Brugia Malayi - Clark Science Center - Smith College

Testing the Ability of SecretomeP Prediction Software to Predict
Brugia malayi Secreted/Non-Secreted Proteins.
Djénè Keita
A
B
Figure 1A and 1B: SecretomeP predictions of 973 known secreted 1 and 503 non-secreted proteins 2 of Brugia malayi. Protein
predictions were classified according to their NN-Score. Classically secreted proteins had an NN-Score≥0.5 with a signal peptide.
Non-classically secreted protein predictions had an NN-score ≥ 0.5. Non-secreted protein predictions had an NN-score of
< 0.5. Non-secreted proteins with a signal peptide had an NN-Score < 0.5 (suggesting membrane proteins). Unknown proteins
predictions were the uncharacterized by SecretomeP. Proteins from Figure B within the non-secreted proteins were previously
identified as cytoplasmic, nuclear regulation, cytoskeletal, or transcription.
Bioinformatics is a field that uses computer technology to collect, store, analyze and integrate biological and genetic
information, which can then be applied to many scientific investigations such as gene-based drug discovery and development.
Brugia malayi is one of the causative agents of lymphatic filariasis, a tropical disease responsible for incapacitating more than 120
million people in the tropical and subtropical areas of Africa and Asia. Much work involving lymphatic filariasis has focused
on analyzing secreted proteins because these proteins are the logical proteins to analyze when looking for highly immunogenic
epitopes. This is because it is these secreted/excreted proteins that most readily come in contact with our immune-type cells. The
focus of my work was to test the ability of SecretomeP prediction software to predict unknown B. malayi proteins by first screening
known B. malayi secreted/non-secreted proteins cited in previous work on lymphatic filariasis. Accordingly, 973 secreted 1 and 503
non-secreted 2 proteins were obtained from the published literature. FASTA files of each of these proteins were manually created
using Genbank. These files were run through SecretomeP. Of the known secreted proteins, SecretomeP was only able to predict
51% of proteins to be secreted (classically and non-classically)[Figure 1A]. Meanwhile, only 55% of the proteins from the nonsecreted
data file were predicted to be non-secreted [Figure 1B]. These results indicate that SecretomeP is not a good prediction
software to use to predict B. malayi secreted and non-secreted proteins because it had a poor rate of prediction rate within each
set of known proteins. It is a poor prediction software for B. malayi proteins and it cannot be used to either verify known B. malayi
proteins or classify unknown proteins. (Supported by the Schultz Foundation)
Advisor: Steven Williams
References:
1
Bennuru S, Semnani R, Meng Z, Ribeiro JMC, Veenstra TD, et al. (2009) Brugia malayi Excreted/Secreted Proteins at the Host/Parasite Interface: Stage- and Gender-
Specific Proteomic Profiling. PLoS Negl Trop Dis 3(4): e410. doi:10.1371/journal.pntd.0000410.
2
Bennuru S, Meng Z, Ribeiro JM, Semnani RT, Ghedin E, et al. (2011) Stagespecific proteomic expression patterns of the human filarial parasite Brugia malayi and
its endosymbiont Wolbachia. Proc Natl Acad Sci U SA 108: 9649–9654.
2012
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