Identification of plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models

Daniel Restrepo-Montoya, David Becerra, Juan G. Carvajal-Patiño, Alvaro Mongui, Luis F. Niño, Manuel E. Patarroyo, Manuel A. Patarroyo

Resultado de la investigación: Contribución a RevistaArtículo

9 Citas (Scopus)

Resumen

Background: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. Results: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. Conclusions: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria. © 2011 Restrepo-Montoya et al.
Idioma originalEnglish (US)
PublicaciónPLoS One
DOI
EstadoPublished - oct 3 2011

Huella dactilar

Plasmodium vivax
Hidden Markov models
Redundancy
Proteins
proteins
Computational Biology
bioinformatics
Bioinformatics
erythrocytes
Vaccines
Erythrocytes
Classifiers
Vivax Malaria
Immunology
reticulocytes
cell invasion
Drug Design
Reticulocytes
vaccine development
Gene encoding

Citar esto

Restrepo-Montoya, Daniel ; Becerra, David ; Carvajal-Patiño, Juan G. ; Mongui, Alvaro ; Niño, Luis F. ; Patarroyo, Manuel E. ; Patarroyo, Manuel A. / Identification of plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models. En: PLoS One. 2011.
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title = "Identification of plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models",
abstract = "Background: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. Results: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. Conclusions: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria. {\circledC} 2011 Restrepo-Montoya et al.",
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year = "2011",
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Identification of plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models. / Restrepo-Montoya, Daniel; Becerra, David; Carvajal-Patiño, Juan G.; Mongui, Alvaro; Niño, Luis F.; Patarroyo, Manuel E.; Patarroyo, Manuel A.

En: PLoS One, 03.10.2011.

Resultado de la investigación: Contribución a RevistaArtículo

TY - JOUR

T1 - Identification of plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden Markov models

AU - Restrepo-Montoya, Daniel

AU - Becerra, David

AU - Carvajal-Patiño, Juan G.

AU - Mongui, Alvaro

AU - Niño, Luis F.

AU - Patarroyo, Manuel E.

AU - Patarroyo, Manuel A.

PY - 2011/10/3

Y1 - 2011/10/3

N2 - Background: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. Results: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. Conclusions: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria. © 2011 Restrepo-Montoya et al.

AB - Background: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. Results: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. Conclusions: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria. © 2011 Restrepo-Montoya et al.

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DO - 10.1371/journal.pone.0025189

M3 - Article

JO - PLoS One

JF - PLoS One

SN - 1932-6203

ER -