FIGURA 6 Brillo Solar
CUENCA SUBCUENCA MICROCUENCA AFLUENTES MICROCUENCAS
2.6Discussion
This work has applied current sequencing technologies and genomics to investigate genetic diversity, and the effect of immunity and antimalarial drugs selection on Malawi P. falciparum genomes. Studies of this kind have successfully identified drug-‐resistance mechanisms and targets of naturally-‐acquired immunity as candidate vaccine targets (Kidgell et al. 2006; Mackinnon and Marsh 2010), but have not yet been conducted in Malawi P. falciparum populations. Here examination of genetic variation is provided in parasites from Chikwawa district, Malawi, where the parasite population is exposed to naturally-‐acquired immunity and was recently exposed to intense pressure from IRS, ITNs, and ACTs. Previous studies have shown that human immune pressure produces genomic regions with high levels of nucleotide diversity, while antimalarial drug pressure results in regions with low diversity and extended haplotypes (Mu et al. 2007, 2010; Sabeti et al. 2006; Dharia et al. 2010; Volkman et al. 2007). This work has used population genetics metrics exploiting these two principles to detect loci under balancing and positive selection in a Malawi P. falciparum population. This population was also compared to five geographically dispersed others using FST and XP-‐EHH to detect regions of genetic divergence and signatures of recent selective sweeps, respectively. In particular, searching for high-‐scoring SNP clusters gave strong indicators of positive selection.
Analysis using Tajima’s D identified potential genomic regions under balancing selection, including six genes encoding merozoite invasion ligands: msp3.8, msp3, dbl-‐msp, eba175, ama1 and surfin4.2. These antigens are exposed to the immune system on the surface of merozoites or during erythrocyte invasion, and are highly polymorphic. Thus, balancing selection at these genes maybe mediated by host immune system as previously reported and have also been listed as possible candidates for vaccines in previous studies
(Alexandre et al. 2011; Baum et al. 2003; Polley and Conway 2001; Ochola et al. 2010; Tetteh et al. 2009; Mu et al. 2010; Amambua-‐Ngwa et al. 2012b).
Positive directional selection was detected in genomic regions near or surrounding drug targets (pfmdr1, pfcrt, pfdhps and gch1) and in surface antigens such as trap, ron2, msp3.8, ama1 and msp7 genes with important roles in invasion of host cells (Vulliez-‐Le Normand et al. 2012; Tufet-‐Bayona et al. 2009; Ghosh et al. 2009). Interestingly, several FST test results reflect parasite adaptation to local drug selection. First, low FST values in pfcrt-‐ K76T between Malawi and Kenya may reflect the withdrawal of CQ in these regions and subsequent disparity in the reduction in the prevalence of resistance alleles to 2-‐4% in Malawi and 60% in Kenya (Nkhoma et al. 2007; Mwai et al. 2009). Second, the FST values in
pfcrt-‐K76T between Malawi and Burkina Faso, and Malawi-‐Mali are heterogeneous and may suggest varying allele frequencies of K76T allele between Mali and Burkina Faso. Third, high FST values in pfcrt-‐K76T between Malawi and Cambodia, and Malawi-‐Mali, suggest that this mutation has reached fixation in Cambodia and Thailand; indeed, CQ remains the first-‐line treatment for P. vivax malaria in these two countries and thus may continue to select for the resistant genotype (Setthaudom et al. 2011). Fourth, fixation of pfdhps-‐K540E between Malawi and Mali, and Malawi-‐Burkina Faso may reflect the use of SP for the treatment of uncomplicated malaria and as intermittent preventive treatment in the two west-‐African countries, where the pfdhps-‐K540E mutation is rare (Pearce et al. 2009; Somé et al. 2010; Dicko et al. 2010). High prevalence of pfdhps-‐K540E and A437G is consistent with 90% prevalence of quintuple mutants in Malawi (Nkhoma et al. 2007) and while 437G is found all over Africa the 540E is largely absent in west Africa (Table 2.8). Whilst, FST may reflect differences in allele frequency due to differential selective pressure, they may also reflect
simply random genetic drift. FST is dependent on absolute diversity, where regions of low diversity in either population (or both) can result in high values, even if those regions have not been selected differently.
Positive directional selection in chromosome 12 containing pfgch1 and transcription factors is also particularly interesting. In P. vivax it is thought to result from drug selection (Dharia et al. 2010). Mutations in these transcription factors are thought to be a source of increased genetic variability that regulate gene expression whose products may include drug-‐resistance genes (Levine and Tjian 2003). Increased expression levels of pvcrt have been observed in CQ-‐resistant parasites (Fernández-‐Becerra et al. 2009), and higher expression levels of pvdhfr occurred in P. vivax isolates relative to P. falciparum, resulting in the proposal that evolution in response to drug and immune pressure might be driven by genetic changes in the corresponding transcription factors (Westenberger et al. 2010).
In conclusion, this chapter describes the sequencing of 93 P. falciparum clinical isolates sourced from uncomplicated malaria cases in Malawi and identification of loci under selection. In addition, positive selection signals are identified by comparing Malawi to five other dispersed P. falciparum populations. Further work could evaluate the role of these loci in malaria intervention strategies. For example, the genetic variation may enable monitoring of P. falciparum transmission dynamics as the epidemiology of malaria changes over time in response to interventions (Volkman et al. 2012). In particular, by using XP-‐EHH and FST it is shown that selection differences between geographically dispersed populations reflect the history of antimalarial drug use and selection at any given time, whereas during intense drug selection, wild-‐type alleles are increasingly replaced by mutant alleles. The ability to use this strategy to monitor local adaptation to drug pressure, monitoring
transmission, and inform the type and timing of interventions is appealing. This knowledge will now be used in Malawi to monitor the impact of ACTs, ITNs and IRS on the local parasite population of Chikwawa district over three malaria seasons.