Decreased In Vitro Artemisinin Sensitivity of Plasmodium falciparum across India.

Artemisinin-based combination therapy (ACT) has been used to treat uncomplicated Plasmodium falciparum infections in India since 2004. Since 2008, a decrease in artemisinin effectiveness has been seen throughout the Greater Mekong Subregion. The geographic proximity and ecological similarities of northeastern India to Southeast Asia may differentially affect the long-term management and sustainability of ACT in India. In order to collect baseline data on variations in ACT sensitivity in Indian parasites, 12 P. falciparum isolates from northeast India and 10 isolates from southwest India were studied in vitro Ring-stage survival assay (RSA) showed reduced sensitivity to dihydroartemisinin in 50% of the samples collected in northeast India in 2014 and 2015. Two of the 10 assayed samples from the southwest region of India from as far back as 2012 also showed decreased sensitivity to artemisinin. In both these regions, kelch gene sequences were not predictive of reduced artemisinin sensitivity, as measured by RSA. The present data justify future investments in integrated approaches involving clinical follow-up studies, in vitro survival assays, and molecular markers for tracking potential changes in the effectiveness of artemisinin against P. falciparum throughout India.

Karyotypic assignment of Sri Lankan Anopheles culicifacies species B and E does not correlate with cytochrome oxidase subunit I and microsatellite genotypes.

BACKGROUND: The identification of species B and E in the Anopheles culicifacies complex in the Indian subcontinent has been based on Y-chromosome karyotype. Since no detectable variations were previously found in DNA markers commonly used for sibling species identification, further molecular characterization using cytochrome oxidase subunit I (COI) and microsatellite markers was carried out on Y-chromosome karyotyped Anopheles culicifacies specie B and E from Unnichchai, Kallady and Ranawarunawa in Sri Lanka. FINDINGS: COI sequence analysis (n = 22) revealed the presence of nine unique haplotypes with six in each species. Three haplotypes were shared by both species. The two sibling species had a pairwise FST value of 1.338 (p < 0.05) with the number of migrants (Nm) value <1. The genetic structure analysis resulted in two genetic clusters not 100% associated with karyotypes. While none of the species B were incorrectly assigned two were inconclusive. Five out of 26 specimens karyotyped as species E were incorrectly assigned, while further 9 were inconclusive. CONCLUSIONS: The new molecular data support the existence of two genetically different populations of the Culicifacies Complex in Sri Lanka that are not associated with the Y-chromosome karyotype. Detailed analysis with more microsatellite markers and assortative mating experiments are needed to establish the presence of the two genetically distinct populations and relate them to Y-chromosome morphology.

Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions, local adaptation and geographic structure.

Recent advances in sequencing allow population-genomic data to be generated for virtually any species. However, approaches to analyse such data lag behind the ability to generate it, particularly in nonmodel species. Linkage disequilibrium (LD, the nonrandom association of alleles from different loci) is a highly sensitive indicator of many evolutionary phenomena including chromosomal inversions, local adaptation and geographical structure. Here, we present linkage disequilibrium network analysis (LDna), which accesses information on LD shared between multiple loci genomewide. In LD networks, vertices represent loci, and connections between vertices represent the LD between them. We analysed such networks in two test cases: a new restriction-site-associated DNA sequence (RAD-seq) data set for Anopheles baimaii, a Southeast Asian malaria vector; and a well-characterized single nucleotide polymorphism (SNP) data set from 21 three-spined stickleback individuals. In each case, we readily identified five distinct LD network clusters (single-outlier clusters, SOCs), each comprising many loci connected by high LD. In A. baimaii, further population-genetic analyses supported the inference that each SOC corresponds to a large inversion, consistent with previous cytological studies. For sticklebacks, we inferred that each SOC was associated with a distinct evolutionary phenomenon: two chromosomal inversions, local adaptation, population-demographic history and geographic structure. LDna is thus a useful exploratory tool, able to give a global overview of LD associated with diverse evolutionary phenomena and identify loci potentially involved. LDna does not require a linkage map or reference genome, so it is applicable to any population-genomic data set, making it especially valuable for nonmodel species.

Molecular characterization and identification of members of the Anopheles subpictus complex in Sri Lanka.

BACKGROUND: Anopheles subpictus sensu lato is a major malaria vector in South and Southeast Asia. Based initially on polytene chromosome inversion polymorphism, and subsequently on morphological characterization, four sibling species A-D were reported from India. The present study uses molecular methods to further characterize and identify sibling species in Sri Lanka. METHODS: Mosquitoes from Sri Lanka were morphologically identified to species and sequenced for the ribosomal internal transcribed spacer-2 (ITS2) and the mitochondrial cytochrome c oxidase subunit-I (COI) genes. These sequences, together with others from GenBank, were used to construct phylogenetic trees and parsimony haplotype networks and to test for genetic population structure. RESULTS: Both ITS2 and COI sequences revealed two divergent clades indicating that the Subpictus complex in Sri Lanka is composed of two genetically distinct species that correspond to species A and species B from India. Phylogenetic analysis showed that species A and species B do not form a monophyletic clade but instead share genetic similarity with Anopheles vagus and Anopheles sundaicus s.l., respectively. An allele specific identification method based on ITS2 variation was developed for the reliable identification of species A and B in Sri Lanka. CONCLUSION: Further multidisciplinary studies are needed to establish the species status of all chromosomal forms in the Subpictus complex. This study emphasizes the difficulties in using morphological characters for species identification in An. subpictus s.l. in Sri Lanka and demonstrates the utility of an allele specific identification method that can be used to characterize the differential bio-ecological traits of species A and B in Sri Lanka.

Genetic population structure of the malaria vector Anopheles baimaii in north-east India using mitochondrial DNA.

BACKGROUND: Anopheles baimaii is a primary vector of human malaria in the forest settings of Southeast Asia including the north-eastern region of India. Here, the genetic population structure and the basic population genetic parameters of An. baimaii in north-east India were estimated using DNA sequences of the mitochondrial cytochrome oxidase sub unit II (COII) gene. METHODS: Anopheles baimaii were collected from 26 geo-referenced locations across the seven north-east Indian states and the COII gene was sequenced from 176 individuals across these sites. Fifty-seven COII sequences of An. baimaii from six locations in Bangladesh, Myanmar and Thailand from a previous study were added to this dataset. Altogether, 233 sequences were grouped into eight population groups, to facilitate analyses of genetic diversity, population structure and population history. RESULTS: A star-shaped median joining haplotype network, unimodal mismatch distribution and significantly negative neutrality tests indicated population expansion in An. baimaii with the start of expansion estimated to be ~0.243 million years before present (MYBP) in north-east India. The populations of An. baimaii from north-east India had the highest haplotype and nucleotide diversity with all other populations having a subset of this diversity, likely as the result of range expansion from north-east India. The north-east Indian populations were genetically distinct from those in Bangladesh, Myanmar and Thailand, indicating that mountains, such as the Arakan mountain range between north-east India and Myanmar, are a significant barrier to gene flow. Within north-east India, there was no genetic differentiation among populations with the exception of the Central 2 population in the Barail hills area that was significantly differentiated from other populations. CONCLUSIONS: The high genetic distinctiveness of the Central 2 population in the Barail hills area of the north-east India should be confirmed and its epidemiological significance further investigated. The lack of genetic population structure in the other north-east Indian populations likely reflects large population sizes of An. baimaii that, historically, were able to disperse through continuous forest habitats in the north-east India. Additional markers and analytical approaches are required to determine if recent deforestation is now preventing ongoing gene flow. Until such information is acquired, An. baimaii in north-east India should be treated as a single unit for the implementation of vector control measures.