TFPP: an SVM-based tool for recognizing flagellar proteins in Trypanosoma brucei.
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.
Department of Bioinformatics, the School of Life Sciences and Technology, Tongji University, Shanghai, China. zhangxb@tongji.edu.cn
Xiaobai
X
Zhang
Yuefeng
Y
Shen
Guitao
G
Ding
Yi
Y
Tian
Zhenping
Z
Liu
Bing
B
Li
Yun
Y
Wang
Cizhong
C
Jiang
D000818:Animals; D019295:Computational Biology / Q000379:methods*; D005407:Flagella / Q000235:genetics / Q000378:metabolism*; D015870:Gene Expression; D006790:Host-Parasite Interactions; D006801:Humans; D020407:Internet; D020543:Proteome / Q000235:genetics / Q000378:metabolism; D015800:Protozoan Proteins / Q000235:genetics / Q000378:metabolism*; D015203:Reproducibility of Results; D060388:Support Vector Machine; D014346:Trypanosoma brucei brucei / Q000235:genetics / Q000378:metabolism* / Q000502:physiology; D014353:Trypanosomiasis, African / Q000469:parasitology
D020543:Proteome; D015800:Protozoan Proteins