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. 2013;8(1):e54032.
doi: 10.1371/journal.pone.0054032. Epub 2013 Jan 17.

TFPP: an SVM-based tool for recognizing flagellar proteins in Trypanosoma brucei

Xiaobai Zhang  1 , Yuefeng Shen, Guitao Ding, Yi Tian, Zhenping Liu, Bing Li, Yun Wang, Cizhong Jiang
Affiliations

TFPP: an SVM-based tool for recognizing flagellar proteins in Trypanosoma brucei

Xiaobai Zhang et al. PLoS One. 2013.

Abstract

Trypanosoma brucei is a unicellular flagellated eukaryotic parasite that causes African trypanosomiasis in human and domestic animals with devastating health and economic consequences. Recent studies have revealed the important roles of the single flagellum of T. brucei in many aspects, especially that the flagellar motility is required for the viability of the bloodstream form T. brucei, suggesting that impairment of the flagellar function may provide a promising cure for African sleeping sickness. Knowing the flagellum proteome is crucial to study the molecular mechanism of the flagellar functions. Here we present a novel computational method for identifying flagellar proteins in T. brucei, called trypanosome flagellar protein predictor (TFPP). TFPP was developed based on a list of selected discriminating features derived from protein sequences, and could predict flagellar proteins with ∼92% specificity at a ∼84% sensitivity rate. Applied to the whole T. brucei proteome, TFPP reveals 811 more flagellar proteins with high confidence, suggesting that the flagellar proteome covers ∼10% of the whole proteome. Comparison of the expression profiles of the whole T. brucei proteome at three typical life cycle stages found that ∼45% of the flagellar proteins were significantly changed in expression levels between the three life cycle stages, indicating life cycle stage-specific regulation of flagellar functions in T. brucei. Overall, our study demonstrated that TFPP is highly effective in identifying flagellar proteins and could provide opportunities to study the trypanosome flagellar proteome systematically. Furthermore, the web server for TFPP can be freely accessed at http:/wukong.tongji.edu.cn/tfpp.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. ROC curve of TFPP.
AUC is 0.9272.
Figure 2
Figure 2. Statistical relationship between the prediction precision and the prediction score.
For the purpose of display, the x-axis is the absolute value of prediction score.
See this image and copyright information in PMC

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Publication types

Grants and funding

This work was supported by the National Natural Science Foundation of China [31200952 to X.Z.]; New Century Talent Project of Ministry of Education of China to [NCET-10-0600 to C.J.]; Aurora Talent Project of Shanghai [10SG24 to C.J.]; and Pujiang Talent Project of Shanghai [10PJ1409500 to C.J.]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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