Plasmodium falciparumpopulation genetic complexity influences transcriptional profile and immune recognition of highly related genotypic clusters

Abstract

As transmission intensity has declined in Senegal, so has the genetic complexity of circulating Plasmodium falciparum parasites, resulting in specific genotypes emerging and persisting over years. We address whether changes in parasite genetic signatures can alter the immune repertoire to variant surface antigens, and whether such responses can influence the expansion or contraction of specific parasite genotypes in the population. We characterize parasites within genotypic clusters, defined as identical by a 24-SNP molecular barcode and a haplotype identifier for other highly polymorphic loci; we measure expression of variant surface antigens (VSA) such as PfEMP-1 by transcript expression typing and expressed var DBL1α sequencing in ex vivo and short-term adapted RNA samples; and we measure IgG responses against VSAs from short-term adapted parasites. We find that parasites within genotypic clusters are genetically identical at other highly polymorphic loci. These parasites express similar Ups var classes and largely the same dominant var DBL1α sequences ex vivo. These parasites are recognized similarly by anti-VSA antibodies after short-term adaptation to culture; however, antibody responses do not correlate with genotype frequencies over time. Both genotype-specific and multiple genotype-reactive surface IgG responses are observed in this population. Parasites with identical genomes are extremely similar in their expression and host antibody recognition of VSAs. Monitoring changes in population-level parasite genomics and transmission dynamics is critical, as fluctuations will influence the breadth of resulting host immune responses to circulating parasite genotypes. These findings suggest shared immune recognition of genetically similar parasites, which has implications for both our understanding of immunity and vaccine development strategies in malaria elimination settings.

Estimating the overlap between two malaria parasites’ var repertoires

“…5; right), with the majority of estimates showing an uncertainty greater than 30 sequences (50% overlap). For comparison, estimates from Thiès, Senegal [13] (n = 36.0) are also shown, whose dramatically lower uncertainty enables more confident conclusions to be drawn.…”

“…For instance, when two parasites are completely different, n ab = 0, so PTS = 0; when two parasites are identical, and both repertoires have been fully sampled, n ab = n a = n b , so PTS = 1. However, when n a or n b is smaller (as is overwhelmingly the case in existing studies [7][8][9][10][11][12][13]) PTS is conservative and systematically underestimates the true overlap between repertoires [20]. For example, if we were able to fully sample two parasites that share 30 of their 60 var tags, their PTS would be 0.5.…”

“…Recent studies of P. falciparum epidemiology and evolution have begun to learn from comparisons of the sets of genomic var repertoires between parasites [7][8][9][10][11][12][13]. Since var repertoires are, themselves, under selection, theory suggests that if a human population has been exposed to particular var genes, then repertoires that contain those var genes will have a lower fitness than repertoires that are entirely unrecognized by local hosts, shaping the var population structure [14,15].…”

“…A followup study to Ref. [10] found that var repertoires in a region of decreasing transmission have coalesced into highly related clusters that appear to be non-overlapping with each other, driven by local immune * daniel.larremore@colorado.edu adaptation [13], although at the time of writing this study remains under peer review (June, 2018). Methods by which we estimate the extent to which var repertoires overlap are therefore important, particularly as studies of the population genetics and genetic epidemiology of malaria's antigens become more sophisticated and data rich.…”

“…Instead, experimentalists use degenerate PCR primers targeting a small "tag" sequence within a particular domain called DBLα [16] which is found in almost all var genes. Due to their experimental accessibility, DBLα tags have been widely used to study the structure and function of var genes [1,6,7,10,13,[16][17][18][19]. Still, these PCR techniques generate a random sample of 60 or fewer unique tag sequences from each parasite.…”