Change search
ReferencesLink to record
Permanent link

Direct link
RSpred, a set of Hidden Markov Models to detect and classify the RIFIN and STEVOR proteins of Plasmodium falciparum
Karolinska Institute.
Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
Karolinska Institute.
Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
2011 (English)In: BMC GENOMICS, ISSN 1471-2164, Vol. 12, no 119Article in journal (Refereed) Published
Abstract [en]

Background: Many parasites use multicopy protein families to avoid their hosts immune system through a strategy called antigenic variation. RIFIN and STEVOR proteins are variable surface antigens uniquely found in the malaria parasites Plasmodium falciparum and P. reichenowi. Although these two protein families are different, they have more similarity to each other than to any other proteins described to date. As a result, they have been grouped together in one Pfam domain. However, a recent study has described the sub-division of the RIFIN protein family into several functionally distinct groups. These sub-groups require phylogenetic analysis to sort out, which is not practical for large-scale projects, such as the sequencing of patient isolates and meta-genomic analysis. Results: We have manually curated the rif and stevor gene repertoires of two Plasmodium falciparum genomes, isolates DD2 and HB3. We have identified 25% of mis-annotated and similar to 30 missing rif and stevor genes. Using these data sets, as well as sequences from the well curated reference genome (isolate 3D7) and field isolate data from Uniprot, we have developed a tool named RSpred. The tool, based on a set of hidden Markov models and an evaluation program, automatically identifies STEVOR and RIFIN sequences as well as the sub-groups: A-RIFIN, B-RIFIN, B1-RIFIN and B2-RIFIN. In addition to these groups, we distinguish a small subset of STEVOR proteins that we named STEVOR-like, as they either differ remarkably from typical STEVOR proteins or are too fragmented to reach a high enough score. When compared to Pfam and TIGRFAMs, RSpred proves to be a more robust and more sensitive method. We have applied RSpred to the proteomes of several P. falciparum strains, P. reichenowi, P. vivax, P. knowlesi and the rodent malaria species. All groups were found in the P. falciparum strains, and also in the P. reichenowi parasite, whereas none were predicted in the other species. Conclusions: We have generated a tool for the sorting of RIFIN and STEVOR proteins, large antigenic variant protein groups, into homogeneous sub-families. Assigning functions to such protein families requires their subdivision into meaningful groups such as we have shown for the RIFIN protein family. RSpred removes the need for complicated and time consuming phylogenetic analysis methods. It will benefit both research groups sequencing whole genomes as well as others working with field isolates. RSpred is freely accessible via http://www.ifm.liu.se/bioinfo/.

Place, publisher, year, edition, pages
BioMed Central , 2011. Vol. 12, no 119
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-66897DOI: 10.1186/1471-2164-12-119ISI: 000288128400001OAI: oai:DiVA.org:liu-66897DiVA: diva2:405244
Note
Original Publication: Nicolas Joannin, Yvonne Kallberg, Mats Wahlgren and Bengt Persson, RSpred, a set of Hidden Markov Models to detect and classify the RIFIN and STEVOR proteins of Plasmodium falciparum, 2011, BMC GENOMICS, (12), 119. http://dx.doi.org/10.1186/1471-2164-12-119 Licensee: BioMed Central http://www.biomedcentral.com/ Available from: 2011-03-21 Created: 2011-03-21 Last updated: 2011-03-30

Open Access in DiVA

fulltext(535 kB)159 downloads
File information
File name FULLTEXT01.pdfFile size 535 kBChecksum SHA-512
93a9c7598cb8cd00759133d155cd7e77cf2be28c8c36fddcac41880d5cde3a97f2d187b52034484f59e8b97c43620ef2ba64c4d14ce3581197c81bfa91af1863
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Kallberg, YvonnePersson, Bengt
By organisation
Bioinformatics The Institute of Technology
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 159 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 82 hits
ReferencesLink to record
Permanent link

Direct link