Identifying host genetic factors controlling susceptibility to blood-stage malaria in mice
Aurélie Laroque
Department of Biochemistry McGill University Montreal, Quebec, Canada
December 2016
A thesis submitted to McGill University in partial fulfilment of the requirements of the degree of Doctor of Philosophy.
© Aurélie Laroque, 2016 ABSTRACT
This thesis examines genetic factors controlling host response to blood stage malaria in mice. We first phenotyped 25 inbred strains for resistance/susceptibility to
Plasmodium chabaudi chabaudi AS infection. A broad spectrum of responses was observed, which suggests rich genetic diversity among different mouse strains in response to malaria. A F2 intercross was generated between susceptible SM/J and resistant C57BL/6 mice and the progeny was phenotyped for susceptibility to P. chabaudi chabaudi AS infection. A whole genome scan revealed the Char1 locus as a key regulator of parasite density. Using a haplotype mapping approach, we reduced the locus to a 0.4Mb conserved interval that segregates with resistance/susceptibility to infection for the search of positional candidate genes. In addition, I pursued the work on the Char10 locus that was previously identified in [AcB62xCBA/PK]F2 animals (LOD=10.8, 95% Bayesian CI=50.7-75Mb). Pyruvate kinase deficiency was found to protect mice and humans against malaria. However, AcB62 mice are susceptible to P. chabaudi infection despite carrying the protective PklrI90N mutation.
We characterized the Char10 locus and showed that it modulates the severity of the pyruvate deficiency phenotype by regulating erythroid responses. We created 4 congenic lines carrying different portions of the Char10 interval and demonstrated that Char10 is found within a maximal 4Mb interval. Exome sequencing in this region identified genetic variants in 13 genes while RNA sequencing revealed 14 genes differentially expressed between CBA/Pk and Char10C congenic mice. Overall, my
ii thesis work uncovered and precised the role of genetic factors controlling susceptibility/resistance to P. chabaudi infection in mice and contributes to better understand the genetic and physiological basis of host response to blood-stage malaria.
iii RÉSUMÉ
Cette thèse examine les facteurs génétiques contrôlant la réponse de l’hôte à la malaria chez la souris. Dans un premier temps, nous avons phénotypé 25 souches de souris pour déterminer leur résistance ou susceptibilité à l’infection par P. chabaudi chabaudi AS. Un spectre de réponses important a été observé, suggérant une diversité génétique riche en réponse à la malaria. Un croisement F2 a été généré entre les souris susceptibles SM/J et les résistantes C57BL/6. Le phenotypage, le génome scan et l’analyse de linkage ont révélé le locus Char1 comme régulateur clé du niveau de parasitémie dans les [SM/JxC57BL/6]F2. Une analyse d’haplotypes dans Char1 a permis de réduire le locus à un intervalle de 0.4Mb pour la priorisation de gènes candidats. J’ai aussi poursuivi le travail sur le locus Char10 qui avaient été identifié dans un croisement [AcB62xCBA/PK]F2 (LOD=10.8, 95% Bayesian CI=50.7-
75Mb). Il avait été précédemment démontré que la déficience en pyruvate kinase protège les souris et les hommes contre la malaria. Cependant, les souris AcB62, qui portent la mutation protectrice PklrI90N s’avèrent être susceptibles à l’infection par P. chabaudi. Nous avons caractérisé le locus Char10 et avons montré qu’il module la sévérité de la déficience en pyruvate kinase en régulant la réponse erythroïde. Nous avons créé 4 lignées congéniques portant des portions différentes de la région
Char10 et avons démontré que le gène responsable de l’effet Char10 se trouve dans un intervalle maximal de 4Mb. Le séquençage d’exome dans cette région a permis d’identifier des variants génétiques dans 13 gènes et le séquençage d’ARN a révélé
iv que 14 gènes étaient différentiellement exprimés entre les lignées CBA/Pk et
Char10C. En résumé, ma thèse aura permis de découvrir et de préciser le rôle de facteurs génétiques contrôlant la résistance/susceptibilité à l’infection par P. chabaudi chez la souris et contribue à l’avancée des connaissances génétiques et des mécanismes physiologiques entourant la réponse de l’hôte à la malaria.
v PREFACE
The work described in chapter 2, 3 and 4 of this thesis has been published as follows:
Chapter 2: Laroque A., Min-Oo G., Tam M., Radovanovic I., Stevenson M.M. and
Gros P. Genetic control of susceptibility to infection with Plasmodium
chabaudi chabaudi AS in inbred mouse strains. Genes and Immunity.
2012; 13: 155-163.
Chapter 3: Laroque A., Min-Oo G., Tam M., Ponka P, Stevenson M.M. and Gros
P. The mouse Char10 locus regulates severity of pyruvate kinase
deficiency and susceptibility to malaria. 2016. Submitted to PLoSOne.
Chapter 4: Laroque A., Min-Oo G., Tam M., Stevenson M.M. and Gros P. The
Char10 locus: a genetic modifier of the malaria-protective effect of
pyruvate kinase deficiency. 2016. In preparation.
In addition, parts of Chapter 1 have been adapted from:
Laroque A., Bongfen S.E., Berghout J. and Gros P. Genetic and genomic analyses of
host-pathogen interactions in malaria. Trends in Parasitology. 2009;
9: 417-422.
vi CONTRIBUTION OF AUTHORS
Chapter 2: I performed most of the work presented in this chapter. Helpful assistance was provided by the following individuals.
Gundula Min-Oo initiated the survey of the 25 inbred strains. She performed the first screening. I took over the 1st and performed a 2nd screening. I smeared the mice and phenotyped them for survival and parasitemia (Table 2.1 and Figure 2.1). Susan
Gauthier generated the [SM/JxC57BL/6]F2 animals. I phenotyped the F2 animals for survival by monitoring disease and taking blood smears for the 250 mice each day during 21 days. Mifong Tam injected all mice and counted the parasitemia levels in the F2 cross. I prepared DNA from tail clips, genotyped all mice for additional microsatellite markers and performed the linkage analysis (Figure 2.3). I performed the haplotype analysis (Figure 2.4). Irena Radovanovic performed the EMMA scan
(Figure 2.S1). Mifong Tam provided guidance and assistance with flow cytometry
(Figure 2.S2). I wrote the first draft of the manuscript and generated all tables and figures. Dr Mary M. Stevenson provided feedback on the article as well as on the experimental design throughout the project.
Chapter 3: I performed most of the work presented in this chapter. Helpful assistance was provided by the following individuals.
I generated the Char10C congenic line (which was initiated by Gundula Min-Oo).
Susan Gauthier helped with the breeding. I phenotyped mice for peak parasitemia
vii and reticulocyte levels. I performed the hematology and the histology characterization
(Figure 3.2 and Figure 3.3). Marc Mikhael and Dr Ponka performed the iron measurements in the plasma (Figure 3.4). I determined the iron measurements in the tissues (Figure 3.3). Mifong Tam performed the biotin labeling assay (Figure 3.5). I did the flow cytometry experiments (Figure 3.6) and, after being trained by Mifong
Tam, the CFUe assay (Figure 3.7). I wrote the first draft of the manuscript and generated all tables and figures. Dr Mary M. Stevenson provided feedback on the article as well as on the experimental design throughout the project.
Chapter 4: I performed most of the work presented in this chapter. Helpful assistance was provided by the following individuals.
Gundula Min-Oo did the linkage analysis of the [AcB62xCBA/Pk]F2 cross, while
Mifong Tam helped with the phenotyping (Figure 4.1 and Figure 4.2).
Gundula Min-Oo and I generated 4 congenic lines. I phenotyped them for both peak parasitemia and reticulocyte levels and refined the Char10 interval (Figure 4.3). I extracted the genomic DNA from ear biopsies for the exome sequencing and analysed the data (Table 4.1). For the RNA sequencing, I extracted the RNA and analysed the results with guidance from David Langlais (Table 4.2). I wrote the manuscript.
My supervisor: Dr. Philippe Gros, provided guidance and advice throughout my PhD, reviewed the results and edited all manuscripts.
viii TABLE OF CONTENT
ABSTRACT ...... ii
RÉSUMÉ ...... iv
PREFACE ...... vi
CONTRIBUTION OF AUTHORS ...... vii
LIST OF FIGURES ...... xii
LIST OF TABLES ...... xiv
ACKNOWLEDGEMENTS ...... xv
RATIONALE AND OBJECTIVES ...... xvi
Chapter 1 : Introduction and literature review ...... 1 1.1 Introduction: historical perspectives and prevalence of malaria ...... 2 1.2. The parasite ...... 6 1.2.1. The Plasmodium life cycle ...... 6 1.2.1.1. Pre-erythrocytic stage (PE) ...... 8 1.2.1.2 Erythrocytic stage ...... 9 1.2.1.3 Sexual life cycle ...... 11 1.2.2 Genetic diversity of Plasmodium falciparum ...... 12 1.3 Malaria pathophysiology and immunity ...... 13 1.3.1 Malaria-related anemia ...... 14 1.3.2 Cytoadherence and rosetting ...... 16 1.3.3 Immunity ...... 17 1.4 The host ...... 20 1.4.1 Malaria’s selective pressure on the human genome ...... 20 1.4.1.1 Erythrocyte polymorphisms ...... 20 1.4.1.1.1 Hemoglobin variants ...... 21 1.4.1.1.2 Other red cell polymorphisms ...... 24
ix 1.4.1.1.3 Emphasis on Pyruvate Kinase (PK) deficiency ...... 26 1.4.1.2 Non erythrocytes genes associated with malaria resistance ...... 28 1.5 Mouse Models ...... 29 1.5.1 Advantages of the mouse as a model organism ...... 29 1.5.2 The Plasmodium chabaudi model of infection ...... 30 1.5.3 Identification of the Char loci ...... 32
Chapter 2 : Genetic control of susceptibility to infection with Plasmodium chabaudi chabaudi AS in inbred mouse strains ...... 35 2.1 Abstract ...... 36 2.2 Introduction ...... 37 2.3 Materials and methods ...... 41 2.4 Results ...... 44 2.5 Discussion ...... 56 2.6 Aknowledgements ...... 59 2.7 Supplementary information ...... 59
Chapter 3 : The Mouse Char10 Locus Regulates Severity of Pyruvate Kinase Deficiency and Susceptibility to Malaria ...... 67 3.1 Abstract ...... 68 3.2 Introduction ...... 70 3.3 Materials and Methods ...... 73 3.4 Results ...... 79 3.5 Discussion ...... 92 3.6 Acknowledgments ...... 96 3.7 Supporting Information ...... 96
Chapter 4 : The Char10 locus: a genetic modifier of the malaria- protective effect of pyruvate kinase deficiency ...... 98 4.1 Abstract ...... 99 4.2 Introduction ...... 100 4.3 Materials and methods ...... 103 4.4 Results ...... 106 4.5 Discussion ...... 118
x 4.6 Acknowledgements ...... 122
Chapter 5 : Summary, Discussion and Futures Directions ...... 123 5.1. Summary ...... 124 5.2 Discussion and futures directions ...... 126 5.3 Final conclusions ...... 133
ORIGINAL CONTRIBUTIONS TO KNOWLEDGE ...... 134
REFERENCES ...... 135
xi LIST OF FIGURES
Chapter 1
Figure 1.1 Countries with ongoing transmission of malaria, 2013 ...... 5 Figure 1.2 The Plasmodium life cycle ...... 7
Chapter 2
Figure 2.1 Differential susceptibility of C57BL/6J and SM/J mice to P. chabaudi chabaudi AS infection ...... 49 Figure 2.2 Segregation analysis of susceptibility of P. chabaudi chabaudi AS infection in [SM/JxC57BL/6J]F1 and F2 mice ...... 50 Figure 2.3 Genetic analysis of differential susceptibility to P. chabaudi chabaudi AS infection in resistant C57BL/6J and susceptible SM/J mice ...... 53 Figure 2.4 Co-segregation of Char1 haplotypes in 129x1/SvJ, C57BL/6J, SM/J, SJL/J, C3H/HeJ and NC/Jic inbred strains ...... 55 Figure 2.S1 Genome-wide association mapping using EMMA ...... 60 Figure 2.S2 Percentage of CD4+ cells in the spleen of C57BL/6J and SM/J mice ...... 61
Chapter 3
Figure 3.1 Construction and Phenotyping of the Char10C congenic line...... 74 Figure 3.2 Comparative hematological profile of the Char10C congenic line...... 82 Figure 3.3 Iron determination in peripheral tissues...... 84 Figure 3.4 Iron-related measurements in plasma...... 85 Figure 3.5 Effect of Char10 on turnover of biotinylated erythrocytes...... 87 Figure 3.6 Flow cytometric analysis of the spleen erythroid compartment...... 90 Figure 3.7 Enumeration of CFU-E progenitors in spleens...... 91 Table 3.S1 Blood Cellular Profile of CBA/Pk and Char10C...... 96
xii Chapter 4
Figure 4.1 Linkage analysis in [AcB62xCBA/Pk]F2 mice...... 108 Figure 4.2 Segregation of peak parasitemia and reticulocyte levels by genotype at Pklr and Char10 loci...... 110 Figure 4.3 Construction and phenotyping of four Char10 congenic lines...... 112
xiii LIST OF TABLES
Chapter 2
Table 2.1 Phenotypic responses of 25 inbred strains to infection with P. chabaudi chabaudi AS ...... 47 Table 2.S1 Genes in the Char1 region containing IFNγ-inducible STAT-1 binding site(s) ...... 62
Chapter 3
Table 3.S1 Blood Cellular Profile of CBA/Pk and Char10C...... 96
Chapter 4
Table 4.1 Exome sequencing analysis of CBA/Pk and Char10C mice. Results are shown for the Char10 region (56.1-60.4Mb) only...... 114 Table 4.2 RNA sequencing analysis. Spleen RNA from CBA/Pk, Char10C and CBA/N was obtained and RNA from 5 mice per group were pooled...... 116
xiv ACKNOWLEDGEMENTS
First, I would like to express my sincere gratitude to my supervisor Dr. Philippe
Gros for his guidance throughout my PhD. Merci pour ta patience, pour ton intelligence. Merci pour ton précieux support, tant sur le plan scientifique que sur le plan humain. Thank you to Gundula Min-Oo for passing on this exciting project. I am extremely indebted to Dr. Mary Stevenson and to Mifong Tam. Thank you Mary for your constructive inputs in my project during all these years. Mifong, you taught me nearly all the technics I have used and were always here to help. My PhD wouldn’t have been the same without you. I would also like to thank the rest of my research advisory committee: Dr. Anny Fortin and Dr. Jörg Fritz for their insightful comments.
Thank you to Susan Gauthier for your help with the mice. Merci à Normand Groulx de nous faciliter la vie au quotidien. Merci pour ton éternelle bonne humeur et pour ton empathie. Thank you to all current and past members of the Gros Lab for the helpful advices, protocols, discussions and laughs. Merci à David pour ton expertise en bio- informatique. Merci à Silayuv, Pierre et Julie pour votre précieuse amitié. Merci à
Hervé pour ton soutien inconditionnel ces 2 dernières années. Merci à sa maman de m’avoir chouchouté pendant que je terminais d’écrire cet été. And thank you to the funding agencies. I was generously supported by the CIHR (Frederick Banting and
Charles Best Scholarship) at the Master’s level, and by the FRSQ and the CIHR
(Canada Graduate Scholarship) at the doctorate level. I also received two Principal’s
Fellowship from McGill University.
xv RATIONALE AND OBJECTIVES
Malaria is a global health problem with half of the world population living at risk of transmission. It also affects dramatically the wealth of individuals and nations.
Although mortality rates have fallen by 60% in the last 15 years, this progress is threatened by the lack of an efficient vaccine and by the emergence of resistance to anti-malarial drugs and insecticides1,2. The genetic basis of malaria is well established. Several major genes effects have been shown to modulate susceptibility to malaria in humans. In mice, ten Chabaudi resistance (Char) loci have been mapped. Our lab successfully identified two genes: Pklr and Vnn3 as key regulator of parasitemia and survival to blood-stage malaria3,4. Those discoveries have been made possible because inbred strains of mice vary in their susceptibility to P. chabaudi parasites. However, most of these Char loci have been found because of differences between susceptible A/J and resistant C57BL/6 mice and a large survey listing responses of other inbred strains to P. chabaudi malaria was lacking at the time I started my project.
Therefore, the objectives of the work presented in Chapter 2 were to a) phenotype a set of 25 phylogenetically distant inbred mouse strains for survival and parasitemia at the peak of infection, and b) uncover novel host genetic factors controlling susceptibility to P. chabaudi chabaudi AS through a linkage analysis approach in a F2 intercross derived from a newly identified susceptible strain: SM/J and resistant C57BL/6.
xvi In chapter 3 and 4, we sought to characterize another locus: Char10 that was previously mapped in F2 animals derived from parental CBA/Pk and AcB62. To dissect the genetic basis of Char10, we created 4 congenic lines carrying different portions of the Char10 interval on a fixed CBA/Pk background. Phenotyping of these lines allowed us to considerably reduce the size of the Char10 region. We then prioritized candidate genes using an exome sequencing approach. Additional studies were performed to phenotypically characterize Char10.
Overall, the objective of this thesis was to dissect genetic factors controlling susceptibility or resistance to P. chabaudi infection in mice and hopefully contribute to better understand the pathogenesis of malaria.
xvii Chapter 1 : Introduction and literature review 1.1 INTRODUCTION: HISTORICAL PERSPECTIVES AND PREVALENCE OF MALARIA
Malaria is an ancient disease, which has been documented throughout history.
Symptoms resembling malaria have been reported for almost 5000 years. In China, the Nei Ching (The Canon of Medicine), in 2700 B.C., contains references to tertian and quartan fevers, splenomegaly, headache and chills5,6. In India, writings from the
Vedic and the Brahmanic periods (3500 to 1900 years ago) describe autumnal fevers and spleen enlargement5,6. In Egypt, not only fevers and enlarged spleen were noted in texts dating back from 3500 to 4000 years ago5 but also immunological studies performed in 1994 by Miller et al. on mummies ranging from 5200 to 1450 years old detected malaria antigen in their skin, muscle, brain and lung7. More recently, Nerlich et al. identified P. falciparum DNA in Egyptian mummy bone samples and skeletons from ~4000 years ago, proving again that P. falciparum malaria was occurring in ancient Egypt8. Later in Greece, literary evidence of malaria episodes was given by
Hippocrates (460-370 B.C.) in his Book of Epidemics6. A condition described as
“Roman fever” was reported in Italy in 200 B.C. in the marshes near Rome, and was given the name mal’aria, which means bad air, as it was believed that swamp fumes were causing the illness1,6. Malaria then spread across Europe6. In the New World, there is no record of malaria before the end of the 15th century5,6. It is assumed that
Europeans explorers first introduced Plasmodium parasites in the Americas. But it is really with the slaves imported from Africa, starting in the middle of the 18th century, that malaria took firm hold across the entire American continent5,6.
2 It is only in 1880 that Charles Louis Alphonse Laveran, a French army surgeon, discovered the malarial parasite in its patient’s blood. He named the parasite Oscillaria malariae and was awarded the Nobel Prize in 1907 for this finding.
A few years later, in 1897, Ronald Ross discovered that mosquitoes transmit malarial parasites1. At the beginning of the 20th century, the economic burden of malaria with the construction of the Panama Canal and the human losses due to the disease in war areas led to the implementation of an integrated program of mosquito control including drainage, brush and grass cutting, oiling, larviciding, prophylactic quinine
(that was discovered back in the 17th century), mosquito screening and adult mosquito killing1,9-12. This program resulted in dramatic decrease in malaria death and malaria eradication became the new goal of the Centers for Disease Control and
Prevention (CDC) and of the WHO1,2.
The protozoan parasite causing the disease has coexisted with insects and vertebrates for millions of years5. Historically, episodes of presence or absence of human malaria have been associated with corresponding periods of economic and agricultural depression or prosperity5. Moreover, migration of humans and changes in population size are known to influence parasite demography13. This suggests that the impact of human life style on the parasite development is important.
Today, malaria is a global health problem, with approximately half of the world’s population living at risk of transmission. Since 2000, malaria mortality rates have fallen by 60% due to implementation of insecticide-treated net (ITN) distribution programs, indoor residual spraying (IRS), chemoprevention in pregnant women and
3 infants living in high transmission area. However, in 2015, malaria was still killing one child every minute. It is endemic in 95 countries and causes an estimated 214 million clinical cases each year, with approximately 438 000 deaths, most of which occur among African children1,2. Moreover, there is currently no efficient vaccine against the disease and the tremendous progress of the past decade are threatened by resistance to most recent drugs artemisinins (already reported in Cambodia,
Myanmar, Thailand and Viet Nam) and to pyrethroids (used for ITNs). Therefore, research for malaria is critical and understanding host responses to Plasmodium parasites will help us find new targets for therapeutic intervention.
4
Figure 1.1 Countries with ongoing transmission of malaria, 2013 Reprinted with permission from the World Malaria Report 2014, p2, Copyright © 2014 World Health Organization. [http://www.who.int/malaria/publications/world_malaria_report_2014/wmr- 2014-no-profiles.pdf]
5 1.2. THE PARASITE
1.2.1. The Plasmodium life cycle
Malaria is caused by a protozoan parasite of the genus Plasmodium belonging to the phylum Apicomplexa, characterized by the presence of a specialized apical organellar complex important for host cell invasion14. Its life cycle is complex. It involves an insect vector (the mosquito), which does not suffer from the presence of the parasite, and a vertebrate host. Vertebrate hosts include mammals, birds and reptiles. Female Anopheles mosquitoes transmit parasites that infect humans, monkeys and rodents. Culex and Aedes mosquitoes infect birds. Vector for reptiles are unknown14,15.
Five species of Plasmodium can infect humans: P. falciparum, P. vivax, P. malariae, P. ovale and P. knowlesi. P. falciparum is the parasite responsible for the vast majority of the clinical cases and for nearly all deaths imputable to malaria worldwide2. Although rare, P. knowlesi malaria can also cause life-threatening illness, with severe respiratory disease and anemia16. Deaths from P. vivax have also been reported, although usually seen in patients with co-morbidities (such as malnutrition or HIV co-infection)17.
This section presents the different stages of the Plasmodium life cycle with an emphasis on the erythrocytic stage, which is the most relevant for the purpose of this thesis work.
6
Figure 1.2 The Plasmodium life cycle “(1) Plasmodium-infected Anopheles mosquito bites a human and transmits sporozoites into the bloodstream. (2) Sporozoites migrate through the blood to the liver where they invade hepatocytes and divide to form multinucleated schizonts (preerythrocytic stage). (3) Hypnozoites are a quiescent stage in the liver that exist only in the setting of P. vivax and P. ovale infection. This liver stage does not cause clinical symptoms, but with reactivation and release into the circulation, late onset or relapsed disease can occur up to many months after initial infection. (4) The schizonts rupture and release merozoites into the circulation where they invade red blood cells. Within red cells, merozoites mature from ring forms to trophozoites to multinucleated schizonts (erythrocytic stage). (5) Some merozoites differentiate into male and female gametocytes. These cells are ingested by the Anopheles mosquito and mature in the midgut, where sporozoites develop and migrate to the salivary glands of the mosquito. The mosquito completes the cycle of transmission by biting another host.” Figure and legend reproduced with permission from: Hopkins H. Diagnosis of malaria. In: UpToDate, Post TW (Ed), Uptodate, Waltham, MA, (Accessed on October 25th, 2016), Copyright © 2016 Uptodate Inc. For more information visit www.uptodate.com.
7 1.2.1.1. Pre-erythrocytic stage (PE)
In humans, the pre-erythrocytic stage starts with the bite of an infected female
Anopheles mosquito, which releases a few dozens to a few hundreds sporozoites in the dermis of the host18,19. Most sporozoites enter blood vessels and travel to the liver. Some remain in the skin or in hair follicles. Others are drained by lymphatics and are thought to influence the immune response19-21.
To go from the skin to the liver, the sporozoite has to cross endothelial barriers.
It must traverse the vascular endothelial barrier to enter blood vessels, recognize and arrest in the liver, and pass from the liver sinusoid to the space of Disse through a cell layer composed of fenestrated endothelia and Kupffer cells. It will then traverse several hepatocytes before settling in a final one19,22-24. In this last hepatocyte, the sporozoite will form a protective parasitophorous vacuole and start its development25.
At this point, the parasite will differentiate. It will become round in shape, increase in size and undergo several rounds of asexual divisions forming many thousands of merozoites. Merozoites then emerge from hepatocytes in small membrane-bound vesicules: the merosomes. Merosomes act as shuttles to ensure delivery of merezoites into the blood circulation, protecting them from phagocytosis19,26. The overall process takes between 2 to 15 days depending on the parasite species and does not give rise to any clinical symptoms27.
As previously mentioned, not all sporozoites go to the liver. In mice, around
50% of parasite remain in the skin and 24 hours after a mosquito bite, ~10% are developing in the dermis or in hair follicles. Although frequently abortive, the
8 development of parasites in the skin leads to infective merozoites that can invade erythrocytes. As in the liver, merozoites are released via merosomes20. Sporozoites that are drained by lymphatics will be trapped in the proximal lymph node where most will be degraded by dendritic leucocytes. Some however will be able to develop into exoerythrocytic stages21. In the lymph nodes, sporozoites will start to elicit an immune response. Indeed, dendritic cells, in cutaneous lymph nodes, will prime a first cohort of CD8+Tcells. These activated CD8+T cells will then travel to different organs including the liver where they will recognize antigen on infected hepatocytes and contribute to protection against liver-stage parasite28.
1.2.1.2 Erythrocytic stage
The erythrocytic stage is responsible for all the symptoms of malaria. The length of the cycle depends on Plasmodium species: 48 hours for P. falciparum, P. vivax and P. ovale, 72 hours for P. malariae and 24 hours for P. knowlesi14.
Merozoites (most of them coming from the liver) are 1µm ovoid cells that can only replicate in erythrocytes. Erythrocyte invasion is therefore a key step in the establishment of human malaria. Merozoites must recognize, attach and enter erythrocytes. Recognition occurs through a primary low affinity contact between the parasite and the red cell. This primary attachment is random (i.e. it can occur anywhere on the merozoite surface) and is reversible. This is followed by a reorientation of the parasite in order to juxtapose the apical end of the merozoite with the erythrocyte membrane. The apical organelles, including micronemes, rhoptries
9 and dense granules, are released. Ligands interact with the red cell membrane, inducing the formation of an irreversible junction between the merozoite and the erythrocyte. The so called tight junction or moving junction is passed around the merozoite until it is completely engulfed, leaving the merozoite within a parasitophorous vacuole that isolates the parasite from the host-cell cytoplasm and form an environment favourable for its development29-32. The invasion process is very rapid (1-2 minutes from the release of merozoites), so that the parasite stays only a very limited time extracellularly, accessible to the immune system of the host29,33.
The molecular basis of invasion is complex. Over 50 P. falciparum proteins are thought to be implicated in the invasion process29. For a detailed review, please refer to 34.Of note, MSPs (merozoite surface proteins) play a role in the initial contact phase. PfEBA (P. falciparum erythrocyte binding antigens) and PfRH (P. falciparum reticulocyte binding protein homologues) are involved after initial contact with the erythrocyte has been made. AMA-1 (apical membrane antigen 1) is another important parasite ligand. It is conserved in Apicomplexa and as such is a malaria vaccine candidate.
Within the erythrocyte, each merozoite will mature and divide into 6-32 or more daughter merozoites (asexual reproduction)27. Once the erythrocytic cycle completed, infected red cells burst to release merozoites in the circulation. Each of those will in turn invade an uninfected red cell, yielding to exponential parasite replication.
10 Inside red cell, the parasite derives energy from anaerobic glycolysis, which may contribute to hypoglycaemia and lactic acidosis35. It also uses haemoglobin as a major source of amino acids for the synthesis of its own proteins36. Degradation of haemoglobin releases heme, which is toxic to biological membranes when found in solution. Do detoxify heme, the parasite converts it into hemozoin, an insoluble microcrystalline pigment. The non-toxic insoluble hemozoin is released in the circulation at the same time than the mature merozoites, when the red cell ruptures. It is then taken up by macrophages37.
In erythrocytes, some parasites develop into sexually dimorphic male and female gametocytes. These gametocytes are taken up by the mosquito during the blood meal14.
1.2.1.3 Sexual life cycle
The sexual cycle of Plasmodium parasites occur in the mosquito vector. The male and female gametes fuse in the mosquito gut to form diploid zygotes. The zygotes them transform into mobile ookinetes that will cross the mitgut membranes.
Once at the basal lamina, they will stop and transform into oocysts. Growth and division of oocysts will lead to the production of haploid sporozoites. Once oocysts burst, sporozoites are released and enter the circulatory system of the mosquito, called haemolymph. Sporozoites then travel to the mosquito salivary glands. The cycle of human infection starts again when a mosquito bites and injects sporozoites in the human dermis15.
11 1.2.2 Genetic diversity of Plasmodium falciparum
The interactions between P. falciparum and humans have put a remarkable selective pressure on both species. Genetic variations allow the parasite to counteract the host immune system, overcome chemotherapeutic agents, vaccines and vector control strategies38.
P. falciparum genome from different geographic regions shows important genetic diversity, especially among surface antigens38-40. As we will see later, the parasite expresses proteins such as PfEMP1, RIFIN and STEVOR at the membrane of the infected erythrocyte. However, the presence of such proteins at the surface of the infected red cell makes Plasmodium visible to the immune system. Therefore, variation of these surface antigens is key to virulence and persistence of the parasite in the blood circulation of the host41.
In P. falciparum, the best studied example of genetic diversity is the var gene family encoding PfEMP1 proteins. Around 60 var genes are estimated to be present on the haploid parasite genome but only one var gene is actively transcribed at a time while the others stay in a silent state. Switches controlled epigenetically occur and provide antigenic variation, allowing the parasite to evade host immunity41-46. In addition, continuous diversification and hypervariablility of var genes is achieved through both meiotic and mitotic recombination41. Meiotic recombination takes place during the sexual stage of the parasite life cycle, in the mosquito gut, and can occur between gene copies found on different chromosomes40,47,48. Mitotic recombination arises during the asexual stage of the parasite life cycle. As the parasite undergoes
12 multiple rounds of replication, occasional double strand breaks (DSBs) are formed and repaired through a mechanism of homologous recombination (HR) (as opposed to non-homologous end joining or NHEJ) which utilizes sequences homologous to the one surrounding the break as a template for the repair. This HR mechanism leads to the production of mosaic sequences that increase the diversity of the gene family. It also preserves open reading frame, which is key to keep genes functional. Indeed, if the survival of the parasite in the host depends on the diversification of surface antigens exposed to the immune system, this has to be counterbalanced by the need to preserve function41,49.
Overall, the great genetic diversity of Plasmodium parasites and their evolutionary plasticity constitute major obstacles to malaria elimination.
1.3 MALARIA PATHOPHYSIOLOGY AND IMMUNITY
The clinical spectrum for P. falciparum malaria is quite large. Uncomplicated malaria can be asymptomatic or presents with non-specific symptoms such as fever, chills, malaise, fatigue, diaphoresis, headache, abdominal pain, diarrhea, nausea, vomiting, myalgias, arthralgias50,51. Some people experience life-threatening complications including severe malarial anemia (SMA), cerebral malaria (CM), respiratory distress, multi-organ failure, hypoglycaemia, metabolic acidosis, jaundice50,52,53. Thrombocytopenia, splenomegaly, hepatomegaly can also develop and splenic rupture occasionally occur54-58.
13 In this section, I will review the pathogenesis of malaria, focussing on anemia and on cytoadherence, as those explain the occurrence of SMA and CM, the two main conditions associated with malaria mortality. Il will also give a brief overview of malaria immunity.
1.3.1 Malaria-related anemia
The etiology of anemia in malaria endemic areas is often complex as multiple factors including malnutrition, iron deficiency, host genetics, co-infections may all contribute to the anemia. In this section, I will focus on malaria-related anemia exclusively.
The World Health Organization defines severe malarial anemia (SMA) as Hb concentrations <5.0 g/dL (or haematocrit <15.0%) in children and Hb <7.0g/dl (or Hct
<20%) in adults with parasitemia >10000 parasites/µL and a normocytic film. SMA or malaria-related anemia is caused by A) rupture of parasitized erythrocytes, B) clearance of both infected and non-infected RBCs, C) bone marrow suppression and dyserythropoiesis59,60.
A) Rupture of parasitized erythrocytes. As previously mentioned (section
1.2.1.2), destruction of parasitized RBCs (pRBCs) occurs at schizont rupture, when
RBCs lyse to release mature merozoites in the blood circulation.
B) Clearance of both infected and non-infected RBCs. The reticuloendothelial system is hyperactivated and removes both infected and uninfected RBCs from the
14 circulation. The intraerythrocytic maturation of the parasite is accompanied by morphological and biochemical changes on the red cell membrane that can be recognized by macrophages as a signal for phagocytosis. Those changes include expression by the parasite of proteins at the surface of pRBCs, red cell membrane damage induced by lipid peroxidation, and abnormal distribution of certain phospholipids such as phosphatidylserine61-63. In addition, for each pRBC removed, an estimated 10 uninfected RBCs are cleared by the spleen due to reduced deformability and lipid peroxidation of their membranes. Although the alteration of non-parasitized RBC membranes is not fully understood, it is thought to be an indirect effect of pro-inflammatory cytokines and/or of parasite products such as hemozoin, which is released in the circulation upon erythrocyte rupture and can damage membranes through an oxidative stress mechanism. The removal of uninfected RBCs is an important phenomenon as it can explain the persistence of anemia once parasites have been cleared63-67.
C) Bone marrow suppression and dyserythropoiesis. Generally, haemolytic anemia is compensated by increased production of erythrocytes in the bone marrow.
However, patients with malaria show decreased number of early erythroid progenitors
(BFU-E and CFU-E) and reticulocytes during infection despite high levels of erythropoietin (EPO) in the blood, suggesting that erythropoiesis suppression contributes to the anemia by failing to replenish the pool of RBCs itself reduced because of P. falciparum infection. In addition, dyserythropoiesis (or abnormal
15 development of erythroid precursors) has been noted especially in children with recurrent/chronic P. falciparum anemia.
1.3.2 Cytoadherence and rosetting
Cytoadherence is an important component of P. falciparum malaria pathogenesis. Approximaletely 12-16h post RBC invasion, sticky knobs composed of both parasite-encoded proteins (e.g. PfEMP1, KHARP, PfEMP2, RESA) and human proteins (e.g. spectrin, actin, band 4.1) are formed at the surface of infected erythrocytes59,68-72. These knobs render RBCs adherent to endothelial cells in venules and capillaries as they bind to a number of endothelial receptors (including CD36, thrombospondin, ICAM-1, VCAM, E-selectin or chondroitin sulphate A)73-76. This results in the sequestration of parasitized RBCs in the microvasculature of various organs such as brain, lung, heart, kidney and placenta and may cause organ failure77.
In the brain, this mechanism leads to the development of cerebral malaria, one of the most severe forms of malaria78. This cytoadherence phenomena protects iRBCs from being cleared by the spleen and allows them to stay in the circulation until schizont rupture. But this comes at a cost for the host since blood flow is consequently reduced and sequestered pRBCs may in the most severe cases cause obstruction to tissue perfusion, inflammation and endothelium disruption79. However, most of the time, malaria is uncomplicated and cytoadherence does not lead to pathogenesis80.
Specific forms of PfEMP1 have been associated with severe disease while mutations in endothelial receptor (e.g. CD36) protect against severe malaria77,81-83.
16 In addition, infected RBCs can bind uninfected RBCs, a phenomenon known as rosetting, which is characterized by the aggregation of uninfected RBCs around a central iRBC. This aggregation is mediated by PfEMP1 binding to receptors on the surface of uninfected RBCs. A few rosetting receptors have been identified: complement receptor 1 (CR1), blood group antigens A and B, CD36 and HS-like
GAG. Immunoglobulins and other serum proteins (e.g. fibrinogen and albumin) have also been shown to promote rosetting. Adhesion of iRBCs can also occur to platelets
(clumping). Both rosetting and clumping contribute to malaria pathology by increasing the level of flow obstruction and have been associated with more severe cases of the disease77,84-87.
1.3.3 Immunity
The severity of the disease depends on several factors such as host genetics and immunity, parasite virulence, endemicity levels. In regions where malaria endemicity is stable (or high), severe malaria occurs mostly in children below the age of 5 years, as older people acquire immunity (nearly complete immunity is achieved by early adulthood). The prevalence of anemia is highest in 6 months to 1-year-old infants and most malarial infections in adults are asymptomatic. Where the transmission is lower or seasonal, full protective immunity is not acquired and severe malaria occurs also in adults. Malaria morbidity has been shown to decline with high level of transmission, and in kids, the clinical presentation of the disease changes from severe anemia in very young children in high endemic area to cerebral malaria in older children in region of lower transmission. In addition, travellers who are not
17 immune and who aren’t taking prophylaxis measures may also experience severe malaria50,59,60,88-94.
Immunity to malaria is complex. Host response to malaria is regulated by both innate and adaptive mechanisms. Innate immunity is important early in the infection, especially in naïve hosts. In holoendemic areas, acquired immunity is typically slow to achieve and requires repeated parasite exposure to be maintained. A detailed review of these mechanisms can be found elsewhere50,95,96. The magnitude and the timing of the innate immune response are critical for the control of parasitemia. An appropriate release of pro and anti-inflammatory cytokines, chemokines and other effector molecules will allow to successfully control the parasitemia whereas a hyper-immune or dysregulated inflammatory response can induce damage to the host50,97. In particular, imbalance of inflammatory mediators is a cause of reduced erythropoiesis in children. Of note, TNFα is important for parasite killing, but high levels of TNFα have been associated with malaria mortality98-101. IFNγ is protective during the early stage of malaria infection, but excessive release of IFNγ has been associated with anemia. And over-production of these two pro-inflammatory mediators contributes to dyserythropoiesis and erythrophagocytosis102. IL12 stimulates secretion of TNFα and
IFNγ from mature T and NK cells103,104, and induces proliferation and differentiation of early hematopoietic progenitors105,106. But low IL12 levels are associated with severe malarial anemia107,108. Th1 cytokines need to be counter-regulated by Th2 or anti- inflammatory cytokines to prevent excessive inflammatory activity. This is the case of
IL-10 and TGFβ, which down-regulate the pro-inflammatory response in P. falciparum
18 malaria109. Effector molecules such as NO also play an important role in the pathogenesis of SMA. NO limits parasitemia because of its parasiticidal properties. Its production is stimulated by pro-inflammatory cytokines and downregulated by anti- inflammatory cytokines. But high levels of NO are associated with poor clinical outcome. In addition, parasite products such as hemozoin, glycosylphosphatidylinositols (GPI) and parasitic antigens stimulate the innate immune response. Hemozoin is phagocytosed by monocytes/macrophages and neutrophils, and has been shown to inhibit erythropoiesis in vitro and in vivo110. GPI, conserved glycan structures abundantly expressed on parasites, have been proposed to contribute to malaria pathogenesis through induction of TNFα, other proinflammatory cytokines and nitric oxide111.
Antibody dependent mechanisms are also important for controlling parasitemia and for reducing clinical symptoms. The type of humoral response to malaria has been shown to correlate with the severity of the disease. IgG1, IgG2, IgG3 were found in higher levels in uncomplicated malaria and in individual reporting more than
5 previous clinical attacks, while IgG4, IgE and IgM were predominant in people with complicated malaria and among individuals reporting less than 5 previous attack112. In addition, Mibei et al. showed that IgG4-associated immune complexes (ICs) might be associated with SMA while total IgG ICs and IgE ICs are associated with increased risk of CM113. Overall, these results demonstrate that the pathogenesis of malaria is in part determined by the type of humoral response, and that this response does change with time and exposure.
19 1.4 THE HOST
1.4.1 Malaria’s selective pressure on the human genome
Malaria genetics has been analysed for years and constitutes one of the best- studied examples that clearly show how host genetic factors can contribute to variability in onset, progression, severity and outcome of the disease. The
Plasmodium parasite has coevolved with insects and vertebrates for millions of years, the genome of one influencing the genome of the others. It is now widely accepted that some deleterious polymorphisms have been retained in human because they confer an advantage against malaria in endemic areas. Haldane, in 1949, initially proposed the “malaria hypothesis” where he attributed the persistence of thalassemia alleles in the Mediterranean to their protective nature against malaria114-116. Since then, this hypothesis was confirmed by epidemiological and in vitro studies. It was also extended to several other genes.
1.4.1.1 Erythrocyte polymorphisms
In blood, parasites replicate inside red cells. They invade erythrocytes by attaching to cell surface receptors, express proteins on the cell surface to escape the immune system and degrade haemoglobin for nutritional needs. Genetic variants affecting invasion or replication of Plasmodium parasites as well as numerous haemoglobin variants have been shown to have major impact on the outcome of infection112.
20 1.4.1.1.1 Hemoglobin variants
Normal adult haemoglobin: haemoglobin A is made of two distinct globin chains (α2β2).
Thalassemias are a group of inherited blood diseases. This common human genetic disorder results in the loss or in the decrease of the synthesis of the α or the β globin chain, leading to abnormal haemoglobin and consequently to anemia5,117.
There are two types of thalassemias: the α and the β-thalassemia, where the α or the
β chain are respectively affected118. In the α-thalassemia, two linked genes: HBA1 and HBA2, both located on chromosome 16 are implicated. In homozygous α0- thalassemia, both genes are deleted and no α-globin is therefore synthesized, whereas in the α+-thalassemia, only one pair of gene is inactivated. Consequently, if the homozygous state of the former leads to stillbirth, the one of the later only results in hypochromic anemia119-121. β-thalassemias are due to mutations in the HBB gene located on chromosome 11. Over 200 mutations have been discovered for the β- globin gene and the severity of the disease is highly variable. However, in the homozygous state, the condition is most of the time lethal in the first few years of life121. Heterozygous states are globally healthy with extremely mild anemia119,120.
Thalassemias are found in all part of the world and there is a clear overlap between the global distribution of thalassemias and the malarious region of Africa,
Mediterranean basin and Asia. In these regions, carrier frequencies for thalassemias are high. β-thalassemia frequency can reach up to 20% in some regions. α- thalassemia frequencies have been shown to vary between 5% and 40% in northern
21 India, and 80% of the population of the northern coast of Papua New Guinea is said to be carrier120. As previously mentioned, Haldane in 1949, was the first to propose that a balanced polymorphism was the possible reason for such high frequencies. He attributed the persistence of thalassemias alleles in a heterozygous state to their protective nature against malaria122,123.
The sickle cell disease is due to a mutation in the gene of the β-globin (HBB) where a valine replaces the glutamate at position 6 leading to the production of haemoglobin S (HbS), a protein that causes erythrocytes to deform because HbS precipitates at low oxygen concentration119,124. The homozygous state for HbS is often fatal whereas the heterozygous variants (HbAS) are healthy and are protected against severe forms of malaria. The sickle cell gene is present in many parts of sub-
Saharan Africa, in the Middle East and on the Indian continent where malaria is endemic and its frequency exceeds 30% in some parts of Africa5,120. As for thalassemias, the persistence of HbS alleles, detrimental in the homozygous state, is attributed to its protective effect against malaria125. The mechanism of resistance of
HbS against malaria is complex. The HbAS condition is responsible for a reduced ability of the parasites to invade RBCs and grow due to lower oxygen tensions in
HbAS erythrocytes versus normal erythrocytes126,127. Parasitized RBCs from people having the sickle cell trait tend to sickle faster than non-parasitized cells128,129, and are then more likely to be cleared by the spleen130. In addition, the HbAS condition enhances immunity against malaria131,132. A study done with children in Kenya showed that protection increased from 2% in the first 2 years of life to 56% at 10
22 years old, returning to 30% after that, implying that enhancement of the acquired immunity was involved133. Another study done in Gabon showed that HbAS patients had higher titres of IgG antibodies against PfEMP1 than normal patients134.
Hemoglobin C (HbC) is due to a mutation of the β-globin gene (HBB) where a lysine replaces the glutamate at position 6, at the exact same position as the HbS mutation. HbC is found primarily in West African populations where malaria is common and its allele frequency reaches 0,12 or more135. Compared to HbS homozygous, HbC homozygous are better fit since they only have a mild form of thalassemia5. Moreover, in the HbC case, both the heterozygous and the homozygous show a protective effect against malaria, with a greater protection for the homozygous. The studies that prove the protection of the HbC trait against malaria have been reviewed by Min-Oo and Gros, 2005122.
Hemoglobin E (HbE) is due to a mutation at position 26 of the β-globin gene, where the glutamate is replaced by a lysine5. High frequencies have been reported throughout Southeast Asia, where malaria is endemic. In some region, up to 70% of the population is carrier120. HbE is very benign, and homozygous have generally symptomless anemia119. To date, no epidemiological study assesses the protective effect against P. falciparum malaria. An in vitro study showed that HbAE erythrocytes are less susceptible to P. falciparum invasion, but this effect was not seen in cells with HbEE136. Moreover, a hospital-based study conducted in Thailand, showed that among patients admitted for acute P. falciparum malaria and treated with artemisinin
23 derivatives, the HbE trait was associated with significantly faster parasitic clearance137.
1.4.1.1.2 Other red cell polymorphisms
G6PD deficiency. Mature red blood cells have no mitochondria, so they rely on anerobic metabolism of glucose to produce energy. G6PD is an enzyme catalysing the first step of the hexose monophosphate pathway leading to synthesis of pentose phosphate. It is critical for protecting red cells from super-radicals build-up as it maintains the balance of reduced versus oxidized form of glutathione by catalysing the conversion of NADP to NADPH116,138. G6PD deficiency is the most common enzymopathy in humans, affecting an estimated 400 million people worldwide139.
Over 130 mutations leading to G6PD deficiency have been discovered. The frequency of this disorder is extremely high in region where malaria is endemic
(tropical countries, Middle East). Its adverse effects include haemolytic anemia and neonatal jaundice when erythrocytes undergo oxidative stress caused by drugs, infections or food116,139. It is now well accepted that G6PD deficiency confers resistance to malaria140-142. If early studies yielded conflicting results due to the X- linked nature of the disorder122, Ruwende et al., in two large case-control studies of over 2000 African children, reported that the common African form of G6PD deficiency (G6PD A-) is associated with a 46-58% reduction in risk of severe malaria for both female heterozygotes and male hemizygotes142. The resistance of G6PD deficiency to malaria is due to the inability of the parasite to survive in stressed G6PD deficient erythrocytes116.
24 Duffy. The Duffy antigen receptor for chemokines (DARC) is encoded by the
FY gene on the erythrocyte, and is used by P. vivax to enable invasion of RBCs141.
Absence of its expression has been reported in West and Central Africa where malaria is endemic. It is due to a mutation in the promoter of the gene, leading to a reduced expression of the antigen, which impairs the attachment of the parasite to the cell, conferring a protective effect against P. vivax invasion 143-145. Duffy blood group negativity reaches fixation in some African populations. However, Duffy-independent
P. vivax infections have been reported recently. The mechanism for P. vivax invasion in Duffy negative individuals is not yet understood146-149.
Blood group O. There are growing evidence that the distribution of major ABO blood groups reflects natural selection because of exposure to P. falciparum malaria.
Indeed, P. falciparum was present when ABO polymorphisms arose. Moreover there is clear prevalence of group O coupled with low prevalence of group A in malarious region, whereas group A is predominant in regions where malaria is absent150. A number of studies (reviewed in150) point towards a survival advantage for group O individuals with P. falciparum malaria. Possible mechanisms include reduced rosetting of RBCs as well as reduced P. falciparum invasion151.
Glycophorin C (GYPC) is a receptor for Plasmodium red cell binding antigen
EBA140. Gerbich (Ge) negativity is due to a deletion of exon 3 of the GYPC gene and is found in coastal areas of Papua New Guinea (45% frequency) where malaria is endemic. It has been associated with reduced invasion of RBCs152.
25 Hereditary elliptocytosis. Defects in red cell membrane associated proteins such as α-spectrin, β-spectrin, protein 4.1, band 3 can cause hereditary elliptocytosis
(HE), a common disorder affecting erythrocyte shape. This disorder occurs essentially in African and Mediterranean regions and confers some resistance against malaria153.
Southeast Asian Ovalocytosis (SAO) (a subtype of HE) is a syndrome due to a mutation in the gene encoding the band 3 protein, a membrane protein of the
- - 120,125 erythrocyte known to be a Cl /HCO3 anion exchanger . The homozygous state is in a 100% lethal in utero whereas the heterozygous state protects against malaria, reducing the risk of infection by P. vivax and P. falciparum. This condition occurs in parts of western pacific where malaria is endemic and if high frequencies have been reported in lowlands of New Guinea, a region known to be highly malarious, SAO is absent of non-malarious regions. Therefore, SAO also follows the malaria hypothesis5. Epidemiological studies showed that children heterozygous for the mutation were protected against cerebral malaria154,155. In vitro studies showed that ovalocytic RBCs from Melanesians are resistant to infection by P. falciparum156 and
P. knowlesi157. However, no reduction in parasitemia was observed in carriers120.
1.4.1.1.3 Emphasis on Pyruvate Kinase (PK) deficiency
PK is a key enzyme of the glycolysis pathway. It catalyses its last and rate- limiting step, converting phosphoenolpytuvate (PEP) into pyruvate with the synthesis of ATP. Four isoforms of PK are found in humans (PK-R, PK-L, PK-M1 and PK-
M2)158. PK-R and PK-L (respectively the erythrocyte and the liver isoform) are both
26 transcribed by the same PKLR gene located on human chromosome 1q21 by use of different promoters159,160. PK-M1 and PK-M2 (“muscle” isoforms) are encoded by the
PKM gene on human chromosome 15q22 by alternative splicing. PK-M1 is expressed in skeletal muscle, heart and brain. PK-M2 is the dominant form in early fetal life and remains dominant in leukocytes, platelets, lung, spleen, kidney and adipose tissue161,162. Undifferentiated erythroid precursors express PK-M2 and the isoenzyme switches for PK-R in mature red cells163,164.
PK deficiency with haemolytic anemia is clinically limited to mutations in the
PKLR gene. Erythrocytes lacking mitochondria, they rely exclusively on glycolysis for
ATP synthesis. A PKR deficiency decreases the amount of ATP required by erythrocytes for normal functioning and cell survival, and as a consequence, their life- span is shortened165.
PK deficiency is transmitted as an autosomal recessive trait. Although the condition is asymptomatic in heterozygotes, it can lead to serious haemolytic anemia in homozygotes or in compound heterozygotes. It is the second most common cause of non-spherocytic hereditary haemolytic anemia in humans after G6PD deficiency.
The severity of hemolysis is however highly variable. It ranges from mild or fully compensated anemia to death in utero. Patients may present with palor, jaundice, splenomegaly and iron overload166-169.
Over 180 mutations have been discovered170,171. The prevalence of PK deficiency is not known although estimates have been made in certain populations
27 and for certain mutations. It is thought to have a worldwide distribution and in
European populations, the number of 51 cases per million has been proposed172. In one study, the frequency of the deficient allele has been shown to be 4 times higher in black populations than in Caucasian populations173. Recent PKLR re-sequencing in human populations where malaria is endemic has suggested that the gene may be under selection174.
PK deficiency has been found to protect mice and humans against malaria. In humans, studies have shown that homozygous PK deficient alleles lead to an important reduction of parasite replication as well as increased phagocytosis of infected erythrocytes175. Additional information relative to PK deficiency can be found in chapters 2 and 3.
1.4.1.2 Non erythrocytes genes associated with malaria resistance
Numerous associations between malaria and genes involved in host inflammatory (TNF, NOS2A, IFNG, IFNAR1, IL12B, IL10) or immune responses
(HLA-B53,HLA-DRB1, IL4, TNFSF5, FCGR2A) have been detected. Some have been tested in different populations but results have been highly variable. These variants are reviewed in details in119. Of note, the tumor necrosis factor (TNF) gene is critical for immunity against malaria. Several polymorphisms have been independently reported in the TNF-promoter and have been associated to severe malarial anemia, susceptibility to cerebral malaria or regulation of parasite density.
Moreover, the TNF gene is found in the MHC class III region, itself flanked by the
28 MHC class I and II loci. It has been suggested that the variability observed in the TNF gene could have arisen from variations in the neighbouring regions119.
In addition, polymorphisms in genes encoding for molecules implicated in cytoadherence such as CD36, ICAM1 or PECAM1 have been described in malarious regions but the results of association studies have been conflicting83,119,176,177.
1.5 MOUSE MODELS
The genetic component of malaria susceptibility is complex in humans. There are multiple genes involved, differential susceptibility among individuals as well as environmental factors impacting the disease. Moreover, incomplete penetrance, variable expressivity, diagnostic challenges or differences in parasite virulence make it difficult to map gene effects in humans. Among mammals, the mouse has nevertheless proven being the experimental animal model for genetic studies.
1.5.1 Advantages of the mouse as a model organism
Mice are very similar to humans in terms of genetics, anatomy and physiology.
40% of the mouse sequence can be aligned to the human one. Coding sequences are highly conserved. 90% of the mouse and human genomes can be partitioned in regions of conserved synteny and about 99% of mouse genes have a ortholog in the human genome178. Mice weigh between 25 and 40g and are among the smallest animals among mammals. They have a short generation time and litter size is
29 relatively high (3-10 pups per litter)179. Their lifespan is also greatly accelerated as compared to humans (one mouse year equals about 30 human years). And they are cost-effective animals180. The use of mice in laboratory settings allows researchers to control for parasite strain and virulence, dose, route of infection and other environmental factors. In addition, a large stock of inbred and wild-derived strains of mice are available to researchers allowing them to dissect complex genetic traits181.
Our ability to manipulate the mouse genome makes it extremely useful to model specific diseases for which the causative gene is known. A great amount of information is also available in accessible public databases such as NCBI, Ensembl,
MGI or the UCSC genome browser182-185.
1.5.2 The Plasmodium chabaudi model of infection
Essentially four species of rodent malaria parasites are used in research laboratories: Plasmodium yoelii, Plasmodium berghei, Plasmodium vinckei and
Plasmodium chabaudi. Plasmodium chabaudi is used to model the blood-stage of the disease, which in humans leads to severe malarial anemia and sometimes death. P. chabaudi parasites can be divided into two subspecies: P. chabaudi chabaudi and P. chabaudi adami. P. chabaudi chabaudi was isolated from Central African Republic
(CAR) and many strains exist: 54X, 864VD, AS and 96V. P. chabaudi adami was isolated in the Congo (Brazzaville)186. All the work in this thesis was performed using
P. chabaudi chabaudi AS.
30 Similarities between P. chabaudi and P. falciparum have been reviewed in187.
Similarly to P. falciparum, P. chabaudi chabaudi AS is generally not lethal (although it can be) and can be transmitted by Anopheles mosquitoes187. Like P. falciparum, P. chabaudi invades both normocytes and reticulocytes188. Parasitized RBCs adhere to vascular endothelium and can induce rosetting189-191. However, P. chabaudi does not induce cerebral malaria as it does not sequester in the brain but in the liver. Cerebral malaria can be induced with another parasite: P. berghei. As with P. falciparum, sequestration of iRBC occurs via endothelial receptors such as CD36 and adhesion molecules such as ICAM192. As in humans, malarial anemia in mice infected with P. chabaudi is due to a combination of hemolysis, clearance of uninfected red cells and dyserythropoiesis, which makes it a good model to study the mechanisms underlying severe malarial anemia in humans187,193.
Experimental infection of P. chabaudi in mice starts with the injection of parasitized RBCs either intraperitoneally (i.p.) or intravenously (i.v). The parasite goes directly in the blood circulation and therefore the liver stage is bypassed. In the first few days, very few parasites can be detected in the blood. This is referred as the prepatent phase. Parasites then replicate rapidly between around day 6 and 10 where a peak of parasitemia can be observed. Following the peak, mice either succumb because of severe malarial anemia or are able to clear the parasites by day 21-
28181,194. Note that the length of the different phases may vary depending on the route of infection, the virulence of the parasite or the genetic background of the mouse strain.
31 1.5.3 Identification of the Char loci
Ten Chabaudi resistance (Char1-10) loci have been mapped so far. The Char1 and Char2 loci were identified by Foote et al. in 1997 on chromosome 9 and 8 respectively in F2 crosses between susceptible SJL, C3H/He and resistant C57BL/6 mice195. Our group, in 1997, independently found the chromosome 8 locus in crosses between A/J and C57BL/6196. Char1 and Char2 were shown to control both survival and parasitemia levels195,196. In addition, Ohno et al., in 2001, mapped the Pymr
(Plasmodium yoelii malaria resistance) locus at the same position than Char1. In their study, [(NC/Jic x 129/SvJ) x NC/Jic] mice were challenged with Plasmodium yoelii.
This suggests that Char1/Pymr does not depend on parasite species197. A third locus,
Char3, maps to the mouse major histocompatibility locus, the H2 complex, on chromosome 17. It controls parasite clearance immediately after the peak of parasitemia198. Four weaker gene effects were identified in F11 advanced intercross lines derived from A/J and C57BL/6 parents: Char5 and Char6 on chromosome 5,
Char7 on chromosome 17 (just outside of the H2 region) and Char8 on chromosome
11 (syntenic with human 5q31-q33 resistance locus)199,200. None of the genes responsible for these QTL have been discovered so far.
Our group also identified the Char4 and the Char9 loci. This was done using a set of 36 AcB/BcA recombinant congenic strains derived from resistant C57BL/6 and susceptible A/J parents201. Two of those strains, AcB55 and AcB61 were found to be resistant to P. chabaudi chabaudi AS infection despite carrying A/J susceptible alleles at Char1 and Char2. Resistance in these strains is determined by a two-locus system
32 on chromosome 3 (Char4) and chromosome 10 (Char9). Char4 was shown to be caused by a loss-of-function mutation in the Pklr gene (PklrI90N)202. This mutation causes hemolytic anemia that is associated with compensatory erythropoiesis and reticulocytosis, and has a protective effect against blood-stage malaria203. Char9- associated-susceptibility is caused by a rearrangement in the promoter of the Vanin3 gene (Vnn3) leading to a loss of transcriptional activity4. Vnn3 codes for a pantetheinase, an enzyme that cleaves pantetheine in vitamin B5 and cysteamine.
Mice treated with cysteamine have a reduction in blood parasitemia and an increased survival204. Moreover, cysteamine was shown to potentiate the anti-malarial efficacy of artemisin drugs205.
Finally, our laboratory identified the Char10 locus on chromosome 9. Despite carrying the protective PklrI90N mutation, the AcB62 strain of mice was found to be susceptible to P. chabaudi infection. This suggested the presence of a genetic modifier of the PklrI90N effect in this strain. Linkage analysis in a F2 population derived from AcB62 and CBA/Pk (another Pk deficient strain) identified Char10 as modulating the protective effect of pyruvate kinase deficiency206. This locus will be further characterized in chapters 3 and 4 of this thesis.
33 PREFACE CHAPTER 2
As previously mentioned, malaria constitutes one of the best-studied example showing how host genetic factors modulate severity to the disease. Several genes have been associated with protection against malaria. In mice, ten Char loci have been mapped so far and our lab successfully identified 2 genes: Pklr and Vnn3 that modulate susceptibility to blood-stage malaria in mice3,4. This forward genetic approach is possible because different strains of mice vary in their response intensities to Plasmodium infection. However, most of these Char loci were discovered in F2 populations derived from susceptible A/J and resistant C57BL/6 strains. In order to increase our chances to find new loci and to avoid falling on loci already discovered, we need to generate new crosses. To do so, we first need to determine which strains are susceptible and which are resistant. In this chapter, we surveyed a set of 25 phylogenetically distant inbred strains of mice for survival and parasitemia level at the peak of infection. We generated a F2 intercross between newly identified susceptible SM/J mice and resistant C57BL/6. A combination of linkage analysis and haplotype mapping approach led to the identification of a 0.4Mb region that segregates with resistance/susceptibility to infection.
34 Chapter 2 : Genetic control of susceptibility to infection with Plasmodium chabaudi chabaudi AS in inbred mouse strains
2.1 ABSTRACT
To identify genetic effects modulating the blood stage replication of the malarial parasite, we phenotyped a group of 25 inbred mouse strains for susceptibility to
Plasmodium chabaudi chabaudi AS infection (peak parasitemia, survival). A broad spectrum of responses was observed, with strains such as C57BL/6J being the most resistant (low parasitemia, 100% survival), and strains such as NZW/LacJ and
C3HeB/FeJ being extremely susceptible (very high parasitemia and uniform lethality).
A number of strains showed intermediate phenotypes and gender-specific effects, suggestive of rich genetic diversity in response to malaria in inbred strains. A F2 progeny was generated from SM/J (susceptible) and C57BL/6J (resistant) parental strains, and was phenotyped for susceptibility to P. chabaudi chabaudi AS. A whole- genome scan in these animals identified the Char1 locus (LOD=7.40) on chromosome 9 as a key regulator of parasite density and pointed to a conserved
0.4Mb haplotype at Char1 that segregates with susceptibility/resistance to infection.
In addition, a second locus was detected in [SM/J x C57BL/6J] F2 mice on the X chromosome (LOD=4.26), which was given the temporary designation Char11. These studies identify a conserved role of Char1 in regulating response to malaria in inbred mouse strains, and provide a prioritized 0.4Mb interval for the search of positional candidates. 2.2 INTRODUCTION
Malaria, caused by infection with Plasmodium parasites, is responsible for an estimated 250 million clinical cases and close to 1 million deaths annually. It is endemic in over 100 countries and half of the world’s population lives at risk of developing malaria (http://www.who.int/en). Despite extensive research efforts, the malaria global health problem has been exacerbated by a widespread resistance to anti-malarial drugs in the Plasmodium parasite and to pyrethroid insecticides in the
Anopheles mosquito vector. In addition, attempts to develop an efficacious vaccine remain, so far, unsuccessful207-209.
In regions of endemic disease, host genetic polymorphisms influencing disease incidence and severity have been well documented with strong evidences of selective pressure by the parasite on the human gene pool119,210. The vast majority of these genetic variations affect the erythroid system, an important replication niche for the parasite, and genes encoding key molecules of the innate or adaptive immune processes. For instance, erythrocyte polymorphisms causing sickle cell anemia,
G6PD deficiencies, α and β thalassemias, Duffy negativity and band 3 ovalocytosis have been associated with protection against malaria120. Finally, numerous case- control studies have detected association between onset or severity of cerebral malaria and genes involved in host inflammatory (tumor necrosis factor-α, interleukin-
12 (IL-12), interferon-γ (IFNγ), NOS2A, LTA, IRF-1) and immune (human leukocyte antigen, FCGR2A) responses119,210,211. Parallel family-based genome-wide linkage analyses in nuclear families from Cameroon, Burkina Faso and Senegal have
37 independently detected a strong effect of a cytokine cluster on 5q31-q33, which regulates the level of blood parasitemia212-215. In the Senegalese families, additional genetic effects of chromosomes (Chrs.) 5p and 13q (number of clinical episodes), and
12 (prevalence of asymptomatic infections) were detected216. Also, a genome-wide linkage analysis of “mild malaria phenotypes” in families from rural Ghana detected a major locus on 10p15.3 (PFFE-1) (malaria fever episodes), with additional contributions (suggestive linkages) from Chrs. 13q and 1p36 (blood parasitemia)213.
These studies have shown that the genetic component of susceptibility to malaria in humans is complex. Reduced penetrance, variable expressivity and a wide disease spectrum associated with variations in parasite-encoded virulence determinants, together with variable diagnostic criteria, make it difficult to decipher and map single gene effects in human populations217.
Such complex genetic traits can be dissected in inbred and recombinant strains of mice, where single gene effects have been fixed by inbreeding and can be identified by positional cloning. In mice, blood-stage malaria (merozoite replication in
RBCs) can be studied in the Plasmodium chabaudi chabaudi AS infection model218, whereas cerebral malaria can be induced by infection with P. berghei ANKA219. The symptoms and pathology, including anemia, associated with blood-stage P. chabaudi chabaudi AS infection in mice resemble those associated with Plasmodium falciparum malaria in humans95,220. Inbred strains differ in their degree of susceptibility to blood-stage malaria induced by infection with P. chabaudi chabaudi AS. Resistant strains such as C57BL/6J (B6) show low parasitemia, with moderate anemia and
38 100% survival181. They develop marked splenomegaly, robust erythropoiesis, as well as local proliferation and accumulation of dendritic cells, natural killer cells, macrophages, and T and B-lymphocytes. An early type-1 immune response, dependent on IL-12 and IFNγ, occurs with development of strong immunity to challenge infection95,221. On the other hand, susceptible strains, such as A/J (A), develop a severe disease associated with high parasitemia, severe anemia and with the majority of mice (~75%) succumbing to disease by 9-12 days after infection. In
A/J mice, there is a defect in both splenic erythropoiesis and early type-1, IL-12- and
IFNγ-dependent immune responses. Studies in backcross and F2 mice, as well as in
AXB/BXA recombinant inbred lines, showed that the genetic control of the A versus
B6 inter-strain difference is multigenic181,222. Additional quantitative trait locus (QTL) mapping by whole-genome scan in crosses between A and B6 by our group,196 and between susceptible SJL, C3H/He and resistant B6 by others195,223 mapped two major
Chabaudi resistance loci on Chrs. 9 (Char1) and 8 (Char2) that control peak parasitemia and survival. A third H-2 linked locus on Chr. 17 (Char3, LOD=5.0) regulates parasite clearance immediately after the peak of infection198. Also, four additional weaker gene effects (LOD<2.0) mapping to Chrs. 5 (Char5 and Char6), 17
(Char7, related to Char3), and 11 (Char8, syntenic with human 5q31-q33) were detected in F11 advanced intercross lines (from A and B6 parents) as modulating blood-stage replication.199,200 The genes responsible for these effects have not been identified.
39 We have used a set of 36 AcB/BcA recombinant congenic mouse lines derived from C57BL/6J (resistant) and A/J (susceptible) progenitors to identify novel gene effects that regulate susceptibility to P. chabaudi chabaudi AS.201 We detected two discordant strains (AcB55 and AcB61) that were highly resistant to infection (low parasitemia, 100% survival) despite presence of A/J-derived susceptibility alleles at
Char1 and Char2. Resistance in these strains is determined by a two-locus system
Char4 (Chr. 3), and Char9 (Chr. 10).202 The Char4 protective effect is caused by homozygosity for a mutation (PklrI90N) in the RBC form of pyruvate kinase (Pklr).3,165
We subsequently showed that loss of PKLR function reduces replication of P. falciparum in human erythrocytes ex vivo.175,224 Char9-associated susceptibility to P. chabaudi chabaudi AS infection is caused by a loss of pantetheinase enzyme activity.4 Treatment of mice with the pantetheinase metabolite cysteamine can reduce blood-stage replication of P. chabaudi chabaudi AS and can strongly potentiate the anti-malarial activity of artemisinin-type drugs.204,205 Finally, we identified AcB62 as a discordant strain, being pyruvate kinase-deficient (PklrI90N), but yet susceptible to P. chabaudi chabaudi AS infection (high parasitemia), suggesting the presence of a locus (designated Char10) modifying the protective effect of pyruvate kinase deficiency.206
40 2.3 MATERIALS AND METHODS
2.3.1 Animals
Pathogen-free, 8-10 week-old inbred mice (C57BL/6J, 129S1SvlmJ, FVB/NJ,
DBA/1LacJ, RBF/DnJ, NZB/BINJ, BALB/cJ, DBA/2J, AKR/J, BTBRT+tf/J, CBA/J,
PL/J, BALB/cByJ, A/J, SM/J, KK/HIJ, NOD/LtJ, MRL/MpJ, CAST/EiJ, SJL/J, SWR/J,
C3H/HeJ, NZW/LacJ, NU/J, and C3HeB/FeJ) were obtained from The Jackson
Laboratory (Bar Harbor, ME, USA). Two hundred and one [SM/JxC57BL/6J]F2 progeny were bred by systematic brother-sister mating of [SM/JxC57BL/6J]F1 progenitors. The F1 and F2 mice were bred in-house in the animal care facility of
McGill University. All animal experiments were performed according to the Canadian
Council on Animal Care guidelines and approved by the Animal Care Committee of
McGill University.
2.3.2 Parasite and infection
A lactate dehydrogenase virus-free isolate of P. chabaudi chabaudi AS, originally obtained from Dr. Walliker (University of Edinburgh), was maintained by weekly passage in A/J mice by intraperitoneal infection with 106 parasitized red blood cells (pRBCs) suspended in 1 ml of pyrogen-free saline. Experimental mice were infected intraperitoneally with 106 pRBCs (inbred strain survey) or intravenously with
105 pRBCs (in the following experiments). The percentage of pRBCs was determined daily on thin blood smears stained with Diff-Quick (Dade Behring, Newark, DE, USA)
41 on days 4 to 21 after infection. Survival from infection was monitored twice daily and moribund animals were killed.
2.3.3 Genotyping
Before infection, tail biopsies were obtained from all animals and genomic DNA was isolated by a standard procedure involving proteinase-K treatment201. All 201
[SM/JxC57BL/6]F2 mice were genotyped for a total of 137 SNPs and microsatellite markers. SNP genotyping was performed at the McGill University and Genome
Quebec Innovation Centre (Montreal, QC, Canada) by using the Sequenome iPlex
Gold technology and a custom panel of SNPs distributed across the genome.
Additional microsatellite markers obtained from the Mouse Genome Informatics
Database (www.informatics.jax.org) were genotyped by a standard PCR-based method using (α-32P) dATP labeling and separation on denaturing 6% polyacrylamide gels.
2.3.4 Linkage analysis
All linkage analysis was performed with R/qtl, using peak parasitemia for individual mice as a phenotype. QTL mapping was performed by using an
Expectation-Maximization (EM) algorithm. Genome-wide significance was calculated by permutation testing (1000 and 14297 tests for autosomes and chromosome X, respectively).
42 2.3.5 EMMA scan
The detailed algorithm underlying the efficient mixed-model for association mapping has been published previously.225 The EMMA algorithm is based on the mixed-model association, where a kinship matrix accounting for genetic relatedness between inbred mouse strains is estimated and the n is fitted to the vector of the phenotype, thereby reducing false positive rates. In order to assess significance, the
Bonferroni multiple testing correction226 was computed. EMMA is publically available as an R package implementation.
2.3.6 Flow cytometry
Spleens from C57BL/6J and SM/J mice were harvested at day 7 after infection and single-cell suspensions were prepared after lysis of erythrocytes with NH4Cl
(Sigma-Aldrich, St Louis, MO, USA). Cell viability was always >95% as determined by
Trypan blue exclusion (Invitrogen, Carlsbad, CA, USA). Cells (1x106) were treated with 0.5 µg of anti-CD16/CD32 monoclonal antibodies (eBiosciences Inc., San Diego,
CA, USA) prior to staining with 1 µg of a phycoerythrin-conjugated monoclonal antibody against mouse CD4 (clone GK1.5, rat IgG2b; eBiosciences). As negative control, cells were also stained with an isotype-matched monoclonal antibody. Cells were acquired using a FACSCalibur and data were analyzed by using the CellQuest software (BD Biosciences, Mississauga, ON, Canada) and FlowJo version 9.3.3.
43 2.3.7 Statistical analysis
An unpaired, two-tailed Student’s t-test was used to establish significance of differences in mean parasitemia levels (Figure 2.1b) and in CD4+ cell percentages
(Figure 2.S2) between different groups of mice. A two-tailed Mann-Whitney test was used to establish significance in parasitemia levels between different groups of mice
(Figure 2.2b). Survival of mice was analyzed by a log-rank test and survival fractions were compared using χ2 statistic. These data were analyzed by using the GraphPad
Prism 4.0 statistical software. P-values < 0.05 were considered significant.
2.4 RESULTS
2.4.1 Phenotypic responses of inbred strains to P. chabaudi chabaudi AS infection
To explore the effect of allelic diversity in the laboratory mouse gene pool on response to blood-stage malaria, we surveyed 25 of the 40 Tier 1-3 inbred strains of the Mouse Phenome project227 for susceptibility to blood-stage malaria. These strains were selected to represent the different ancestry of the laboratory mouse
(phylogenetic differences) and maximize the representation and sampling of the allelic pool present in the wild. Between 5 and 20 animals from each inbred strain were challenged intraperitoneally with 106 P. chabaudi chabaudi AS parasitized erythrocytes (pRBCs) and progress of infection was monitored over the course of 3 weeks. In these animals, blood parasitemia was measured daily on thin blood smears and parasitemia at the peak of infection was determined. Survival from infection was
44 also monitored daily. The strains tested, the number of animals tested, the peak parasitemia and the survival rates are summarized in Table 2.1. We observe a variety of responses to P. chabaudi chabaudi AS infection, ranging from resistant to highly susceptible. We also noted a general gender effect on peak parasitemia, which tended to be lower in females than males, and in some of the strains this gender effect was concomitant to differential rates of recovery and survival. Strains such as
SM/J, KK/HIJ, NOD/LtJ, MRL/MpJ, CAST/EiJ, SJL/J, SWR/J, C3H/HeJ, NZW/LacJ,
NU/J and C3HEB/FeJ were found to be highly susceptible, with very high peak parasitemia (> 50%) and uniform lethality in both genders (except for NOD/LtJ, SJL/J and NU/J for which only one gender was tested). A second group of strains showed an intermediate phenotype. A/J, CBA/J, PL/J, and BALB/cByJ showed high parasitemia and significant lethality, but a significant fraction of the mice (up to 60% in some strains) recovered from infection despite high peak parasitemia levels. In addition, strains such as BALB/cJ, DBA/2J, AKR/J and BTBRT+tf/J presented a striking gender effect: all females survived the infection while all males succumbed.
129S1/SvlmJ, FVB/NJ, DBA/1LacJ, RBF/DnJ and NZB/BINJ were all found to be resistant with respect to overall survival (both in males and females), with peak parasitemia levels ranging from 41 (low) to 67% (high). Finally, C57BL/6J was found to be the most resistant inbred strain, with relatively low peak parasitemia values (31-
43%) and uniform survival from infection. These results suggest a rich phenotypic diversity in the response of inbred strains to blood-stage malaria.
45 To explore the genetic basis for inter-strain differences in response to P. chabaudi chabaudi AS, we used the strain distribution pattern (peak parasitemia) and high density single-nucleotide polymorphism (SNP) data sets available for the 25 strains (Mouse HapMap SNP data) to perform whole-genome association mapping.
We used a statistical method EMMA225 that corrects for population structure and genetic relatedness between inbred strains by estimating a kinship matrix. EMMA analysis failed to identify a significant locus that determines the differential susceptibility of inbred strains to blood stage malaria (Figure 2.S1). This suggests a complex and multigenic control of susceptibility to P. chabaudi chabaudi AS in inbred mouse strains.
46 Table 2.1 Phenotypic responses of 25 inbred strains to infection with P. chabaudi chabaudi AS
Strain No. of mice (M,F) Peak Parasitemia (%pRBCs) Survival (%)
Males Females Males Females
C57BL/6J (5,5) 43±4 31±7 100 R 100 R 129S1/SvlmJ (4,4) 56±2 41±4 100 R 100 R FVB/NJ (5,5) 61±5 48±4 80 R 100 R DBA/1LacJ (0,5) ND 48±3 ND 100 R RBF/DnJ (5,0) 56±4 ND 80 R ND NZB/BINJ (5,0) 67±6 ND 80 R ND BALB/cJ (5,5) 51±10 41±6 0 S 100 R DBA/2J (4,4) 58±6 43±3 0 S 100 R AKR/J (5,5) 61±4 51±2 0 S 100 R BTBRT+tf/J (4,4) 72±6 68±4 0 S 100 R CBA/J (5,5) 65±6 57±9 40 I 60 I PL/J (5,0) 49±7 ND 40 I ND BALB/cByJ (4,4) 54±9 69±4 50 I 0 S A/J (10,10) 60±8 52±7 0 S 50 I SM/J (5,5) 62±13 60±7 20 S 20 S KK/HIJ (4,4) 59±4 51±3 0 S 0 S NOD/LtJ (5,0) 63±5 ND 0 S ND MRL/MpJ (5,5) 63±5 61±3 0 S 0 S CAST/EiJ (4,4) 69±3 56±4 0 S 0 S SJL/J (0,5) ND 57±4 ND 0 S SWR/J (5,5) 70±1 70±4 0 S 0 S C3H/HeJ (5,5) 71±5 66±9 0 S 0 S NZW/LacJ (5,5) 72±4 68±5 0 S 0 S NU/J (0,5) ND 73±3 ND 0 S C3HeB/FeJ (5,5) 72±2 70±5 0 S 0 S
Abbreviations: R, resistant; I, intermediate; S, susceptible; ND, not determined; pRBC, parasitized RBC. Twenty five commonly used inbred strains from the Jackson Phenome Database were phenotyped for susceptibility to P. chabaudi chabaudi AS infection. Mice were infected intraperitoneally with 106 pRBCs and parasitemia (expressed as percentage of pRBCs) and survival were assessed daily after infection. Mean peak parasitemia levels are indicated ± s.d. Resistance or susceptibility status was based on overall survival.
47 2.4.2 Genetic analysis of differential susceptibility of C57BL/6J and SM/J mice
We turned to standard QTL mapping to identify genetic effects regulating response to P. chabaudi chabaudi AS in these strains. We arbitrarily selected
C57BL/6J and SM/J as representative resistant and susceptible strains for further genetic analyses. Differential susceptibility in these two strains is associated with differential rates of blood-stage replication of the parasite during the first week infection (Figure 2.1a). At day 8 parasitemia peaks in both strains but is very high in
SM/J (~65%) and much lower in C57BL/6J (~28%) (Figure 2.1b). Subsequently,
C57BL/6J mice recover from infection and clear the parasite, while SM/J succumb from hyper-parasitemia and associated severe malaria-induced anemia by day 10
(Figure 2.1c).
The genetic control of differential susceptibility of the C57BL/6J and SM/J strains to P. chabaudi chabaudi AS, including the number and chromosomal positions of potential regulating loci, was studied by linkage analysis in an informative crosses.
For this, we generated 201 [SM/JxC57BL/6J] informative F2 mice and phenotyped them for susceptibility to P. chabaudi chabaudi AS by using peak parasitemia as a phenotypic measure of susceptibility in individual animals. Control C57BL/6J, SM/J as well as [SM/JxC57BL/6J]F1 and [SM/JxC57BL/6J]F2 animals were infected with P. chabaudi chabaudi AS. Studies in [SM/JxC57BL/6J]F1 mice showed that they were highly resistant to infection: they showed very low parasitemia either lower (33%, males) or equal (28%, females) to that measured in the resistant C57BL/6J controls
(44%, males; 28%, females) with no recorded mortality (Figure 2.2a and 2.2b).
48 †
***
P = 0.0035
Figure 2.1 Differential susceptibility of C57BL/6J and SM/J mice to P. chabaudi chabaudi AS infection Mice were infected intravenously with 105 pRBCs, and daily parasitemia (expressed as percentage of pRBCs) and survival were recorded. (a) Course of infection (blood parasitemia) in C57BL/6J and SM/J mice over a 21-day period. (b) Peak parasitemia levels are shown for strains C57BL/6J and SM/J. Each circle represents one mouse. Statistical significance (two-tailed Student’s t-test; compared with B6) is indicated by asterisks: ***P<0.0001. (c) Kaplan-Meier survival curve. SM/J is represented by a dashed line and C57BL/6J by a solid line. Survival curves were compared by log-rank test and the median survival of SM/J was found to be significantly different from C57BL/6J (P=0.0035).
49 P < 0.0001
***
Males Females
20
15
10
Number of individuals 5
0 -20 -10 0 10 20 30 Sex corrected peak parasitemia Figure 2.2 Segregation analysis of susceptibility of P. chabaudi chabaudi AS infection in [SM/JxC57BL/6J]F1 and F2 mice 17 F1 and 201 F2 animals, as well as parental controls, were infected intravenously with 105 pRBCs and daily parasitemia (expressed as percentage of pRBCs) as well as survival from infection were recorded. (a) Kaplan-Meier survival curve. Survival curves were compared by log-rank test and the median survival of SM/J was found to be significantly different from C57BL/6J (P<0.0001). (b) The peak of parasitemia is shown separately for males and females. Each circle represents one mouse. Statistical significance between F2 males and females (two-tailed Mann-Whitney test) is indicated by asterisks: ***P<0.0001. (c) Distribution of peak parasitemia in the entire F2 population after regression of peak parasitemia levels to a gender-specific mean.
50 This result suggests that susceptibility in SM/J mice is completely recessive. In
[SM/JxC57BL/6J]F2 animals, parasitemia ranged from the very high to very low extremes represented by the parental strains, with 10% of the F2 mice succumbing from infection. Overall parasitemia values were significantly lower in
[SM/JxC57BL/6J]F2 females compared to males (Figure 2.2b). Hence, for genetic analysis in these mice, we regressed the peak parasitemia levels to gender-specific means and transformed the data to a “sex-adjusted peak parasitemia” (Figure 2.2c).
Once corrected for sex, F2 animals show a normal and continuous distribution (Figure
2.2c), amenable to QTL mapping.
2.4.3 Genetic mapping studies in [SM/JxC57BL/6J]F2 mice
All 201 [SM/JxC57BL/6J]F2 mice were genotyped for 137 informative polymorphic markers (SNPs and microsatellites) distributed with an average of 10-
15Mb across the mouse genome. Quantitative trait analysis was performed in R/qtl across all chromosomes, using sex-adjusted peak parasitemia as a quantitative trait.
Genome-wide significance thresholds were determined by empirical permutation testing, consisting of 1000 tests for autosomes and 14297 tests for the X chromosome. This analysis identified a highly significant linkage on Chr. 9 (peak LOD score=7.40, peak marker=rs13480415) and a weaker linkage on Chr. X (peak LOD score=4.37, peak marker=DXMit170) (Figure 2.3a and b). The Bayesian 95% credible interval for the distal Chr. 9 locus was determined to be 101.4-111.4Mb (99% confidence interval= 100.4-112.4Mb) (Figure 2.3b). Strikingly, this region has previously been shown to carry the Char1 locus by Foote et al.195, and shown to
51 control susceptibility to infection with P. chabaudi adami DS in [C3H/HexC57BL/6] and [SJLxC57BL/6]F2 crosses, with C57BL/6 being resistant and C3H/He and SJL being susceptible. Ohno et al.,197 in 2001, mapped, in the same region, a locus they called Pymr in a [(NC/Jic×129/SvJ)×NC/Jic] cross where mice were challenged with
Plasmodium yoelii 17XL, with 129/SvJ being resistant and NC/Jic being susceptible. It is therefore extremely likely that the Chr. 9 locus we detected as influencing susceptibility to P. chabaudi chabaudi AS in [SM/JxC57BL/6J]F2 is in fact Char1.
Allelic combination (Figure 2.3c) indicates that susceptibility alleles at Char1 (peak marker rs13480415) are inherited in a completely recessive manner in male and female mice, consistent with the mode of inheritance detected by analysis of response of [SM/JxC57BL/6J]F1 mice (Figure 2.2a and b). The weaker gene effect on chromosome X (peak marker DXMit170) was given the temporary designation
Char11 (LOD=4.26), and maps to a Bayesian 95% credible interval spanning positions 79-133Mb (Figure 2.3b). SM/J allele(s) at Char11 are associated with lower parasitemia compared to mice carrying the C57BL/6J allele(s) (Figure 2.3c), with the effect being stronger in males.
Overall our results point to Char1 as the major gene effect regulating differential susceptibility to blood-stage malaria in C57BL/6J and SM/J mouse strains.
52 6
4 p=0.05 LOD score
2
0
2 1 6 7 5 8 9 410 113 12 13 14 15 16 171819 X Chromosome
Chromosome 9 Chromosome X 4 p=0.05 6 3
4 p=0.05 2
2 LOD score LOD score 1
0 0 0 20 40 60 80 100 120 0 50 100 150 Map position (Mb) Map position (Mb)
sex 55 F M 50 50
45 45
40 40 Peak parasitemia (%pRBC) Peak parasitemia (%pRBC) AA AB BB AA AB AY BY genotype at rs13480415 genotype at DXMit170
Figure 2.3 Genetic analysis of differential susceptibility to P. chabaudi chabaudi AS infection in resistant C57BL/6J and susceptible SM/J mice Whole-genome analysis was performed in 201 [SM/JxC57BL/6J]F2 mice infected intravenously with 105 pRBCs, using sex-corrected peak parasitemia as a quantitative trait. Interval mapping was performed using the R/qtl software package. (a) Results for all chromosomes are plotted. Significance thresholds revealed by permutation testing (1000 permutations for autosomes and 14297 permutations for the X chromosome) are indicated. (b) Enhanced view of Chr. 9 and X. The vertical lines and hatched area delimit the 1.5-LOD support interval. (c) Effect of Char1 and Char11 alleles at peak marker on peak parasitemia. Males and females are plotted separately in order to reveal any potential sex effect. A and B correspond to SM/J and C57BL/6J alleles, respectively.
53 2.4.4 Haplotype analysis of Char1 in 129/SvJ, C57BL/6J, SM/J, SJL/J, C3H/HeJ and NC/Jic mouse strains
The gene(s) underlying the Char1 effect has not yet been identified, despite much effort. We performed haplotype analysis of the Char1 region (100.4-112.4Mb) in inbred mouse strains that a) had been phenotyped previously for susceptibility to malaria, and b) where high-density SNP maps are available to support this analysis.
In addition, we selected strains in which resistance/susceptibility to P. chabaudi or P. yoelii infection had been linked previously195,197 or here to Char1 alleles. We aimed to identify possible segments of the Char1 region that may segregate with resistance/susceptibility in these strains, and that may facilitate the delineation of a minimal physical interval for Char1. We used two recently available SNP lists. The first consisted of 28 000 SNPs for Chr. 9 only and was obtained from G. Churchill at the Jackson laboratory (personal communication). The second consisted of about 132
000 SNPs for the entire genome and was obtained from the Mouse HapMap project.
Genotypes for these SNPs were available for strains 129/SvJ, C57BL/6J, SM/J, SJL/J and C3H/HeJ, while we generated haplotype information for the NC/Jic by genomic
DNA sequencing. In Figure 2.4, the C57BL/6J and 129/SvJ haplotypes (resistant strains) are fixed in gray, whereas discordant SNPs are labeled in black. We detected a unique bi-allelic haplotype block between positions 108.5 and 108.9 Mb that was common to the two resistant strains (129/SvJ and C57BL/6J) but was different from the susceptible strains (SM/J, SJL/J, C3H/HeJ and NC/Jic). Our findings suggest that the gene responsible for the Char1 effect may be contained within this sub-haplotype.
54 100.4 Mb 112.4 Mb
Char1
NC/Jic le
b C3H/HeJ
SJL/J Suscepti
SM/J
C57BL/6J
Resistant 129x1/SvJ
C57BL/6 allele non-C57BL/6 allele not determined
Figure 2.4 Co-segregation of Char1 haplotypes in 129x1/SvJ, C57BL/6J, SM/J, SJL/J, C3H/HeJ and NC/Jic inbred strains The position of the unique bi-allelic haplotype block common to C57BL/6J and 129/SvJ (resistant strains), but different from SM/J, SJL, C3H/He and NC/Jic (susceptible strains), is shown. SNP-based genotypes for C57BL/6J, 129/SvJ, SM/J, SJL/J and C3H/HeJ were obtained from the Mouse HapMap project. The genotype of NC/Jic for the indicated SNPs was determined by genomic DNA sequencing. C57BL/6J alleles are depicted in gray. Alleles different from C57BL/6J alleles are depicted in black. Inbred strains were segregated into susceptible (S) and resistant (R) strains.
55 2.5 DISCUSSION
To explore the phenotypic diversity of inbred strains of mice for susceptibility to malaria, we surveyed a set of 25 phylogenetically distant inbred strains of mice selected from the Tier 1-3 strains sets from the Mouse Phenome Project.227 These strains were infected with the murine malarial parasite P. chabaudi chabaudi AS and parasitemia was followed daily during infection and survival was monitored. Parasite density at the peak of infection and survival were used to estimate the degree of susceptibility to infection. These experiments produced several observations. First, there is great diversity in response to infection among inbred strains, covering a broad spectrum, ranging from resistant C57BL/6J (low parasitemia, no lethality) to susceptible strains such as SM/J, KK/HIJ, NOD/LtJ, MRL/MpJ, CAST/EiJ, SJL/J,
SWR/J, C3H/HeJ, NZW/LacJ, NU/J, and C3HEB/FeJ (very high parasitemia and associated anemia, high lethality). Second, there was a striking gender effect, which was most visible in strains showing an intermediate level of susceptibility, with females showing a higher degree of resistance (lower parasitemia, increased survival). Such a gender effect had been detected previously in mice, and has been attributed to the major male sex hormone, testosterone. Indeed, administration of testosterone results in increased female susceptibility whereas castration improves outcome in male mice228-230. Third, haplotype association mapping by EMMA analysis failed to detect any single major locus contributing to resistance/susceptibility in the entire cohort of inbred strains phenotyped. This observation together with the broad spectrum of response to infection suggested that the genetic control of susceptibility
56 to blood-stage malaria in mouse is complex, with a plurality of independent loci involved.
To initiate the search for novel loci regulating parasite replication and survival to infection, we selected C57BL/6J as the most resistant strain and SM/J as a susceptible parent, and generated an informative F2 cross. These F2 mice were phenotyped for response to P. chabaudi chabaudi AS and linkage analysis was conducted by a whole-genome scanning approach. This study detected a major genetic effect on Chr. 9, which colocalizes with the known Char1 locus195. Char1 was previously mapped by Foote et al.195 as regulating susceptibility to blood-stage malaria (parasite density, survival) in two independent [C3H/HexC57BL/6] and
[SJLxC57BL/6]F2 crosses (LOD=9.1 and 6.6), where mice were challenged with P. chabaudi adami DS. Ohno et al.197 mapped, in the same region, the Pymr locus, which determines susceptibility of [(NC/Jic×129/SvJ)×NC/Jic] backcross mice to infection with P. yoelii 17XL. Together, these results indicate that the Char1 locus is a major regulator of response to infection with different malarial parasites in unrelated inbred strains. Our linkage studies in [SM/JxC57BL/6J]F2 provided a 95% Bayesian credible interval of 101.4-111.4Mb (LOD=7.41; P-value<0.01). In an effort to further reduce the size of the Char1 interval, we conducted haplotype analysis in six inbred strains for which the malaria susceptibility phenotype had been established and had been demonstrated to be regulated by Char1 alleles in informative crosses. This analysis showed a lack of haplotype association except for a small region overlapping positions 108.5Mb-108.9Mb. This segment shows the same haplotype for resistant
57 C57BL/6J and 129/SvJ mice, while showing the same and opposite haplotype for susceptible SM/J, SJL/J, C3H/HeJ and NC/Jic strains. Although this haplotype association has low power, it nevertheless suggests that the 13 genes contained within this region (Table 2.S1) should be prioritized for the search of positional candidates for the Char1 effect.
Early response to P. chabaudi chabaudi AS infection involves a robust Th1 polarization of the immune response mediated by IL-12 and IFNγ production by mononuclear phagocytes and T-lymphocytes/natural killer cells, respectively, and mice lacking IFNγ, IL12p40 or CD4+ T cells are susceptible to P. chabaudi chabaudi
AS infection95,221. Interestingly, susceptible SM/J mice were found to have significantly lower numbers of CD4+ T cells in the spleen than resistant C57BL/6J mice (Figure 2.S2), suggesting that the gene(s) underlying Char1 could be immune- related. STAT1 is a signal transducer and activator of transcription that mediates signaling by IFNs. In response to IFNγ, STAT1 is tyrosine and serine-phosphorylated.
It then forms a homodimer called IFNγ-activated factor, migrates into the nucleus and binds to an IFNγ-activated sequence to drive the expression of target genes.
Recently, Robertson et al.231 used chromatin immunoprecipitation and DNA sequencing to map functional STAT1-binding sites (and associated genes), which are induced by IFNγ treatment of human HeLa S3 cells. We investigated the Char1 region for the presence of positional candidates that may be bound to STAT1 in response to
IFNγ. We found that there is a cluster of genes containing STAT1-binding site(s) in the large Char1 interval. More interestingly, nearly all of the 13 genes found in the
58 small haplotype block (108.5-108.9Mb) contain STAT1-binding site(s) (Table 2.S1).
This suggests that genes in this 0.4-Mb block have an important role in regulating response to infection through IFNγ-dependent pathways. Additional experiments will be needed to test this hypothesis.
2.6 AKNOWLEDGEMENTS
We thank Dr. Molly Bogue, Director of the Mouse Phenome Project at the
Jackson Laboratory, for providing mice and Dr. Gary Churchill at the Jackson
Laboratory for sharing a list of 28 000 SNPs from Chr. 9. We also thank Dr. Tamio
Ohno at Nagoya University for providing DNA from NC/Jic mice, and further acknowledge Susan Gauthier for breeding and maintaining the mice. This work was supported by a CIHR Team Grant in Malaria (CTP 79842) and operating grant MOP-
79343 (PG), FRSQ (AL) and CIHR (GM-O, AL) studentships.
2.7 SUPPLEMENTARY INFORMATION
Supplementary information follows.
59
Figure 2.S1 Genome-wide association mapping using EMMA Using the R package implementation of EMMA, genome-wide association mapping was conducted across 25 inbred mouse strains. We obtained genotype data consisting of 132 000 SNPs from the Mouse HapMap project. These were then correlated with the peak parasitemia levels as the phenotypic data and consequently, the analysis yielded –log10 transformed P values indicating association significance for each SNP genome-wide. Standardized threshold was set at P value 1.0x10-5 (solid line) and the Bonferroni multiple testing correction threshold was calculated to be at P value 3.79x10-7 (dashed line).
60 ***
Figure 2.S2 Percentage of CD4+ cells in the spleen of C57BL/6J and SM/J mice C57BL/6J (n=6) and SM/J (n=7) mice were infected i.v. with 105 P. chabaudi- parasitized RBCs. Mice were sacrificed at day 7 post-infection, and spleen cells were analyzed by FACS for CD4+ T cells in. Each circle represents one mouse. Statistical significance (two-tailed Student’s t-test) is indicated by asterisks: ***P<0.0001.
61 Table 2.S1 Genes in the Char1 region containing IFNγ-inducible STAT-1 binding site(s) This list is based on the study of Robertson et al231. The small haplotype block (108.5-108.9Mb) is highlighted in gray
Gene name Gene ID Chr. strand txStart txEnd IFNγ-inducible STAT-1 binding site(s) Nmnat3 NM_144533 chr9 + 98105934 98220778 + Rbp1 NM_011254 chr9 + 98232312 98255900 Rbp2 NM_009034 chr9 + 98299904 98319089 4930579K19Rik NR_029444 chr9 - 98371811 98372963 + Copb2 NM_015827 chr9 + 98373082 98397727 + Mrps22 NM_025485 chr9 - 98398090 98411011 + 2410012M07Rik AK010476 chr9 + 98674140 98675932 7420426K07Rik NM_001033983 chr9 + 98712470 98713974 Foxl2os AK143359 chr9 - 98759132 98764651 Faim BC079662 chr9 + 98801467 98811370 Pik3cb NM_029094 chr9 - 98847753 98949439 + Cep70 BC050819 chr9 + 99052827 99109753 + Mras BC024389 chr9 - 99197331 99235248 + Esyt3 NM_177775 chr9 - 99210386 99258949 + 1600029I14Rik AK005560 chr9 + 99279798 99284103 Armc8 NM_028768 chr9 - 99289446 99378251 + Dbr1 NM_031403 chr9 + 99385150 99393695 + Dzip1l NM_028258 chr9 + 99438946 99478607 + Cldn18 NM_019815 chr9 - 99500150 99519367 Sox14 BC100555 chr9 - 99683463 99685522 Il20rb NM_001033543 chr9 - 100267072 100276227 + Nck1 NM_010878 chr9 - 100304355 100355405 + Stag1 NM_009282 chr9 + 100452974 100767894 + Pccb NM_025835 chr9 - 100791389 100844227 + Ppp2r3a BC031532 chr9 - 100963037 101001751 + Ephb1 NM_173447 chr9 - 101778391 102210896 + Ky NM_024291 chr9 + 102362400 102402206 Cep63 BC048718 chr9 - 102442948 102463661 + Anapc13 NM_181394 chr9 + 102485574 102490054 + Amotl2 BC027824 chr9 + 102578229 102591567 + Gm5627 NM_001034892 chr9 + 102597797 102614835 + Ryk NM_013649 chr9 + 102693138 102765678 + Slco2a1 NM_033314 chr9 + 102866769 102944918 + Rab6b NM_173781 chr9 + 102970223 103043419 + Srprb NM_009275 chr9 - 103046182 103060215 + Trf NM_133977 chr9 - 103067026 103088436 1300017J02Rik NM_027918 chr9 - 103108679 103146447 Topbp1 NM_176979 chr9 + 103163476 103208575 + Cdv3 NM_175565 chr9 - 103211257 103223688 + Bfsp2 NM_001002896 chr9 - 103283074 103338478 + Tmem108 NM_178638 chr9 - 103342588 103619967 Nphp3 NM_028721 chr9 + 103860948 103901892 Uba5 NM_025692 chr9 - 103905859 103921464 + Acad11 NM_175324 chr9 + 103922047 103985991 + Ccrl1 NM_145700 chr9 - 103956488 103985278 + Dnajc13 NM_001163026 chr9 - 104053962 104089987 + Acpp NM_019807 chr9 - 104157344 104196067 + Cpne4 NM_028719 chr9 + 104427887 104892642 + Mrpl3 NM_053159 chr9 + 104911369 104935574 + Nudt16 BC064048 chr9 - 104987772 104989892 1700080E11Rik NM_028562 chr9 - 105001443 105003182 Nek11 NM_172461 chr9 - 105020566 105253343 + Aste1 NM_025651 chr9 + 105253621 105263561
62 Gene name Gene ID Chr. strand txStart txEnd IFNγ-inducible STAT-1 binding site(s) Atp2c1 NM_175025 chr9 - 105269461 105353199 + Col6a6 NM_172927 chr9 - 105632211 105667748 + Glyctk NM_174846 chr9 - 106010958 106016200 Wdr82 AK037620 chr9 + 106029028 106049222 + Ppm1m NM_198931 chr9 - 106053053 106057040 Twf2 NM_011876 chr9 + 106061208 106073486 + Tlr9 NM_031178 chr9 + 106080698 106084977 + Alas1 NM_020559 chr9 - 106092030 106105957 + Wdr51a NM_027354 chr9 + 106139501 106207977 + Dusp7 NM_153459 chr9 + 106226732 106233822 Rpl29 NM_009082 chr9 + 106287639 106289668 + Acy1 NM_025371 chr9 - 106291096 106296337 + Abhd14a NM_145919 chr9 - 106298159 106305737 + Abhd14b NM_029631 chr9 + 106306761 106311016 + Parp3 NM_145619 chr9 - 106328453 106334752 + Rrp9 NM_145620 chr9 + 106335409 106343515 + Iqcf1 BC049769 chr9 + 106358088 106360345 Iqcf5 AK005734 chr9 + 106372673 106374104 Iqcf3 NM_026645 chr9 - 106401489 106419726 Iqcf4 NM_026090 chr9 - 106426419 106429068 Tex264 NM_011573 chr9 - 106516855 106543768 Rad54l2 NM_030730 chr9 - 106550341 106647186 + Vprbp NM_001015507 chr9 + 106680076 106738528 + Rbm15b NM_175402 chr9 - 106742097 106745157 + Manf NM_029103 chr9 - 106746861 106750016 + Dock3 NM_153413 chr9 - 106797711 107134190 + Mapkapk3 NM_178907 chr9 - 107113027 107147978 + Cish NM_009895 chr9 + 107154789 107160062 + Hemk1 NM_133984 chr9 - 107185809 107196396 + 6430571L13Rik NM_175486 chr9 + 107198740 107207784 Cacna2d2 NM_020263 chr9 + 107257712 107387153 Cacna2d2 AK044603 chr9 + 107258164 107385640 Tmem115 NM_019704 chr9 + 107392045 107396757 + Cyb561d2 NM_019720 chr9 - 107397113 107399966 + Tusc4 NM_018879 chr9 + 107400328 107403796 + Zmynd10 NM_053253 chr9 + 107405410 107409420 Rassf1 NM_019713 chr9 + 107412756 107420361 Gm9917 AK044848 chr9 - 107420950 107426516 Tusc2 NM_019742 chr9 + 107421355 107424209 Hyal2 NM_010489 chr9 + 107427263 107430879 + Hyal1 NM_008317 chr9 + 107435062 107438228 + Nat6 NM_019750 chr9 + 107438269 107442148 + Hyal3 NM_178020 chr9 + 107439407 107445458 + Ifrd2 NM_025903 chr9 + 107445818 107451139 + Sema3b NM_009153 chr9 - 107456455 107463503 + Gnai2 NM_008138 chr9 - 107472595 107493430 + Slc38a3 NM_023805 chr9 - 107509256 107525475 Gnat1 NM_008140 chr9 - 107532575 107537693 Sema3f NM_011349 chr9 - 107539602 107568576 + Rbm5 NM_148930 chr9 - 107598601 107629077 + Rbm6 NM_029169 chr9 - 107631665 107730808 + Mon1a NM_028369 chr9 + 107746282 107761226 Mst1r NM_009074 chr9 + 107764989 107778482 + 4921517D21Rik NM_026338 chr9 + 107786569 107790562 Camkv NM_145621 chr9 + 107794025 107807791 Traip NM_011634 chr9 + 107809063 107830369 + Uba7 NM_023738 chr9 + 107833667 107842157 Cdh29 NM_177090 chr9 + 107841158 107853108 6230427J02Rik NM_026597 chr9 - 107842326 107843980 Cdhr4 AK006216 chr9 + 107853863 107857776 Ip6k1 NM_013785 chr9 + 107860748 107906881 +
63 Gene name Gene ID Chr. strand txStart txEnd IFNγ-inducible STAT-1 binding site(s) Gmppb NM_177910 chr9 + 107907409 107909802 + Rnf123 NM_032543 chr9 - 107909940 107935904 + Amigo3 NM_177275 chr9 + 107911259 107913802 Mst1 NM_008243 chr9 + 107938551 107943092 Apeh NM_146226 chr9 - 107943513 107952552 + Bsn NM_007567 chr9 - 107961290 108048359 + Dag1 NM_010017 chr9 - 108064058 108121837 + Nicn1 NM_025449 chr9 + 108148549 108154588 + Amt NM_001013814 chr9 + 108155014 108159689 Tcta NM_133986 chr9 - 108161051 108164044 + Rhoa NM_016802 chr9 + 108164297 108196023 + Usp4 NM_011678 chr9 + 108205962 108250621 + Gpx1 NM_008160 chr9 + 108241605 108242669 + 1700102P08Rik NM_053216 chr9 + 108250928 108255858 BC048562 NM_001004192 chr9 + 108294584 108304186 Klhdc8b NM_030075 chr9 - 108305741 108319684 Ccdc71 NM_133744 chr9 + 108318655 108323647 Lamb2 NM_008483 chr9 + 108338047 108348632 + Usp19 NM_027804 chr9 + 108348850 108359800 + Qars NM_133794 chr9 + 108366176 108374016 Qrich1 NM_175143 chr9 + 108375205 108403437 + Impdh2 NM_011830 chr9 + 108418603 108423667 + Ndufaf3 NM_023247 chr9 - 108423968 108425445 + Dalrd3 NM_026378 chr9 + 108427995 108430874 Wdr6 NM_031392 chr9 - 108430415 108436869 + P4htm NM_028944 chr9 - 108437026 108454937 + Arih2 NM_011790 chr9 - 108460281 108506785 + Mir191 NR_029577 chr9 + 108470650 108470723 + Slc25a20 NM_020520 chr9 + 108519501 108542045 + Prkar2a NM_008924 chr9 + 108549546 108606728 + Ip6k2 NM_029634 chr9 + 108653216 108663555 Nckipsd NM_030729 chr9 + 108665602 108675589 + Celsr3 NM_080437 chr9 + 108683542 108710186 Slc26a6 NM_134420 chr9 + 108756368 108764474 + Uqcrc1 NM_025407 chr9 + 108793552 108806577 + Col7a1 NM_007738 chr9 + 108810681 108841812 + Ucn2 AF331517 chr9 + 108843110 108843965 Pfkfb4 NM_173019 chr9 + 108848900 108889603 + Shisa5 NM_025858 chr9 + 108896032 108915128 + Trex1 NM_011637 chr9 - 108915337 108917129 + Atrip NM_172774 chr9 - 108917154 108931517 + Ccdc72 NM_183250 chr9 - 108935393 108939787 + Ccdc51 NM_025689 chr9 + 108946742 108949898 + Plxnb1 NM_172775 chr9 + 108952997 108977316 Fbxw21 NM_177069 chr9 - 108996859 109019428 Fbxw13 NM_177598 chr9 - 109036632 109053381 Fbxw20 NM_001008428 chr9 - 109074837 109092130 Fbxw14 NM_015793 chr9 - 109128532 109145079 Fbxw28 AK143322 chr9 - 109180292 109197060 Fbxw14 AK135771 chr9 - 109180647 109197059 Fbxw22 BC084593 chr9 - 109235816 109261693 Fbxw16 NM_177070 chr9 - 109289724 109339200 Fbxw19 NM_177703 chr9 - 109335980 109353260 Fbxw15 NM_199036 chr9 - 109410016 109425668 Fbxw24 NM_001013776 chr9 - 109458522 109483454 Fbxw18 NM_001033794 chr9 - 109534139 109560106 Fbxw26 NM_198674 chr9 - 109574971 109603493 Spink8 NM_183136 chr9 + 109674050 109684029 3000002C10Rik AK082178 chr9 - 109685348 109690108 Nme6 NM_018757 chr9 + 109690199 109700367 + Camp AK158005 chr9 - 109704792 109706852
64 Gene name Gene ID Chr. strand txStart txEnd IFNγ-inducible STAT-1 binding site(s) Cdc25a NM_007658 chr9 + 109733365 109751294 + Mtap4 NM_008633 chr9 + 109776635 109929122 + Dhx30 NM_133347 chr9 - 109929496 109960758 + Smarcc1 NM_009211 chr9 + 109977230 110084485 + Cspg5 NM_013884 chr9 + 110090626 110107751 2610002I17Rik BC048732 chr9 + 110150383 110166490 + Scap NM_001001144 chr9 + 110178522 110230112 + 5830462I19Rik AK134160 chr9 - 110217214 110220597 Ngp NM_008694 chr9 + 110265015 110268177 Klhl18 NM_177771 chr9 - 110271093 110321510 + Ptpn23 NM_001081043 chr9 - 110287593 110310714 + Kif9 NM_010628 chr9 + 110321840 110369990 + Setd2 NM_001081340 chr9 + 110435143 110521118 + Nradd NM_026012 chr9 - 110465952 110469209 Ccdc12 NM_028312 chr9 + 110501318 110556370 + Pth1r BC013446 chr9 - 110566957 110591938 + Myl3 NM_010859 chr9 + 110608496 110614610 Prss42 NM_153099 chr9 + 110643000 110648552 Prss44 NM_148940 chr9 + 110658842 110669339 Prss43 NM_199471 chr9 + 110671505 110676318 Prss45 NM_153172 chr9 + 110679403 110686125 Prss46 NM_183103 chr9 + 110689321 110701338 Prss50 NM_146227 chr9 + 110702782 110709442 Tmie NM_146260 chr9 - 110710862 110724899 Als2cl NM_146228 chr9 + 110724989 110745339 Tdgf1 NM_011562 chr9 - 110784418 110790883 Lrrc2 NM_028838 chr9 + 110796360 110828878 Rtp3 NM_153100 chr9 - 110829760 110834529 1700061E17Rik AK131745 chr9 + 110831016 110832620 Ltf NM_008522 chr9 + 110864107 110887582 Ccrl2 NM_017466 chr9 - 110899650 110902086 Lrrfip2 BC014761 chr9 + 110964490 111069036 + Mlh1 NM_026810 chr9 - 111073070 111116378 + Epm2aip1 NM_175266 chr9 + 111116744 111123905 + Trank1 BC086653 chr9 + 111219635 111240590 Dclk3 NM_172928 chr9 + 111283928 111333927 + Stac NM_016853 chr9 - 111406249 111535105 Arpp21 NM_033264 chr9 - 111910147 112032615 Pdcd6ip BC026823 chr9 - 113503169 113556899 + Clasp2 NM_029633 chr9 + 113661283 113767152 + Ubp1 NM_013699 chr9 + 113780349 113825700 + Fbxl2 NM_178624 chr9 - 113825655 113875449 4930520O04Rik BC020150 chr9 + 114217152 114219168 Crtap NM_019922 chr9 - 114223835 114239368 + Glb1 NM_009752 chr9 + 114249816 114323075 + Ccr4 NM_009916 chr9 - 114340322 114345242 Cnot10 NM_153585 chr9 - 114434575 114488772 Dync1li1 NM_146229 chr9 + 114537528 114572473 Cmtm6 NM_026036 chr9 + 114579900 114598041 Cmtm7 NM_133978 chr9 - 114605534 114630527 + Cmtm8 NM_027294 chr9 - 114638042 114692850 Gpd1l NM_175380 chr9 - 114750997 114782525 + Osbpl10 NM_148958 chr9 + 114915976 115080919 + Stt3b NM_024222 chr9 - 115091281 115159119 + Tgfbr2 NM_009371 chr9 - 115936404 116023987 + Rbms3 NM_178660 chr9 - 116426293 117100841 + Azi2 NM_013727 chr9 + 117889389 117912535 + Cmc1 NM_026442 chr9 - 117913792 117998778 +
65 PREFACE TO CHAPTER 3 AND 4
In Chapter 2, we identified a 0.4Mb haplotype block segregating with susceptibility/resistance to infection in the Char1 region. The Char1 interval was at that time still being investigated by the team of S. Foote who had already generated congenic mice to dissect the genetic basis of susceptibility to P. chabaudi adami in
[C3H/HexC57BL/6] and [SJLxC57BL/6]F2 crosses.
In Chapter 3 and 4, we move to another locus: Char10 that our lab had just discovered. We generated 4 congenic lines carrying different portions of the Char10 interval and characterized the region both phenotypically and genetically.
66 Chapter 3 : The Mouse Char10 Locus Regulates Severity of Pyruvate Kinase Deficiency and Susceptibility to Malaria 3.1 ABSTRACT
Pyruvate kinase (PKLR) deficiency protects mice and humans against blood- stage malaria. Although mouse strain AcB62 carries a malaria-protective PklrI90N genetic mutation, it is phenotypically susceptible to blood stage malaria induced by infection with Plasmodium chabaudi AS, suggesting a genetic modifier of the PklrI90N protective effect. Linkage analysis in a F2 cross between AcB62 (PklrI90N) and another
PK deficient strain CBA/Pk (PklrG338D) maps this modifier (designated Char10) to chromosome 9 (LOD=10.8, 95% Bayesian CI=50.7-75Mb). To study the mechanistic basis of the Char10 effect, we generated a congenic line (Char10C = CBA/Pk.AcB62-
Char10) that harbors the Char10 chromosome 9 segment from AcB62 fixed on the genetic background of CBA/Pk. The Char10 effect is shown to be highly penetrant as the Char10C line recapitulates the AcB62 phenotype, displaying high parasitemia following P. chabaudi infection, compared to CBA/Pk. Char10C mice also display a reduction in anemia phenotypes associated with the PklrG338D mutation including decreased splenomegaly, decreased circulating reticulocytes, increased density of mature erythrocytes, increased hematocrit, as well as decreased iron overload in kidney and liver and decreased serum iron. Erythroid lineage analyses indicate that the number of total TER119+ cells as well as the numbers of the different
CD71+/CD44+ erythroblast sub-populations were all found to be lower in Char10C spleen compared to CBA/Pk. Char10C mice also displayed lower number of CFU-E per spleen compared to CBA/Pk. Taken together, these results indicate that the
68 Char10 locus modulates the severity of pyruvate kinase deficiency by regulating erythroid responses in the presence of PK-deficiency associated haemolytic anemia.
69 3.2 INTRODUCTION
Malaria is one of the clearest and best studied examples of an infectious disease which intensity and outcome are strongly influenced by genetic factors of the host119. This includes loss-of-function variants of erythrocyte-specific proteins (so- called hemoglobinopathies), which cause severe and life-threatening disease in the homozygous state, but which heterozygosity exerts a protective effect against blood- stage or cerebral malaria. This is the case of hemoglobin variants associated with sickle cell anemia (HbS), or α and β thalassemias, HbC, HbE, as well as G6PD deficiency, Duffy negativity, and Melanesian ovalocytosis (Band 3 protein)120,122,232. In addition, in the major blood groups, A and B have been found to be associated with a greater risk of severe malaria in some studies, suggesting a protective role of the O blood group233. Finally, genome wide studies, and numerous studies with candidate genes have identified variants in genes involved in host inflammatory (TNFα, IFNγ,
NOS2A, LTA, IRF1) and immune responses (HLA, FCGR2A), and that are associated with malaria severity and/or outcomes119. Finally, these complex genetic effects are further modulated by poorly identified environmental factors, including density of the insect vector populations, virulence determinants of the Plasmodium parasites
(including resistance to anti-malarial drugs), poor nutritional status of the host
(anemia), and co-infection with other accidental or endemic bacterial or helminth pathogens50,234.
Genetic studies in mouse models of blood stage (Plasmodium chabaudi AS) and cerebral malaria (Plasmodium berghei ANKA) have proven valuable to identify
70 genetic determinants of susceptibility or resistance to infection4,195-199,201,202,206,223,235-
240. The relevance of these candidate genes to pathogenesis and host response to the human malarial parasite (Plasmodium falciparum) can then be tested in human population studies. A striking example is the Char4 locus, one of the 11 mapped Char loci (Chabaudi resistance), which control susceptibility (parasitemia at the peak of infection, overall survival) to P. chabaudi AS in inbred, recombinant inbred, and recombinant congenic strains of mice. The Char 4 locus was identified as protective against blood stage malaria in strains AcB55 and AcB61. These two strains are derived from the highly susceptible A/J parental strain and harbor susceptibility alleles at the major Char1 and Char2 loci201,202. Char4-determined malaria-resistance in
AcB55 and AcB61 was shown to be caused by homozygosity for a loss-of-function mutation at the Pklr gene (PklrI90N) that encodes the erythrocyte specific pyruvate kinase3. Pyruvate kinase catalyses the last step of glycolysis, converting phosphoenolpyruvate to pyruvate with the generation of one molecule of ATP. PK- deficiency in AcB55/AcB61 causes hemolytic anemia, extramedullary erythropoiesis, reticulocytosis, and protection against infection (low parasitemia, survival) 3,203. The malaria-protective phenotype of PK-defciency was found to be recapitulated in an independent mutant variant (PklrG338D) from the CBA/N-Pkslc strain165.
Pyruvate kinase deficiency is the most frequent abnormality of the glycolytic pathway and is the second most common cause of non-spherocytic hereditary hemolytic anemia in humans. Importantly, studies of human erythrocytes from 3 PK- deficient patients infected ex vivo with P. falciparum showed that homozygosity for
71 PK-deficient alleles causes a dramatic reduction in parasite replication and increased phagocytosis of parasitized erythrocytes. P. falciparum infected erythrocytes from heterozygotes were also more avidly phagocytozed than control infected erythrocytes175. Finally, re-sequencing the PKLR gene in human populations (21 ethnic groups, 6 geographical clusters) from current or ancestral areas of malaria endemicity (Africa, South-East Asia) identified a rich genetic diversity at human
PKLR, and have suggested that the gene may be under selection241,242.
AcB62 is another recombinant congenic strain that carries the malaria- protective PklrI90N mutation. Yet, AcB62 is susceptible to P. chabaudi with high peak parasitemia (~60%) compared to AcB55/61 (~35%) and to C57BL/6J resistant controls (~35%), suggesting the presence of a genetic modifier of the PklrI90N malaria- protective effect in this strain206. A genome scan in PK-deficient [AcB62 X CBA/N-
Pkslc]F2 mice infected with P. chabaudi was conducted using peak parasitemia as a quantitative measure of susceptibility. These F2 mice are informative for mapping this modifier, as they are fixed for PK deficiency, although the CBA/N-Pkslc allele
(PklrG338D) is more severe than the PklrI90N allele of AcB62165. Linkage analysis identified a major locus on chr 9 controlling parasitemia in infected animals, that we designated Char10 (LOD = 10.8; 95% confidence interval 51.3Mb-68.3Mb). There was an additional effect on chr 3 (LOD = 3.8; near Pklr), due to Pklr mutant alleles of different severity segregating in this cross165,206.Hence the Char10 locus is a modifier of the malaria-protective effective effect of PK-deficiency.
72 In this study, we have studied the mechanism by which the Char10 locus modulates the penetrance and expressivity of pyruvate kinase deficiency in the
AcB62 mouse strain.
3.3 MATERIALS AND METHODS
3.3.1 Mice
A/J and C57BL/6J mice were purchased from the Jackson Laboratory (Bar
Harbor, ME, USA). The AcB recombinant congenic strain AcB62 was generated according to a breeding scheme of Demant and Hart243 and has been described previously201. CBA/Pkslc (CBA/Pk) mice were provided by the Japan SLC Animal
Facility (Mr H Asai). Char10C congenic mice were generated from CBA/Pkslc
(background strain) and AcB62 (donor strain) using marker-assisted backcrossing
(Fig 3.1A). All strains were maintained under pathogen-free conditions in the animal facility of McGill University and handled according to the guidelines and regulations of the Canadian Council on Animal Care. Mice experimentation protocol was approved by the McGill Facility Animal Care Committee (P. Gros, Principal Investigator; protocol number: 5287), and includes procedures to minimize distress and improve welfare.
73
Figure 3.1 Construction and Phenotyping of the Char10C congenic line. (A) Physical delineation of the chromosome 9 (Char10) segment from the AcB62 strain backcrossed onto the genetic background of the CBA/Pk strain. The LOD trace was adapted from Min-Oo et al. 2010206. The schematic representation of the recombinant chromosome 9 is shown below for the Char10C congenic line and for parental CBA/Pk and AcB62. The positions of informative markers used for genotyping and the length of the chromosome 9 transferred are given in megabases and are drawn to scale. (B) Course of Plasmodium chabaudi AS infection (blood parasitemia) in CBA/Pk, AcB62 and Char10C mice over a period of 20 days. Five to eleven animals per group were profiled. (C) Peak parasitemia levels are shown for strains CBA/Pk, AcB62 and Char10C. Each dot represents one mouse. Statistical significance (two-tailed Student’s t-test; compared to CBA/Pk) is indicated by stars: *P<0.05.
74 3.3.2 Parasite and infection
A lactate dehydrogenase virus-free isolate of P. chabaudi chabaudi AS, originally obtained from Dr Walliker (University of Edinburgh), was maintained by weekly passage in A/J mice by intraperitoneal infection with 106 parasitized red blood cells (pRBCs) suspended in 1mL of pyrogen-free saline. Experimental mice were infected intravenously with 105 pRBCs and the percentage of pRBCs was determined daily on thin blood smears stained with Diff-Quick (Dade Behring, Newark, DE, USA) on days 4 to 21 after infection. Survival from infection was monitored twice daily, everyday of the experiment, and moribund animals were sacrificed. A monitoring log, placed in the mouse room, was signed by research personnel following each check.
We did not experience any unexpected deaths. Humane endpoints were used during all of our animal survival studies, and in accordance with the McGill University FACC
(Facility Animal Care Committee). At any time, if any of our experimental mice exhibited signs of distress such as weight loss exceeding more than 20% body weight, a body condition score (BCS) < 2, moderate to severe dehydration, decreased mobility, loss of appetite, ruffled fur with loss of grooming behavior, lethargy and or hunched posture, these mice were immediately euthanized (carbon dioxide exposure) following anesthesia with isoflurane.
3.3.3 Hematological parameters
Fresh whole blood was collected in heparinized tubes by cardiac puncture from nine to ten animals per strain. Red blood cell counts, haemoglobin, haematocrit, and
75 Mean Corpuscular Volume (MCV) were determined by the Diagnostic and Research
Support Service of the Animal Resources Centre of McGill University. Reticulocytes counts were performed on methylene-blue-stained thin blood smears; four fields of
100 cells were counted per mouse.
3.3.4 Histology
Spleen, liver and kidney were obtained from CBA/Pk, Char10C and C57BL/6 mice, fixed overnight in 10% formalin (neutral buffered), dehydrated in ethanol/xylene, and embedded in paraffin wax. Histology sections were cut on a microtome at 4 µm and fixed to glass slides. Sections were de-paraffinized in xylene, rehydrated in a series of ethanol baths, and then stained for iron using Perl’s Prussian blue solution, dehydrated in ethanol/xylene, and mounted with Acrytol (Leica Biosystems, Canada).
3.3.5 Iron-related and erythropoietin (EPO) measurements
Iron biochemical determination in spleen, liver and kidney was performed according to the method described by Torrance and Bothwell244. Briefly, iron quantification was done by acid digestion of tissue samples at 65°C for 20h, followed by colorimetric measurement of the absorbance of the iron-bathophenanthroline complex at 535nm. Quantitative measurements of plasma iron, total iron binding capacity (TIBC) and transferrin saturation were performed at the Molecular Diagnostic laboratory of the Jewish General Hospital, Montreal, Canada. Plasma EPO levels
76 were quantified using a sandwich enzyme-linked immunosorbent assay (ELISA)
(R&D Systems, Minneapolis, MN, USA) according to the manufacturer’s guidelines.
3.3.6 Flow cytometry
Spleens and bone marrow were harvested. Single cell suspensions were prepared in PBS supplemented with 2% FBS and 2mM EDTA and filtered through a
40µm cell strainer (BD Biosciences, Mississauga, ON, Canada) to remove cell aggregates. Single cell suspensions were counted manually and viability determined by trypan blue exclusion was always >95%. Cells (1x106) were then incubated with
0.5 µg of anti-CD16/CD32 monoclonal antibodies (eBioscience Inc, San Diego, CA,
USA) prior to staining with the following fluorescence-conjugated antibodies purchased from eBioscience: anti-mouse TER119-PE (clone TER119), anti-mouse
CD71-FITC (clone R17217) and anti-mouse CD44-APC (clone IM7). Non-viable cells were excluded using 7-AAD viability staining solution (eBioscience Inc, San Diego,
CA, USA). Cells were acquired using BD FACSCanto II (BD Biosciences,
Mississauga, ON, Canada) and data were analysed using FlowJo version 9.3.3.
3.3.7 Erythroid colony-forming unit (CFU-E) assays
Single cell suspensions were prepared from CBA/Pk, Char10C and C57BL/6J spleen and bone marrow in IMDM (Life Technologies, ON, Canada) supplemented with 10% FBS and 100U/mL penicillin/streptomycin (Thermo Scientific, UT, USA).
Spleen or bone marrow were harvested from 3 mice per group and pooled. Cells
77 were plated into 1% methylcellulose medium supplemented with 15% FBS, 1% BSA,
10 µg/mL insulin and 200 µg/mL transferrin (M3234, Stem Cell Technologies, BC,
Canada). Various concentrations (0-200 mU/mL) of erythropoietin (R&D Systems,
Minneapolis, MN, USA) as well as 2 mM of L-glutamine (Life Technologies, ON,
Canada) were added to the medium. Cells were plated in 35 mm dishes (Sarstedt,
Montreal, Canada) at a density of 4x104 cells/mL for spleen and 2x104 cells/mL for bone marrow. CFU-E were scored after 2.5 days of culture in a 5% CO2 humidified incubator kept at 37°C.
3.3.8 Biotinylation of RBCs
In vivo biotinylation of erythrocytes was performed as we have described165.
Briefly, the entire RBC population was biotinylated at t = 0 following i.v. injection of
0.1 ml of sulfo-NHS-biotin (Pierce, Rockford, IL) at a concentration of 50 mg/mL and the frequency of biotinylated RBCs in the blood was determined by flow cytometry.
Five microliters of blood was taken from tail vein and diluted in 1 mL of PBS. Cells were counted and approximately 1 × 108 RBCs were stained with 3 µg PE- streptavidin (BD Biosciences, Mississauga, ON) in 0.2 ml PBS for 30 min at 4°C. After washing with PBS, the stained cells were analyzed by FACSCalibur using
CellQuestPro software. The frequency of the biotinylated RBCs in the blood was followed at regular intervals during a period of 30 days.
Adoptive transfer of biotinylated RBC was performed as described previously245. Briefly, blood from CBA/N donor was collected and washed three time
78 in PBS supplemented with 0.1% glucose and was then incubated for 15 min in 0.1 mg/mL biotin-NHS at room temperature. It was then washed once with PBS supplemented with 0.1% glucose and 100mM glycine, and a second time with PBS alone. 1.9x109 RBCs in 0.3 mL were injected i.v in each recipient mouse. The frequency of biotinylated RBCs was analysed during a period of 50 days.
3.3.9 Statistical analysis
Statistical significance between groups was tested by an unpaired, two-tailed
Student t-test. The data were analysed using GraphPad Prism 6.0 statistical software.
P-values <0.05 were considered significant. *P<0.05; **P<0.01; ***P<0.001;
****P<0.0001.
3.4 RESULTS
3.4.1 Creation and Characterization of a Char10 Congenic Mouse Line
Char10 was previously shown to regulate parasitemia levels at the peak of infection in pyruvate kinase deficient [AcB62xCBA/Pk] F2 mice, and was mapped to the proximal portion of chromosome 9206. This cross segregates two Pklr mutations, the PklrI90N allele from AcB62 and the more severe PklrG338D mutation from
CBA/Pk165. This complicates the study of the mechanism of action of the Char10 locus and its effect on the malaria-protective phenotypes imparted by PK-deficiency in these F2 mice. To initiate the identification of the cellular and biochemical pathways underlying the Char10 effect, we used a marker-assisted strategy to construct a
79 congenic line in which the chromosome 9 portion overlapping the Char10 locus from
AcB62 (donor strain) was transferred by serial backcrossing (4 generations) to the genetic background of CBA/Pk. The resulting congenic line, designated Char10C, was genotyped for informative markers on chromosome 9, and was found to be homozygote for an AcB62 chromosome 9 segment spanning from 35.21Mb to
74.88Mb (Fig 3.1A). The Char10C line is also homozygote for CBA/Pk derived
PklrG338D mutant alleles on chromosome 3, as expected. In all subsequent experiments, comparative studies in the Char10C and CBA/Pk lines were performed to gain insight into the function of Char10.
To validate the modulating effect of Char10 on PK-deficiency associated malaria phenotype, we infected AcB62, CBA/Pk and Char10C mice with P. chabaudi chabaudi AS and followed blood parasitemia over time. Char10C mice were found to be susceptible to P. chabaudi chabaudi AS infection, with peak parasitemia levels
(43.5%) resembling those seen in the parental AcB62 (57%), and clearly distinct from those detected in the CBA/Pk mutant (12.48%) (Figs 3.1B and 3.1C). These results demonstrate that the Char10 locus (AcB62-derived alleles) is sufficient to suppress the malaria-protective effect of PK-deficiency (PklrG338D) in CBA/Pk. Furthermore, the
Char10 effect is fully penetrant as the congenic line recapitulates the phenotype of the AcB62 parental line (peak parasitemia).
80 3.4.2 Char10 modulates the extent of the PK deficiency-associated anemia
Protection against blood-stage malaria in PK-deficient AcB55, AcB61 and
CBA/PK has been linked to anemia, and to altered properties of PK-deficient erythrocytes, such as high reticulocytosis and shortened half-life or mature red cells in peripheral blood. In addition, we have observed a quantitative correlation between intensity of anemia phenotypes (reticulocytes) and resistance to malaria (peak parasitemia) in individual [AcB62xCBA/Pk] F2 and [AcB55 x A] F2 mice3,165,203.
Therefore, we investigated the effect of the Char10 locus on the anemia-associated phenotypes characteristic of PK-deficiency, initially by comparing haematological profiles of Char10C and CBA/Pk (Fig 3.2). Char10C mice are significantly less anemic than CBA/Pk mice. They show higher numbers of erythrocytes (6.3 vs 5.1 x
1012/L), higher hematocrit (0.37 vs. 0.33L/L), and lower numbers of circulating reticulocytes (31.1% vs. 42.4%). Char10C mice also have a lower mean corpuscular volume (MCV) of total RBCs, which is probably due to the lower proportion of reticulocytes. Finally, and although tissue section identified intense expansion of the spleen red pulp and associated secondary erythropoiesis in both mouse strains,
Char10C mice show a highly significant reduction in splenomegaly when compared to
CBA/Pk (Fig 3.2F). This initial haematological profiling suggests that the Char10 locus modulates intensity of PK-deficiency in CBA/Pk.
81
Figure 3.2 Comparative hematological profile of the Char10C congenic line. Hematological parameters were obtained in naïve adult mice (>8 weeks old).. Abbreviations: RBCs, red blood cells; MCV, mean corpuscular volume. Each dot represents one mouse. Statistical significance (two-tailed Student’s t-test; compared to CBA/Pk) is indicated by stars: *P<0.05.
82 3.4.3 Char10 modulates the extent of PK-deficiency-induced iron overload in peripheral tissues
Hemolytic anemia in conditions such as PK-deficiency are often accompanied by iron overload in peripheral tissues246,247. We investigated whether Char10 had an effect on iron metabolism at such sites. Staining of tissue sections with Perls’
Prussian blue showed reduced iron in liver and kidney of Char10C mice (but not spleen), when compared to CBA/Pk (Fig 3.3A). In liver, iron deposits appeared mostly in mononuclear phagocytes (Kupffer cells), while in kidney, iron deposits appeared mostly at the apex of epithelial of proximal tubules. Further quantification of iron in organ extracts confirmed results of histochemistry and identified significantly lower iron stores in liver and kidney in Char10C mice compared to CBA/Pk (Figs 3.3B, 3.3C and 3.3D). Char10C mice also showed lower plasma iron levels and lower plasma transferrin saturation than in CBA/Pk mice (Figs 3.4A and 3.4C), while total iron binding capacity (TIBC) was similar in both strains (Fig 3.4B). Erythropoietin (EPO) is critical for erythrocyte production in response to anemia248. We determined that plasma levels of EPO in Char10C mice were about half that of CBA/Pk (Fig 3.4D).
Taken together, iron and EPO measurements in tissue and plasma provide complementary information that Char10 modulates the severity of haemolytic anemia caused by Pklr deficiency.
83
Figure 3.3 Iron determination in peripheral tissues. Spleen, liver and kidney of CBA/Pk, Char10C and C57BL/6 mice were harvested an used for histochemical and biochemical determination of iron content. (A) Histochemical staining of spleen, liver and kidney sections stained with Perl’s Prussian blue. (B) Iron biochemical quantification in spleen, liver and kidney extracts. Each dot represents one mouse. Statistical significance (two-tailed Student’s t-test; compared to CBA/Pk) is indicated by stars: *P<0.05.
84
Figure 3.4 Iron-related measurements in plasma. Comparative analyses of plasma from CBA/Pk vs Char10C mice. (A) Iron total concentration. (B) Total iron-binding capacity. (C) Transferrin saturation. (D) Erythropoietin concentration. Each dot represents one mouse. Statistical significance (two-tailed Student’s t-test; compared to CBA/Pk) is indicated by stars: *P<0.05.
85 3.4.4 Effect of Char10 regulation on metabolism of PK-deficient erythrocytes
Results so far indicate that Char10 alleles impact the severity of anemia phenotypes (erythrocyte and reticulocyte numbers, plasma iron and tissue iron stores) in PK-deficient CBA/Pk and Char10C mice. This could reflect differential fragility of PklrG338D deficient erythrocytes produced in CBA/Pk vs. Char10C congenic mice, perhaps resulting in haemolytic signals of different intensities. Alternatively, this could suggest Char10-regulated hematopoietic responses of different intensities in response to the same PklrG338D associated haemolytic insult. To distinguish between these two possibilities, we determined the half-life of PklrG338D deficient erythrocytes produced in CBA/Pk vs. Char10C congenic mice using an in vivo biotinlylation assay we have previously described165. In this protocol, biotin is injected intravenously, and the disappearance of biotin-labeled erythrocytes is monitored daily by FACS, and erythrocytes half-life is determined (Fig 3.5A). These experiments showed an identical half-life of ~5 days for erythrocytes produced in both mouse lines. The half- life of erythrocytes can also be influenced by the pace at which they are removed from the circulation. Hence, we used a modification of this protocol to assess the capacity of the reticulo-endothelial system (macrophages) of CBA/Pk and Char10C to eliminate normal erythrocytes (from wild type PK-sufficient CBA/N) labelled ex vivo with biotin and injected back in both mouse strains (Fig 3.4B and 3.4C). These experiments showed that CBA/Pk and Char10C mice could eliminate normal RBCs at the same rate. Hence the Char10 locus does not modulate erythrocytes half-life either directly, or through differential rates of removal by the reticuloendothelial system.
86
Figure 3.5 Effect of Char10 on turnover of biotinylated erythrocytes. (A) Turnover of in vivo biotinylated erythrocytes from CBA/Pk and Char10C mice, as determined by flow cytometry (B) Turnover of ex vivo biotinylated control CBA/N erythrocytes following adoptive transfer into CBA/Pk and into Char10C mice, and as measured by flow cytometry over a period of 50 days. (C) Enlargement of the linear portion of the graph shown in panel B.
87 3.4.5 Char10 regulation of erythropoiesis in PK-deficient mice
We investigated a possible effect of Char10 alleles on erythroid response to haemolytic anemia. For this, we used FACS analysis to distinguish and to quantify the different populations of maturing erythroblasts from spleen, the major site of ertyhropoiesis in PK-deficient mice. In these studies, TER119 was used as a general marker of the erythroid lineage and CD71 (transferrin receptor; data not shown) and
CD44 (hyaluronic acid receptor) as maturation markers for the erythroid lineage. The expression of CD71 and CD44 in TER119+ erythroblasts decreases with maturation, and when combined with analysis of cell size, this previously described strategy249,250 permits the identification of four erythroblast maturation stages (Figs 3.6A and 3.6B).
The number of total TER119+ cells, as well as the numbers of the different erythroblast sub-populations (labelled I to IV) were all found to be lower in Char10C spleen compared to CBA/Pk controls (Figs 3.6C and 3.6D). This is consistent with the higher splenomegaly of CBA/Pk compared to Char10C, and strongly suggests increased erythropoiesis in the former CBA/Pk compared to Char10C. Interestingly, we noted that the relative percentage of TER119+ cells in the spleen, or the respective percentage of each erythroblast sub-populations was similar in CBA/Pk and Char10C (Figs 3.6E and 3.6F).
To determine whether the Char10 effect on both the splenic TER119+ erythroid cell populations and circulating reticulocytes may be linked to altered maturation of early erythroid progenitors, we measured the potential of splenic cells from both strains to form CFU-E in vitro in response to EPO. Dose-response experiments
88 suggested that 10U/mL EPO was sub-optimal and non-saturating, and was selected for our assay conditions (Fig 3.7A). The total number of CFU-E per spleen was found to be lower in Char10C than in CBA/Pk (Fig 3.7B). This result suggests more robust erythropoiesis in CBA/Pk than in Char10C mice, in agreement with the higher number of TER119+ erythroid precursors detected in the spleen of these mice by FACS analysis (Fig 3.6). On the other hand, the relative frequency of CFU-E formed per
4x104 cells plated was found to be the same in the two strains (Fig 3.7C).
Taken together, these results strongly suggest that the Char10 locus differentially modulates erythroid response to the same PK-deficiency haemolytic stimulus. The Char10 effect appears to be at the level of global erythroid response as opposed to the intrinsic ability of erythroid precursors to fully differentiate into erythrocytes.
89
Figure 3.6 Flow cytometric analysis of the spleen erythroid compartment. (A) Single spleen cells suspensions from CBA/Pk and Char10C mice were labelled with antibodies against TER119 and CD44. (B) Distribution of CD44+ populations versus FSC of TER119+ gated cells was used to identify 4 sub-populations of erythroblasts (I to IV) as described 250. The total number of Ter119+ erythroblasts (C) and of the 4 sub-populations of erythroblasts (D) is shown. (F) Erythroblasts expressed as percentage of TER119+ cells. Each dot represents one mouse, and all experiments were done in triplicate. Statistical significance (two-tailed Student’s t-test; compared to CBA/Pk) is indicated by stars: *P<0.05.
90
Figure 3.7 Enumeration of CFU-E progenitors in spleens. Spleens of three male CBA/Pk, Char10C and C57BL/6 mice were pooled for analysis. (A) Erythropoietin (EPO) titration was performed on CBA/Pk spleens, and to determine sub-optimal EPO concentrations required to stimulate CFU-E colony formation. Histograms represent the mean of two technical replicates. Erythropoietin titration. (B) Total number of CFU-E per spleen determined following culture in EPO at 10mU/mL (C) Proportion of CFU-E colonies per 4x104 cells plated at 10mU/mL EPO.
91 3.5 DISCUSSION
Erythrocyte senescence in haemolytic anemia such as that encountered in pyruvate kinase deficiency and during Plasmodium infection is associated with decreased ATP levels, heme deposition, and oxidative damage which cause decreased deformability, retention in red pulp splenic sinuses and phagocytosis by residents macrophages251-253. Hemolytic anemia is associated with compensatory erythropoiesis in the spleen (also in liver and bone marrow), with noticeable splenomegaly, increased numbers of TER119+ erythroblasts in these organs, and of circulating reticulocytes. This chronic compensatory erythropoiesis is associated with increased intestinal iron uptake and ultimately, iron overload in peripheral tissues. We showed previously that in mice and humans, PKLR-deficiency is associated with increased resistance to malaria3,175,203. Resistance may be accounted for by a) diminished replication of Plasmodium parasites in the unfavourable environment of reduced ATP content of PK-deficient erythrocytes224, or b) reduced half-life and increased phagocytosis of PK-deficient RBCs, including Plasmodium infected ones175, or c) a combination of both. The malaria-protective effect of PK-deficiency is phenotypically similar to that of inactivation of other erythrocyte proteins (G6PD,
Band-3, DARC), including hemoglobin (sickle cell anemia, thalassemias)122.
In three recombinant congenic strains that share common ancestry (AcB55,
AcB61, AcB62), we identified a severe loss of function in Pklr (PklrI90N) that accounts for the Char4 locus. This locus is associated with protection against P. chabaudi induced blood-stage malaria in AcB55 and AcB613. In AcB61, the protective effect of
92 PklrI90N (Char4) is further modified by the Char9 locus on chromosome 10 which causes increased malaria-susceptibility due to the loss of pantetheinase activity
(Vnn3) and its key metabolic product, cysteamine4,204,205. On the other hand, and despite carrying the PklrI90N mutation, AcB62 mice are susceptible to P. chabaudi infection, and show high parasitemia at the peak of infection with significant mortality206. Mapping studies in an informative F2 cross generated between AcB62
(PklrI90N) and CBA/N-Pkslc (PklrG338D) identified the major genetic modifier of Pklr- associated malaria resistance to be linked to chromosome 9 (Char10; LOD=7.24) with additional effects linked to segregation of functionally distinct mutant pklr alleles mapping to chromosome 3 (LOD=3.7)165,206.
A first aim of our study was to establish the effect of the Char10 locus on the modulation of PK-deficiency associated resistance to blood-stage malaria. For this, we generated a congenic line (Char10C) in which the Char10 alleles of AcB62 were introduced onto genetic background of the CBA/N-Pkslc mouse strain by continuous marker-assisted backcrossing. With respect to reticulocytosis and response to malaria, we observed that the Char10C line recapitulates the phenotype of AcB62, displaying reduced blood reticulocytes at steady state and high parasitemia following
P. chabaudi infection (Fig 3.1). This established that Char10 is the major regulator of both phenotypes, with phenotypic expression being fully penetrant. Hence, comparative analyses in the CBA/N-Pkslc and Char10C strain pairs was used to study the effect of Char10.
93 We observed that, compared to the CBA/N-Pkslc parent, the Char10C mice display a reduction in anemia phenotypes associated with the PklrG338D mutation including decreased splenomegaly, diminished circulating reticulocytes, increased density of mature erythrocytes, increased hematocrit, as well as decreased iron overload in kidney and liver and decreased serum iron and transferrin-bound iron
(Figs 3.2, 3.3 and 3.4). Several possibilities must be considered to explain the role of
Char10 in seemingly regulating penetrance and/or expressivity of the anemia phenotypes associated with Pklr-deficiency. First, Char10 may directly influence the effect of loss of Pklr function on RBC metabolism including fragility. This appears unlikely, as Pklr-deficient erythrocytes have the same half-life in Char10C and in
CBA/N-Pkslc mice (Fig 3.5A), and normal erythrocytes are cleared with similar efficiency by both mouse lines (Figs 3.5B and 3.5C). Second, it is possible that
Char10 affects a sensing mechanism of the host that detects signals of haemolytic anemia, a hypothesis we cannot formally exclude. Thirdly, Char10 could regulate the extent of compensatory erythropoiesis in response to the same haemolytic insult caused by the PklrG338D mutation. This could manifest itself either through cell- autonomous mechanisms affecting the potential of individual erythoblast precursors to mature into erythrocytes, or though modulation of the total number of erythroblasts produced in the global response to haemolytic anemia. The data presented in Figs
3.6 and 3.7 argue against a cell-autonomous effect of Char10 on intrinsic differentiation potential of erythroblasts in vivo and CFU-E colony formation ex vivo.
This is clearly distinct from mutations that affect regulation of pro- or anti-apoptotic response in erythroblasts in response to EPO254. Finally, it is possible that Char10
94 has pleiotropic effects on a combination of the above-mentioned host response pathways. Nevertheless, our results establish Char10 as a critical regulator of erythropoietic response (compensatory erythropoiesis) to haemolytic anemia in pyruvate kinase deficiency.
Identifying the gene and protein underlying the Char10 effect will be of considerable interest, possibly providing new targets for intervention in conditions such as haemolytic anemia. Currently, the Char10 interval stands at >35Mb (size of the congenic segment fixed in Char10C mice) and contains >200 genes; Hence, it is not possible to discuss the implication of potential positional candidates in the phenotype. Nevertheless, it is worth mentioning that Char10 maps to a portion of chromosome 9 that harbors a previously published quantitative trait locus designated
Splq4 and that regulates spleen weight in a large F2 cross between parental strains selected for large differences in body weight255. It is tempting to speculate that the same gene underlies Char10 and Splq4 effects. Irrespective of the molecular basis of the Char10 effect, it will be interesting to determine whether or not Char10 can modulate penetrance and expressivity of other gene mutations that are known to cause defects in erythrocytes function and that protect against malaria, including hemoglobin genes (sickle cell anemia, α/β thalassemias), ankyrin deficiency, G6PD- deficiency and others.
95 3.6 ACKNOWLEDGMENTS
We are indebted to Susan Gauthier for her technical assistance in breeding and maintaining the mice colonies.
3.7 SUPPORTING INFORMATION
Table 3.S1 Blood Cellular Profile of CBA/Pk and Char10C.
96
Figure 3.S1 Numbers of CFU-E progenitors in bone marrow (BM) of CBA/Pk, Char10C and C57BL/6 mice. Femurs of three male mice (one femur per mouse) were pooled for each strain. Erythropoietin titration was performed on CBA/Pk femurs. Histograms represent the mean of two technical replicates. (A) Erythropoietin titration. (B) Total number of CFU- E per femur at 10mU/mL of EPO. (C) Number of CFU-E per 4x104 cells plated at 10mU/mL EPO.
97 Chapter 4 : The Char10 locus: a genetic modifier of the malaria-protective effect of pyruvate kinase deficiency
98 4.1 ABSTRACT
Pyruvate kinase (PKLR) deficiency protects mice and humans against blood- stage malaria. Mouse strains AcB55, AcB61 and AcB62 carry the same malaria- protective PklrI90N mutation, which causes hemolytic anemia with compensatory erythropoiesis and reticulocytosis. However AcB62 is susceptible to malaria (P. chabaudi AS), suggesting a genetic modifier of the PklrI90N protective effect in this strain. Linkage analysis in a F2 cross between AcB62 (PklrI90N) and another PK deficient strain CBA/Pk (PklrG338D), revealed a major locus on chr 9: Char10
(LOD=10.8, 95% Bayesian CI=50.7-75Mb) controlling parasite replication. An additional effect was found on chr 3 and is due to distinct Pklr alleles segregating in this cross. Here we show that the Char10 locus also controls reticulocytosis
(LOD=12.8, 95% Bayesian CI=58-67Mb). To reduce the size of Char10 and to eliminate the confounding effect of the chr 3 locus, we generated 4 congenic lines
(Char10 A1, A2, B and C) in which different Char10 chr 9 segments from AcB62 were transferred onto CBA/Pk by serial backcrossing. Phenotyping of these lines for reticulocyte number and peak parasitemia demonstrated that Char10 is found within a maximal physical interval spanning 56.1-60.4Mb. Exome sequencing in CBA/Pk and
Char10C identified genetic variants in 13 genes while RNA sequencing revealed that
14 genes are differentially expressed between CBA/Pk and Char10C mice.
99 4.2 INTRODUCTION
Malaria continues to be a major health problem with approximately 40% of the world population living at risk. It is endemic in 97 countries and causes an estimated
207 million clinical cases each year with approximately 627 000 deaths affecting mostly sub-Saharan children below the age of five.
The genetic component of malaria is complex due to multiple genes involved, differential susceptibility among individuals and environmental factors. It has been analysed for years and constitute one of the best-studied example that clearly show evidence of selective pressure on the human genome by a pathogen. Many polymorphisms have been shown to protect against malaria in the heterozygous state while being deleterious at the homozygous state. This includes mutations in erythrocyte-specific proteins causing sickle cell anemia, α and β thalassemias, G6PD deficiency, Duffy negativity, Melanesian ovalocytosis, HbC, HbE120,122,232.
Furthermore, in the ABO blood groups, the A haplotype has been associated with a greater risk of severe malaria, suggesting that the O blood group confers protection against the disease233. Finally, polymorphisms in genes involved in host inflammatory
(TNFα, IFNγ, NOS2A, LTA, IRF1) or immune responses (HLA, FCGR2A) have been shown to affect the severity and outcome of malaria119.
Study of genetic control of malaria is complex in humans. Mouse models have proven to be a valuable tool and present several advantages such that environmental factors can be controlled or eliminated. We, and others, have used a mouse model using the rodent parasite Plasmodium chabaudi to identify novel host genetic factors
100 controlling susceptibility/resistance to blood-stage malaria in mice. Studies in inbred or recombinant strains of mice have identified several Chabaudi resistant loci (Char1-
11) that control replication of the parasite at the peak of infection, survival or parasite clearance195,198-200,202,206,223.
In particular, Char4 was identified as being the major locus controlling both parasitemia and reticulocytes levels in informative F2 populations derived from recombinant congenic strains of mice AcB55 and AcB613,202. AcB55 and AcB61 are very resistant to P. chabaudi chabaudi AS infection despite a susceptible A/J background at Char1 and Char2181. Resistance in these strains was shown to be caused by a loss-of-function mutation in the Pklr gene (PklrI90N), which encodes for the erythrocyte specific pyruvate kinase3. A third strain, AcB62, also carries the protective PklrI90N mutation but was found to be susceptible to P. chabaudi chabaudi
AS, suggesting the presence of a genetic modifier of the PklrI90N effect in this strain206.
Pyruvate kinase deficiency is the most frequent abnormality of the glycolytic pathway and is the second most common cause of nonspherocytic hereditary hemolytic anemia in humans after glucose-6-phosphate dehydrogenase (G6PD) deficiency. Pyruvate kinase catalyses the last and rate limiting step of glycolysis, a critical pathway for energy production in cells lacking mitochondria170. In mice, PK deficiency is associated with constitutive anemia, splenomegaly, compensatory reticulocytosis and protection against malaria3,203. Studies in human erythrocytes show that pyruvate kinase deficiency protects against infection and replication of P. falciparum parasites175. Furthermore, studies in human populations from Cabo
101 Verde241 and from sub-Saharan regions of Angola and Mozambique242 suggest that
PKLR is under malaria selective pressure.
In order to investigate the genetic control of malaria susceptibility in AcB62 mice, an informative F2 cross was generated between AcB62 and another Pklr deficient strain: CBA/N-Pkslc (CBA/Pk), previously found to be highly resistant to P. chabaudi chabaudi AS infection165,206. Linkage analysis in this cross revealed a major locus on chromosome 9: Char10 (LOD=10.8, 95% Bayesian CI=50.7-75Mb) controlling the extent of parasite replication at the peak of infection and modifying the malaria-protective effect of PK deficiency206. The Char10 locus was further characterized and was shown to modulate the severity of PK deficiency-associated anemia by regulating the level of erythroid precursors, iron and erythropoietin in
Char10C congenic mice (carrying susceptible AcB62 Char10 chromosome 9 fragment on a CBA/Pk background) compared to CBA/Pk controls256.
In this study, we reduced the Char10 region by creating and phenotyping additional sub-congenic mouse lines carrying different portions of the Char10 interval.
We also prioritized genes underlying the locus using whole exome sequencing and
RNA-sequencing approaches.
102 4.3 MATERIALS AND METHODS
4.3.1 Mice
A/J and C57BL/6J mice were originally purchased from the Jackson Laboratory
(Bar Harbor, ME, USA). The AcB recombinant congenic strain AcB62 was generated according to a breeding scheme of Demant and Hart243 and has been described previously201. CBA/Pkslc (CBA/Pk) mice were generously provided by the Japan SLC
Animal Facility (Mr H Asai). Char10 congenic mice were generated from CBA/Pkslc
(background strain) and AcB62 (donor strain) using marker-assisted backcrossing
(Figure 4.3A). All strains were maintained under pathogen-free conditions in the animal facility of McGill University. Mice were handled according to the guidelines of the Canadian Council of Animal Care, and all experiments were performed in compliance with the ethics committee of McGill University.
4.3.2 Parasite and infection
A lactate dehydrogenase virus-free isolate of P. chabaudi chabaudi AS, originally obtained from Dr Walliker (University of Edinburgh), was maintained by weekly passage in A/J mice by intraperitoneal infection with 106 parasitized red blood cells (pRBCs) suspended in 1mL of pyrogen-free saline. Experimental mice were infected intravenously with 105 pRBCs and the percentage of pRBCs was determined daily on thin blood smears stained with Diff-Quick (Dade Behring, Newark, DE, USA) on days 4 to 21 after infection. Survival from infection was monitored twice daily and moribund animals were sacrificed.
103 4.3.3 Genotyping and linkage analysis
Genomic DNA from all [AcB62xCBA/Pk]F2 mice was extracted from tail biopsies by a standard proteinase K treatment protocol201. The genomic DNA was genotyped for a total of 130 microsatellite and SNP markers. Microsatellite markers were genotyped by a standard PCR-based method using (α-32P)dATP labelling and separation on denaturing 6% polyacrylamide gels. SNP genotyping was performed at
KBiosciences, UK (www.kbiosciences.co.uk) from a custom panel. Additional SNP genotyping was performed in house by standard PCR followed by fluorescence- based sequencing. QTL mapping was performed using Haley-Knott multiple regression analysis257 or EM maximum likelihood algorithm258. A two-dimensional scan was performed using the two-QTL model and empirical genome-wide significance was calculated by permutation testing (500 tests). All linkage analysis was performed using R/qtl.
4.3.4 Whole exome capture sequencing
Genomic DNA from CBA/Pk and Char10C mice was extracted from ear biopsies by a standard proteinase K treatment protocol201. Whole exome capture sequencing was performed at the Australian Phenomics Facility, Australian National
University, Canberra. Exome enriched libraries were prepared from mouse DNA samples using the Agilent SureSelect Mouse All Exon kit (5190-4641, Agilent) following the manufacturers instructions and paired-end (100bp) sequenced in an
Illumina HiSeq2000.
104 Sequence reads were mapped to the GRCm38 assembly of the reference mouse genome using the default parameters of the Burrows-Wheeler Aligner (BWA).
Untrimmed reads were aligned allowing a maximum of two sequence mismatches and reads with multiple mappings to the reference genome were discarded along with
PCR duplicates. Sequence variants were identified with SAMtools and annoted using
Annovar. Variants common to CBA/Pk and Char10C mice were excluded.
Homozygous non-synonymous variants falling in coding sequences or in splice sites
(within 4 bases of an exon) and with sequencing coverage ≥ 8 reads were considered as putative causative mutations. A version of PolyPhen2 was utilized for the calculation of variant effect.
4.3.5 RNA sequencing (RNA-seq)
Total spleen RNA of CBA/Pk, Char10C and CBA/N mice was Trizol extracted and was further DNase treated and purified using RNeasy columns (Qiagen). RNA integrity was assessed on a Bioanalyzer RNA pico chip. The RNA-seq libraries were prepared following ribosomal RNA depletion by the Molecular Biology and Functional
Genomics Facility of the Institut de Recherche Clinique de Montréal (IRCM). Libraries were sequenced on an Illumina HiSeq 2000 sequencer (paired-end 50bp) at the
McGill and Genome Quebec Innovation Center. The quality of raw reads was assessed with FASTQC version 0.10.1. Poor quality bases and adapter sequences were trimmed with Trimmomatic. The reads were aligned to the GRCm38 genome with TopHat version 2.0.10. The raw alignments counts were calculated with HTSeq version 0.5.3 and normalized relative to the total number of reads. DESeq2 version
105 1.2.10 was used to calculate the differential expression of genes directly from the alignments counts calculated with HTSeq. Genes with expression below 5 RPKM in all three strains of mice were removed. Pairwise comparisons with expression ratios of 1.5X and above were considered significant.
4.4 RESULTS
4.4.1 Genetic analysis of differential reticulocytosis in [AcB62xCBA/Pk] F2 mice
The Char10 locus was previously mapped on mouse chromosome 9
(LOD=10.8, 95% Bayesian confidence interval=50.7-75Mb) in [AcB62xCBA/Pk] F2 animals and was found to control parasite replication at the peak of P. chabaudi chabaudi AS infection206. It was also shown to regulate erythroid responses in the presence of PK deficiency associated anemia256. Here we investigate the genetic control of reticulocytosis in the same [AcB62xCBA/Pk] F2 population. 237 F2 mice were phenotyped for reticulocyte levels. A typical distribution of those levels in AcB62 and CBA/Pk parental controls as well as in F1 and F2 mice, is shown in Figure 4.1A.
CBA/Pk have very high levels of reticulocytes in blood (~42%) compared to AcB62
(~26%). F1 mice show an intermediate phenotype (~34%) suggestive of a codominant mode of inheritance. In F2 animals, reticulocyte levels range from very high to low extremes represented by the parental strains (15 to 63%). F2 mice displayed a normal and continuous distribution around the mean, amenable to QTL mapping.
106 All 237 [AcB62xCBA/Pk] F2 mice were genotyped for 130 informative markers
(microsatellites and SNPs) across the genome. Quantitative trait analysis was performed in R/qtl across all chromosomes using reticulocyte levels as a quantitative trait, for males (n=140) and females (n=97) and for all mice together (Figure 4.1B).
Genome-wide significance thresholds were determined by empirical permutation testing, consisting of 500 tests. This analysis identified a highly significant linkage on chromosome 9 (Char10) and one weaker on chromosome 3 (Pklr), as did the analysis previously done using parasitemia as a quantitative trait206. The chromosome 3 locus was shown to be caused by different Pklr mutations segregating in this cross (I90N in
AcB62 and G338D in CBA/Pk)165. The Char10 LOD score was however significantly higher in the analysis done with reticulocytes (LOD score=12.8) compared to the one with parasitemia (LOD score=10.8). The 95% Bayesian confidence interval was also narrower (58-67Mb vs. 51-68Mb) (Figure 4.1C). Overall, these results demonstrate that the Char10 locus not only controls the extent of parasite replication at the peak of
P. chabaudi chabaudi AS infection in a context of PK deficiency, it also clearly modulates the constitutive level of circulating reticulocytes in naïve mice.
107
Figure 4.1 Linkage analysis in [AcB62xCBA/Pk]F2 mice. (A) The number of reticulocytes in individual mice (percentage of total red cells) was determined and the segregation by genotype (A, AcB62; C, CBA/Pk) at the Char10 D9Mit4 marker is shown. Each dot represents one mouse. (B) Linkage analysis with reticulocytes as a quantitative trait. Results for males and females are shown separately (blue and red lines) and together (black line). Positions of informative markers are indicated by lines on the x-axis. (C) Enhanced view of chromosome 9. Linkage with reticulocytes is shown in black. Linkage with peak parasitemia is shown in blue.
108 Interestingly, parasitemia and reticulocytes levels showed a strong inverse correlation. Mice carrying CBA/Pk alleles at Char10 were found highly resistant to P. chabaudi chabaudi AS malaria (low corrected parasitemia) but high levels of reticulocytes (44%), whereas mice carrying AcB62 alleles were susceptible with high parasitemia and lower reticulocyte percentages (31%) (Figure 4.2A and B). Moreover, we show that Char10 and Pklr have clear additive effects for both traits; mice carrying
CBA/Pk-derived alleles at both Char10 and Pklr have lowest parasitemia and highest reticulocyte levels (Figure 4.2C and D).
109
Figure 4.2 Segregation of peak parasitemia and reticulocyte levels by genotype at Pklr and Char10 loci. (A) and (B) Segregation of peak parasitemia (A) and reticulocyte levels (B) at the Char10 locus. The genotype is indicated on the x-axis (A, AcB62; C, CBA/Pk). (C) and (D) Additive effect of Pklr and Char10 loci on parasitemia (C) and reticulocytes levels (D). Each dot represents one mouse.
110 4.4.2 Creation and phenotyping of four Char10 mouse congenic lines
In order to reduce the size of the Char10 interval and to remove the confounding effect of the chromosome 3 locus (Pklr), we generated 4 congenic lines in which Char10 chromosome 9 segments from AcB62 were transferred onto the genetic background of CBA/Pk by serial backcrossing. Lines A1 and A2 carry upper portions of the Char10 interval (respectively 35.21-51.9Mb and 39.4-57.5Mb), line B the lower part (59.7-?) and line C carries the full Char10 interval (Figure 4.3A).
Phenotyping of the full C congenic line previously showed that the Char10 locus is sufficient to supress the malaria-protective effect of PK-deficiency in CBA/Pk mice256.
Char10C mice are indeed susceptible to P. chabaudi chaubaudi AS malaria and have low levels of reticulocytes as opposed to CBA/Pk controls (low parasitemia; high reticulocytes) but similarly to AcB62. Lines A1, A2 and B were also phenotyped for peak parasitemia and reticulocyte levels. All three lines were found to be as resistant to P. chabaudi chabaudi AS infection than CBA/Pk controls and present high levels of reticulocytes (Figure 4.3B and C). This shows that the gene underlying the Char10 interval is not found within the subcongenic fragments of these lines and this consequently reduces the Char10 locus to a region spanning 56.07 to 60.4 Mb.
111
Figure 4.3 Construction and phenotyping of four Char10 congenic lines. (A) Different portions of the chromosome 9 Char10 segment from the AcB62 strain (grey) were transferred onto the genetic background of the CBA/Pk strain (black). Abbreviations: H, high; L, low. (B) Peak parasitemia levels are shown for strains AcB62, CBA/Pk, Char10A1, B and C. Two independent infections are presented and separated by a vertical line. (C) Reticulocytes levels are shown for strains AcB62, CBA/Pk, Char10A1, A2, B and C. Each dot represents one mouse. Statistical significance (one-way ANOVA) is indicated by stars: ****P<0.0001.
112 4.4.3 Gene priorization using a whole exome sequencing approach
In order to detect putative causative mutations in genes found in the Char10 interval, a whole exome sequencing approach was used on CBA/Pk and Char10C genomic DNA. Each strain was initially compared to the reference genome
(C57BL/6). Variants common to CBA/Pk and Char10C mice were then excluded.
Homozygous non-synonymous polymorphisms found in coding sequences or in splice sites (within 4 bases from an exon) and with sequencing coverage ≥ 8 reads were considered significant.
The reduced Char10 interval (56.07-60.4 Mb) contains a total of 84 genes. In this region, the whole exome sequencing analysis identified 28 SNPs in 13 genes
(Table 4.1). 25 SNPs were found in exons, 3 in possible splicing sites. 6 genes present more than one polymorphism (Cyp11a1, Ccdc33, Gm7589, Adpgk, Myo9a and Thsd4). We propose that these 13 genes should be prioritized for the search of positional candidates.
113 Table 4.1 Exome sequencing analysis of CBA/Pk and Char10C mice. Results are shown for the Char10 region (56.1-60.4Mb) only.
114 4.4.4 Gene priorization using a RNA-sequencing approach
We conducted a RNA-sequencing experiment on CBA/Pk, Char10C and
CBA/N spleens (Table 4.2). Pairwise comparisons were performed between each strain and expression ratios of 1.5X and above were considered significant. We previously showed that Char10 modulates the severity of PK-associated anemia by regulating the level of erythroid precursors in blood and spleen. CBA/N mice are PK- sufficient, as opposed to CBA/Pk and Char10C mice which are PK-deficient.
Consequently, CBA/N mice do not show PK-associated anemia and compensatory erythropoiesis as do CBA/Pk and Char10C mice. Therefore, genes commonly expressed in CBA/Pk and Char10C mice and overexpressed in these two strains compared to CBA/N should include genes implicated in erythropoiesis. Here we show that this is actually the case. Genes known to play a major role in erythropoiesis such as Pklr, Hbb, Gata1, Tal1, Nfe2, Klf1, Lmo2, Foxo3 or Zfpm1 were at least 4 times more expressed in CBA/Pk and Char10C compared to CBA/N mice (data not shown).
In the reduced Char10 interval (56.07 to 60.4 Mb), 10 genes were found to be at least
1.5X more expressed in CBA/Pk and Char10C than in CBA/N mice, but only one:
Rps11-ps1 was found to be differentially expressed between CBA/Pk and Char10C mice. 14 genes in total were differentially expressed between CBA/Pk and Char10C and 4 of those (Cyp11a1, Stra6, Thsd4 and Lrrc49) were identified previously with genetic variants polymorphic between CBA/Pk and Char10C mice in the whole exome sequencing approach.
115 Table 4.2 RNA sequencing analysis. Spleen RNA from CBA/Pk, Char10C and CBA/N was obtained and RNA from 5 mice per group were pooled.
116
117 4.5 DISCUSSION
Linkage analysis has been used extensively to map loci modulating response to P. chabaudi malaria infection in mice. Strikingly, we showed that Char10 regulates two quantitative traits in [AcB62xCBA/Pk]F2 animals : parasitemia at the peak of infection (LOD score=10.8; 95%; credible interval= Chr9 51-68Mb)206 and reticulocyte levels in naïve mice (LOD score=12.8; 95% credible interval= Chr9 58-67Mb) in the presence of PK-deficiency. The strong linkages are overlapping (Figure 4.1C).
Moreover, parasitemia and reticulocyte levels showed strong inverse correlation
(Figure 4.2). This suggests the presence of a major genetic factor influencing both traits.
The minimal intervals predicted by the two QTL analysis are however quite large (peak parasitemia=17Mb; reticulocytes=9Mb) and the presence of the Pklr locus on chromosome 3, that was previously shown to be caused by different Pklr alleles segregating in AcB62 and CBA/Pk animals, make it difficult to assess the effect of
Char10 in this cross. The creation and phenotyping of Char10C congenic mice, which were generated by transferring AcB62 Char10 Chr9 fragment onto CBA/Pk background by serial backcrossing, previously showed that Char10 was sufficient to supress alone the malaria protective effect of pyruvate kinase deficiency256. In order to reduce the Char10 locus to a size amenable to positional cloning, we generated additional congenic lines carrying different portion of the Char10 interval (AcB62- derived) on a CBA/Pk background. Phenotyping of these lines for parasitemia and
118 reticulocyte levels allowed us to shrink Char10 to a region of 4 Mb spanning 56.07-
60.4 Mb.
This reduced Char10 region contains a total of 84 genes. Whole exome sequencing performed on CBA/Pk and Char10C mice revealed homozygous non- synonymous variants in 13 of those genes. Among these 13 genes, 2 stood up based on literature. Adpgk (59.1Mb) encodes the ADP-dependent glucokinase. This enzyme is related to the hexokinase family. As such, it catalyses the glucose phosphorylation in the first and rate limiting step of the glycolytic pathway but has the particularity of utilising ADP as phosphoryl donor instead of ATP259. Being part of the same pathway than PK, Adpgk is a good candidate for the Char10 locus, which was shown to modulate PK-associated anemia. Variants in Char10C mice consist of two alanine to serine conversions at position 341 and 373 (Table 4.1), which bring two new hydroxyl groups that could potentially affect the secondary structure of the protein. Although human ADPGK was proposed not to make a quantifiable contribution to glycolysis260, hexokinase deficiency in patients‘blood has been associated with nonspherocytic haemolytic anemia, compensatory reticulocytosis and increased erythrocyte’s mean corpuscular volume261, and these symptoms were previously found significantly more pronounced in CBA/Pk compared to Char10C mice.
The gene Neo1 is also a possible candidate for Char10. It encodes the cell surface protein Neogenin1, which is a member of the immunoglobulin superfamily.
We previously showed that Char10 modulates the level of iron in kidney and liver of
Char10C compared to CBA/Pk mice. A recent study by Lee et al. demonstrates that
119 Neo1 regulates iron homeostasis, neogenin-deficient mice exhibiting iron overload and reduced hepcidin expression in the liver262. The variant found for Neo1 in our whole exome sequencing study occurs 4 bases upstream of exon 12. Additional experiments would be needed to see if the observed mutation affects the splicing of the protein.
The Char10 segment on Char10C mice is derived from AcB62 mice. AcB62 is a recombinant congenic strain derived from A/J and C57BL/6 and which carries the
A/J genome in the Char10 region201. The A/J genome sequence is available on the
Wellcome Trust Sanger Institute website. All the SNPs found on Char10C mice were compared to this database and all were found to be true A/J SNPs. None of the polymorphism found on the Char10C background is therefore a “de novo” mutation that could have arisen during the generation of the Char10C congenic strain.
In order not to miss genes that may not contain mutations in coding sequences or in putative splicing site but that could be differentially expressed between CBA/Pk and Char10C mice, we performed a RNAsequencing analysis in those mice. 14 genes (Table 4.2) were shown to be differentially expressed between CBA/Pk and
Char10C and could therefore be possible candidate for the Char10 interval. Out of those 14 genes, only 4 (Cyp11a1, Stra6, Thsd4 and Lrrc49) were identified in the whole exome sequencing approach as carrying genetic variants polymorphic between
CBA/Pk and Char10C. We also showed that genes known to be implicated in erythropoiesis were significantly more expressed in CBA/Pk and Char10C than in the
Pk-sufficient strain CBA/N. This is the case for Pklr, Hbb, Gata1, Tal1, Nfe2, Klf1,
120 Lmo2, Foxo3 and Zfpm1 that were at least 4 times more expressed in CBA/Pk and
Char10C compared to CBA/N mice. In the Char10 region, only one gene was found to be both overexpressed in CBA/Pk and Char10C compared to CBA/N mice and differentially expressed between CBA/Pk and Char10C. This gene: Rps11-ps1 encodes for a ribosomal protein. Considering that mature red cells are lacking ribosomes (as well as nucleus or any other organelles), a defect in this gene would more likely affect the maturation of erythroid cells rather than the metabolism of mature RBCs themselves. Note that it was previously shown that the maturation of erythroid progenitors into reticulocytes was not different between CBA/Pk and
Char10C mice despite a higher numbers of those in CBA/Pk as compared to
Char10C mice256.
The Char10 congenic segment was initially standing at a size >35Mb. This study considerably reduces the size of the interval to a 4Mb region containing 84 genes. Exome sequencing and RNA sequencing analysis identified genes to be prioritized. Finding the gene underlying the Char10 locus will allow us to better understand the pathogenesis of malaria and anemia and may help us develop new therapeutic or prophylactic tools for intervention.
121 4.6 ACKNOWLEDGEMENTS
We thank Susan Gauthier for her technical assistance in breeding and maintaining the mice colonies. This work was supported by CIHR grant MOP-79343,
FRSQ (AL) and CIHR (AL, GMO) studentships.
122 Chapter 5 : Summary, Discussion and Futures Directions
123 5.1. SUMMARY
Malaria remains to date the most important parasitic disease in the world.
Tremendous efforts have been allotted to elucidate malaria pathogenesis, including host response to infection and the complex genetic determinants that regulates its effectiveness. Understanding malaria requires studying mechanisms of parasite invasion, parasite biology, innate and adaptive host immune responses. The work in this thesis focused on the identification of novel host genetic factors influencing susceptibility/resistance to blood-stage malaria in mice. To do so, we have used a forward genetic approach (chapter 2 and 4) combined with biochemistry and next generation DNA and RNA sequencing (chapter 3 and 4).
In chapter 2, we surveyed a set of 25 phylogenetically distant inbred mouse strains for susceptibility to Plasmodium chabaudi chabaudi AS infection. A broad spectrum of responses (peak parasitemia and survival) was observed, suggestive of rich diversity in response to malaria in inbred strains. F2 animals were generated from
SM/J (susceptible) and C57BL/6J (resistant) parental strains and were phenotyped for susceptibility to P. chabaudi chabaudi AS. A whole genome scan in this cross identified the Char1 locus on chromosome 9 as a key regulator of parasite density and pointed to a conserved 0.4Mb haplotype block at Char1 that segregates with resistance/susceptibility to infection. In addition, a second locus: Char11 was detected on chromosome X. This chapter identified a conserved role of Char1 in
124 regulating response to malaria in inbred mouse strains and provided a prioritized
0.4Mb interval for the search of positional candidates235.
In chapter 3 and 4, we phenotypically characterized and dissected the genetic component of the Char10 locus, which was previously shown to modulate the extent of parasitemia in the context of pyruvate kinase deficiency in a [CBA/Pk x AcB62]F2 intercross206. We showed that Char10 was not only controlling parasitemia following
P. chabaudi chabaudi AS infection, it is also controlling the level of reticulocytes in naïve mice. The linkage analysis performed in [CBA/Pk x AcB62]F2 animals revealed, in addition to the Char10 locus, the presence of an effect on chromosome 3 that was due to distinct Pklr alleles segregating in this cross. To reduce the size of the Char10 interval and to eliminate the confounding effect of the chromosome 3 locus, we generated 4 congenic lines in which different portions of the chromosome 9 Char10 region from AcB62 were transferred onto a CBA/Pk background. Phenotyping of these lines demonstrated that Char10 modifies the protective effect of the Pklr mutation by reducing the extent of anemia in these mice. It also allowed us to reduce
Char10 to a 4Mb region amenable to positional cloning. We then used whole exome sequencing and RNA sequencing approaches to prioritize genes in the Char10 interval. These approaches identified a few genes with homozygous non-synonymous variants polymorphic between CBA/Pk and full congenic Char10C mice or/and with differential expression between these strains.
125 5.2 DISCUSSION AND FUTURES DIRECTIONS
5.2.1 Positional cloning of the Char1 locus
The Char1 locus was previously mapped by Foote et al.195 in two independent
F2 crosses where mice were infected with P. chabaudi adami DS, and Ohno et al.197 mapped, in the same region, the Pymr locus, which determines susceptibility of mice to P. yoelii 17XL. Although those loci were mapped in 1997 and 2001 respectively, the gene underlying the Char1/Pymr interval has never been found. Foote et al. and
Ohno et al. identified loci that were quite large (16.8 and 17.4 Mb respectively). The haplotype analysis performed in chapter 2 allowed reducing this interval to a 0.4 Mb region containing 13 genes. In order to validate that the gene underlying Char1 is actually found within that small haplotype block, a few approaches could be implemented.
First, we could generate congenic strains of mice carrying different portions of the large Char1 interval. We would phenotype these mice for peak parasitemia and survival and see where the susceptibility/resistance is transferred. This should reduce the initial Char1 region significantly and would be a first step in confirming that the portion of Char1 carrying the 0.4Mb haplotype block is responsible for the Char1 effect.
The haplotype analysis was performed using 2 lists of SNPs, the first consisting of 28 000 SNPs for Chr. 9 only and was provided by G. Churchill at the
Jackson laboratory (personal communication), and the second consisted of 132 000
126 SNPs for the entire genome and was obtained from the Mouse HapMap project227.
Although these high densitiy SNP maps were quite informative, we could refine the study by performing a whole genome sequencing analysis in the Char1 region in all strains in which resistance/susceptibility to P. chabaudi or P. yoelii has been linked to this locus. This would help better delineate and potentially further subdivide the 0.4Mb haplotype block, but could also suggest coding or regulatory variants segregating with the Char1 determined differential susceptibility trait.
We could also look at genes differentially expressed between susceptible versus resistant lines to see if a pattern of expression segregates with resistance/susceptibility to P. chabaudi or P. yoelii, and with potential regulatory
SNPs. To do so, a RNA sequencing approach could be used, or if the 0.4 Mb interval is confirmed by the above studies, qPCR could be performed on the 13 genes contained in this small region.
In addition, functional studies could help phenotypically characterize the Char1 locus. We demonstrated in chapter 2 that susceptible SM/J mice were found to have significantly lower number of CD4+ T cells in the spleen than C57BL/6 mice. We also showed that there is a cluster of genes containing STAT1-binding site(s) in the large
Char1 interval and that nearly all 13 genes found in the 0.4Mb haplotype block contain STAT1-binding site(s). STAT1 is a key regulator of production of the pro- inflammatory cytokine IFNγ by CD4+ and CD8+ T cells. Together, this suggests that the gene(s) underlying Char1 is immune-related and has a role in regulating response to infection in an IFNγ-dependent fashion. To refine this analysis, we could look at the
127 levels of CD4+ T cells in all strains used to map Char1/Pymr and see if all susceptible mice present with lower CD4+ T cell numbers than resistant mice. We could also perform flow cytometry on spleen and bone marrow of those strains to analyse the myeloid compartment, another compartment where STAT1 plays a key role in regulation of early immune responses. This would tell us if only CD4+ T cells are affected or if other immune cell types are impacted by the Char1 locus. Finally, ELISA for cytokines such as IFNγ, IL12, IL18, IL10, TGFβ could be performed. Ultimately, all these functional studies should help guide the identification of the gene(s) underlying
Char1.
5.2.2 Positional cloning of the Char10 locus
5.2.2.1 Further functional characterization of the Char10 locus
Hemolytic anemias are conditions in which red cells are destroyed or removed from the circulation before their normal life span is over. They are classically associated with compensatory erythropoiesis. In mice, Pk deficiency anemia was previously shown to be associated with rapid red cell turnover and compensatory reticulocytosis165,203.
In chapter 3, we demonstrated that Char10 modulates the malaria-protective effect of Pk deficiency by reducing the extent of anemia in mice. Char10 was found to control the production of erythropoietin, erythroid progenitors, erythroblasts, reticulocytes, with very anemic CBA/Pk strain having less RBCs but more RBC precursors than less anemic Char10C strain. However, no difference in RBC turnover
128 was observed, suggesting that the life-span of mature red blood cells is not affected by the Char10 locus.
Mentzer et al.263 previously showed that selective reticulocyte destruction was occurring in human erythrocyte PK deficiency. They found that a significant proportion of newly made reticulocytes were sequestered by the reticuloendothelial system and destroyed, while others were able to survive. A differential sequestration and destruction of young reticulocytes in CBA/Pk and Char10C mice could explain why
CBA/Pk have higher levels of reticulocytes and lower levels of RBCs in the circulation compared to Char10C mice despite the same ‘mature RBC’ life-span.
To test for this hypothesis, apoptosis of reticulocytes in the blood circulation, spleen and liver could be determined by flow cytometry and the number of phagocytic cells in the circulation could also be assessed.
Aizawa et al.264 found that in CBA/Pk mice, significant apoptosis was going on in spleen TER119+ cells and they concluded that ineffective erythropoiesis was happening in those mice. Although we showed that the erythropoiesis process was not different in CBA/Pk versus Char10C mice, a higher level of apoptosis in the spleen of CBA/Pk could be the sign that more reticulocytes are removed early from the circulation and sequestered in the spleen where they end up dying.
Last but not least, the maturation of reticulocytes in the blood circulation could be assessed by flow cytometry as previously done in another mouse model by Holm
129 et al.265 During normal reticulocyte maturation, there is a decrease of both RNA and cell surface transferrin receptors (Trfr). This feature could be used to compare the populations of reticulocytes in CBA/Pk and Char10C mice and identify a possible blockage in reticulocyte maturation.
5.2.2.2 Adpgk, hexokinases and apoptosis
In chapter 4, we used exome sequencing as well as RNA sequencing approaches to help prioritize the genes in the Char10 interval. Adpgk, a gene coding for an enzyme related to the hexokinase family, was found to be a possible candidate for Char10. Indeed, hexokinases catalyse the first and rate limiting step of the glycolysis266; they’re part of the same pathway than Pk.
Hexokinase deficiency has been reported in humans with a degree of severity that ranges from mild, fully compensated anemia to severely affected patients exhibiting neonatal hyperbilirubinemia and requiring later in life transfusion at regular intervals because of intractable anemia. However, jaundice, reticulocytosis and splenomagly are common hallmarks of HK deficiency and are usually present even in mildly affected individuals.261,267,268 In mice, a model of Pk deficiency called Downeast anemia, is caused by a homozygous mutation that leads to decreased expression of
HK1 in erythroid tissues, spleen and kidney. Mice present with nonspherocytic haemolytic anemia, splenomegaly, reticulocytosis and marked accumulation of iron in liver and kidney.269
130 Different isotypes of hexokinases are known (HK1-4, HKR, Adpgk). HK1 is found in most tissues. In addition, and depending on the tissue, another or a combination of hexokinases may be present. HK1, HKR and Adpgk are found in erythrocytes.259,260,266,270 Interestingly, it has been reported that HK activity declines as red cell age, especially during reticulocyte maturation. It is also shown that HK deficiency impact young erythrocytes much more than older red cells which can meet their smaller energy needs even with low levels of HK.267,271 Furthermore, it has been demonstrated that Adpgk expression was highly expressed compared to average gene in many normal tissues. Extremely high values were reported in peripheral red cells (32 times the median transcript).260 This suggests an important role of Adpgk in erythrocytes. Although human ADPGK was proposed not to make a quantifiable contribution to glycolysis in human cancer cell lines260, the role of ADPGK in red cells, more than ever in a context of Pk deficiency has never been investigated. As opposed to the other hexokinases that all use ATP to convert glucose into glucose-6- phosphate, Adpgk has the particularity of using ADP as a phosphoryl donor259. In Pk deficient erythrocytes, the fact that Adpgk saves ATP may be of great importance.
Finally, and although the mechanism is not clear, a few articles suggests that mitochondrial HK plays a role in apoptosis inhibition.272-275
The two mutations found in Adpgk were identified on the Char10C (ie, AcB62 or A/J) background and consist of two alanine to serine conversions at position 341 and 373 of the protein. Although gain of function mutations are rare, a more efficient
131 Adpgk enzyme in Char10C mice could explain their reduced anemic phenotype compared to CBA/Pk mice.
5.2.2.3 Pkm: another interesting candidate gene
As previously mentioned, four PK isoenzymes are known in humans, and they are expressed in a tissue-specific manner.158 They’re encoded by two genes: PKLR and PKM.159 PKLR encodes both the liver (L-type) and the erythrocyte (R-type) isoforms through the use of alternate tissue-specific promotors.160 PKM encodes the
M1 and M2 isoforms, initially identified as ‘muscle’ isoforms, although not exclusively found in muscles. M1 and M2 are produced by alternate splicing.162 M1 is found in skeletal muscle, heart and brain. M2 is the predominant enzyme in fetal tissues and in erythroid precursors. It is then replaced by tissue-specific isoforms (R-PK in erythrocytes). PKM2 remains important in kidney, leukocytes, platelets, lung, spleen and adipose tissue.170
Although no genetic variants polymorphic between CBA/Pk and Char10C mice has been identified in Pkm by whole exome sequencing or regular Sanger sequencing techniques, and although the RNA-sequencing approach didn’t point towards a differential expression of Pkm in those strains, we can’t ignore this gene as a) it is found within the Char10 interval and b) we are looking for the presence of a genetic modifier of the Pklr effect in those mice. Tsujino et al. demonstrated that
CBA/Pk mice have a delayed onset of haemolytic anemia after birth compared to
CBA wild-type mice (not Pk deficient) that coincides with a delayed switching from Pk-
132 M2 to Pk-R.276 In addition, persistent M2 isoenzyme in erythrocytes of Pk-R deficient patients has been reported and may represent a compensatory mechanism for their
PK-R deficiency.267 Persistent M2 in Char10C reticulocytes or delayed onset of anemia in young Char10C compared to CBA/Pk mice could explain the differential anemic phenotype of these two mouse strains.
5.3 FINAL CONCLUSIONS
Eleven Char loci have been discovered so far but only two genes (Pklr for
Char4 and Vnn3 for Char9) have been identified. The large gene-rich regions are often difficult to dissect and require a combination of forward genetic techniques, phenotypic characterization and other complementary approaches so that candidate genes can be prioritized. The work in this thesis dissected two of these loci and has successfully broken down some of their complexity. Future identification of the genes will allow us to better understand the molecular mechanisms and pathogenesis of malaria and possibly uncover new targets for therapeutic intervention.
133 ORIGINAL CONTRIBUTIONS TO KNOWLEDGE
1. Phenotyping of 25 phylogenetically distant inbred mouse strains for
susceptibility to Plasmodium chabaudi chabaudi AS infection (peak
parasitemia, survival).
2. Identification of the Char1 and Char11 loci (on chr 9 and X respectively) as
key regulators of susceptibility to malaria in a novel [SM/JxC57BL/6]F2
intercross.
3. Reduction of the Char1 interval to a conserved 0.4Mb haplotype that
segregates with susceptibility/resistance to infection.
4. Phenotypic characterization of the Char10 locus: Char10 modifies the
protective effect of the Pklr mutation by reducing the extent of anemia in mice.
5. Genetic characterization of the Char10 locus: generation of 4 congenic mouse
lines carrying different portions of the Char10 interval, reduction of the Char10
locus from a 24.3Mb to a 4.3Mb region and priorization of genes candidates.
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