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