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Genome-Wide Identification of Molecular Mimicry Candidates in Parasites

Overview of attention for article published in PLOS ONE, March 2011
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Title
Genome-Wide Identification of Molecular Mimicry Candidates in Parasites
Published in
PLOS ONE, March 2011
DOI 10.1371/journal.pone.0017546
Pubmed ID
Authors

Philipp Ludin, Daniel Nilsson, Pascal Mäser

Abstract

Among the many strategies employed by parasites for immune evasion and host manipulation, one of the most fascinating is molecular mimicry. With genome sequences available for host and parasite, mimicry of linear amino acid epitopes can be investigated by comparative genomics. Here we developed an in silico pipeline for genome-wide identification of molecular mimicry candidate proteins or epitopes. The predicted proteome of a given parasite was broken down into overlapping fragments, each of which was screened for close hits in the human proteome. Control searches were carried out against unrelated, free-living eukaryotes to eliminate the generally conserved proteins, and with randomized versions of the parasite proteins to get an estimate of statistical significance. This simple but computation-intensive approach yielded interesting candidates from human-pathogenic parasites. From Plasmodium falciparum, it returned a 14 amino acid motif in several of the PfEMP1 variants identical to part of the heparin-binding domain in the immunosuppressive serum protein vitronectin. And in Brugia malayi, fragments were detected that matched to periphilin-1, a protein of cell-cell junctions involved in barrier formation. All the results are publicly available by means of mimicDB, a searchable online database for molecular mimicry candidates from pathogens. To our knowledge, this is the first genome-wide survey for molecular mimicry proteins in parasites. The strategy can be adopted to any pair of host and pathogen, once appropriate negative control organisms are chosen. MimicDB provides a host of new starting points to gain insights into the molecular nature of host-pathogen interactions.

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Geographical breakdown

Country Count As %
United Kingdom 3 3%
United States 2 2%
Brazil 2 2%
France 1 <1%
Spain 1 <1%
Australia 1 <1%
Unknown 101 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 25%
Researcher 23 21%
Student > Master 9 8%
Student > Bachelor 9 8%
Student > Doctoral Student 6 5%
Other 16 14%
Unknown 20 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 48 43%
Biochemistry, Genetics and Molecular Biology 13 12%
Medicine and Dentistry 9 8%
Computer Science 4 4%
Social Sciences 4 4%
Other 12 11%
Unknown 21 19%