In silico guided reconstruction and analysis of ICAM-1-binding var genes from Plasmodium falciparum

ICAM-1 Kilifi variant is not associated with cerebral and severe malaria pathogenesis in Beninese children

Background

Cytoadhesion and sequestration of Plasmodium falciparum infected red blood cells (iRBC) in the microvasculature of vital organs are a major cause of malaria pathology. Several studies have provided evidence on the implication of the human host intercellular adhesion molecule-1 (ICAM-1) as a major receptor for iRBCs binding to P. falciparum erythrocyte membrane protein 1 (PfEMP1) in the development of severe and cerebral malaria. The genetic polymorphism K29M in the immunoglobulin-like domain of ICAM-1, known as ICAM-1Kilifi, has been associated with either increased or decreased risk of developing cerebral malaria.

Methods

To provide more conclusive results, the genetic polymorphism of ICAM-1Kilifi was assessed by PCR and sequencing in blood samples from 215 Beninese children who presented with either mild or severe malaria including cerebral malaria.

Results and conclusions

The results showed that in this cohort of Beninese children, the ICAM-1kilifi variant is present at the frequencies of 0.27, similar to the frequency observed in other African countries. This ICAM-1kilifi variant was not associated with disease severity in agreement with other findings from the Gambia, Tanzania, Malawi, Gabon, and Thailand, suggesting no evidence of a direct link between this polymorphism and the pathogenesis of severe and cerebral malaria.

Varia: a tool for prediction, analysis and visualisation of variable genes

Background

Parasites use polymorphic gene families to evade the immune system or interact with the host. Assessing the diversity and expression of such gene families in pathogens can inform on the repertoire or host interaction phenotypes of clinical relevance. However, obtaining the sequences and quantifying their expression is a challenge. In Plasmodium falciparum, the highly polymorphic var genes encode the major virulence protein, PfEMP1, which bind a range of human receptors through varying combinations of DBL and CIDR domains. Here we present a tool, Varia, to predict near full-length gene sequences and domain compositions of query genes from database genes sharing short sequence tags. Varia generates output through two complementary pipelines. Varia_VIP returns all putative gene sequences and domain compositions of the query gene from any partial sequence provided, thereby enabling experimental validation of specific genes of interest and detailed assessment of their putative domain structure. Varia_GEM accommodates rapid profiling of var gene expression in complex patient samples from DBLα expression sequence tags (EST), by computing a sample overall transcript profile stratified by PfEMP1 domain types.

Results

Varia_VIP was tested querying sequence tags from all DBL domain types using different search criteria. On average 92% of query tags had one or more 99% identical database hits, resulting in the full-length query gene sequence being identified (> 99% identical DNA > 80% of query gene) among the five most prominent database hits, for ~ 33% of the query genes. Optimized Varia_GEM settings allowed correct prediction of > 90% of domains placed among the four most N-terminal domains, including the DBLα domain, and > 70% of C-terminal domains. With this accuracy, N-terminal domains could be predicted for > 80% of queries, whereas prediction rates of C-terminal domains dropped with the distance from the DBLα from 70 to 40%.

Conclusion

Prediction of var sequence and domain composition is possible from short sequence tags. Varia can be used to guide experimental validation of PfEMP1 sequences of interest and conduct high-throughput analysis of var type expression in patient samples.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04573-6.

Structural insights into diverse modes of ICAM-1 binding by Plasmodium falciparum-infected erythrocytes

A major determinant of pathogenicity in malaria caused by Plasmodium falciparum is the adhesion of parasite-infected erythrocytes to the vasculature or tissues of infected individuals. This occludes blood flow, leads to inflammation, and increases parasitemia by reducing spleen-mediated clearance of the parasite. This adhesion is mediated by PfEMP1, a multivariant family of around 60 proteins per parasite genome which interact with specific host receptors. One of the most common of these receptors is intracellular adhesion molecule-1 (ICAM-1), which is bound by 2 distinct groups of PfEMP1, A-type and B or C (BC)-type. Here, we present the structure of a domain from a B-type PfEMP1 bound to ICAM-1, revealing a complex binding site. Comparison with the existing structure of an A-type PfEMP1 bound to ICAM-1 shows that the 2 complexes share a globally similar architecture. However, while the A-type PfEMP1 bind ICAM-1 through a highly conserved binding surface, the BC-type PfEMP1 use a binding site that is more diverse in sequence, similar to how PfEMP1 interact with other human receptors. We also show that A- and BC-type PfEMP1 present ICAM-1 at different angles, perhaps influencing the ability of neighboring PfEMP1 domains to bind additional receptors. This illustrates the deep diversity of the PfEMP1 and demonstrates how variations in a single domain architecture can modulate binding to a specific ligand to control function and facilitate immune evasion.

From genomic to LC-MS/MS evidence: Analysis of PfEMP1 in Benin malaria cases

Background

PfEMP1 is the major protein from parasitic origin involved in the pathophysiology of severe malaria, and PfEMP1 domain subtypes are associated with the infection outcome. In addition, PfEMP1 variability is endless and current publicly available protein repositories do not reflect the high diversity of the sequences of PfEMP1 proteins. The identification of PfEMP1 protein sequences expressed with samples remains challenging. The aim of our study is to identify the different PfEMP1 proteins variants expressed within patient samples, and therefore identify PfEMP1 proteins domains expressed by patients presenting uncomplicated malaria or severe malaria in malaria endemic setting in Cotonou, Benin.

Methods

We performed a multi-omic approach to decipher PfEMP1 expression at the patient’s level in different clinical settings. Using a combination of whole genome sequencing approach and RNA sequencing, we were able to identify new PfEMP1 sequences and created a new custom protein database. This database was used for protein identification in mass spectrometry analysis.

Results

The differential expression analysis of RNAsequencing data shows an increased expression of the var domains transcripts DBLα1.7, DBLα1.1, DBLα2 and DBLβ12 in samples from patients suffering from Cerebral Malaria compared to Uncomplicated Malaria. Our approach allowed us to attribute PfEMP1 sequences to each sample and identify new peptides associated to PfEMP1 proteins in mass spectrometry.

Conclusion

We highlighted the diversity of the PfEMP1 sequences from field sample compared to reference sequences repositories and confirmed the validity of our approach. These findings should contribute to further vaccine development strategies based on PfEMP1 proteins.