Polymorphisms in the Plasmodium falciparum Erythrocyte Membrane Protein1 (Pfemp1) Gene at Two Malaria Endemic Sites in Kenya

Abstract

The variant Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) found on infected erythrocyte surface in malaria patients is encoded by Pfemp1 gene. This protein has been implicated in mediating different forms of malaria pathology such as rosseting of infected erythrocytes and cytoadherence of infected erythrocytes on endothelial cells of blood capillaries. This results in severe forms of the disease such as cerebral malaria and severe anemia. This PfEMP1 protein also mediates antigenic variation by P. falciparum thus rendering immune responses ineffective. PfEMP1 is coded for by highly variable var genes, with each parasite haploid genome containing over sixty copies of the gene. Only one gene is expressed at a given time and the expression pattern is mutually exclusive.The broad aim of this project was to profile the sequence tags of the DBLα domain of Pfemp1 genes in field isolates from the two malaria endemic sites. Blood samples from malaria positive patients were collected on Whatmann filter paper during a clinical field study at Mbita (Western Kenya) and Tiwi (Coastal Region, Kwale). Parasite DNA was extracted from the samples followed by PCR analysis using primers that target the DBLα domain of Pfemp1 genes. Some of the PCR product was sequenced by 454-next generation sequencing, Roche. The sequence reads were then translated into protein sequences of DBLα sequence tags and classified into various groups based on the number of cysteine residues in the sequence and positions of limited variations (PoLVs). This analysis revealed that group1/group1-like DBLα sequence tags were more prevalent in isolates from Tiwi than those from Mbita. Group 1 sequences are associated with expression of group A var genes that have been associated to severe malaria symptoms. Their presence in these isolates indicated that the patients from both sites were prone to developing severe symptoms like cerebral malaria and severe malarial aneamia. It was also found that group 4 sequence tags were the most frequent tags in field isolates from both study sites. These sequence tags have been associated to the expression of group B and C var genes. Expression of these genes is associated to mild symptoms of malaria. The sequence data can predicatively indicate the level of disease severity the circulating parasite population can course. Since the binding capacity of particular sequence types does not depend on expression level, these results suggested that the patients could have progressed to develop severe forms of malaria had they not be taken for early intervention. The high frequency of group-4 DBLα sequence tags indicated that a majority of the patients had started developing semi-immunity to malaria since they predict mild forms of malaria symptoms. A further analysis of sequence tags revealed sequences which were absent in the database after a Blast search at NCBI. This study therefore reports sequences unique to field isolates from the study sites. Further, it was observed that one sequence tag from Tiwi isolates possessed both MFK and REY motifs at PoLV1 and PoLV2 respectively. These two motifs have been found to be mutually exclusive hence this observation suggests that there is a possibility for the two motifs to co-exist in the same sequence tag although the chances of co-existence remain rare.A network was constructed to assess the genetic relationship between sequence tags based on position specific polymorphic blocks (PSPBs) in DBLα sequence tags. Sequences from Mbita study site and those from Tiwi largely clustered into separate giant networks with only a limited number of sequences from the two sites linking to each other. This observation suggested that parasite populations from the two endemic sites could be genetically distinct and that PfEMP1 sequencing could be a useful tool of understanding the genetics of parasite populations. This observation could also inform future efforts in the development of malaria vaccine. Thus the network approach of studying relationships between DBLα sequences is a useful tool of uncovering the genetic structure of parasite populations circulating in different malaria endemic region