Characterization of Plasmodium falciparum structure in Nigeria with malaria SNPs barcode

Malaria caused by Plasmodium falciparum is still a major health challenge in Nigeria despite the global decline of its incidence and mortality rate [1]. Malaria is estimated to kill between 81,000–150,000 people yearly in Nigeria [1]. Even with the adoption of artemisinin-based combination therapy (ACT) as the first-line treatment in malaria, the use of intermittent preventive measures (IPT) for pregnant women, and the use of long-lasting insecticide-treated nets (LLIN), there has not been the expected reduction in the incidence, prevalence, or mortality of malaria in Nigeria [1]. As such, Nigeria alone is still contributing to 30% of the total world malaria burden. This situation underscores the need to develop and implement new tools to monitor parasite population dynamics and diversity in order to measure the impact and success of different intervention measures across Nigeria [2].

The use of molecular markers such as the merozoite surface protein 1 (msp1), merozoite surface protein 2 (msp2) and glutamine rich protein (glurp) to establish the population features of P. falciparum in various parts of Nigeria is well documented [3‐5]. The lack of a standard and/ reference for the interpretation of results across borders is a major disadvantage to the use of these techniques [6]. Microsatellites, which are short tandem repeats (STRs) in the genome of P. falciparum, have also been used in characterizing P. falciparum field isolates with good success [5]. The possibility of microsatellites rapidly evolving is a major challenge for use as genotyping technique [7].

The malaria barcode [8] is a combination of SNPs that express a unique pattern of variation on the P. falciparum genome sequence, combined with high-resolution melt (HRM) analysis [9] is more accurate in determining the population diversity of P. falciparum and has the ability to differentiate between closely related parasites. SNP genotyping approaches have also been used to evaluate interventions, pursue malaria elimination and monitor malaria transmission [10, 11]. HRM analysis is a simple polymerase chain reaction (PCR) performed under slightly different or modified conditions in the presence of a specific dye developed for the detection of DNA sequence variants [9]. HRM is based on amplicon melting in which the SNPs allele is determined by the melting curve, i.e., monitoring the dissociation rate of the DNA with a dye and plotting the progress as a melt curve [12]. The melt curve is determined by factors such as heterozygosity, GC content and sequence length. The P. falciparum barcode also uses separate probes for each assay, allowing better peak differentiation for more accurate SNPs genotyping, which makes it different from other HRM applications. The gradual increase in temperature during the melting stages of the HRM allows for the detection of slight genetic differences like SNPs. A major advantage the HRM SNP barcode has over the use of molecular polymorphic markers such as msp1, msp2 and glurp is the ability to detect changes in population structure such as decline or increase in transmission rate or relatedness of isolates based on identity by descent. However, this technique is not as effective in differentiating reinfection/recrudescence as in the polymorphic markers i.e., msp1 and msp2. Also, HRM is relatively easy to use, simple, flexible, low cost, non-destructive in nature, very sensitive and specific [8].

The 24-SNPs barcode assay can be used to detect changes in parasite population features by tracking parasite genotypes over time and through routes of vector and human migration [10]. For instance, it has been applied to show the emergence of highly related P. falciparum parasites in Senegal [10], interrogate the impact of intervention strategies in Zambia and Zimbabwe [11] and investigate outbreaks from clonal expansion of P. falciparum in Panama [9]. However, no such study has been conducted or reported in Nigeria. This study therefore seeks to leverage on this novel genotyping technique for the first time in Nigeria to study P. falciparum obtained from blood samples of children with uncomplicated malaria, to have an insight to the population structure of the parasite.

This study present the very first application of the 24-SNPs molecular barcode in effectively measuring inter and intra population diversity for P. falciparum samples in Nigeria. The HRM technique has been used to evaluate parasite population dynamics of P. falciparum in several parts of the world [8, 10, 20]. The HRM technique is a sensitive genotyping technique capable of identifying both known and novel polymorphisms, detect multiple genotypes that indicate mixed infections, distinguish between variants when multiple copies of a locus are present and easily deployable to field samples [21]. The knowledge of the distribution of complexity of infection (COI) across a patient population has been said to reveal information about disease transmission and epidemiology [22]. High complexity of infection has been found to be seasonal in Senegal and positively associated with the degree of parasitaemia in individual patients [23]. Over the years, the complexity of infection of P. falciparum in samples obtained from representative parts of the country has served as an indicator for transmission patterns of the parasite within the country and influenced various government control and intervention measures such as adoption of ACTs for malaria treatment, rapid diagnosis of all malaria cases, wider distribution of LLIN and quality monitoring of malaria cases to ensure the progressive control of malaria in Nigeria [24].

Previous molecular epidemiological studies showed high levels of polyclonal infections especially in malaria hyper endemic parts of the country, thus indicating high P. falciparum transmission within and between various parts of the country. For instance, Engelbrecht et al. [3] using the msp2 genotyping technique, reported polyclonal infections at 80% from samples obtained in the Northern region of Nigeria. Previous studies in Ibadan using msp2 reports 89–100% polygenomic infections in samples obtained prior to treatment [4, 25]. However, recent studies have presented the steady decline in clonality from polygenomic to monogenomic infections in Nigeria [5, 17, 26].

HRM has been reported to be a better genotyping technique over the use of length polymorphic markers such as msp2 [8], however Chi square analysis of prevalence of polygenomic infections in this study showed that there was no significant difference (Enugu, p = 0.46 and Ibadan p = 0.16) between both genotyping techniques. This may be due to small sample size used in the HRM analysis.

A major advantage the HRM technique has over other genotyping techniques such as msp1, msp2, and glurp is that the HRM is a more robust genotyping technique having the ability to resolve two closely related samples [8]. This is due to the wider SNPs coverage and also capability to determine other parameters that define population diversity.

Parasite population diversity parameters such as the AMAF and barcode π provide further insight to the nature of parasite diversity within Enugu and Ibadan. Baniecki et al. [12] had suggested that AMAF values higher than 0.1 represent a significant degree of diversity within that particular SNP of the barcode. In this study, AMAF values from both populations revealed a significant degree of SNP diversity (> 0.1) for all but one (assay 24: 0.02) SNPs of the 23 considered. The 24th SNP assay in the barcode showed 100% and 97% homogenicity for the reference allele in the Enugu and Ibadan parasite populations, respectively. This may be due to the absence of selective pressure for the alternate allele of this SNP in these 2 populations and regions. However, further barcoding assay of larger samples from these states and country in general may be required to confirm if the low occurrence of the alternate allele in the 24th SNP assay is a common trend. This may serve as a means of tracking transmission of parasite from other population with higher alternate allele occurrence. The barcode (π) was also determined to define the population diversity of the parasite in the two study sites. Results showed the π values 0.328 and 0.318 for Enugu and Ibadan respectively, suggest the existence of a low level of genetic diversity among the parasite in each of these populations. This may be due to a bottleneck caused as a result of selective pressures that eliminated other genetically diverse but susceptible P. falciparum clones originally present in these regions. The high prevalence of monoclonal infections observed in this study as well as other parameters determined in this study further supports evidence of the low genetic diversity of P. falciparum in these locations.

The population divergence of P. falciparum population between Ibadan and Enugu was investigated by computing population divergence features such as fixation index (F_ST) and principal component analysis (PCA). When SNP barcode data of two populations are analysed the F_ST value ranges from 1 (high divergence) to 0 (no divergence) [27]. In this study, F_ST value of 0.02 between Ibadan and Enugu parasite populations was observed. This suggests that there is low genetic variation in circulating P. falciparum parasites of both populations. Although these two regions are over 500 km away from one another, they are by no means isolated thus encouraging circulation of same parasite population. The lack of genetic variance observed in this study could be due to constant and ease of travel between the two cities, similar epidemiological conditions in both areas and/or similar selective pressure from the various control and management measures within the country at large. A recent study has shown that great geographical distance, even at the continental level, does not necessarily result in high level of genetic divergence between populations [12]. The PCA of both populations further confirmed the genetic similarities of P. falciparum in Enugu and Ibadan. A similar clustering patterns were observed between the parasite populations (Fig. 4).

Based on the observations of low genetic divergence between Enugu and Ibadan populations as well as the low intra population diversity in each population, its suggested that HRM technique, although may be more expensive can be used to investigate the current trend of population diversity and divergence in other parts of the country. This would provide sufficient information about the composition of parasite populations across Nigeria and significantly influence controls measure and intervention for the spread of malaria.

This work demonstrates, that the 24-SNP HRM barcode can effectively be used to monitor P. falciparum population diversity and divergence in Nigeria. Future work is to utilize this assay to build on this characterisation of parasite populations in regions of varying endemicity across the nation. Also, reports from other studies has shown that this technique can be used to monitor changes in parasite population diversity and clonality over time, transmission patterns, and emerging drug resistance which were not considered in this study and could be included in future studies in Nigeria. By building a more complete snapshot of P. falciparum infection, policy makers, drug developers, and healthcare professionals can be empowered to take informed action to further the goal of malaria elimination in Nigeria.