins in P. aeruginosa to date, and illustrates the utility of a combined approach for genome-scale studies.
Type I signal peptides are the most common N-terminal export signal A combination of four signal peptide and two transmembrane helix prediction methods, as well as manual motif searching, was used to identify potential export signals in the P. aeruginosa PAO1 genome. Type I or type II signal peptides and their cleavage sites were predicted using SignalP v.3.0's neural network and hidden Markov model tools (Bendtsen et al. 2004 ), LipoP v.1.0 (Juncker et al. 2003), and Phobius (Kall et al. 2004). Phobius and TMHMM (Krogh et al. 2001) were used to identify membrane-targeting transmembrane segments. Type IV and TAT signal peptides were identified manually. The predictions for each of the 5570 ORFs in the P. aeruginosa PAO1 genome are presented in Supplemental Table 1. The majority of proteins using an N-terminal signal peptide for export are substrates of the Sec pathway and are cleaved by SPase I. In the P. aeruginosa genome, 801 (14.4%) proteins were predicted by at least three of the four methods to contain a cleavable type I signal peptide (Table 1; Supplemental Table 2). The programs typically agree in their predictions, with 518 out of 801 signal peptides having four identically predicted cleavage sites and an additional 56 signal peptides with three identically predicted cleavage sites.
To depict representative type I signal peptides, amino acid sequence logos were constructed for P. aeruginosa type I signal peptides (Fig. 1A). The logo illustrates that predicted P. aeruginosa type I signal peptides are similar to those of other Gram-negative bacteria with respect to the N region charge and length and the H region length and hydrophobicity (von Heijne 1985 , 1989). The A-X-A motif for the SPase I cut site in the C region is also conserved, although this reflects the biases in data used to train the predictive methods.
In addition to the 801 proteins with strongly predicted signal peptides, 57 proteins yielded inconclusive results, with only two out of four methods making a signal peptide prediction. These proteins were therefore classified as possible type I signal peptides (Table 1; Supplemental Table 3). This list includes the known TAT substrate phospholipase PlcH (PA0844) (Voulhoux et al. 2001 ), a lectin protein thought to be anchored in the outer membrane (PA3361), and the probable outer membrane protein OprC (PA3790). Interestingly, this list also contains three regulatory proteins that are predicted to be cytoplasmic (PA1949, PA1998, PA2267) by PSORTb v.2.0 (Gardy et al. 2004). These three proteins likely represent the small number of false positives inherent in any predictive technique.
The PAO1 genome is predicted to encode a high proportion of lipoproteins
Manual scanning reveals novel putative prepilin peptidase substrates The 13 predicted prepilin peptidase substrates occurred in clusters along the genome. Reasoning that neighboring proteins might exhibit type IV-like signal sequences missed in the initial scan, we manually inspected the 10 proteins both upstream and downstream of the clusters. A further 10 sequences representing possible prepilin peptidase substrates were identified in this fashion. In total, 23 proteins were predicted to represent prepilin peptidase substrates, six of which have not been previously described (Table 2).
TAT motifs are found in 10 novel putative substrates Proteins exported via the TAT machinery display an RRXFL[KR]-like motif at their N terminus, which otherwise contains a leader sequence that resembles a tripartite signal peptide (Berks 1996 ). The P. aeruginosa genome has been scanned for the presence of TAT substrates in two previous studies. Ochsner et al. (2002) identified 18 putative substrates through a manual inspection approach. Their criteria included the presence of twin arginines, a match to at least one of the remaining residues in the motif, a hydrophobic tract following the motif, and an AXA cleavage site. Dilks et al. (2003) implemented their TATFIND v.1.2 program to identify 57 putative substrates, using the criteria of the presence of an XRRXXX motif within residues 1-34 as well as an uncharged region of  13 residues downstream of the twin arginines. In the present analysis, we first scanned proteins with predicted type I or II signal peptides for the presence of the TAT motif RRXFL[KR] immediately N-terminal to a stretch of hydrophobic residues. We predicted 14 proteins with type I signal peptides that also possess TAT motifs, while one protein with a predicted type II signal peptide contains the TAT motif (PA4712) (Table 3A). However, several putative TAT substrates reported in the earlier two studies were not identified in this analysis. We attribute this to the fact that many of these proteins do not contain traditional type I or type II signal peptides. Thus a second analysis was performed in which we eliminated the requirement for a predicted signal peptide. When the entire genome was searched without the signal peptide filtering step, an additional 12 putative TAT substrates were found (Table 3B).
In total, 27 potential TAT substrates were identified, 10 of which were not described in either of the two previous studies. The sequence logo derived from the twin arginine motif from these 27 proteins is shown in Figure 1C. The 10 novel substrates we predicted include FepD, HcnC, Sss, GlcE, and six hypothetical or conserved hypothetical proteins. Sss, however, is annotated as a site-specific recombinase and likely represents a false positive associated with the scanning procedure. We believe that these proteins may have been missed in the previous two analyses due to the requirement for an AXA cleavage site in the Ochsner et al. (2002 ) study, and the minimum of 13 uncharged residues downstream of the twin arginines required by TATFIND.
Eight proteins identified by Ochnser et al. (2002) were not found in the present study. Inspection of these revealed that the proteins either exhibit weakly hydrophobic regions downstream of their motifs or have less than two residues in common with the FL[KR] portion of the TAT motif. We also did not identify 41 proteins reported in Dilks et al. (2003
Transmembrane helices for membrane targeting
PhoA fusion screening to identify exported proteins Plasmids were purified from all PhoA positive colonies regardless of the stability of the PhoA phenotype. Only plasmids with high and intermediate yields were used as templates in sequencing reactions. In some cases, we observed extremely low plasmid yields, suggesting that plasmid loss had occurred. A total of 646 plasmids were sequenced and mapped to the P. aeruginosa genome to identify the gene randomly cloned upstream of the 'phoA gene. This analysis yielded a total of 474 proteins cloned in the correct orientation to produce a PhoA fusion protein, while the majority of remaining sequences were of poor quality and did not produce high-scoring BLAST hits to the PAO1 genome. Eliminating the redundant BLAST hits reduced the list to 310 unique P. aeruginosa-PhoA fusion proteins (Supplemental Table 6). The ability of these proteins to direct PhoA to the cytoplasmic membrane is likely due to the presence of an export signal. Of the 310 proteins identified in the PhoA screen, 296 displayed a predicted cleavable N-terminal signal peptide or contained one or more predicted transmembrane helices (Table 4). These data indicate that our consensus computational prediction strategy displayed high recall—in other words, a low number of false-negative results was encountered. However, we are unable to comment on the precision, or false-positive rate, of the strategy, as the PhoA fusion simply indicates export and does not provide information on the nature of the export signal itself.
Export signals were annotated as type I, probable type I, type II, type IV, TAT, or transmembrane helix based on the predictions generated in the initial computational screen. Similar proportions of type II and type IV signal peptides were observed in both the whole genome predictions and among the PhoA fusion proteins, indicating that the prediction of these two types of signals might be relatively straightforward, particularly compared with prediction of type I signal peptides. The proportion of type I signal peptides identified in the PhoA screen was  20% higher than the proportion predicted genome-wide, indicating that the predictive methods may be missing some noncanonical N-terminal signal peptides or that the PhoA fusion method preferentially identifies type I signal peptides.
PhoA fusions reveal misannotated start sites and confirm expression of 150 hypothetical proteins
The protein sequences and upstream regions were examined for alternative start sites by manual scanning and GeneMark 2.4 analysis (Lukashin and Borodovsky 1998
Next, the remaining proteins were compared to the PSORTdb database of proteins of experimentally verified localization (http://db.psort.org) using a BLASTp search and an Evalue cutoff of 1e - 10. None of the proteins were homologous to exported proteins, but four proteins (PA2451, PA3919, PA4091, PA2744) showed similarity to cytoplasmic proteins. Lastly, the protein sequences were similarly compared to the PSORTdb database of proteins with computationally predicted subcellular localizations. The predictions contained in the database were generated with PSORTb v.2.0, the most precise bacterial subcellular localization predictor available (Gardy et al. 2004 Among the proteins that produced active PhoA fusions, 150 are annotated as hypothetical or conserved hypothetical proteins. This finding suggests that these proteins are likely localized to the membrane and thus provides some preliminary information regarding the function of these proteins that have not as yet been characterized.
In the first part of our analysis, a genome-wide computational screen for exported proteins was performed. Multiple predictive methods, including machine learning methods and manual pattern matching, were used to identify P. aeruginosa PAO1 proteins containing possible export signals. In large-scale genome studies, it is critical to employ a consensus approach in order to reduce the number of false positives and to increase the confidence of the prediction. Our study reports 100% agreement between the genome-wide predictions and the experimental PhoA fusion data. The consensus prediction method used here indicates that 38% of the genome encodes proteins exported via five types of export signal: type I signal peptides, type II (lipoprotein) signal peptides, type IV (prepilin) signal peptides, TAT (twin arginine transporter) signal peptides, and membrane-targeting transmembrane helices. Approximately 40% of these predicted exported proteins appear to utilize cleavable type I signal peptides, according to three or more of the predictive methods. A small number of false positives were observed that include four of the 719 proteins with strongly predicted signal peptides (PA2003, PA2554, PA3883, PA5389) that show significant similarity to cytoplasmic proteins and three proteins with weakly predicted signal peptides (PA1949, PA1998, PA2267). Furthermore, predictions may also reflect biases in the programs' training data, such that certain noncanonical type I signal peptides might be missed. This is likely the case with many of the 57 proteins with weakly predicted type I signal peptides since many of them appear to be candidates for export based on their annotated functions; however, at least two of the four methods failed to predict a signal peptide. The methods used to identify the other classes of signal peptide are more specialized and appear to result in better predictions compared with type I signal peptide methods. LipoP v.1.0 predicted 185 potential lipoproteins in the genome, 109 more than are presently annotated in the pseudomonas.com database. The Pseudomonas Genome Database annotations were calculated using PSORT I, and the increase in predicted lipoproteins reported here illustrates the importance of using up to date computational methods. We predicted 23 putative prepilin peptidase substrates in the PAO1 genome, of which six represent novel candidates. These include five proteins occurring in a cluster, four of which are annotated as probable type II secretion system proteins and may represent novel type II secretion proteins, similar to the Xcp and Hxc machinery. There are likely more prepilin peptidase substrates within the P. aeruginosa genome, which could be identified through searching with a more degenerate motif. For example, the supposedly invariant Gly residue preceding the cleavage site appears to be replaceable by an Ala residue, as seen in the previously identified FimT protein, as well as in PA2672 and PA2674 reported here.
Fifteen putative TAT substrates were initially identified in the present analysis, which utilized stringent criteria, including the presence of a predicted N-terminal signal peptide and a match of at least five of the six residues in the RRXFL[KR] motif. An expanded analysis searching for potential TAT substrates across the whole genome—not just within the subset of proteins with predicted signal peptides—identified a further 12 possible TAT substrates. This indicates that it is important not to overlook proteins without a predicted signal peptide, as they may contain functioning TAT-directing motifs. In fact, of the 18 previously identified TAT substrates reported by Ochsner et al. (2002 Our computational analysis showed that the majority of exported proteins are likely cytoplasmic membrane proteins that lack cleavable signal peptides but possess one or more transmembrane helices as an export signal. This estimate of proteins possessing transmembrane helices, 18.7% of the P. aeruginosa proteome, is similar to the 18.5% of proteins predicted by PSORTb to be localized to the cytoplasmic membrane. This may reflect the fact that computational prediction of transmembrane helices is generally regarded to be more accurate than the prediction of targeting signals, due to the sequence constraints associated with crossing a lipid bilayer. As signal peptide prediction methods improve, we are likely to see an increase in the number of predicted exported proteins.
PhoA fusion methods are a versatile genetic tool to identify proteins that are translocated across the cytoplasmic membrane. By using a plasmid-based 'phoA screen, 310 unique P. aeruginosa fusion proteins were successfully identified. This approach to identify membrane-localized proteins is as efficient as reported in previous P. aeruginosa membrane proteomic studies (Nouwens et al. 2000
Although there is a possibility that certain P. aeruginosa-specific export signals may not be recognized as PhoA fusions expressed in a recombinant E. coli host, the strong conservation of the inner membrane targeting and translocation machinery should not affect the export of most PhoA fusion proteins. In addition, we have used this approach previously to identify secreted proteins in Helicobacter pylori (Bina et al. 1997 The 310 proteins identified in this PhoA screen reflect many of the known functions associated with the cell envelope. The outer membrane proteins identified included those that function as porins, iron uptake receptors, and efflux channels, the three largest families of outer membrane proteins, and proteins involved in secretion and adhesion. Periplasmic proteins identified included the binding components of ABC transporters, cell wall biosynthesis enzymes, stress response proteases, and chaperones. Inner membrane proteins included transport proteins, chemotaxis transducers, two-component sensors, efflux pumps, cell wall biosynthesis enzymes, and proteins involved in secretion. The PhoA fusion data provided confirmation that 14% of our predicted exported proteins are indeed exported, although the export signals themselves cannot be identified. The laboratory analysis also identified 14 proteins with no predicted export signal. Three of these 14 contained mispredicted start sites, and the new translation products displayed type I signal peptides. Nine of the remaining proteins showed significant similarity to known and predicted cytoplasmic proteins and likely represent false positives (3%) associated with the PhoA fusion technique. A second class of false positives, not counted in the 310 successful fusions, occurred at a similar rate and included fusions to genes in the opposite orientation of the 'phoA gene. The false positives found in the PhoA screen do not overlap with the false positives found in the computational screen and, had the computational screen not been performed, would have gone unnoticed. The remaining proteins without a predicted signal peptide exhibited significant similarity to an exported protein and a bacterial cytoskeletal protein, however their export signals remain unclear. In summary, we used a combined computational and experimental approach to identify exported proteins in P. aeruginosa. Our approach illustrates the effectiveness of using two complementary methods for genome-wide analyses. Computational techniques have the advantage of yielding a large number of predictions—ideal for genome-wide studies—and when a consensus method is employed the number of false-positive results is reduced. Laboratory methods, although they generally provide fewer results, can both confirm predictions and reveal interesting cases meriting closer inspection, including erroneous annotations and potentially unusual sequence features. We believe that this combined analytical approach is readily adaptable to other bacteria—the increase of the breadth of training data available means that current export signal predictive methods can be applied to a diverse range of organisms with accurate results, and the PhoA fusion is commonly used to study exported proteins. In addition to creating the P. aeruginosa signal peptide data set described in this report (Supplemental Table 1), we have provided laboratory-based experimental evidence to confirm the export of 14% of the predicted export candidates, as well as the existence of 150 proteins annotated as hypothetical or conserved hypothetical. The genome-wide identification of exported proteins will help define this important subset of the P. aeruginosa genome and may assist in the discovery of novel drug targets.
Data set The version of the P. aeruginosa PAO1 genome used in the present analysis was downloaded from http://www.pseudomonas.com, updated June 10, 2004. This version of the genome contains 5570 proteins.
Prediction of N-terminal signal sequences
Sequences of type IV prepilin precursors and related proteins (Lory 1994
Possible TAT substrates were identified by searching for occurrences of the RRXFL[KR] motif (Chaddock et al. 1995
Proteins utilizing a transmembrane helix for targeting were identified by both Phobius and TMHMM (Krogh et al. 2001
Construction of a P. aeruginosa-PhoA fusion library
We thank Agnes Kwasnika, Amélie Casgrain, and Jiesong Hua for their technical assistance. S.L. is supported by a Canadian Cystic Fibrosis Foundation (CCFF) fellowship. J.L.G. and F.S.L.B. are a Michael Smith Foundation for Health Research trainee and scholar, respectively. R.E.W.H. holds a Canada Research Chair. Funding for this research was from the FPMI program supported by Genome Canada, the Canadian Institutes of Health Research (CIHR), and from CCFF.
3 Corresponding author. E-mail bob{at}cmdr.ubc.ca; fax (604) 827-5566.  Article and publication are at http://www.genome.org/cgi/doi/10.1101/gr.3257305. [Supplemental information is available online at www.genome.org.]
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ABSTRACT
Results
helices and recognition by the SRP is sufficient for membrane-targeting (de Gier et al. 1998
pH-dependent thylakoidal protein translocase. EMBO J. 14: 2715-2722.
