PLASMODIUM FALCIPARUM HISTIDINE- RICH PROTEIN 2 GENE VARIATION AND MALARIA DETECTION IN MADAGASCAR AND PAPUA NEW GUINEA
by
NIGANI WILLIE
Submitted in partial fulfillment of the requirement for the degree of
Master of Science
Biology
CASE WESTERN RESERVE UNIVERSITY
May, 2018
CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES
We hereby approve the thesis/dissertation of Nigani Willie candidate for the degree of Master of Science*
Committee Chair Hillel Chiel
Committee Member Peter A. Zimmerman
Committee Member Emmitt Jolly
Committee Member Daniel Tisch
Date of Defense February 16, 2018*
*We also certify that written approval has been obtained for any proprietary material contained therein.
Contents ACKNOWLEDGEMENTS ...... vii ABSTRACT ...... 0 CHAPTER 1: LITERATURE REVIEW ...... 1 1.1. MALARIA EPIDEMIOLOGY ...... 1 1.1.1. MALARIA EPIDEMIOLOGY IN MADAGASCAR ...... 2 1.1.2. MALARIA EPIDEMIOLOGY IN PAPUA NEW GUINEA ...... 2 1.2. MALARIA PARASITE BIOLOGY ...... 3 1.2.1. LIFE CYCLE OF MALARIA PARASITES ...... 4 1.2.2. MALARIA PARASITE VECTORS ...... 9 1.2.3. CLINICAL SYMPTOMS OF MALARIA INFECTION ...... 10 1.3. BRIEF HISTORY OF MALARIA PARASITE DISCOVERY ...... 10 1.4. MALARIA CONTROL: DIAGNOSIS AND TREATMENT ...... 11 1.4.1. MALARIA MICROSCOPY ...... 14 1.4.2. MOLECULAR DETECTION OF MALARIA PARASITES...... 15 1.4.3. RAPID DIAGNOSTIC KITS AND MALARIA DIAGNOSIS ...... 16 1.5. HISTIDINE-RICH PROTEIN 2 ...... 17 1.5.1. BIOLOGICAL FUNCTION OF PfHRP2 ...... 18 1.5.2. PfHRP2-BASED RDTS ...... 21 1.5.3. THE PFHRP2 GENE ...... 22 1.5.4. BAKER AMINO ACID REPEATS AND FALCIPARUM RDT DETECTION ...... 24 CHAPTER 2: OBJECTIVE OF THE MASTERS THESIS ...... 26 CHAPTER 3: METHODS ...... 27 3.1. ETHICS STATEMENT ...... 27 3.2. STUDY SITES AND SUBJECTS ...... 27 3.2.1. SAMPLING IN MADAGASCAR ...... 27 3.2.2. SAMPLING IN PAPUA NEW GUINEA ...... 28 3.2.3. SAMPLE COLLECTION AND PROCESSING ...... 28 3.3. IN VITRO CULTIVATION OF P. FALCIPARUM PATIENT ISOLATES ...... 29 3.4. PREPARATION OF DNA TEMPLATES ...... 30 3.5. MOLECULAR DIAGNOSIS OF PLASMODIUM SPECIES INFECTION ...... 30 3.6. AMPLIFICATION AND DETECTION OF THE PFHRP2 GENE ...... 31 3.7. DNA SEQUENCE ANALYSIS OF THE PFHRP2 GENE ...... 32 3.8. STATISTICAL ANALYSES ...... 33 CHAPTER 4: RESULTS ...... 34 PART 1. MADAGASCAR ...... 34 4.1. DETECTION OF PLASMODIUM PARASITES IN MADAGASCAR ...... 34 4.1.1. MOLECULAR DIAGNOSIS OF MALARIA PARASITES IN MADAGASCAR ...... 34 4.1.2. PCR DETECTION OF THE PFHRP2 GENE IN MADAGASCAR ...... 34 4.1.3. RDT AND P. FALCIPARUM DETECTION IN MADAGASCAR...... 35 4.2. PFHRP2 GENE IN MADAGASCAR ...... 37 4.2.1. PFHRP2 GENE IN 5 CULTURED 5 P. FALCIPARUM ISOLATES ...... 37 4.2.2. AMPLIFICAITON OF PFHRP2 GENE IN MADAGASCAR ...... 40 4.2.3. SEQUENCING OF PFHRP2 GENE IN MADAGASCAR ...... 40 4.2.4. DISTRIBUTION OF PFHRP2 AMINO ACID REPEATS IN MADAGASCAR ...... 41 4.2.5. BAKER REPEAT TYPES AND RDT PERFORMANCE IN MADAGASCAR ...... 44 4.2.6. DISTRIBUTION OF PFHRP2 EPITOPES IN MADAGASCAR ...... 45 PART 2. PAPUA NEW GUINEA ...... 47 4.3. DETECTION OF PLASMODIUM INFECTIONS IN PAPUA NEW GUINEA ...... 47 4.3.1. MOLECULAR DIAGNOSIS OF PLASMODIUM IN PAPUA NEW GUINEA ...... 47 4.3.2. DETECTION OF THE PFHRP2 GENE IN PNG ...... 47 4.4. PFHRP2 GENE ANALYSIS IN PAPUA NEW GUINEA ...... 48 4.4.1. PFHRP2 GENE AMPLIFICAITON AND SEQUENCING IN PNG ...... 48 4.4.2. SEQUENCING OF PFHRP2 GENE PNG ...... 49 4.4.3 DISTRIBUTION OF PFHRP2 AMINO ACID REPEATS IN PNG ...... 50 4.4.4. BAKER REPEAT TYPES AND RDT IN PNG...... 54 4.4.5. DISTRIBUTION OF PFHRP2 EPITOPES IN PAPUA NEW GUINEA ...... 55 CHAPTER 5: DISCUSSIONS ...... 57 5.1. MADAGASCAR ...... 57 5.2. PAPUA NEW GUINEA ...... 61 5.3 LIMITATIONS ...... 64 CHAPTER 6: CONCLUSIONS ...... 65 APPENDIX ...... 67 Table A1. PCR Protocols ...... 67
ii
Table A2. Baker repeat “Barcodes” of Madagascar PfHRP2 exon-2 sequences in GenBank ... 68 Table A3. Baker repeat “Barcodes” of Madagascar PfHRP2 exon-2 sequences in This Study . 70 Table A4. Baker repeat “Barcodes” of PNG PfHRP2 exon-2 sequences in GenBank ...... 70 Table A5. Baker repeat “Barcodes” of PNG PfHRP2 exon-2 sequences in This Study ...... 71 FIGURE A1. 18S rRNA gene PCR gel ...... 72 FIGURE A2. PfHRP2 primer set#2 PCR ...... 73 FIGURE A2.1. PfHRP2 primer set#2 PCR on P. falciparum laboratory strains ...... 73 FIGURE A2.2. PfHRP2 primer set#2 PCR on Madagascar samples ...... 74 FIGURE A2.3. PfHRP2 primer set#2 PCR on Papua New Guinea samples ...... 74 FIGURE A3. PfHRP2 primer set#3 (nest 2) PCR on Madagascar samples ...... 75 FIGURE A3. RDT detection of Malaria in P. falciparum culture isolates ...... 76 REFERENCES ...... 77
iii
List of Tables
Table 1.1 Types of Baker Amino Acid Repeat Types in PfHRP2 ...... 24 Table 4.1. pfhrp2 gene vs 18S rRNA gene detection in Madagascar ...... 34 Table 4.2. pfhrp2 gene vs LDR-FMA malaria detection in Madagascar ...... 34 Table 4.3. RDT vs 18S rRNA gene detection in Madagascar ...... 36 Table 4.4. RDT vs LDR-FMA malaria detection in Madagascar ...... 36 Table 4.5. Prevalence of Baker amino acid repeat types in Madagascar ...... 43 Table 4.6 Prediction of RDT detection sensitivity of P. falciparum in Madagascar ...... 44 Table 4.7. Baker repeat types and Malaria Diagnosis in Madagascar ...... 45 Table 4.8. Prevalence of PfHRP2 major epitopes amongst P. falciparum in Madagascar ...... 46 Table 4.9. pfhrp2 gene vs 18S rRNA gene detection in PNG ...... 47 Table 4.10. pfhrp2 gene vs LDR-FMA malaria detection in PNG ...... 47 Table 4.11. Prevalence of PfHRP2 amino acid repeat types in PNG ...... 51 Table 4.12. Prevalence of “Non-Baker” amino acid repeat types in Madagascar and PNG ...... 53 Table 4.13. Prediction of RDT detection sensitivity for Papua New Guinea ...... 54 Table 4.14. Baker Repeat Types and Malaria Diagnosis in Papua New Guinea ...... 55 Table 4.15. Prevalence of PfHRP2 major epitopes amongst P. falciparum in Papua New Guinea ...... 56
iv
List of Figures
Figure 1.1 Life Cycle of Malaria Parasites. 4 Figure 1.2 Location of the pfhrp2 gene on chromosome 8 flanked by seven microsatellites 23 Figure 3.1 Diagrammatic representation of the overlapping regions of the pfhrp2 gene amplified by using three different sets of primers. 31 Figure 4.1 Agarose (1.5%) gel of pfhrp2 gene PCR using primer set #1 on P. falciparum culture isolates from Madagascar. 38 Figure 4.2 Agarose gel (2%) of pfhrp2 gene PCR using primer set #2 on P. falciparum in blood spots from Madagascar. 38 Figure 4.3 Agarose (1%) gel of pfhrp2 gene PCR using primer set #3 on P. falciparum culture isolates from Madagascar. 38 Figure 4.4 Alignment of PfHRP2 exon-1 amino acid sequence of 5 P. falciparum culture isolates from Madagascar and reference sequence. Figure 4.5 Average frequency of Baker amino acid repeat types in Madagascar PfHRP2 sequences from the current study and previous studies. 42 Figure 4.6 Average frequencies of 14 major epitopes (RDT MAbs targets) found in Madagascar PfHRP2 sequences. 46 Figure 4.7 Average frequency of Baker amino acid repeat types in Papua New Guinea sequences from the current study and previous studies. 52 Figure 4.8 Average frequencies of 14 major epitopes (RDT MAbs targets) found in PNG PfHRP2 sequences. 56
v
LIST OF ABBREVIATIONS
CDC Center for Disease Control
DNA Deoxyribonucleic acid
RNA Ribonucleic acid
18S rRNA Small subunit ribosomal RNA
LDR-FMA Ligase Detection Reaction-Fluorescent Microsphere Assay pfhrp2 Plasmodium falciparum histidine-rich protein 2 gene
PfHRP2 Plasmodium falciparum histidine-rich protein 2
HRP2 Plasmodium falciparum histidine-rich protein 2
PfHRP3 Plasmodium falciparum histidine-rich protein 3
HRP3 Plasmodium falciparum histidine-rich protein 3
P. falciparum Plasmodium falciparum
P. vivax Plasmodium vivax
P. malariae Plasmodium malariae
P. ovale Plasmodium ovale
P. knowlesi Plasmodium knowlesi
PCR Polymerase Chain Reaction qPCR Quantitative PCR, real time PCR
PNG Papua New Guinea
RDT Rapid Diagnostic Test
RBC Red Blood Cells, erythrocytes
WHO World Health Organization
vi
ACKNOWLEDGEMENTS
I would like to thank all the great people who have made my master’s degree possible. I thank my advisor, Dr. Peter A. Zimmerman for accepting me into his lab and allowing me to work on this research project. I also thank him for his advice, guidance and resources without which the research would be impossible. I also want to thank Dr. Rajeev K. Mehlotra for his time and immense contributions to my research. His advice, patience and mentorship were vital to my research. I also appreciate and thank the people in Zimmerman Lab (2015-2017), namely Dr. Daniel Tisch, Melinda Zikursh, Julie Jules, Scott Small and Krufinta Bun who have all contributed to my learning of laboratory procedures (bench-work), data analysis and writing of this thesis. I also want to thank all the study participants and collaborators (Dr. Rosalind Howes and colleagues) in Madagascar (2013–2017) and Papua New Guinea (2001–2003) who made this study possible. I thank Dr. Kazura and the Center for Global Health and Disease and its administration, Dr. Zimmerman and the Fogarty International Training Grant for accepting me and supporting my study at Case Western Reserve University, Cleveland, Ohio. I also thank Julia Brown and the Biology Department, the CWRU School of Graduate studies and the International Students Services (ISS) for their support. I heartfelt gratitude to the Jasper family for becoming my family making Cleveland feel like home. Also, I want to personally thank each and every person for all the support and for being there when I was diagnosed and received treatment for heart disease. God bless you all. I also would like to thank my father and my late mother for bringing me into this world and pushing me to do more in life. I thank my family and, my daughters who are now the inspiration in my life to do even more. Finally, I thank God for everything – for life, its blessings and lessons.
vii
Plasmodium falciparum Histidine-rich Protein 2 Gene Variation and Malaria Detection in Madagascar and Papua New Guinea
NIGANI WILLIE ABSTRACT
Plasmodium falciparum histidine-rich protein 2 (PfHRP2) forms the basis of many current malaria
rapid diagnostic tests (RDTs). However, parasites lacking the pfhrp2 gene do not express the
PfHRP2 protein and are, therefore, not identifiable by PfHRP2-detecting RDTs. In this study, the
performance of the SD Bioline Malaria Ag P.f/Pan RDT together with pfhrp2 variation in
Madagascar was evaluated. The study also evaluated pfhrp2 gene variation in PNG. Genomic
DNA isolated from patient blood samples from Madagascar (n = 260) and PNG (n = 169) were
subjected to molecular detection (18S rRNA PCR, followed by post-PCR LDR-FMA) for the identification of Plasmodium spp. infections. PCR amplification of the pfhrp2 gene, sequencing and gene analysis enabled studying of gene variation. PCR diagnosis showed that 28.8% (75/260) in Madagascar and 81.1% (137/169) in PNG had Plasmodium infections. 94.6% (71/75) and 91.2%
(125/137), of the infections were P. falciparum in Madagascar and PNG, respectively. Compared to molecular detection, the sensitivity and specificity of the RDT (in Madagascar) for P.
falciparum detection were 87% and 89%, respectively. From randomly selected pfhrp2 gene- positive samples, 16 pfhrp2 gene sequences from Madagascar and 18 pfhrp2 gene sequences from
PNG were generated. Although extensive variations of the pfhrp2 gene were observed in both countries, this study showed that there was no indication of pfhrp2 deletion. The study also did not observe a clear correlation between pfhrp2 sequence structure and RDT detection rates. Although the absence of pfhrp2 deletion from the samples screened here is encouraging, continued monitoring of the efficacy of RDTs currently used in Madagascar and PNG is warranted. CHAPTER 1: LITERATURE REVIEW
1.1. MALARIA EPIDEMIOLOGY
Malaria remains a high cause of morbidity and mortality in the world.1–3 According to the World
Health Organization (WHO) World Malaria Report of 2017, about 445,000 people die every year
due to malaria and about half of the world’s population (~3.2 billion people) are at the risk of a
malaria infection.1 In 2015, it was estimated that global deaths caused by malaria occurred mostly
in the African Region (91%), followed by the South-East Asia Region (6%) and the Eastern
Mediterranean Region (2%).1 The vast majority of deaths (99%) are due to P. falciparum malaria.
P. vivax is estimated to have been responsible for 3100 deaths in 2015 (range: 1800–4900), with
86% occurring outside Africa.1
About 216 million cases of malaria occurred worldwide in 2016 (95% confidence interval
(CI: 196-263 million), compared with 237 million cases in 2010 (95% confidence interval (CI:
218-278 million) and 211 million cases in 2015 (95% confidence interval (CI: 192-257 million).
Most of the cases were from the African Region (90%), South-East Asia Region (7%) and the
Eastern Mediterranean Region (2%).1 Between 2000 and 2015, the global incidence rate of malaria
decreased by 41% globally to 21%.1 Of 91 countries and territories with malaria transmission in
2015, 40 are reported to have achieved a reduction in incidence rates of 40% or more from 2010
to 2015, and can be considered on track to achieve the WHO Global Technical Strategy milestone
of a further reduction of 40% by 2020.1
The African region accounts for 88% of the global cases of malaria, the South-East Asia
Region accounts for 10% and, the Eastern Mediterranean Region accounts for about 2%.1,2 The
most prevalent malaria parasite in the African region is P. falciparum and for most countries
outside of sub-Saharan Africa, P. vivax is the dominant malaria.1,3
1
1.1.1. MALARIA EPIDEMIOLOGY IN MADAGASCAR
Malaria is a major public health concern in Madagascar.1,4,5 Intervention programs introduced in
2000 brought substantial reductions in malaria infections to this East African island country.4,6
This progress, however, was disrupted by political instabilities in 2009 leading to a re-emergence
of cases in 2010.4,6
In 2015, about 2.4 million cases of malaria have been reported in Madagascar and over 550
deaths are estimated to occur annually due to malaria.7 According to a major national review of
the health status of the Malagasy population, malaria is the second most common cause of death
in children under 5 years in district hospitals and the fourth leading cause of all outpatient
consultations across all age groups.8
The WHO reported that over 90% of the Malagasy population (23 million people) are at
the risk of malaria infection.1 The island of Madagascar is biogeographically diverse, with varied
malaria transmission patterns across different parts of the island ranging from epidemic, to highly
seasonal, to sustained year-round transmission.4
Malaria in Madagascar is predominantly caused by P. falciparum, though the other three
human Plasmodium spp. are also present.4 Collective reports estimate that 96% of the malaria cases are due to P. falciparum infections and about 4% are caused by P. vivax.7 P. vivax malaria
infections are found most commonly found in the fringe zone between the west coast and the
central highlands.4
1.1.2. MALARIA EPIDEMIOLOGY IN PAPUA NEW GUINEA
Malaria is also a major public health concern in Papua New Guinea (PNG),9–11 an island country
in the south Pacific region, known for its rigid terranes, thick rainforests and swampy areas. The
epidemiology of malaria is remarkably complex in PNG due to the environmental and cultural
2
diversity in the country.9,12 The intensity of infection in PNG is described as ranging from unstable
low levels of endemicity where outbreaks are common to holoendemic transmissions comparable
to that seen in sub-Saharan Africa.9
All four human species of malaria causing parasites are found in both lowland and highland areas of PNG with P. falciparum infections reaching holoendemic levels.9,13 P. falciparum and P. vivax are responsible for 65%–80% and 10%–30% of malaria infections in PNG, respectively.14
The high frequency of P. vivax is an important difference to most African situations.9
About 1 million people in PNG are infected every year and around 500 deaths are caused
by malaria every year.14 According to WHO reports, almost 96% of the population (7.8 million
people) are at risk of malaria infection.1
1.2. MALARIA PARASITE BIOLOGY
Malaria is an acute, febrile disease that can rapidly develop into a deadly disease if left
untreated.15,16 This deadly disease is caused by parasites of the Plasmodium genus that are spread
through the bites of infected female Anopheles mosquitoes.17
Malaria is prevalent in tropical and subtropical regions of the world where Anopheles mosquitoes
can survive and multiply.16,17 Most of these tropical countries are also developing countries and
many are resource-challenged.1,15,16
Four species of Plasmodium parasites are known to cause malaria in humans: Plasmodium
falciparum (PF); Plasmodium vivax (PV); Plasmodium malariae (PM) and; Plasmodium ovale
(PO).16 A fifth parasite, P. knowlesi (PK), primarily infecting the Asian macaque is also known to cause zoonotic infections.15,16 Plasmodium parasites have a complex life cycle that requires a
mammalian host and a mosquito vector.15,16
3
1.2.1. LIFE CYCLE OF MALARIA PARASITES
Figure 1.1. Life Cycle of Malaria Parasites [Zimmerman and Howes, 2014]
Throughout their life cycle, Plasmodium parasites undergo different developmental stages that are
reflected in by morphological changes. The life cycle of a malaria parasite can be divided into two developmental stages: asexual reproduction, which occurs in mammalian hosts and; sexual reproduction, in the mosquitoes.16
Each Plasmodium species exhibit characteristic morphologies (size, shape and appearance)
in different developmental stages. By morphology, the asexual stage in mammals can be further
divided into four developmental stages: hepatic schizonts; intra-erythrocytic trophozoite; schizont
4 and gametocyte stages. The sexual reproduction stage in mosquitoes can also be further divided into three developmental stages: ookinete; oocyst and sporozoite stages.18
A malaria infection is initiated when an infective female Anopheles mosquito bites a mammalian host for a blood meal. During the blood meal, the infected mosquito may inject about
15-200 elongated sporozoites, from their saliva into the host.18 The introduced sporozoites, each about 15µm in length, reach the host blood vessels by migrating through the host dermal tissue.
Sporozoites may also be deposited in a blood pool formed from blood capillary damage by a mosquito during probing and the deposited sporozoites may then enter host blood vessels. Recent studies have shown that it may take up to 1-3 hours for sporozoites to reach blood vessels from the bite sites.19 Once in circulation, sporozoites passively reach the liver sinusoids in about 10-30 minutes.20
From the liver sinusoidal vein, the sporozoites actively breach the sinusoidal wall to enter the hepatocytes to initiate liver invasion.20 The sinusoidal wall is a cell layer composed of highly fenestrated endothelial cells and Kupffer cells, which are resident macrophages in the liver.20
Sporozoites get to the hepatocytes through the Kupffer cells via internalized vacuoles21 or, by migrating extracellularly through the fenestrations of the sinusoidal endothelial cells.22 It is now known that sporozoites may transverse several hepatocytes before invading one that will serve as the host cell. This particular behavior of the sporozoites is not well understood.23
A sporozoite invades its host hepatocyte through an invagination process of the host cell membrane to form a parasitophorous vacuole, within which the parasite resides throughout liver stage development.24 This process requires release of parasite proteins that carry out membrane remodeling functions to facilitate invasion of the host cell.24 The rapid invasion of hepatocytes suggests efficient specific targeting of the hepatocytes by parasites.24
5
Within the hepatocyte, the invasive sporozoite differentiates into a liver stage trophozoite, the replicative form (or schizont). The differentiation process involves the breaking down and active expulsion of the sporozoite inner membrane complex. Organelles (such as mitochondria, endoplasmic reticulum), required for parasite replication within the hepatocyte are retained.24
Schizonts appear as clusters of small basophilic bodies usually exceeding the size of the uninfected hepatocyte (having diameters of about 40-80µm) when they mature.24 In P. vivax and P. ovale, instead of schizonts, the early trophozoite stage parasites differentiate into latent hepatic stages called hypnozoites, which are responsible for malaria episodes long after a mosquito bite.25
A schizont (mother cell) then undergoes exo-erythrocytic schizogony, which is a phase of asexual multiplication characterized by rapid growth and numerous rounds of DNA replication resulting in the replication of parasite organelles and the formation of a multinucleate syncytium.
Parasites derive nutrients from the host hepatocyte both by passive diffusion through pores in the membrane of the parasitophorous vacuole, and by active processes such as those that take up glucose.24
Morphological and positional changes then facilitate multiple invaginations of the parasite plasma membrane, packaging of organelles and eventually segregation into individual, uninucleate merozoites (daughter cells). The parasitophorous vacuole membrane then breaks down and merozoites are released into the host cytoplasm.24
The degradation of the parasitophorous vacuole membrane is immediately followed by, or simultaneous with, the packaging of merozoites into vesicles called merosomes. These merosomes are then extruded from the infected hepatocyte into the liver sinusoid. It was previously thought that the exponential increase in merozoite numbers causes the infected hepatocytes to rupture and spill into the liver sinusoid.18
6
It is estimated that about 30,000–40,000 merozoites, infectious to erythrocytes, are produced per
schizont in this liver stage.16,18 The exo-erythrocytic schizogony process lasts for about 5-7 days.
The pre-erythrocytic infection, from mosquito bite to merozoite release into the bloodstream is
said to last about two weeks.24
Infected hepatocytes, detach from the surrounding liver tissue caused by non-apoptotic and
non-necrotic cell death pathways induced by merozoites. Merozoites also inhibit the host DNA
fragmentation and host mechanisms to delay cell death. This allows, the merozoite-containing
merosomes, whose membranes are composed of host hepatocyte plasma membrane, to evade
detection and engulfment by immune cells present in the liver. Merosomes then travel passively
in the bloodstream, through the heart and into the lung vasculature where they burst to release
merozoites into the bloodstream.24
Within 1-2 minutes of release, merozoites will attach to red blood cells (RBCs) via ligands
on the merozoite surface to their specific receptors on the RBC membrane.26 This leads to the RBC
invagination that allows entry of the merozoite into the RBC.26 In a similar fashion to that of
sporozoite differentiation in hepatocytes, the merozoite resides in a parasitophorous vacuole in the
RBC while undergoing development (erythrocytic schizogony). This involves transformation to
the early ring stage (immature) trophozoite.26 By microscopy, trophozoites appear as rings are
about 1-2µm in diameter.26
At this stage, a trophozoite can undergo one of two transformations.16,18 Firstly, the trophozoites may mature into schizonts which will develop into dozens of new merozoites.
Erythrocytic schizonts are multinucleate, amorphous in shape and about 7-8µm in length.
Merozoites formed in this stage may then initiate a second phase of asexual multiplication
(erythrocytic schizogony) where merozoites transform into a trophozoites, which form schizonts
7
that will form dozen new merozoites, i.e. asexual proliferation. Depending on the Plasmodium
species, about 6-32 new merozoites are produced per schizont thus an exponential production of
merozoites that will lead to the merozoites bursting from the schizont and rupturing infected RBCs.
Released merozoites then invade other uninfected RBCs. This process is repeated almost indefinitely and leads to the pathology and malarial symptoms that manifest in infected individuals.16,18,27
Alternatively, instead of undergoing asexual proliferation, immature trophozoites may
differentiate into male and female gametocytes (gamete precursors).28 Gametocytes are dormant
or non-pathogenic and can grow to lengths ranging 7-14µm, usually occupying most of the RBC
cytoplasm. Gametocytes in are roundish, have a pointed end and may have a visible distinctive
pigment pattern. They may be difficult to distinguish from immature trophozoites in a Giemsa-
stained blood film.28 When the mosquitoes bite a human host during a blood meal, gametocytes
circulating in blood are be taken up by mosquitoes.16,18,27–29
Gametogenesis, the development of gametocytes into microgametocytes and
macrogametocytes, mature male and female gametes, respectively, occurs in mosquitoes.
Gametocyte development involves morphological changes to the parasite, which can be divided
into five stages (I-V).16,18,27 The morphological features and differences between male and female
gametes are more apparent by Stage IV of development. The macrogametocytes are characterized
by a relatively small nucleus (with a nucleolus) and a dark-stained cytoplasm.28,30,31 The
microgametocytes, on the other hand, are about 15-25µm in length, slender, have a larger nucleus
but lack a nucleolus. Microgametes have a more diffused staining.30 The duration of gametogenesis
differs for each plasmodium species: P. falciparum takes about 8-10 days P. vivax and P. ovale,
take 3- 4 days and P. malariae takes about 6-8 days.31
8
In the mosquito gut, a (haploid) microgametocyte undergoes three rounds of nuclear division to
produce an eight nuclei (octaploid) flagella microgametes.32 Each resulting microgamete is
capable of penetrating and fertilizing a macrogamete i.e. fusion of the male and female gamete
plasma membranes followed by fusion of their nucleus to form a zygote.32 Zygotes transform into
extracellular, motile ookinetes. The ookinetes migrate out of the blood bolus, traverse the midgut
epithelium into the basal sub-epithelial space between the midgut epithelium and the basal lamina
(BL), where they transform into ovoid oocysts. The oocysts may have diameters of up to 50µm.33
The immature oocysts then undergo sporogenesis inside the mosquito cavity where they
mature and partition into sporoblasts (multinucleated oocysts). Sporozoites bud from these
multinucleated oocysts and when these oocysts burst, they release thousands of budding
sporozoites into the mosquito cavity. Most sporozoites develop abnormally, being shortened,
malformed and immotile, are not able to infect salivary glands. Relatively few (hundreds) of the
sporozoites develop normally being thin, elongate and about 15µm long are able to ultimately
affect the infected mosquito’s salivary glands.34 A sporogonic cycle can last 8-15 days.16,34 The sporozoites reach the mosquito salivary glands, where they attach to and invade gland cells.
Sporozoites transit through the cytoplasm of the gland cells and exit into the secretory cavity, where they come to rest and remain viable for weeks, awaiting the next blood meal for transmission to the vertebrate host. When infected mosquitoes blood-feed, they release salivary gland sporozoites into the skin.16
1.2.2. MALARIA PARASITE VECTORS
There are 41 known genera of mosquitoes and only the females in the Anopheles genus are vectors for Plasmodium parasites.17 The Anopheles genus has over 400 known species of mosquitoes and
30–40 of these are known to be these vectors, i.e. transmit malaria to humans.17
9
The successful development of Plasmodium parasites from gametocyte to sporozoite in a
mosquito, depends on factors such as ambient temperature, humidity and the survival of the
mosquito.17,18 Plasmodium parasites are not harmful to their mosquito vectors. 17,18,35
1.2.3. CLINICAL SYMPTOMS OF MALARIA INFECTION
An infected person diagnosed with malaria can generally be categorized as having either
uncomplicated, clinical or severe malaria.36 Symptoms of a malaria infection generally include
fever, headache, chills and vomiting.37 These symptoms usually manifest in infected individuals
7–15 days after the infection through the bite of an infected mosquito.37 If not treated within 24–
48 hours from the onset of symptoms, conditions usually worsen, progressing to severe malaria
which often leads to death of the patient.37,38
Severe malaria is characterized by one or more of the following clinical criteria: impaired
consciousness/coma, severe normocytic anemia [hemoglobin < 7], renal failure, acute respiratory
distress syndrome, hypotension, disseminated intravascular coagulation, spontaneous bleeding,
acidosis, hemoglobinuria, jaundice, repeated generalized convulsions, and/or parasitemia of ≥ 5%.
2,37,39 and should be treated aggressively with parenteral antimalarial therapy.37,38,40
1.3. BRIEF HISTORY OF MALARIA PARASITE DISCOVERY
Malaria parasites were first sighted in 1880 in the blood of an infected Algerian soldier by
Alphonse Laveran.41 Laveran called the malaria parasites, Oscillaria malariae.17,41 The scientific
community slowly accepted that malaria was caused by parasites as the oil-emersion microscope lens was invented coupled with the development of staining methods between 1880–1891.17,42,43
Italian scientists, Celli and Marchiafava, proposed the genus name Plasmodium for
malaria-causing parasites in 1886.44 In that same year, Camillo Golgi distinguished P. vivax from
P. malariae. Sacharov in 1889 and, Celli and Marchiafava in 1890 discovered P. falciparum as a
10
species different from P. vivax and P. malariae. Grassi and Felleti named Plasmodium vivax in
1892.17,44 In 1897, Marchiafava and Bignami showed that the parasite sighted by Laveran in 1880 was Plasmodium falciparum.17,44
In 1897 Ronald Ross found malaria parasites in Anopheles mosquitoes.17,44 Italian
scientists confirm that female anopheles mosquitoes were responsible for transmitting malaria to
humans in 1898.44 In that year, Ross also showed malaria parasites develop in the mosquito gut and migrate to its salivary glands.17,44 In 1901, the first experimental evidences of malaria relapses
were reported by Manson.17 Mesnil and Roubaud achieved the first experimental infection of
chimpanzees with P. vivax in 1917.17
In 1920, Marchoux proposed three possible models to account for relapse in 1926.17 James
in 1931 and Fairly in 1945, demonstrated the transportation of sporozoites to extra-erythrocytic tissues.17 Shute in 1946, proposed that there is sometimes a delay of malaria onset after mosquitoes
feed on humans.17
In 1948, Shortt and Garnham discovered the developmental hepatic stages and blood stages
of the malaria parasite. The dormant liver stages and final stages in the parasite life cycle was
demonstrated in 1982 by Krotoski.42,43,45
1.4. MALARIA CONTROL: DIAGNOSIS AND TREATMENT
The WHO stated in its ‘Global Technical Strategy (GTS) for Malaria 2016–2030’ that malaria elimination requires “universal diagnosis and prompt effective treatment of malaria in public and private health facilities and at community level.” 46 The WHO defines malaria elimination as “the interruption of local mosquito-borne malaria transmission, i.e. the reduction to zero of the incidence of malaria infection in a defined geographical area.”46 Prevention of re-establishment
of transmission after elimination is necessary for malaria control and elimination programs.27,46–49
11
The accurate and accessible diagnosis of malaria is essential for its control and
elimination.1 The WHO recommends that the diagnosis of all suspected malaria cases should be
confirmed by reliable parasite detection methods before administering antimalarial treatment.1
Diagnostic methods such as quality-assured light microscopy,50 antibody-based Rapid Diagnostic
Test kits (RDTs) 51–53 and nucleic acid amplification (NAA) methods27,54,55 have been and are still
very crucial in the substantial progress made towards reducing the malaria burden across the world
and achieving the goals of malaria elimination programs.2,3,46,56
Almost all diagnostic methods in malaria parasite detection are known to have reached a limit of detection (LOD) which vary from one type to another.27,57,58 Sub-microscopic infections
(SMIs) are “invisible” to microscopy27,39,59 and PCRs may not be able to detect developmental
stages of parasites and infections below 0.05 iRBCs/uL, and most NAA methods are laboratory-
bound. Deletions and possibly variation in the genes for RDT target proteins, i.e. P. falciparum
Histidine-rich protein (pfhrp2),52,60–67 have been reported to be the causes of decreased
sensitivity53,65,68–70 and/or false negative71–76 and false positive77–80 results in parasite detection by
RDT.
Accurate diagnosis is important before treatment is administered. The Center for Disease
Control (CDC) has stated three important reasons for determining an infecting Plasmodium species
for treatment purposes.40 Firstly, P. falciparum and P. knowlesi infections can cause rapidly progressive severe illness or death while the other species, P. vivax, P. ovale, or P. malariae, are
less likely to cause severe manifestations.40 Secondly, P. vivax and P. ovale infections also require treatment for the hypnozoite forms that remain dormant in the liver and can cause a relapsing infection.40,81 Finally, P. falciparum and P. vivax species have different drug resistance patterns in
12 differing geographic regions.82,83 For P. falciparum and P. knowlesi infections, the urgent initiation of appropriate therapy is especially critical.36,40
Patients diagnosed with uncomplicated malaria due to P. falciparum can be treated with oral chloroquine right after diagnosis and at 6, 24, and 48 hours. Alternatively, hydroxychloroquine may also be taken orally similarly. The initial doses are usually twice the amount of the follow-up doses.40 Four other options are recommended for chloroquine-resistant P. falciparum infections.
Atovaquone-proguanil (Malarone), artemether-lumefantrine (Coartem) combination medicines are the first two options and both also be used for non-pregnant adult and pediatric patients.40 The third option for treatment is quinine sulfate combined with doxycycline, tetracycline or clindamycin. It is recommended that quinine treatments are continued for 7 days.40 The fourth option, mefloquine, is only recommended when the options cannot be used, since it is associated with rare but potentially severe neuropsychiatric reactions.40,84 The treatment options are the same for both pediatric patients and adults except that dosage is adjusted by weight.40
For P. vivax and P. ovale infections where relapse can occur due to hypnozoites that remain dormant in the liver, a 14-day course of primaquine phosphate is recommended by CDC.40,81
Screening of patients are required for glucose-6-phosphate-dehydrogenase (G6PD) deficiency, prior to treatment, because primaquine can cause hemolytic anemia in G6PD-deficient individuals.40,81 Primaquine is not recommended for pregnant mothers and children less than 8 years old.40,81
The WHO Guidelines for Treatment of Malaria85 recommends artemisinin-based combination therapies (ACT), namely atemether-lumefantrine, artesunate-amodiaquine, artesunate-mefloquine, dihydroartemisinin-piperaquine, artemisinin-sulfodoxine-pyramethamine
(SP), for treating children and adults with uncomplicated malaria (except women in first-trimester
13
pregnancy) for 3 days.85 According to this guideline, pregnant women in the first trimester with
uncomplicated malaria should be treated with quinine and clindamycin for 7 days.85
In people who have HIV/AIDS with uncomplicated malaria, the WHO treatment guidelines
advises to avoid artesunate-SP combination if they on co-trimoxazole treatment and, artesunate-
amodiaquine f they are on efavirenz or zidovudine.85
The WHO also advises G6PD-testing for guiding primaquine administration for treating
and preventing relapse of P. vivax and P. ovale infections. A 14-day course of primaquine (0.25-
0.5 mg/kg by weight daily) is recommended except for pregnant women and infants aged less than
6 months. In people with G6PD deficiency, an 8-week course of primaquine base at 0.75mg/kg by
weight once with close medical supervision for potential primaquine-induced hemolysis is strongly
advised by the WHO Guidelines for Treatment of Malaria.85
1.4.1. MALARIA MICROSCOPY
Light microscopy (LM) is still considered the gold standard in in the world for the detection
of Plasmodium parasite infections in humans. LM is still widely used due to its low cost, less
sophistication and high positive predictive values.57,58,86
To examine a patient’s blood for malaria parasites, a slide is prepared by spreading out a
drop of the patient’s blood in a “blood smear” on a microscope slide and staining with Giesma
stain to give parasites a distinctive appearance.30 The blood slide is then examined by a skilled
laboratorian to determine the presence, the species of the parasites and, the density of infection,
i.e. parasitemia.30,87
The limit of detection (LOD) for thick (1.0 x 106 RBCs) and thin (1.25 x 105 RBCs) blood smears in microscopy is about 5–200 iRBCs per µL (0.00010000–0.0010000%) where an average microscopist may detect >100 iRBCs and an expert microscopist may detect >5-10 iRBCs.27 The
14
LOD and also the quality of results for microscopy diagnosis depends on the quality of the
reagents, of the microscope, and on the experience of the microscopist.27,30,87
Although microscopy is much simpler and less costly compared to molecular methods, it
is not readily available in most malaria-endemic countries. Microscopy is also labor-intensive and
time-consuming. It requires substantial training and expertise due to fleeting skills. These
problems are magnified in non-endemic regions where light microscopy is infrequently performed
for malaria diagnosis, resulting in missed diagnosis, misidentification of Plasmodium species, and
therapeutic delays. In many remote health centers, there may be no appropriate microscope in
working order or a lack of consumables, such as slides or Giemsa stain, and most times the staff
may have not received appropriate training.27,30,57,58,87
1.4.2. MOLECULAR DETECTION OF MALARIA PARASITES
Alternative methods for malaria parasite detection include nucleic acid amplification
(NAA) techniques, such as conventional polymerase chain reaction (PCR) and real time PCR (q-
PCR) and ligase detection reaction-fluorescent microsphere assay (LDR-FMA).27,55,88 DNA (or
RNA) from parasites are extracted from peripheral blood of patients and gene amplification of specific parasite genes are used as makers for parasite detection.54,55,59
NAA techniques allow for more sensitive and specific detection of Plasmodium species
from peripheral blood. PCRs can detect parasites at very low parasitemia i.e. up to 0.05 iRBCs/uL
of blood or 0.00000100% parasitemia, which is about 2-4 orders of magnitude greater than
microscopy and RDTs.27 Molecular diagnosis techniques, such as PCR followed by LDR-FMA,
also enables the differentiation between plasmodium species and even laboratory strains.55,88
PCR is most useful for confirming the species of malarial parasite after the diagnosis has been
established by either smear microscopy or RDT.88 However, apart from posing similar
15
complications such as those discussed for microscopy, PCR techniques are often too expensive for
endemic countries, which are mostly developing countries where the need for diagnosis
paramount.88 In the standard healthcare setting, the use of PCR techniques are limited in the diagnosis of acutely ill patients. The turn-around time for PCR results are often not practical to be
of value in establishing the diagnosis of malaria infection.27
1.4.3. RAPID DIAGNOSTIC KITS AND MALARIA DIAGNOSIS
Rapid Diagnostic Test (RDT) kits are lateral flow devices that can detect parasite antigens present
in the peripheral blood of infected individuals. RDTs work by facilitating the migration (in a
mobile phase), of the antigens from a drop of peripheral blood (5-10µL), across a nitrocellulose
membrane and capturing the antigens by monoclonal antibodies (MAbs). MAbs are conjugated to
either a liposome containing selenium dye or gold particles in a mobile phase reaction. A second
or third capture monoclonal antibody applied to a strip on the surface of a nitrocellulose membrane
acts as the immobile phase. The migration of the antigen-antibody complex in the mobile phase along the strip enables the labeled antigen to be captured by the monoclonal antibody of the immobile phase, thus producing a visible colored line. Incorporation of a labeled goat anti-mouse antibody capture ensures that the system is controlled for migration.51,52,60
It has been reported that the sensitivity and specificity of RDTs in comparison to light
microscopy were about 98.2% and 97.1%, respectively and with PCR detection, the sensitivity and
specificity were 97.1% and 96.9%, respectively.62 While the limit of detection for RDTs is about
200 iRBCs/uL (0.01000000% parasitemia) on average,1,27 recently manufactured kits report
detection at 50 iRBCs/uL.72
RDTs are highly practical in developing countries where malaria is endemic. Their use in
malaria diagnosis in these countries, which are also resource-limited, has significantly increased
16
in the last decade or so.27,89 Microscopy and molecular methods due to their cost are not readily
available in remote health care facilities in most developing countries.89 The WHO recognizes
RDTs as the low cost and practical alternative to conventional light microscopy or molecular diagnosis and recommends RDTs as point-of-care diagnostic tools in developing countries.1,27,89
Apart from having low costs, RDTs do not require sophisticated equipment, technique, highly
trained laboratory personnel or electricity.69,80 RDTs also are easy to learn and have very short
turn-around times (~20 minutes).69,80 RDTs are also highly practical in developed countries since
laboratory technicians in these countries are rarely confronted with malaria and therefore not
experienced enough to reliably diagnose potentially life threatening falciparum malaria using
microscopy.89
The WHO reports that there has been a noticeable increase of malaria RDT sales (i.e.
between 2010 and 2016, over 1.66 billion RDTs were sold globally).1 According to the WHO 2017
malaria report, by 2016 over 312 million RDTs have been used worldwide for malaria diagnosis1.
The widespread use of RDTs has made it possible for malaria to be diagnosed extensively in
endemic countries, thus significantly improving the quality of case management and reducing
morbidity and mortality in the world.69,80
1.5. HISTIDINE-RICH PROTEIN 2
P. falciparum parasites produce the Plasmodium falciparum Histidine-Rich Protein 2 (PfHRP2),
which is water-soluble protein and is released into the bloodstream of infected humans.61,90 Other
Plasmodium parasites are not known to express PfHRP2. All known laboratory strains of P.
falciparum parasites express the PfHRP2 except strains DD2 and 7G8 which are known have a
deletion of the pfhrp2 gene.53,65 The protein is composed of varying number of amino acids ranging
220–300,70 of mostly histidine (34%), alanine (37%) and aspartic acid (10%) and weighs about
17
60–105 kDA.90 It is expressed continuously throughout the ring, trophozoite and schizont stages
of P. falciparum life cycle67 and can be synthesized as early as 2 hours post infection of hosts.91
PfHRP2 is localized in several cell compartments including the cytoplasm but can also be found concentrated in packets inside the host erythrocyte cytoplasm and on the surface of the infected erythrocyte membrane.61,67 Whole blood PfHRP2 concentrations are higher in severe malaria than
plasma PfHRP2 concentrations,92 which can reach concentrations of about 100 µg/ml,93 plasma
PfHRP2 levels are considerably higher in severe malaria than in uncomplicated malaria.92
Quantitative PfHRP2 has been identified as a metric of the total parasite biomass, as it
includes antigen release from the sequestered parasite biomass, which is not accurately discernible
on peripheral blood smear.94 Plasma PfHRP2 levels at presentation correlated with severity of
malaria illness in adults from East Asia94,95 and Africa96 thus plasma PfHRP2 was an independent predictor of mortality.94–96 However, a recent study in Papua New Guinean children found no association between plasma PfHRP2 and severity of malaria.97 Differences in age, pfhrp2 strain
variation, and/or intensity of transmission are known to influence the utility of plasma PfHRP2 in
predicting parasite biomass.96 Transmission is generally higher in Africa and PNG than in Asia.1,14
Persistent circulating plasma PfHRP2 from recent infection has been hypothesized to potentially
overestimate parasite biomass97 and blood PfHRP2 can persist up to four weeks after successful drug treatment.98
1.5.1. BIOLOGICAL FUNCTION OF PfHRP2
Although the exact function or functions of PfHRP2 remains to be established, several biological roles have been ascribed for this cytosolic protein.93,99–102 PfHRP2 has been implicated in the
polymerization of ferri-protoporphyrin IX (FePPIX) or free heme to form the inactive hemozoin
(β-hematin).91,99 During blood stage infection, PfHRP2 is secreted by the parasite into the host
18
erythrocyte cytoplasm where it ends up underneath the erythrocyte membrane.100 PfHRP2 and hemoglobin are then transported into the food vacuole by either of the 2 proposed mechanisms.99,100
Early studies suggest that PfHRP2 and hemoglobin may be transported into the food
vacuole as separate structures99 Later studies suggest that the neutral pH of the cytosol promotes the binding PfHRP2 to hemoglobin outside the food vacuole to form PfRHP2-hemoglobin (or
FePPIX-PfHRP2) complex before being taken into the food vacuole.100 The binding of PfHRP2 to
hemoglobin, inside or outside the food vacuole, undisputedly is known to occur through the
PfHRP2 repetitive amino acid sequence AHHAHHAAD to FePPIX of hemoglobin via a hexa-
coordination to form the FePPIX-complex.100
Degradation of hemoglobin takes place inside the food vacuole, and this process is initiated
by the conversion of oxyhemoglobin to methemoglobin, a reaction that produces free FePPIX and
100 a superoxide anion that dismutates to H2O2. (H2O2 which is a potentially harmful oxidant that
can cause damage to proteins and lipids in the presence of transition metals and reducing
substances.100 The toxicity of free heme, on the other hand, is due to its reducing properties).100
Within the food vacuole where conditions are acidic, PfHRP2 promotes the crystallization of free heme to form the granular pigment hemozoin (β-hematin).100 The detoxification process here,
therefore has been shown to be initiated and accelerated by PfHRP2 binding to free heme.100
Although the spectroscopic properties of thePfHRP2-FePPIX complex are well documented,99,100
its biochemical properties are not fully understood.
Absorbance spectroscopy analysis demonstrated that the formation of the heme-PfHRP2
complex is disrupted by chloroquine thus signifying chloroquine as an inhibitor of heme detoxification/binding to PfHRP2.103,104
19
PfHRP2 is also implicated in the inhibition of antithrombin during parasite infection.101 A
study in 2011101 showed that PfHRP2 binds tightly and selectively to coagulation-active
glycosaminoglycans (dermatan sulfate, heparan sulfate, and heparin) and inhibits antithrombin
(AT). This study showed that in purified systems, recombinant PfHRP2 neutralized the heparin-
catalyzed inhibition of factor Xa and thrombin by AT in a Zn2+-dependent manner.101 PfHRP2
attenuated the prolongation in plasma clotting time induced by heparin, suggesting that PfHRP2
inhibits AT activity by preventing its stimulation by heparin.101 In the microvasculature, where erythrocytes infected with P. falciparum are sequestered, high levels of released PfHRP2 may bind cellular glycosaminoglycans, prevent their interaction with AT, and thereby contribute to the procoagulant state associated with P. falciparum infection.101
PfHRP2 has also been shown to bind to actin in vitro in a pH-dependent manner quite
similar to the hisactophilin (an amoebic protein that induces actin polymerization), and transport
it from the cytoplasm to the nucleus in response to pH changes.102 PfHRP2 was also shown to bind
to phosphatidylinositol 4,5-bisphosphate (PIP2) and significantly changes its structure from coil-
to-helix in a pH-dependent manner, a feature described for several actin-binding proteins. These studies suggest a function of PfHRP2 as a “pH-sensor protein” with a possible role in cytoskeleton remodeling of infected erythrocytes.102
Another study in 2016 was able to provide evidence showing that PfHRP2 is a virulence
factor that triggers the inflammasome in vascular endothelial cells.93 This study by Pal et al,
showed that PfHRP2 binding to brain endothelial cells results in the rearrangement of tight
junction proteins which would result in the compromising of the blood-brain barrier (BBB).93 Thus
it was proposed here that PfHRP2 contributes to the pathogenesis of cerebral malaria.93
20
PfHRP2 is also found in several other cellular compartments and this may also suggest additional
functions of this protein.69,91,100
1.5.2. PfHRP2-BASED RDTS
Currently the principal application of detailed knowledge of the PfHRP2 protein is its role as the
target antigen for RDT monoclonal antibodies (as previously mentioned in 1.4.3) in Falciparum
malaria detection.61,62,69 Over the past 10 years, the PfHRP2 antigen and its gene have become the
focus of significant number of studies thus contributing to improvements in the sensitivity and
specificity of RDTs for malaria detection.69,89
1.5.2.1. PFHRP2-BASED RDTS IN MADAGASCAR
A quality-control and evaluation program was set up in 2008 between WHO and the Foundation
for Innovative New Diagnostics (WHO-FIND) to evaluate malaria RDT products. Since then 202 unique products have been tested in the program; 65 of them detect P. falciparum alone, 143 detect
and distinguish P. falciparum from non-P. falciparum (either pan-specific or species-specific for
P. vivax or P. vivax, ovale and malariae), and 10 detect P. falciparum and non-P. falciparum
without distinguishing between them.105 Currently, 12 malaria RDTs are WHO prequalified; seven
are intended to detect P. falciparum only, four detect and distinguish P. falciparum from non-P.
falciparum, and one detects all species but does not distinguish between them
(http://www.who.int/malaria/news/2016/rdt-procurement-criteria/en/). SD Bioline Malaria Ag
P.f/Pan RDT used in the present study is among the four WHO prequalified RDTs that can detect
and distinguish P. falciparum from non-P. falciparum malaria.
Rapid diagnostic tests for malaria in Madagascar were first introduced in 2003.106,107 A policy shift
towards their routine use began in 2007 and these now represent the first-line diagnostic for
malaria.4 A number of RDTs detecting P. falciparum-specific HRP2 (PfHRP2) have been tested
21
in Madagascar: MakroMED;106 the Malaria Hexagon dipstick;107 PALUTOP(+4);7 SD Bioline
Malaria Ag P.f/Pan;108 and OnSite and CareStart™.109 The study that assessed the performance of
SD Bioline Malaria Ag P.f/Pan RDT was conducted between August and October 2007 on 200
patients with suspected uncomplicated malaria, and compared the RDT results with those obtained
by microscopy and real-time polymerase chain reaction (PCR) combined.108 In that study, the
sensitivity and specificity of the RDT for detection of P. falciparum were 92.9% and 98.9%, respectively. The sensitivity decreased to 77.3% at parasitemia levels < 100 parasites/µL.
1.5.2.2. PFHRP2-BASED RDTS IN PAPUA NEW GUINEA
In a PNG study carried out between July 2010 and November 2013, the CareStart™ P.f/Pan combo
RDT (Access Bio, USA), was compared with light microscopy and qPCR in detecting Plasmodium infections in women who reported to the Modilon General Hospital, Madang, PNG.110 This study
showed the sensitivity of CareStart™ P.f/Pan combo RDT was lower than light microscopy (LM)
when both were compared to qPCR detection of malaria parasites.110 The study also found that the
RDT was not sufficiently sensitive (45% sensitivity) for use in intermittent screening amongst
asymptomatic (anemic) women.110 Overall, that study observed that RDT missed 54.4% of
peripheral P. falciparum infections in the study subjects. Another study, published in 2011, showed that plasma PfHRP-2 concentrations are not significantly higher in severe malaria cases than those
with uncomplicated infections at presentation, with individual values in a wide range from <.15 to
27,338 ng/mL.97
1.5.3. THE PFHRP2 GENE
The PfHRP2 is the gene product of pfhrp2 (MAL7P1.231), a single copy gene,111 located
subtelomerically on chromosome 8 (formerly chromosome 7) of the P. falciparum genome.75 (see
Figure 1.2). The pfhrp2 gene consists of an intron and 2 exons and is about 1063bp in length (based
22 on the 3D7 laboratory strain).111 This gene is flanked by seven microsatellites: four upstream and three downstream from of the pfhrp2 locus.75 The two genes immediately flanking pfhrp2 are:
PF3D7_0831900 (a pseudogene or Plasmodium exported protein of unknown function) that lies upstream, and PF3D7_0831700 (a putative heat shock protein 70 gene) that lies downstream.112
As a subtelomeric gene, the frequent chromosomal rearrangements constantly expose the pfhrp2 gene to partial or full deletions and high sequence polymorphism.113
A structural homologue of the pfhrp2 gene, PfHRP3 (PF3D7_1372200, not investigated in this study), is located subtelomerically on chromosome 13.66,112
Figure 1.1. Location of the pfhrp2 gene on chromosome 8 (position 1,374,236 to 1,375,299) flanked by seven microsatellites (15, 5.2, 2.5 1.4, -3.8, -9.5, -41). Each value indicating their distance in kb, upstream (+) and downstream (-) from the pfhrp2 locus
1.5.3.1. PFHRP2 GENE DELETION AND VARIATION
Extensive polymorphisms, in the form of differing peptide lengths, amino acid repeat types and their arrangements, in the exon-2 of the pfhrp2 gene have been reported52,60–67,78–80 but they seem not to affect RDT detection sensitivity at >200 parasites/µL.66 Many studies have also reported that P. falciparum parasites that lack the pfhrp2 gene.52,60–67 P. falciparum parasites lacking the
23
pfhrp2 gene were first reported in Peru,114 followed by subsequent reports in other parts of South
America,73,112,115 Central America,116 Asia68,117–119 and Africa71,120. Partial or full deletions of the
pfhrp2 gene results in the absence of the pfhrp2 antigen in P. falciparum parasites which when tested on pfhrp2-based RDTs show as negative, i.e. false negative results.71–76
1.5.4. BAKER AMINO ACID REPEATS AND FALCIPARUM RDT DETECTION
Baker et al, in 200565 and 2010,66 characterized the amino acid sequences of the PfHRP2 protein
into 24 types of amino acid repeats (see Table 1.1). Baker reported that 2 of these repeat types, 2
(AHHAHHAAD) and 7 (AHHAAD) occur with high prevalence and frequency amongst P.
falciparum parasites.65 (see Tables 1.1 and 4.5).
Table 1.1 Types of Baker Amino Acid Repeat Types in PfHRP2 as designated by Baker et al 2005
Code Repeat Sequences pfhrp2 PfHRP3 Code Repeat Sequences pfhrp2 PfHRP3 1 AHHAHHVAD + + 13 AHHASD - 2 AHHAHHAAD + + 14 AHHAHHATD + - 3 AHHAHHAAY + - 15 AHHAHHAAN - + 4 AHH + + 16 AHHAAN - + 5 AHHAHHASD + - 17 AHHDG - + 6 AHHATD + - 18 AHHDD - + 7 AHHAAD + + *19 AHHAA + - 8 AHHAAY + - *20 SHHDD + + 9 AAY + - *21 AHHAHHATY + - 10 AHHAAAHHATD + - *22 AHHAHHAGD + - 11 AHN + - *23 ARHAAD + - 12 AHHAAAHHEAATH + - *24 AHHTHHAAD + - * updated in Baker et al 2010
24
Baker et al, then proposed a regression model, as a function of the number of these 2 repeat
types, for predicting RDT sensitivity to P. falciparum infection. However, subsequent studies were
not able to confirm this correlation between Baker’s regression model with parasites from global studies at higher parasitaemia, which also led to Baker et al refuting this prediction model.66
Biochemical studies100 have shown that the amino acid repeat sequence AHHAHHAAD
(similar to the so-called Baker repeat type 2 and), which occurs about 33-45 times in the pfhrp2
protein,65 is largely responsible for the its function.100 Another study of pfhrp2 epitopes, reported
that epitopes with the highest prevalence, frequencies and binding affinity for antibodies in RDTs
have amino acid sequences similar to this particular amino acid repeat.69
25
CHAPTER 2: OBJECTIVE OF THE MASTERS THESIS
Although extensive studies have been carried out on the (partial and full) deletions and
polymorphism in the pfhrp2 gene amongst P. falciparum parasites in some malaria-endemic
countries, only three have reported on Madagascar65,66,72 and two on Papua New Guinea.65,66 It has
been estimated, in these two countries, 67% and 51% of malaria cases, respectively, are diagnosed using RDTs.7,14
The WHO emphasizes RDT diagnosis of malaria as necessary for malaria elimination in
resource-challenged endemic countries.1,27,89 With reports of increasing pfhrp2 gene deletions
emerging from endemic countries, cases of misdiagnosis (false negative results) are likely to
increase as well thus hindering elimination efforts.65,66,72
Furthermore, there is limited data on the effectiveness of RDTs in Madagascar and PNG.
Therefore, it is critically important that frequent surveys be conducted to monitor the effectiveness
RDT detection of malaria in Madagascar, PNG and other endemic countries. It is also equally
important that more studies be done on pfhrp2 gene polymorphism and deletion in these countries.
This masters’ research project thus aims to study the pfhrp2 gene and pfhrp2-based RDT use
in Madagascar and Papua New Guinea. The goals of this research project therefore are:
1. To determine the prevalence of Plasmodium and P. falciparum infections in Madagascar
and PNG
2. To investigate the polymorphism of the pfhrp2 gene amongst P. falciparum parasites in
Madagascar and PNG and, its effect on RDT sensitivity for P. falciparum detection
3. To detect, if any, deletions of the pfhrp2 gene amongst parasites in these two countries.
4. To determine the presence of PfRHP2 epitopes which are targets for monoclonal antibodies
used in RDTs in these two countries
26
CHAPTER 3: METHODS 3.1. ETHICS STATEMENT
The Madagascar part of the study was conducted following protocols approved by the University
Hospitals of Cleveland Institutional Review Board (#09-13-01), the Division of Microbiology and
Infectious Diseases/NIAID/NIH, the Madagascar Ministry of Health Ethics Committee (#099).
Approval for sampling in the PNG part of the study was obtained from the Papua New
Guinea Medical Research Advisory Committee, the Institutional Review Board for Human
Investigation at University Hospitals of Cleveland, and the International Centers for Tropical
Disease Research Network/NIAID/NIH.
Patients were enrolled at the sites following informed consent by local doctors qualified in
NIH Human Subjects Training. A parent or guardian provided written informed consent on behalf of child participants under the age of 18 years.
3.2. STUDY SITES AND SUBJECTS
This study is part of the ongoing malaria epidemiological (longitudinal) studies being conducted in Madagascar since 2013, (2013–2018).4,6 This analysis for this master research project was
conducted on samples collected between January 2014 and August 2015. The second part of this
master research analyzed samples collected from a series of cross-sectional studies in Papua New
Guinea from August 2001 to June 2003.12
3.2.1. SAMPLING IN MADAGASCAR
In Madagascar the study site covers the western highlands fringe region of Madagascar, in the
foothills between the central highlands and the western tropical coastal zone.4,6,121 This area is
endemic for both P. falciparum and P. vivax malaria, and shows distinct malaria seasonal trends that peak from December to May annually. The study was set up with local doctors at the 3 health
27
centers, all within the Ampasimpotsy area; North, South and Center. They are all in
Tsiroanomandidy district, and just Southeast of the town of Tsiroanomandidy (50-100 km).
Patients who reported to these health centers were screened for malaria using the SD
Bioline Malaria Ag P.f/Pan test kit (Standard Diagnostics, Inc., Republic of Korea) and light
microscopy by a qualified technician. All malaria infections were treated with a weight adjusted
course of artesunate-amadiaquine in accordance with the guidelines of the Madagascar Ministry
of Health guidelines 5 during the time of sample collection.
3.2.2. SAMPLING IN PAPUA NEW GUINEA
For the Papua New Guinean part of the study, the source of study samples were five villages, (from a total of 29 villages in an ongoing collaborative study12), within the Wosera-Gawi district of the
East Sepik Province.
The Wosera-Gawi district and its surrounding areas are known to have perennial transmissions of malaria. The entomologic inoculation rate is estimated at about 30
bites/person/year.12 The prevalence of malaria parasites in the district is about 60% with P.
falciparum as the predominant species (55%), followed by P. vivax (25%) and P. malariae
(20%).13 Irregular changes over time in malaria transmission was reported here but no clear-cut
seasonal patterns were reported for Wosera.13 The geographical distribution of these malariometric indices and immune responses was reported to be non-uniform within this study.13
Study subjects were screened for malaria standard light microscopy by a qualified technician. All malaria infections were treated with a weight adjusted course of CQ or
Amodiaquine in accordance with the guidelines of the Papua New Guinea National Department of
Health11 during the time of sample collection.
3.2.3. SAMPLE COLLECTION AND PROCESSING
28
In Madagascar, patient samples were collected using finger-prick blood spotted onto a Whatman
3MM filter paper. Two spots were made onto the same filter paper from each patient. In addition,
for the in vitro cultivation of patient isolates,122 a 7-10mL venous blood sample was drawn into a
K+-EDTA and/or Na+-heparin Vacutainer and stored at 4°C for 2-4 hours.
Cryopreservation of the P. falciparum- or P. vivax-infected blood samples followed the
method using Glycerolyte 57 solution as described by J. Normark 87 Cryopreserved samples in 2- mL tubes were shipped in a liquid nitrogen shipper from Madagascar to the United States over a
10-day period. The samples were carefully unpacked onto dry ice to minimize thawing during transfer to longer-term storage in liquid nitrogen freezer until cultivation.
In Papua New Guinea, 7-10mL venous blood samples were drawn into a K+-EDTA and/or
Na+-heparin Vacutainer and stored at 4°C for 2-4 hours. Protocols described above were followed for the safe storage and transport of samples from PNG to the United States over a 10-day period.
3.3. IN VITRO CULTIVATION OF P. FALCIPARUM PATIENT ISOLATES
In vitro culture of P. falciparum isolates was initiated for 5 different patient blood samples from
Madagascar. These were: patient sample Ex30704 (collected in EDTA); Ex2004 (collected in
EDTA); 2070803 (collected in EDTA); Ex2002 (collected in heparin); and 30205 (collected in
EDTA). These P. falciparum isolates were cultured in RPMI 1640 (CorningTM cellgroTM,
Manassas, VA), containing 25mM HEPES and 0.2% Sodium bicarbonate. This medium was
further supplemented with 200mM L-Glutamine, 200mM Hypoxanthine, 50mg/mL Gentamicin
sulfate, and 10% Albumax. This complete malaria culture medium (CMCM)123 was stored at 4°C.
The cryopreserved P. falciparum-infected blood samples were thawed using a modified decreasing NaCl concentration gradient (12%, 1.6% and 0.9%) method.124 After the final NaCl treatment, the blood sample pellet volume was measured (30–80µL) and re-suspended in 5mL of
29
CMCM in a 6-well tissue culture plate. Leukocyte-depleted blood from a local healthy donor was to the CMCM containing P. falciparum-infected patient blood pellet to achieve 4% hematocrit.
The tissue culture plate was kept in a Sterilite® box with lid, which was gassed with 5% CO2 +
5% O2 + 90% N2 mixture. Parasite cultures were maintained at 37°C in 5% CO2. The culture medium was changed daily using complete medium stored at 4°C.
3.4. PREPARATION OF DNA TEMPLATES
For the samples collected as blood spots on filter papers, dried blood spot protocol was used to extract genomic DNA using a QIAamp® 96 DNA Blood Kit (QIAGEN, Valencia, CA). Genomic
DNA Extraction was also extracted from venous blood samples using a QIAamp® 96 DNA Blood
Kit (QIAGEN, Valencia, CA). Additionally, DNA was extracted from 50–100µL of each P. falciparum in vitro culture using a QIAamp® DNA Micro Kit (QIAGEN, Valencia, CA).
3.5. MOLECULAR DIAGNOSIS OF PLASMODIUM SPECIES INFECTION
Polymerase chain reaction (PCR)-based Plasmodium species diagnosis employed a ligase detection reaction-fluorescent microsphere assay (LDR-FMA). All methods for PCR amplification of small sub-unit ribosomal RNA (18S rRNA) target sequences and Plasmodium species-specific detection by LDR-FMA have been described by McNamara et al.55 Genomic DNA extracted from
P. falciparum-, P. vivax-, P. malariae-, and P. ovale-infected samples, which were provided by the Malaria Research and Reference Reagent Resource Center (MR4; now merged with BEI
Resources) and Dr. W.E. Collins (Centers for Disease Control and Prevention), served as positive controls. Species-specific fluorescence data were collected using the Bio-Plex® Manager 3.0 software (Bio-Rad, Hercules, CA).
30
3.6. AMPLIFICATION AND DETECTION OF THE PFHRP2 GENE
The pfhrp2 gene was amplified using 3 sets of primers (Primer sets #1, #2 and #3). All three primer sets amplified different but overlapping regions of the pfhrp2 gene to allow for sequencing of the entire gene, as shown diagrammatically in Figure 3.1. Primer sets #1 and #3 were used to amplify
the gene regions from the cultured isolates. Primer sets #2 and #3 were used to amplify the gene
regions from blood samples collected onto filter papers. The primer sequences, expected PCR
product sizes, and amplification conditions are presented in the Appendix (Table A1). Genomic
DNA from the P. falciparum strains 3D7 and HB3 were used positive controls, whereas that from
Dd2 strain, which lacks pfhrp2 gene,53,65 was used as a negative control in these amplification
reactions.
Figure 3.1 Diagrammatic representation of the overlapping regions of the pfhrp2 gene amplified by using three different sets of primers. Nucleotide positions are based on the reference sequence GenBank accession U69551.1.
Amplicons generated with primer sets #1 and #3 for the culture isolates, and with primer set #2 for
the blood spot samples were purified using a QIAquick® PCR Purification Kit (QIAGEN,
Valencia, CA). Primer set #3 generated multiple bands for the blood samples. From this gel, the most relevant amplicons were cut and purified using a QIAquick® Gel Extraction Kit (QIAGEN,
Valencia, CA). The nucleotide sequences of the pfhrp2 gene in all purified amplicons were
determined Sanger sequencing, which was performed using a modified Applied Biosystems
BigDye® Terminator v3.1 Cycle sequencing kit protocol.
31
3.7. DNA SEQUENCE ANALYSIS OF THE PFHRP2 GENE
The CodonCode Aligner v.6.0.2 was used for alignment and base-calling of the raw sequences.
The Geneious v.10.0.2 was used for the alignment of sequences, virtual construction of the pfhrp2 gene, translation of the gene into protein sequences, grouping of specific amino acid repeats, identification of insertions/deletions, and for comparison with pfhrp2 sequences from previous studies.
For gene analysis of samples from Madagascar, the sequences generated in this study (n =
18) were compared with a total of 97 sequences from previous studies (GenBank accession#
U69551.1,125 EU589688.1–EU5899767.1,72 FJ871304.1–FJ871319.166). One of these sequences
contains exon-1 sequence, generated from ItG2 clone from a Brazilian patient.125 The remaining
96 sequences are exon-2 generated from Madagascar patients.66,72
For gene analysis in PNG, the sequences generated in this study (n = 18) were compared with a total of 15 sequences from previous studies.65,66 (GenBank accession# AY816241.1–
AY816243.1, AY816253.1– AY816258.165, FJ871161.1– FJ871163.1, FJ871241.1, FJ871294.1,
FJ871358.166) (Prior to this study, these 15 sequences were the only pfhrp2 gene sequences from
PNG that were available on GenBank).
The pfhrp2 gene sequences were translated into protein sequences and 24 amino acid repeat types (1-24) were classified as described by Baker et al, 2010.66 The predictive model, based on
the number of type 2 x type 7 repeats > 43, developed by Baker et al, 200565 was used to assess
whether an isolate would be detected, if present at a density of ≤250 parasites/µL, by an RDT
detecting pfhrp2.
Mariette et al in 200872 described a classification for Baker’s predictive model – the protein
sequences were classified into 4 groups as a function of the number of type 2 x type 7 repeats,
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group A (very sensitive, >100); group B (sensitive, 50–100); group C (“borderline”, 50–100); and
group D (non-sensitive, <43).
Finally, the sequences from this study (Madagascar, n = 18; PNG, n = 18) and previous
studies (Madagascar, n = 96; PNG, n = 15) were analyzed for the identification and distribution of
14 major epitopes, ranging 8–15 amino acids, that are recognized by 11HRP2-specific
commercially available monoclonal antibodies (MAbs).69
3.8. STATISTICAL ANALYSES
2 x 2 contingency table analyses were used for comparing RDT and molecular detection (PCRs and LDR-FMA) of Plasmodium ssp. and P. falciparum to pfhrp2 gene detection assays in
Madagascar (n = 260) (see Tables 4.1, 4.2, 4.3 and 4.4) and PNG (n = 169) (see Tables 4.9 and
4.10). Sensitivity measures the proportion of ‘true positives’, i.e. RDT and/or pfhrp2-positives that are also identified as Plasmodium spp. and/or P. falciparum-positives by molecular detection.
Specificity measures the proportion of ‘true negatives’, i.e. RDT and/or pfhrp2-negatives that are also identified as Plasmodium spp. and/or P. falciparum-negatives by molecular detection.
Microscopy data was considered in these analyses.
For gene sequence analysis, prevalence was used to describe the presence of a specific amino acid repeat type or epitope in the pfhrp2 gene (or pfhrp2 protein) sequences, from
Madagascar in this study (n = 18) and previous studies (n = 96) and, in PNG in this study (n = 18) and previous studies (n = 18). Frequency was used to describe the number of times a specific amino acid repeat type or epitope occurs within each sequence from this study and previous studies for both countries. Frequency data was presented as average frequency, calculated as [number of each amino acid repeat or epitope within all sequences/total number of all amino acid repeat types or epitopes within all sequences] x 100.
33
CHAPTER 4: RESULTS
PART 1. MADAGASCAR 4.1. DETECTION OF PLASMODIUM PARASITES IN MADAGASCAR
Results for the diagnosis of Plasmodium spp. infections by microscopy, RDT, 18S rRNA gene
PCR and LDR-FMA and, detection of the pfhrp2 gene from blood spot samples collected in
Ampasimpotsy, Madagascar are presented here (in Tables 4.1–4.4).
4.1.1. MOLECULAR DIAGNOSIS OF MALARIA PARASITES IN MADAGASCAR
Molecular diagnosis by 18S rRNA gene PCR and LDR-FMA determined that all of the 5 cultured
samples from Madagascar were positive only for P. falciparum infection.
PCR detection of 18S rRNA gene in the blood spot samples (n = 260) from Madagascar showed
that 29% (n = 75) were positive for Plasmodium spp. infection. LDR-FMA assays on the 18S rRNA PCR products distinguished that P. falciparum was present in 95% (71/75), P. vivax in 4%
(3/75) and P. ovale in 3% (2/75) of the infected samples.
4.1.2. PCR DETECTION OF THE PFHRP2 GENE IN MADAGASCAR
Table 4.1. pfhrp2 gene PCR vs 18S rRNA gene PCR detection Table 4.2. pfhrp2 gene PCR vs Pf (LDR-FMA) detection
18S+ 18S- Totals Pf+ Pf- Totals pfhrp2+ 68 5 73 pfhrp2+ 68 5 73 pfhrp2- 7 180 187 pfhrp2- 3 184 187 Totals 75 185 260 Totals 71 189 260
Using primer set #2 (described earlier), the PCR assay in Madagascar blood spots showed that 73
out of 260 samples were positive for the pfhrp2 gene. From these 73 pfhrp2 PCR-positive samples,
68 were positive for both Plasmodium spp. and P. falciparum infections, i.e. 96% (68/71) P.
34
falciparum-positive samples were positive for the pfhrp2 gene. Five pfhrp2 gene-positive samples
were negative for both Plasmodium spp. and P. falciparum infections.
180 out of 187 pfhrp2-negative samples were not infected by any Plasmodium spp. Seven pfhrp2- negative samples were positive for Plasmodium infections; 3 were P. falciparum positive; 3 were infected with P. vivax; and 2 had P. ovale infections. One of these samples had a (P. falciparum-
P. ovale) mixed infection.
Comparisons between pfhrp2 gene and Plasmodium spp. detection by 18S rRNA gene PCR
(shown in Table 4.1) and P. falciparum detection by LDR-FMA (shown in Table 4.2) for the blood
spot samples allowed us to estimate the distribution of pfhrp2 gene amongst P. falciparum in
Madagascar. The sensitivity and specificity of pfhrp2 gene detection against Plasmodium spp. infections (18S rRNA gene detection) were 91% and 97%, respectively. The sensitivity and specificity of the pfhrp2 gene detection against specific P. falciparum infections (LDR-FMA detection) were 96% and 97%.
4.1.3. RDT AND P. FALCIPARUM DETECTION IN MADAGASCAR
Rapid diagnostic test (RDT) kit analysis of all the 5 cultured isolates from Madagascar were all positive for P. falciparum infection. (see Figure A5 in the Appendix)
From the 260 study samples from Madagascar, RDT data was available for only 223 of these samples (see Table 4.3) 31% (70/223) were positive and about 69% (153/223) were negative by RDT diagnosis. 79% (55/70) of RDT positive samples had Plasmodium infections (i.e. true positives) and 94% (144/153) of RDT negative samples were negative for Plasmodium spp. infections (i.e. true negatives). The concordance of RDT and 18S rRNA PCR detection is 89%.
15 samples that were negative for Plasmodium spp. infections tested positive by RDT (i.e. false positives). Among these 15 samples, one had no microscopy data, six were microscopy
35
positive for P. falciparum, whereas 8 were microscopy negative (i.e. “true” false positives). 9
samples that were positive for Plasmodium spp. infections tested negative for RDT. (i.e. false
negatives). Among these 9 samples, one sample had no microscopic data, 6 were microscopy negative whereas 2 were microscopy positive for P. falciparum (i.e. “true” false negatives). The
one sample that had no microscopic data was positive for P. ovale infection by 18S rRNA gene
PCR.
Combining microscopy, RDT and 18S rRNA gene PCR diagnosis analyses (Table 4.3) and
considering the “true” false negatives and “true false positives, the sensitivity and specificity of
the RDT for the detection of Plasmodium spp. infections were 96% and 94%, respectively.
Table 4.3. RDT vs 18S rRNA gene PCR detection Table 4.4 RDT vs Pf (LDR-FMA) Malaria detection
18S+ 18S - Totals Pf+ Pf- Totals RDT+ 55 15 70 RDT+ 54 16 70
RDT- 9 144 153 RDT- 8 145 153 Totals 64 159 223 Totals 62 161 223
For RDT-positive samples (Tables 4.3 and 4.4), 98% (54/55) of Plasmodium spp.
infections were P. falciparum. 95% (145/153) of RDT-negative samples were also negative for P.
falciparum by LDR-FMA (i.e. true negatives). The concordance of RDT and 18S rRNA gene PCR
detection is 89%.
8 out of 62 P. falciparum infections (Table 4.4) were negative by RDT. These 8 samples
were also pfhrp2 gene PCR-positive. Among these 8 samples, 6 samples were microscopy
negative, whereas two samples were microscopy positive for P. falciparum, thus these two samples
were “true” false negatives (for RDT detection of P. falciparum by LDR-FMA).
36
This analysis also showed that 16 samples that were RDT positive were also P. falciparum
negative by molecular diagnosis. 15 of these were pfhrp2 gene negative. Among these 16 samples,
one did not have microscopy result, seven samples were microscopy positive for P. falciparum, whereas 10 samples were microscopy negative, thus these 10 samples were “true” false negatives
(for RDT detection of P. falciparum by LDR-FMA).
From 260 blood spot samples, microscopy data was available for 136 samples. Three out of 136 of these samples were P. vivax mono-infections. A comparison of RDT and microscopy data (n = 133) showed an overall concordance between these two diagnoses was 91%. The sensitivity and specificity of the RDT were 96% and 88%, respectively.
Combining all microscopy, RDT and LDR-FMA diagnoses analyses (Table 4.4), and considering the “true” false negatives and “true false positives, the sensitivity and specificity of the RDT for the detection of Plasmodium spp. infections were 95% and 94%, respectively.
4.2. PFHRP2 GENE IN MADAGASCAR
Amplification of the pfhrp2 gene from P. falciparum cultured isolates (n = 5) and field blood spots
(n = 260) from Madagascar, using primer sets #1, #2 and #3, are shown in Figures 4.1–4.3)
4.2.1. PFHRP2 GENE IN 5 CULTURED 5 P. FALCIPARUM ISOLATES
Genomic DNA from 5 P. falciparum cultured isolates from Madagascar were amplified using primer sets #1, #2 and #3. Amplicons generated with primer set #1 were visualized on 1.5% agarose gel as band sizes of 450-500bp. (Figure 4.1)
37
control
-
100bp ladder 100bp 1000 900 800 700 600 500 400 300 200 100
Figure 4.1 Agarose (1.5%) gel of pfhrp2 gene PCR using primer set #1 on P. falciparum culture isolates from Madagascar
control - 100bp ladder 1000 900 800 7006 00 500 400 300 200 100
Figure 4.2 Agarose (2.0%) gel of pfhrp2 gene PCR using primer set #2 on P. falciparum in samples from Madagascar
13 11 12 14 15 9 8 10 6 7 4 5 2 1 3 DD2 3D7 control
-
100bp ladder 1000 8009 00 6007 00 500 400 300 200 100
Figure 4.3 Agarose (1.0%)gel of pfhrp2 gene PCR using primer set #3 on P. falciparum culture isolates from Madagascar
38
Figure 4.4 Alignment of PfHRP2 exon-1 amino acid sequence of 5 P. falciparum culture isolates from Madagascar and reference sequence PFAHRPA1 (GenBank accession #U69551.1).125
Sequence analysis of these amplicons revealed that their actual sizes were: Ex30704,
442bp; Ex2004, 451bp; 2070803, 459bp; Ex2002, 450bp; and 3020205, 459bp. Exon-1 was found to be 69bp (23 amino acids) in length in all 5 isolates. The nucleotide sequence of the intronic region ranged 147–165 in length. Sequence analysis showed that nucleotide/amino acid sequence was identical in all five cultured parasites, and was identical to the exon-1 sequence, PFAHRPA1, used as reference (GenBank Accession# U69551.1).125 (see Figure 4.4).
Amplification by primer set #2 produced amplicons with sizes ranging from 220–250bp on
2.0% agarose gels. Sequence analysis shows that primer set #2 amplicons overlap with amplicons from primer sets #1 and #3. (see Figure 3.1). Primer set #2 amplicons, in fact, are redundant to primer set #1 amplicons and therefore were not sequenced for latter sequencing exercise, i.e. sequencing of field samples from Madagascar and PNG.
Amplification with primer set #3 showed band sizes of 850–900bp on 1% agarose gel.
Sequence analysis of these amplicons revealed that their actual sizes were: Ex30704, 859bp (286 amino acids); Ex2004, 844bp (281 amino acids); 2070803, 873bp (291 amino acids); Ex2002,
844bp (281 amino acids); and 3020205, 866bp (288). Each sequence was unique, i.e. no sequence was identical to another. Furthermore, all these 5 sequences were different from the 96 sequences
39
reported previously from Madagascar. Complete gene sequences, generated with primer sets #1
and #3, from this analysis were submitted to GenBank (accession # KX886207.1–KX8862011.1)
4.2.2. AMPLIFICAITON OF PFHRP2 GENE IN MADAGASCAR
From the samples collected during these epidemiological studies, 260 samples from Madagascar were randomly selected for amplification of the pfhrp2 gene with primer sets #2 and #3.
Amplification with primer set #2 involves a nested PCR (see the Appendix). From this assay 73 out of 260 samples from Madagascar produced expected nest 2 amplicons of 200–250bp on 2% agarose gel. These samples were described earlier (section 4.1.2.) as pfhrp2 gene positive.
PCR amplification using primer set #3 was met with some challenges. The amplification showed multiple bands on 1% agarose gels. This situation did not improve even after modifying
PCR reagents and/or amplification conditions. Using primers identical to primer set #3 in this study on Madagascar samples, Mariette et al. reported that the pfhrp2 fragment ranged in size from
435–927bp, predicting proteins of 145–309 amino acids. Following this observation, 2–4 bands per sample were cut and purified, ranging 400–1000bp, from 9/70 and 12/128 (positive with primer set #2) randomly selected samples from Madagascar, respectively, and sequenced the purified amplicons by Sanger dideoxy method previously. Because no sequence variation in exon-1 was observed among the 5 culture isolates, PCR amplification (primer set #1 PCR) and sequencing of exon-1 in these pfhrp2 gene positive samples from Madagascar (n = 73) was not carried out.
4.2.3. SEQUENCING OF PFHRP2 GENE IN MADAGASCAR
From 73 pfhrp2 positive samples from Madagascar, 9 pfhrp2 exon-2 amplicons were randomly selected and sequenced by Sanger dideoxy method in this study. From these 9 samples, a total of
13 exon-2 sequences, ranging from 528–877bp (175–291 amino acids) were generated. Although
40
all the 13 sequences were unique, they were found to have similar characteristics to those reported in a previous study in Madagascar. 72
A comparison among these 13 sequences revealed multiple-strain infections inferred by
the presence of two different sequences in four of the nine samples. This analysis also showed that
11 of the sequences were unique and, one sequence was present in two different samples. All of
these 12 sequences (11 unique + 1 common) were different from the 5 exon-2 sequences generated from the P. falciparum cultured isolates.
Finally, a comparison between these 12 sequences and 96 pfhrp2 exon-2 sequences from
the previous studies conducted in Madagascar65,66,72 showed that no sequences were shared
between these 2 studies, i.e., each sequence was unique. Exon-2 sequences from this 13 pfhrp2
sequences from Madagascar were submitted to GenBank (accession # MF554693–MF554705).
To summarize the results from sequence analysis of the pfhrp2 gene in P. falciparum from
Madagascar, no variation in exon-1 (n = 5, all identical sequences) was found and a large variation
in exon-2 (n = 18, with 16 unique sequences) in this study and in previous studies65,66,72 (n = 96,
all unique sequences).
4.2.4. DISTRIBUTION OF PFHRP2 AMINO ACID REPEATS IN MADAGASCAR
Translation of nucleotide (i.e. pfhrp2 exon-2) sequences into protein (pfhrp2) sequences enabled
classifying of into 24 amino acid repeat types (so-called Baker repeats).65 Of the 24 Baker repeat
types, 20 repeats (1–14, 19–24) are found in pfhrp2. Of these 20 pfhrp2 amino acid repeats, 12
repeats were identified in these sequences (n = 18). The same repeats were also present in previous
sequences (n = 96)65,66 from Madagascar. In addition, two repeats were present only in the previous
sequences. Consistent with differences in exon-2 sequence length, total number of Baker repeats
ranged 18–33 (mean = 27) in the current study and 14–37 (mean = 30) in previous studies.
41
12.0 11.0 10.0 9.0
8.0 This Study 7.0 Previous Studies 6.0 5.0 4.0 Average Frequencies 3.0 2.0 1.0 0.0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Amino Acid Repeat Type#
Figure 4.1 Average frequency of Baker amino acid repeat types in Madagascar PfHRP2 sequences from the current study (n = 18) and previous studies (n = 96).
However, it was also observed that almost all sequences started with repeat type 1
(AHHAHHVAD) and ended with type 12 repeat (AHHAAAHHEAATH). The other repeat types were dispersed throughout the protein sequence, except for repeat type 10 (AHHAAAHHATD) which mostly occurred near the terminal end before the end repeat, type 12.
The prevalence of each repeat type here and among previous sequences is presented in
Table 4.5. Repeat types 1, 2, 6, 7 and 12 were present in almost all sequences (94–100%). Repeat types 3, 5, 8 and 10 were also highly prevalent in all sequences (79–98%). Prevalence of repeat types 4, 13 and 19 were low to moderate in all samples (3–26%). The average frequencies of each amino acid repeat type in this study and previous studies are presented in Figure 4.4. Repeat types
2 and 7 were the most frequent in this study (mean 11, range = 4–14; mean 4, range = 0–7); and in previous studies (mean 12, range = 4–16; mean = 6, range = 2–13).
42
Table 4.5. Prevalence of Baker PfHRP2 amino acid repeat types amongst P. falciparum in Madagascar
Prevalence This Study Previous studies
Repeat type (n = 20) (n = 96) # Sequence % (n) % (n)
1 AHHAHHVAD 95 (19) 99 (95) 2 AHHAHHAAD 100 (20) 100 (96)
3 AHHAHHAAY 90 (18) 93 (89) 4 AHH 30 (17) 26 (25)
5 AHHAHHASD 85 (19) 80 (77) 6 AHHATD 95 (18) 100 (96)
7 AHHAAD 90 (18) 100 (96) 8 AHHAAY 90 (19) 98 (94)
9 AAY 5 (1) 0 (0) 10 AHHAAAHHATD 80 (16) 79 (76)
11 AHN 0 (0) 0 (0) 12 AHHAAAHHEAATH 100 (20) 100 (96)
13 AHHASD 15 (3) 7 (7) 14 AHHAHHATD 10 (2) 8 (8) 15 AHHAHHAAN 0 (0) 0 (0)
16 AHHAAN 0 (0) 0 (0) 17 AHHDG 0 (0) 0 (0) 18 AHHDD 0 (0) 0 (0) 19 AHHAA 15 (3) 3 (3)
20 SHHDD 0 (0) 0 (0) 21 AHHAHHATY 0 (0) 0 (0)
22 AHHAHHAGD 0 (0) 0 (0) 23 ARHAAD 0 (0) 1 (0)
24 AHHTHHAAD 0 (0) 0 (0) † Classified by Baker et al 2005, Baker et al 2010,
In addition to the Baker repeats, seven (A–G) non-Baker repeats were identified in these sequences and 19 (19 (E–W) in previous sequences with low prevalence (6–11% and 6–22%, respectively). (see Table 4.12). Two of these non-Baker repeats, type E (ADHAA) and type G
(AAD) were also found in sequences from previous studies.65 It is not possible that these repeat
43
types are not novel and have been found in pfhrp2 exon-2 sequences from other areas; repeat type
C (AHHAPD) has been found in pfhrp2 sequences from India.126
4.2.5. BAKER REPEAT TYPES AND RDT PERFORMANCE IN MADAGASCAR
The regression model developed by Baker et al, 2005 may be used to classify the predictive
sensitivity of P. falciparum parasites, to pfhrp2-based RDTs.65 A modified form of this
classification described by Mariette et al, 2008,72 is shown in Table 4.6. According to this
predictive model, 5 out of 18 (28%) PfHRP2 sequences (each representing a single P. falciparum
parasite) in this study and, 10 out of 96 (10%) from previous studies had a Baker score (type 2 x
type 7) < 43 and thus are likely to be non-sensitive to pfhrp2-based RDTs.
On the other hand, 72% (13/18) from this study and 86 (90%) from previous studies with
a 2 × type 7 score > 43 are likely to test as positive for P. falciparum by pfhrp2-based RDTs. A
comparison of Baker repeats type 2 and type 7 numbers and all three diagnostic analyses, namely
RDT, microscopy, and P. falciparum detection by LDR-FMA, for the 20 samples that were sequenced is shown in Table 4.7). (2 sequences were generated much later during the study from
2 “true false negative samples). Among the samples that were RDT positive, 12 had > 43 repeats, whereas five had < 43 repeats. Among the samples that were RDT negative, one sample had > 43 repeats, whereas two had < 43 repeats.
Table 4.6 Prediction of RDT detection sensitivity of P. falciparum in Madagascar
Group† Sensitivity Prevalence This study (n = 18) Previous studies (n = 96) % (n) % (n) A Very sensitive 0 (0) 10 (10) B Sensitive 33 (6) 68 (65) Borderline 39 (7) 11 (11) C Non-sensitive 28 (5) 10 (10)
† Classified by Mariette et al. (2008)
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Table 4.7 Baker Repeat Types and Malaria Diagnosis in Madagascar
Sample Repeat Type score (2 x 7) RDT Microscopy LDR-FMA Ex2002 a 48 (12 x 4) + + + Ex2004 a 55 (11 x 5) + + + Ex30704a 55 (11 x 5) + + + 2070803a 44 (11 x 4) + + + 3020205a 48 (12 x 4) + + + 1021506b 10 (10 x 1) + + + Ext2246A b 0 (12 x 0) + + + Ext2246Bb 20 (4 x 5) + + + Ext2263b 28 (7 x 4) + + + Ext30507Ab 44 (11 x 4) + + + Ext30507Bb 44 (11 x 4) + + + Ext30508b 91 (13 x 7) + + + Ext2229Ab 70 (14 x 5) + + + Ext2229Bb 78 (13 x 6) + + + Ext2223Ab 44 (11 x 4) + + + Ext2223Bb 50 (10 x 5) + + + 2100306b 78 (13 x 6) - - - Ext2230b 28 (7 x 4) + + + 3091101c 0 (14 x 0) - + + 2011303c 32 (8 x 4) - + + a GenBank accession# KX8862207.1 - KX8862011.1 b GenBank accession# MF554693.1 - MF554705.1 c "true" false negatives (Table 4.2)
4.2.6. DISTRIBUTION OF PFHRP2 EPITOPES IN MADAGASCAR
Epitope identification and analysis on all sequences revealed that eight of the 13 major epitopes were present in almost all of the sequences from this study (94–100%) and in previous studies (94–
100%) as shown in Table 4.8. Among these, 3 major epitopes, AHHAADAHHA, DAHHAHHA and AHHAADAHH, were present within those sequences at much higher average frequencies
(10–15) than the other 5 major epitopes (1 – 4). (see Figure 4.6) These 3 major epitopes have been shown to be recognized by 3A4 and PTL-3 (DAHHAHHA), C1-13 (AHHAADAHHA) and S2-5 and C2-3 (AHHAADAHH) MAbs.69
45
Table 4.8. Prevalence of PfHRP2 major epitopes amongst P. falciparum in Madagascar
Prevalence Epitope Current Study Previous Study MAb† (%) (n = 18) (%) (n = 96) DAHHAHHA 100 (18) 100 (96) 3A4 / PTL-3 DAHHAADAHH 94 (17) 100 (96) 2G12-1C12 DAHHVADAHH 11 (2) 0 (0) 2G12-1C12 YAHHAHHA 100 (18) 100 (96) 1E1-49, PTL-3 DAHHAHHV 94 (17) 98 (94) 1E1-49 HATDAHHAAD 67 (12) 83 (80) A6-4 HATDAHHAAA 78 (14) 88 (84) A6-4 AHHAADAHHA 100 (18) 100 (96) C1-13 DAHHAADAHHA 94 (17) 100 (96) N7 AHHAADAHH 100 (18) 100 (96) S2-5, C2-3 AHHASDAHH 94 (17) 79 (76) S2-5 TDAHHAADAHHAADA 67 (12) 76 (73) TC-10 AAYAHHAHHAAY 0 (0) 0 (0) Genway †Lee et al, 2012
30
25
20
Current Study 15 Previous Studies
10 Average Frequency Average
5
0
Major Epitope in PfHRP2
Figure 4.6. Average frequencies of 13 major epitopes (RDT MAbs targets) found in Madagascar PfHRP2 sequences.
46
PART 2. PAPUA NEW GUINEA 4.3. DETECTION OF PLASMODIUM INFECTIONS IN PAPUA NEW GUINEA
In this part of the results, the diagnosis of Plasmodium spp. infections by microscopy, 18S rRNA
PCR and LDR-FMA and, the diagnosis of the pfhrp2 gene in Wosera, East Sepik, PNG, are presented here. RDT diagnosis of malaria were not carried out for samples from PNG at the time of sample collection.12
4.3.1. MOLECULAR DIAGNOSIS OF PLASMODIUM IN PAPUA NEW GUINEA
PCR detection of the 18S rRNA gene in venous blood samples (n = 169) from PNG showed that
81% (137) were positive for a Plasmodium spp. infection as detected by 18S rRNA gene PCR.
The LDR-FMA assay on the 18S rRNA gene PCR products showed that 91% (125/137) of the infected samples were P. falciparum. 32% (44/137) were P. vivax infections, 23% (31/137) had P. malariae and 2% (3/137) were P. ovale. In these infected samples, about 37% (51/137) had mixed infections i.e. infection with two or more Plasmodium parasites. 50 out of 51 of these mixed infections were of P. falciparum and at least one Plasmodium parasite.
4.3.2. DETECTION OF THE PFHRP2 GENE IN PNG
Table 4.9. pfhrp2 gene vs 18S rRNA gene detection Table 4.10. pfhrp2 gene vs Pf (LDR-FMA) Malaria detection
18S+ 18S- Totals Pf + Pf - Totals pfhrp2+ 112 8 120 pfhrp2+ 109 11 120 pfhrp2- 25 24 49 pfhrp2- 16 33 49 Totals 137 32 169 Totals 125 44 169
PCR detection of the pfhrp2 gene in PNG samples showed that 120 out of 169 samples were positive for the gene. 112 of the pfhrp2 gene positive samples were also positive for Plasmodium spp. infections. 25 Plasmodium infections were negative for the pfhrp2 gene while 8 samples that were negative for Plasmodium infections were positive for the pfhrp2 gene by PCR.
47
97% (109/112) of the Plasmodium infected samples were from P. falciparum. 12%
(16/125) of the P. falciparum infections did not amplify the pfhrp2 gene, i.e. false negatives.
Among these 16 samples, 14 were microscopy negative whereas two samples were positive, i.e.
“true” false negative. (The parasitemia in these samples were 840 parasites/µL and 40
parasites/µL).
11 samples that were positive for the pfhrp2 gene by PCR were negative for the P.
falciparum infection by LDR-FMA, i.e. false positives. Two out of 11 had P. vivax infections and
one was infected with P. malariae. 10 out of 11 of these samples were also negative for P.
falciparum by microscopy. One of these samples was positive by microscopy with a parasitemia
of 1120 parasites/µL.
Comparing all diagnostic assays in PNG and considering the fact that pfhrp2 gene is
expressed exclusively by P. falciparum,61,90 the specificity and sensitivity of pfhrp2 gene detection
amongst P. falciparum parasites in PNG are 98% and 81%, respectively.
RDT diagnosis of malaria for these samples was not available for these samples from PNG.
4.4. PFHRP2 GENE ANALYSIS IN PAPUA NEW GUINEA
PCR amplification of the pfhrp2 gene, using primer set #2 and #3, on 169 randomly selected samples from PNG, showed that 120 amplified the pfhrp2 fragments in both primers, i.e. primer set #2 positive samples were also primer set #3 positive.
4.4.1. PFHRP2 GENE AMPLIFICAITON AND SEQUENCING IN PNG
PCR amplification of the pfhrp2 gene, using primer set #2 and #3, on 169 randomly selected samples from PNG, showed that 120 amplified the pfhrp2 fragments in both primers, i.e. primer
48
set #2 positive samples were also primer set #3 positive and primer set #2 negative samples were
also negative for primer set #3.
PCR amplification using primer set #3 (of pfhrp2 exon-2), however, was also met with
similar challenges such as those observed in the Madagascar blood sport samples, i.e. multiple
bands were seen on 1% agarose gels. This problem was solved as described earlier: bands in the
within the range 435–927bp of were cut, extracted from the gel, cleaned and sequenced by Sanger
dideoxy method.
PCR amplification and sequencing of exon-1 (primer set#1) in these pfhrp2 positive
samples from PNG (n = 120) was not carried out since it was then evident that the pfhrp2 exon-1
from P. falciparum parasite cultures were identical in sequence.
4.4.2. SEQUENCING OF PFHRP2 GENE PNG
From the 120 samples that were positive for pfhrp2, 12 samples were randomly selected for
sequencing by Sanger dideoxy method. From these 12 samples, a total of 18 exon-2 sequences, ranging from 528–877bp (175–291 amino acids) were generated. These sequences have been submitted to GenBank (accession #: MF673786–MF673803). The analysis of these 18 sequences revealed mixed infections, inferred by the presence of 2 different sequences in 6 of the samples 12 samples from PNG.
A comparison among these 18 sequences showed that all (n = 18) were unique, i.e. no 2 sequences were identical. These sequences were found to be similar types of Baker repeats as those reported from previous sequences in PNG.66 Also comparing these 18 sequences with 15 pfhrp2
exon-2 sequences from previous studies conducted in various locations around PNG65,66 showed
that no sequences were shared between all the sequences, i.e. each sequence was unique. Exon-2
49 sequences from this 13 pfhrp2 sequences from Madagascar were submitted to GenBank (accession
# MF554693–MF554705).
To summarize the results from sequence analysis of the pfhrp2 gene in P. falciparum from
PNG and a large variation in exon-2 (n = 18) was also observed in this PNG study and in previous sequences from PNG65,66 (n = 15).
4.4.3 DISTRIBUTION OF PFHRP2 AMINO ACID REPEATS IN PNG
The pfhrp2 exon-2 sequences from PNG were translated into protein (pfhrp2) sequences using
Geneious v.10.0.2 in order to identify 1`Baker65 amino acid repeats and study their distribution in
PNG. Amongst the pfhrp2 exon-2 sequences in P. falciparum parasites from PNG, 13 Baker amino acid repeats types (1, 2, 3, 4, 5, 6, 7, 19, 12, 13, 14, and 19) were identified in this study (n = 18) as well as from previous studies65,66 (n = 15). Similar patterns of differences as those observed in the Madagascar pfhrp2 exon-2 sequences were observed in PNG sequences in the lengths, types and total number of Baker repeats. These amino acid repeats in PNG sequences ranged 15–33
(mean = 25) in the current study and 24–39 (mean = 31) in previous studies.
It was also observed here that almost all sequences started with repeat type 1
(AHHAHHVAD) and ended with type 12 repeat (AHHAAAHHEAATH). An observation similar to that seen in Malagasy sequences was that other repeat types were dispersed throughout the protein sequence, except for repeat type 10 (AHHAAAHHATD) which mostly occurred near the terminal end before the end repeat, type 12. It was also noted that some PNG sequences from this study (6/18) lacked the amino acid repeat type 10.
The prevalence of each repeat type here and among previous sequences is presented in
Table 4.11. Repeat types 1, 2, 3, 6, 7 and 12 were present in almost all sequences in this study (93–
100%) and previous studies. (94–100%). Repeat types 5, 8 and 10 were also highly prevalent in
50 all sequences. The range was lower in this study (72–78%) than in previous studies (93%).
Prevalence of repeat types 4, 13 and 19 were low to moderate in all samples in this study (22–
39%) and in previous studies (13–33%).
Table 4.11. Prevalence of PfHRP2 amino acid repeat types amongst P. falciparum in Papua New Guinea
This Study Previous studies Repeat type (n = 18) (n = 15) # Sequence % (n) % (n) 1 AHHAHHVAD 94 (17) 100 (15) 2 AHHAHHAAD 100 (18) 100 (15) 3 AHHAHHAAY 89 (16) 100 (15) 4 AHH 17 (3) 33 (5) 5 AHHAHHASD 78 (14) 93 (14) 6 AHHATD 89 (16) 100 (15) 7 AHHAAD 94 (17) 100 (15) 8 AHHAAY 83 (15) 93 (14) 9 AAY 6 (1) 0 (0) 10 AHHAAAHHATD 56 (10) 93 (14) 11 AHN 0 (0) 0 (0) 12 AHHAAAHHEAATH 100 (18) 100 (15) 13 AHHASD 17 (3) 13 (2) 14 AHHAHHATD 0 (0) 0 (0) 15 AHHAHHAAN 0 (0) 0 (0) 16 AHHAAN 0 (0) 0 (0) 17 AHHDG 0 (0) 0 (0) 18 AHHDD 0 (0) 0 (0) 19 AHHAA 22 (4) 13 (2) 20 SHHDD 0 (0) 0 (0) 21 AHHAHHATY 0 (0) 0 (0) 22 AHHAHHAGD 0 (0) 0 (0) 23 ARHAAD 0 (0) 0 (0) 24 AHHTHHAAD 0 (0) 0 (0)
It was also observed that almost all of the pfhrp2 exon 2 sequences contain the amino acid sequence
‘HETQAHVDD’ which precedes Baker repeat type 1. The significant variations observed in the
51
length of pfhrp2 exon 2 are due to the differing numbers of 27-, 18- and 9bp repeats (9-, 6- and 3-
amino acid repeats). All sequences observed were unique to each other and to those from previous
studies.65,66 This was also observed in Madagascar sequences and in the current and previous
studies.65,66,72 The average frequencies of each amino repeat type in this PNG study and previous
studies are presented in Figure 4.6. Repeat types 2 and 7 were the most frequent in this study (mean
11, range = 4–14; mean 4, range = 0–7, respectively) and in previous studies (mean 4, range = 4–
16; mean 6, range = 2–13, respectively). This is followed moderately by repeat types 1 and 6 also in this study (mean 2, range = 0–4; mean 3, range = 0–5, respectively) and in previous studies
(mean 2, range = 1–4; mean 4, range = 2–7, respectively). Repeat types 3, 5, 8 and 10 have lower frequencies in this study (mean 1, range = 1–2; mean 1, range = 0–3; mean 1, range = 0–2; mean
2, range = 0–3, respectively) and in previous studies (mean 1, range = 0–3; mean 1, range = 0–1; mean 1, range = 0–2; mean 1, range = 0–3, respectively).
12.0 11.0 10.0 9.0 8.0 7.0 6.0 This Study 5.0 Previous Studies 4.0 Average frequencies 3.0 2.0 1.0 0.0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Amino Acid Repeat Type#
Figure 4.2 Average frequency of Baker amino acid repeat types in PNG sequences from the current study (n = 18) and previous studies (n = 15.)65,66
52
In the pfhrp2 sequences from PNG, four (C, N, Y and Z) non-Baker repeats were identified in this study and two (A and X) from previous studies. Three of these sequences (A, C and N), although not novel, were also found in the Malagasy sequences. All non-Baker repeats from the current study are show in Table 4.12.
Table 4.12 Prevalence of “Non-Baker” amino acid repeat types in Madagascar and Papua New Guinea
. Madagascar Papua New Guinea "Non-Baker" Current Previous Current study Previous studies repeats study studies # Sequence % (n=20) % (n=96) % (n=18) % (n=15) A AHHADY 6 (1) 0 (0) 0 (0) 7 (1) B AHHVAD 11 (2) 0 (0) 0 (0) 0 (0) C AHHAPD 6 (1) 0 (0) 22 (4) 0 (0) D AHHADD 11 (2) 0 (0) 0 (0) 0 (0) E ADHAA 6 (1) 17 (3) 0 (0) 0 (0) F AHHVHH 11 (2) 0 (0) 0 (0) 0 (0) G AAD 6 (1) 6 (1) 0 (0) 0 (0) H HATD 0 (0) 11 (2) 0 (0) 0 (0) I AHHAAH 0 (0) 11 (2) 0 (0) 0 (0) J ADA 0 (0) 11 (2) 0 (0) 0 (0) K SHH 0 (0) 22 (4) 0 (0) 0 (0) L AHHASH 0 (0) 6 (1) 0 (0) 0 (0) M AHHTH 0 (0) 6 (1) 0 (0) 0 (0) N AHD 0 (0) 11 (2) 6 (1) 0 (0) O AAAD 0 (0) 6 (1) 0 (0) 0 (0) P ATD 0 (0) 6 (1) 0 (0) 0 (0) Q AHHAT 0 (0) 6 (1) 0 (0) 0 (0) R AHATD 0 (0) 11 (2) 0 (0) 0 (0) S AHDAND 0 (0) 6 (1) 0 (0) 0 (0) T AHHAY 0 (0) 6 (1) 0 (0) 0 (0) U HAAD 0 (0) 6 (1) 0 (0) 0 (0) V AHYAA 0 (0) 6 (1) 0 (0) 0 (0) W AHHTAD 0 (0) 6 (1) 0 (0) 0 (0) X AHHETD 0 (0) 0 (0) 0 (0) 7 (1) Y AHHATY 0 (0) 0 (0) 6 (1) 0 (0) Z AHHAVD 0 (0) 0 (0) 6 (1) 0 (0)
53
4.4.4. BAKER REPEAT TYPES AND RDT IN PNG
Using Baker’s regression model65 and the Mariette’s classification,72 the predicted sensitivity of
P. falciparum from PNG to pfhrp2-based RDTs were estimated as shown in Table 4.13. Based on this predictive model, 11 out of 18 PfHRP2 sequences (each representing a single P. falciparum parasite) in this study and, three out of 15 in previous studies had a Baker type 2 x type 7 < 43 thus are likely to be non-sensitive to pfhrp2-based RDTs. On the other hand, seven from this study and
11 from previous studies with a 2 × type 7 score > 43 are likely to test as positive for P. falciparum by pfhrp2-based RDTs.
Table 4.13 Prediction of RDT detection sensitivity of P. falciparum in Papua New Guinea
Group† Sensitivity Prevalence This study (n = 18) Previous studies (n = 15) % (n) % (n) A Very sensitive 6 (1) 7 (1) B Sensitive 28 (5) 66 (10) Borderline 6 (1) 7 (1) C Non-sensitive 61 (11) 20 (3)
†Classified by Mariette et al. (2008)
A comparison of Baker repeats type 2 × type 7 numbers and diagnostic analyses, namely microscopy and P. falciparum detection by LDR-FMA, for the 18 sequences that were generated from PNG samples is shown in Table 4.14. All 18 sequences were from LDR-FMA-positive samples with 10 that are microscopy-positive. Amongst the microscopy-positive, four had > 43 repeats, whereas six had < 43 repeats. Amongst the eight microscopy-negative sequences, three had > 43 whereas five had > 43 repeats.
54
Table 4.14 Baker Repeat Types and Malaria Diagnosis in Papua New Guinea
Sample Repeat Type score (2 x 7) RDT Microscopy LDR-FMA DFA4927a 32 (16 x 2) not done + + DFA4929a 80 (10 x 8) not done - + DFA4934a 77 (11 x 7) not done + + DFA4938a 22 (11 x 2) not done - + DFA4940Aa 66 (11 x 6) not done - + DFA4940Ba 42 (6 x 7) not done - + DFA4942a 55 (11 x 5) not done - + DFA5008Aa 108 (12 x 9) not done + + DFA5008Ba 60 (12 x 5) not done + + DFB0007Aa 24 (8 x 3) not done - + DFB0007Ba 21 (7 x 3) not done - + DFB0013Aa 39 (13 x 3) not done + + DFB0013Ba 11 (11 x 1) not done + + DFB0014Aa 22 (11 x 2) not done + + DFB0014Ba 16 (4 x 4) not done + + DFB0031Aa 0 (7 x 0) not done + + DFB0031Ba 48 (8 x 6) not done + + DFB0051a 30 (15 x 2) not done - +
a GenBank accession# MF673786–MF673803
4.4.5. DISTRIBUTION OF PFHRP2 EPITOPES IN PAPUA NEW GUINEA
Epitope identification and analysis on all sequences revealed that eight of the 13 major epitopes were present in almost all of the sequences from this study (94–100%) and in previous studies (94–
100%) (see Table 4.15). Among these, 3 major epitopes, AHHAADAHHA, DAHHAHHA and
AHHAADAHH, were present within those sequences at much higher average frequencies (10–15) than the other 5 major epitopes (1 – 4) (see Figure 4.8). These 3 major epitopes, similarly to
Malagasy sequences, have been shown to be recognized by these MAbs: 3A4 and PTL-3
(DAHHAHHA); C1-13 (AHHAADAHHA) and; S2-5 and C2-3 (AHHAADAHH).69
55
Table 4.15. Prevalence of PfHRP2 major epitopes amongst P. falciparum in Papua New Guinea
Prevalence Epitope Current Study Previous Study MAb† (%) (n = 18) (%) (n = 15) DAHHAHHA 100 (18) 100 (15) 3A4 / PTL-3 DAHHAADAHH 94 (17) 100 (15) 2G12-1C12 DAHHVADAHH 0 (0) 0 (0) 2G12-1C12 YAHHAHHA 94 (17) 100 (15) 1E1-49, PTL-3 DAHHAHHV 89 (16) 100 (15) 1E1-49 HATDAHHAAD 61 (11) 83 (11) A6-4 HATDAHHAAA 67 (12) 88 (12) A6-4 AHHAADAHHA 100 (18) 100 (15) C1-13 DAHHAADAHHA 94 (17) 100 (15) N7 AHHAADAHH 100 (18) 100 (15) S2-5, C2-3 AHHASDAHH 78 (14) 100 (15) S2-5 TDAHHAADAHHAADA 50 (9) 53 (8) TC-10 AAYAHHAHHAAY 0 (0) 0 (0) Genway †Lee et al, 2012
30
25
20 Current Study
Previous Studies 15
10 Average Frequency Average
5
0
Major Epitope in PfHRP2
Figure 4.8. Average frequencies of 13 major epitopes (RDT MAbs targets) in Papua New Guinea PfHRP2 sequences.
56
CHAPTER 5: DISCUSSIONS
The ability to accurately diagnose Plasmodium infections is critical to malaria control and
elimination in endemic countries.51,52 The introduction of RDTs in the 2000’s has added a new dimensions to the diagnosis of malaria – RDT detection of malaria has become a routine practice
in a significant number of laboratories in the world.1 Apart from malaria case management in endemic countries RDTs are now vital tools in malaria surveillance and case investigations in non- endemic countries as well.1,51,52
The effect of pfhrp2 gene sequence variation on RDT diagnosis of malaria in low
parasitemia was first suggested by Baker in 2005.65 Subsequent studies conducted globally on
more diverse and larger sample sizes, however, were not able to establish a link between sequence
variation and RDT sensitivity.66 On the other hand, parasites that lack pfhrp2 expression due to
deletion (or partial deletion) of the pfhrp2 gene are now known to be non-detectable by pfhrp2- based RDTs and therefore directly affect malaria control and elimination efforts in endemic countries.71,72-75 The WHO therefore recommends the use of RDTs other than “PfHRP2-detecting
only” RDTs for endemic areas where a high pfhrp2 gene deletion may be suspected.
(http://www.who.int/malaria/news/2016/rdt-procurement-criteria/en/).
5.1. MADAGASCAR
Based on the amplification of both exon-1 and exon-2 of the pfhr2 gene, together with the use of
SD Bioline Malaria Ag P. f/Pan RDT and molecular diagnosis of P. falciparum infection, no
indication of a pfhrp2 gene deletion was found in the study samples from central Madagascar. This
result is consistent with those previous studies conducted 7–8 years ago in Madagascar,66,72 one of
which was conducted country-wide.72
57
Given that pfhrp2 deletion has been reported from the continent of Africa with the past five
years,71,120,127 resulting from the strong selective pressure on the P. falciparum population, no
indication of deletion in the current study samples is encouraging. However, the observation that
eight out of 223 (3.6%) samples were RDT-negative but P. falciparum-positive (false negatives),
two of which were microscopy-positive, warrants continued monitoring.
The detection limit of the SD Bioline Malaria Ag P.f/Pan RDT, used in this present study
is 50 parasites/µL for malaria antigen pfhrp2 and 100 parasites/µL for malaria antigen pLDH
(manufacturer’s note). Among 223 study samples in this study for which an RDT result was available, one sample had P. falciparum at 30 parasites/µL (an expect microscopist can detect 5–
10 parasites/µL).27 This sample was found to be RDT positive but pfhrp2- and Plasmodium spp
PCR- negative.
Comparison of RDT and P. falciparum LDR-FMA results (n = 223) showed that RDT
sensitivity was 87%. Among the eight RDT-negative P. falciparum-positive samples, all of which were pfhrp2 gene-positive, six were microscopy-negative, indicating sub-microscopic infections.
Ironically, two samples that had 4,830 and 6,310 P. falciparum parasites/µL were also RDT negative (“true” false negatives).
Although anti-pfhrp2 antibody levels in plasma were not measured in the present study, reduced sensitivity of PfHRP2-detecting RDTs has been seen among people with high anti-
PfHRP2 antibody levels.80 The RDT specificity was 90%. Among 16 RDT-positive but LDR-
FMA-negative samples, 15 were pfhrp2 gene-negative, seven were microscopy-positive, whereas eight were microscopy-negative (“true” false negatives). Regarding the seven microscopy positive samples, one possibility that was not explored in this study is that in the absence of pfhrp2, the
RDT positivity could be due to PfHRP3 detection114 (see Limitations).
58
Regarding the eight microscopy negative (“true” false positives) samples, a reason for their
RDT positivity could be the persistence of pfhrp2 antigenemia after anti-malarial therapy,98 which needs to be further examined. Regardless of the reasons, the sensitivity and specificity results of this study, when compared with those of the previous study,108 substantiate the need to continually
monitor the performance of the SD Bioline Malria Ag. P.f/Pan RDT in Madagascar.
In the present study, 89% of pfhrp2 exon-2 sequences were found to be unique. This
observation is in agreement with previous observations from Madagascar: in a country-wide
assessment of polymorphism in exon-2, 96% unique sequences were identified.72 In a global
analysis of exon-2 sequence variation, 100% variability was observed in Madagascar samples.66
In this global analysis, the pfhrp2 sequence diversity was higher in countries with high
transmission intensity such as in continental Africa (87–100%).66 A strong correlation between
malaria transmission intensity and pfhrp2 diversity may be expected, as malaria infections in high
transmission settings, including those in Madagascar, often involve multiple-strain infections.128
In the current study, two different exon-2 sequences were present in four of the nine blood spot
samples, implying multiple-strain infections.
On the other hand, all five pfhrp2 exon-1 sequences were identical. They were identical to
the exon-1 sequence from a Brazilian isolate,125 and those from 29 isolates from French Guiana.129
This low-level variation in exon-1 may be due to the fact that exon-1 codes for a signal peptide.130
The signal sequences of several processed and translocated P. falciparum proteins are known, and there is evidence that these parts of the protein are less variable among different strains.131
Although comparative analysis of the exon-2 sequences showed that no two sequences were the same between the current study (n = 18) and previous studies (n = 96), the prevalence
(Table 4.5) and frequency (Figure 4.5) of each of the 12 Baker repeat types, common between
59
these two groups, were comparable. This was also true for the repeat types 2 and 7, which were
used in a predictive model to assess whether an isolate would be detected, if present at a density
of ≤ 250 parasites/μL, by an RDT detecting pfhrp2.65,72 Previously, this analysis predicted that 9%
(range 6–14%) of Malagasy isolates with parasite densities ≤ 250 parasites/μL would not be
detected.72 In the present study, using the SD Bioline Malaria Ag P.f/Pan test kit, it was found that
correlation between the predictive model and the performance of this RDT was unclear.
17 different exon-2 sequences from this study were generated from 18 samples that were
positive by all three diagnostic analyses (RDT, P. falciparum LDR-FMA, and microscopy) (Table
4.7). Among these 17 sequences, 5 sequences were identified where the number of type 2 × type
7 repeats were < 43, ranging from 0 (12 × 0, respectively) to 28 (7 × 4, respectively). The parasitemia in these samples ranged 400–15,450/μL.
On the other hand, one sequence was generated from a sample that was negative by all three diagnostic analyses; a very low-level parasitemia and variation in amplification between two different PCRs may explain this result. In this sequence the number, of type 2 × type 7 repeats,
was 78 (13 × 6, respectively). In addition, when the two “true” false negative samples were sequenced, that had 4,830 and 6,310 P. falciparum parasites/µL, the number of type 2 × type 7 repeats were 0 (14 × 0, respectively) and 32 (8 × 4, respectively), respectively. These results generally agree with those reported by Baker et al. in a later study,66 which did not find a
correlation between pfhrp2 structure and the overall RDT detection rates.
Although limited, these results also suggest that the diversity of pfhrp2 may not be a
primary factor influencing the performance of SD Bioline Malaria Ag P.f/Pan RDT in Madagascar.
This is also supported by the finding that there was no correlation between pfhrp2 sequence length
or repeat type and pfhrp2 plasma concentration in African children.132
60
Studies that have evaluated the effect of pfhrp2 sequence variation on the binding of 11
MAbs1 have led to the characterization of 13 major epitopes (Table 4.8) recognized by those
MAbs.69,70 Using the amino acid sequences encoded by a total of 448 pfhrp2 genes originating
from P. falciparum isolates collected from a range of geographical regions,66 these 13 major epitopes were found to vary in their prevalence and average frequencies.69 Since durability to heat
is critical to the usefulness of RDTs in the tropical field setting, thermostability of those MAbs
was determined, and was also found to vary considerably.69 Results of these experiments enabled
the identification of MAbs with the most desirable characteristics for inclusion in RDTs. To the
knowledge of the current study, the information regarding pfhrp2-specific MAbs being used in SD
Bioline Malaria Ag P.f/Pan RDT is not disclosed by the manufacturer.
When epitope identification was performed in all Madagascar sequences, it was observed that epitopes DAHHAHHA, AHHAADAHHA, and AHHAADAHH were present in high prevalence and frequencies. Epitopes AHHAADAHHA and DAHHAHHA are recognized by
MAbs C1-13 and PTL-3, respectively, both of which have shown the best potential (based on the prevalence and frequency of epitopes together with the heat durability profile) for use in an RDT.69
The current study’s epitope identification results should be helpful for studies comparing performances of different RDTs in Madagascar, as well as for those evaluating new antibodies for the development of improved RDTs.133,134
5.2. PAPUA NEW GUINEA
The P. falciparum laboratory line parasite, D10, originated from Papua New Guinea135 and has been reported to lack the pfhrp2 gene53,70 similar to the Dd2 and 7G8 laboratory lines.53,65 In the
current study 16 out of 125 (13%) samples positive for P. falciparum by PCR did not amplify the
61
pfhrp2 gene. Two out of the 16 pfhrp2 gene-negative samples were also positive by microscopy
(with parasitemia around 840 parasites/µL and 40 parasites parasites/µL) for P. falciparum.
However, RDT diagnosis of malaria was not done on these PNG study samples12 and PCR amplification of pfhrp2 and PCR diagnosis are not sufficient to indicate or establish a pfhrp2 gene deletion in the current study.53 P. falciparum parasites lacking the pfhrp2 gene have been reported
in neighboring Asian countries; India,117 Thailand,66 Indonesia98 and the China-Myanmar border area.136 Eleven study samples from PNG that were positive for the pfhrp2 gene were negative for
P. falciparum by LDR-FMA and microscopy. The detection limit of RDTs are estimated to be
around 200 parasites/µL27 while microscopy can go as low as 5-50 parasites/µL27 and molecular
detection even lower at 0.05 parasites/µL27 A possible reason why this was observed could be the
presence of persistent circulating PfHRP2 antigens after parasite clearance.98
A study by Umbers et al, 2015 in Madang, PNG reported that CareStart™ P.f/Pan combo
RDT, currently in use in PNG (but not used in this study) had a sensitivity that was lower than
light microscopy when both were compared against real time PCR.110 The sensitivity of this RDT
was about 45% and, according to this study 54% of qPCR-positive peripheral P. falciparum
infections were missed by this RDT.110 The detection limit of the CareStart™ P.f/Pan combo RDT was reported to be about 100 parasites/µL.137
In contrast, a very recent evaluation of CareStart™ P.f/Pan in Senegal showed higher
sensitivity (97.3%) than light microscopy (93.2%).138 The specificity, however, of microscopy
(100%) was better than this RDT (94.1%) in that study.138
Although many parasite, host or device factors may influence the accuracy and sensitivity of pfhrp2-based RDTs53,65,80,98 and, pfhrp2 gene detection was not carried out in that study,110
pfhrp2 gene deletion may still be suspected since it has been already been reported in PNG;53,70
62 thus the findings in PNG from previous studies110 and findings in the current study support continuous monitoring of RDT usage for malaria diagnosis.
In the current PNG study, 100% (18/18) of the pfhrp2 sequences were found to be unique, i.e. 100% variability. This observation is consistent with previous observations of pfhrp2 exon-2 polymorphism where 71% (12/17) of unique pfhrp2 exon-2 sequences were identified in P. falciparum parasites from PNG.65,66 Analysis of pfhrp2 exon-2 sequences from current and previous studies (89% and 100%, respectively) in Madagascar are also in agreement with previous and current observation in PNG. Six out of 12 P. falciparum-infected blood samples from PNG amplified two different pfhrp2 gene sequences which suggested multiple-strain infections. The high pfhrp2 gene diversity and multiple-infection observed in the current study is expected of
PNG, a country with high malaria transmission intensity.128
Two out of the 18 pfhrp2 exon-2 sequences in the current study lack the Baker amino acid repeat type 1 and instead the exon-2 in these two pfhrp2 sequences began with Baker repeat type
2. This phenomenon was not observed in sequences from previous studies. Apart from this observation and the observation that no two sequences were identical in the study, the distribution of pfhrp2 amino acid repeat types in the current study (n = 18) and in previous studies (n = 15) were almost similar to pfhrp2 exon-2 sequences observed in the current (n = 18) and previous (n
= 96) Malagasy sequences.
The lack of RDT data for the PNG samples prevented the study from evaluating the effect of pfhrp2 sequence variation on RDT detection of P. falciparum infections in PNG. Excluding other factors that may influence RDT sensitivity53,65,80,98 and using Baker’s regression model65
(based on the number of Baker repeat types 2 and 7), it may be predicted that 11 out of 18 pfhrp2 sequences in the current study belong to P. falciparum parasites that may not be detectable by
63
RDT. (see Table 4.14). Similarly, three out of 15 pfhrp2 sequences from previous studies belong
to P. falciparum parasites that may not be RDT sensitive.
Apart from Baker’s regression model, an approach by Lee et al, 2012, to evaluate the effect
of the pfhrp2 gene sequence on RDT sensitivity characterized 13 major epitopes, in the pfhrp2
amino acid sequence, recognized by 11 monoclonal antibodies (MAbs).69,70
Similar to the Malagasy sequences, the 13 major epitopes were found in the PNG pfhrp2
exon-2 sequences and they vary in their prevalence and average frequencies. The epitope
identification in the PNG pfhrp2 gene sequences also show that the major epitopes DAHHAHHA,
AHHAADAHHA, and AHHAADAHH were present in high prevalence and frequencies. The study therefore recommends the use of RDTs that use MAbs (C1-13 and PTL-3)69 which recognize
these three major epitopes.
As mentioned earlier, the epitope identification results in this study should be helpful for
the comparison of different RDT performances in PNG and the evaluation of new MAbs for
improving RDTs for use in malaria detection in PNG.133,134
5.3 LIMITATIONS
The current study did not attempt to amplify the pfhrp2 gene paralog, pfhrp3. PfHRP3 has a
sequence homology of more than 75% in the tandem repeat region to PfHRP2 and is recognized
by most anti-PfHRP2 MAbs including C1-13.69,70 Normally, this cross-reactivity may not have a
major impact on the sensitivity of the RDTs because of the lower abundance of PfHRP3.67
However, in situations of low-level parasitemia or pfhrp2 gene deletions, PfHRP3 has been shown to have enhanced the sensitivity of the RDTs.114 It is also noted apart from PfHRP3 cross- reactivity, the effect of multiple-strain infections (intra-species) and multiple Plasmodium parasite
64
infections (inter-species) and other parasite or host factors, on RDT sensitivity were not evaluated
in this study.
In the current study, three samples, positive by P. falciparum LDR-FMA, were pfhrp2 PCR negative but RDT positive (false negatives in Table 4.2). In addition, seven samples, negative by
LDR-FMA but positive by microscopy, were pfhrp2 PCR negative but RDT positive (false positives in Table 4.4). This raises the possibility that they study may have missed pfhrp2 deletion because the RDT positive results for all these samples were due to PfHRP3 detection. It should also be noted that PCR/ LDR-FMA detection of Plasmodium parasites has a significantly higher sensitivity compared to RDT detection.139
The other limitation might be that the samples in the current study had limited geographic
origin, i.e. all were from single locations in both countries. Two previous studies analyzed pfhrp2 sequence variation in Madagascar and did not find pfhrp2 deletion.66,72 One of these studies was
conducted country-wide but did not use any RDT.72 Further studies should evaluate the performance of the pfhrp2-detecting RDT together with pfhrp2 variation in PNG and elsewhere in
Madagascar.
CHAPTER 6: CONCLUSIONS
Some major conclusions can be drawn from this study. First, the pfhrp2 exon-1 sequence is
possibly consistent across P. falciparum parasites that are pfhrp2 exon-1 positive.
Second, although Baker’s regression model for predicting parasite sensitivity to RDT did
not hold true for higher parasitaemia i.e. >250 parasites/µL,65,70 and also for a larger sample sizes,66
the Baker amino acid repeat naming system still served as a suitable method for analysis of the pfhrp2 exon-2 sequences in this study and in previous studies.66,70,75,126
65
Third, pfhrp2 gene deletion, assessed by analyzing both exons, was not found in the samples screened here. Fourth, the overall performance of the SD Bioline Malaria Ag P.f/Pan test kit (sensitivity and specificity 87% and 89%, respectively) includes the observation that the RDT did not detect eight P. falciparum PCR-positive samples (two microscopy-positive samples).
Finally, the RDT performance did not seem to be correlated with pfhrp2 gene variation, as described by Baker et al.66 Primary, community-based healthcare facilities in Madagascar and
PNG do not have capacity for microscopy-based diagnosis, this is limited to referral hospitals.5,11A
heavy reliance is therefore placed on RDTs for point-of-care malaria diagnosis in Madagascar and
PNG. The observed absence of pfhrp2 deletion from the samples screened here supports this continued recommendation for RDT.
However, since pfhrp2 gene deletions yielding false-negative RDTs have been confirmed
in Africa and South East Asia, and RDT negative samples without this gene deletion were found
in this study, it is essential from a public health perspective to perform routine screening so that
continued efficacy of RDT-based diagnosis is ensured in Madagascar and PNG.
66
APPENDIX Table A1. PCR Protocols
67
Table A2. Baker repeat “Barcodes” of Madagascar PfHRP2 exon-2 sequences in GenBank
GenBank Acc#: “Barcodes” FJ871319 1 1 1 2 2 3 2 6 7 7 7 7 2 2 2 2 2 2 2 2 3 5 7 8 2 7 7 6 2 10 12 FJ871318 1 2 2 2 3 2 2 2 2 2 2 2 8 2 7 6 14 2 7 6 2 7 7 10 12 FJ871317 1 1 2 2 3 2 6 2 7 7 7 2 2 2 2 2 2 3 5 7 8 2 7 6 6 7 7 6 2 7 10 12 FJ871316 1 1 1 2 2 3 2 6 7 7 7 7 2 2 2 2 2 2 3 5 7 8 2 7 6 6 7 7 6 2 12 FJ871315 1 1 2 2 3 2 6 7 7 2 2 2 2 2 2 2 8 2 7 6 7 7 2 10 7 2 10 12 FJ871314 1 1 1 1 2 2 2 3 2 6 7 7 2 2 2 2 2 2 2 3 2 7 8 2 7 6 7 7 6 2 10 12 FJ871313 1 2 2 3 2 6 2 7 6 2 2 2 2 2 2 2 3 5 7 8 2 7 6 2 6 7 7 6 2 2 10 10 12 FJ871312 1 1 2 2 3 2 4 2 2 2 2 2 2 2 2 8 2 7 6 2 6 2 6 2 7 7 7 7 6 12 FJ871311 1 1 1 2 2 4 2 2 2 2 2 2 2 2 5 7 8 2 8 2 7 7 6 14 2 6 7 7 7 6 2 6 2 12 FJ871310 1 1 1 1 2 2 3 2 6 7 7 7 7 2 2 2 2 2 2 2 3 5 7 8 2 7 6 7 7 7 6 2 10 12 FJ871309 1 1 2 3 2 2 2 2 2 2 2 2 3 5 7 8 7 7 6 2 6 2 6 2 6 2 6 2 6 2 7 10 12 FJ871308 1 1 1 2 2 2 3 2 2 2 2 2 2 2 2 2 8 2 7 6 2 6 7 6 6 7 7 7 6 2 10 10 12 FJ871307 1 1 2 4 2 4 2 2 2 2 2 2 2 3 5 7 8 2 7 6 2 6 2 7 6 12 FJ871306 1 1 1 2 2 2 2 2 2 2 2 2 2 2 3 2 7 8 2 6 7 6 6 7 7 7 7 10 12 FJ871305 1 1 2 2 3 2 6 7 7 7 7 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 7 6 2 10 12 FJ871304 1 1 3 2 2 2 3 2 2 2 2 2 2 2 2 5 7 8 2 7 6 2 6 2 6 2 6 2 6 7 6 7 7 7 7 10 1 EU589767 1 1 2 2 3 2 2 2 2 2 2 2 2 3 5 7 13 7 J 7 8 2 7 7 6 2 K 7 7 12 EU589766 1 1 1 1 2 2 3 2 6 6 2 6 2 2 2 1 2 2 7 8 5 7 8 2 7 2 6 7 7 6 10 12 EU589765 1 1 1 1 1 2 2 2 2 2 2 2 2 2 3 5 7 8 2 13 6 7 6 6 7 7 6 2 6 2 10 12 EU589764 1 4 2 2 2 2 2 2 2 2 2 3 5 7 8 2 8 2 7 6 7 6 2 6 7 6 7 6 2 7 L 7 10 12 EU589763 1 1 1 1 2 2 2 4 2 2 2 2 2 2 2 3 5 7 8 2 7 7 7 7 6 2 10 6 10 12 EU589762 1 1 1 1 1 2 2 2 2 2 2 2 2 3 5 7 8 2 7 7 6 2 6 7 6 6 7 7 6 2 10 10 12 EU589761 1 1 2 2 2 2 2 2 2 2 2 2 2 2 5 7 8 2 7 7 7 7 7 6 2 10 6 10 12 EU589760 1 1 2 2 3 2 6 6 6 6 7 6 7 6 2 2 2 2 3 5 7 8 2 7 7 6 2 2 2 7 7 6 2 10 10 12 EU589759 1 4 2 4 2 2 4 2 7 2 2 2 2 2 7 8 2 8 2 7 6 2 6 7 7 7 7 7 6 2 2 2 10 10 12 EU589758 1 4 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 8 2 7 6 7 6 7 6 7 7 6 M 7 10 10 12 EU589757 1 1 I 7 8 2 H 6 6 7 7 6 2 2 2 N L 12 EU589756 1 1 1 1 1 2 2 2 6 7 7 2 2 2 2 2 3 5 7 8 2 7 6 6 2 7 6 2 10 10 12 EU589755 1 1 1 2 2 3 2 2 2 2 2 2 2 2 3 5 7 8 2 6 7 6 7 7 7 7 10 6 12 EU589754 1 1 2 2 2 8 2 2 2 2 2 2 2 3 2 2 8 2 7 6 7 6 7 7 2 2 10 10 10 12 EU589753 1 1 2 2 2 2 4 2 2 2 2 2 2 5 7 8 2 7 6 14 2 6 7 7 7 7 6 2 19 7 E 12 EU589752 2 4 2 4 4 0 2 2 2 2 2 2 3 2 6 7 8 2 7 7 7 7 10 10 12 EU589751 1 2 2 3 2 6 4 4 P 6 2 2 2 2 3 5 7 8 2 7 6 2 6 2 2 6 7 7 10 19 I Q 12 EU589750 1 1 1 2 2 3 2 7 7 7 7 6 2 2 2 2 2 2 2 5 7 8 2 7 7 6 6 2 6 2 10 12 EU589749 1 1 2 2 3 2 6 6 7 7 7 3 5 7 8 2 7 6 2 7 6 2 7 6 2 10 10 12 EU589748 1 1 2 2 3 2 6 7 7 6 2 2 2 2 2 2 2 3 5 7 8 2 7 6 7 7 7 10 10 12 EU589747 1 1 1 2 2 2 4 2 2 2 2 2 2 2 3 5 7 8 2 7 6 7 7 7 6 7 7 6 2 10 10 12 EU589746 1 1 2 2 2 3 2 6 7 7 7 2 2 2 2 2 3 5 7 8 2 7 6 2 6 2 10 10 12 EU589745 1 1 2 2 2 2 3 2 6 7 P 14 2 2 2 2 2 2 3 5 7 8 2 7 6 7 7 6 4 10 10 12 EU589744 1 4 2 2 2 2 7 2 2 2 2 2 3 5 7 8 2 8 2 7 6 7 6 7 6 7 6 7 7 6 2 10 10 12 EU589743 1 1 2 2 3 2 4 2 2 2 2 2 5 7 8 2 7 6 7 7 10 10 12 EU589742 1 2 2 2 2 2 3 2 3 5 7 8 2 2 2 2 2 3 5 7 8 2 7 6 7 6 7 7 6 2 10 6 12 EU589741 1 1 2 2 2 2 2 2 2 2 2 2 2 3 5 7 8 2 3 5 7 8 2 7 7 7 6 7 7 6 14 2 5 7 8 12 EU589740 1 1 1 2 2 3 2 6 7 7 2 2 2 2 2 3 5 7 8 2 7 6 7 6 7 7 6 2 10 10 12 EU589739 1 2 2 2 3 2 2 2 2 2 2 2 2 3 5 7 7 8 2 7 6 7 7 7 7 6 7 7 6 2 10 12 EU589738 1 1 1 1 2 2 2 3 5 7 8 2 7 7 6 2 6 7 6 2 2 10 10 12 EU589737 1 1 2 2 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 7 6 7 7 6 2 2 10 10 12 EU589736 1 1 2 2 3 2 6 7 7 7 7 2 2 2 2 2 3 5 7 8 2 7 6 2 6 2 7 R 6 12 EU589735 1 1 2 2 3 2 6 7 2 2 2 2 2 2 2 2 3 5 7 8 2 7 6 2 6 7 6 7 10 6 S 12 EU589734 1 4 2 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 6 7 6 7 6 7 7 6 2 10 10 12 EU589733 1 1 1 2 2 2 2 2 2 2 2 2 14 2 3 2 8 2 7 6 7 7 6 2 10 E T 12 EU589732 1 1 2 2 3 2 6 7 7 6 7 2 2 2 2 2 2 2 2 3 5 7 7 6 7 7 6 2 7 12 EU589731 1 1 2 2 3 2 6 7 6 4 2 6 2 2 6 2 2 2 2 3 2 8 2 7 6 2 6 2 6 7 7 6 7 7 10 10 1 EU589730 1 1 2 2 2 3 2 2 2 2 2 2 2 2 3 5 7 7 8 2 7 6 7 7 7 7 6 7 7 6 2 10 10 12 EU589729 1 1 1 1 1 2 2 2 2 2 2 2 2 2 3 5 7 8 2 13 6 7 6 6 2 6 U V W 6 4 X 12 EU589728 1 1 2 2 3 2 6 7 7 7 2 7 2 2 2 2 2 2 2 3 5 7 8 2 4 6 7 7 6 4 4 4 12 EU589727 1 1 2 2 3 2 6 7 7 6 2 2 2 2 2 2 3 5 7 8 2 7 6 7 6 7 7 6 2 4 X S 6 12 EU589726 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 6 7 7 6 7 7 6 2 10 10 12 EU589725 1 1 2 2 3 2 6 6 7 7 7 7 2 2 2 2 2 3 5 7 8 2 6 7 7 7 6 2 10 12 EU589724 1 1 2 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 7 7 7 6 7 7 6 2 5 7 8 12 EU589723 1 1 2 3 2 2 2 2 2 2 3 5 7 8 2 7 6 7 6 7 7 6 2 7 6 2 10 10 12 EU589722 1 1 1 2 2 2 2 6 6 7 7 2 2 2 2 2 3 5 7 8 2 7 6 2 6 2 10 10 12 EU589721 1 1 1 1 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 7 6 7 Y 12 EU589720 1 1 1 1 2 2 3 2 6 7 6 7 7 2 2 2 2 2 2 2 3 5 7 8 2 7 6 7 7 6 2 19 E 6 12 EU589719 1 2 1 2 2 2 2 2 6 7 7 7 2 2 2 2 2 2 3 5 7 8 2 7 6 7 7 6 2 10 4 6 12 EU589718 1 1 1 2 2 3 2 2 2 7 2 2 2 2 2 2 2 2 2 7 7 7 6 2 10 10 12 EU589717 1 1 2 2 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 7 6 7 7 6 2 5 7 8 2 6 12 EU589716 1 1 1 2 2 3 2 7 2 2 2 2 3 5 7 8 2 7 6 7 7 6 2 10 12 EU589715 1 2 1 2 1 1 2 7 6 2 2 2 2 3 5 7 8 2 7 7 8 2 6 2 6 2 7 10 10 12 EU589714 1 1 1 2 1 2 2 3 2 6 7 7 7 7 7 7 7 7 7 2 2 3 5 7 8 2 7 6 7 7 2 10 10 12 EU589713 1 1 1 1 2 2 3 2 2 2 2 2 2 2 2 3 5 7 8 2 7 6 2 6 7 7 12 EU589712 1 1 2 2 3 2 2 2 2 2 2 5 7 8 5 7 8 2 7 7 6 2 6 2 7 7 6 2 10 10 12 EU589711 1 1 2 2 3 2 O 2 2 2 2 2 2 2 3 5 7 8 2 7 6 7 6 7 7 7 7 7 7 7 7 10 10 12 68
EU589710 1 1 1 2 2 2 2 2 2 2 2 2 2 3 5 7 8 2 13 6 7 6 6 7 7 6 2 10 10 12 EU589709 1 1 1 2 3 2 2 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 6 2 7 6 7 7 7 7 10 12 EU589708 1 1 2 2 3 2 2 2 2 2 2 5 7 8 5 5 7 7 7 7 6 2 6 2 7 7 7 6 2 10 10 12 EU589707 1 1 2 2 3 2 2 2 2 2 2 2 2 2 2 8 2 7 6 6 2 6 7 7 7 7 10 10 12 EU589706 1 1 2 2 2 2 3 2 2 2 2 2 2 3 5 7 8 2 8 2 7 6 7 6 7 7 6 7 7 10 10 12 EU589705 1 1 1 2 2 2 3 2 2 2 2 2 2 2 2 8 2 7 6 7 7 6 7 7 7 7 7 10 10 10 12 EU589704 1 2 2 3 2 6 7 7 2 2 2 2 2 2 3 5 7 8 2 7 7 6 7 7 2 2 10 10 12 EU589703 1 1 2 2 3 2 6 2 6 2 2 2 1 2 2 5 7 8 5 7 8 2 6 2 6 7 7 10 10 6 12 EU589702 1 1 1 1 2 2 3 2 4 2 2 2 2 2 2 7 6 7 8 2 8 2 7 7 6 7 7 6 2 10 10 12 EU589701 1 1 2 2 3 2 2 2 2 2 2 2 2 3 5 7 13 7 8 2 7 6 2 6 7 7 7 10 12 EU589700 1 1 2 1 1 1 1 2 2 2 2 2 2 3 5 7 8 2 7 14 2 7 7 6 6 2 10 10 12 EU589699 1 4 2 2 2 2 2 2 2 2 2 3 5 7 8 2 8 2 7 6 7 6 7 7 6 2 10 10 12 EU589698 1 1 1 2 2 3 2 2 2 2 2 2 2 3 5 7 8 2 7 6 2 6 2 7 7 7 6 7 12 EU589697 1 1 1 1 1 4 23 2 2 2 2 2 2 2 3 5 7 8 2 7 7 6 2 6 7 6 6 7 7 6 2 10 10 12 EU589696 1 1 2 2 2 2 3 2 2 2 2 2 2 2 2 3 5 7 8 7 6 7 7 7 7 6 7 7 6 2 10 12 EU589695 1 1 2 2 2 8 2 4 2 2 2 2 2 2 2 8 2 7 6 2 6 2 6 2 7 7 7 6 12 EU589694 1 1 2 2 8 2 7 6 14 2 6 14 2 6 2 7 6 2 7 10 10 12 EU589693 1 1 2 2 2 3 2 2 2 2 2 2 8 2 6 2 6 2 7 7 7 7 7 6 2 7 10 10 12 EU589692 1 1 2 2 3 2 6 7 6 4 2 6 2 2 2 2 3 5 7 8 2 7 6 2 6 7 7 10 10 12 EU589691 1 1 1 1 1 2 2 2 2 2 2 2 2 2 3 5 7 8 2 13 6 7 6 6 7 7 6 2 6 2 10 12 EU589690 1 1 1 1 1 2 2 2 2 2 2 2 2 2 3 5 7 8 2 13 6 7 7 7 7 7 6 2 6 2 10 12 EU589689 1 1 2 2 2 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 6 2 6 2 6 2 10 10 12 EU589688 1 1 2 2 2 3 2 2 2 2 2 2 2 2 3 5 7 7 8 2 7 6 7 7 7 7 7 6 7 7 6 2 10 12
Baker et al in 2005 (updated in Baker et al, 2010) assigned numbers (1–24) to different amino acid repeat type that they observed in protein sequences of PfHRP2 and PfHRP3. (see Table 1.1). The sequence of these numbers, i.e. “Barcode” represent the sequence of amino acid repeat types as shown in the Appendix Table A2-A5. Since then, “non-Baker” repeat types or other amino acid sequences have also been observed by others. (see Table 4.12).
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Table A3. Baker repeat “Barcodes” of Madagascar PfHRP2 exon-2 sequences in This Study
Sample GenBank “Barcodes” ID: Acc#: Ex2004 KX886207 1 1 1 2 2 3 2 2 2 2 2 4 D 2 3 5 7 8 2 13 6 2 6 2 7 7 7 7 10 6 E 12 Ex2002 KX886208 1 1 1 2 2 3 2 2 2 2 2 2 2 3 5 7 8 2 6 6 2 6 2 7 7 4 D 7 10 6 19 12 Ex30704 KX886209 1 1 1 1 1 1 1 2 2 2 2 2 2 2 A 2 7 6 2 6 6 2 7 7 6 2 7 10 7 10 12 2070803 KX886210 1 1 1 2 2 3 2 6 B 1 2 2 2 2 2 3 5 7 8 2 7 6 2 6 7 7 6 2 10 10 19 12 3020205 KX886211 1 1 1 2 2 3 2 C B 2 2 2 2 2 2 3 5 7 8 2 7 6 2 6 7 7 6 2 10 10 19 12 1021506 MF554693 1 1 1 2 2 3 2 2 2 2 2 2 2 3 5 7 8 2 6 6 12 Ext2246A MF554694 1 1 1 2 2 2 2 2 2 2 2 2 2 2 3 2 13 12 Ext2246B MF554695 1 1 1 2 3 2 7 6 6 7 7 7 7 6 2 10 10 10 8 2 6 12 Ext2263 MF554696 1 1 2 2 2 2 3 5 7 8 2 7 6 7 7 6 2 2 10 12 Ext30507A MF554697 2 2 2 2 2 2 2 2 3 5 7 8 2 7 6 6 7 7 6 2 2 10 12 Ext30507B MF554698 1 1 2 2 3 2 6 7 7 7 2 2 2 2 2 2 2 3 5 7 8 2 12 Ext30508 MF554699 1 1 2 2 3 2 6 7 7 7 2 2 2 2 2 2 2 3 5 7 8 2 7 6 6 7 7 6 2 2 10 12 Ext2229A MF554700 1 1 2 2 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 7 7 7 6 2 6 2 10 6 10 12 Ext2229B MF554701 1 1 2 2 2 2 2 2 2 2 2 2 2 F 9 5 7 8 7 7 7 7 7 6 2 6 2 10 6 10 10 6 10 12 Ext2223A MF554702 1 1 2 2 3 2 6 4 2 6 2 2 2 2 3 5 7 8 2 7 6 2 6 2 6 7 7 10 10 12 Ext2223B MF554703 1 1 2 2 3 2 6 4 2 6 F G 2 2 2 3 5 7 8 2 7 6 2 6 2 6 7 7 10 10 12 2100306 MF554704 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 6 6 7 7 7 7 6 2 10 10 10 12 Ext2230 MF554705 1 1 2 2 2 2 3 5 7 8 2 7 6 7 7 6 2 2 10 12 3091101 * 1 2 2 3 2 4 14 4 4 4 4 4 4 4 4 4 4 4 4 4 14 2 2 2 2 3 5 7 8 2 7 7 7 2 8 2011303 * 1 1 2 2 3 2 2 2 2 2 2 2 2 2 2 13 7 8 2 6 4 4 14 2 13 4 13 6 2 12 *submitted to Genbank
Table A4. Baker repeat “Barcodes” of PNG PfHRP2 exon-2 sequences in GenBank
GenBank Acc#: "Barcode" AY816241.1 1 1 2 2 2 2 2 3 5 7 8 2 7 7 6 7 6 7 6 7 2 10 10 12 AY816242.1 1 1 2 4 7 4 7 2 2 2 2 2 2 3 5 7 8 2 7 6 2 6 2 6 2 6 2 6 2 10 10 12 AY816243.1 1 2 2 2 2 2 3 2 2 2 2 2 2 2 8 5 7 7 8 2 7 6 2 10 6 12 AY816253.1 1 1 1 3 2 4 7 5 2 2 2 2 5 7 8 5 7 8 2 7 6 2 6 7 6 7 7 6 7 10 10 12 AY816254.1 1 2 2 2 2 2 2 3 2 2 2 2 2 5 2 8 5 7 8 2 7 6 6 6 6 6 2 7 19 13 6 12 AY816255.1 1 2 2 2 2 2 2 3 2 2 2 2 2 2 2 7 13 7 7 2 7 6 6 6 6 6 2 7 10 6 12 AY816256.1 1 2 2 2 2 2 2 3 2 2 2 2 2 2 2 8 5 7 8 2 7 6 6 6 6 6 2 7 10 6 12 AY816257.1 1 1 1 3 2 4 7 5 2 2 2 2 5 7 8 5 7 8 2 7 6 2 6 7 6 7 7 6 7 10 10 12 AY816258.1 1 1 1 2 2 3 2 2 2 2 2 2 2 3 5 7 8 2 7 6 2 6 10 2 7 6 6 7 7 6 7 7 6 7 7 6 2 10 12 FJ872261.1 1 1 1 2 2 3 2 4 2 4 2 2 2 2 5 7 8 2 7 6 7 6 7 6 7 6 7 7 6 7 10 10 12 FJ872262.1 1 1 1 2 3 2 6 7 7 6 2 2 2 2 2 5 7 8 2 8 2 7 10 2 6 7 7 2 10 10 12 FJ872263.1 1 1 2 2 3 2 6 7 7 6 2 2 2 2 2 5 7 8 2 8 2 7 10 2 6 7 7 2 10 10 12 FJ871241.1 1 1 1 2 2 3 2 2 2 2 2 2 2 3 5 7 8 2 7 6 6 2 7 7 6 7 A 6 2 10 12 FJ871294.1 1 1 2 1 1 2 2 4 7 2 2 2 2 2 2 3 5 7 8 2 7 6 7 7 6 7 7 7 19 X 10 6 12 FJ871358.1 1 1 1 2 2 3 2 2 2 2 2 2 2 3 5 7 8 2 7 6 6 2 7 7 6 7 7 6 2 10 10 12
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Table A5. Baker repeat “Barcodes” of PNG PfHRP2 exon-2 sequences in This Study
GenBank GenBank ID: "Barcode" Acc#: DFA4927 MF673786.1 1 1 1 2 2 2 3 2 2 2 2 2 2 2 2 9 2 7 6 2 6 2 2 6 2 7 10 6 12
DFA4929 MF673787.1 1 1 1 1 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 6 7 7 6 7 7 6 7 7 10 10 12
DFA4934 MF673788.1 1 1 2 1 1 2 2 2 2 2 2 2 2 2 3 5 7 8 2 7 6 7 7 7 7 7 10 10 6 12
DFA4938 MF673789.1 1 1 2 2 3 2 6 7 7 6 2 2 2 2 2 2 4 19 5 C 8 2 13 2 12
DFA4940-1 MF673790.1 1 1 2 2 3 2 7 8 2 6 7 2 2 2 2 2 3 5 7 Z 2 7 6 7 7 13 2 12
DFA4940-2 MF673791.1 2 2 1 2 7 8 2 7 6 7 7 7 7 7 6 2 2 10 10 12
DFA4942 MF673792.1 1 1 2 2 3 2 6 7 2 2 2 2 2 3 5 7 8 2 7 6 7 7 6 2 2 10 10 12
DFA5008-1 MF673793.1 1 1 2 2 2 3 2 6 7 7 7 7 7 2 2 2 2 2 2 3 5 7 8 2 7 6 7 7 6 2 10 10 12
DFA5008-2 MF673794.1 1 1 1 2 2 3 2 2 2 2 2 2 2 3 5 7 8 2 6 6 2 6 2 7 7 7 7 10 6 12
DFB0007-1 MF673795.1 1 1 2 2 3 2 2 2 2 2 2 3 5 7 C 8 C 19 6 7 7 6 12
DFB0007-2 MF673796.1 1 1 2 2 N 7 6 2 2 C 7 7 6 2 2 2 10 10 12
DFB0013-1 MF673797.1 1 1 2 2 3 2 6 2 6 6 6 2 2 2 2 2 2 2 3 5 7 8 2 7 7 6 2 10 10 12
DFB0013-2 MF673798.1 1 1 1 2 2 3 2 2 2 2 2 2 2 3 5 7 8 2 6 6 4 2 12
DFB0014-1 MF673799.1 1 1 1 2 2 3 2 2 2 2 2 2 2 2 3 5 7 8 2 7 12
DFB0014-2 MF673800.1 1 1 1 2 2 3 5 13 7 8 2 7 6 6 7 6 2 10 10 10 7 12
DFB0031-1 MF673801.1 1 1 1 2 1 3 2 3 2 2 2 2 2 3 12
DFB0031-2 MF673802.1 2 2 4 Y 2 2 3 5 7 8 2 6 6 2 6 2 7 7 7 7 7 6 6 2 12
DFB0051 MF673803.1 1 2 2 2 2 2 2 3 2 2 2 2 2 2 2 8 5 7 8 2 7 6 6 6 6 6 2 12
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FIGURE A1. 18S rRNA gene PCR gel
The diagnostic assay for malaria infection in the current study includes PCR amplification of a region of the 18S rRNA gene, a multi-copy gene, found in all four malaria-causing parasites, carried out in study samples from PNG (shown above) and Madagascar. The presence of bands ranging from 500–550bp indicates Plasmodium infection. This PCR exercise is followed by Ligase Detection Reaction-Fluorescent Microsphere Assay (LDR-FMA) that allows distinguishing between the different Plasmodium species in the infected samples.55
72
FIGURE A2. PfHRP2 primer set#2 PCR
FIGURE A2.1. PfHRP2 primer set#2 PCR on P. falciparum laboratory strains
The PCR amplification of the pfhrp2 gene using primer set #2 in P. falciparum laboratory strains show the presence of the gene in the strains Hb3, 3d7, K1, 1917, 1905, W2MEF, FCB and ITG2F6. The amplicons showed here are about 200–250bp. The laboratory strains Dd2 and 7G8, which lack the pfhrp2 gene,53,65 did not show any bands.
73
FIGURE A2.2. PfHRP2 primer set#2 PCR on Madagascar samples
FIGURE A2.3. PfHRP2 primer set#2 PCR on Papua New Guinea samples
The PCR amplification of the pfhrp2 gene using Primer set #2 showed was the best option out of the three primer sets for the identification of pfhrp2-positive samples in Madagascar and PNG samples. Bands of sizes ranging from 200–250 bp indicated pfhrp2 presence thus pfhrp2-positive samples.
74
FIGURE A3. PfHRP2 primer set#3 (nest 2) PCR on Madagascar samples
The PCR amplification of the pfhrp2 gene using Primer set #3 showed multiple bands in genomic DNA extract from blood spot samples from Madagascar thus posing a challenge to identify pfhrp2-positive samples. However, bands could be cut from gels within the range of 435–927 base pairs and sequence. The sequences generated were identifiable as pfhrp2 gene sequence fragments in Geneious v.10.0.2 when compared to reference pfhrp2 sequences from GenBank.
75
FIGURE A3. RDT detection of Malaria in P. falciparum culture isolates
Five P. falciparum culture isolates (Ex2004, Ex2002, Ex30704, 2070803 and 3020205) were tested for P. falciparum by PfHRP2-based RDT (CarestartTM Malaria HRP2/pLDH(Pf/PAN) Combo RDT). All 5 parasite cultures showed all bands (111) i.e. positive for control, P. falciparum and PAN (other Plasmodium spp.)
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