Natalia Marta Par

Zmarlak

Mitri Christian

The secreted mosquito leucine-rich repeat protein APL1C is a pathogen binding factor essential for immunity to Plasmodium ookinetes and sporozoites

I would like to

LIST OF FIGURES

Female Anopheles mosquitoes -vector of malaria

Morbidity and mortality caused by mosquito-borne diseases makes a mosquito the most dangerous animal for a human being [START_REF] Chandrasegaran | Linking Mosquito Ecology, Traits, Behavior, and Disease Transmission[END_REF] . The hematophagous female mosquito acquires essential nutrients for egg development by taking blood from vertebrate animals including or humans. Through the bloodmeal, mosquitoes can ingest and eventually transmit pathogenic microbes with injected saliva to the vertebrate host during the next bloodmeal. Many mosquito species are vectors responsible for the transmission of multiple pathogens, including protozoans, viruses, bacteria and nematodes, causing diseases such as malaria, yellow fever, dengue, filariasis or encephalitis. This blood dependency has been used by the pathogens to co-evolve with their respective mosquito hosts to assure their transmission. Mosquito vectors thus bridge the physical barriers that would be impossible for the pathogen to cross through direct contact between humans or animals [START_REF] Rosenberg | Vector-borne infections[END_REF] .

Mosquitoes of the genus Anopheles are responsible for the transmission of the protozoan parasite Plasmodium, the causative agent of malaria, the world's deadliest parasitic disease. In 2019, there were 229 million diagnosed cases of malaria worldwide, with 409 000 human deaths reported. Approximately 94% of global malaria cases occur in sub-Saharan Africa. Children under 5 years old are the most vulnerable group to malaria and constitute two-thirds of all malaria deaths worldwide in 2019 3 .

History of malaria, mosquito-vector discovery and vector control

Malaria is one of the oldest human diseases. The first recorded mention that corresponded to malaria symptoms appeared in notes from ~2700 BC. The word "malaria" comes from an Italian appellation of the disease during Middle Age, mal'aria, meaning "spoiled air'", reflecting the doctrine that lasted for over 2500 years, which considered malaria as an aerial infection arising from the marshes. Our understanding of this disease started at the end of the XIX century when a French physician, Alphonse Laveran, discovered Plasmodium parasites in a malaria infected patient [START_REF] Cox | History of the discovery of the malaria parasites and their vectors[END_REF] . For this finding, Laveran won the Nobel Prize in Physiology or Medicine in 1907.

In the 1890s, Patrick Manson proved an association between insects and pathogens causing human and animal diseases. His discovery of mosquito involvement in transmission of filarial worms responsible for lymphatic filariasis suggested that this insect could also be responsible for malaria transmission [START_REF] Chernin | an annotated bibliography and a note on a collected set of his writings[END_REF] . Scientists postulated the possibilities of human infection by drinking water contaminated by infected mosquitoes or inhaling dust from dried-up ponds in which infected mosquitoes died. Others suspected that the parasites could be transmitted mechanically from host to host on the proboscis of a mosquito [START_REF] Cox | History of the discovery of the malaria parasites and their vectors[END_REF][START_REF] Chernin | an annotated bibliography and a note on a collected set of his writings[END_REF] . But finally, in 1897 Ronald Ross, after many attempts, successfully infected female mosquitoes with Plasmodium from the blood of infected patients, thus resolving all previous speculations. His observations of circular parasites in dissected mosquito midguts (now called oocysts) were followed by research on avian malaria, where he demonstrated the rupture of oocysts leading to sporozoite release in the circulatory system of the mosquitoes (hemocoel) and their migration to the salivary glands, thus completing the parasite life cycle [START_REF] Cox | History of the discovery of the malaria parasites and their vectors[END_REF][START_REF] Hagan | Ronald Ross and the problem of malaria[END_REF] .

The ground-breaking discovery of R. Ross opened a new avenue in fighting malaria disease, through controlling the essential part of Plasmodium parasite transmission by targeting the Anopheles mosquito vector. The historic success of malaria eradication GENERAL INTRODUCTION 20 in various parts of the world was mainly achieved by vector control programs. The early malaria vector control programs attempted to eliminate mosquito through environmental management based on knowledge of insect development. The mosquito lifecycle includes four stages: egg, larva, pupae and adult, of which the first three are aquatic. Therefore, early strategies concentrated on limiting the aqueous environment, such as drainage of habitats, oil application to open water bodies, gridditching of marshes, modification of river boundaries and other engineering approaches, which decreased mosquito populations by denial of larval habitat [START_REF] Patterson | Looking Backward, Looking Forward: The Long, Torturous Struggle with Mosquitoes[END_REF][START_REF] Becker | Mosquitoes and Their Control[END_REF][START_REF] Rieckmann | The chequered history of malaria control: are new and better tools the ultimate answer?[END_REF] .

However, the most efficient tool appeared with the use of insecticides. Since the first half of the 20th century, different classes of insecticides have been successively used: organochlorines, organophosphates, carbamates and synthetic pyrethroids. Use of insecticides greatly limited mosquito-borne diseases and in some areas even eradicated malaria. Indoor residual spraying (IRS) using dichlorodiphenyltrichloroethane (DDT) implemented in the Global Malaria Eradication Campaign (GMEC) in 1955, showed spectacular success in decimating disease vectors. However, despite the efficiency of DDT in reducing mosquito vector populations, safety concerns for humans and their environments led to its ban in many countries in the 1970s. Moreover, at least during the last 20 years, the widespread development of mosquito resistance to the most commonly used insecticides caused serious problems in many areas resulting in recurrent outbreaks of mosquito-borne diseases [START_REF] Raghavendra | Malaria vector control: from past to future[END_REF][START_REF] Bhatt | The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015[END_REF][START_REF] Keiser | Reducing the burden of malaria in different ecoepidemiological settings with environmental management: a systematic review[END_REF][START_REF] Benelli | Current vector control challenges in the fight against malaria[END_REF][START_REF] Liu | Insecticide Resistance in Mosquitoes: Impact, Mechanisms, and Research Directions[END_REF][START_REF] Wilson | The importance of vector control for the control and elimination of vector-borne diseases[END_REF][START_REF] Jayaraj | Organochlorine pesticides, their toxic effects on living organisms and their fate in the environment[END_REF] . Alternative approaches that have already been implemented use natural insecticidal materials obtained from animals, plants, bacteria or minerals instead of chemical insecticides. Classified as biopesticides, entomopathogenic bacteria and fungi, such as Bacillus thuringiensis var. israelensis (Bti) or Metarhizium spp. displayed promising results in mosquito elimination. Nevertheless, their efficacy GENERAL INTRODUCTION 21 varies in different environments, affected by factors such as water pollution or instability to UV radiation 17 . Therefore, according to World Health Organization (WHO) recommendations, insecticide-based strategies, including insecticide-treated mosquito nets (ITNs) and IRS using pyrethroids, remain the mainstay interventions for mosquito vector control. At the same time, the recent WHO Health and Environment Linkages Initiative (HELI) stressed the importance of basic knowledge on mosquito vector behaviour and ecology, in order to develop tailor-made vector management actions in malaria endemic sites. This strategy enables implementation of integrated vector management (IVM), which besides conventional methods in fighting mosquito vector (ITNs and IRS) implements alternative strategies, such as environmental manipulation.

IVM is a dynamic and still-evolving field necessary for sustainable and ecologically sound mosquito control strategies 18 .

Why is Africa the most malaria endemic continent -what makes a competent mosquito vector?

Plasmodium parasite transmission between humans requires a competent mosquito vector. Vector competence defines the intrinsic ability of a vector to carry, tolerate the development and transmit a microbe and it reflects the susceptibility of a mosquito vector to such microbe 19 . Vector competence is usually measured experimentally as the prevalence of infected and infectious vectors at given times post-microbial exposure [START_REF] Beerntsen | Genetics of mosquito vector competence[END_REF] . The reasons for high malaria endemicity cases in Africa is a combination of physiologically permissive vector species mainly belonging to the Anopheles gambiae sensu lato (s.l.) complex and, most importantly, their highly anthropophilic feeding behaviour. The anthropophily of A. gambiae s.l. probably originated from the integration of these mosquitoes into human ecosystems about 8000 years ago when GENERAL INTRODUCTION 22 the advent of agriculture led to the new ecological niche of fixed human settlements 19,[START_REF] Powell | An evolutionary perspective on vector-borne diseases[END_REF][START_REF] Carter | Evolutionary and historical aspects of the burden of malaria[END_REF] .

Among approximately 100 Plasmodium species that are infective for different vertebrates, five of them cause malaria in humans: Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae, Plasmodium ovale and Plasmodium knowlesi [START_REF] Tuteja | Malaria -an overview[END_REF][START_REF] White | Plasmodium knowlesi: the fifth human malaria parasite[END_REF] . Today the majority of malaria cases in Africa are caused by P.

falciparum [START_REF] Tuteja | Malaria -an overview[END_REF] .

A. gambiae was initially considered as a single malaria vector species across the African continent. However, beginning in the 1960s hybridization experiments combined with genetic studies showed that A. gambiae s.l. is a complex of at least seven morphologically indistinguishable sibling species, and more taxa continue to be discovered [START_REF] Davidson | Anopheles gambiae Complex[END_REF][START_REF] Coluzzi | A Polytene Chromosome Analysis of the Anopheles gambiae Species Complex[END_REF][START_REF] Riehle | A cryptic subgroup of Anopheles gambiae is highly susceptible to human malaria parasites[END_REF] . Different species display diverse biting behaviour and ecological preferences, including indoor (endophagous) or outdoor (exophagous) biting behaviour. Therefore, indoor targeted vector control strategies are not completely efficient against outdoor-biting taxa or genotypes. This behavioural diversity of A.

gambiae s.l. increases the challenge in vector control strategies. Mosquito genotyping combined with behavioural and infectious studies are helping to better understand the complexity of the efficient transmission system in order to develop more efficient control strategies.

The complex lifecycle of Plasmodium parasite in vertebrate and mosquito

As pointed out, the success of parasite transmission to humans depends on the vector competence of the mosquito. Plasmodium has a complex lifecycle that requires two hosts: the intermediate vertebrate host, and the definitive mosquito host. Plasmodium sporozoites are transmitted to the vertebrate host through the saliva of an infected mosquito (Figure 1). Sporozoites are carried by blood flow to the liver where they infect hepatocytes. There, the parasites grow and multiply to be released into the blood stream as merozoites, which infect red blood cells (RBCs). Repetitive intraerythrocytic cycles occur to form different stages: rings, trophozoites and schizonts, which release new merozoites that invade non-infected RBCs. The contents of the infected RBCs released upon their lysis stimulate the production of tumour necrosis factor and other cytokines, which are responsible for clinical manifestations of malaria disease. People infected with Plasmodium typically experience fever, shivering, cough, respiratory distress, joint pain, headache, diarrhoea, vomiting and convulsions. P. falciparum is the most dangerous human malaria species and can be sequestered in microvasculature of different organs, including the brain, which can result in cerebral malaria and potentially death [START_REF] Tuteja | Malaria -an overview[END_REF][START_REF] Aly | Malaria Parasite Development in the Mosquito and Infection of the Mammalian Host[END_REF][START_REF] Siciliano | Enlightening the malaria parasite life cycle: bioluminescent Plasmodium in fundamental and applied research[END_REF] . None of the parasite asexual blood stages are infectious to the mosquito. After several erythrocytic cycles, stress and other signals leads to parasite differentiation into female and male gametocytes, maturating through five different stages (I-V). Nevertheless, the mechanism of the parasite commitment to start sexual development still remains ambiguous, as approximately 10% of the merozoites undergo sexual development [START_REF] Josling | Sexual development in Plasmodium parasites: knowing when it's time to commit[END_REF] .

Only stage V mature female and male gametocytes are transmissive stages from human to mosquito. Upon a bloodmeal on an infected host, the female mosquito ingests both female and male gametocytes. In the midgut lumen, each male gametocyte produces eight flagellated motile microgametes in a process called exflagellation, induced by environmental and vector factors (Figure 2). Released motile male gametes attach and fertilize female gametes within ~30 min after ingestion, forming zygotes. The zygotes transform into motile ookinetes that traverse mosquito midgut epithelial cells, from the apical to the basal side where they round up to become oocysts. These first steps of the parasite development in the mosquito, from gametocyte fertilization to ookinete traversal, are relatively rapid, taking approximately 24 hours. The subsequent steps are longer in time. Within the sessile oocysts, multiple rounds of mitosis result in thousands of sporozoites. Between 10-12 days after oocyst establishment, mature oocysts undergo membrane rupture, leading to the release of sporozoites in the mosquito hemocoel, which is an open circulatory system, from which sporozoites invade the salivary glands. There, the sporozoites remain metabolically quiescent for the life of the vector, and are transmitted in the saliva to a new host during later bloodmeals [START_REF] Vlachou | The developmental migration of Plasmodium in mosquitoes[END_REF][START_REF] Baton | Spreading the seeds of million-murdering death: metamorphoses of malaria in the mosquito[END_REF][START_REF] Shahabuddin | Plasmodium ookinete development in the mosquito midgut: a case of reciprocal manipulation[END_REF][START_REF] Guttery | Sexual Development in Plasmodium: Lessons from Functional Analyses[END_REF][START_REF] Smith | Plasmodium oocysts: overlooked targets of mosquito immunity[END_REF][START_REF] Siciliano | Critical Steps of Plasmodium falciparum Ookinete Maturation[END_REF] .

Two bottlenecks of Plasmodium development in mosquito vector

Even though Anopheles female mosquitoes are essential for Plasmodium transmission, not all of them are competent vectors for the parasites. In other words, the fact that a mosquito takes a bloodmeal from Plasmodium-infected host does not mean that the parasites will successfully develop within the insect vector. Indeed, during the parasite lifecycle, the largest losses in the number of parasites occur inside the mosquito host [START_REF] White | Evolution of Anopheles gambiae in Relation to Humans and Malaria[END_REF] . This indicates that the mosquito mounts defence mechanisms towards Plasmodium that can lead to complete elimination of the parasites from the mosquito host. During the early stages of Plasmodium development in the mosquito, from gamete fertilization to ookinete formation, the parasites are still exposed to the vertebrate host immune factors present in the ingested blood sera, which can impede parasite development in the mosquito [START_REF] Smith | The Plasmodium bottleneck: malaria parasite losses in the mosquito vector[END_REF] . The mosquito microbiome, which expands in abundance after the bloodmeal, could have deleterious, neutral, or beneficial effects on early parasite development, and is not yet well understood [START_REF] Pumpuni | Bacterial population dynamics in three anopheline species: the impact on Plasmodium sporogonic development[END_REF][START_REF] Rodgers | Microbiota-induced peritrophic matrix regulates midgut homeostasis and prevents systemic infection of malaria vector mosquitoes[END_REF][START_REF] Jupatanakul | The insect microbiome modulates vector competence for arboviruses[END_REF][START_REF] Dong | Implication of the mosquito midgut microbiota in the defense against malaria parasites[END_REF] . Finally, digestive enzymes in the mosquito midgut as well as the development of the chitin-based peritrophic matrix around the ingested blood bolus could serve as a mechanical barrier that some ookinetes fail to pass [START_REF] Smith | The Plasmodium bottleneck: malaria parasite losses in the mosquito vector[END_REF] . However, the most dramatic bottlenecks in the Plasmodium lifecycle appear during ookinete traversal through midgut epithelium, as out of ~1000 ookinetes invading the midgut epithelium, ~5 may succeed in forming oocysts [START_REF] Wang | Genetic approaches to interfere with malaria transmission by vector mosquitoes[END_REF][START_REF] Sinden | Plasmodium differentiation in the mosquito[END_REF] .

The next bottleneck is when sporozoites are released from mature oocysts in the hemolymph to invade the salivary glands. It is estimated that approximately 80% of released sporozoites will fail to infect the salivary glands [START_REF] Rosenberg | The Number of Sporozoites Produced by Individual Malaria Oocysts[END_REF][START_REF] Hillyer | Efficiency of salivary gland invasion by malaria sporozoites is controlled by rapid sporozoite destruction in the mosquito haemocoel[END_REF][START_REF] Graumans | When Is a Plasmodium-Infected Mosquito an Infectious Mosquito?[END_REF]

LRR domain proteins in immunity

LRR motifs have been identified in proteins ranging from viruses to eukaryotes.

Despite distinct evolutionary origin, many plant and animal immune receptors or factors including cell-adhesion molecules, hormone receptors, tyrosine kinase receptors or extracellular matrix-binding glycoproteins contain LRR domain. LRR proteins serve as significant mediators in both innate and, replacing immunoglobulin (Ig) domain, in alternative-adaptive immune systems where they play a dual function. Firstly, serving in pathogen sensing, through direct or indirect recognition of the pathogens, and secondly, as signal mediator, through the elicitors of downstream immune signalling they activate. LRR domains vary in their lengths and pattern of conserved residues, mediating ligand binding interactions [START_REF] Enkhbayar | Structural principles of leucine-rich repeat (LRR) proteins[END_REF] . In the next parts, I give an overview of distinct conserved immune protein families from different organisms, all carrying the LRR domain required for achieving their protective function.

LRR proteins in the innate immune system 1.2.2.1.1 Drosophila Toll receptors

Toll and the members of the Toll-dependent signalling pathway were initially found in Drosophila as involved in early embryonic development in the dorso-ventral patterning of the embryo [START_REF] Govind | Control of development and immunity by rel transcription factors in Drosophila[END_REF][START_REF] Anderson | Establishment of dorsal-ventral polarity in the Drosophila embryo: genetic studies on the role of the Toll gene product[END_REF] . Further studies demonstrated the contribution of Toll signalling pathway in defence against Gram-positive bacteria and fungi [START_REF] Valanne | The Drosophila Toll Signaling Pathway[END_REF][START_REF] Rutschmann | Cutting edge: the toll pathway is required for resistance to gram-positive bacterial infections in Drosophila[END_REF][START_REF] Anderson | Toll signaling pathways in the innate immune response[END_REF] . Toll protein is a transmembrane receptor with extracellular LRR domain that binds a ligand and an intracellular Toll/interleukine-1 receptor (TIR) domain that takes part in the intracellular signal transduction. Toll is not activated by direct recognition of a PAMP, but it binds instead to the active form of the protein ligand Spätzle (Spz) with a high affinity (kd=0.4nM) [START_REF] Arnot | Molecular mechanism that induces activation of Spatzle, the ligand for the Drosophila Toll receptor[END_REF] . Spz is a cytokine that is produced as a pro-form. Spz activation takes place upon proteolytic cleavage in response to infection through serine protease cascades that lead to the activation of Spätzle-processing enzyme (SPE), which is required to activate Spz [START_REF] Valanne | The Drosophila Toll Signaling Pathway[END_REF] . Spz binding to Toll induces receptor dimerization through disulphide bridges of conserved cysteine residues [START_REF] Hu | Multimerization and interaction of Toll and Spätzle in Drosophila<[END_REF] . This dimerization induces an intracellular signalling, leading to the phosphorylation of the inhibitor of nuclear factor kappa B (IκB) Cactus (a negative regulator of the Toll pathway). Once phosphorylated, Cactus releases the nuclear factor kappa-B (NF-κB) transcription factor(s) Dorsal or Dif, which migrate to the nucleus and activates the transcription of several genes, such as antimicrobial peptides (AMP) [START_REF] Valanne | The Drosophila Toll Signaling Pathway[END_REF] . Apart from humoral response, Toll receptor activation also induces cellular responses in Drosophila, such as phagocytosis, melanization or encapsulation [START_REF] Govind | Innate immunity in Drosophila: Pathogens and pathways[END_REF][START_REF] Valanne | The Drosophila Toll Signaling Pathway[END_REF] . The Drosophila genome encodes nine Toll receptors that all share a similar molecular structure, with an ectodomain composed mainly of LRR and cysteine-rich flanking motifs. Besides Toll (also known as Toll-1), only Toll-5 and Toll-9 induce the expression of the anti-fungal peptide drosomycin [START_REF] Ooi | The Drosophila Toll-9 activates a constitutive antimicrobial defense[END_REF] , whereas Toll-7 was shown to interact with viral pathogens, inducing antiviral autophagy in Drosophila [START_REF] Nakamoto | Virus recognition by Toll-7 activates antiviral autophagy in Drosophila[END_REF] . Therefore, Toll proteins are responsible for indirect recognition of pathogens and activation of humoral and cellular immune responses in Drosophila. [START_REF] Valanne | The Drosophila Toll Signaling Pathway[END_REF][START_REF] Hu | Multimerization and interaction of Toll and Spätzle in Drosophila<[END_REF][START_REF] Xu | Structural basis for signal transduction by the Toll/interleukin-1 receptor domains[END_REF][START_REF] Brennan | Drosophila: The Genetics of Innate Immune Recognition and Response[END_REF] 1.

Toll-like receptors (TLR)

Identification of Toll receptors in Drosophila opened new perspectives to understand the innate immune system, which was understudied in higher organisms in favour to the adaptive immune response. In deuterostomes, Toll-like receptors (TLRs), which are transmembrane proteins, were identified as the major PRRs that underwent purifying and diversifying selection, ranging from 222 TLR genes in sea urchin Strongylocentrotus purpuratus to 12 TLR in mouse [START_REF] Leulier | Toll-like receptors--taking an evolutionary approach[END_REF] , in order to adapt to a variety of coevolving pathogens. Among mammals, human encodes at least 10 TLRs. In contrast to Drosophila, where the Toll-dependent pathway is induced by Gram-positive and fungal pathogens, TLR in mammals are activated upon structurally variant PAMPs from different organisms and that constitute a large repertoire of microbial structures (Table 1). Depending on the sensed pathogen, TLRs activate intracellular signalling pathways that induce transcription of various defence factors, including inflammatory cytokines, chemokines, major histocompatibility complex (MHC) and co-stimulatory molecules 68 .

TLR activity require dimerization of LRR ectodomain that is proposed to bring together intracellular TIR domains, thus enabling activation of downstream signal transduction process [START_REF] Jin | Crystal structure of the TLR1-TLR2 heterodimer induced by binding of a tri-acylated lipopeptide[END_REF] . TLRs dimerization can be homo-and heterologous, and the variety of TLR dimer combinations increases their microbial sensing repertoire [START_REF] Medzhitov | Toll-like receptors and innate immunity[END_REF] . An example of this cooperation was demonstrated for TLR2 heterodimer with either TLR1 or TLR6, where the TLR2 partner determines the specificity of the ligand recognition [START_REF] Oliveira-Nascimento | The Role of TLR2 in Infection and Immunity[END_REF] . In response to microbial invasion, extracellular PAMPs or DAMPs can activate TLRs on the cell surface. However, TLRs can also be found in the intracellular compartment, where they are located in the membranes of endosomes and lysosomes. In particular, intracellular TLRs sense viral and bacterial nucleic acids during viral particles endocytosis and degradation in late endosomes or lysosomes [START_REF] Lee | Trafficking of endosomal Toll-like receptors[END_REF] . Moreover, it was suggested that the intracellular localization of these TLRs could enable discrimination between viral DNA and self-DNA. Lastly, secreted TLR (sTLR) were also described, e.g. sTLR2, which has been shown to arise from ectodomain shedding of the extracellular domain [START_REF] Langjahr | Metalloproteinase-dependent TLR2 ectodomain shedding is involved in soluble toll-like receptor 2 (sTLR2) production[END_REF] . Soluble form of receptor was found in blood and breast milk to inhibit inflammatory reaction. Such reaction is proposed to work in the way that sTLR2 could negatively regulate TLR2 activation by behaving as a decoy receptor [START_REF] Lebouder | Soluble Forms of Toll-Like Receptor (TLR)2 Capable of Modulating TLR2 Signaling Are Present in Human Plasma and Breast Milk[END_REF][START_REF] Cattaneo | Analysis of Toll-Like Receptors in Human Milk: Detection of Membrane-Bound and Soluble Forms[END_REF] .

Taken together, the TLR family serves mainly as direct PRRs for microbial sensing that mount innate immune responses as well as playing key role in linking innate with adaptive immunity [START_REF] Abreu | Innate immunity and toll-like receptors: clinical implications of basic science research[END_REF]68,[START_REF] Akira | Toll-like receptors: critical proteins linking innate and acquired immunity[END_REF][START_REF] Medzhitov | The Toll receptor family and microbial recognition[END_REF][START_REF] Takeda | TLR signaling pathways[END_REF][START_REF] El-Zayat | Toll-like receptors activation, signaling, and targeting: an overview[END_REF] .

Nucleotide-binding leucine-rich repeat receptors

Nucleotide-binding leucine-rich repeat receptors (NLRs) represent the major class of intracellular innate immune receptors found in both animals and plants (described below). In animals, the cytoplasmic detection system induced by NLRs was proposed to play a defence function in host tissues where TLRs are absent or expressed at low levels [START_REF] Viala | Nods and 'intracellular' innate immunity[END_REF] . This is the case for the intestinal epithelial cells, which are in constant contact with the microbial flora. Therefore, expression of TLRs is down-regulated in these cells in order to avoid high stimulation and aberrant inflammations due to the microbial Based on N-terminal domain composition, the NB-LRR proteins can be categorized as two types. The common core is composed of C-terminal LRR domain and a central NBS domain, whereas the variable N-terminal domains carry coiled-coil (CC) domain or a domain homologous to Drosophila Toll/human interleukin-1 receptor (TIR) [START_REF] Padmanabhan | The leucine-rich repeat domain in plant innate immunity: a wealth of possibilities[END_REF] (Figure 3A). These receptors mediate the activation of the mitogen-activated protein kinase (MAPK) pathway that in turn leads to increased transcription of pathogenresponsive genes, production of reactive oxygen species (ROS), all of which contribute to prevention of pathogen spreading [START_REF] Padmanabhan | The leucine-rich repeat domain in plant innate immunity: a wealth of possibilities[END_REF][START_REF] Chisholm | Host-microbe interactions: shaping the evolution of the plant immune response[END_REF] All three APL1 gene genes are comprised of a small 5' exon followed by a second longer exon separated by a short intron. The encoded proteins are characterized by an N-terminal signal peptide, a series of LRR motifs spanning ~300 amino acids and a coiled-coil domain at the C-terminus. In addition to common core sequence among the three genes, APL1C (and some allelic variants of APL1A) also carry an N-terminal repeated motif of the amino acids P-A-N-G-G-L (called PANGGL region), with an unknown function 107 106 .

Besides the common LRR domain, some of the other LRR genes in A. gambiae share a similar protein structure as the APL1 gene members and together constitute a subfamily of LRR immune genes, called leucine-rich repeat immune molecules (LRIM) 107 . Apart from LRR, these proteins include a coiled-coil domain and patterns of cysteine residues that give possibilities for disulphide bridges between two protein partners. The coiled-coil domain was proposed to drive or consolidate interactions such as combinatorial oligomerizations to promote the orientation of the cysteine residues for stabilizing the disulphide bridges. LRIMs also have a signal peptide with, for some members, a transmembrane domain, suggesting they are secreted into the mosquito hemolymph or exposed on cell membranes. The PANGGL domain present in APL1C and some APL1A allelic forms is exceptional for these proteins and was not found in any other mosquito protein 107 . The LRIM family can be classified in four groups: "Long" subgroup that includes APL1 genes, the "Short" subgroup, the Transmembrane (TM) LRIM and Coil-less subgroups. The "Long" and "Short" subgroups differ each other from the length of their LRR domain 107 . The variable LRRs domains among LRIMs form a stable arc or horseshoe-like fold that could facilitate protein interactions (Figure 5). The structure of LRIMs promotes genes interaction and was best studied in the case of APL1C, which forms a heterodimer with LRIM1 via interaction of their C-terminal coiled-coil domains and a single disulphide bond 108 . This dimerization is absolutely necessary for the antimalarial activity of the Anopheles complement-like protein, TEP1

(thioester-containing protein)

APL1 functional activity and the mosquito complement system

APL1C and LRIM1 form a heterodimer necessary for the antimalarial activity of the Anopheles complement-like protein, Thioester-containing Protein 1 (TEP1) 108,111 . The two other APL1 genes (APL1A and APL1B) also have the capacity to heterodimerize with the LRIM1 protein, suggesting that LRIM1 may act as a common core protein for different heterocomplex formation with APL1 as well as other LRR proteins, including the LRIM members 104 . This is consistent with the role of LRIM1 as an antagonist of both P. berghei and P. falciparum midgut infection, and also against Gram-negative bacteria 104,113,114 .

TEP1 is a structural and functional homolog of vertebrate complement factor C3 and of members of the α2-macroglobulin family (A2Ms) 115,116 .

In vertebrates, the complement system is composed of soluble and cell-membrane proteins, acting together in the cascade leading to pathogen clearance through their phagocytosis or membrane attack complex (MAC) formation. There are three complement pathways (Figure 6): i) the classical pathway, which is initiated by an antibody-antigen complex ii) the lectin pathway where the mannose or different sugar moieties present on the microbial surface are bound by mannan-binding lectin (MBL)

iii) the alternative pathway which is initiated by the spontaneous hydrolysis of the C3 factor. This pathway is either self-amplified on the surfaces of microbes or inhibited in the case of host self-surfaces. Despite distinct arms of pathogen recognition, all three pathways induce subsequent proteolysis events and converge to the central C3 factor.

Upon proteolytic cleavage, C3 produces anaphylatoxin C3a that recruits neutrophils and monocytes at the site of infection. This promotes inflammation and C3b opsonin inducing phagocytosis and/or downstream reactions with other complement factors, all ending with MAC formation (Figure 6) 117,118 .

Figure 6. Complement pathway activation and outcome in vertebrates.

In A. gambiae, the TEP1-mediated complement-like pathway is the best described immune effector mechanism. TEP1 is secreted into the hemolymph as a full-length protein before being cleaved to the active form. The cleaved TEP1 form called TEP1cut is stabilized in the hemolymph by the heterodimer LRIM1/APL1C to form a complex.

This interaction with the LRR heterodimer is necessary to maintain a functional thioester bond that can covalently attach to the parasite surface 119 . In the absence of APL1C or LRIM1, TEP1 is unable to specifically bind to the parasite surface, and deposits apparently non-specifically on self-tissues, the thioester bond being hydrolysed over time, resulting in non-functional precipitation of TEP1 109,110 . TEP1

was demonstrated to bind to different pathogens, including Gram-positive and Gramnegative bacteria and P. berghei ookinetes in mosquito midguts 115 , mediating their killing 120 . Like the APL1 gene family, TEP1 genes are highly polymorphic in A. gambiae genome with distinct alleles correlating with susceptibility or resistance to Plasmodium 115,121 . Variation of resistance and susceptible alleles are associated with variable loops within the thioester domain 119 .

Besides the interaction with TEP1, the APL1C-LRIM1 heterocomplex can also interact with other TEP family members, such as TEP3 and TEP4, indicating that LRIM members can form multiple distinct immune complexes 111 . Functional analysis A.

coluzzii detected a protective phenotype of TEP4 for P. falciparum but not rodent malaria species, whereas TEP3 displayed the inverse protective phenotype 104 . This protective specificity mirrors the distinct antagonistic activity observed for APL1A and APL1C proteins against P. falciparum and P. berghei, respectively.

Scope of the thesis

The phenotype of APL1 function in the anti-Plasmodium response has been described, but the molecular mechanism of activity is not known. The only structural mechanistic information is related to their ability to form, in the case of APL1C, a heterodimer with another LRR, LRIM1, which stabilizes the active TEP1cut protein. In addition, unlike LRIM1, which dimerizes with all three APL1 genes, APL1A and APL1C display a discriminating protective phenotype against human and rodent malaria parasites species, respectively. Consistently, a recent study revealed specificity in complementlike pathway activation towards Gram-negative bacteria through protease cleavage of the APL1C C-terminus in the LRIM1/APL1C complex 122 . Thus, LRIM1 which has the capacity to bind to the three APL1 genes, might constitute a common structural scaffold where activities directed towards distinct pathogens may be determined by the APL1 partner. Therefore, I postulate the following hypotheses:

1. APL1C might act as a pathogen specificity component in its heterocomplex with the common scaffold component LRIM1, which would explain how the complement-like effector activity of the otherwise nonspecifically-binding TEP1

protein is brought into proximity with the target pathogen surface.

2. Because APL1C is secreted into the hemolymph, APL1C could also display functional activity against free sporozoites in the hemocoel to limit Plasmodium invasion of the salivary glands and thus transmission.

3. APL1 proteins, similar to other LRR proteins, may act in signal transduction to initiate immune signalling cascades, and if so, the architecture of the pathways may be reflected at least in part by transcriptional regulation of target genes.

To examine these assumptions, I used as a study model the rodent malaria P. berghei and A. coluzzii mosquitoes, and thus focused on APL1C as a model system for the APL1 immune gene family.

III. RESULTS

APL1C protein is a pathogen binding factor for the midgut ookinete stage of Plasmodium

Blood feeding induces an extracellular layer of APL1C surrounding the midgut

The active, cleaved TEP1 form is bound in the hemolymph by the heterodimer LRIM1/APL1C to form a complex to allow specific deposition on the surface of the ookinetes exiting the mosquito midgut 115,109 . However, while TEP1 was detected on midgut ookinetes, the localisation of the LRR partners during this process is not known.

Therefore, I detected APL1C on mosquito midguts after a P. berghei-infected bloodmeal (IBM) 24 h post-feeding by immunofluorescence assay (IFA) on permeabilized midguts, using a polyclonal anti-APL1C antibody (pAb) 102 . Non-infected bloodmeal (NBM) and unfed (UF) midguts served as the controls (for the experimental design see Annex Figure S1). IFA followed by confocal microscopy analysis showed that while no APL1C signal was detected on UF midguts, a layer of APL1C protein surrounding the midgut epithelial cells was detected on both NBM and IBM midguts (Figure 7A). Quantitative and comparative analysis of the APL1C protein signal intensity between IBM, NBM and UF mosquito midguts confirmed significant statistical difference either between UF and NBM (p<0.0001), or between UF and IBM (p<0.0001) (Figure 7B). The comparison between IBM and NBM midguts was not statistically different (Annex, Table S1). I queried the exact APL1C positioning through reconstructed optical sections of confocal stack midgut images (Figure 7C, projected RESULTS

52

as orthogonal views on the right side and below the stack picture). This analysis revealed that APL1C protein was localised on the basal side of the midguts tissue.

The simplest interpretation is that the observed IFA midgut presence of APL1C is a proxy for the concentration of systemic APL1C in the mosquito hemolymph, which diffuses through the porous basal lamina 123 . This conclusion is strengthened by the similar localisation pattern detected using a diffusible dextran the size of APL1C

(Figure S2). I cannot eliminate the possibility that the midgut extracellular APL1C

detected after a bloodmeal could be specifically targeted to the midgut, although there is no known mechanism that would explain this. Thus, I conclude that mosquito blood feeding causes elevated levels of APL1C protein within the hemolymph, which can be conveniently measured using dissected midguts as a proxy assay that is simpler than perfusion of hemolymph from individual mosquitoes. The APL1C in the extracellular space surrounding the midgut epithelium could serve as part of an initial immune sentinel barrier. The specificity of the anti-APL1C pAb was confirmed on midguts collected from mosquitoes depleted for APL1C gene expression by RNAi-mediated gene silencing.

A. coluzzii mosquitoes were injected with double-stranded RNA of APL1C gene RESULTS

54

(dsAPL1C) or dsGFP (for control group) and blood fed 72 h post-treatment. APL1C

gene expression was efficiently silenced at 72 h post dsAPL1C treatment as compared to dsGFP-injected controls, measured by quantitative polymerase chain reaction (qPCR, Figure 8A). IFA analysis of the midguts 24 h after NBM revealed APL1C protein signal in dsGFP controls and no signal in APL1C-silenced midguts (Figure 8B).

Hence, the IFA signal observed on the mosquito midgut samples is specific for presence of the APL1C protein.

APL1C expression 72 h after dsAPL1C injection

normalized APL1C cDNA detection in "dsAPL1C" versus "dsGFP" treatments was computed using triplicates from the same cDNA dilution. Graph represents mean with ±SEM of the expression fold change between "dsAPL1C" and "dsGFP" control from two biological replicates (N=2). Data for qPCR analysis was analysed by unpaired t-test (significance level of t-test pvalue: ** p-value <0.01). B. Immunostaining analysis of NBM mosquito midgut after APL1C gene silencing reveals no APL1C signal on APL1C-silenced midguts. APL1C protein images are from midguts of dsGFP-injected control mosquitoes. The scale bar is 10 µm.

APL1C presence on the basal side of the midgut epithelium is microbiome independent

I showed that NBM is sufficient to cause presence of the APL1C protein on A. coluzzii midguts. Since mosquito blood feeding induces expansion of the bacterial flora [START_REF] Pumpuni | Bacterial population dynamics in three anopheline species: the impact on Plasmodium sporogonic development[END_REF] , I queried the role of the microbiome as a potential signal promoting elevated APL1C abundance on the midgut epithelium. Prior to a bloodmeal, two groups of mosquitoes were treated or not with a wide-spectrum antibiotic (ATB) cocktail. The ATB efficiency on the microbiome was confirmed by qPCR measuring bacterial ribosomal DNA (rDNA 16S) (Figure 9A). After the bloodmeal, IFA analysis showed that APL1C presence was still elevated on the midguts in the +ATB midguts group, and with an intensity similar to that of -ATB control group (Figure 9B), indicating the bacteria microbiome expansion post-NBM does not influence APL1C abundance detected on the midgut.

APL1C binds to Plasmodium ookinetes exiting the basal side of the midgut epithelium

Elevated hemolymph APL1C levels are induced by NBM, and are also present in the hemolymph within the midgut extracellular space delimited by the basal lamina.

Therefore, I assessed whether APL1C binds to Plasmodium ookinetes. IFA analysis on midguts collected 24 h post-IBM displayed APL1C signal on some parasites, but the majority of parasites were negative for APL1C (Figure 10 A and B "Merge" RESULTS 57 column). Overall, 18% of live (GFP) ookinetes present in the infected midguts were positive for APL1C (Figure 10C). In addition, APL1C occasionally labelled structures previously reported as stalk-form ookinetes 124 , but these structures were negative for GFP (Figure 10C). It suggests that these GFP-negative forms were probably undergoing lysis, and GFP protein leaked from dead parasites. This is consistent with the description of mosquito complement leading to parasite lysis and previous observations, in which parasite ookinetes labelled by TEP1 at 24 h post-infection were found both, live (GFP-positive) and dead (GFP-negative) 115 125 . APL1C labelling localises with dead ookinetes in mosquito midgut. Immunostaining analysis RESULTS

58

of mosquito midgut infected with GFP-expressing parasites (green) at 24 h post-infection. The APL1C staining reveals APL1C protein signal (red) with a shape related to ookinete structure but where GFP signal from the parasite is lacking, probably due to parasite lysis. Note nucleus staining in the DAPI + phalloidin channel. The scale bar is 2 µm.

Ookinete traversal through the midgut epithelium is a dynamic process, and 24 h after IBM the majority of parasites are still found in the blood bolus, while some are intracellular and only a minority have exited from epithelial cells 126 . Despite permeabilization of the midgut tissues during the IFA analysis, only 18% of GFPpositive parasites were APL1C-labeled. An additional control was performed using anti-GFP antibody which labelled 93% of parasites in the midguts, confirming efficient permeabilization and antibody access within the tissue (Annex, Figure S3). Therefore, I determined the localization (apical and/or basal) of APL1C-labelled parasites on the midgut epithelium. Reconstructed optical sections of the confocal stack images revealed that APL1C-labeled parasites were strictly located at the basal side of the midgut epithelium (Figure 11A). In contrast, the ookinetes that were crossing or that remained on the apical side of the midgut epithelium lumen were not labelled with APL1C (Figure 11B). This result is consistent with the 18% APL1C-labeled parasites, as it was reported that between 24 and 25 h post-infection, around 15% of them reach the basal lamina 126 .

LRR proteins bind autonomously to the ookinete surface (coll.: C. Lavazec, Institut Cochin, Paris)

As APL1C has been shown to act in a heterodimeric complex with LRIM1 109 , we wished to determine whether LRIM1 could also be detected on the ookinete surface.

We developed a powerful ex vivo model of mosquito hemocoel immunity using the 4a3A hemocyte-like cell line. Cells were transfected to express, either separately or RESULTS 60 simultaneously, V5-tagged LRIM1 (V5-LRIM1) or V5-APL1C (used as positive control for the binding). After verifying that both V5-APL1C and V5-LRIM1 protein constructs were secreted at day 3 post transfection from hemocyte-transfected cells in the medium (Annex, Figure S4) we investigated their labelling on fluorescent-GFP parasites. To validate the ex vivo system, we phenocopied APL1C binding to the parasites on the midgut epithelium observed in vivo. Transfected cells were exposed to A. coluzzii midguts infected with P. berghei (24 h post-IBM) and we found that V5-APL1C as well as V5-LRIM1 were co-localized with parasites (Figure 12A). The V5-RFP-transfected proteins, used as negative control, displayed no labelling on the GFP parasites (Figure 12A), although as expected it was secreted into the medium (Annex,

Figure S4

). In addition to validation of the in vivo system, these results indicated that as for APL1C, the subunit partner LRIM1 also binds to the parasite, and in similar proportions for V5-APL1C or V5-LRIM1-labelled parasites (12% and 10% respectively) (Figure 12B). Interestingly, the proportion of labelled parasites did not increase in cells co-transfected with both tagged-LRRs (11%) as compared to the single transfected treatments (Figure 12B). This observation is consistent with but does not prove that labelled parasites are bound with LRIM1/APL1C heterodimers.

To distinguish extracellular ookinetes from those that were still within the lumen or epithelial cells, we immunostained non-permeabilized infected midguts using P.

berghei-specific Pbs28 antibody. Only 18% of the GFP ookinetes were labelled with the Pbs28 antibody (Figure 12B), indicating those that reached the basal side of the midgut at 24 h post-IBM. We then tested whether APL1C and LRIM1 parasite binding is dependent on the presence of TEP1 protein. Cells were transfected to express V5-tagged APL1C and/or V5-tagged LRIM1 as above, but with TEP1 gene expression silenced (dsTEP1 or dsGFP as control). Depletion of TEP1 protein was confirmed by Western blot using an anti-TEP1 antibody (Figure 13A). A. coluzzii midguts collected 24 h post-infection were incubated in medium from transfected cells. Depletion of TEP1 did not alter the proportion of V5-LRR-labelled parasites as compared to the dsGFP controls, whether APL1C and LRIM1 were expressed individually or simultaneously (Figure 13B). These results indicate that while TEP1 requires at least APL1C or LRIM1 for specific parasite binding, the reciprocal is not true, suggesting that TEP1 binding on the parasite must occur indirectly and secondarily, mediated by LRR binding to the parasite surface. S1). These results indicate that phagocytic hemocytes are required both for APL1C gene expression as well as normal APL1C protein levels in the mosquito hemolymph. S1), and if individual replicates showed a common trend of change, individual p-values were combined using the meta-analytical approach of Fisher (significance level of Fisher-combined p-value: ** p-value <0.01).

Nitration pathway activity is required for full APL1C abundance in hemolymph

RESULTS

65

The release of microvesicles by mosquito hemocytes appears to be correlated with the deposition of TEP1 upon the ookinete surface, because depletion of the nitration pathway simultaneously abolished release of hemocyte-derived microvesicles (HdMv)

and impaired TEP1 binding to the parasites 128 . This observation led to the hypothesis that factors delivered by HdMv may promote TEP1 binding to ookinetes, although the contents of the HdMv are unknown. APL1C is expressed in hemocytes and its presence is required for TEP1 binding to parasites. Therefore, I evaluated whether APL1C could be a component of the HdMv payload to deliver APL1C into the hemolymph and ultimately to the midgut surface.

First, APL1C subcellular localization was determined by IFA with APL1C antibody on perfused hemocytes and on 4a3A hemocyte-like cells, revealing that APL1C protein is found in vesicle-like structures in perfused hemocytes (Figure 15A). This observation is consistent with our previous report of localization of APL1 family gene APL1A within hemocyte vesicles 106 and with the hypothesis that APL1C may be secreted from hemocytes in microvesicles. Next, the nitration pathway was inactivated by cosilencing the genes for heme peroxidase (HPX2) and NADPH oxidase 5 (NOX5), with the aim to inhibit the release of HdMv. Mosquitoes were treated with dsNOX5/HPX2 or control dsGFP prior to an IBM, and the efficiency of HPX2 and NOX5 depletion was confirmed by RT-qPCR. (Figure 15B).

Midguts from each group were collected 24 h after Plasmodium infection and APL1C abundance on the midgut was quantified using IFA with APL1C antibody. Midguts from mosquitoes depleted for NOX5/HPX2 displayed decreased APL1C abundance as compared to dsGFP treated controls (p<0.0001) (Figure 15C and Annex Table S1).

Western blot analysis of extract from whole mosquitoes confirmed that the observed phenotype did not result from APL1C protein decrease after inhibition of the nitration RESULTS 66 pathway, and in fact APL1C protein was slightly increased in silenced mosquitoes as compared to dsGFP controls (Figure 15D), which could be explained if APL1C protein is retained in non-released HdMv. Overall, these results indicate that an active nitration pathway is necessary for wild-type levels and localization of free APL1C in the hemolymph, as measured by APL1C abundance captured on the midgut.

APL1C protein is a pathogen binding factor for the hemocoel sporozoite stage of Plasmodium

Sporozoites affect APL1C protein abundance

Only a small proportion of the thousands of sporozoites released by each oocyst invade the salivary glands, while the majority of sporozoites are destroyed in the mosquito hemocoel by an unknown mechanism [START_REF] Hillyer | Efficiency of salivary gland invasion by malaria sporozoites is controlled by rapid sporozoite destruction in the mosquito haemocoel[END_REF] . Phagocytosis of sporozoites by hemocytes was observed, but was numerically insufficient in itself to explain sporozoite clearance from the hemocoel. Thus, the mechanism of sporozoite destruction in the hemocoel remains unknown.

To examine the activity of APL1C against released sporozoites in the hemocoel, the protein was dependent only on the bloodmeal and not infection (Figure 16). At 10 d and 12 d post-bloodmeal, APL1C abundance in both IBM and NBM mosquitoes was equivalent to the UF controls, indicating that APL1C levels return to baseline after the effect of the bloodmeal decays. Notably, at 18 d post-bloodmeal during sporozoite release, APL1C protein abundance was significantly higher in IBM as compared to either NBM or UF mosquitoes, which were not different from each other (Figure 16).

The APL1C increase at 18 d post-IBM indicates that APL1C induction at this time point was dependent only on the presence of circulating sporozoites. This result suggests that APL1C is a component of immune signalling responding to free sporozoites, and could help to limit salivary gland invasion and thus transmission of Plasmodium.

APL1C activity in the hemocoel limits sporozoite invasion of salivary glands

Based on the APL1C protein increase in mosquitoes at the time of high sporozoite release at 18 d post-IBM, APL1C was tested for a protective role against sporozoites.

Mosquitoes were treated with dsAPL1C or control dsGFP at 9 d post-IBM, approximately 3 d before the beginning of sporozoite release (experimental design, S2). There was no effect on infection intensity, that is, the numbers of sporozoites in positive glands (Annex, Table S2). Thus, APL1C activity controls the efficiency of sporozoite invasion of salivary glands, and therefore should influence vector competence for parasite transmission. Prevalence from each replicate was compared between the two conditions by chi-square test.

All statistical differences were first tested independently within replicates (individual p-values in Annex Table S2), and if individual replicates showed a common trend of change, individual p-values were combined using the meta-analytical approach of Fisher (significance level of chi-square **** p-value <0.0001).

RESULTS

71

APL1C binds to free Plasmodium sporozoites in the mosquito hemolymph

The simplest model to explain APL1C inhibition of sporozoite invasion into the salivary glands is similar to the above proposed model for ookinete immunity, where LRR proteins recognize and bind to the pathogen, then recruiting the TEP1 effector for lysis of the cell. Therefore, we tested whether APL1C binds directly to sporozoites.

Sporozoites were perfused from IBM mosquitoes at 17 d post-IBM and IFA was performed using APL1C antibody. The majority (97%) of sporozoites were labelled with APL1C antibody (Figure 18A andB), indicating that APL1C protein binds to sporozoites in the mosquito hemocoel. As a control, 2 of 210 sporozoites perfused from APL1C-silenced mosquitoes were detectably labelled with APL1C antibody (Figure 18C andD). These results demonstrate that APL1C protein binds to free sporozoites in the hemolymph, which is consistent with its protective activity against salivary gland infection shown above.

RESULTS

APL1C protective activity against sporozoites does not require the complement proteins TEP1 or TEP3

For killing of rodent Plasmodium midgut ookinetes, it was previously shown that a physical complex of the APL1C-LRIM1 heterodimer with either one of the thioester proteins TEP1 or TEP3 is required 104,111 . Therefore, the role of TEP1 and TEP3 in APL1C-mediated sporozoite protection was queried. Expression of TEP1 and TEP3 S2), and if individual replicates showed a common trend of change, individual p-values were combined using the meta-analytical approach of Fisher (significance level of chi-square: n.s.=not significant).

Implication of the APL1 LRR family in immune signal transduction

APL1C binds to both ookinete and sporozoite parasite stages, and appears to be a component of pathogen sensing for free sporozoite presence in the hemocoel. APL1C may generate signals leading to the expression of additional downstream immune factors. To test the hypothesis that APL1 family proteins lead to downstream immune signalling, a transcriptomic analysis using RNA sequencing (RNAseq) was carried out to detect the transcriptional effects of APL1A and APL1C activity (Figure 20). Because the phenotypes of each gene are largely mediated by different immune pathways 103,102 , it was expected that the transcriptional effects of each gene would be different.

APL1A and APL1C gene silencing in A. coluzzii

The APL1 genes are characterized by their exceptional genetic diversity observed in wild mosquitoes as well as in the lab-reared colonies 105,106 . This genetic variability within each gene include gene insertion-deletions 106 , and variants in the region targeted for gene silencing using dsRNA could affect silencing efficiency. Therefore, I identified the potential APL1A and APL1C variants segregating in the studied mosquito colony (Fd03) to verify that they are sensitive to the designed dsAPL1A and dsAPL1C fragments targeting the gene 3'UTRs 102,103 . 3' Rapid Amplification of cDNA Ends (3' RESULTS 76 RACE) was used to sequence APL1A and APL1C 3'UTR variation. Five different APL1A 3' variants were identified, and all of them overlapped and would be sensitive to the designed dsAPL1A fragment (Figure 21A). Among 22 sequenced clones, 18 represented one major structural variant with 8 bp and 9 bp insertions compared to the reference sequence, resulting in a shifted stop codon (stop codon depicted as 'TAG' on Figure 21A). Another variant (1 clone) lacked a stop codon. A third variant included two deletions of 308 bp and 15 bp, as compared to the reference sequence, which also shifted the stop codon. This variant also displayed a 9 bp insertion after the stop codon.

The two remaining other variants are the closest to the reference sequence, with a stop codon located at the same position.

For APL1C, over 31 sequences analysed, 4 different structural variants were identified.

All of them overlapped with the dsAPL1C fragment (Figure 21B). All variant cases encoded the stop codon in the same place as the reference sequence (Figure 21B).

The differences between the variants were observed in the 3'UTR region. These differences included insertion-deletion events as compared to the reference sequence (Figure 21B). Thus, sequence analysis indicated that all APL1A and APL1C gene variants identified in the Fd03 colony used in this study should be efficiently targeted by the synthesized dsAPL1A and dsAPL1C fragments.

Kinetics of APL1A and APL1C silencing

The next step was to establish the correct time point(s) after gene silencing to collect samples for RNAseq. Ideally, as depicted in Figure 22, it would be the best to capture the first layer of the genes affected by APL1A and APL1C silencing and avoid the subsequent layer(s) of indirectly affected genes and secondary effects. Collecting the samples at latter time points (red arrow, Figure 22) would increase the number of In order to determine the optimal time to harvest RNA for collecting mosquitoes after gene silencing, pools of eight mosquitoes were collected at 6, 12, 24, 30, 48 and 72 h for each treatment (dsAPL1A, dsAPL1C and dsGFP). Efficiency of APL1A and APL1C transcript silencing was measured by qPCR and determined as expression fold change of the dsGFP control group. Silencing of APL1A was efficient already at 6 h with 70% of transcript decrease. For the next time points (12, 24, 30, 48 and 72 h posttreatment), APL1A transcript was further decreased to at least 90% below controls (Figure 23A). For APL1C transcript levels were decreased by 90% at 6 h post-dsRNA treatment, which persisted until 72 h post-treatment. Therefore, I screened earlier time points post-dsAPL1C treatment (0, 1, 2 and 4 h), in order to test how the silencing efficiency evolved. The results illustrated in Figure 23B showed that the major effect of gene silencing occurred 1-2 h after dsRNA treatment. APL1C protein levels were also measured at the same time points. Pools of eight mosquitoes were collected at 6, 12, 24, 48 and 72 h post dsRNA and proteins extracted from mosquitoes were quantified by Western blot. (depicted as a dotted line), measured by densitometry. GAPDH density signal was used to normalize APL1C signal in both "dsGFP" and "dsAPL1C" treatments, and the normalized APL1C signals were then compared between "dsAPL1C" and "dsGFP" conditions.

RESULTS

The amount of APL1C protein decreased by 50% at 12 h post-dsRNA and more than 90% reduction at 48 and 72 h as compared to dsGFP controls (Figure 24). It was estimated that 50% protein reduction at 12 h post-dsRNA treatment should be appropriate to identify the more proximal gene expression affected by APL1C silencing. The protein analysis could not be conducted for APL1A protein because of the absence of specific antigen targets for APL1A antibody production. However, analysis of the transcript level showed that APL1A silencing was as efficient as APL1C at 12 h post-dsRNA treatment (Figure 23A). Taken together, for both APL1A and APL1C silencing, I decided to collect mosquito RNA samples at 12 h post-dsRNA treatment, as the earliest time-point that would preferentially capture the most proximal response genes to APL1 depletion. Four independent biological replicates were performed, where mosquitoes were injected with dsAPL1A, dsAPL1C or dsGFP as control. For each replicate, total RNAs were extracted from a pool of eight collected APL1C protein level after dsAPL1C injection females, at 12 h post-dsRNA treatment. APL1A or APL1C silencing efficiency was confirmed in each replicate by qPCR analysis (Figure 25A andB). In addition, APL1C protein decrease in dsAPL1C-injected mosquitoes was confirmed by Western blot analysis (Figure 25C). expression is silenced 12 h post dsAPL1A treatment. APL1A silencing was verified by qPCR measurement between dsAPL1A and dsGFP (dotted line) treatments. The ratio of the normalized APL1A cDNA detection in "dsAPL1A" versus "dsGFP" treatments was computed using triplicates from the same cDNA dilution. Graph represents mean with ±SEM of the expression fold change between "dsAPL1A" and "dsGFP" control from four (N=4) biological replicates. B. APL1C expression is silenced 12 h post dsAPL1C treatment. APL1C silencing was verified by qPCR measurement between dsAPL1C and dsGFP (dotted line) treatments.

The ratio of the normalized APL1C cDNA detection in "dsAPL1C" versus "dsGFP" treatments was computed using triplicates from the same cDNA dilution. Graph represents mean with ±SEM of the expression fold change between "dsAPL1C" and "dsGFP" control from four (N=4) biological replicates. A and B data for qPCR analysis was analysed by unpaired t-test (significance level of t-test p-value: **** p-value <0.0001). C. APL1C protein level is decreased by more than 50% at 12 h post dsAPL1C treatment. The graph represents the level of APL1C protein in dsAPL1C-injected mosquitoes normalized with the dsGFP control (depicted as a dotted line), measured by densitometry. GAPDH density signal was used to normalize APL1C signal in both dsGFP and dsAPL1C treatments. Graph represents mean with ±SEM from four biological replicates (N=4). Data were analysed by Image Lab 6.0.1 and statistically analysed by unpaired t-test (significance level of t-test p-value: *** p-value <0.001).

RNAseq and bioinformatic analysis

Differentially expressed genes were identified bioinformatically (see Materials and Methods). Results of the differential analysis are presented graphically as volcano and 2. As depicted on the volcano plot, the comparison between dsAPL1A and dsGFP highlighted surprisingly only one candidate gene displaying a statistically significant modulated expression upon APL1A gene depletion (Figure 26A). Overall, the mosquito transcriptome was nearly non-affected by the lack of APL1A. In contrast, depletion of APL1C at the same time point highly influenced mosquito transcriptome profile, with gene candidates that were statistically significantly down-or upregulated (Figure 26B). MA-plots for both tested conditions display similar profile among tested conditions (Figure 27). Nevertheless, APL1C depletion influenced the expression of a greater number of genes than APL1A depletion (Figure 27B). The only candidate gene from APL1A depleted mosquitoes encodes "defective in cullin neddylation protein" (AGAP002513). Among APL1C-downregulated and upregulated gene candidates, 112 and 154 genes have an annotated function, respectively (Annex, Table S4 and Table S5).

A B

qPCR validation of the RNAseq gene candidates.

The APL1C gene candidate gene targets revealed by the RNAseq experiment were tested by qPCR analysis. Candidates with adjusted p-values<0,05 and log2 foldchange (log2FC) cut-off of -1 (16 genes) and log2FC cut-off of 0,87 (27 genes), for down-and upregulated genes, respectively, were tested. Results showed that the expression of tested genes correlated between RNAseq and qPCR experiments (p<0.0001 Figure 28), thus validating performed RNAseq analysis.

APL1C controls expression of immune-like genes in the mosquito

The 423 genes significantly affected by APL1C depletion were each screened for encoded protein domains displaying immune-like function, such as LRRs [START_REF] Riehle | Natural malaria infection in Anopheles gambiae is regulated by a single genomic control region[END_REF]104,110 , TEPs 104,111,120,131 , CLIP-serine proteases [132][133][134][135] , serine proteases inhibitors (serpins) 136,137 , ankyrin repeats 138 , immunoglobulins 139 , heme peroxidase 140,141 and angiotensin-converting 142-145 . Among the downregulated genes, 22 genes encodes for such immune-like domains (Table 3), whereas 6 genes were identified with such domains among the up-regulated genes (Table 4). Interestingly, within 22 downregulated-immune-like genes, I identified nimrod B2 and Scavenger receptors coding genes, both being implicated in phagocytosis in mosquitoes 146,147 .

IV. DISCUSSION

Dual functionality for APL1C as guard and PRR-like factor

The LRR APL1 proteins are the key components of the mosquito defence against Plasmodium infection [START_REF] Riehle | Natural malaria infection in Anopheles gambiae is regulated by a single genomic control region[END_REF]102,103 . However, little was known about the mechanism of APL1 function in mosquito anti-Plasmodium defence. This thesis work showed that APL1C can bind to both Plasmodium ookinetes and sporozoites and thus acts as a pathogen binding factor. Therefore, I propose that APL1C could behave as a PRR in heterocomplex with LRIM1 for initiating complement-like cascade via TEP1cut stabilization and binding to the parasites at least in mosquito midgut, which probably elicit a signalling pathway, as shown that APL1C controls the expression of several genes in A. coluzzii. In addition, it was observed that APL1C presence on the mosquito midguts was not restricted to the parasite surface, as it could form hemolymphoriginated, extracellular layer on the basal side of the midgut epithelial cells. The APL1C protein level is induced by the bloodmeal independently from the presence of the parasite, which suggests that APL1C acts as a guard protein in mosquito hemolymph, where beneath basal lamina of the midgut, it could form a state of immune readiness to face Plasmodium and probably other potential microbes that may emerge from the blood-engorged midguts. The bloodmeal thus constitutes a generalized signal that induces APL1C and other immune factors that may recognize a large range of blood borne potentially pathogenic microbes. In the case of the malaria parasites, when the ookinetes traverse the midgut epithelium and reach the basal side of the cells into the extracellular space, APL1C appears ready to "catch" the parasites through a binding process for blocking their further development. 151,152 . However, the most intriguing resemblance with the APL1C-LRIM1 LRR protein complex is the jawless vertebrate VLRB proteins. They are secreted LRR-antibody-like receptors inducing the classical-complement cascade [START_REF] Sutoh | The immune system of jawless vertebrates: insights into the prototype of the adaptive immune system[END_REF] and circulate as disulphide-bridged multimers 153 . Therefore, the combinatorial immune LRR protein complexes could constitute a repertoire of antibody-like structures in Anopheles mosquitoes for facing distinct microbial infections.

The HdMvs, a source of secreted APL1C, mediated by the nitration pathway?

Phagocytic hemocytes represent more than 80% of total hemocytes in mosquitoes 154,155 and were reported to affect TEP1 binding to the ookinete on infected midguts 127 . Presented results demonstrated the important role of the phagocytic cells as a source of APL1C expression. APL1C proteins, which are expressed in hemocytes, and especially in phagocytic hemocytes, are localized in cytoplasmic vesicles. This suggests that, consistent with the presence of a signal peptide on its protein sequence, APL1C is secreted through this vesicle structure. Nitration has been shown to control release of hemocyte-derived microvesicles (HdMv) that were proposed to transport key factors mediating subsequent TEP1 binding and lysis of ookinetes 128 . It was found that silencing the nitration pathway, and thus inhibiting the release of HdMv, also reduced APL1C abundance in the midgut extracellular space, strongly suggesting that AP1C may be part of the payload of HdMv. To demonstrate this assumption, one possibility would be to physically isolate and collect these HdMvs and perform either a proteomic study or, more directly, a Western blot analysis using anti-APL1C antibody.

APL1C presence in hemolymph at the basal side of the midgut epithelium is not PAMP dependent

Nitric oxide (NO) production was correlated with Plasmodium ookinete invasion of the midgut epithelium 156 and was described as mediating protein nitration of ookineteinvading epithelial cells ('Time Bomb' model) 157 . Activation of the nitration pathway leads to ookinete tagging as a danger (or non-self) signal, which promotes the activation of the mosquito complement cascade 140 . This suggests that activation of the immune response in mosquito is not initiated by Plasmodium PAMP but by parasiteinduced tissue damage signals (DAMP) such as nitration. In line with this assumption, a study showed that TEP1 binds damaged sperm cells in a male mosquito in nitration pathway-dependent manner 158 . In the case of APL1C, presented results showed that a non-infected bloodmeal (NBM) also induced APL1C protein levels in mosquito.

Because bloodmeals increase the abundance of the bacterial flora [START_REF] Pumpuni | Bacterial population dynamics in three anopheline species: the impact on Plasmodium sporogonic development[END_REF] , I tested whether the enteric microbiome can induce elevated APL1C levels in the hemolymph, the source of the APL1C protein measured by IFA on dissected midguts. However, a similar abundance of APL1C protein between ATB-treated and control midguts groups, ruled out the microbiome as potential signal elicitor leading to increased APL1C protein level. Therefore, an alternative hypothesis for this signal would be related to the mechanical stretching of the midgut induced by the bloodmeal, which could damage the cellular integrity of the epithelium. To test this hypothesis, we could perform a blood-free feeding that would mimic the mechanical distension of the midgut epithelium and assess APL1C presence on the midgut epithelium.

Another possibility for the induction signal would be related to the physiological stress induced by bloodmeal chemical components or metabolites. Digestion of vertebrate haemoglobin results in the production of large amounts of free heme, a cytotoxic molecule that generates reactive oxygen species, which can disrupt phospholipid bilayers of cell 159 . Thus, the oxidative stress induced by the bloodmeal could serve as a danger signal, inducing the presence of LRR protein in the hemolymph, which diffuses through the porous basal lamina into the extracellular space around the midgut.

Taken together, knowing that APL1C presence on the midgut in the absence of Plasmodium is even not microbiome-related strengthens the hypothesis of a PAMPindependent source of signal to induce APL1C secretion in the hemolymph.

The sophisticated sporogony control by APL1C

Little attention has been paid on the mosquito immune response against the last stage of Plasmodium development, which are the sporozoites. My results showed that APL1C protein binds to the released sporozoites in the hemolymph, and more importantly, it also controls sporozoite infection prevalence in the salivary glands. The temporal behaviour of APL1C protein during sporogonic development appeared consistent with its immune functionality against the ookinete and the late sporozoite stages. APL1C protein levels were unchanged at the time corresponding to the oocyst stage, suggesting that it is not active against this parasite stage. This is consistent with other reports that the oocyst stage does not seem to stimulate immune responses.

Indeed, oocyst surface proteins such as laminin are in fact mosquito host-derived factors [START_REF] Smith | Plasmodium oocysts: overlooked targets of mosquito immunity[END_REF] , and these could hide the oocyst from the immune system recognition. The oocyst acquires metabolic resources from the mosquito for its enormous growth and internal cell divisions to generate thousands of sporozoites, however this appears to occur quietly from an immune perspective, until oocyst rupture. Therefore, potential inflammatory responses or cell apoptosis leading to DAMPs production are probably not prominent during the oocyst stage.

In addition, thesis results showed that APL1C protective function against the sporozoites does not involve the same factors as operate against the ookinete stage.

TEP1 and TEP3 that were both reported to control P. berghei ookinetes and to interact with the APL1C/LRIM1 complex 104,111 are not involved in protection against sporozoite salivary gland invasion. However, I cannot rule out that the control of sporozoites in collaboration with APL1C would require other TEP factors. In addition, it has been reported that unlike to the ookinete that harms the midgut epithelial cells, this is not likely the case for the sporozoites on the salivary gland epithelium as neither NOS increase, nor apoptosis has been reported 137 . Finally, a low proportion of phagocytized sporozoites was observed [START_REF] Hillyer | Efficiency of salivary gland invasion by malaria sporozoites is controlled by rapid sporozoite destruction in the mosquito haemocoel[END_REF] , suggesting that the phagocytic cells are activated during sporozoite release, and this activation might contribute to APL1C release in the hemolymph. Taken together, additional work is still needed to fully elucidate the killing mechanism of the sporozoites induced by APL1C.

Whole transcriptome analysis reveals differential signalling function of APL1 genes

Genomic and evolutionary studies revealed that immune-related genes and especially microbial-sensor coding genes such as PRR evolve faster than other insect genes 160- 162 . The APL1 gene family underwent an expansion from a single ancestral gene to three genes in the lineage of African Anopheles 163 . The expanded APL1 genes acquired distinct immune activities, as exemplified by functional differences in anti-Plasmodium responses 103 . My RNAseq data analysis of APL1A and APL1C silencing treatments revealed distinct profiles of downstream-modulated genes. While depletion of APL1A expression did not induce differences in overall transcriptome, APL1C depleted treatment led to high number of modulated genes. Interestingly, APL1C

appears to be orthologous to the ancestral single APL1 gene of Anopheles 163 .

Therefore, it should likely still display the more ancestral APL1 functions, while the APL1A and APL1B paralogs are derived forms and evolved new functions. APL1C might protect against a broader spectrum of microbes as compared to, for example, APL1A, which could respond to a more specialized microbial profile. Consistently, functional studies revealed that, in addition to the rodent malaria parasites, APL1C

protects against E. coli bacteria 122 .

Even though my thesis did not concentrate on the allelic variation of each gene, my 3' RACE sequencing study of APL1A and APL1C identified allelic variants. It was previously reported that among distinct APL1A alleles segregating in the Ngousso A.

coluzzii colony, only the APL1A 2 allele was associated with the protective phenotype of APL1A in P. falciparum challenge experiments 106 . My RNAseq experiment used the Fd03 colony, which has not been tested in a similar association study. Therefore, it cannot be excluded that current Fd03 colony may not carry the APL1A

V. CONCLUDING REMARKS AND FUTURE

My thesis work gave insight in the function of LRR proteins in A. coluzzii mosquito.

Focusing on the antimalarial APL1C gene as a representative of immune LRR family member, my results showed that it acts as pathogen binding factor in the mosquito hemolymph. I present evidence that APL1C and LRIM1 are directly associated to the Plasmodium ookinete surface, that APL1C binding to the parasite requires activity of the nitration pathway and the participation of phagocytic hemocytes. In addition to limiting the midgut stage of infection, presented results revealed that APL1C binds to the surface of free sporozoites in the hemocoel, and is required to limit salivary gland infection by sporozoites. These results are consistent with a model in which APL1C

protein acts as a pathogen recognition factor released from hemocytes at elevated levels following a bloodmeal (Figure 29), diffuses in the hemolymph to form a protective layer in the midgut basal extracellular space and also protects the open systemic compartment from microbes (such as sporozoites) escaping the epithelial barrier of the midgut. APL1C release after a bloodmeal is triggered by nitration that could function as a DAMP. The bloodmeal induction of APL1C creates a state of immune readiness on the midgut epithelium against microbes ingested with the blood that could infect the mosquito. Furthermore, APL1C appears to be an active recognition factor in the hemolymph, where it binds to sporozoites and apparently tags them for killing by unknown effectors. Assuming that as PRR-like factors APL1 genes might elicit a signal transduction pathway, I performed a RNAseq analysis to identify the downstream factors of APL1A and APL1C. Consistently with their distinct activity, the results revealed distinct transcriptomic profiles between both genes. These results are consistent with the hypothesis that mosquito immune LRR proteins are functional counterparts of the immunoglobulin-based receptors that vertebrates use for antigen recognition, although the parasite surface ligands remain unknown.

Lastly, it would be interesting to enlarge these findings to other members of the LRR family and assess the pathogen-specificity of their combinatorial binding property, as this family could represent the first secreted LRR pathogen recognition factors in the invertebrates.

Mosquito feeding on non-infected mice or P. berghei-infected mice

For all the experiments, P. berghei-infected mice were used at 4-8% parasitemia, with mature gametocytes. Exflagellation tests were performed to evaluate the maturity of male gametocytes. First, both non-infected and infected mice were anesthetized by intraperitoneal (IP) treatment of ketamine (Imalgene 1000 at 125 mg/kg) and xylazine (Rompun 2% at 12.5 mg/kg), then mosquitoes were allowed to feed on the anesthetized mice for 20 min. Unfed mosquitoes were discarded and fed mosquitoes were maintained at 21°C and 70% relative humidity on 10% sucrose solution as previously described 103 .

Midguts immunofluorescence assay (IFA)

Immunostainings were performed as previously described 128 . Briefly, mosquitoes were subjected to P. berghei-infected bloodmeal (IBM), non-infected bloodmeal (NBM) or 10% sucrose solution (unfed, UF) and incubated at 21°C. 24 h after, midguts from each condition were dissected in sterile 1× PBS, fixed for 40s in 4% paraformaldehyde for easier removal of the blood and opened longitudinally in sterile PBS to remove the blood bolus. Cleaned midguts were then fixed in 4% paraformaldehyde in 1× PBS for 1 hour at room temperature and rinsed five times in sterile PBS for 5 minutes each. In a next step, midguts were permeabilized, and blocked in PBT (PBS supplemented with 1% bovine serum albumin (BSA) and 0.1% Triton X-100) for 2 h at room temperature.

Midguts were then incubated overnight with a rabbit polyclonal anti-APL1C antibody (pAb) 102 (1:600 in PBT) at 4°C. The next day, midguts were rinsed five times (10 min each) with PBT, followed by a 2-hour incubation at room temperature with Alexa Fluor 647-conjugated anti-rabbit IgG secondary antibody (Thermofisher) (1:500 in PBT) at room temperature. Then, midguts were rinsed five times in PBT (10 min each).

Immunostained tissues were counterstained for 10 min with 405 phalloidin-iFluor (actin, 1:1,000 abcam) and subsequently for 10 minutes with DAPI (nuclei, 10 μg/ml, Thermofisher). All incubations were performed with 12 rpm rocking. Lastly, tissues were rinsed in sterile PBS and mounted in Vectashield (Vector Laboratories). Antibody accessibility to whole midgut tissue (permeabilization control) was performed as described above, using anti-GFP Alexa Fluor 647-conjugated primary antibody (Thermofisher).

Confocal Microscopy

Midguts where APL1C signal was subjected for quantitative analysis were imaged on a laser-scanning confocal microscope (LSM700, Carl Zeiss Jena

Image analysis

Images were analysed with Fiji 167 . 3D Images were filtered first with a 3x3 median filter then with a Gaussian filter with sigma=0.7 pixels. The 3D stacks were then projected using Maximum Intensity Projection. A selection was created using an intensity threshold using ImageJ 'default' method. Finally, Figure 7B, Figure 14C and Figure 15C report the mean intensity for the channel APL1C in the selection.

Dextran injection

Using a Nanoject II injector (Drummond Scientific), cold-anesthetized A. coluzzii females were injected intrathoracically with 138 nl of 70 kD dextan 488-conjugate of concentration 10 mg/ml. 1,5 h post-injection, midguts were dissected, fixed and counterstained with DAPI and phalloidin as described above. Injections were performed with a glass capillary needle as previously described 102,168 .

Plasmids construction

APL1C and LRIM1 alleles were amplified by PCR from A. coluzzii Ngousso mosquitoes using the primers flanking the coding regions of each gene (Table S6) and cloned into a dual His-and V5-tag insect expression vector (pAc5.1 V5-His, Invitrogen). To generate a plasmid control, RFP (Red Fluorescent protein) coding sequence from the mammalian expression vector pTagRFP (Evrogen) was cloned in the pAc5.1 V5-His expression vector using EcoRI and NotI restriction enzymes. To ensure RFP protein secretion in the culture medium, the signal sequence from APL1C was amplified from A. coluzzii Ngousso mosquitoes with the primers (Table S6) and cloned in the pAc5.1

V5-His-RFP expression vector.

Insect cell culture and transfection

A. coluzii derived 4a-3A hemocyte-like cells were cultured in monolayer at 27°C in Insect X press medium (Lonza) supplemented with 5% fetal bovine serum (GIBCO BRL) and 50µg/ml gentamycin (Sigma). Before transfection, 1.10 5 cells were allowed to grow in an 8-wells Lab-Tek chamber slide system (Thermo Scientific) for one hour.

Cells were transfected with the expression vector using cellfectin II reagent (Invitrogen) according to the manufacturer's protocol.

Ex vivo midgut assay

24 h post P.berghei-infected blood feeding (IBM), A. coluzzii Ngousso midguts were dissected in PBS and placed for 2 h at 21°C in culture medium of 4a-3A hemocyte-like cells that were transfected 3 days before with pAc5.1 V5-His-RFP, pAc5.1 V5-His-APL1C or pAc5.1 V5-His-LRIM1 expression vectors. After incubation, transfected cells and dissected midguts treated for immunostaining analysis with a mouse V5 monoclonal antibody (mAb, Invitrogen) at 1:500 or a mouse Pbs28 mAb (without permeabilization) 169 , followed by 1 h with Alexa Fluor 594-conjugated anti-mouse IgG secondary antibody at 1:2,000. Nuclei were stained with Hoechst 33342. After mounting in SlowFade Gold antifade reagent (Molecular Probes), samples were observed using a Leica DM 5000 B fluorescent microscope.

Double-stranded RNA synthesis and gene silencing

Double-stranded RNAs were synthesized from PCR amplicons using the T7

Megascript Kit (Ambion) as described previously 102 . The sequences of the primers used for synthesis of dsRNA for each gene are enlisted in Annex Table S7. 500 ng of dsRNA were injected into the thorax of cold-anesthetized A. coluzzii females using a nano-injector (Nanoject II, Drummond Scientific). dsGFP was used as a control.

Treatments were performed with a glass capillary needle as previously described 102,168 . The efficiency of the gene silencing was monitored by quantitative Polymerase Chain Reaction (qPCR) and western blot analysis where specific antibody was available.

RNA extraction and RT

Total RNA was extracted with TRIzol reagent (Invitrogen). cDNAs were generated using M-MLV reverse transcriptase (Invitrogen) from 1 µg of total RNAs in 40 µL.

Quantitative polymerase chain reaction (qPCR)

Using cDNA or genomic DNA, all qPCRs were performed as described in 104 , using SYBR green supermix (KAPA SYBR FAST ABI, Sigma-Aldrich) and the CFX96 Touch Real-Time PCR Detection System (Biorad). Ribosomal protein rpS7 gene was used as an internal control. The quantification of each gene was obtained as a ratio of the rpS7. All the primers sequences are enlisted in Annex Table S7. Analysis of the expression of transcript relative to rpS7 was performed according to the 2-ΔΔCt method 170 . PCR conditions of the run were: 95°C for 10min, then 40 cycle of [95°C for 15 sec, 60°C for 1min (plateread), melting curve analysis].

Protein extraction and western blotting from whole mosquitoes

Pools of 8 mosquitoes were placed in tubes containing glass beads with 150µl of freshly prepared 1X RIPA buffer (Cell Signalling) and 1X protease inhibitor cocktail (Roche). Samples were grinded in FastPrep using 3 cycles of 30s with 1400 rpm shaking each (with 30s breaks between each cycle to avoid sample heating). Grinded samples were centrifuged for 5 min, 18,000g, 4°C. Collected supernatant was sonicated in ice and centrifuged for 15 min, 18,000g, 4°C. Reduced protein samples were prepared by adding XT sample buffer (Bio-Rad), 1X DTT and heating at 95°C for 5 min. Samples were loaded and separated on 4-12% Criterion SDS-PAGE gels (Bio-Rad). Protein from equivalent of 0.2 mosquito were transferred to the membrane using Trans-Blot Turbo Transfer System (Bio-Rad), after which immunoblots were blocked for 1 hour in 5% BSA in TBST (Tris-buffered saline, 0.1% Tween 20). Immunoblots were probed overnight with a rabbit pAb anti-APLC antibody at 1:5,000 with 5% BSA in TBST. Next day, membranes were rinsed three times in TBST for 10 minutes each, stained by a mouse anti-GAPDH antibody (Thermofisher) at 1:4,000 and followed by horseradish peroxidase-conjugated anti-mouse IgG secondary antibody (Thermofisher) at 1:8,000, which was used as a loading control. Detection step was performed using the Enhanced chemiluminescence (ECL) system (Biorad) following the manufacturer's instructions. The levels of APL1C were quantified by densitometry using the Image Lab analysis software (BioRad). To normalize expression, the ratio of the GAPDH density from the control sample to the GAPDH density from sample of interest was determinate as a normalization factor. APL1C band intensity was normalized using GAPDH normalization factor.

Mosquito antibiotic treatment (ATB)

Mosquitoes were treated with an antibiotic (ATB) cocktail: penicillin 62.5 μg/mL, streptomycin 100 μg/mL and gentamicin 50 μg/mL in 10% sucrose solution directly after emergence and were kept under ATB pressure for three days, and ATB solution were changed every day. Mosquitoes treated (+ATB) or non-treated (-ATB) (for control) were fed on naive mouse for 20 min. Unfed mosquitoes were discarded and fed mosquitoes were maintained at 21°C and 70% relative humidity. For the (+ATB) group the antibiotic pressure was maintained after the feeding until their collection for midgut dissection.

Microbiota analysis

Dissection was performed as described previously 171 . Briefly, before dissection, mosquitoes were washed in 75% ethanol for 5 min, and then three times in sterile PBS to eliminate non-attached bacteria, thus preventing bacteria contamination during dissection. For each biological replicate, midguts were collected from each mosquito group (-ATB) and (+ATB), frozen immediately on dry ice and stored at -80°C until processing. To assess antibiotic effectiveness, mosquito midguts from each group (-ATB) and (+ATB) were collected 24h post-feeding. Bacterial DNA was extracted with DNeasy PowerSoil Kit (QIAGEN). The V4 region of the 16S rDNA (Annex, Table S7)

was used for measuring the total bacterial abundance by quantitative PCR. DNA samples from each independent biological replicate were used to perform distinct qPCR in triplicate and fold changes obtained between (+ATB) and (-ATB) were combined as a mean and illustrated graphically.

Clodronate-chemical depletion of phagocytic cells

Phagocyte Depletion Using Clodronate Liposomes was performed as previously described 172 . Briefly, female mosquitoes were injected intrathoracically with either 101.2nL of control liposomes (LPs) or CLDs in concentration 1.25mg/ml (standard macrophage depletion kit; Encapsula NanoSciences) using a Nanoject II injector (Drummond Scientific). Liposome treatments were performed 24 h before mosquito exposure to P. berghei IBM. The efficiency of phagocytic cell depletions using CLD was tested by measuring the expression level of two phagocytic markers: eater and nirmrodB2 by qPCR comparing CLD and LP injected mosquitoes, using pool of 8 mosquitoes from each batch.

Nitration pathway depletion

Nitration pathway depletion was performed as previously described 128 . Briefly, female mosquitoes were injected intrathoracically with either 1µg of dsNOX5/HPX2 (500ng for each) or dsGFP as a control using a Nanoject II injector (Drummond Scientific). Ds treatments were performed 72 h before mosquito exposure to P. berghei IBM. The efficiency of nitration pathway depletion was tested by measuring the expression level of NOX5 and HPX2 by RT-qPCR between dsNOX5/HPX2 and dsGFP injected mosquitoes prior to IBM (72h post treatment) and 24h post IBM (96h post treatment) from pool of 8 mosquitoes from each batch.

Sporozoite salivary glands collection

The salivary glands (SG) from infected mosquitoes were collected at day 19 post infection (10 days post ds GFP and dsAPL1C treatment), as previously reported with minor modifications 173 . Briefly, mosquitoes were rinsed one time in ethanol and two times in PBS. Then, each mosquito was placed on the glass side with PBS. Mosquito dissection and SG collections were gently performed under the stereomicroscope using the needles of the insulin syringes. SG were collected separately for each mosquito. Briefly, each pair of isolated SG was placed separately and individually in a 1.5-ml microcentrifuge tube containing 20μl of 1× PBS on ice. Then each tube was gently crushed with a pestle for microtubes in order to release the sporozoites from the salivary glands. The solution was homogenized by vigorous pipetting.

Sporozoites were shortly centrifuged on the 35µm filter to remove remaining salivary glands debrides. 10 μl of the solution was placed in a Kova slide. Once the parasites were settled, presence and number of sporozoites were measured with an epifluorescence microscope using a GFP filter.

Hemolymph sporozoites IFA

Mosquitoes were perfused with 4% PFA in 1xPBS straight to poly-L-lysine microscopy chamber (Ibidi GmbH). Slides were centrifuged for 2 min at 500g and fixed for 30min with subsequent centrifugation for 2min at 500g centrifugation in order to settle down the sporozoites. Fixed samples were rinsed three times in PBS and blocked for one hour in 1% BSA and 1X PBS prior to overnight incubation with anti-APL1C pAb (1:300 in 1% BSA in 1X PBS) at 4°C with 12 rpm rocking. The next day, samples were rinsed three times in 1% BSA in 1X PBS for 10 minutes each and incubated for two h with the secondary anti-rabbit Alexa Fluor 647 antibody (Thermofisher) diluted 1:500 in 1%

BSA and 1X PBS at room temperature with 12 rpm rocking. Then, samples were rinsed three times in 1% BSA and 1X PBS for 10 minutes each and stained with DAPI.

Immunostained samples were rinsed in PBS and observed under the inverted Axio Observer fluorescence microscope (ZEISS).

Statistical analyses

Differences in APL1C protein signal intensity in midguts were tested using Wilcoxon-Mann-Whitney test. All statistical differences were first tested independently within replicates (individual p-values in Annex, Table S1), and if individual replicates showed a common trend of change, then individual p-values were combined using the metaanalytical approach of Fisher 174 . For qPCR analysis using the 2-ΔΔCt method, difference in deltaCt distribution across the independent biological replicates was statistically tested using Student t-test. For western blot analysis, normalized band intensity was compared by Student t-test. Differences in salivary glands infection prevalence were tested using the Chi-Square test. All statistical differences were first tested independently within replicates (individual p-values in Annex, Table S2), and if individual replicates showed a common trend of change, individual p-values were combined using the meta-analytical approach of Fisher 174 .

3' Rapid Amplification of cDNA Ends (3'RACE)

Total RNA from pool of 8 females were subjected to a first strand cDNA synthesis at the poly(A) tail of mRNA using the adapter primer (AP) according to the manufacturer (Invitrogen). Amplification of 3' fragments of APL1A and APL1C were performed by PCR. Two rounds of PCR were performed: first, using the with Gene-Specific Primers (GSPs) designed for each APL1A and APL1C and producer provided Abridged Universal Amplification Primer (AUAP) that targets the cDNA complementary to the 3' end of mRNA. Second PCR round was performed with a second, nested-GSP for APL1A and APL1C (Annex Table S7) and AUAP primers. For each gene, GST and presence of the adapter sequence among all of the sample files. Therefore, remaining adapter sequences were trimmed with cutadapt 177 version 1.9.1 and remaining dsAPL1A and dsAPL1C fragments were removed using samtools version 1.9 178 .

Spliced Transcripts Alignment to a Reference (STAR) alignment tool 179 version 2.5.0a

was used for alignment against the reference genome of Anopheles gambiae str.

PEST version AgamP4 (from VectorBase). Reads summarization was performed using featureCounts version 1.6.1 180 . Counts data were analysed with SARTools package 181 , using R version 3.6.1 (R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, (Austria), and the Bioconductor package DESeq2 version 1.24.0 182 using default parameters. Due to the batch effect caused by time difference of RNA collection between replicate nr 1 and replicates nr 2, 3 and 4, the replicate nr 1 was excluded from the final RNAseq analysis. A generalized linear model was applied in order to test for inter-condition differences. For each pairwise comparison, raw p-values were adjusted for multiple testing using the Benjamini and Hochberg procedure 130 . Genes with adjusted p-values below 0.05 were considered differentially expressed. b Median values of tested conditions in each replicate.

Figures

c Statistical differences for APL1C signal intensity on the midguts were tested in each replicate using the Wilcoxon-Mann-Whitney test.

d This p-value was calculated using the method of R.A. Fisher to combine independent tests of significance 174 . Notation NA (Not Applicable) indicates that the direction of phenotypic effect among experimental replicates was not consistent and therefore replicates were not statistically combined.

Table S1. Statistical analysis of APL1C signal on mosquito midguts. Summary data for all experimental replicates testing the APL1C protein signal as compared to control treatment. Community Annotation, IP-Interpro, UP-UniPro. Genes in purple treatments were tested by qPCR. For the rest of the genes within the cutoff, the specific primers were not available. The "Gene name" column include the abbreviation used in qPCR analysis. Gene name in black correspond to the annotated gene name. Gene name in red correspond to abbreviation of gene function, whereas the genes without annotated function are called by the four last digits of their AGAP number and are depicted in green.

1 UF 4 - - - - - - 2 UF 5 - - - - - - 3 UF 4 - - - - - - 4 UF 10 - - - - - - 1 NBM 6 NBM
Table S6. Primers sequences used for the plasmids construction.

Figure 1 . 24 Figure 2 . 25 Figure 3 .

 1242253 Figure 1. Plasmodium parasite asexual development in a human host. ............ 24 Figure 2. Plasmodium development in female Anopheles.. ................................ 25 Figure 3. LRR-containing immune receptors, modes of pathogen perception and activation in plants. ......................................................................................... 36

Figure 4 . 39 Figure 5 . 45 Figure 6 . 47 Figure 7 . 53 Figure 8 . 54 Figure 9 .

 4395456477538549 Figure 4. Schematic structure of a VLR protein and VLR gene assembly.. ....... 39 Figure 5. Classification of mosquito LRIM proteins.. ........................................... 45 Figure 6. Complement pathway activation and outcome in vertebrates. ........... 47 Figure 7. Blood feeding induces the presence of APL1C protein on the basal side of the mosquito midgut. ................................................................................. 53 Figure 8. Anti-APL1C pAb labelling is specific to the APL1C protein. ............... 54 Figure 9. The mosquito microbiome does not influence APL1C protein abundance on the midgut 24 h after NBM. ............................................................ 56

Figure 10 .

 10 Figure 10. APL1C binds to ookinetes in A. coluzzii midguts. ............................. 57

Figure 11 . 59 Figure 12 . 61 Figure 13 . 62 Figure 14 . 64 Figure 15 . 66 Figure 16 . 68 Figure 17 . 70 Figure 18 . 72 Figure 19 . 73 Figure 20 . 75 Figure 21 . 3 ' 77 Figure 22 . 78 Figure 23 . 79 Figure 24 .

 1159126113621464156616681770187219732075213772278237924 Figure 11. APL1C binds to the ookinetes located on the basal side of the midgut. ..................................................................................................................... 59 Figure 12. APL1C and LRIM1 both bind to P. berghei.......................................... 61 Figure 13. APL1C and LRIM1 both bind to P. berghei ookinetes independently of TEP1 presence. ................................................................................................... 62 Figure 14. Full APL1C gene expression and protein abundance in the hemolymph requires phagocytic hemocytes. ...................................................... 64 Figure 15. Nitration pathway activity mediates APL1C protein presence in mosquito hemolymph. ............................................................................................ 66 Figure 16. APL1C protein level is increased by blood feeding and sporozoite release in A. coluzzii. .............................................................................................. 68 Figure 17. APL1C activity limits sporozoite invasion of salivary glands. .......... 70 Figure 18. APL1C protein binds to free sporozoites in mosquito hemolymph. .................................................................................................................................. 72 Figure 19. APL1C protective activity against sporozoites does not require the complement proteins TEP1 or TEP3...................................................................... 73 Figure 20. Overview of the RNAseq experiment. .................................................. 75 Figure 21. 3' APL1A and APL1C fragments identified by 3' RACE overlap with dsAPL1A and dsAPL1C fragments. ....................................................................... 77 Figure 22. The potential time effect after APL1 depletion on the number of the affected genes. ........................................................................................................ 78 Figure 23. APL1 gene silencing efficiency after dsRNA treatment. .................... 79 Figure 24. The kinetics of APL1C protein levels after dsAPL1C. ........................ 80

Figure 25 . 81 Figure 26 . 82 Figure 27 . 83 Figure 28 . 85 Figure 29 . 98 DNA

 25812682278328852998 Figure 25. APL1 genes silencing controls prior to the RNAseq analysis. ......... 81 Figure 26. Volcano plots visualize the differential expression analysis of RNAseq taken in dsAPL1A vs dsGFP (A) and dsAPL1C vs dsGFP conditions (B). ............................................................................................................................ 82 Figure 27. MA-plots visualizing the log ratio of differential expression as a function of the mean intensity taken in dsAPL1A vs dsGFP (A) and dsAPL1C vs dsGFP conditions (B).............................................................................................. 83 Figure 28. qPCR gene expression analysis validates RNAseq APL1C gene targets. ..................................................................................................................... 85 Figure 29. Proposed model of APL1C function in anti-Plasmodium response.98

Figure 1 .

 1 Figure 1. Plasmodium parasite asexual development in a human host. Detailed description in the text.

Figure 2 .

 2 Figure 2. Plasmodium development in female Anopheles. Detailed description in the text.

1. 2 Microbial sensing by the immune system 1 . 2 . 1

 2121 Basis of microbial immune sensing and evolutionOne of the challenges in immunology is to understand how the host organism detects the presence of infectious agents and mounts efficient killing mechanisms against these intruders, without destroying self-tissues. Sensing intruder as "non-self" or as lacking "self-markers" constitutes the starting point of the host response as a defence reaction in all living organisms. For microbial sensing, host-derived factors need to come in contact with the pathogen and generate the signals that will be transduced into a downstream immune response leading to the clearance of the microbes. Even such simple organisms as prokaryotes have defence mechanisms based on restriction enzymes and clustered regularly interspaced palindromic repeats (CRISPRs) that target invading pathogenic phages for degradation[START_REF] Barrangou | CRISPR-Cas systems: Prokaryotes upgrade to adaptive immunity[END_REF] . The foundational defence strategies in eukaryotic organisms are generally classified as the innate immune system, a host defence system in which plants and animals share similar inherited molecular modules including for pathogen sensing. The principle of innate immune recognition is based on the detection of constitutive and conserved products from structural microbial surface proteins or from their metabolism. Different pathogens share unique structures, for example lipopolysaccharide (LPS) or peptidoglycan, which are bacterial surface molecules, characterized as Pathogen Associated Molecular Patterns (PAMPs) and which are not synthetized by eukaryotic cells. The structure of these components is conserved, as they are often essential components for microbial survival and fitness. PAMPs are sensed by host germline-encoded proteins serving as pathogen recognition receptors (PRRs). Activation of PRRs through PAMP recognition transduces an immune signal inside the cells that leads to diverse killing mechanisms of the invaded pathogen (opsonization, activation of complement, phagocytosis, activation of pro-inflammatory signalling pathways, induction of apoptosis etc.).In the first vertebrates, around 500 million years ago, a more sophisticated mechanism called adaptive immunity, was built upon the innate immune layer. One of the unique features of adaptive immunity is the rearrangement of immune receptor gene segments, which result in development of clonally diverse immune cells called lymphocytes, where each possesses a unique antigen recognition receptor. Somatic recombination leads to the development of a large repertoire of lymphocytes that can recognize distinct microbes and mount highly specific immune responses tailored to the threat. Pathogen recognition occurs through mature effector lymphocytes with cytotoxic and pro-inflammatory functions or plasma cells that secrete antibodies (the soluble forms of the antigen-specific receptors). Moreover, the clonal expansion and long life of primed cytotoxic lymphocytes and plasma cells provide a protective immune memory to prevent reinfection[START_REF] Janeway | Innate Immune Recognition[END_REF][START_REF] Cooper | How did our complex immune system evolve?[END_REF][START_REF] Buchmann | Evolution of Innate Immunity: Clues from Invertebrates via Fish to Mammals[END_REF] .The recognition of a microbial intruder leads to the activation of defence mechanisms in the host-organism, leading to the immune responses. The study of Drosophila melanogaster was highly relevant to mammalian biology, given the evolutionary conservation of many key signal transduction pathways. In Drosophila, the innate immune system recognizes infectious microbes[START_REF] Govind | Innate immunity in Drosophila: Pathogens and pathways[END_REF] . Drosophila Toll and Immunodeficiency (Imd) immune pathways represent two distinct major arms of the immune response, which are activated by different microbes. Gram-positive bacteria and fungi activate the Toll signalling pathway, whereas Gram-negative bacteria activate the Imd pathway. Both pathways induce humoral and cellular changes in the insect host in order to eliminate or control the invasion of the intruder. Besides Toll and Imd immune-signalling pathway, the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) and RNA interference (RNAi) pathways are immune arms of the antiviral response. Thus, invertebrate innate immunity is able to mount different defence response against distinct pathogens[START_REF] Buchon | Immunity in Drosophila melanogaster--from microbial recognition to whole-organism physiology[END_REF] .

Figure 3 .

 3 Figure 3. LRR-containing immune receptors, modes of pathogen perception and activation in plants. A. An overview of LRR-containing immune receptors in mammals and plants. B. NB-LRR immune signalling activation pathway. Figure reproduced from 86 .

Figure 4 )

 4 Figure 4) 92 .

Figure 4 .

 4 Figure 4. Schematic structure of a VLR protein and VLR gene assembly. A. VLR monomers adopt a horseshoe-like solenoid fold characteristic of the LRR protein family. B. The germline VLR gene has a non-functional intervening region instead of the diversity region. Sequences coding for LRR modules (color-coded as in panel A) are located in multiple copies adjacent to the germline VLR gene. C. In developing lymphocytes, VLR is assembled by a gene conversion-like mechanism. Gene conversion can begin from either end of the gene.

Figure reproduced from 92 .

 92 Figure reproduced from 92 .

Figure 5 .

 5 Figure 5. Classification of mosquito LRIM proteins. Figure reproduced from 107 .

Figure 7 .

 7 Figure 7. Blood feeding induces the presence of APL1C protein on the basal side of the mosquito midgut. A. Immunostaining analysis of the midguts from mosquitoes subjected to P. berghei-infected bloodmeal (IBM), normal bloodmeal (NBM) and unfed control (UF). Depicted pictures are representative for at least two replicates in each group. For the in vivo system, all immunostaining analysis were performed with an anti-APL1C pAb followed by fluorophore-conjugated IgG secondary antibody (red). Nuclei and actin were stained with DAPI and Phalloidin (blue). The scale bar is 10 µm. B. Quantitative analysis of the APL1C signal between IBM, NBM and UF midguts reveals increase of APL1C protein on the midguts after IBM and NBM. Graph labels and statistical tests for this figure: tests of APL1C protein signal intensity on the midgut indicate each midgut subjected for the analysis as a dot, bars represent mean with ±SEM. Sample sizes (N) show the number of independent replicate experiments, (n) the total number of midguts dissected across replicates. Data were analysed by measuring APL1C signal intensity (RawIntDen) using ImageJ v1.52p and the intensity from each midgut was compared between the two conditions by Mann-Whitney test. All statistical differences were first tested independently within replicates (individual p-values in Annex, Table S1), and if individual replicates showed a common trend of change, individual p-values were combined using the meta-analytical approach of Fisher (significance level of Fisher-combined p-value: **** p-value <0.0001). C. The XZ and YZ orthogonal views of the NBM stack picture show APL1C protein localising extracellularly, on the basal side (ba) of the midguts. No APL1C signal was found on midgut lumen (lu). The scale bar is 10 µm.

Figure 8 .

 8 Figure 8. Anti-APL1C pAb labelling is specific to the APL1C protein. A. APL1C silencing was verified by qPCR measurement between dsAPL1C and dsGFP (dotted line) 72 h posttreatment (corresponding to expression status at the time of the NBM). The ratio of the

Figure 9 .

 9 Figure 9. The mosquito microbiome does not influence APL1C protein abundance on the midgut 24 h after NBM. A. Bacterial abundance was significantly reduced after antibiotic treatment. Antibiotic efficiency on bacterial abundance was confirmed by qPCR detection of 16S rDNA in controls (-ATB, dotted line indicates y=1.0) and ATB-treated (+ATB), 24h post NBM.The ratio of the normalized 16S rDNA detection in "+ATB" versus "-ATB" treatments was computed using triplicates from the same cDNA dilution. Graph represents mean with ±SEM of the expression fold change between "+ATB" and "-ATB" control from two biological replicates (N=2). Bacterial qPCR data were analysed by unpaired t-test using (*** p-value <0.001). B. Immunostaining analysis of the +ATB midguts group shows that bacterial depletion did not diminish APL1C abundance on NBM midguts. Images are representative of two independent biological replicates of 3-7 midguts each. The scale bar is 10 µm.

Figure 10 .

 10 Figure 10. APL1C binds to ookinetes in A. coluzzii midguts. A. Immunostaining analysis of IBM mosquito midguts 24h post-infection shows GFP-expressing ookinetes (green) associated with APL1C protein (red arrows on the "Merge" picture) and APL1C-negative parasites (green arrow on the "Merge" picture). Scale bar is 10 µm. B. Enlarged projections of APL1C-negative parasites (1) and APL1C-positive parasites (2) from (A). The scale bar is 2 µm. C. Depending on APL1C binding, GFP-positive parasite numbers (n=1087 number of the parasites scored across the replicates) were scored and are shown in the pie chart (red: APL1C-positive parasites, green: APL1C-negative parasites) as the mean percentage obtained from four independent experiments (N=4, 4 to 7 midguts per each replicate). D.

Figure 11 .

 11 Figure 11. APL1C binds to the ookinetes located on the basal side of the midgut. XZ and YZ orthogonal views of the stack pictures links APL1C protein binding with parasite spatial localisation in mosquito midguts. Yellow lines depict the parasite, which spatial localisation is presented on the sides of the stack picture. A. Illustration of a parasite traversing the midgut epithelium that is labelled with APL1C on the basal side of the mosquito midgut. B. The parasites that did not traverse the midgut epithelium and remained on the apical side of the mosquito midgut are not labelled with APL1C. The midgut lumen (lu) and basal site (ba) of the midgut are depicted on the orthogonal view pictures. The scale bar is 10 µm.

  Figure 12. APL1C and LRIM1 both bind to P. berghei. A. Immunostaining analysis of mosquito midguts infected with GFP parasites (green) after 2 h incubation in culture medium from transfected 4a3A cells. Staining with an anti-V5 monoclonal antibody (mAb) followed by fluorophore-conjugated IgG shows parasites associated with V5-APL1C and V5-LRIM1 tagged proteins (red). Nuclei were stained with Hoechst 33342 (blue). The scale bar is 2 µm. B. V5-positive parasites and V5-negative parasites after staining with anti-V5 antibodies in each condition were scored and illustrated in pie charts (red: V5-positive parasites, green: V5-negative parasites) as the mean percentage obtained from three independent experiments (N=3, 3-10 midguts per experimental point). The proportion of parasites reaching the basal side of the midgut epithelium at 24 h post-infection was scored using the anti-Pbs28 antibody (red: Pbs28-positive parasites, green: Pbs28-negative parasites). Data from collaboration: C. Lavazec, Institut Cochin, Paris.

62 Figure 13 . 63 3. 1 . 5

 62136315 Figure 13. APL1C and LRIM1 both bind to P. berghei ookinetes independently of TEP1 presence.A. TEP1 protein is successfully depleted by dsTEP1 in 4a3A cells. Expression ratios of protein levels TEP1/tubulin were quantified by densitometry. The efficiency of the gene silencing effect was monitored at day 6 by immunoblotting analysis of cells and culture medium of the 4a3A cell line using an anti-TEP1 antibody and an anti-tubulin antibody. For each condition, the ratio of protein levels TEP1/tubulin was calculated and the percentage of TEP1 signal reduction relative to tubulin was quantified in dsTEP1-transfected cells as compared to dsGFP transfected cells. B. APL1C and LRIM1 binding to the parasites are TEP1 independent. Proportions of parasites associated with V5-tagged proteins in cells depleted for TEP1, after staining with anti-V5 antibodies. Parasite numbers in each condition were scored and are shown in the pie chart (red: V5-positive parasites, green: V5-negative parasites) as the mean percentage obtained from three independent experiments (3-10 midguts per experimental point). DsGFP transfected cells were used as a control. Numbers of V5-positive and V5negative parasites from each replicate were compared between the two conditions by chisquare test (significance level of chi-square: n.s.=not significant). Data from collaboration: C. Lavazec, Institut Cochin, Paris.

Figure 14 .

 14 Figure 14. Full APL1C gene expression and protein abundance in the hemolymph requires phagocytic hemocytes. A. Phagocytic hemocytes were depleted by clodronate treatment (CLD). CLD-mediated phagocyte depletion was verified by qPCR measurement of phagocyte markers, eater and nimrodB2 between CLD-treated mosquitoes and liposome controls (LP, indicated as dotted line), 24 h post-treatment prior to IBM. The ratios of normalized eater, nimrodB2 transcript detection were computed using triplicates from the same cDNA dilution, and graph represents mean with ±SEM of the expression fold change from three biological replicates (N=3). qPCR was analysed by unpaired t-test (* p-value<0.05; ** p-value<0.01). B. APL1C expression was reduced in CLD-treated mosquitoes. Analysis of APL1C expression was performed as described in A. C. Hemolymph APL1C protein abundance measured as IFA signal intensity on midguts dissected from mosquitoes treated with CLD prior to IBM. Data points on graph indicate single midguts, bars indicate mean with ±SEM. The number of independent replicate experiments (N) the total number of midguts dissected across replicates (n) are indicated. Data were analysed by measuring APL1C signal intensity (RawIntDen) using ImageJ v1.52p and the intensity from each midgut was compared between the two conditions by Mann-Whitney test. All statistical differences were first tested independently within replicates (individual pvalues in Annex TableS1), and if individual replicates showed a common trend of change,

Figure 15 .

 15 Figure 15. Nitration pathway activity mediates APL1C protein presence in mosquito hemolymph. A. Immunostaining analysis of perfused hemocytes from mosquitoes indicates that APL1C is localized in subcellular vesicles (red). Cells were stained with Hoechst 33342 to label nuclei (blue) and phalloidin for actin (green). Scale bar, 5 µm. Data from collaboration: C. Lavazec, Institut Cochin, Paris. B. Expression of NOX5 and HPX2 genes is decreased after treatment with dsNOX5/HPX2. NOX5 and HPX2 silencing was verified by qPCR measurement between dsNOX5/HPX2 and dsGFP (dotted line) 72 h post-treatment (before IBM).The ratio of normalized NOX5 or HPX2 cDNA detection in "dsNOX5/HPX2" versus "dsGFP" was computed using triplicates from the same cDNA dilution. Graph represents mean with ±SEM of the expression fold change between "dsNOX5/HPX2" and "dsGFP" control from three biological replicates (N=3). Data for qPCR analysis was analysed by unpaired t-test

  abundance of APL1C protein was first measured by Western blot at four time points during Plasmodium development in the vector: young oocysts at 4 d post-bloodmeal, late oocysts before sporozoite release at 10 d post-bloodmeal, early sporozoite release RESULTS 68 at 12 d post-bloodmeal, and late sporozoite release at 18 d post-bloodmeal. Unfed mosquitoes (UF) were used as controls. At 4 d post-bloodmeal, APL1C protein was increased in both IBM and NBM mosquitoes as compared to UF, but there was no difference between IBM and NBM, indicating that the early stage induction of APL1C

Figure 16 .

 16 Figure 16. APL1C protein level is increased by blood feeding and sporozoite release in A. coluzzii. Immunoblot analysis of APL1C protein levels after IBM. Protein extract from whole mosquitoes collected at day 4 (early oocyst), day 10 (mature oocyst, before sporozoite release), day 12 (early sporozoite release) and day 18 (late sporozoite release) were probed with an anti-APL1C pAb and anti-GAPDH antibody as a loading control. NBM and UF samples

Figure S5 ).

 S5 Figure S5). Silencing efficiency was confirmed for APL1C transcript and protein, and

Figure 17 .

 17 Figure 17. APL1C activity limits sporozoite invasion of salivary glands. A. Silencing of APL1C gene expression is efficient until at least 10 d after dsAPL1C treatment, the time point when salivary glands were dissected. APL1C silencing was verified by qPCR measurement between dsAPL1C and dsGFP (dotted line) treatments. The ratio of the normalized APL1C cDNA detection in "dsAPL1C" versus "dsGFP" treatments was computed using triplicates from the same cDNA dilution. Graph represents mean with ±SEM of the expression fold change between "dsAPL1C" and "dsGFP" control from four biological replicates (N=4). Data for qPCR analysis was analysed by unpaired t-test (significance level of t-test **** p-value <0.0001). B.APL1C protein level is efficiently decreased 10 d after dsAPL1C treatment. Graph represents the protein ratio between "dsAPL1C" and "dsGFP" control (depicted as a dotted line), measured by densitometry. GAPDH density signal was used to normalize APL1C signal in both dsGFP and dsAPL1C treatments, and the normalized APL1C signals were then compared between these two treatments. C. APL1C depletion led to increased sporozoite infection prevalence of the salivary glands. The proportions of the sporozoite-infected salivary glands (blue) or non-infected (yellow) in dsAPL1C and dsGFP treated mosquitoes were scored (n=total number of salivary glands dissected across the replicates) and are illustrated in the pie chart as the mean percentage obtained from four independent experiments (N=4).

Figure 18 .

 18 Figure 18. APL1C protein binds to free sporozoites in mosquito hemolymph. A. Immunostained GFP sporozoites (green) from mosquitoes perfused 17 days post-IBM are labelled with APL1C protein (red). Nuclei were stained with DAPI (blue). Images are representative of two independent biological replicates. The scale bar is 5 µm. B. The proportion of circulating sporozoites (n=152) labelled with APL1C protein was scored and illustrated in a pie chart as a mean percentage from two independent experiments (red: APL1C-positive sporozoites, green: APL1C-negative sporozoites). C. Sporozoites perfused from dsGFP-injected mosquitoes are labelled by APL1C protein. The main picture depicts merge (scale bar 10 µm), whereas pictures below show 3 channels of enlarged projections of sporozoites (scale bar 2 µm), indicated by the numbers on the merge picture. D. Sporozoites perfused from dsAPL1C-treated controls are not labelled by APL1C protein. The main picture depicts merge (scale bar 10 µm), whereas pictures below 3 channels of enlarged projections of sporozoites (scale bar 2 µm), indicated by the numbers on the merge picture.

RESULTS 73 was

 73 silenced individually or simultaneously by treatment with dsRNA at 9 d post-IBM, and sporozoite infection prevalence and intensity in the salivary glands was measured at 19 d post-IBM (experimental design, FigureS5). Silencing efficiency was confirmed at 10 d after dsRNA treatment (Figure19A). Neither TEP gene, alone or together, displayed an influence on sporozoite infection of salivary glands (Figure19B). These results indicate that while TEP1 and TEP3 both display anti-ookinete function in the mosquito midguts 104,111,129 115 , they do not contribute to APL1C-mediated antisporozoite function. APL1C may recruit different TEP family members for sporozoite protection, or sporozoite destruction could be mediated by a distinct mechanism that does not include a TEP effector. Further work will be required to distinguish between these models.

Figure 19 .

 19 Figure 19. APL1C protective activity against sporozoites does not require the complement proteins TEP1 or TEP3. A. TEP1 and TEP3 expression are efficiently silenced at the time of the salivary gland dissection (10 days post-dsTEP1, dsTEP3 or dsTEP1/TEP3treatments). TEP1 and TEP3 silencing was verified by qPCR. The ratio of normalized TEP1 or TEP3 cDNA detection in "dsTEP1", "dsTEP3" or "dsTEP1/TEP3" versus "dsGFP" treatments was computed using triplicates from the same cDNA dilution. Graph represents mean with ±SEM of the expression fold change between "dsTEP1", "dsTEP3" or "dsTEP1/TEP3" as

Figure 20 .

 20 Figure 20. Overview of the RNAseq experiment. The APL1A or APL1C genes were silenced in A. coluzzii, with dsGFP treatment as the control, and RNAs were subjected to RNAseq. Bioinformatic analysis identified differentially expressed genes for each silenced gene as compared to the control.

RESULTS 77 Figure 21

 7721 Figure 21. 3' APL1A and APL1C fragments identified by 3' RACE overlap with dsAPL1A and dsAPL1C fragments. A. 3'RACE of APL1A gene identified 5 different 3'APL1A fragment variants. B. 3'RACE of APL1C gene identified 4 different 3'APL1C fragment variants.

RESULTS 78 differentially

 78 expressed genes to test and decrease their informativeness for identifying the proximal target genes of putative APL1 signalling.

Figure 22 .

 22 Figure 22. The potential time effect after APL1 depletion on the number of the affected genes. 'a' and 'b' correspond to the hypothetical first layer of genes directly affected by depletion of APL1 (green arrows). The influence of APL1 on downstream expression could be caused by any combination of transcriptional, translational and post-translational effects. The red arrows indicate the genes that are secondary, tertiary and subsequently affected by the time post-APL1s depletion.

Figure 23 .

 23 Figure 23. APL1 gene silencing efficiency after dsRNA treatment. A. The kinetics of APL1A transcript depletion after dsAPL1A treatment in A. coluzzii. APL1A silencing was verified by qPCR measurement relative to dsGFP controls (dotted line). The ratio of the normalized APL1A cDNA detection in "dsAPL1A" versus "dsGFP" treatments was computed using triplicates from the same cDNA dilution. Graph represents mean with ±SEM of the expression fold change between "dsAPL1A" and "dsGFP" control from at least two biological replicates. B. The kinetics of APL1C transcript depletion after dsAPL1C treatment. APL1C silencing was verified by qPCR and computed as above. For A and B data for qPCR analysis was analysed by unpaired t-test (significance levels of t-test p-values: ** p-value<0.01; *** pvalue <0.001; **** p-value <0.0001).

Figure 24 .

 24 Figure 24. The kinetics of APL1C protein levels after dsAPL1C. The graph represents the level of APL1C protein in dsAPL1C-treated mosquitoes normalized with the dsGFP control

Figure 25 .

 25 Figure 25. APL1 genes silencing controls prior to the RNAseq analysis. A. APL1A

Figure 26 ,Figure 27 )

 2627 as well as summarized in Table

Figure 26 .

 26 Figure 26. Volcano plots visualize the differential expression analysis of RNAseq taken in dsAPL1A vs dsGFP (A) and dsAPL1C vs dsGFP conditions (B). Each dot represents a gene, which expression was compared between the tested conditions (APL1A-depleted mosquitoes vs dsGFP control or APL1C-depleted mosquitoes vs dsGFP control). Red dots correspond to significantly different genes based on adjusted p-value. For each pairwise comparison, raw p-values were adjusted for multiple testing using the Benjamini and Hochberg procedure 130 . Genes with adjusted p-values below 0.05 were considered differentially expressed

Figure 27 .

 27 Figure 27. MA-plots visualizing the log ratio of differential expression as a function of the mean intensity taken in dsAPL1A vs dsGFP (A) and dsAPL1C vs dsGFP conditions (B). Each dot represents a gene which expression was compared between the tested conditions. Differentially expressed features are highlighted in red and the triangles correspond to features having a too low/high log2(FC) to be displayed on the plot.

Figure 28 .

 28 Figure 28. qPCR gene expression analysis validates RNAseq APL1C gene targets. Gene expression is reported as expression log2 foldchange [log2FC, x-axis] measured between "dsAPL1C" and "dsGFP" conditions. Expression of each tested gene is depicted as a red bar for qPCR analysis and black bar for RNAseq analysis. For gene calling (y-axis), annotated genes are called with their gene name or aberrations of gene function, whereas the genes without annotated function are called by the last four digits of their AGAP number. The correlation between qPCR and RNAseq was tested by computing Pearson correlation coefficients. Significance levels of Pearson correlation **** p-value <0.0001).

Figure 29 .

 29 Figure 29. Proposed model of APL1C function in anti-Plasmodium response. Detailed description in text.

Figure S2 .

 S2 Figure S2. Mosquito hemolymph-injected dextran diffuses on mosquito midguts in a way resembling APL1C protein deposition. Immunostaining analysis of the midguts from dextran-injected mosquitoes shows that dextran diffuses through basal lamina and is deposed on the tissue. The scale bar is 10µm.

Figure S3 .

 S3 Figure S3. Tissue permeabilization enables antibody access to all the parasites present in mosquito midguts. IFA of P. berghei-infected mosquito midguts collected 24 h post-IBM and immunostained with anti-GFP conjugated antibody. GFP-expressing ookinetes (green) are also associated with anti-GFP protein (red). Nuclei and actin were stained with DAPI and Phalloidin (blue). The scale bar is 10 µm.

Figure S4 .

 S4 Figure S4. V5-tagged protein constructs are secreted from hemocyte-like cells. A. Immunoblot analysis using a mouse anti-V5 mAb and culture medium of the 4a3A hemocytelike cell line transfected with plasmids encoding V5-tagged APL1C and LRIM1 under reducing (R) and non-reducing (NR) conditions. Estimated sizes of monomeric APL1C and LRIM1 forms including V5-tag are: 88 kDa (APL1C) and 60 kDa (LRIM1), respectively. The results show

Figure S5 .

 S5 Figure S5. Workflow of salivary glands infection prevalence and intensity analysis after dsRNA treatment. Mosquitoes were injected 9 d post IBM with dsRNAs (dsAPL1C, dsTEP1, dsTEP3 or co-injected with dsTEP1/dsTEP3). DsGFP-injected mosquitoes served as a control. In the case of double treatment (dsTEP1/dsTEP3), a double dose of dsGFP was also injected in the control group. Salivary glands were dissected 19 d post IBM (10 d post dsRNA treatment) and collected separately in 1,5 ml tube with 20 µl of PBS. Sporozoites were released from the salivary gland tissues by grinding and filtering in order to get rid of tissue debrides.The collected sporozoites containing flow-through were subsequently loaded into a Kova slide and screened for measuring sporozoites infection prevalence and intensity.

Figure S6 .

 S6 Figure S6. RNAseq bioinformatic analysis pipeline that identified differentially expressed genes in APL1A and APL1C depleted mosquitoes. Each step of the analysis is presented in blue bracket, and the bioinformatic tools used for each step are indicated in green font.

Figure S7 .a

 S7 Figure S7. Total sequence number reported in the RNAseq analysis for all the studied samples. The results show that all samples displayed a close total number of reads (30-40 M reads).

  Statistically significant differences are indicated by green shading. Rows indicate the treatment for a given replicate, the experiment number, the number of mosquitoes used for the statistical analysis. Individual p-values were calculated for each replicate by statistical comparison between the corresponding control experiment shown in the column "Experiment #" and indicated in "Tested conditions" column. If the different replicates of a tested condition were consistent (display the same phenotypic direction), then the individual p-values were combined by Fisher's method "Fisher combined prob". If the replicate phenotypes were not consistent, the individual p-values are shown but combining of p-values is not justified.

a

  Applicable to mosquito genes; ID based on the Reference Strain Anopheles gambiae PEST. b T7 sequence is underlined. c In case of published primers sequence, link to the publication source is indicated. TM refers to the primers designed in this manuscript.

  Plasmodium is in direct contact with the insect hemolymph, thus with soluble mosquito immune factors. Therefore, the mosquito hemolymph appears to be a battlefield in which Plasmodium parasites are attacked by mosquito defence factors. While the role of mosquito immune factors in the first bottleneck has been clearly demonstrated, this is not the case for the second one, concerning the large sporozoite clearance seen in the hemolymph, and this still needs to be clarified.

. During these two main bottlenecks of parasite development in the mosquito,

Table 1 . Role of human TLRs in pathogen recognition.

 1

  Table modified from 67 .

  Only signals as a dimer when combined with TLR2 for all its ligands; recognizes Borrelia burgdorferi OspA; required for adaptive immune response Tri-acyl lipopeptides (bacteria, eg, M tuberculosis)

	Toll-like receptor	Ligand(s)
	TLR1	Soluble factors ( Neisseria meningitidis)
		Associates with CD11/CD18, CD14, MD-2, TLR1, TLR6, dectin 1; Lipoprotein/lipopeptides (a variety of microbial pathogens)
		Peptidoglycan
		Lipoteichoic acid
		Lipoarabinomannan (mycobacteria)
		Phenol-soluble modulin ( Staphylococcus epidermidis)
		Glycoinositolphospholipids ( Trypanosoma Cruzi )
		Glycolipids ( Treponema maltophilum)
		Porin ( Neisseria )
		Zymosan (fungi)
		Atypical LPS ( Leptospira interrogans)
		Atypical LPS ( Porphyromonas gingivalis)
		HSP70 (host)
		CMV virions
		Hemagglutinin (H) protein of wild-type measles
	TLR2	Bacterial fimbriae
	TLR3	Double-stranded RNA in viruses
		Gram-negative enteric LPS (requires coreceptors MD-2 and CD14)
		Additional ligands
		Chlamydial heat shock protein 60
		RSV F protein
		Taxol (plant)
		M tuberculosis HSP65
		Envelope proteins (MMTV)
		HSP60 (host)
		HSP70 (host)
		Type III repeat extra domain A of fibronectin (host)
		Oligosaccharides of hyaluronic acid (host)
		Polysaccharide fragments of heparan sulfate (host)
		Fibrinogen (host)
	TLR4	Beta-defensin2
	TLR5	Flagellin (monomeric) from bacteria
		See TLR2 (as dimmers with TLR2)
		Phenol-soluble modulin
	TLR6	Di-acyl lipopeptides (mycoplasma)
		Responds to imidazoquinoline anti-viral agents (synthetic compounds)
		Loxoribine (synthetic compounds)
		Bropirimine (synthetic compounds)
		Endogenous and exogenous ligands unknown.
	TLR7	Single-stranded RNA
		Imidazoquinoline (synthetic compounds)
	TLR8	Single-stranded RNA
	TLR9	Bacterial DNA as "CpG" motifs
	TLR10	Unknown

1.2.2.2 LRR-coding receptors in adaptive-like immunity of jawless vertebrates

	GENERAL INTRODUCTION
	first line of host-defence machinery and enters the cell, a second layer of defence takes enzymatic activity of multiple or many pathogen-effectors 87 (Figure 3B). NB-LRRs are composed of multiple, variable LRR modules (LRRV), 24-residue called end LRRV
	over. Plant evolution has generated proteins that detect specific effector molecules, in normally kept in a resting state by intramolecular interactions involving the LRR (LRRVe), a connecting peptide (CP) and a C-terminal LRR-capping motif (LRRCT,
	a mechanism called effector-induced immunity (ETI) 88 . Plant effector-induced domain. Pathogen recognition occurs either by direct association between the LRR
	immunity is more akin to mammalian adaptive immunity in that pathogen effectors and domain and a pathogen-effector protein or by indirect association mediated by a host
	virulence factors are specifically recognized. The genes encoding the specificity protein (Figure 3B). Upon ligand binding, conformational changes and/or protein
	determinants of effector-induced immunity are known as resistance (R) genes. Most oligomerization leads to the activation of NB-LRR (Figure 3B). This is accompanied or
	known R genes encode proteins belonging to the family of nucleotide binding (NB) followed by exchange of ADP for ATP at the NB domain that leads to defence
	LRR proteins (NB-LRR). NB-LRR proteins are involved in the recognition of specialized signalling. The activity of NB-LRR proteins result in activation of defence factors
	pathogen effectors (also called avirulence (Avr) proteins) that are thought to provide transcription in nucleus or plant hypersensitive response (HR), which is a form of
	virulence function in the absence of the proper R gene 88 . Nevertheless, unlike programmed cell death localized to infection sites 86,89,90 .
	mammalian adaptive immunity, plant defence relies on innate immunity. Therefore,
	their capability to recognize specifically a large repertoire of pathogen effectors
	suggests they encode a high number of NB-LRR genes. Indeed, in the genome of
	Arabidopsis there are approximately 150 predicted NB-LRRs 87 . However, this number Jawless vertebrates (agnathans) and jawed vertebrates (gnathostomes) diverged
	is probably still below the wide range microbes that plants have to face. This questions approximately 550 million years ago. While jawed vertebrates are predominant, the
	of how an effector-induced immune response in plants coordinates resistance to a jawless clade has only two extant representatives: hagfishes and lampreys. As
	broad range of pathogens and their corresponding effectors, in sometimes very long-mentioned above, the arsenal of adaptive immune recognition in gnathostomes is
	lived individuals, up to centuries, is still not completely clarified. It was proposed that based on Ig domain B and T lymphocyte receptors (BCRs and TCRs) and major
	NB-LRR bacterial effector recognition likely evolved as an indirect mechanism. Based histocompatibility complex (MHC) molecules. While none of these proteins are present
	on the fact that the majority of characterized bacterial effectors display enzyme activity in agnathans, hagfishes and lampreys were shown to mount adaptive-like immune
	that modify plant proteins, enzymatic functions of multiple distinct pathogen-effectors responses to repetitive antigenic challenges through the expression of unique antigen
	target the same host proteins. Therefore, rather than developing receptors for every receptors named variable lymphocyte receptors (VLRs). These VLRs generate
	possible effector, host plants have evolved mechanisms to monitor common plant antigen-recognition diversity through a gene conversion-like mechanism involving a
	proteins that are targets of pathogen virulence. Thus, by monitoring perturbations in variable LRR segment domain 91 . Three VLR genes have been identified, VLRA, VLRB
	. Nevertheless, if a microbe overcomes the key host proteins, R proteins such as the NB-LRR, indirectly detect the functional and VLRC and they share a similar protein organization with a N-ending LRR-capping
	motif (LRRNT) followed by 18-residue N-terminal LRR module (LRR1), diverse region
	39

CURRENT KNOWLEDGE, GAPS AND OBJECTIVES 2.1 Natural resistance to Plasmodium highlighted a family of LRR genes termed APL1 (Anopheles Plasmodium- responsive leucine-rich repeat)

	GENERAL INTRODUCTION
	have eight to ten antigen binding sites 93 , leading to the neutralization of the pathogen Functional analysis performed in the laboratory by measuring the presence of midgut
	and subsequent elimination by phagocytosis or complement pathway activation 92 . In oocysts after gene silencing showed that a functional APL1A gene protects against
	summary, suggesting a convergent evolution, jawed and jawless vertebrates use infection with P. falciparum, while functional APL1C protects against the rodent malaria
	remarkably different modules (Ig and LRR, respectively) in common strategies, forming parasites, P. berghei and P. yoelii 102,103 . Furthermore, protection against P. falciparum
	transmembrane or soluble antibody receptors as the arm of adaptive immune response correlates with the transcriptional regulation of APL1A by the isoform Imd/Rel2-S but
	91,92,93,94,95 Like all invertebrates, mosquitoes lack adaptive immune response, thus using their not Imd/Rel-2F 103 , whereas protection against P. berghei correlates with the
	innate immune system to face microbial invasion. The availability of complete genome transcriptional regulation of APL1C by the Toll/Rel1 pathway 102 . Gene APL1B protects
	sequences as well as comparative genome studies between mosquitoes and the against both human and rodent malaria parasites in collaboration with APL1A and
	arthropod model organism, Drosophila, contributed to identification of mosquito APL1C, respectively 104 . The APL1 genes display high polymorphism with a rate of non-
	immune factors 96,97 . However, Drosophila and Anopheles diverged from a common synonymous variation 10-fold higher than any another A. gambiae genes. This pattern
	ancestor around 250 million years ago and have extremely different lifestyles, is consistent with adaptive maintenance of polymorphism, which can be seen in so-
	especially with the obligate hematophagy of mosquito females. Therefore, while the called "trench warfare" models of fluctuating recurrent pathogen epidemics 105 . Such
	main immune pathways were found to be conserved, flies and mosquitoes are exposed polymorphism results in different encoded protein variants that likely lead to protective
	to different microbial repertoires and thus underwent different evolutionary pressures phenotypes against distinct pathogens. Indeed, in a study of the A. gambiae Ngousso
	that have shaped their respective immune systems. While it is difficult to measure colony, which segregates three different major structural alleles of APL1A, only one
	fitness trade-offs in nature, identifying the molecular components of natural resistance allele was associated with protection against P. falciparum 106 . This observation
	could help understand how they are genetically structured in wild mosquito vector highlights that APL1 allelic variation could contribute to natural variation in mosquito
	populations 98 . A field-based genetic mapping survey of wild mosquito populations susceptibility to Plasmodium, and also that studies in different mosquito colonies
	revealed that about 50% of the A. gambiae s.s. tested carried a significant locus should take into consideration presence of different genetic forms that could affect the
	controlling susceptibility to natural P. falciparum. This genomic locus located on phenotype.
	chromosome 2L was mapped in both East and West African wild A. gambiae 99,100,101 ,
	suggestive of a widespread and shared genetic mechanism of malaria resistance.
	This diverse region (LRRV) composed of multiple LRR modules determines receptor
	Candidate gene filtering of the locus by bioinformatics and transcriptional regulation
	specificity. VLRs A, B and C are a membrane-bound protein receptor. However, in
	highlighted a family of three genes encoding LRR proteins and named Anopheles
	addition to be a transmembrane protein, VLRB can also be secreted as a soluble
	Plasmodium-responsive leucine-rich repeat 1 (APL1). The genes, APL1A, APL1B and
	protein. Secreted VLRB molecules occur as pentamers or tetramers of dimers and
	APL1C, share ≥50% peptide identity and have distinct functional activities 102,103 .
	40

. II.

  subjected for the analysis as a dot, bars represent mean with ±SEM.Sample sizes (N) show the number of independent replicate experiments, (n) the total number of midguts dissected across replicates. Data were analysed by measuring APL1C signal intensity (RawIntDen) using ImageJ v1.52p and the intensity from each midgut was compared between the two conditions by Mann-Whitney test. All statistical differences were first tested

	independently within replicates (individual p-values in Annex Table S1), and if individual
	replicates showed a common trend of change, individual p-values were combined using the
	meta-analytical approach of Fisher (significance level of Fisher-combined p-value: **** p-value
	<0.0001). D. The APL1C protein level in whole mosquitoes increases upon nitration pathway
	depletion. Immunoblot analysis of APL1C protein level 72 h after dsNOX5/HPX2 treatment.
	Protein extracts from mosquitoes injected with dsNOX5/HPX2 and dsGFP (control) were
	subjected to a Western blot with an anti-APL1C pAb and anti-GAPDH antibody as a loading
	control. The normalized APL1C signal density was compared between "dsNOX5/HPX2" and
	"dsGFP" mosquitoes (dotted line). Graph represents mean with ±SEM of the protein ratio
	between "dsNOX5/HPX2" and "dsGFP" from three biological replicates (N=3). Data were
	analysed by Image Lab 6.0.1 and statistically analysed by unpaired t-test (significance level of
	t-test * p-value<0.05).
	). Data for qPCR analysis was analysed by unpaired t-test
	(significance levels of t-test p-values: ** p-value <0.01; **** p-value <0.0001). B. NOX5 and
	HPX2 silencing was verified accordingly to (A) 96 h post treatment (24 h after IBM). C. Nitration
	pathway elicits APL1C presence in the hemolymph, measured by detection of protein captured

in the extracellular space of dissected midguts. Quantitative analysis of the APL1C signal on the midguts from the mosquitoes in which the nitration pathway was depleted as compared to controls reveals decreased APL1C protein in mosquitoes depleted for nitration activity. Graph labels and statistical tests for this figure: tests of APL1C protein signal intensity on the midgut RESULTS 67 indicate each midgut

  were used as controls for each time point. The normalized APL1C signal was compared between NBM or IBM mosquitoes versus UF mosquitoes (dotted line). APL1C protein level increases at day 4 after NBM or IBM and at day 18 after IBM as compared to controls. Graph represents mean with ±SEM of the protein ratio between "IBM" or "NBM" and "UF" control from three biological replicates (N=3). Data were analysed by Image Lab 6.0.1 and statistically

	analysed by unpaired t-test (significance levels of t-test p-values: n.s., not significant; * p-
	value<0.05; ** p-value <0.01).

Table 2

 2

	summarizes significantly down-or upregulated genes in mosquitoes depleted
	for APL1A or APL1C. As reported graphically, APL1A depletion caused
	downregulation of only one gene, and none were upregulated. In contrast, APL1C
	silencing significantly regulated 423 genes, 200 downregulated and 223 upregulated.
				Total number of
	Tested condition	Downregulated	Upregulated	differentially
				expressed genes
	dsAPL1A vs dsGFP	1	0	1
	dsAPL1C vs dsGFP	200	223

Table 2 . Number of up-, down-and total number of differentially expressed genes in each compared condition.

 2 The gene was defined as differentially expressed if adjusted p-

	value <0,05.

Table 3 . List of the immune-like genes, which expression is downregulated upon APL1C

 3

	depletion. Genes are enlisted according to the descending expression fold change between
	"dsAPL1C" and "dsGFP" (control) treatments. The columns include gene ID referred as the
	AGAP number; gene name, N/A stands for not annotated gene; expression foldchange and

log2foldchange, adjusted p-value (p-adj), gene description including encoded protein function or predicted protein domain based on the databases: VB-VectorBase Community Annotation, IP-Interpro, UP-UniPro.

Table 4 . List of the immune-like genes, which expression is upregulated upon APL1C

 4

	Gene ID	Gene name	FoldChange	log2FoldChange	p-adj	Gene description	Gene description source
	AGAP009751 ANCE2	1,868	0,901 0,00605 angiotensin-converting enzyme 2	VB
	AGAP004038 HPX8	1,858	0,893 0,0032 heme peroxidase 8		VB
	AGAP004036 HPX7	1,838	0,878 0,02739 heme peroxidase 7		VB
	AGAP003591 N/A	1,826	0,869 0,00944 LRR-repeat protein 1		VB
	AGAP011534 N/A	1,51	0,594 0,02302 Ankyrin repeat Ankyrin repeat and LEM domain-containing protein 2 IP
	AGAP004563 ANCE9	1,313	0,393 0,04951 angiotensin-converting enzyme 9	VB
	depletion. Genes are enlisted according to the ascending expression fold change between
	"dsAPL1C" and "dsGFP" (control) treatments. The columns include gene ID referred as the
	AGAP number; gene name, where N/A stands for not annotated gene; expression foldchange
	and log2foldchange, adjusted p-value (p-adj), gene description including encoded protein
	function or predicted protein domain based on the databases: VB-VectorBase Community
	Annotation, IP-Interpro, UP-UniPro.

  It has been recently reported that mosquito infection with Gram-negative, but not Gram-positive bacteria specifically induces APL1C cleavage by a still unidentified protease 122 . My thesis work showed that APL1C binds to the Plasmodium ookinetes but we still do not know if this binding requires or not the cleavage process, or if the cleavage of APL1C occurs posteriori of the parasite binding. Another possibility would be that previously reported cleavage of APL1C is bacteria-specific, and thus does not occur in the case of Plasmodium parasites. PRR have been described mainly as transmembrane but can be also present as soluble receptors. The peptidoglycan recognition proteins (PGRPs) are

conserved in both vertebrates and insects. In Drosophila, transmembrane, cytosolic and soluble forms of PGRPs display recognition and catalytic properties linked to their capacity to bind PGN 148-150 . C-type lectins (CTLs) are another example of PRRs that occur extracellularly and are either secreted or membrane-bound. C-type lectins are pattern recognition receptors that function in both mammalian and insect innate immunity through the carbohydrate recognition domain. In A. gambiae two CTLs cooperate to defend the mosquito against Gram-negative bacterial infections. CTL function was also assessed towards mosquito Plasmodium infection, where two CTL, CTL4 and CTLMA2 protect the ookinetes against a potent mosquito innate immune response, melanization

: 1, 2, 6, 20, 22, 29, S1, S5, S6 were created with BioRender.com

Ogunah, J. A., Lalah, J. O. & Schramm, K.-W. Malaria vector control strategies. What is appropriate towards sustainable global eradication? Sustainable Chemistry and Pharmacy 18, 100339, (2020).

  This p value was calculated using the method of R.A. Fisher to combine independent tests of significance174 . Notation NA (Not Applicable) indicates that the direction of phenotypic effect among experimental replicates was not consistent and therefore replicates were not statistically combined.

							Median values
	2 3	7B	NBM NBM	4 6	vs UF NBM vs UF NBM vs UF	1,11E+08 1,20E+08 3,48E+08	vs vs vs	1,64E+07 3,28E+05 6,56E+06	0,0095 0,0095 0,0159	< 0.0001
	4		NBM	10	NBM vs UF	1,78E+08	vs	3,03E+06	<0,0001
	3 4		IBM IBM	5 11	IBM vs UF IBM vs UF	6,06E+07 3,88E+08	vs vs	6,56E+06 3,03E+06	0,0317 <0,0001	< 0.0001
	--	--	--	--	NBM vs IBM NBM vs IBM	3,48E+08 1,78E+08	vs vs	6,06E+07 3,88E+08	0,1775 0,5573	NA
	5		LP	8	-	-	-	-	-	-
	6		LP	8	-	-	-	-	-	-
	7		LP	8	-	-	-	-	-	-
	5	14C	CLD	6	CLD vs LP	9,37E+06	vs	3,52E+07	0,0813
	6		CLD	10	CLD vs LP	1,42E+07	vs	1,19E+08	0,0676	0,0087
	7		CLD	10	CLD vs LP	1,80E+07	vs	1,04E+08	0,0343
	8		dsGFP	6	-	-	-	-	-	-
	9		dsGFP	6	-	-	-	-	-	-
	10		dsGFP	8	-	-	-	-	-	-
					dsNOX5/HPX2
	8	15C	dsNOX5/HPX2	6	vs dsGFP	2,82E+07	vs	1,98E+08	0,0152
	9		dsNOX5/HPX2	7	dsNOX5/HPX2 vs dsGFP	3,25E+06	vs	7,05E+07	0,0012	< 0.0001
					dsNOX5/HPX2
	10		dsNOX5/HPX2	8	vs dsGFP	3,70E+07	vs	1,46E+08	0,0379
	d Statistical differences for salivary glands infection intensity were tested for each replicate (dstarget
	gene vs dsGFP control) using the Wilcoxon-Mann-Whitney test.

b a The corresponding figure numbers associated with data. b Statistical differences for salivary glands infection prevalence were tested for each replicate (target gene vs dsGFP control) using the χ2 test.

c

Table S2 . Statistical analysis of P. berghei salivary glands infection prevalence following gene silencing.

 S2 Summary data for all experimental replicates testing the effect of a targeted gene silencing as compared to control treatment dsGFP. Statistically significant differences are indicated by green shading. Rows indicate target gene tested (injected dsRNA) for a given replicate, with the corresponding replicates indicated in the following row(s) . Individual p-values were calculated for each replicate by statistical comparison between the dsRNA-targeted gene and the corresponding dsGFP control showed in column "Experiment #". If the different replicates of a tested gene were consistent (display the same phenotypic direction), then the individual p-values were combined by Fisher's method "Fisher combined If the replicate phenotypes were not consistent, the individual p-values are shown but combining of p-values is not justified.

		AGAP001375	SRPN12	0,587	-0,768		0,01173398 serine protease inhibitor (serpin) 12				VB
		AGAP029185		0,587	-0,768		0,03890513 CBM21 (carbohydrate binding type-21) domain			IP
		AGAP001181		0,588	-0,767		0,01484981 N/A					N/A
		AGAP001344		0,593	-0,754		0,04919363 Transcription factor, T-box p53-like transcription factor, DNA-binding		IP
		AGAP013202		0,596	-0,746		0,03049047 N/A					N/A
		AGAP011666 AGAP005094		0,598 0,599	-0,742 -0,74		ANNEX 0,01271696 N/A ANNEX 0,0114621 Protein of unknown function DUF1397				N/A IP
		AGAP011911		0,606	-0,722		0,04405244 F-box protein 39					UP
		AGAP000198	Cht5-5	0,607	-0,719		0,03823344 Chitinase					UP
		Experiment # 1 2 3 4 Gene ID AGAP005503 AGAP007033 AGAP010058 AGAP009217 AGAP001669 AGAP008512 AGAP000113 AGAP011509 AGAP013201 AGAP006400 AGAP007319 AGAP010057 AGAP008444 AGAP010854 AGAP011564 AGAP029297 AGAP001486 AGAP005450 AGAP011749 AGAP029820 AGAP006835 AGAP008059 AGAP009415 AGAP009982 AGAP013459 AGAP004936 AGAP007974 AGAP011341 AGAP007349 AGAP013106 AGAP003038 prob". Table S3. APL1C controls sporozoite intensity in mosquito hemolymph. APL1C depletion Figure # a Injected dsRNA Number of mosquitoes Salivary glands infection prevalence (%) Infection prevalence -individual p-value b Infection prevalence -Fisher combined prob. c Salivary glands infection intensity (median) Infection intensity -individual p-value d Infection intensity -Fisher combined prob. c dsGFP 30 70 -----dsGFP 20 25 --6,40E+03 --dsGFP 20 65 --2,40E+03 --dsGFP 36 47,22 --2,90E+03 --17C dsGFP dsAPL1C 2 745 6 652 Gene name FoldChange log2FoldChange p-adj Gene description Gene description source SDR11 0,06 -4,055 3,95E-07 dehydrogenase/reductase SDR family member 11 precursor VB APL1C 0,151 -2,726 2,90E-17 Anopheles Plasmodium-responsive Leucine-Rich Repeat 1C VB PAS1 0,227 -2,139 0,0115104 neuronal PAS domain protein 1 VB CLIPB12 0,243 -2,043 0,01173398 CLIP-domain serine protease VB CPR6 0,324 -1,625 0,04941549 cuticular protein RR-2 family 6 VB 8512 0,332 -1,59 1,48E-05 NodB homology domain, Glycoside hydrolase/deacetylase, beta/alpha-barrel IP 113 0,341 -1,552 2,79E-07 Peptidase M14, carboxypeptidase A Cytosolic carboxypeptidase, N-terminal IP COEunkn 0,359 -1,478 0,0087826 carboxylesterase VB 3201 0,363 -1,462 0,04950774 Ecdysteroid kinase-like, Protein kinase-like domain superfamily, CHK kinase-like IP APH2 0,403 -1,31 0,00950344 alkaline phosphatase 2 VB 7319 0,432 -1,212 0,00889759 N/A N/A 0,44 -1,186 0,02827811 nicotinic acetylcholine receptor, beta-2 subunit VB CPLCG1 0,446 -1,164 0,00160066 cuticular protein CPLCG family (CPLCG1) VB SCF45 0,453 -1,141 0,00952942 solute carrier family 45, member 1/2/4 VB GGT 0,455 -1,137 0,04950774 glucosyl/glucuronosyl transferases VB 0,611 -0,711 0,03524546 Major facilitator superfamily IP 0,612 -0,707 0,04822763 N/A N/A 0,621 -0,687 0,03414776 Kazal domain IP 0,621 -0,687 0,0179084 Major facilitator superfamily domain IP 0,621 -0,686 0,01484981 ATP:guanido phosphotransferase, Glutamine synthetase/guanido kinase, catalytic domain IP 0,627 -0,674 0,02237205 N/A N/A CSP1 0,628 -0,671 0,0179084 chemosensory protein 1 VB 0,629 -0,668 0,01811537 lysophosphatidate acyltransferase VB 0,63 -0,666 0,00551591 N/A N/A 0,632 -0,662 0,02129007 N/A N/A 0,638 -0,649 0,02341124 EGF-like domain IP drm 0,638 -0,649 0,02362829 Protein drumstick UP 0,641 -0,641 0,02984576 Ets domain, Pointed domain, Sterile alpha motif/pointed domain superfamily, Winged helix DNA-binding domain superfamily IP 0,642 -0,64 0,02867749 N/A IP 0,644 -0,635 0,0478941 Niemann-Pick Type C-2 VB 0,648 -0,625 0,02373187 Major facilitator, sugar transporter-like, Sugar transporter, conserved site IP AGAP012648 0,46 -1,121 0,03487263 Sulfotransferase domain, P-loop containing nucleoside triphosphate hydrolase IP AGAP005470 0,648 -0,625 0,01426511 N/A IP
		1 2 3 AGAP029110 AGAP007786 results in higher number of sporozoites present in mosquito hemolymph. Infected mosquitoes dsAPL1C 30 96,67 0,0056 ---dsAPL1C 9 100 0,0002 4,44E+02 0,1898 dsAPL1C 34 84,85 0,0942 4,25E+03 0,5657 < 0.0001 9110 0,469 -1,093 0,02867749 C-type lectin-like/link domain superfamily IP 0,648 -0,625 0,03909671 isocitrate dehydrogenase (NAD+) VB AGAP003334 CPLCX2 0,474 -1,077 0,02778496 cuticular protein unclassified VB AGAP001748 ChS 0,476 -1,072 0,01545946 chitin synthase VB AGAP007939 0,649 -0,624 0,04375476 starch phosphorylase VB AGAP000986 CPAP3-D 0,652 -0,618 0,04997375 cuticular protein VB were perfused 17 d post-P. berghei infection (8 d post dsAPL1C or dsGFP treatment). The AGAP029383 0,477 -1,069 0,04961506 Pyruvate kinase, C-terminal domain superfamily IP AGAP001417 0,658 -0,603 0,03653976 Brain protein 44-like protein VB number of perfused sporozoites was counted in both studied conditions and reported in the AGAP001470 1470 0,486 -1,041 0,00667323 Leucine-rich repeat, typical subtype IP AGAP001052 0,66 -0,598 0,04989706 ubiquitin carboxyl-terminal hydrolase 2/21 VB NA AGAP005496 LRIM12 0,487 -1,039 0,01760889 leucine-rich immune protein (Short) VB AGAP001799 0,661 -0,598 0,03494485 tropomyosin 1 VB table. AGAP028512 0,504 -0,99 0,02877573 N/A N/A AGAP006260 0,661 -0,597 0,0478941 Z band alternatively spliced PDZ-motif protein 66 VB
		4 AGAP005459 AGAP003860 AGAP003600 AGAP008640	CPR16	0,505 0,665 0,508 0,666	dsAPL1C -0,985 -0,588 -0,978 -0,586	32	75 cuticular protein RR-1 family 16 0,0195 0,01650848 proline dehydrogenase 0,028741 0,02279322 Elongation of very long chain fatty acids protein 1,90E+03 0,02488032 N/A	0,642		VB VB UP N/A
		AGAP006480 AGAP010229		0,509 0,666	-0,974 -0,586		0,03487263 N/A 0,03282155 beta-ureidopropionase					N/A VB
		5 AGAP013507 AGAP004846	SCRB9	0,509 0,667	dsGFP -0,974 -0,583	18	61,11 0,01960246 N/A 0,01746087 Class B Scavenger Receptor (CD36 domain). --6,00E+03	-		N/A VB
		AGAP001969 AGAP012515	ATPsynF	0,51 0,667	-0,972 -0,584		0,04950774 polyubiquitin 0,01746087 F-type H+-transporting ATPase subunit f				VB VB
		6 AGAP009623 AGAP012643 AGAP007045	GAPDH LRIM15	0,513 0,668 0,514	dsGFP -0,964 -0,581 -0,961	36	50 0,0115104 glyceraldehyde 3-phosphate dehydrogenase --0,00979108 solute carrier family 7 (cationic amino acid transporter, y+ system) 6,39E+02 0,01484981 leucine-rich immune protein (TM) SEA domain, EGF-like domain, Cellulose/chitin-binding protein, N-terminal, DOMON domain, --	VB VB VB
		7 AGAP013192 AGAP007611 AGAP028028 AGAP009200	LRIM16A	0,514 0,669 0,514 0,669	dsGFP -0,96 -0,579 -0,959 -0,579	27	48,15 0,04875578 venom allergen 0,0179084 Galactose-binding-like domain superfamily --0,01173009 Leucine-rich immune protein (TM) 0,03564164 collagen type IV alpha	4,20E+03	-	-	VB IP UP VB
		AGAP010814 AGAP011355	TEP6	0,517 0,671	-0,952 -0,576		0,0238129 thioester-containing protein 6 0,04483169 Domain of unknown function DB, Immunoglobulin subtype 2, Fibronectin type III		VB IP
		8 AGAP003692 AGAP029127	CSP5	0,518 0,672	dsGFP -0,948 -0,574	40	72,5 0,03379828 Aminopeptidase 0,03681021 chemosensory protein 5 -	-	5,10E+03	-	-	UP VB
		AGAP007416 AGAP001313		0,519 0,673	-0,945 -0,571		0,02784284 SMAD domain, Dwarfin-type, SMAD/FHA domain superfamily 0,02279322 Muscular protein 20			IP VB
		5 AGAP005952 AGAP005010 AGAP001594 AGAP004643	SCRB6	0,52 0,673 0,526 0,674	dsTEP1 -0,943 -0,572 -0,926 -0,569	23	73,91 0,01964634 N/A 0,0055572 Homeobox KN domain, Iroquois-class homeodomain protein 0,382 2,90E+03 7,71E-05 GNAT domain, Acyl-CoA N-acyltransferase 0,0114621 Class B Scavenger Receptor (CD36 domain).	0,4233		N/A IP IP VB
		6 AGAP008368 AGAP010145 AGAP029054 AGAP010230	19B TEP14 NimB2	0,527 0,674 0,527 0,675	dsTEP1 -0,924 -0,569 -0,923 -0,566	43	67,44 0,03909671 thioester-containing protein 14 0,1158 0,03681021 Yellow 0,01800364 nimrod B2 0,0112639 MAGUK p55 subfamily member 3 0,21	6,00E+02	0,598	0,3517485	VB UP VB VB
		AGAP000424 AGAP001303	SAP1	0,528 0,676	-0,921 -0,564		0,03250892 N/A 0,02450875 chemosensory protein 6					N/A VB
		7 AGAP004809 AGAP003620 5 AGAP009871 AGAP012718 AGAP006900 AGAP028064 AGAP005878	APN1 CPR75 LRIM16B	0,528 0,678 0,531 0,535 0,678 0,535 0,682	dsTEP1 -0,92 -0,56 dsTEP3 -0,913 -0,903 -0,56 -0,901 -0,552	26 21	61,54 0,00889759 alanyl aminopeptidase N 1 0,3276 0,01890109 N/A 76,19 0,3091 0,01317147 cuticular protein RR-1 family 75 0,00057426 proline oxidase Zinc finger, RING-type, Lon, substrate-binding domain, Tetratricopeptide-like helical domain 6,50E+02 0,1402 2,55E+03 0,04961506 superfamily, PUA-like superfamily 0,1303 0,26 NA 0,04181769 Leucine-rich immune protein (TM) 0,04464053 POU domain transcription factor, class 3	VB N/A VB VB IP UP VB
		6 AGAP006898 AGAP028061 AGAP013245 AGAP004834	Cht6	0,537 0,682 0,538 0,683	dsTEP3 -0,897 -0,551 -0,894 -0,549	36	63,89 0,03680706 chitinase 0,01261935 Protein SOGA 0,234 0,03922705 N/A 0,02318625 PMP-22/EMP/MP20/Claudin superfamily	5,80E+03	0,0035		VB IP N/A IP
		AGAP010385 AGAP008400		0,545 0,683	-0,875 -0,551		0,03182168 N/A 0,00979108 Laminin G domain, Concanavalin A-like lectin/glucanase domain superfamily, CSPG repeat	N/A IP
		7 AGAP010562 AGAP002859 AGAP003060 AGAP007876		dsTEP1/TEP3 0,546 -0,872 0,684 -0,548 0,55 -0,861 0,684 -0,549	20	60 0,03494485 Amino acid/polyamine transporter I, Cationic amino acid transporter, C-terminal 0,4208 1900 0,6591 0,57 0,02847867 solute carrier family 8 (sodium/calcium exchanger) 4,37E-05 N/A 0,01327857 N/A	NA	IP VB N/A N/A
	2645	8 AGAP008209 AGAP004799 AGAP001582 AGAP002204 AGAP005043 AGAP001603 AGAP004263 AGAP003354 AGAP007061 AGAP028680 AGAP012447 AGAP028612 AGAP010193 AGAP003695 AGAP010891 AGAP008091 AGAP029564 AGAP003775 AGAP007849 AGAP029055 AGAP007963 AGAP005837 AGAP007717 AGAP009224 AGAP028167 AGAP012256 AGAP012399 AGAP013061 AGAP028496 AGAP001375 AGAP029185 AGAP001369 AGAP001181 AGAP006452 AGAP001344 AGAP007373 AGAP013202 AGAP011666 AGAP010233 AGAP004457 AGAP005094 AGAP004237 AGAP011911 AGAP001413 AGAP000198 AGAP006179 AGAP029297 AGAP001486 AGAP002456 AGAP005450 AGAP029561 AGAP011749 AGAP010502 AGAP029820 AGAP004642 AGAP006835 AGAP008516 AGAP008059 AGAP010750 AGAP009415 AGAP000305 AGAP009982 AGAP007629	dsTEP1/TEP3 0,552 -0,858 0,553 -0,856 0,688 -0,54 0,554 -0,853 0,688 -0,541 0,557 -0,845 0,689 -0,538 0,557 -0,845 0,69 -0,535 0,558 -0,842 0,691 -0,534 0,563 -0,828 0,693 -0,529 0,571 -0,807 0,694 -0,528 0,573 -0,804 0,694 -0,527 0,575 -0,798 0,695 -0,526 0,577 -0,793 0,695 -0,525 COEJHE5E 0,58 CYP6M1 CYP325D1 TO1 A5R3 GLURIIe CTLGA3 CLIPE1 -0,786 0,581 -0,783 0,695 -0,525 0,581 -0,783 0,695 -0,525 0,696 -0,523 0,582 -0,781 0,7 -0,514 SRPN12 0,587 -0,768 0,587 -0,768 0,701 -0,512 0,588 -0,767 0,701 -0,513 0,593 -0,754 0,701 -0,512 0,596 -0,746 0,598 -0,742 0,701 -0,512 0,702 -0,51 0,599 -0,74 0,704 -0,505 0,606 -0,722 0,705 -0,505 Cht5-5 0,607 -0,719 0,706 -0,502 0,611 -0,711 0,612 -0,707 0,707 -0,5 0,621 -0,687 0,708 -0,497 0,621 -0,687 0,709 -0,497 0,621 -0,686 NPF 0,71 -0,495 0,627 -0,674 0,71 -0,494 CSP1 0,628 -0,671 0,71 -0,493 0,629 -0,668 0,711 -0,492 0,63 -0,666 LANB2 0,711 -0,492	24	79,17 0,00645541 cytochrome P450 0,551 0,0005304 N/A 0,03681021 Ankyrin repeat-containing domain superfamily 8,40E+03 0,03487263 cytochrome P450 0,03187828 Inactive dipeptidyl peptidase 10 0,0114621 mitochondrial 18 kDa protein 0,00889759 takeout 1 0,01317147 antigen 5 related protein 3 0,03487263 Leucine-rich repeat, typical subtype 0,02503675 Leucine-rich repeat, cysteine-containing subtype, F-box domain 0,03823344 ionotropic receptor GLURIIe 0,0330731 N/A 0,03441075 C-type lectin (CTL) -galactose binding 0,02075811 aminopeptidase N 0,03225499 ariadne-1 0,00051006 CLIP-domain serine protease 0,03718961 Immunoglobulin-like domain, CD80-like, immunoglobulin C2-set 0,04464053 N/A 0,03049047 laminin, alpha 1/2 0,02215262 EGF-like domain 0,0282315 Sarcoplasmic calcium-binding protein 0,01173009 carboxylesterase GroES-like superfamily, Polyketide synthase, enoylreductase domain, NAD(P)-binding domain 0,4738 0,03161692 SH3 domain 0,02705207 superfamily 0,03383209 0,04528598 Polypeptide N-acetylgalactosaminyltransferase Proteinase, regulatory CLIP domain, Serine proteases, trypsin domain, Peptidase S1A, chymotrypsin family, Peptidase S1, PA clan 0,01850004 maltase 0,02160989 Haemolymph juvenile hormone binding, Takeout superfamily 0,02222595 Zinc finger C2HC domain-containing protein 0,01173398 serine protease inhibitor (serpin) 12 SH3 domain, IMD/I-BAR domain, AH/BAR domain superfamily, I-BAR domain containing protein 0,03890513 CBM21 (carbohydrate binding type-21) domain 0,03282155 IRSp53/IRTKS/Pinkbar 0,01484981 N/A 0,03681021 Thioredoxin domain 0,04919363 Transcription factor, T-box p53-like transcription factor, DNA-binding 0,03379828 Tetraspanin 0,03049047 N/A 0,01271696 N/A 0,025216 integrin beta 1 0,03718961 Sugar transporter ERD6-like 4 0,0114621 Protein of unknown function DUF1397 0,03182418 nuclear lamin L1 alpha 0,04405244 F-box protein 39 0,02373187 N/A 0,03823344 Chitinase 0,01271696 troponin C 0,03524546 Major facilitator superfamily P-loop containing nucleoside triphosphate hydrolase, Dynamin-type guanine nucleotide-binding (G) VB IP N/A VB VB VB VB IP VB VB IP VB N/A VB VB IP VB VB N/A VB IP VB IP IP UP VB IP IP IP VB IP IP IP N/A UP IP N/A VB VB N/A VB IP N/A UP VB UP IP 0,04822763 N/A 0,03049047 domain, EH domain-containing protein, N-terminal IP N/A 0,03414776 Kazal domain 0,00889759 N/A N/A IP 0,0179084 Major facilitator superfamily domain 0,04372467 N/A N/A IP 0,01484981 ATP:guanido phosphotransferase, Glutamine synthetase/guanido kinase, catalytic domain 0,03374923 Neuropeptide F UP IP 0,02237205 N/A 0,02561527 nicotinate phosphoribosyltransferase VB N/A 0,0179084 chemosensory protein 1 0,0375236 ryanodine receptor 2 VB VB 0,01811537 lysophosphatidate acyltransferase 0,04961506 SPARC VB VB 0,00551591 N/A N/A 0,00944157 laminin gamma 1 VB
		AGAP013459 AGAP004936 AGAP001366 AGAP007974 AGAP007791 AGAP011341 AGAP008702 AGAP007349 AGAP005247 AGAP003785	drm GPRNPR2	0,632 0,638 0,712 0,638 0,713 0,641 0,713 0,642 0,714 0,716	-0,662 -0,649 -0,49 -0,649 -0,489 -0,641 -0,487 -0,64 -0,486 -0,482		130 Serine proteases, trypsin domain, Peptidase S1A, chymotrypsin family, Serine protease gd, N-0,02129007 N/A N/A 0,02341124 EGF-like domain 0,02279322 terminal domain IP IP 0,02362829 Protein drumstick 0,03201638 sodium/potassium-transporting ATPase subunit beta VB UP 0,02984576 0,03161692 Putative neuropeptide receptor 2 UP Ets domain, Pointed domain, Sterile alpha motif/pointed domain superfamily, Winged helix DNA-binding domain superfamily IP 0,02867749 N/A IP 0,03282155 Protein of unknown function DUF4728 IP 132 0,03653976 glucose dehydrogenase (acceptor) VB
		AGAP013106 AGAP003843		0,644 0,716	-0,635 -0,482		0,0478941 Niemann-Pick Type C-2 0,04950774 cytochrome c heme-lyase					VB VB
		AGAP003038 AGAP010394		0,648 0,717	-0,625 -0,481		0,02373187 Major facilitator, sugar transporter-like, Sugar transporter, conserved site 0,0431993 Patched-related		IP UP
		AGAP005470 AGAP010938		0,648 0,718	-0,625 -0,477		0,01426511 N/A 0,03909671 Trp repressor/replication initiator, Brinker DNA-binding domain			IP IP
		AGAP007786 AGAP000847		0,648 0,72	-0,625 -0,473		0,03909671 isocitrate dehydrogenase (NAD+) 0,03462588 CDC-like kinase					VB VB

Table S4 . Full list of genes, which expression was downregulated upon APL1C depletion in RNAseq experiment. Genes

 S4

		AGAP009224 AGAP012256 AGAP007549 AGAP007502 AGAP008063 AGAP001380 AGAP000681	0,695 0,695	1,774 1,551 1,547 1,434 1,429	-0,525 -0,525	0,827 0,633 0,629 0,52 0,515	0,02705207 superfamily 0,04528598 Polypeptide N-acetylgalactosaminyltransferase 0,030783776 Six-bladed beta-propeller, TolB-like Major royal jelly protein/protein yellow 0,008897593 kinesin family member 11 0,036201432 exosome complex component CSL4 0,023933025 translation initiation factor 6 0,0436892 tRNA:m4X modification enzyme	IP	VB VB VB VB	IP UP
		AGAP012399 AGAP002532 AGAP001453 AGAP000496	0,696	1,765 1,546 1,422	-0,523	0,82 0,629 0,508	0,01850004 maltase 0,004238876 Cyclin, C-terminal domain Cyclin, N-terminal 0,049973746 N/A 0,019328566 geminin	IP	N/A VB	VB
		AGAP028496 AGAP001369 AGAP005844 AGAP011454 AGAP006941 AGAP007505 AGAP008879 AGAP009442 AGAP006452 AGAP011845 AGAP003883 AGAP009431 RpS21	0,7 0,701 0,701	1,76 1,544 1,42 1,76 1,539 1,419 1,751 1,537 1,415	-0,514 -0,512 -0,513	0,816 0,626 0,506 0,816 0,622 0,505 0,808 0,62 0,501	0,02222595 Zinc finger C2HC domain-containing protein 0,03282155 0,006233202 Bifunctional purine biosynthesis protein 0,001831642 rotatin 0,037189609 ATP-dependent RNA helicase DDX51/DBP6 SH3 domain, IMD/I-BAR domain, AH/BAR domain superfamily, I-BAR domain containing protein VB VB VB IRSp53/IRTKS/Pinkbar 0,014849805 vitellogenic carboxypeptidase-like protein VB 0,011462104 Protein of unknown function DUF389 IP 0,049415485 cyclin-dependent kinase regulatory subunit CKS1 VB 0,03681021 Thioredoxin domain ANNEX ANNEX 0,022152616 Histone H2A UP ANNEX 0,000709794 peptidyl-tRNA hydrolase, PTH2 family VB ANNEX 0,00055617 40S ribosomal protein S21 UP ANNEX	IP IP IP
		AGAP007373 AGAP011713 AGAP003578	0,701	1,734 1,535	-0,512	0,794 0,618	0,03379828 Tetraspanin 0,016059772 ribonuclease P protein subunit POP4 0,033798283 aldehyde dehydrogenase (NAD+) Major facilitator superfamily MFS transporter	VB	VB	UP
		AGAP010233 AGAP006404 AGAP001166 AGAP003205	0,701	1,733 1,532 1,411	-0,512	0,793 0,616 0,497	0,025216 0,018003641 N/A integrin beta 1 0,021172723 GINS complex subunit 4 0,036174833 superfamily	N/A	VB IP	VB
		AGAP004457 AGAP004237 AGAP001413 Gene ID AGAP012040 AGAP009792 AGAP011383 AGAP006179 AGAP006728 COEAE7G 0,702 0,704 0,705 Gene name FoldChange -0,51 -0,505 -0,505 1,724 0,786 log2FoldCha 0,03718961 Sugar transporter ERD6-like 4 0,03182418 nuclear lamin L1 alpha 0,02373187 N/A nge p-adj Gene description 0,032254989 N/A 1,719 0,781 0,000530401 importin subunit alpha-2 1,41 0,495 0,037458371 rRNA-processing protein EBP2 RNA recognition motif domain Tudor domain Nucleotide-binding alpha-beta plait domain superfamily N/A VB 2-oxoisovalerate dehydrogenase E2 component 0,706 -0,502 0,01271696 troponin C 10,483 3,39 4,20E-10 carboxylesterase AGAP001699 1,713 0,777 0,048918391 fatty-acid amide hydrolase 2 VB SNase-like, OB-fold superfamily RNA-binding domain AGAP000549 1,409 0,494 0,049507741 (dihydrolipoyl transacylase) P-loop containing nucleoside triphosphate hydrolase, Dynamin-type guanine nucleotide-binding (G) Gene description VB VB source VB N/A VB VB VB AGAP029790 9790 10,297 3,364 0,0324689 Domain of unknown function DUF4806 IP AGAP012192 1,712 0,776 0,008897593 DNA mismatch repair protein MLH1 VB AGAP010722 1,529 0,612 0,028086615 superfamily IP AGAP002961 1,409 0,495 0,036810206 ribosomal RNA-processing protein 12 VB
		AGAP002456 AGAP029561 AGAP010502 AGAP004642 AGAP008516 AGAP010750 AGAP000305 AGAP007629 AGAP001366 AGAP007791 AGAP008702 AGAP005247 AGAP003785 AGAP003843 AGAP010394 AGAP010938 AGAP000847 AGAP008366 AGAP009693 AGAP006063 AGAP008246 GBD NPF LANB2 GPRNPR2 TEP2 AGAP002846 AGAP003090 AGAP009830 AGAP029411 9411 AGAP002378 AGAP013324 AGAP008292 TRYP4 AGAP009381 CRBP AGAP012477 GBD_2 AGAP006727 COEAE6G 0,707 0,708 0,709 0,71 0,71 0,71 0,711 0,711 0,712 0,713 0,713 0,714 0,716 0,716 0,717 0,718 0,72 0,72 0,721 0,722 AGAP012375 AGAP028639 AGAP004239 AGAP001224 AGAP011676 UP2M AGAP003350 GTP AGAP029623 9623 AGAP007300 AP AGAP007959 7959 AGAP013642 U1 AGAP001423 BPBP AGAP007122 TU1 AGAP003974 AGAP001529 AGAP005917 AGAP003552 AGAP007417 AGAP000479 AGAP007635 AGAP005581 AGAP000719 Ahcy13 AGAP013400 AGAP002478 AGAP005800 AGAP011534 AGAP029374 AGAP013023 AGAP005149 AGAP006234 AGAP002967 AGAP011966 AGAP003890 AGAP005922 AGAP012894 AGAP011887 AGAP010538 AGAP028053 AGAP001352 1352 AGAP005260 AGAP007668 eIF3g AGAP008290 TRYP6 AGAP003594 AGAP006438 AGAP007556 0,724 AGAP005052 AGAP009825 AGAP002151 AGAP009569 0,724 AGAP005296 U11_1 AGAP011897 AGAP013441 AGAP008118	-0,5 -0,497 -0,497 -0,495 -0,494 -0,493 -0,492 -0,492 -0,49 -0,489 -0,487 -0,486 -0,482 -0,482 -0,481 -0,477 -0,473 -0,475 -0,473 -0,47 2,577 1,711 1,528 1,406 2,419 1,71 1,528 1,403 2,36 2,32 1,707 1,698 1,526 1,518 1,402 2,264 2,246 2,147 2,122 2,113 2,041 2,026 2,018 1,695 1,515 1,399 1,69 1,515 1,687 1,511 1,685 1,51 1,399 1,684 1,682 1,51 1,398 1,664 1,498 1,397 1,497 1,397 1,492 1,392 1,997 1,663 1,492 1,389 1,973 1,661 1,387 1,66 1,491 1,655 -0,465 1,654 1,491 1,386 -0,466 1,971 1,65 1,487 1,385	0,03049047 0,00889759 N/A domain, EH domain-containing protein, N-terminal 0,04372467 N/A 0,03374923 Neuropeptide F 0,02561527 nicotinate phosphoribosyltransferase 0,0375236 ryanodine receptor 2 0,04961506 SPARC 0,00944157 laminin gamma 1 0,02279322 Serine proteases, trypsin domain, Peptidase S1A, chymotrypsin family, Serine protease gd, N-terminal domain 0,03201638 sodium/potassium-transporting ATPase subunit beta 0,03161692 Putative neuropeptide receptor 2 0,03282155 Protein of unknown function DUF4728 0,03653976 glucose dehydrogenase (acceptor) 0,04950774 cytochrome c heme-lyase 0,0431993 Patched-related 0,03909671 Trp repressor/replication initiator, Brinker DNA-binding domain 0,03462588 CDC-like kinase 0,01847926 thioester-containing protein 2 0,03618715 RNA pseudouridylate synthase domain-containing protein 2 0,0179084 N/A 1,366 0,016879105 gamma-butyrobetaine dioxygenase 0,775 0,041598991 Trunk VB 0,612 0,013462018 ubiquitin-conjugating enzyme E2 O VB 0,491 0,01612065 Chitin binding domain IP 1,274 0,024111017 N/A 0,774 0,023876565 Adenylosuccinate lyase UP 0,612 0,036267067 putative G-protein coupled receptor GPCR VB 0,489 0,036201432 trypsin 4 VB 1,239 0,0375236 Cellular retinaldehyde-binding protein 1,214 0,013171475 gamma-butyrobetaine dioxygenase 0,772 0,015519838 carboxylesterase VB 0,764 0,017608886 protein aurora borealis 0,609 0,014757327 N/A N/A cleavage and polyadenylation specificity factor VB 0,602 0,034317264 polo-like kinase 1 VB 0,488 0,025215999 subunit 3 VB 1,179 7,71E-05 uncoupling protein 2, mitochondrial 1,167 0,019596342 phosphoenolpyruvate carboxykinase (GTP) 1,103 0,010492105 Sulfotransferase domain P-loop containing nucleoside triphosphate hydrolase 1,085 0,019602457 alkaline phosphatase 1,079 0,006046664 N/A 1,029 0,030548251 U1 spliceosomal RNA [Source:RFAM;Acc:RF00003] 1,018 0,013739866 Bifunctional purine biosynthesis protein 1,013 0,000530401 tubulin, alpha 1 0,761 0,008897593 tRNA (cytidine32/guanosine34-2'-O)-methyltransferase 0,6 0,001102944 H/ACA ribonucleoprotein complex subunit UP 0,484 0,036201432 ATP-dependent DNA helicase Q4 VB VB 0,757 0,023186247 SET and MYND domain-containing protein 5 0,599 0,029157396 E3 ubiquitin-protein ligase SHPRH VB Cytosolic fatty-acid binding Lipocalin/cytosolic fatty-VB 0,755 0,017422566 pre-rRNA-processing protein IPI3 0,595 0,014849805 60S ribosomal protein L7 VB acid binding domain Calycin Intracellular lipid binding VB 0,753 0,00105879 3-hydroxyisobutyrate dehydrogenase 0,595 0,028478668 Adenosylhomocysteinase UP 0,485 0,014432066 protein IP UP 0,752 0,008897593 cyclin B Ankyrin repeat Ankyrin repeat and LEM domain-Zinc finger, AD-type Domain of unknown function VB 0,75 0,01612065 DNA replication licensing factor MCM7 0,594 0,023015671 containing protein 2 IP 0,484 0,039588096 DUF4806 IP VB 0,735 0,03161692 0,583 0,006127055 H/ACA ribonucleoprotein complex subunit 3 VB 0,483 0,049507741 protein SHQ1 VB Histone RNA stem-loop-binding protein SLBP1/SLBP2 0,582 0,016802001 bloom syndrome protein VB 0,482 0,036187152 transcription termination factor 2 VB Histone RNA hairpin-binding protein, RNA-binding domain IP 0,577 0,024880322 U3 small nucleolar ribonucleoprotein protein IMP4 VB 0,477 0,044831691 DNA-directed RNA polymerase III subunit RPC5 VB 0,998 0,015519838 Histone H2B 0,734 0,017908403 nuclear pore complex protein Nup37 0,578 0,0381339 M-phase phosphoprotein VB 0,474 0,047484681 N/A N/A VB 0,98 0,023186247 0,732 0,011510398 dTMP kinase Zinc finger, AD-type Zinc finger C2H2-type 0,472 0,006887628 Eukaryotic translation initiation factor 3 subunit G UP VB Haemolymph juvenile hormone binding Takeout superfamily 0,731 0,020786941 trypsin 6 0,576 0,036857325 Transcription factor Grauzone IP Regulator of chromosome condensation, RCC1 VB 0,727 0,006046664 ribosomal biogenesis protein LAS1 VB TRM13/UPF0224 family, U11-48K-like CHHC zinc Regulator of chromosome condensation 1/beta-0,03487263 Immunoglobulin subtype 2, Fibronectin type III U11/U12 small nuclear ribonucleoprotein 65 kDa 0,726 0,03653976 deoxyribodipyrimidine photo-lyase VB 0,576 0,018500044 finger domain Zinc finger C2H2 superfamily IP 0,471 0,033160605 lactamase-inhibitor protein II IP 0,01271696 syntenin-1 isoform 1 0,979 0,01964634 protein 0,722 0,018003641 N/A N/A 0,572 0,023186247 SS18 family IP 0,47 0,023352255 serine/threonine-protein kinase Chk1 VB	IP N/A N/A UP VB VB VB VB IP VB UP IP VB VB UP IP VB VB VB N/A VB UP VB VB VB IP VB N/A VB VB UP IP N/A IP VB VB
		AGAP010436 AGAP007364 7364 AGAP010918 AGAP004018 AGAP007020 TPX5	0,729	-0,456 1,956 1,645 1,486 1,378	0,03049047 adenylate cyclase 2 0,968 0,009791078 Maternal protein exuperantia 0,718 0,038914815 cleavage stimulation factor subunit 2 0,571 0,023186247 PDZ domain Harmonin 0,462 0,049615058 thioredoxin peroxidase 5	VB	IP VB	IP	VB
		AGAP002492 AGAP004596 AGAP006241 INX2 PyK AGAP008487 AGAP000374 AGAP029620 AGAP000162 CBS AGAP000168 GPRFZ3 AGAP004335 AGAP009579 AGAP007005 AGAP007788 AGAP002513 AGAP007833 AGAP029606 AGAP002010 AGAP000331 AGAP000815 INTB AGAP001590 AGAP005057 AGAP008914 AGAP007198 AGAP002898 GSTZ1 AGAP009638 AGAP000304 AGAP008254 AGAP005032 AGAP012305 AGAP029317 AGAP006233 AGAP029627 AGAP002088 AGAP003029 AGAP012686 AGAP005174 AGAP002337 eIF3d AGAP000772 772 AGAP001522 AGAP000416 AGAP009751 ANCE2 AGAP011652 AGAP008771 AGAP003086 AGAP002394 AGAP002106 AGAP004038 HPX8 AGAP008738 AGAP002706 AGAP002113 AGAP010540 540 AGAP005829 MAS_1 AGAP000180 PC AGAP004036 HPX7 AGAP028655 8655 AGAP003591 LRR1 AGAP007991 AGAP002387 AGAP029470 AGAP010789 AGAP028653 AGAP002985 AGAP029584 AGAP002117 AGAP002653 AGAP029679 AGAP005629 AGAP003264 AGAP006092 AGAP007026 Ccs AGAP011393 AGAP009024 AGAP011309 AGAP000650 AGAP027988 AGAP010978 AGAP003740 AGAP008163 AGAP006997 Aats-ala-m 0,733 0,735 0,735 0,736 0,736 0,738 0,739 0,743 0,744 0,747 0,751 0,752 0,753 0,754 0,754 0,757 0,759 0,761 0,761 0,765 0,766 0,767 0,773 AGAP010941 AGAP009488 AGAP002404 AGAP003545 Osk AGAP001595 RpS29 AGAP001141 AGAP003087 AGAP004825 AGAP029794 AGAP009862	-0,448 -0,444 1,954 1,486 1,377 -0,445 1,931 1,482 -0,442 -0,442 -0,438 -0,437 -0,428 -0,426 -0,421 -0,413 -0,412 -0,409 -0,408 -0,408 -0,401 -0,398 -0,393 -0,394 -0,386 -0,384 -0,384 -0,372 1,912 1,481 1,645 1,48 1,375 1,644 1,473 1,366 1,881 1,641 1,364 1,868 1,641 1,472 1,861 1,471 1,363 1,858 1,638 1,471 1,363 1,852 1,844 1,84 1,838 1,829 1,826 1,822 1,82 1,633 1,624 1,47 1,363 1,623 1,469 1,357 1,623 1,469 1,355 1,618 1,355 1,617 1,469 1,355 1,613 1,467 1,346 1,606 1,464 1,345 1,601 1,464 1,343 1,6 1,46 1,339 1,816 1,598 1,459 1,335	0,04748468 nuclear respiratory factor 1 0,01800364 pyruvate kinase 0,967 9,44E-05 Innexin inx2 0,571 0,026506785 Sphingomyelin phosphodiesterase 0,461 0,034944849 anaphase-promoting complex subunit 1 Copper type II, ascorbate-dependent 0,03078378 Thrombospondin type-1 (TSP1) repeat, Somatomedin B domain 0,949 0,015459457 Cystathionine beta-synthase monooxygenase, N-terminal DOMON domain 0,568 0,030490471 Putative frizzled receptor 3 Forkhead-associated (FHA) domain Zinc finger, PHD-0,02117272 filamin 0,04961506 dihydropyridine-sensitive l-type calcium channel 0,02650679 N/A 0,02925868 E3 ubiquitin-protein ligase RNF31 0,0005304 Defective in cullin neddylation protein 0,02143453 FAM21/CAPZIP domain 0,01261935 IQ motif, EF-hand binding site, Myosin head, motor domain, P-loop containing nucleoside UP VB UP triphosphate hydrolase, 0,04981479 N/A 0,02741115 low density lipoprotein-related protein 2] 0,02318625 integrin beta subunit 0,03618715 DBB domain, Ankyrin repeat-containing domain superfamily 0,01569346 Resistance to inhibitors of cholinesterase protein 3, N-terminal 0,02561527 Basic-leucine zipper domain 0,02535361 N/A 0,03489037 glutathione S-transferase zeta class 1 0,03494485 Stabilizer of axonemal microtubules 1/2 0,04989706 Protein twisted gastrulation 0,03379828 VWFC domain 0,04950774 calnexin 0,04950774 Muscle LIM protein at 84B 0,935 0,039588096 PHM/PNGase F domain superfamily Tyramine beta-0,566 0,023015671 Phospholipase D-like domain IP type SMAD/FHA domain superfamily PHD finger Exoribonuclease, phosphorolytic domain 1 Ribosomal 0,718 0,049973746 hydroxylase/Dopamine beta-hydroxylase IP 0,566 0,018596807 U3 small nucleolar RNA-associated protein 15 VB 0,459 0,036201432 protein 12, MRG binding domain superfamily IP protein S5 domain 2-type fold PNPase/RNase PH domain superfamily 0,717 0,049507741 Zinc finger C2H2-type IP 0,559 0,02827811 nucleoporin SEH1 VB 0,45 0,027842842 Eukaryotic translation initiation factor 3 subunit D UP 0,912 0,019328566 N/A 0,714 0,009529416 Thyroid receptor-interacting protein 13 VB DNA-directed RNA polymerases I and III subunit 0,448 0,030053919 hydroxyacylglutathione hydrolase VB 0,901 0,006046664 angiotensin-converting enzyme 2 0,714 0,024988431 AAA family ATPase, CDC48 subfamily protein VB 0,558 0,036187152 RPAC1 VB xeroderma pigmentosum group C-complementing 0,896 0,001831642 TMEM192 family Eukaryotic translation initiation factor 4E binding 0,557 0,036810206 DNA-directed RNA polymerase III subunit RPC3 VB 0,447 0,0324689 protein VB 0,893 0,003199427 heme peroxidase 8 0,712 0,048387263 protein IP 0,556 0,023812903 small nuclear ribonucleoprotein G VB 0,446 0,023409625 cytochrome b5 VB 0,889 0,010020081 N/A 0,883 0,008897593 microtubule-associated protein, RP/EB family 0,88 0,0112639 phosphoribosylaminoimidazole carboxylase 0,878 0,02739326 heme peroxidase 7 0,871 0,006887628 N/A 0,869 0,009441568 LRR-repeat protein 1 0,866 0,034317264 Triacylglycerol lipase family Lipase/vitellogenin Alpha/Beta hydrolase fold Lipase, N-terminal 0,864 0,004983856 acid phosphatase 0,707 0,019448835 Sterile alpha motif domain K Homology domain IP 0,7 0,023352255 EB domain 0,555 0,028478668 Pleckstrin homology domain IP 0,447 0,017608886 Structural maintenance of chromosomes protein 6 UP IP 0,698 0,023196353 N/A 0,555 0,034944849 Cell death regulator Aven IP 0,44 0,045285977 phenylalanyl-tRNA synthetase alpha chain VB N/A 0,699 0,034944849 Zinc finger, AD-type Zinc finger C2H2-type 0,555 0,03823344 N/A N/A 0,438 0,036810206 histone acetyltransferase 1 VB IP 0,694 0,027272801 U3 small nucleolar RNA-associated protein 4 RNA polymerase I-specific transcription initiation 0,439 0,043199303 copper chaperone for superoxide dismutase VB VB 0,693 0,018115369 integrator complex subunit 7 0,554 0,035419211 factor RRN3 VB 0,438 0,044633666 nuclear GTP-binding protein VB VB 0,689 0,015519838 ribonucleases P/MRP protein subunit RPP40 0,553 0,034910795 Zinc finger, AD-type Zinc finger C2H2-type IP 0,429 0,037106786 nuclear pore complex protein Nup62 VB VB 0,684 0,046466887 N/A 0,55 0,029845759 U4/U6 small nuclear ribonucleoprotein SNU13 VB 0,428 0,036201432 alanyl-tRNA synthetase, mitochondrial VB N/A 0,679 0,027784962 Zinc finger C2H2-type Zinc finger protein 511 0,55 0,034910795 histone transcription regulator VB 0,425 0,049615058 cullin 5 VB IP 0,678 0,020044331 protein oskar 0,546 0,010729313 40S ribosomal protein S29 VB 0,421 0,044831691 Zinc finger C2H2-type IP VB 0,861 0,009953441 TMEM192 family 0,676 0,022564284 Serine proteases, trypsin domain Peptidase S1A, WD40 repeat WD40/YVTN repeat-like-containing PapD-like superfamily Immunoglobulin-like fold ADP-ribose pyrophosphatase, mitochondrial IP 0,545 0,031358359 chymotrypsin family IP 0,417 0,048227633 domain superfamily IP	VB VB IP VB VB N/A VB UP IP IP N/A VB VB IP IP IP N/A VB IP VB IP VB VB N/A VB UP IP VB IP VB N/A VB VB VB N/A VB IP VB IP
		AGAP007049 AGAP006389 AGAP005400 AGAP011145 AGAP000427 AGAP004008 AGAP002409 AGAP002121 AGAP010586 AIMP1 AGAP008763 AGAP008015 AGAP007817 AGAP005320 AGAP001023 AGAP009606 AGAP029259	0,774 0,776 0,78 0,78 0,793	-0,369 -0,366 -0,358 1,811 1,802 1,597 1,457 1,453 1,335 -0,359 1,795 1,597 1,45 -0,334 1,791 1,591	0,01441075 N/A 0,01944884 ribonuclease kappa 0,03057533 four and a half LIM domains 0,856 0,033798283 ATP-dependent RNA helicase DDX56/DBP9 0,85 0,005953354 vitellogenin receptor 0,676 0,029845759 0,543 0,006127055 tRNA pseudouridine38-40 synthase aminoacyl tRNA synthase complex-interacting Protein kinase domain Serine-threonine/tyrosine-protein kinase, catalytic domain 0,539 0,016879105 DNA-directed RNA polymerase II subunit RPB7 0,417 0,029255508 multifunctional protein 1 0,01932857 MIF4G-like, type 3, Armadillo-type fold 0,844 0,005266262 lamin 0,675 0,017908403 Protein NEDD1 0,536 0,039878744 U3 small nucleolar RNA-interacting protein 2 Elongation factor EFG, domain V-like Transcription IP UP 0,03681021 myofilin variant B 0,841 0,01042075 Domain of unknown function DUF3421 DM9 repeat VB VB VB VB 0,67 0,0112639 N/A N/A RNA recognition motif domain Nucleotide-binding factor, GTP-binding domain Translation elongation	VB VB VB IP	N/A VB VB IP VB
		AGAP008046 AGAP011858 AGAP007145 AGAP011677	0,793	-0,335 1,791 1,584 1,335	0,03414776 Protein kinase C and casein kinase substrate in neurons 2 protein 0,841 0,011510398 zinc finger HIT domain-containing protein 3 0,663 0,017908403 N/A alpha-beta plait domain superfamily RNA-binding 0,417 0,020085987 factor EFTu-like, domain 2	N/A	IP	VB	UP
	2660 2662 2663 2661	are enlisted according to the descending expression fold change between "dsAPL1C" and "dsGFP" (control) treatments. The columns AGAP004689 0,797 -0,327 0,0282315 Plexin domain-containing protein IP AGAP011459 0,804 -0,315 0,03909671 Cyclic nucleotide-binding domain, Ion transport domain, RmlC-like jelly roll fold AGAP001333 st 1,783 0,834 0,011462104 protein scarlet Nucleotide-binding alpha-beta plait domain superfamily AGAP009336 1,45 0,536 0,022152616 domain superfamily IP AGAP008000 1,334 0,416 0,044640528 sepiapterin reductase VB VB IP AGAP006645 0,809 -0,307 0,03374923 Leucine-rich repeat, typical subtype IP AGAP007474 0,823 -0,281 0,02721754 Talin-1 VB AGAP009668 0,85 -0,234 0,03161692 lysosomal-associated membrane protein 1/2 VB AGAP002581 1,782 0,833 0,019328566 Meiosis regulator and mRNA stability factor 1 OST-AGAP002535 1,449 0,535 0,023186247 serine/threonine-protein phosphatase PGAM5 VB AGAP002968 1,324 0,405 0,048634299 thiamine pyrophosphokinase VB MCM domain Nucleic acid-binding, OB-fold Mini-AGAP007823 1,582 0,662 0,049415485 HTH/LOTUS domain IP AGAP007413 1,445 0,531 0,033798283 BRCT domain Microcephalin-like IP AGAP005115 1,323 0,404 0,044831691 N/A N/A chromosome maintenance protein MCM, AAA-lid domain AGAP009048 1,582 0,662 0,049897056 protein arginine N-methyltransferase 5 VB AGAP000785 1,444 0,53 0,034872633 Synaptic vesicle protein VB AGAP003063 1,319 0,399 0,044831691 Rwd domain-containing protein VB IP AGAP007549 1,774 0,827 0,030783776 AGAP010609 1,582 0,662 0,049507741 DnaJ (Hsp40) homolog subfamily C VB AGAP002594 1,443 0,529 0,032821552 apolipoprotein D VB AGAP009091 1,317 0,397 0,034625882 aromatic-L-amino-acid decarboxylase VB Six-bladed beta-propeller, TolB-like Major royal jelly protein/protein yellow AGAP012154 1,581 0,661 0,017624312 solute carrier family 15 member 1 VB AGAP000666 1,442 0,528 0,03823344 ubiquitin carboxyl-terminal hydrolase 16/45 VB AGAP004563 ANCE9 1,313 0,393 0,049507741 angiotensin-converting enzyme 9 VB IP AGAP002532 1,765 0,82 0,004238876 Cyclin, C-terminal domain Cyclin, N-terminal AGAP008578 1,58 0,66 0,023186247 ATP-dependent RNA helicase DDX4 VB AGAP006947 1,311 0,391 0,044831691 Cytochrome B561-related IP IP AGAP005844 1,76 0,816 0,006233202 Bifunctional purine biosynthesis protein VB AGAP007505 1,76 0,816 0,014849805 vitellogenic carboxypeptidase-like protein AGAP006938 Art7 1,578 0,658 0,033798283 Protein arginine N-methyltransferase 7 UP AGAP007775 1,578 0,658 0,03823344 ATP-dependent DNA helicase PIF1 AGAP003486 1,302 0,38 0,034625882 N/A N/A Helicase, C-terminal DEAD/DEAH box helicase UP domain Helicase superfamily 1/2, ATP-binding domain AGAP008090 1,302 0,38 0,036201432 nuclear pore complex protein Nup205 VB VB AGAP012964 1,578 0,658 0,017608886 Sarcospan IP AGAP029449 1,441 0,527 0,014751272 P-loop containing nucleoside triphosphate hydrolase IP AGAP008635 1,295 0,373 0,032228725 protein SDA1 VB include gene ID referred as the AGAP numbers; gene names, N/A means not annotated gene; AGAP011845 1,751 0,808 0,022152616 Histone H2A UP AGAP004108 1,574 0,654 0,023812903 Amalgam VB AGAP009512 1,44 0,526 0,019885369 E3 ubiquitin-protein ligase UBR7 VB expression foldchange and log2foldchange; adjusted p-value (p-adj); gene description including encoded protein function or predicted protein domain based on the databases: VB-VectorBase Community Annotation, IP-Interpro, UP-UniPro. Red dotted line indicates the cutoff tested by qPCR. Genes in purple treatments were tested by qPCR. For the rest of the 134 AGAP011713 1,734 0,794 0,016059772 ribonuclease P protein subunit POP4 VB AGAP006404 1,733 0,793 0,018003641 N/A N/A AGAP012040 1,724 0,786 0,032254989 N/A N/A AGAP009792 1,719 0,781 0,000530401 importin subunit alpha-2 VB AGAP001699 1,713 0,777 0,048918391 fatty-acid amide hydrolase 2 VB AGAP012192 1,712 0,776 0,008897593 DNA mismatch repair protein MLH1 VB AGAP002846 1,711 0,775 0,041598991 Trunk VB AGAP002378 1,71 0,774 0,023876565 Adenylosuccinate lyase UP AGAP006727 COEAE6G 1,707 0,772 0,015519838 carboxylesterase VB AGAP012375 1,698 0,764 0,017608886 protein aurora borealis VB AGAP003974 1,695 0,761 0,008897593 tRNA (cytidine32/guanosine34-2'-O)-methyltransferase VB AGAP003552 1,69 0,757 0,023186247 SET and MYND domain-containing protein 5 VB AGAP000479 1,687 0,755 0,017422566 pre-rRNA-processing protein IPI3 VB AGAP005581 1,685 0,753 0,00105879 3-hydroxyisobutyrate dehydrogenase UP AGAP002478 1,684 0,752 0,008897593 cyclin B AGAP005800 1,682 0,75 0,01612065 DNA replication licensing factor MCM7 AGAP010722 1,529 0,612 0,028086615 superfamily IP AGAP001224 1,402 0,488 0,025215999 subunit 3 VB VB SNase-like, OB-fold superfamily RNA-binding domain cleavage and polyadenylation specificity factor VB 135 AGAP010791 1,569 0,65 0,008897593 polyribonucleotide nucleotidyltransferase VB AGAP001656 1,568 0,649 0,029622655 ribosomal RNA-processing protein 7 Acyltransferase 3 Nose resistant-to-fluoxetine protein, AGAP005990 1,285 0,362 0,046758013 glycolipid transfer protein domain-containing protein 1 VB VB AGAP011457 1,565 0,646 0,013171475 ribose 5-phosphate isomerase A AGAP000535 1,438 0,524 0,030035206 N-terminal IP AGAP008795 1,285 0,362 0,029622655 Zinc finger, AD-type Zinc finger C2H2-type IP VB AGAP010453 1,56 0,642 0,021290069 ribosome biogenesis protein NSA1 AGAP001380 1,434 0,52 0,023933025 translation initiation factor 6 VB AGAP009920 RpL37a 1,283 0,359 0,035903402 60S ribosomal protein L37a VB VB AGAP012107 1,557 0,638 0,036201432 SUMO-conjugating enzyme UBC9 AGAP000681 1,429 0,515 0,0436892 tRNA:m4X modification enzyme VB cap-specific mRNA (nucleoside-2'-O-)-VB AGAP012216 1,557 0,639 0,006887628 sterol O-acyltransferase AGAP000496 1,422 0,508 0,019328566 geminin VB AGAP000826 1,282 0,358 0,044052437 methyltransferase 1 VB VB AGAP010406 1,554 0,636 0,035660224 origin recognition complex subunit 3 AGAP006941 1,42 0,506 0,037189609 ATP-dependent RNA helicase DDX51/DBP6 VB AGAP011173 RpL11 1,278 0,354 0,039015507 60S ribosomal protein L11 VB VB AGAP007502 1,551 0,633 0,008897593 kinesin family member 11 AGAP009442 1,419 0,505 0,049415485 cyclin-dependent kinase regulatory subunit CKS1 VB AGAP009572 RpS15a-2 1,276 0,351 0,033798283 40S ribosomal protein S15a VB VB AGAP008063 1,547 0,629 0,036201432 exosome complex component CSL4 AGAP009431 RpS21 1,415 0,501 0,00055617 40S ribosomal protein S21 UP AGAP002539 1,269 0,343 0,035419211 integrator complex subunit 3 VB VB AGAP001453 1,546 0,629 0,049973746 N/A Major facilitator superfamily MFS transporter AGAP007740 RpLP1 1,264 0,338 0,027842842 60S ribosomal protein LP1 VB N/A AGAP011454 1,544 0,626 0,001831642 rotatin AGAP003205 1,411 0,497 0,036174833 superfamily IP VB AGAP008879 1,539 0,622 0,011462104 Protein of unknown function DUF389 AGAP011383 1,41 0,495 0,037458371 rRNA-processing protein EBP2 VB AGAP012219 Med1 1,253 0,326 0,03589132 mediator of RNA polymerase II transcription subunit 1 VB IP AGAP003883 1,537 0,62 0,000709794 peptidyl-tRNA hydrolase, PTH2 family VB AGAP003578 1,535 0,618 0,033798283 aldehyde dehydrogenase (NAD+) AGAP000549 1,409 0,494 0,049507741 2-oxoisovalerate dehydrogenase E2 component (dihydrolipoyl transacylase) AGAP002525 1,223 0,29 0,049507741 eukaryotic translation initiation factor 2A VB VB VB AGAP001166 1,532 0,616 0,021172723 GINS complex subunit 4 AGAP002961 1,409 0,495 0,036810206 ribosomal RNA-processing protein 12 VB VB Nucleotide-binding alpha-beta plait domain superfamily AGAP008292 TRYP4 1,403 0,489 0,036201432 trypsin 4 VB RNA recognition motif domain Tudor domain 136 AGAP009830 1,406 0,491 0,01612065 Chitin binding domain IP 137 138
		AGAP003090 AGAP005917		1,528 1,399		0,612 0,484	Histone RNA stem-loop-binding protein SLBP1/SLBP2 0,013462018 ubiquitin-conjugating enzyme E2 O VB 0,036201432 ATP-dependent DNA helicase Q4 VB

genes within the cutoff, the specific primers were not available. APL1C was excluded from qPCR analysis. The "Gene name" column includes the abbreviation used in qPCR analysis.

Gene name in black correspond to the annotated gene name. Gene name in red correspond to abbreviation of gene function, whereas the genes without annotated function are called by the four last digits of their AGAP number and are depicted in green.

Table S5 . Full list of genes, which expression is upregulated upon APL1C depletion in RNAseq experiment.

 S5 Genes are enlisted according to the ascending expression fold change between "dsAPL1C" and "dsGFP" (control) treatments. The columns include gene ID referred as the AGAP numbers; gene names, where N/A means not annotated gene; expression foldchange and log2foldchange; adjusted p-value (p-adj); gene description including encoded protein function or predicted protein domain based on the databases: VB-VectorBase

Table S7 . List of the primers used for dsRNA synthesis, qPCR and RACE.

 S7

	Annotation_ID a Gene_name Primer_f 5'-3 b	Primer_r 5'-3 b	Source c	Purpose
	N/A	GFP	GAATTGTAATACGACTCACTATAGGGCATGGTGAGCAAGGGCGAG	GAATTGTAATACGACTCACTATAGGGCTTACTTGTACAGCTCGTC		dsRNA synthesis
	AGAP007036	APL1A	TAATACGACTCACTATAGGACTACCACCAGCCGAAAGATG	TAATACGACTCACTATAGGATCTGGTCTTGTATAGTACAATGG		dsRNA synthesis
	AGAP007033	APL1C	TAATACGACTCACTATAGGAGGCCAAGAAGAACCGCAATCC	TAATACGACTCACTATAGGATCACAGTGATTTCAGGGTGTGC		dsRNA synthesis
	AGAP008072	NOX5	TAATACGACTCACTATAGGGTCGTACGAATGGTCGAGTGA	TAATACGACTCACTATAGGGCCAAACTGGTCGCACTTGTA		dsRNA synthesis
	AGAP009033	HPX2	TAATACGACTCACTATAGGGACGACGACGGTGTGTACAAG	TAATACGACTCACTATAGGGATACTCGGCCGAATCGAAC		dsRNA synthesis
	AGAP010815	TEP1	TAATACGACTCACTATAGGTTTGTGGGCCTTAAAGCGCTG	TAATACGACTCACTATAGGACCACGTAACCGCTCGGTAAG		dsRNA synthesis
	AGAP010816	TEP3	TAATACGACTCACTATAGGGCACCTCGACTGAGAAAGGTTTG	TAATACGACTCACTATAGGGCTGATTATTTATATAGTTTTAC		dsRNA synthesis
	AGAP010592	S7	CACCGCCGTGTACGATGCCA	ATGGTGGTCTGCTGGTTCTT		qPCR
	N/A	16S_V4q	GTGCCAGCMGCCGCGGTAA	GGACTACHVGGGTWTCTAAT		qPCR
	AGAP007036	APL1A	GACTGCAAGCCGAGATCGATACC	CATCCATCTGGTCCTTGAGCTTA		qPCR
	AGAP007033	APL1C	AAGCAGGCTGAGTTGAGACAGG	GCCCAAGTAACATCATACACAC		qPCR
	AGAP012386	eater	TTCACCCGTCTGCGAGGGATGCAAGC	GTCAACGTGCATAGTAGCGTCTCCGTAGC		qPCR
	AGAP009762	nimrodB2	CAATCTGCTCAAATGGCTGCTTCCACG	GCTGCAAACATTCGGTCCAGTGCATTC		qPCR
	AGAP009033	HPX2	CCGCTTCTACAACACGATGA	CGACCAGATGGGCAAGTAT		qPCR
	AGAP008072	NOX5	TCATGCATCGCTACTGGAAG	CCAGAAAAGTCCACCTTGG		qPCR
	AGAP010815	TEP1	AAAGCTGTTGCGTCAGGG	TTCTCCCACACACCAAACGAA		qPCR
	AGAP010816	TEP3	ACCGCCAGGCGTACGTGATGG	CAAACCTTTCTCAGTCGAGGT		qPCR
	AGAP005503	SDR11	CAGTGTGGTAGGCCATACGG	TTCAGCTCACTAGGGACCG		qPCR
	AGAP010058	PAS1	CTCGGACACAACGTAGTTGG	AGCTGGAAGATCGCACTGGC	TM	qPCR
	AGAP009217	CLIPB12	ATAATTCTCAGATGTGTGCG	CCATCCCAAAAGCATGTGCC	TM	qPCR
	AGAP001669	CPR6	AAGACTGTTTGATGTTGACC	AGATCCATCTCGTTTTTGCC	TM	qPCR
	AGAP008512	8512	TTGGAACGCCTTTTGGACCG	CTTGTGGTGAAACATTTGCG	TM	qPCR
	AGAP000113	113	CAACTTCGCGAAACCTCGCC	CTGTTCGACAGAAAGCTGCC	TM	qPCR
	AGAP011509	COE	GTGCCATACACGGGGATGAT	ATCAACTCCACTGTCCAGCG	TM	qPCR
	AGAP013201	3201	ATGATGTTTCAATTCGAGCC	AGATCTATCCCTGGAGAACCG	TM	qPCR
	AGAP006400	APH2	CATGTCCCAGACAACCGTGA	TGCCGAGGTTCGATTTCACA	TM	qPCR
	AGAP007319	7319	TTATGAAGTGAAAGCTGACGC	CCTCCGCAACCTGGTTATGCC	TM	qPCR
	AGAP010854	SCF45	ACCTGTAGGACCTTAGCACGCC	AAGGTGCTAAAGTAGCTCGC	TM	qPCR
	AGAP011564	GGT	ATTACCGGGATCATGACGG	CGTTCACGACCGCCATCGCTG	TM	qPCR
	AGAP012648	2648	GGTCCATGCCTCAAGAAGTC	AAGATTGCAAACGGTGCGAG	TM	qPCR
	AGAP029110	9110	CGAGCTACTAACGCTTGGGC	GGGAATTCAGGATTACGCGG	TM	qPCR
	AGAP003334	CPLCX2	GTCCACCACGCCCCGGTCGTG	CCACCGGGACCGGGTGCACGGA	TM	qPCR
	AGAP001748	ChS	GCGTACTTCGAACGCTGGCG	TCGTCATCCTCAATTACCGG	TM	qPCR
	AGAP001470	1470	GAAGGTAAGCTCCGACACCT	CTGGCCGGCCTGCTCGAGCT	DOI: 10.1073/pnas.1900147116	qPCR
	AGAP006728	COEAE7G	CGGTGTAACGCATGGCACGC	TGCGACCGGTGCTGGTACCG	TM	qPCR
	AGAP029790	9790	GCAAGTAGGCTGAAGTAG	TCATGCGCTGATCGAAAACG	TM	qPCR
	AGAP008246	GBD_46	GGTCGGGACTGTGAACAAGAA	ACGAGGGTTTCGACGAACAAT	TM	qPCR
	AGAP029411	9411	GCGATTTCTAGCCTTCGTGC	CGTGTCGTAGTGAGCGTAGG	TM	qPCR
	AGAP009381	CRBP	GTGTGCGAATCCAAGTCAGC	CCACTCTACCCTGCAACCTG	TM	qPCR
	AGAP012477	GBD_77	CCATGTCACTGGTTCGCTG	ATAGAGGCCGATTGTGTGGC	TM	qPCR
	AGAP011676	UP2M	TTGCTTGAAGCTCTCACCGT	AAGACGAAAAATCCCCGCGA	TM	qPCR
	AGAP003350	GTP	TCAGTTCAGCAGAACCAATCCA	GCACTTAGGCACGAGAGTGT	TM	qPCR
	AGAP029623	9623	CGATGAAGCGATCGAACCTC	GCAAGTTGCTGCTCGATGAA	TM	qPCR
	AGAP007300	AP	AGTTTCCCGACGTTGGTCTC	CACCGAGCGTTGCATAGTTG	TM	qPCR
	AGAP007959	7959	TTGCCGTGAATATCGTGCCT	ACCGCCGCTGTTGCTATTAT	TM	qPCR
	AGAP001423	BPBP	ATTATTGCGCGCGAAGTGTC	TCTTCTTCTTGCGCAGCACT	TM	qPCR
	AGAP007122	TU1	GCTTTCTGCTGTTCCACTCG	GGGTAGACGGCGAACTGTAG	TM	qPCR
	AGAP001352	1352	GTTTCTTCTGCCTCAACCGC	AGAGCCGGATTGGGACAAAC	TM	qPCR
	AGAP005296	U11 5296	GAAGGGACAGGCGTTCGTTA	CGCTTGGTCGATGCAGTTTT	TM	qPCR
	AGAP007364	7364	CGAGTCGGTTAAGTCCTTCG	TCGTCCAAAACTAACTTCGCT	TM	qPCR
	AGAP006241	INX2	GGTCCAGAGTGTGTCGAAGG	CACACGCCTTCCTCATCGTA	TM	qPCR
	AGAP000162	CBS	GCAACGACGTTCGGTATTCG	TCCAAAACTGCCAACAGGGT	TM	qPCR
	AGAP000772	772	TGCTAGGGGTACACGTGAGA	GCCCCAGCACAATGCAAAAT	TM	qPCR
	AGAP009751	ANCE2	ACTCCGGTGTGGAGCCGCCGG	CACGTACTCGCCCGCCAGCG	TM	qPCR
	AGAP004038	HPX8	ACGGGCCCCGGACCAATCCG	CCGCTAGTGACCCCTCCAGG	TM	qPCR
	AGAP010540	540	GATTGGCCGGAAGGAAGTGA	CACGTGTTTGCAGACGATCC	TM	qPCR
	AGAP005829	MAS 5829	GGAAGGAGTACGATCCGCAG	GTTCGTATCACCCATCCGCT	TM	qPCR
	AGAP000180	PC	AGCGAGGAGCAGATTGTGTG	CTTCATGTCGATCAGCGCAC	TM	qPCR
	AGAP004036	HPX7	GTACGCTGTACCAGGAGGCG	TACCGATGGGTTGGTGTGCG	TM	qPCR
	AGAP028655	8655	TACAAGTACAGCTCCGTGCG	GGGGGCACTTCCTACCTAGA	TM	qPCR
	AGAP003591	LRR1	GTTCGTCACACCCGAGCACG	TTCCCCACGGTAAGACACGG	TM	qPCR
	AGAP007036	APL1A_GSP	CATTTGCTGCACGTGGAACGTAACCAGC	N/A	TM	RACE
	AGAP007033	APL1C_GSP GGCAAGCGTTTAAGTTGGGCGAAACGCA	N/A	DOI: 10.1371/journal.pone.0003672	RACE
	AGAP007036	APL1A_GSP_nested TAGGCTGGAAAACCTTTACCTCGACCAC	N/A	TM	RACE
	AGAP007033	APL1C_GSP_nested GTTGGATAATAAGAGGGCAAAGCAGGC	N/A	TM	RACE

VI. MATERIALS AND METHODS

DeYoung, B. J. & Innes, R. W. Plant NBS-LRR proteins in pathogen sensing and host defense. Nature immunology 7, 1243-1249, (2006).

Ricklin, D., Hajishengallis, G., Yang, K. & Lambris, J. D. Complement: a key system for immune surveillance and homeostasis. Nat Immunol 11, 785-797, (2010).

Le, B. V., Williams, M., Logarajah, S. & Baxter, R. H. Molecular basis for genetic resistance of Anopheles gambiae to Plasmodium: structural analysis of TEP1 susceptible and resistant alleles. PLoS Pathog 8, e1002958, (2012).

Kurata, S. Peptidoglycan recognition proteins in Drosophila immunity. Dev Comp Immunol 42, 36-41, (2014).

Neyen, C., Poidevin, M., Roussel, A. & Lemaitre, B. Tissue-and ligand-specific sensing of gram-negative infection in drosophila by PGRP-LC isoforms and PGRP-LE. J Immunol 189, 1886-1897, (2012).

LIST OF TABLES Table 1. Role of human

PERSPECTIVES Ethic statement

This study was conducted in strict accordance with the recommendations from the

Mouse infections with Plasmodium berghei

All experiments were performed with three-week-old female Swiss Mus musculus mice (Janvier, France). Mice were inoculated with 10 5 red blood cells (RBCs) infected with GFP-expressing under the hsp70 regulatory regions P. berghei parasite 165 . Four days post-treatment, blood samples were taken from the tail, and parasitemia was determined by flow cytometry. Furthermore, male gametocyte maturity was verified by performing an exflagellation test as previously described 166 . nested-GST were located before stop codon of the reference gene sequences. The PCR amplicons were subsequently cloned using TOPO cloning system (Invitrogen) and plasmids were collected, purified (QIAGEN) and subjected for sequencing.

RNA sequencing experiment and bioinformatic analysis

RNA sequencing

Anopheles mosquitoes were injected with dsGFP, dsAPL1A or dsAPL1C. For each condition, a pool of 8 mosquitoes was collected at 12 h post-treatment. Total RNA extractions from intact mosquitoes were performed on each pool using TRIzol reagent (Invitrogen). This experiment was repeated four times, yielding to a total number of 12 samples. All RNA-seq was performed at the University of Minnesota Genomics Center (genomics.umn.edu).

Details for RNA sequencing experiment and analysis

Prior to the library composition, RNA from each sample was quantified using fluorimetry (RiboGreen assay) and RNA integrity was assessed using capillary electrophoresis (Agilent BioAnalyzer), generating an RNA Integrity Number (RIN).

ABSTRACT

Abstract: Anopheles mosquito is a vector of Plasmodium parasite, the causative agent of malaria. The Anopheles leucine-rich immune molecule (LRIM) family members are leucine-rich repeat (LRR) proteins, which certain were described as key antagonists of Plasmodium parasites in Anopheles mosquito midgut. APL1C (Anopheles Plasmodium-responsive factor) is a representative of LRIM members which specifically protects against rodent malaria parasites by stabilizing the complementlike protein TEP1. By combining cell biology with functional genomic approaches, this study shows that mosquito bloodmeal induce the presence of an extracellular layer of APL1C protein surrounding the midgut beneath of the basal lamina. Consistently with the formation of this layer, APL1C binds to the ookinetes that emerged on the basal side of the midgut. This presence occurs independently from TEP1 function, requires the contribution of the phagocytic cells and nitration pathway. In addition, APL1C defence function is not restricted to the ookinete in the midgut but it also acts against the latest Plasmodium stage, the sporozoites. APL1C inhibits salivary glands infection prevalence, and consistently, it also binds to the surface of the sporozoites in the hemocoel. However, unlike to the midgut stages, anti-sporozoites APL1C-dependent mechanism involves different partners. Moreover, RNAseq study revealed APL1C gene targets, including genes with immune-like function. These results generate novel biological insight for the function of APL1C, and probably other LRIM and LRR family members, as a pathogen recognition receptor inducing immune response against pathogens that come in contact with mosquito hemolymph compartment.

Key words:

Anopheles, leucine-rich repeat, pathogen recognition, immune signalling, complement-like pathway, Plasmodium.

Résumé : L'anophèle est le moustique vecteur du parasite Plasmodium, responsable du paludisme. Chez ce moustique, des protéines de la famille LRIM (Anopheles leucine-rich immune molecule) ont été décrites comme antagonistes du développement de Plasmodium. L'une d'entre elles, APL1C (Anopheles Plasmodiumresponsive factor) protège spécifiquement le moustique contre les parasites Plasmodium de rongeurs en collaboration avec la protéine TEP1 du complément. En combinant des approches de biologie cellulaire et de génomique fonctionnelle, mon travail de thèse montre que le repas sanguin des moustiques induit le recrutement d'APL1C au niveau du pôle basal de l'épithélium digestif. Ce positionnement d'APL1C lui permet de se lier aux stades ookinètes du parasite émergeant du côté basal de l'épithélium, et ce, indépendamment de la fonction de TEP1. Néanmoins, cette action d'APL1C requiert la contribution des phagocytes et de la Nitration. Par ailleurs, mon travail montre que l'action d'APL1C ne se restreint pas à l'ookinète car elle agit aussi contre le dernier stade de développement de Plasmodium, les sporozoïtes. Avec la ABSTRACT 141 capacité de se lier aux sporozoites, APL1C contrôle la prévalence d'infection des glandes salivaires du moustique, mais avec des partenaires différents de ceux agissant sur les ookinètes. Finalement, une étude transcriptomique m'a permis d'identifier des facteurs agissant en aval d'APL1C. L'ensemble de ces résultats génère de nouvelles connaissances relatives à la fonction des membres de la famille LRIM en tant que récepteurs de reconnaissance d'agents pathogènes capable de déclencher une réponse immunitaire dans différents compartiments tissulaires du moustique.

Mots clés : Anopheles, motifs riches en leucines, reconnaissance microbienne, signalisation immunitaire, système assimilé au complément, Plasmodium.