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Do pathogenic bacteria encode more secreted proteins than their non-pathogenic relatives?

Background

Pathogenic and non-pathogenic bacteria secrete proteins for nutrient acquisition, cell-cell communication, and niche adaptation [1]. We hypothesized that pathogenic bacteria may encode larger fractions of secreted proteins (fsp) than their non-pathogenic relatives, assuming that pathogens might be under selective pressure to secrete virulence proteins involved in host immune evasion, invasion, and toxigenesis. To test this hypothesis, we compared the Sec-dependent fsp of various gram-positive and gram-negative bacteria and investigated the relation between the fsp and pathogenic potential of an organism.

Methods

We developed a pipeline that starts by a Perl script that truncates protein sequences to 70 amino acids or fewer followed by the application of existing signal prediction tools [24] and ends by the statistical analysis of the prediction data. For subsequent comparative secretome analyses, we used both the hidden Markov models- and the neural networks-based methods implemented in the SignalP 3.0 algorithm [2] (URL: http://www.cbs.dtu.dk/services/SignalP) with modified thresholds. We used DataDesk (Data Description, Inc., Ithaca, NY; URL: http://www.datadesk.com) for all statistical analyses (including correlation analysis, analysis of variance, and multivariate analysis) and for plotting the results.

Results

We determined the theoretical secretomes of 176 chromosomes and 115 plasmids in five gram-positive and five gram-negative bacterial genera containing pathogenic and non-pathogenic members (Figure 1). Our analysis showed significant differences in chromosomally encoded fsp between gram-positive and gram-negative bacteria (chromosomes of gram-negative bacteria have larger fsp), while there was no particular pattern in plasmid-encoded fsp. Whereas the overall difference between pathogenic and non-pathogenic species was not statistically significant, significant correlation was observed between fsp and pathogenesis in gram-positive cocci. For example, pathogenic Staphylococcus aureus have higher fsp than other staphylococci, while the non-pathogenic Streptococcus thermophilus has the lowest fsp of all streptococci (Figure 2).

Figure 1
figure1

Predicted fractions of secreted proteins by the chromosomes of ten bacterial genera with pathogenic and non-pathogenic member. NN = neural networks method; HMM = hidden Markov models method.

Figure 2
figure2

Pathogenic Gram-positive cocci encode larger fractions of secreted proteins than non-pathogenic relatives. NN = neural networks method; HMM = hidden Markov models method. (A) Staphylococcal species (epid = epiderimidis; haemo = haemolyticus; sapro = saprophyticus). (B) Streptococcal species (aga = agalactiae; pneu = pneumoniae; pyog = pyogenes; ther = thermophilus) P values: aureus vs. all: P < 10-6; ther vs. all: P = 0.002 (NN), 0.0001 (HMM); agal vs. pyog: P = 0.012 (NN), 0.003 (HMM).

Conclusion

We developed a pipeline for the determination and comparison of fractions of secreted proteins in bacterial genomes, and observed significant differences between pathogenic and non-pathogenic species of staphylococci and streptococci.

References

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    Zhou M, Boekhorst J, Francke C, Siezen RJ: LocateP: genome-scale subcellular- location predictor for bacterial proteins. BMC Bioinformatics 2008, 9: 173. 10.1186/1471-2105-9-173

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Correspondence to Ramy Karam Aziz.

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Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Mahmoud, A.A., Aziz, R.K. Do pathogenic bacteria encode more secreted proteins than their non-pathogenic relatives?. BMC Bioinformatics 11, P28 (2010). https://doi.org/10.1186/1471-2105-11-S4-P28

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Keywords

  • Hide Markov Model
  • Secrete Protein
  • Pathogenic Bacterium
  • Perl Script
  • Immune Evasion