ACTAUNIVERSITATIS

UPSALIENSISUPPSALA

2014

Digital Comprehensive Summaries of Uppsala Dissertationsfrom the Faculty of Medicine 1020

Dynamics of Resistant Plasmodiumfalciparum Parasites

NIZAR ENWEJI

ISSN 1651-6206ISBN 978-91-554-9007-2urn:nbn:se:uu:diva-230224

Dissertation presented at Uppsala University to be publicly examined in C8:305, BMC,Husargatan 3, Uppsala, Wednesday, 8 October 2014 at 09:15 for the degree of Doctor ofPhilosophy (Faculty of Medicine). The examination will be conducted in English.

AbstractEnweji, N. 2014. Dynamics of Resistant Plasmodium falciparum Parasites. DigitalComprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1020.49 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-554-9007-2.

Persistence of drug resistant Plasmodium falciparum is a major problem to management andcontrol malaria in endemic areas. The focus of this thesis was to study the dynamics of resistantP. falciparum parasites. The study was performed in two African countries: 1) Sudan: Asarvillage in eastern Sudan, here we examined the persistence of drug sensitive and resistant P.falciparum genotypes among individuals with single-clone and multiple clones infection duringthe dry season. We genotyped microsatellite loci in the vicinity of the dihydrofolate reductasegene (dhfr) and the dihydropteroate synthase gene (dhps). Microsatellite investigation showedthat asymptomatic parasitemia persisted in some patients for several months throughout thedry season and into the next transmission season. In some samples mixed infections weredetected, and we noted several cases where the microsatellite haplotype varied from month tomonth, suggesting turnover of different parasite populations in the blood. This demonstratesthat even during asymptomatic infections there can be dynamics within the parasite populationin an individual. In addition, we calculated the parasite density throughout the dry seasonto the next transmission season by using allele-specific quantitative PCR. Parasite densityduring the dry season fluctuated, but was generally lower than in the first transmission season.A significant difference (P<0.05) between dry and first transmission season was found inregard to the parasite density, whereas no significant difference was observed when dry andsecond transmission season were compared (P>0.05). 2) Ethiopia: West Arsi zone, one of themalaria endemic zones of the Oromia region. In the first study we determined the prevalenceof asymptomatic malaria carriages from November-December 2012. According to PCR theprevalence of sub-microscopic P. falciparum carriage was 19.2%, microscopy-based prevalencewas 3.7% while the prevalence was 6.9% using RDT. Based on this, PCR was considered abetter tool for measuring Plasmodium prevalence than microscopy and RDT. A second studyaddressed the genetic diversity of chloroquine resistance (CQR) in P. falciparum by analysingfour microsatellite markers in and around the pfcrt gene. Although CQ was withdrawn for morethan a decade, 100% of the parasites still carried the Pfcrt K76T mutation. Only the CVIEThaplotype was identified. Based on combinations of MS markers, seven different EthiopianCQR variants (E1-E7) were identified. Both intronic and MS flanking the pfcrt gene showedlow levels of diversity.

Nizar Enweji, Department of Medical Biochemistry and Microbiology, Box 582, UppsalaUniversity, SE-75123 Uppsala, Sweden.

© Nizar Enweji 2014

ISSN 1651-6206ISBN 978-91-554-9007-2urn:nbn:se:uu:diva-230224 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-230224)

To the memory of my father To my mother To my wife and my daughter To my wonderful sister and devoted brothers

List of Papers

This thesis is based on the following papers, which are referred to in the text by their Roman numerals.

I Enweji N*, Kheir A*, Kerje S, Abdel-Muhsin A, Babiker H,

Swedberg G. Dynamics of asymptomatic malaria infections as revealed by microsatellite typing. Manuscript

II Enweji N, Sharif H, Abdel-Muhsin A, Babiker H, Swedberg

G. Real-time quantitative PCR for determining Plasmodium falciparum parasite density in patients with asymptomatic infection in a seasonal transmission area. Manuscript

III Golassa L, Enweji N, Erko B, Assefa A, Swedberg G. (2013) Detection of a substantial number of sub-microscopic Plasmo-dium falciparum infections by polymerase chain reaction: a potential threat to malaria control and diagnosis in Ethiopia. Malaria journal, 12:352

IV Golassa L*, Enweji N*, Erko B, Assefa A, Swedberg G. (2014)

High prevalence of pfcrt-CVIET haplotype in isolates from as-ymptomatic and symptomatic patients in south-central Oromia, Ethiopia. Malaria journal, 13:120

*Shared authorship

Reprints were made with permission from the respective publishers.

Publication not included in this thesis: Kamugisha E, Sendagire H, Kaddumukasa M, Enweji N, Gheysari F, Swed-berg G, Kironde F. (2011) Detecting adenosine triphosphatase 6 (pfATP6) point mutations that may be associated with Plasmodium falciparum resis-tance to artemisinin: prevalence at baseline, before policy change in Uganda. Tanzan J Health Res. 13(1):40-7.

Contents

Introduction ................................................................................................... 11 Global burden of malaria .......................................................................... 11 The malaria parasite and vector ................................................................ 11 Life cycle of the malaria parasite ............................................................. 12 Malaria symptoms .................................................................................... 13 Transmission and epidemiology ............................................................... 13 Malaria control ......................................................................................... 14 The P. falciparum parasite ....................................................................... 15 Microsatellite loci ..................................................................................... 16 Antimalarial drug resistance ..................................................................... 16

Chloroquine ......................................................................................... 17 Sulfadoxine-pyrimethamine ................................................................ 17 Artemisinin based combination therapy (ACT) ................................... 17

Epidemiology of drug resistance .............................................................. 18 Mechanisms of drug resistance ................................................................ 19 Origins and evolution of antimalarial drug resistance .............................. 19 Antimalarial resistance genes ................................................................... 20

Pfcrt ..................................................................................................... 20 Pfdhfr and Pfdhps ................................................................................ 20

Malaria in Sudan (eastern part) ................................................................ 21 Malaria in Ethiopia ................................................................................... 21

Aims of the thesis.......................................................................................... 23

Material and methods .................................................................................... 24 Study sites ................................................................................................ 24

Eastern Sudan ...................................................................................... 24 Ethiopia ................................................................................................ 24

Genotyping ............................................................................................... 25 Blood sampling and storage ................................................................. 25 DNA extraction .................................................................................... 25 PCR-RFLP ........................................................................................... 25 Sequencing ........................................................................................... 25 Microsatellite analysis (STR) .............................................................. 25 Real-time PCR ..................................................................................... 26

Statistics ................................................................................................... 26

Ethical considerations .............................................................................. 26

Results and discussion .................................................................................. 27 Paper I ...................................................................................................... 27 Paper II ..................................................................................................... 31 Paper III .................................................................................................... 33 Paper IV ................................................................................................... 36

Conclusions ................................................................................................... 38

Acknowledgments......................................................................................... 39

References ..................................................................................................... 43

Abbreviations

ACT Artemisinin based combination therapy bp Base pair CDC Center for Disease Control and Prevention CQ Chloroquine CQR Chloroquine resistance DNA Deoxyribonucleic acid EIR Entomological inoculation rate HIV Human immunodeficiency virus IPTp Intermittent preventive treatment for pregnant women IRS Indoor residual spraying ITNs Insecticide treated bed nets Kb Kilo base pair MS Microsatellites PCR Polymerase chain reaction Pfcrt P. falciparum chloroquine resistance transporter gene Pfdhfr P. falciparum dihydrofolate reductase Pfdhps P. falciparum dihydropteroate synthase RDTs Rapid Diagnostic Tests RFLP Restriction fragment length polymorphism RT-PCR Real-time polymerase chain reaction SP Sulfadoxine-pyrimethamin TB Tuberculosis WHO World Health Organization

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Introduction

Global burden of malaria Even though it has been more than 100 years since the discovery of the causative parasites of malaria, the disease still remains a major global health problem. Reports from the World Health Organisation (WHO) have shown that half of the world’s population, in 97 countries, live at risk of malaria (WHO 2013a). About 207 million cases of malaria worldwide (uncertainty interval, 135-287 million), associated with almost 627 000 malaria deaths (uncertainty interval, 473 000-789 000), were estimated in 2012. The risk of suffering or even dying from contracting malaria varies considerably between populations. For instance, children less than five years of age, pregnant women, and patients with HIV/AIDS are at higher risk than any other population group. In addition, 90% of malaria-related deaths occur in Africa, where one child dies of malaria every 60 seconds.

It has been shown that malaria is closely associated with economic and social development (Malaney, Spielman et al. 2004). Malaria is known to be both a disease of poverty and a cause of poverty. While poverty can cause malaria by decreasing the capacity for disease prevention (at both individual and government levels), malaria can also cause poverty, for example through indirect economic costs, medical cost, loss of income, or a negative impact on trade. Although the work towards elimination of malaria began several decades ago, the focus has now shifted from eradication to control, due to the dramatic acceleration of disease and mortality rates (Gregson and Plowe 2005). During the last 10 years this trend has been reversed.

The malaria parasite and vector Malaria is caused by protozoan parasites of the phylum Apicomplexa and genus Plasmodium. There are about 120 Plasmodium species that can infect mammals, birds and reptiles. Five Plasmodium species can infect humans: Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae, Plasmodium ovale and Plasmodium knowlesi. It has been reported that P. knowlesi, whose natural host is macaque monkeys, can infect humans as well (Singh, Kim Sung et al. 2004, Cox-Singh and Singh 2008). The most

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common human-infecting species are P. vivax and P. falciparum, which cause the most severe cases of disease and the highest number of deaths. According to WHO 2000, different malaria parasite species vary in geographical distribution, microscopic morphology, clinical presentation, and susceptibly to anti-malarial drugs.

Human malaria is transmitted from one human to another by the bite of an infected female mosquitoes of the Anopheles genus. The main vectors are the Anopheles gambiae complex in sub-Saharan Africa (Coetzee, Craig et al. 2000), and the Anopheles minimus complex in South East Asia (Van Bortel, Trung et al. 2003).

Life cycle of the malaria parasite The life cycle of the malaria parasite is extremely complex and requires both the human host and an insect vector. The life cycle of the malaria parasite is illustrated in Figure 1. When an infected female Anopheles mosquito penetrates human skin to obtain a blood meal it injects saliva mixed with an anticoagualant, and also injects sporozoites into the blood stream. The sporozoites travel to the liver and enter the liver cells (hepatocytes). At this stage they can either remain dormant as a hypnozoite form (P. vivax or P. ovale) (Schlitzer 2008, Winzeler 2008) or, in the case of P. falciparum, the sporozoites remain in the liver for 7-14 days and undergo asexual replication to form tissue- stage schizogonts (exo-erythrocytic schizonts), in which each sporozoite can give rise to tens of thousands of merozoites. When the hepatocyte ruptures, merozoites are released into the blood stream and invade erythrocytes. Once inside the erythrocyte, the parasite matures from merozoite to early trophozoite (ring stage). The trophozoite develope to schizont.

The erythrocyte ruptures and releases merozoites into the blood stream again. Plasmodium enters a sexual phase when some merozoites in the erythrocytes develop into gametocytes, cells capable of producing both male and female gametes. Gametocytes can be ingested by Anopheles mosquitoes biting an infected individual, and form micro (male)-and macrogametes (female) in the mid-gut of the mosquito. The gametes undergo fertilization and form a zygote, which rapidly develops into an ookinete that penetrates the intestinal walls of the mid-gut and develops into an oocyst. Asexual replication occurs within the oocyst and produces sporozoites. These sporozoites migrate to the salivary glands of the mosquito, and from there are injected into the blood stream of a human, thus starting the parasite life cycle again.

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Figure 1. Diagram of the malaria parasite’s life cycle. EA Winzeler Nature 455, 756-751 (2008).

Malaria symptoms The symptoms of malaria infection in humans are caused by the asexual blood stage of the parasite life cycle. Uncomplicated or mild malaria symptoms are fever, headache, diarrhoea, vomiting, coughing and abdominal pain. Severe malaria symptoms including respiratory distress, coma, cerebral malaria, anemia, renal failure, splenomegaly and hypoglycemia (Weatherall, Miller et al. 2002). If the uncomplicated malaria infection is not treated it can develop into severe malaria and lead to death.

Transmission and epidemiology There are about 400 species of Anopheles mosquitoes, of which about 40 can transmit malaria. Malaria is transmitted by different Anopheles species, depending on the region and the environment. Anophelines that can transmit malaria are found not only in malaria-endemic areas, but also in areas where malaria has been eliminated. The latter areas are thus constantly at risk of re-introduction of the disease (CDC 2012a).

Malaria transmission can be stable or unstable. It can be rather constant from year to year in stable areas, whereas in unstable areas the transmission varies. Although both are endemic, there is a greater risk of epidemics in the unstable areas, i.e. the number of malaria cases considerably exceeds what is

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normally expected. The stable transmission is more common in areas where the vector favours feeding on humans and has a high survival rate. On the other hand, in areas where the vector bites animals and human and/or has a low survival rate, the unstable transmission is more common (Reiter 2008). The percentage of people live in areas at risk of malaria is illustrated in Figure 2.

Figure 2. World map demonstrate percentage of people live in areas at risk of malaria transmission. Adopted from (WHO, 2014).

Malaria control Malaria is both preventable and a curable disease. Increased malaria prevention and control measures dramatically has decreased the malaria burden in many places (WHO 2014). The world's first attempt to eradicate malaria came after World War II. The WHO started malaria eradication programs in 1955 in many African countries (WHO 2008). Malaria diagnosis was historically based only on symptoms, with fever being the main symptom. Fever, however, is not exclusively a symptom of malaria. Therefore, many patients have been given the wrong treatment where antimalarials have been overused. Thus, the WHO recommended a parasitological confirmation of the diagnosis of malaria before starting treatment. The two main methods for malaria diagnosis are: 1). Microscopic diagnosis: Microscopy is the gold standard and preferred technique for diagnosing malaria. Examination of thick and thin blood films reveals malaria parasites. Further, thick films are more sensitive than thin films for detecting low density malaria parasitaemia.

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2). Rapid Diagnostic Tests (RDTs): These are also known as dipsticks. If microscopy is not available or not feasible, a rapid diagnostic test (RDT) should be used as an alternative way of diagnosing malaria in patients. The test provides results in 2-15 minutes (CDC 2012c, WHO 2013c). HRP2 antigen is targeted by RDT and is specific to the P. falciparum parasite; pLDH and parasite aldolase are target antigens for RDT and are specific to species other than P. falciparum (Moody 2002, Hawkes, Conroy et al. 2014). The tools currently used for malaria control are: Insecticide treated bed nets (ITNs): This is simply a mosquito net treated with insecticides. ITNs are much more protective than untreated nets. In Africa, ITNs have been shown to reduce the death of children younger than 5 years old, from all causes, by about 20% (CDC 2014). Indoor residual spraying (IRS): The objective of this method is to kill mosquitoes by spraying the inside walls and other surfaces of a house with a residual insecticide. For several months, the insecticide will kill mosquitoes that come in contact with these surfaces. IRS usually kills mosquitoes after they have fed if they come to rest on the sprayed surface. Therefore. IRS prevents transmission of infection to other people (CDC 2012b). Intermittent preventive treatment (IPTp): This prophylactic treatment is recommended for pregnant women. IPTp reduces maternal malaria episodes, maternal and fetal anaemia, low birth weight, and neonatal mortality (WHO 2013b). IPTp with sulfadoxine-pyrimethamine (IPTp-SP) has been shown to successfully reduce the burden of pregnancy-associated malaria (PAM), and is currently part of the national malaria prevention programme in most African countries (Bertin, Briand et al. 2011). Larvicides: This is an insecticide used to kill immature mosquitoes before they become adults (mosquito larva stage) (CDC 2013).

A limited number of antimalarial drugs are under current clinical use; these include: Chloroquine, antifolate (Sulfadoxine-pyrimethamine), lumefantrine, artemisinin and its derivatives (artesunate, artemether), as well as antibiotics. The purpose of antimalarial treatment in severe malaria is to prevent death. For uncomplicated malaria, the purpose is to cure, i.e. eradicate the infection to prevent development to severe disease.

The P. falciparum parasite The P. falciparum clone 3D7 nuclear genome covers 22.8 megabases (Mb) of DNA, consists of 14 chromosomes, and encodes about 5300 genes. It also contains apicoplast and mitochondrial genomes, which are extrachromosomal DNA of sizes 35kb and 6kb, respectively. The malaria

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parasite is found to be rich in Adenine/Thiamine (A+T), which comprises about 80% of the P. falciparum genome (Gardner, Hall et al. 2002).

Microsatellite loci Microsatellites (MS), known as simple sequence repeats (SSRs) or short tandem repeats (STRs), are repeating sequences of 2-6 base pairs of DNA. MS are considered to be molecular markers that can provide valuable information on population structure in the malaria parasite and are common in the P. falciparum genome (Su and Wellems 1996, Su, Ferdig et al. 1999). MS are widely distributed in eukaryotic genomes, and are highly variable. In addition, microsatellites can be amplified for identification by the PCR process, using the unique sequences of flanking regions as primers, and they have been used in many different research areas, such as forensics, diagnosis and identification of human diseases, population studies, and conservation biology. MS-based studies have the limitation that they only reflect relatively recent evolution of P. falciparum. Therefore, markers with lower mutation rates are more powerful in studying long-term evolutionary history (Ferdig and Su 2000, Su and Wootton 2004). Mutations associated with drug resistance in P. falciparum have occurred within the past 50 years, and therefore provide a unique chance to identify allelic associations.

These drug resistance genotypes are characterised by reduced diversity around the major resistance alleles (Su and Wootton 2004). In Asia and Africa, microsatellite markers with multiple allele flanking genes associated with drug resistance, such as dhfr and pfcrt, were investigated. This allowed for typing of specific haplotypes flanking these regions and enabled identification of drug resistance origin, as well as tracing the spread of these mutations (Nair, Williams et al. 2003, Roper, Pearce et al. 2003).

Antimalarial drug resistance In 1973 the WHO defined drug resistance as the ability of the parasite to survive and/or multiply despite the administration and absorption of a drug given in dose equal to or higher than recommended, but within the limits of tolerance of the subject (WHO 1986).

Drug resistance may cause treatment failure; however, treatment failure does not always have to be caused by drug resistance. Other factors may lead to treatment failure: inadequate dose or duration of treatment; fake drug with no or little active ingredient; or poor absorption. In malaria treatment, resistance to all known anti-malarial drugs, including the newly introduced

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artemisinin based combination therapy (Carrara, Zwang et al. 2009), has developed to various degrees in several countries.

Chloroquine Chloroquine (CQ) was discovered in 1934 by Hans Andersag and co-workers at the Bayer laboratories in Eberfeld, Germany and given the name Resochin (Dondorp, Yeung et al. 2010). CQ has been used for decades as an anti malarial medication, is cheap to produce and relatively well tolerated compared to Quinine (QN). The standard dose of CQ recommended by WHO for treatment of uncomplicated malaria is 10mg/kg on days 0 and 1 and 5mg/kg on day 2, giving a total dose of 25mg/kg. CQ may cause side effects, such as: diarrhoea, nausea temporary hair loss, dizziness and worse psoriasis (Taylor and White 2004, AlKadi 2007). CQ is also used for treatment of other diseases, including viral infection, cancer and arthritis (Savarino, Boelaert et al. 2003).

Sulfadoxine-pyrimethamine Sulfadoxine-pyrimethamin (SP) or Fansidar is currently the main option to treat malaria in pregnancy. Use of SP began after the widespread resistance to chloroquine. The drug is easy to use because treatment involves only a single oral dose and it is cheap. SP acts by interfering with two key enzymes in the folate biosynthesis pathway. Sulfadoxine is a competitive inhibitor of dihydropteroate synthase (DHPS). Pyrimethamine is a competitive inhibitor of dihydrofolate reductase (DHFR). The inhibition of these two enzymes affects the tetrahydrofolate synthesis that is required for DNA synthesis (Sibley, Hyde et al. 2001). The WHO recommends intermittent preventive treatment for pregnant women (IPTp) in all areas with moderate to high malaria transmission in Africa (WHO 2013b).

Artemisinin based combination therapy (ACT) The World Health Organisation (WHO) recommended a switch of first-line treatment against uncomplicated malaria to artemisinin-based combination therapies (ACTs) for countries where conventional antimalarial treatments such as chloroquine (CQ) and sulphadoxine-pyrimethamine (SP) have become ineffective (WHO 2006).

Combination therapy for treatment of infectious diseases is common in diseases such as TB, HIV infection, and in cancer. This strategy is also applicable to malaria treatment. By using ACT for malaria infection the chance that the parasites develop resistance as a result of genetic mutations to two drugs with different modes of action becomes much lower than that of parasites developing resistance to a single treatment (White 1999, Nosten

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and White 2007). Therefore, there are a number of ACTs being used or tested in different P. falciparum-endemic regions (Kremsner and Krishna 2004). The most common antimalarials used in combination therapy are: artemether-lumefantrine (AL), artesunate-mefloquine (ASMQ), artesunate-amodiaquine (ASAQ), artesunate- sulfadoxine-pyrimethamine (AS-SP) and dihydroartemisinin-piperaquine (DHA-PQ). Artemether–lumefantrine (Coartem) is a fixed-dose oral combination for treating uncomplicated falciparum malaria in adults and children (Kokwaro, Mwai et al. 2007). Coartem’s efficacy against falciparum malaria has been validated in several clinical trials. Ethiopia adopted artemether-lumifantrine as first line therapy in 2004 (FMOH (Federal Republic Ethiopia 2004, Jima, Tesfaye et al. 2005, Assefa, Kassa et al. 2010) . In Sudan, artesunate–sulphadoxine–pyrimethamine (AS–SP) and artemether–lumefantrine (AL) are the recommended first- and second-line treatments for uncomplicated P. falciparum malaria, respectively (Abdallah, Ali et al. 2012). In addition, Artemisinin and its derivatives are generally safe and well-tolerated (Cui and Su 2009).

Epidemiology of drug resistance Chloroquine resistance (CQR) was first reported in 1957 in the Cambodia–Thailand border. In 1959, chloroquine resistance emerged independently in South America, and was reported in Africa 17 years after the first cases in Asia. However, once chloroquine-resistant P. falciparum strains had gained a toehold in Africa, they spread rapidly from country to country (Payne 1987). The increase in CQR in East Africa has led to a rise in malaria mortality. Correspondingly, a significant rise in malaria mortality in children under 5 years of age has been observed in Senegal in West Africa, simultaneously with the emergence of CQR in the area. However, antimalarial drug resistance has also been implicated in the increasing frequency and severity of epidemics. The conditions for the development and spread of drug resistance differ between the Asian and African continents. Migration of individuals carrying resistant gametocytes has probably been of major importance for the spread of CQR between different endemic areas in Asia and Oceania and for the initial introduction of CQR to East Africa (WHO 2001). Widespread chloroquine resistance has forced those countries to switch treatment from chloroquine to sulfadoxine/pyrimethamine (SP, trade name Fansidar) (Gatton, Martin et al. 2004). Since the 1980s, SP failures have increased significantly, due to the presence of resistant parasites (Maiga, Djimde et al. 2007). First reports on SP resistance were reported on the Thai-Cambodian border, then increasing resistance was documented in other parts of Southeast Asia, southern China and the Amazon Basin,

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rendering them established multi-drug resistant (MDR) areas (Wernsdorfer and Payne 1991, Wongsrichanalai, Pickard et al. 2002).

Mechanisms of drug resistance Many factors affect the emergence and spread of resistance to antimalarial drugs, such as: characteristics of the drug itself, the human host, the vector, the parasite and the environment (see Figure 3).

Figure 3. Factors affecting the emergence and spread of resistance to antimalarial drugs.

Origins and evolution of antimalarial drug resistance Resistance in nature occurs through spontaneous mutations, which are rare events. For some drugs a single mutation is enough to cause resistance, while for others multiple mutations may be necessary. The development of resistance is the result of both genetic change and its selection. The intensity and the timing of resistance emergence depend on several factors. The single most important reason is, however, the drug pressure. There are two processes which are necessary for evolution of drug resistance: (a) A resistant genotype is generated by mutation; (b) the spread of this mutation within and between parasite populations (Anderson and Roper 2005).

HOSTImmunityMigration

PARASITEFitnessMutation rateGenetic basis of resistance

DRUGDrug useDrug pressureHalf lifeDosing

ENVIROMENTTransmission intensityClonal multiplicity

VECTORMigrationParasite preference

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Mutation rates in Plasmodium genes have been found to be in the order of 10-9, when measured (Paget-McNicol and Saul 2001).

Antimalarial resistance genes Three genes relevant to the study are discussed: chloroquine resistance transporter gene (pfcrt), associated with chloroquine resistance; and the genes encoding dihydropteroate synthase dhps and dihydrofolate reductase dhfr, which are associated with Sulfadoxine/Pyrimethamine resistance.

Pfcrt A major breakthrough in the search for the genetic basis of CQR in P. falciparum was the identification of Plasmodium falciparum chloroquine resistance transporter gene (pfcrt) on chromosome 7. PfCRT is a 48kDa protein containing 424 amino acid, 10 predicted transmembrane-spanning domains, and is localised to the digestive vacuole (DV) membrane in erythrocytic stage parasites (Fidock, Nomura et al. 2000).

The main point of mutation, K76T, appears to be necessary for the resistance phenotype, and is the most reliable molecular marker of resistance among the various pfcrt mutations(Djimde, Doumbo et al. 2001). The whole section 72-76 of pfcrt seems to be important. P. falciparum CQR strains carrying haplotype CVIET at position 72-76 of the pfcrt locus are common in South-East Asia and Africa, and SVMNT haplotype has been reported in South America (Fidock, Nomura et al. 2000) but rarely in Africa (Alifrangis, Dalgaard et al. 2006).The P. falciparum chloroquine-sensitive strains from malarious regions around the world carry CVMNK haplotype at codons 72-76 (Mehlotra, Fujioka et al. 2001).

Pfdhfr and Pfdhps Mutations in the genes that encode the target enzymes of the antifolate drugs have been known for several years to be associated with in vitro resistance to these drugs. The major enzyme targets of malaria chemotherapeutic in the folate biosynthetic pathway are dihydrofolate reductase (DHFR) and dihydropteroate synthase (DHPS); the inhibition of these enzymes leads to decreased production of tetrahydrofolate (Ferone 1977). Tetrahydrofolate is an essential cofactor for the production of a number of folate precursors, including methionine and dTMP. Moreover, decreased production of these precursors would severely inhibit the Plasmodium parasite life cycle (Sibley, Hyde et al. 2001). Mutations in the dhfr gene are associated with pyrimethamine resistance and mutations in the dhps gene are associated with sulfadoxine resistance (Brooks, Wang et al. 1994, Salgueiro, Vicente et al.

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2010). The mutations found to be associated with pyrimethamine resistance are: S108N, N51I, C59R, and I164L. A change from wild type Ser108 to Asn 108 (S108N) in dhfr is enough to cause a low level of pyrimethamine resistance. The other additional mutations (N51I, C59R and I164L) in the dhfr gene can yield higher levels of SP resistance than does the mutation S108N alone (Cowman, Morry et al. 1988, Peterson, Walliker et al. 1988). In sulfadoxine resistance, five points of mutation have been involved (S436A/F, A437G, K540E, A581G and A613S/T) in the dhps gene. The double dhps mutation A437 and K540E is highly associated with SP treatment failure (Happi, Gbotosho et al. 2005, Alker, Kazadi et al. 2008). In East Africa, a triple mutation of dhfr (S108N, N51I, C59R) combined with a dhps double mutation (A437G and K540E), which is known as a “quintuple mutant”, is predictive for SP treatment failure (Kublin, Dzinjalamala et al. 2002, Sridaran, McClintock et al. 2010, Zeile, Gahutu et al. 2012). Pfdhfr (I164L) is linked with high levels of pyrimethamine resistance (Sirawaraporn, Sathitkul et al. 1997).

Malaria in Sudan (eastern part) Eastern Sudan has a dry savanna climate. The epidemiology of malaria is considered to be hypoendemic, with a short transmission period during the rainy season between July and November, followed by a hot dry season between November and June.

The transmission season is thus confined to the short period from November to December. The main mosquito vector in the region is Anopheles arabiensis. The predominant parasite species is P. falciparum, which accounts for more than 90% of malaria cases, while P.vivax causes about 5%. The entomological inoculation rate (EIR) has been estimated to be less than one infective bite per person per year (Babiker, Abdel-Muhsin et al. 1998, Hamad, Nugud Ael et al. 2002). P. falciparum parasites that cause clinical malaria during transmission seasons are characterised by great diversity, and are found as multiple clones in infected patients. Thus, it is suggested that these parasites belong to larger parasite reservoirs existing prior to the start of the next transmission season (Babiker, Abdel-Muhsin et al. 1998, Abdel-Wahab, Abdel-Muhsin et al. 2002).

Malaria in Ethiopia Of Ethiopia’s 68 million inhabitants, about 45 million are estimated to be at risk of malaria infection. The most important determinants of malaria transmission in Ethiopia are altitude and climate (rainfall and temperature). In addition, transmission is seasonal and mostly unstable in character. The

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major transmission of malaria follows the June – September rains and occurs between September and December. The minor transmission season occurs between April and May following the February – March rains. The major transmission season occurs in almost every part of the country, whereas the bimodal pattern of transmission is limited and restricted to a few regions that receive the small(belg) rains. There are four major eco-epidemiological strata of malaria in the country:

I. Malaria-free highland areas above 2,500 metre altitude. II. Highland fringe areas between 1,500 - 2,500 metre (affected by

frequent epidemics). III. Lowland areas below 1,500 metre (seasonal pattern of

transmission ). IV. Stable malaria areas (all year round transmission).

The most dominant malaria parasites in Ethiopia are P. falciparum and P. vivax, which are distributed all over the country and account for 60% and 40% of malaria cases respectively. The parasite is mainly transmitted by the major mosquito vector Anopheles arabiensis. However, in some areas Anopheles pharoensis, Anopheles funestus and Anopheles nili also transmit the disease (WHO 2012)

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Aims of the thesis

The overall aim of this thesis was to provide a better understanding of dynamics of P. falciparum parasites in symptomatic and asymptomatic infections. The specific aims were:

I. To determine the dynamics of parasite populations during asymp-

tomatic infections by using microsatellite analysis linked to dhfr and dhps genes.

II. To estimate the parasite density during the first transmission sea-son, the dry season and the second transmission season by using Real-time quantitative PCR.

III. To investigate the presence of sub-microscopic Plasmodium fal-ciparum infections using polymerase chain reaction (PCR) and to compare the PCR-based parasite prevalence against microscopy and rapid diagnostic test (RDT).

IV. To address the genetic diversity of chloroquine resistance in P. falciparum by analysing four microsatellite markers in and around the Pfcrt gene.

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Material and methods

Study sites Studies that are included in this thesis have been performed in two African countries, Sudan (Eastern region) and Ethiopia (West Arsi zone, Shalla district).

Eastern Sudan The study was conducted in Asar village, Gedaref state in Eastern Sudan. The transmission season is short (8-12 weeks) and distinctly seasonal, following the annual rains from July to November and reaching a peak in October. The number of malaria cases decreased substantially by January. A longitudinal survey (papers I&II) was conducted from October 1993 to December 1994; a cohort of 81 patients was followed for 15 months and here we reported 25 patients who showed persistent parasitaemia during the whole period, even during the dry season.

Ethiopia The study was performed in Shalla district West Arsi zone, which is one of the malaria endemic zones of the Oromia region, with a population of around 177,000 living in malarious areas. The study district is located at a distance of 251 km from Ethiopia’s capital, Addis Ababa, and is 1500-2300 m above sea level (Golassa, Enweji et al. 2014).

West Arsi zone has ten districts, of which Shalla district has the highest number of malaria cases; here, P. falciparum and P.vivax are the two common causes of malaria. Two cross sectional studies (papers III and IV) were performed in the area from November to December 2012. A total of 1,453 blood samples were collected from clinical patients and sub-clinical subjects. The clinical patients were diagnosed by microscopy and RDT (SD BIOLINE Malaria Ag P.f/P.v POCT test kits (Standard Diagnostic, Inc, Germany, LOT No: 145021)) were used according to the manufacturer’s instructions.

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Genotyping Blood sampling and storage All blood samples were collected on Whatman 3MM filter paper for parasite genotyping. After the blood had dried, the filter papers were stored in individual sealable plastic bags at room temperature.

DNA extraction DNA was extracted from filter paper using the Chelex method (Plowe, Djimde et al. 1995). This protocol is designed for the isolation of genomic DNA from dried blood spots. The blood spots were excised from filter papers using a sterilised hole punch (1/8 inch) diameter. The samples were stored at -20˚C for long term storage or at 4˚C for shorter storage times.

PCR-RFLP PCR-Restriction Fragment Length Polymorphism (RFLP) is, equipment wise, a simple way to analyse SNPs and therefore a suitable method to use in the field. The nested-PCR products were digested with one unit of ApoI restriction enzyme at 55°C for three hours incubation time to identify the K76T mutation. After incubation, restriction fragments were analysed on 2% agarose gels with ethidium bromide and were visualised by UV Transilluminator in a VWR Gel Documentation System.

Sequencing DNA sequencing samples were purified before sequencing using GeneJET PCR purification kit (Thermo Scientific) and sequenced using an automatic sequencer ABI3730 DNA analyzer at Uppsala Genome Centre.

Microsatellite analysis (STR) Three MS loci, located 0.3, 4.4 and 5.3kb from position 108 of the dhfr gene and 0.8, 4.3 and 7.7kb from the 3ˋend of the dhps gene were analysed to determine variation of microsatellites flanking the drug resistance genes (paper I). Four highly polymorphic MS loci (msint 2, msint 3, mscrt -2 and mscrt -29) were used for determining variation among pfcrt gene; each MS marker was amplified by semi-nested PCR in a LifePro thermal cycler (Bioer). Fluorescent PCR products were analysed in ABI 3730 DNA Analyzer

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(Applied Biosystem). GeneMapper v4.0 software was used for analysis of the fragment data (paper IV).

Real-time PCR Real-time quantitative PCR was used for determining the parasite density among asymptomatically infected patients (paper II). A LNA®-dual-labelled fluorogenic probe (Sigma-Aldrich) was designed to detect the dhfr108 wild-type sequence. The probe was dual labelled with a reporter dye at the 5' end and a quencher moiety at the 3' end. The MiniOpticon real-time PCR detection system (Bio-Rad) was used for all reactions.

Statistics In paper II, GraphPad Prism software v5.0 was used for the statistical analyses. The data are expressed as the mean (95% confidence interval (CI)), if not otherwise indicated. A paired-sample t-test was performed to determine the differences between groups. Differences were regarded as significant when the P value < 0.05. In paper III, statistical analysis was performed using Stata version 11. The X2 test was used to compare the plasmodium carriage among different age groups. The test was considered statistically significant if the P value was < 0.05. In paper IV, the heterozygosity (He) for each MS locus was calculated using the following formula: He = [n/ (n-1)] [1-ΣPi2] where n is the number of alleles in the sample and p is the frequency of the ith allele.

Ethical considerations Ethical approval for Paper I and Paper II was obtained from the ethical committee of the Ministry of Health in Sudan. For Paper III and IV ethical approval was obtained from institutional review boards of Aklilu Lemma Institute of Pathobiology, Addis Ababa University and of the Armauer Hansen Research Institute, as well as the National Research Ethics Review Committee in Ethiopia.

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Results and discussion

Paper I As shown in Table 1, a remarkable variation in the microsatellite markers neighbouring both the dhps and dhfr genes during the dry season was identified. Most samples contained unique MS haplotypes, as expected. In addition, very few haplotypes appeared in more than one patient. Out of the 25 individuals that were selected for this study, only five patients are presented in the table below. From the first transmission season to the middle of the dry season only one haplotype persisted in patient 1. However, as shown by marked changes in both the dhfr and dhps MS patterns, the patient was obviously infected with a new variant after the 8th month of the dry season. In patient 2, MS genotyping showed a fluctuation between single and double parasite clones. In the second transmission season, another parasite clone appeared to have infected the patient, though parasitemia was still quite low, and the patient was asymptomatic with no fever.

When dhfr MS were analysed in patient 3, mixed infections in the first transmission season were indicated. In addition, 3 different parasite clones persisted in the dry season, as shown by both the dhfr and dhps MS patterns. In contrast, patient 4 was infected with the same parasite clone (dhps MS loci) from the first transmission season to the 4th month of the dry season. MS genotyping revealed a shift in the parasite population around the 5th month that remained stable until the second transmission season, when a new shift appeared. On the other hand, the dhfr MS analysis for the same patient showed that the same clone persisted during the first transmission season, but that a shift in parasite population occurred around the 4th month. In the dry season, a mixed population of parasites (dhfr MS) was detected around the 6th month and then remained stable from the 7th month until the second transmission season, when a new shift appeared. There was no variation at all in either dhps or dhfr MS patterns throughout the dry season in patient 5. The patient however was infected by a new variant in the following transmission season, as shown by marked changes in both the dhps and dhfr microsatellite patterns. The results show one of the few instances in which different patients harboured parasites with the same haplotype. This is seen in patients 4 and

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5, who carried parasites with nearly the same dhps MS patterns during the dry season.

Table 1. Neighbouring microsatellite loci located 0.8, 4.3 and 7.7 kb downstream of the dhps gene, and neighbouring microsatellite loci located 0.3, 4.4 and 5.3 kb downstream of the dhfr gene among 25 P. falciparum isolates from Asar village in Eastern Sudan. Patient number (1, 2, 3, 4, and 5).

Haplotype Microsatellite loci dhps

Microsatellite loci dhfr

0.8 kb 4.3 kb 7.7 kb

0.3 kb 4.4 kb 5.3 kb

1/2 123 115 99 87 174 208 1/3 123 115 99 87 174 208 1/4 123 115 99 87 174 208 1/5 123 115 99 87 174 208 1/6 123 115 99 87 174 208 1/7 123 115 99 87 174 208 1/8 123 115 99 87 174 208 1/10 141 107 99 104 174 215 1/11 143 107 99 108 174 215 1/12 143 107 99 104/108 174 215 1/13 141 107 99 87 176 215 1/14 141 107 99 104 176 215 1/15 141 107 99 104 176 215 2/2 114 107/117 122 104/108 176 221 2/3 114 109 122 87 176/179 221 2/4 119 107/117 109 104 179 221 2/5 143 109 109 104 179 221 2/6 114/131 109 109 104 179 221 2/7 114 109 109 104 179 221 2/8 114 109 109 104 179 221 2/9 114 109 109 104 179 221 2/10 114 109 109 104 179 221 2/11 114 109 109 104 179 221 2/12 125 109 109 104 179 221 2/13 141 117 99 87 179 221 2/14 114 117 99 87 179 221 2/15 114/121 109 99 87 179 221 3/3 119 111 111 87 168/176 215 3/5 131 111 109 87 179 215 3/6 123 111 99 87 179 215 3/7 131 111 109 87 179 215 3/8 123 111 99 104 179 215 3/9 123 111 99 104 179 215

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3/10 123 109 109 87 179 215 3/11 131 109 109 87 161 194 3/12 123 109 109 87 179 194 3/13 123 109 109 104 179 215 4/2 131 111 109 84 176 192 4/3 131 111 109 84 176 192 4/4 131 111 109 87 179 194 4/5 123 115 99 87 179 194 4/6 123 115 99 87 179 194/227 4/7 123 115 99 87 179 194 4/8 123 115 99 87 179 194 4/9 123 115 99 87 179 194 4/10 123 115 99 87 179 194 4/11 123 115 99 87 179 194 4/12 123 115 99 87 179 194 4/14 125/129 113 109 84 176 192 5/3 123 115 99 87 179 219 5/4 123 115 99 87 176 219 5/5 123 115 99 87 176 219 5/6 123 115 99 87 176 219 5/7 123 115 99 87 176 219 5/8 123 115 99 87 176 219 5/9 123 115 99 87 176 219 5/11 123 115 99 87 176 219 5/12 123 115 99 87 176 219 5/14 137 105 126 87 176 219 5/15 137 105 126 87 176 219 ●1st transmission season, ●Dry season, ●2nd transmission season

Our study has exploited the unique malaria epidemiology settings of Asar village in eastern Sudan, where a long dry period followed by brief annual rains and the appearance of Anopheles mosquitoes causes malaria transmis-sion to be short and seasonal (Babiker, Lines et al. 1997, Hamad, Nugud Ael et al. 2002). During the dry season, a high degree of fluctuation between different parasite clones was observed. The absence of mosquito transmis-sion during the dry season in Asar suggests that this fluctuation is possibly driven by competitive interaction between different parasite clones within the human host (de Roode, Culleton et al. 2004, Wargo, Huijben et al. 2007). Such competition could eliminate genotypes with survival disadvantages, including mutations causing drug resistance in the absence of drug pressure. Data from our study show that the parasites found in patients during the dry season are not simply resting. In addition, the parasites are shown to turn-over from month to month. Therefore, several people carry mixed infections

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of at least two variants of the parasite. These variants grow during the dry season without causing any symptoms.

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Paper II In this study, 25 patients were recruited and followed throughout three different seasons: the first transmission season, the dry season and the second transmission season. The parasite density was calculated during a period of 15 months in each patient. When examining the data as a whole, the mean parasite density in the first transmission season was 616 (95% confidence interval (CI): 302-1288) parasite/μL, which was considered to be a high level (Figure 4). During the dry season the parasite density fluctuated with a mean of 219 (95 % CI: 98-490) parasites/μL, which was significantly lower than in the first transmission season (P<0.05). The mean parasite density in the second transmission season was 209 (95 % CI: 110-400) parasites/μL. In addition, when compared with the dry season, there was no significant difference between the means of parasite density between the two seasons (P>0.05).

Figure 4. Diagram illustrating the difference in parasite density between (A) the dry season and the 1st transmission season (P<0.05) and (B) the dry season and the 2nd transmission season (P>0.05). Error bars indicate mean with SEM.

The decrease in parasite densities when entering the dry season is explained by the fact that all patients were treated for malaria infection during the first transmission season. It is possible that some limited mosquito transmission of P. falciparum continued at a local level during this time. In the absence of mosquito transmission, the newly appearing clones could only have origi-nated from parasites already present in the patient but otherwise undetectable at the earlier times of sampling. Furthermore, such parasites could have been either sequestered outside the peripheral circulation at this time or have been present at levels too low to have been detectable (Babiker, Abdel-Muhsin et al. 1998).

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The large difference in parasite density between individuals in the first transmission season may be explained by differences in immunity when infection was acquired, meaning that those who displayed high parasitaemia had low immunity due to the absence of previous infections. The relatively low parasitaemia observed in the second transmission season can be ex-plained by the remaining immune response sustained by the persistent para-sitaemia during the dry season.

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Paper III Out of the total number of collected blood samples, the prevalence of P. falciparum infection diagnosed by microscopy was 3.7% (54/1,453) while that diagnosed by RDT was 6.9% (100/1,453). From the remaining 1, 299 negative samples, 400 were randomly selected and tested by PCR. The prevalence of sub-microscopic P. falciparum carriages with infections detected by PCR was 19.2% (77/400). Although sub-microscopic infections were lower in females than males, the difference was not statistically significant between the two groups.

As shown in Table 2, when the 154 samples that were shown to be positive by microscopy and RDT were tested by PCR to evaluate the two diagnostic tests against PCR, the latter detected 90.7% (49/54) and 80% (80/100) of the microscopy and RDT positive samples, respectively. The prevalence of P. falciparum by age group as diagnosed by the 3 different tests is shown in Figure 5. The highest prevalence of microscopic as well as RDT P. falciparum was among the youngest age group (2-5 years) while the older group (>35 years) had the lowest prevalence. PCR showed an unequivocal superior diagnostic performance compared to both RDT and microscopy.

Table 2. Evaluation of rapid diagnostic test- and microscopy-positive results against polymerase chain reaction

Microscopy (n=54)* RDT (n=100)* PCR P. falciparum Mixed

(PF/PV) P.falciparum

Mixed (PF/PV)

P.falciparum 44 5 73 7

Negative 3 2 20 0

Total 47 7 93 7

*Only microscopy and RDT positive samples were subjected to PCR (the overall results of microscopy and RDT not indicated in the table).

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Figure 5. Prevalence of microscopic and sub-microscopic P. falciparum by age group as diagnosed by microscopy, RDT and PCR.

It is noticeable that the PCR analyses in our study helped to establish two relationships, i.e. the rate of false positives and false negatives given by mi-croscopy and RDT, respectively. Both have implications for malaria control measures.

Regarding the false positive rate and its implications, anti-malarial drugs were prescribed for 9.3 and 20.0% microscopy- and RDT-based parasite-negative patients, respectively, as observed by PCR. Similar percentages of parasite-negative patients receiving antimalarial drugs have been also shown in countries such as Tanzania (Masanja, McMorrow et al. 2010), Uganda (Sserwanga, Harris et al. 2011) and Zanzibar (Msellem, Martensson et al. 2009), where high malaria transmission settings are observed. For false negatives, the discussion revolves around 19.2% prevalence of sub-microscopic P. falciparum. Our study results indicate that considerable numbers of P. falciparum infections were missed by both RDT and micros-copy. Therefore the need for a more sensitive assay for the detection of sub-microscopic parasitaemia can be suggested from the study findings.The presence of sub-microscopic asymptomatic P. falciparum infections may represent a significant challenge to malaria control programmes since such parasitaemic individuals may serve as a reservoir of infection and contribute to mosquito infection (Ochola, Vounatsou et al. 2006, Okell, Ghani et al. 2009).The agreement between RDT and microscopy was 89.4% (42/47) and 71.4% (five out of seven) in detecting P. falciparum and mixed infections, respectively. Both RDT and microscopy underestimated the true parasite prevalence in the study area. In this study, microscopy and RDT detected 38.9 and 60%, respectively, of the infection identified by PCR. In addition, the false positivity rate of RDT was 2.1% higher than microscopy. The detection of a high prevalence of PCR-based submicroscopic P. falcipa-rum in the study area would provide significant implications for malaria

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control measures in Ethiopia since such infections are important contributors to the infectious reservoir (Schneider, Bousema et al. 2007, Diallo, Ndam et al. 2012), and could, even at low densities, be a potential source of transmis-sion for vectors and for malaria attack within the population. The increased sub-microscopic carriage in older age groups, which was observed in our study corroborates similar finding in Tanzania (Manjurano, Okell et al. 2011). However, asymptomatic carriage is probably a common occurrence in the study area. Further studies to reveal the magnitude of sub-microscopic asymptomatic carriage will be necessary for guiding and monitoring future malaria elimi-nation efforts in Ethiopia.

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Paper IV PCR results from pfcrt analysis showed that 100% (n = 99) of the patients harboured the pure mutant allele of pfcrt 76 T. Of the fragments that were resistant to ApoI digestion (76 T genotype), 20 were randomly selected for complete sequence for amino acids positions 72-76. All the isolates harboured the pfcrt-CVIET genotype. No single wild-type, CVMNK pfcrt genotype, was detected in the study area.

Four MS loci were analysed for all the isolates, two intronic (msint 2, msint 3) and two flanking (mscrt -2, mscrt -29). Only 79 samples were successfully analysed for MS haplotypes, leaving 20 of the isolates to be excluded from the analysis due to unsuccessful amplification or because they had either multiple alleles (>one peak in the sequencing electropherogram) or missing data at one or more codons. As presented in Table 3, the 79 isolates grouped into seven different CQR haplotypes (E1-E7). The most prevalent haplotype, E1 (82.3%), had allelic combination of (149-179-198-204).When looking at the isolate sources, it is noticeable that two allelic combinations in E3 and E5 were found in isolates collected from asymptomatic subjects; while another two allelic combinations in E6 and E7 were specific to isolates collected from symptomatic subjects.

Table 3. Pfcrt allelic types defined by mutations in positions amino acids 72-76 and polymorphisms in MS markers (intronic and flanking) in 79 P. falciparum isolates in Shalla district, south-central Oromia, Ethiopia. Haplo-type ID

Ms loci Geno-type of Pfcrt

Isolate sources Iso-lates n=79

Preval- ence

mscrt-29

mscrt -2

msint3

msint2

Clinical Asymp-tomatic

E1 149 179 198 204 CVIET 35 30 65 82.3% E2 149 181 198 204 CVIET 3 2 5 6.3% E3 149 179 198 209 CVIET 0 2 2 2.5% E4 149 179 198 215 CVIET 1 1 2 2.5% E5 149 179 198 197 CVIET 0 1 1 1.3% E6 149 181 198 215 CVIET 3 0 3 3.8% E7 149 177 198 204 CVIET 1 0 1 1.3% Haplotypes ID (E1-E7) were classified as different if they contained ≥ one different alleles across all loci. Allelic size at each MS locus is shown.

The widespread resistance to chloroquine in Ethiopia has triggered and urged the distribution of ACT for falciparum malaria. Therefore, artemether-lumefantrine has been the choice for P. falciparum therapy in Ethiopia since 2004. The high level of pfcrt K76T mutation observed in this study is in accor-dance with a study conducted in a rural hospital in southern Ethiopia (Mula,

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Fernandez-Martinez et al. 2011),although CQ has, since 1999, been with-drawn in Ethiopia. This is the first report in Ethiopia to reveal the presence of a single CQR mutant pfcrt genotype, CVIET the most common haplotype in Africa.

The CQR isolates from our study findings showed reduced diversity with respect to all MS markers (two introns and two flanking). The isolates were 89.9, 100, 88.6 and 100% identical with respect to msint 2 (0 kb), msint 3 (0 kb), mscrt -2 (-2.814 kb) and mscrt -29 (-29.268 kb), respectively. Of the seven haplotypes identified in the study area, haplotype E1 is the most prevalent allelic type. It can be inferred from this study that parasites identi-fied from asymptomatic subjects are more diverse than those present in symptomatic infections (clinical) sample sets. Even though malaria transmis-sion setting of the study area was low, asymptomatic parasite carriage is still associated with a higher multiplicity of infection. The number of MS alleles varied among the pfcrt introns and flanking loci that were successfully ana-lysed, with msint 2 displaying the greatest number of alleles (n = 4). On the other hand, msint 3 and mscrt -29, showed no polymorphisms. The low het-erozygocity of intronic and flanking MS alleles shown in this study may indicate that the parasite population in the study area is genetically homoge-neous, which could be the result of the CQ-selective sweep.

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Conclusions

The parasite population can be dynamic in an individual even during asymptomatic infections. Microsatellite analysis showed clear signs of variation in infected individuals during a long period with no transmission of malaria.

Real-time PCR was demonstrated to be a reliable method for meas-uring varying amounts of P. falciparum parasites collected from old samples, and the parasite levels observed matched those obtained earlier by microscopy studies.

PCR was found to have good sensitivity to detect a higher number of

infected subjects with low and sub-microscopic parasite densities than RDTs and microscopy.

Decreased diversity in markers surrounding pfcrt in chloroquine resistant isolates suggests that chloroquine selection has led to homogenization among the parasite population in the study area in Ethiopia.

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Acknowledgments

I would like to express my sincere gratitude to everyone who has contributed to this work and helped me along the way: First and foremost, I would like to thank my supervisor Göte Swedberg for giving me this opportunity to explore the world of research. Your sense of humour really is the stuff of legends.

Special thanks to my examiner Erik Fries for the interesting discussions about both science and life. Big thanks go to Barbro Lowsin. You have been incredibly supportive during the period of my PhD study. The administrative and technical staff Susanne L, Rehné, Alexis, Erika, Veronica, Marianne, Kerstin, Olav and Magnus, thank you for all your assistance throughout the years and you should all know how great you are. My co-authors, especially Susanne Kerje and Lemu Golassa, for fruitful collaborations. Former members of the GS-lab: Izla, Hasanti, Iouana, Irem, Mona, Rebecca, Lamjia, Ali S and Ahed; we truly had some amazing times. My great students: Mevan, Fatemahe, Valentina, Omar, Ali, Ravin, Katia, Toqa. In addition, Sama, even though you were not really my stu-dent, you are a wonderful person. Wiliam, Erasmus and Chi, my African friends, thank you for the fruitful discussions and advice. Many thanks to Amany and Hamza. Shady and Wael for creating a nice atmosphere in the BMC, especially when we played ping-pong.

Many thanks go to my former office mates Yani, Benjamin and Andrea. Dan Andersson-lab former members: Maria, Anna, Sanna, Peter, Chris and Song, thank you for being helpful and truly inspiring scientists. The present members: Marlen, Marius, Lisa T, Sohaib, Jocke, Anna, Ulrika, Hava, Lisa A, Hervé, Michael, Fredrika, Karin and Erik always have a smile to greet me, which means a lot on bad days. Linus, thank you for all the comments and questions in my half-time exam. You opened my eyes to the critical points in my work.

40

Diarmaid Hughes-lab: Lisa P, Rahel, Eva G, Linnea, Franzi, Jessica, Sha, Gerrit and Douglas - thank you guys for bringing life to the lab and you should all know how great you are. I would like to express my warm thanks to Camilla Eriksson and Magnus Jansson for helping me design the cover of my thesis. Many thanks go to Roshi, Mehran, Armita, Almera and Claudia.

Special thanks go to the Swedish Malaria Network (SMN) Stockholm, Sweden for organising the SMN annual meeting and the Nordic malaria conference.

Many thanks go to former Libyan students in Sweden: Khaled Nadeem, Ali, Ahmed Elmarghani, Mohammed R, Osama, Jamal, Mohsen, Yousef E and to my friends in Uppsala Sami, Fathi, Ibrahim, Adel, Abdelmoati and Yousef (Elwanasa!!!).

My friends in Libya: Osama Alsertawi, Ibrahim Elmarghani, Aimen El-kanuni, Khaled Rzzam, Seddik Ben-Milad, Tarek Elmezdawi, Ab-dulrrahaman Elmezwegi, Ezz-Eldeen Abed, Enser, Ibrahim Nweji, Ali Algordab, Adnan Daza, Taha Elnefathi, Abdulkareem Alhrary, Omar Almogerbi, Sabri Altwejery, Adel Ben-Taher, Nouri Elgmatti, Adel Almabrook and Mr. Yousef Greaa; we have shared a million memories, some sad and many happy ones, and opened those special places in the heart, thank you.

My teachers at Tripoli University, Abobaker Algosbi, Mogahed Abosh-werb and Lutfi Ben Mosa. I will never forget your help and support and I know that being able to help someone learn something is a talent.

My best friends in Uppsala Mevan Nadir and Mohammed Alzrigat - you guys made my life so wonderful in Sweden, thank you. I am also sincerely grateful to my neighbours Hasan Baygan, Ibtisam Zaza, Basel and Manar Irabi. I am really thankful and it will be very difficult in the future not hav-ing you around. My friends at Uppsala Budoklubb (Aikido group), I have learned a lot from you all, thank you.

Mohamed Atiya, Guma Abdeldaim and Abdurrahaman Ben Nweji - this is one of the hardest parts of my thesis to write, you should know that your support and encouragement was worth more than I can express on paper but I have to say that a million friends is not a miracle!! The miracle is to make such a friend who can stand with you when millions are against you. Thank you.

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My relatives Mansour, Mohamed, Nageuaa, Hamida, Mufida and Entesar Nweji. Anas and Amir Elkanuni and Aimen dahdah. Thank you for your support. Above all, All thanks to my merciful God (Allah) for being always there for me. And then to:

My wonderful sister and fantastic brothers, I am proud to have you all in my life, thank you for your support, encouragement and never ending faith in me.

A special thanks to my parents: words cannot express how grateful I am to my mother and father for all of the sacrifices that you’ve made on my be-half. Your prayers for me were what sustained me thus far. I love you so much. Last but not least, I would like express appreciation to my beloved wife Hanan Sharif for her understanding and love during all these years. Your support and encouragement was in the end what made my PhD thesis possible. I ♥ you darling. And last, 100 kisses goes to my little princess Nour (my eyes), you are the queen of my heart and you are the best thing that has happened in my life. When I come home and see your face and hear your excited screams all my troubles and worries melt away. I finally found what true love means, I love you so much.

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,أبي العزيز

, أكتب أسطري ھذه وأنا في غاية الشوق لك ولرؤياك ولتقبيل رأسك الزاكي ويدك الكريمةأبي الحبيب أعلم أن ھذه الكلمات التي تعبّر عّما في داخلي من شكر وحب وتقدير لجھودك

ولكنني أعلم أشد العلم بأن ُدعائي لك , عليه االن لن تصلكوتضحيتك لكي أصل الي ما أنا أبي الغالي يصعب عليّا تصديق أنني لن أراك مرةً أخرى وأنك قد رحلت عنّي بدون . يصلك

وكم كنت أتمنى أن تكون بجانبي يوم حصولي على شھادة الدكتوراة ألنك أنت , أن أودعكدراستنا ونجاحنا أنا وأخوتي والحمد لطالما كنت حريصا جدا على , من يستحق التكريم

.الذي وفقني في تحقيق أحد أمانيك أسأل هللا العلي القدير أن يرحمك ويغفر لك ويُنير قبرك ويجعله روضة من رياض الجنّة

).آمين يارب العالمين(

,أمي الحبيبة الغالية ر وعرفان على كل مامن الصعب أن أجد الكلمات التي تعبّر عّما في داخلي من حب وتقدي

أسأل هللا العلي , قّدمتيه لي والزلتي تقّدميه وبارك هللا فيك ورزقني بّرك وأطال هللا في عمرك!أحبك يا أمي.. القدير أن يوفقني على ارضاؤك

,إخوتي األعزاء

.أتمنى لكم التوفيق. ليالدائم وسام ورامي شكرا على تشجيعكم ودعمكم , طالل, حاتم, إبتسام

وعبد أيمن الكانوني, إبراھيم المرغني, أسامة السرتاوي,محمد عطية ,عبد الرحمان نويجي .الرحمان المزوغي شكرا على وقوفكم إلى جانبي طيلة فترة دراستي

محمد وبشير الشريف وأُسرھم الكريمة جزاكم هللا كل خير على محبتكم , راشد خليفة

.تي لكم بالتوفيقتمنيا.. ووقوفكم بجانبي في جميع الظروف

عائلة محمد الشريف شكراً جزيال لكم على كل ماقدمتوه من حب ودعم وتشجيع طيلة فترة .دراستي

ل هللا أن يوفقني على رعايتكم واسعادكم طوال بة نور وزوجتي الغالية أم نور أسأإبنتي الحبي

.أشكركم على حبكم ودعمكم لي, عمري

Nizar Enweji 20 August 2014 Uppsala, Sweden

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