Tissue-specific responses of brain and lung endothelial cell miRNA and mRNA profiles to the ring-stage Plasmodium falciparum-infected red blood cells

Tissue-specific responses of brain and lung endothelial cell miRNA and mRNA profiles to the ring-stage Plasmodium falciparum-infected red blood cells | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Tissue-specific responses of brain and lung endothelial cell miRNA and mRNA profiles to the ring-stage Plasmodium falciparum-infected red blood cells Nahla Metwally, Maria del Pilar Martinez Tauler, Hanifeh Torabi, and 14 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4222036/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract MicroRNAs (miRNAs) control 60% of genes expressed in the human body, but their role in malaria pathogenesis is incompletely understood. For the first time, we demonstrate cell type-specific alterations to the miRNA profiles during the early response to malaria infection in brain and lung endothelial cells (ECs). In brain ECs, incubation with Plasmodium falciparum -infected red blood cells in the ring stage (iRBCs) most significantly affected endocytosis-related miRNAs and mRNAs. Contrastingly, in lung ECs, iRBCs altered electron transport chain-related miRNAs and mRNAs. We also present a novel dataset of inherent differences between microRNA profiles in brain and lung ECs and their secreted extracellular vesicles (EVs). We demonstrated that shear stress affected multiple pathways in brain ECs, which were controlled by numerous human miRNAs. Together, these findings demonstrate that host miRNAs respond to parasite exposure; this is accompanied by stimulation of downstream signaling pathways within the ECs. Therefore, we consider miRNAs to be the initial spark (Code of duty) for the early host-parasite interaction events. Health sciences/Pathogenesis/Infection Biological sciences/Microbiology/Parasitology/Parasite host response Brain endothelial cells lung endothelial cells miRNA mRNA NGS shear stress endocytosis malaria Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Widespread parasite resistance to artemisinin therapy is hampering malaria eradication programs, and more research into the host response to infection is needed to develop adjuvant therapies that minimize complications. [ 1 , 2 ]. Malaria deaths reached 608,000 cases in 2022 with 249 million clinical malaria infections. Pregnant women and children under 5 years of age are most likely to develop severe malaria, with children < 5 years of age accounting for 67% of all malaria deaths [ 3 ]. Five parasite species cause malaria, and Plasmodium falciparum ( P. falciparum ) is the most virulent, responsible for 95% of malaria deaths and 200 million annual clinical infections. The life cycle of P. falciparum is complex, including sexual and asexual stages in female Anopheles mosquitoes and human hosts. When a female Anopheles mosquito infected with P. falciparum bites a person, it injects falciparum sporozoites into the skin. These sporozoites then travel to the liver and invade a hepatocyte, where they undergo a cycle of asexual replication. This produces a hepatic schizont containing numerous merozoites. The merozoites then enter the bloodstream and infect red blood cells (RBCs), developing from ring stages to trophozoites and then to schizonts. Once mature, the schizonts rupture, releasing more merozoites that continue the replication cycle. Finally, some of the parasites produce male and female gametocytes. The mosquito takes these up to continue the cycle [ 4 ]. Fatalities occur due to serious complications of malaria. These complications include cerebral malaria (CM), lung injury, renal failure, acidosis, and severe anemia [ 5 – 7 ]. The virulence of P. falciparum is attributed to the parasites’ ability to modify the erythrocyte surface to adhere and to evade the host immune attack. The major antigenic ligand found to be responsible for the cytoadhesive properties of the infected red blood cells (iRBC) are members of the P. falciparum erythrocyte membrane protein-1 ( Pf EMP1) family [ 8 – 9 ]. The pathogenesis of severe malaria is hotly debated; some researchers suggest that cytoadhesion is the overriding pathogenic mechanism, whilst others believe that inflammatory processes are more important. An accumulating body of evidence indicates that vascular endothelial dysfunction is also important and could be the interface between cytoadhesion and inflammation [ 9 – 12 ]. We concluded that establishing the causal role of any single mechanism in severe malaria in human is difficult. That’s why we planned to investigate more deeply into the host-parasite interaction mechanisms. In the human host, RBCs and endothelial cells (ECs) are the primary cells that interact with parasites during P. falciparum infection. During this host-parasite interaction, biological material is exchanged. This includes the transfer of human microRNA (miRNA) between iRBCs and other non-infected cells within the human host, including non-infected RBCs, ECs, and immune cells [ 13 ]. Although miRNAs are known to control 60% of the human genes, but their role in malaria complications remains incompletely understood. miRNAs miRNAs are non-coding RNAs approximately 20 nucleotides in length, and are found in mammals, plants, and viruses. According to miRBase version 22, the human genome encodes ~ 300 true mature miRNAs, of which 1,115 are currently annotated [ 14 ]. An individual miRNA can repress tens to hundreds of genes, and miRNAs regulate nearly every cellular and metabolic process [ 15 – 17 ]. Since the discovery of miRNA in 1993, miRNA has been increasingly recognized as an essential post-transcriptional gene regulator [ 17 ]. Different steps of miRNA biogenesis occur in the nucleus and cytoplasm. In the nucleus, the corresponding region of the genome is transcribed by RNA polymerase II to produce primary miRNA (pri-miRNA) > 200 nucleotides in length. The DiGeorge Syndrome Critical Region 8 (Drosha/DGCR8) complex, which consists of RNase III family enzymes, crops the pri-miRNA into precursor miRNA (pre-miRNA) 70 nucleotides in length [ 18 ]. The pre-miRNA is then transported into the cytoplasm. The trans-activation responsive RNA-binding protein (TRBP)/dicer complex cuts the hairpin-like structure in pre-miRNA, processing pre-miRNA into a 14-21-nucleotide duplex mature miRNA structure comprised of two strands, the mature miRNA targeting strand and the miRNA passenger strand. mRNA target recognition occurs via binding of the short seed region (2–8 nucleotides) at the 5’ miRNA end (guide strand) and a partially or perfectly complementary region on the target mRNA 3’ untranslated region (UTR). This binding interaction represses translation of target mRNA and in some cases targets mRNA for degradation. The passenger strand was thought to be degraded, but recent research has shown that both miRNA strands have functional significance [ 19 – 20 ]. It was previously thought that miRNAs only negatively regulate target mRNA, but recent observations suggest that miRNAs can both repress and stimulate gene expression depending on various factors such as cellular conditions, sequences, and cofactors [ 21 ]. isomiRs The discovery of miRNA isoforms, or isomiRs, was facilitated by high-throughput technologies such as deep RNA sequencing. IsomiRs differ from canonical miRNAs in length and/or sequence and are generated via RNA modifications catalyzed by enzymes such as deaminases and exonucleases. These molecules were initially hypothesized to be RNA-sequencing/mapping errors. However, subsequent studies demonstrated that small RNA-sequencing data contained a significantly higher percentage of untemplated nucleotide additions (%NTA) than the expected sequencing error rate calculated using small artificial RNAs. These studies confirm that canonical microRNA sequence modifications are physiological events that occur in vivo rather than experimental artifacts, which has been supported by the development of more advanced analysis algorithms. IsomiRs, like their canonical counterparts, have distinct functional roles. isomiRs bind Argonaute (Ago) proteins, as demonstrated by co-immunoprecipitation assays, and inhibit target gene expression, as demonstrated by in vitro luciferase assays [ 22 – 25 ]. Vascular endothelium Approximately 96,000 km of blood vessels contained in the human body are maintained by ECs, a heterogeneous cell type that responds to signals in the microenvironment. ECs line the blood and lymph vessels except for the placenta, and form a physical barrier between the blood and tissue. ECs consist of a luminal membrane in direct contact with blood and circulating cells [ 26 – 27 ] and a basolateral surface. The basolateral surface is separated from the surrounding tissue by a basement membrane consisting of glycoproteins produced by ECs and anchored to their cell membrane. ECs perform numerous functions that depend on their location and activation status. These include maintaining vascular tone, controlling homeostasis, transporting hormones, and recruiting immune cells. ECs initiate and amplify the inflammatory response to vascular insults. ECs exhibit tissue type-specific heterogeneity. For example, tight junctions, absence of fenestrae, reduced pinocytic activity, and carrier-mediated transport systems are unique features of ECs that maintain the blood-brain barrier (BBB). The BBB protects the central nervous system from pathogens and toxic substances and restricts entry of antibodies and immune cells [ 28 ]. Endothelial shear stress Vascular ECs sense hemodynamic changes and signals transmitted by the blood and respond by releasing vasoactive substances [ 29 ]. Shear stress affects EC morphology, electrochemical activities, and gene expression. Most importantly, NO release increases in response to shear stress, which is regulated by rapid activation of endothelial nitric oxide synthase 3 (eNOS) and upregulation of eNOS gene expression and transcriptional activation [ 30 ]. Under physiological conditions, endothelium-derived relaxation and contraction factors are in equilibrium. Vascular homeostasis is maintained with a slight bias in favor of vasodilation [ 29 ]. The endothelium is exposed to radial forces caused by intravascular pressure, tangential forces in the vessel wall caused by the balance between cell-cell contacts and vessel movement, and axial shear forces caused by the friction of blood flowing against the vessel wall. ECs are typically exposed to shear stress of 1–100 dyne/cm 2 in the form of steady or pulsatile unidirectional shear. In culture, ECs are different from cells that grow in static conditions, forming a functionally confluent monolayer of cells. ECs can sense and respond to many stimuli, including the shear force of blood flowing through cell-cell junctions, heterotrimeric G proteins, primary cilia, caveolae, integrins, and the glycocalyx (GCX) [ 29 – 30 ]. Extracellular vesicles Extracellular vesicles (EVs) are tiny lipid particles released by every living cell. They contain proteins, lipids, RNA, and DNA and can transport bioactive molecules. EVs also act as carriers that facilitate cell-to-cell communication, including antigen presentation and inflammatory activation [ 31 , 32 ]. Recently, there has been a lot of interest in studying the biology and functions of EVs, particularly in immune regulation and host-pathogen interactions. Vascular cell-pathogen interactions Jambusaria et al. referred to the genetic signature of ECs as “postal codes” for organ-specific drugs. Identifying the differences in genetic signatures between ECs in different organs provides insight into the molecular underpinnings of EC heterogenicity [ 33 ]. Prior studies have explored the transcriptional landscape of brain ECs, and a smaller number of studies have evaluated the transcriptional profiles of lung ECs, but very few studies have explored the organ-specific heterogenicity of EC miRNA profiles. Lung ECs are in contact with the external environment due to their gas exchange function, and thus must initiate a rapid immune response in the event of infection. Lung ECs also facilitate the entrance of immune cells into the lungs to fight invading bacteria and viruses. Contrastingly, brain ECs prevent toxic molecules from entering the brain and maintain a much tighter barrier structure [ 27 ]. Understanding how ECs of different organs respond to stimuli contributes to drug design for infectious disease. In the present study, we investigated intrinsic immune pathways in the brain and lungs ECs that might contribute to complications or protect the host. To pursue these scientific questions, we designed experiments to investigate the mRNA and miRNA profiles of primary human brain and lung ECs exposed to iRBCs. First, we compared the profiles of both ECs and EVs secreted by ECs to characterize the intrinsic heterogeneity between brain and lung ECs. Second, we exposed brain and lung ECs to authentic shear stress stimulation with similar stress levels to microvessels to create a physiologically relevant model. We subsequently evaluated the cellular response to shear stress and iRBC exposure to identify affected pathways and identify miRNAs that could potentially regulate these pathways. We demonstrated that shear stress activated multiple processes in brain ECs, including IL-8 signalling and strengthening of tight junctions. miRNAs differentially expressed in the ECs potentially controlled these pathways. Incubation with ring-stage iRBCs results in the activation of endocytic pathways in brain ECs. Contrastingly, in lung ECs, the most prominent activated pathway was the electron transport chain. In silico analyses identified that in the context of malaria exposure, endocytosis and electron transport pathways were potentially targeted by candidate miRNAs. The candidate miRNAs were significantly altered following 8 hours of co-incubation with ring-stage iRBCs at a shear stress of 1.5 dyne/cm 2 . Results Experimental Models Experiments were conducted in brain and lung human primary ECs. Cellular miRNA and mRNA sequencing were performed after exposing both cell types to multiple stimuli (Fig. 1 A): a) shear stress of 1.5 dyne/cm 2 (ECs 1.5 ), b) shear stress plus fever (40°C) (ECs 1.5+40°C ), c) shear stress plus uninfected RBCs (ECs 1.5+RBCs ), and d) shear stress plus ring stage-iRBCs, or iRBCs (ECs 1.5+Rings ) (Fig. 1 B). The supernatant of static culture was also collected for EV purification and subsequent miRNA isolation and sequencing (Fig. 1 C). Deep NGS sequencing was then conducted, and data were extracted (20 million reads for miRNA and 6–10 million reads for mRNA) (Fig. 1 D). The obtained data were analysed by CLC genomics, Ingenuity Pathway Analysis (IPA), KEGG, and Reactome analyses (Fig. 1 E). Raw data are uploaded to the NCBI platform (PRJNA1066103). Heterogeneity of miRNA and mRNA in brain and lung ECs and secreted EVs To characterize intrinsic differences between primary brain ECs (HBMECs) and primary lung ECs (HMVEC-L), we performed miRNA/mRNA-seq on both HBMECs and HMVEC-L (Supplementary Tables S1 and S2). Figure 2 A shows a heat map of miRNAs differentially expressed in lung and brain ECs. Brain ECs exhibited higher expression of 118 mature miRNAs relative to lung ECs, while 152 mature miRNAs were more highly expressed in lung ECs relative to brain ECs (Supplementary Table S1). Seed miRNAs differentially expressed in lung and brain ECs are blotted in the lower part of the heatmap (Fig. 2 A). The most significantly altered nine miRNAs with increased brain EC expression level are shown in Fig. 2 B. The most significantly altered mature miRNAs that were more highly expressed in lung ECs are shown in Fig. 2 C. Subsequently, we stained brain and lung ECs with the EC marker CD29 to confirm its expression on EC surfaces (Supplementary Figure S1). We then purified and prepared EVs as previously described [ 34 ] for analysis with transmission electron microscopy (TEM). Figure 2 D shows TEM images of EVs purified from primary brain ECs (HBMEC-EVs). We then labelled EVs with CD29 (Fig. 2 E), thus confirming that these EVs originated from ECs. We also purified and labelled EVs from primary lung ECs (HMVEC-L-EVs) (Figs. 2 F-G). Both EV populations retained the normal characteristics of EVs [ 35 ]. Differential miRNA expression analysis revealed 19 mature and 180 seed miRNAs differentially expressed between brain (HBMEC-EVs) and lung (HMVEC-L-EVs) EVs (Fig. 2 H and Supplementary Table S3). The six mature miRNAs with significantly higher expression in HBMEC-EVs are plotted in Fig. 2 I. The twelve mature miRNAs with significantly higher expression in HMVEC-L-EVs are plotted in Fig. 2 J. In parallel, we scanned the mRNA profiles for HBMECs and HMVEC-L (Supplementary Table S2). A total of 3,497 genes were differentially expressed between HBMECs and HMVEC-L. A total of 1,601 genes were exclusively expressed in lung ECs, while 1,896 genes were exclusively expressed in brain ECs. Reactome pathway analysis revealed three prominent clusters of genes highly regulated in each cell type. In brain ECs, the primary clusters were intercellular communication, signal transduction, and the immune response. In lung ECs, the most prominent clusters were extracellular matrix organisation, cellular response to stimuli, and haemostasis (Supplementary Figure S2A-S2B). Effect of shear stress on HBMEC miRNA and mRNA profiles The EC response to shear stress is involved in multiple developmental and physiological vascular processes such as angiogenesis, vascular morphogenesis, vascular remodelling, and vascular tone. To identify miRNAs affected by physiological shear stress (1.5 dyne/cm 2 ), we compared miRNA expression between HBMECs exposed to 1.5 dyne/cm 2 shear stress (HBMEC 1.5 ) and HBMECs cultivated under static conditions (HBMEC static ) (Supplementary Table S4). Figure 3 A shows a heatmap representing differentially expressed mature and seed miRNAs in HBMEC 1.5 cells relative to HBMEC static cells. The 18 most differentially expressed miRNAs are plotted in Figs. 3 B- 3 S. In parallel, mRNA from the same samples was sequenced (Supplementary Table S5). A total of 6,182 genes were affected by shear stress, with 3,693 genes upregulated and 2,489 genes downregulated. Subsequently, we identified the target genes of differentially expressed miRNAs (Supplementary Table S6). Respectively, pathway analysis identified that miRNAs targeting eleven major pathways were affected by shear stress, with differential miRNA expression in HBMEC 1.5 relative to HBMEC static (Fig. 3 T). The most affected pathways were cytokine-cytokine receptor interaction, actin cytoskeleton, calcium signalling, and cell adhesion molecules. Figure 4 A shows which components of the calcium channel pathway were upregulated by shear stress (red), downregulated by shear stress (green), and unchanged (blue), as identified by mRNA-sequencing. This was consistent with prior reports of mechanosensitive calcium-permeable channels in ECs in response to shear stress [ 36 – 42 ]. Subsequently, we determined which miRNA candidates within the ECs could affect differentially regulated pathways. We identified 33 candidate miRNAs that target genes in calcium channel pathways (Table 1). ECs have a low resting intracellular calcium concentration, which is maintained by plasma membrane calcium-ATPase (PMCA) and sarco/endoplasmic reticulum Ca2 +− ATPase (SERCA) channels. PMCAs are localized to EC plasma membranes and SERCAs are localized to endoplasmic reticulum membranes. Both classes of ATPases actively transport calcium ions from the cytoplasm to the extracellular space or ER to maintain low intracellular calcium concentrations. Stimulation of G protein-coupled receptors (GPCRs) activates phospholipase C (PLC), triggering hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP2) to diacylglycerol (DAG) and inositol triphosphate (IP3). IP3 facilitates calcium entry from the sarcoplasmic reticulum and extracellular space. Store-operated cation channels and receptor-operated cation channels facilitate calcium entry from the extracellular space. During stimulation, calcium influx into ECs facilitates dephosphorylation of nuclear factor of activated T-cells (NFAT) from phospho-NFAT (pNFAT) to NFAT. NFAT then translocates to the nucleus [ 35 – 37 ], activating transcription of ICAM1 (Intracellular adhesion molecule − 1). Secondly, we investigated the effects of shear stress on tight junction (TJ) components in HBMEC 1.5 . TJs are formed by homophilic interactions between transmembrane proteins and junctional adhesion molecules on neighbouring cells. TJs determine the tightness of the endothelial barrier by regulating diffusion of fluids, ions, and small plasma proteins and penetration of cells such as leukocytes, neutrophils, and lymphocytes. We identified that out of nine genes encoding TJ components, six were significantly upregulated by exposure to shear stress, including CLDN, JAM1, JAM3, ESAM, PECAM1 , and CD99 (Fig. 4 B). Analysis of differentially expressed miRNAs identified that hsa-miR-625-5p, which targets CLDN, and has-miR-154-5p, which targets JAM3 , are significantly expressed in brain ECs subjected to shear stress (Table 1) (Supplementary Tables S4, S5, and S6). Shear stress also affected the complement and coagulation cascade, with upregulation of JAM1, CD40, and PECAM1 (Fig. 4 C). Figure 4 D shows genes involved in the leucocyte transmigration pathway. ICAM-1 was upregulated by shear stress, and is targeted by hsa-miR-431-5p. PVR, which was also upregulated by shear stress, is targeted by hsa-miR-193a-5p (Table 1) (Supplementary Tables S4, S5 and S6). We then evaluated the CxC subfamily pathway, in which seven genes were upregulated by shear stress in brain ECs, including CXCL1, CXCL8, CXCL8, CXCL16, CXCR5, and CXCR4 , while only one gene, CXCR7 , was downregulated. miRNA target analysis identified that both hsa-miR-493-5p and hsa-miR-889-3p target CXCL8 , while hsa-654-5p targets CXCL16 (Fig. 4 E). mRNA and miRNA profiles of HBMECs exposed to iRBCs under physiological shear stress. The initial molecular response of ECs to malaria infection remains incompletely understood. Figure 5 A shows a heatmap comparing the miRNA profiles of HBMECs exposed to shear stress and incubated with ring-stage iRBCs (HBMEC 1.5+Rings ) HBMECs exposed to shear stress and co-incubated with non-infected RBCs (HBMEC 1.5+RBCs ) were used. Considering only mature miRNAs, three miRNAs were significantly downregulated and three miRNAs were upregulated under these conditions. Analysis of miRNA isomers identified 33 miRNA candidates significantly upregulated by exposure to iRBCs and 18 candidate miRNAs significantly downregulated (HBMEC 1.5+Rings relative to HBMEC 1.5+RBCs ) (Supplementary Table S7). Figure 5 B-I shows the top miRNAs that are significantly expressed as a response to the HBMEC 1.5+Rings . The mRNA target showed that miRNAs regulating the endocytosis, TNF signalling, NF-Kappa B and cytokine-cytokine receptor interaction pathways were affected by iRBC exposure (Fig. 5 J). Figure 6 A shows the endocytosis pathway, with genes upregulated by iRBC exposure indicated in red, downregulated genes indicated in green, and unaffected genes indicated in blue, as demonstrated by mRNA-sequencing analysis. Endocytosis is the cellular process by which substances are taken into cells. The material to be internalized is surrounded by an area of the cell membrane, which then buds off inside the cell to form a vesicle containing the material that has been taken up. Endocytosis is a form of intracellular active substance transport. Endocytic pathways fall into four major categories: receptor-mediated endocytosis (or clathrin-dependent endocytosis), caveolae, pinocytosis, and phagocytosis. Thirteen genes encoding components of clathrin-dependent endocytosis were upregulated by exposure to iRBCs (Fig. 6 A). Only two genes involved in clathrin-independent endocytosis (ARF6 and MHC I) were upregulated. Genes encoding components of early endosome regulation were also upregulated (10 genes), as were genes encoding components of late endosomes and multivesicular bodies (14 genes) (Fig. 6 A, Supplementary Table S7). Immune response pathways, including the CXC subfamily, were also affected in HBMEC 1.5+Rings (Fig. 6 B). Six genes, including CXCL1, CXCL6, CXCL8 , CXCL3, CXCL2 and CXCR4 were downregulated in HBMEC 1.5+Rings , while only CXCL12 was upregulated. Effect of shear stress on HMVEC-Ls miRNA and mRNA profiles We investigated the effects of shear stress on HMVEC-L cells by applying shear stress of 1.5 dyne/cm2. A total of 1174 genes were significantly regulated when we compared the cells exposed to shear stress to those that were cultivated under static conditions (Supplementary Table S8). One of the main pathways that were stimulated due to shear stress was Interleukin 10 signaling (high expression of ICAM-1, CXCL2, IL6, CXCL8, PTGS2 , and CXCL3 ). Also, both Interleukin 4 and 13 signaling pathways were also turned on. Adding to this some of the genes in the potassium channel pathway were downregulated ( KCNN2, KCNJ8, KCND2 and KCNK2 ) (Supplementary Table S8). In contrast to the brain ECs, the tight junction genes were not affected by shear stress in the lung ECs. In the miRNA profile of the HMVEC-L cells, only 12 isomiRs were significantly regulated. The following candidates were highly regulated: hsa-miR-4797-3p, hsa-miR-4670-3p, hsa-miR-6813-3p, has-miR-1286, hsa-miR-6828-5p, hsa-miR-7154-3p, hsa-miR-2467-3p and hsa-miR-4661-5p. On the other hand, the following isomiRs were downregulated: hsa-miR-555, hsa-miR-6873-5p, hsa-miR-4725-5p and hsa-miR-6792-5p. mRNA and miRNA profiles of HMVEC-Ls exposed to iRBCs under shear stress To determine how lung ECs are affected by the presence of malaria parasites, we incubated lung ECs with infected or uninfected RBCs under shear stress conditions (HMVEC-L 1.5+RBCs vs. HMVEC-L 1.5+Rings ). Figure 7 A shows a heat map of miRNAs differentially expressed in HMVEC-L 1.5+Rings cells relative to HMVEC-L 1.5+RBCs cells. Eighteen mature miRNAs were significantly upregulated and 36 mature miRNAs were significantly downregulated in HMVEC-L 1.5+Rings relative to HMVEC-L 1.5+RBCs . Among isomiRs, 219 miRNAs were differentially expressed in HMVEC- L1.5+Rings relative to HMVEC-L 1.5+RBCs , with 126 miRNAs upregulated and 93 miRNAS downregulated (Supplementary Table S9). The miRNAs were then strictly filtered to the nine most significantly affected miRNAs (Figs. 7 B-J). We used predictive modelling to identify the target genes of differentially expressed miRNAs (Supplementary Table S10). Pathway analysis of mRNA-sequencing data identified that the primary gene set differentially expressed in HMVEC-L 1.5+Rings relative to HMVEC-L 1.5+RBCs was the electron transport chain (ETC) (Fig. 7 k). Out of 35 genes in the ETC pathway, 30 genes were upregulated in HMVEC-L 1.5+Rings relative to HMVEC-L 1.5+RBCs . A recent study reported that the ETC plays a role in immune cell activation, proliferation, and differentiation [ 42 ]. Supplementary Table S10 shows miRNA candidates that target genes in the ETC pathway. How fever (40°C) affects the mRNA and miRNA profiles of HBMEC and HMVEC-Ls under shear stress The brain ECs reacted to fever by highly regulating 97 genes that are involved mainly in the regulation of the HSF1-mediated heat shock response pathway and the cellular response to heat stress pathway (Supplementary Table S11). In addition, 59 genes were downregulated in response to heat stress. Those were involved mainly in the interferon Alpha, beta, and gamma signaling pathways. The miRNA profiles of those cells showed a down-regulation of about 300 mature miRNAs in response to fever, in addition to significant regulation of 225 isomiRs (Supplementary Table S11). IPA miRNA target filter analyses showed that the affected miRNAs and isomiRs target mostly the above-mentioned genes within the mRNA profile (Supplementary Table S11). Considering the Lung ECs, they reacted to fever by regulating 169 genes involved mainly in the cellular response to stress pathways (Supplementary Table S12). The miRNA profiles of those cells only 8 isomiRs that reacted to fever. hsa-miR-4442, hsa-miR-6814-5p, hsa-miR-3197, hsa-miR-4501, hsa-miR-491-3p and hsa-miR-3135a were significantly downregulated. On the other hand, hsa-miR-3606-3p and hsa-miR-520a-5p were highly significantly regulated. Discussion The present study investigated the initial response of host ECs to malaria infection. Recent studies have identified significant innate immune functions of ECs, including cytokine secretion, phagocytosis, and antigen presentation [ 45 ]. ECs can also detect pathogen-associated molecular patterns and damage-associated molecular patterns (DAMPs) and elicit pro-inflammatory immune-enhancing responses and anti-inflammatory immunosuppressive responses [ 46 ]. Brain EC-specific alterations in miRNA/mRNA profiles in response to shear stress and infectious stimuli Our findings demonstrate that a subset of microRNAs are highly expressed in brain ECs and their secreted EVs under normal static conditions. This miRNA set was affected by shear stress and malaria infection stimuli. Shear stress of 1.5 dyne/cm 2 , which is similar to that of physiological shear stress in microvessels, significantly altered expression of 18 miRNA candidates significantly, including miR-196b-5p,-224-5p,-369-5p, -411-5p, -127-3p, -100-5p, -379-5p, -204-5p, -199a-3p, -99a-5p, -652-5p,-154-5p, -431-5p, -193-5p, -654-5p,-493-5p, -889-3p and − 181a-2-3p. A prior study reported six mechano-sensitive endothelial miRNAs, including hsa‐miR‐8060,‐4534,‐630,‐5703, 1587,‐1268a and ‐4788,197‐5p [ 47 ]. However, these miRNAs were not affected by shear stress in the present study. This could be because the investigators subjected ECs to higher shear levels (4 dyne/cm 2 and 100 dyne/cm 2 ) than that used in the present study (1.5 dyne/cm 2 ), which is similar to physiological shear stress in microvessels. This highlights the potential roles of other miRNAs that will be investigated in our future studies. Consistent with our findings, prior studies have demonstrated that shear stress decreases expression of mechanosensitive miR-181b-5p, which suppresses NLRP3 inflammasome-dependent pyroptosis. Clinical data are also consistent with this notion, revealing that miR-181b acts in combination with the lncRNA ANRIL to mediate NF-κB signalling [ 48 – 51 ]. We demonstrated that shear stress increased expression of genes encoding TJ components in brain ECs, which are likely targeted by miR-625-5p and − 154-5p. These results are consistent with a recent study demonstrating that laminar flow protects vascular endothelial junctions [ 52 ]. We also found that shear stress upregulated CXCL1,8,2,3, and 16 in brain ECs. These genes were likely targeted by hsa-miR-493-5p, -889-3p and 654-5p, consistent with a prior study from Shaik et al. reporting that exposure to shear stress increases EC secretion of CXC chemokines [ 53 ]. Exposure to parasite-infected RBCs altered expression of eight miRNAs in brain ECs, including miR-4509, -142-5p,-144-3p, -342-3p, -497-5p, -103b, -4485-3p, and − 4289. A prior study analysed EV miRNA profiles in EVs mice infected with Plasmodium ANKA and P. yoelii . The study identified high levels of miR-146a and miR-193b in EVs from cerebral malaria-infected mice compared with EVs from non-cerebral malaria-infected mice and non-infected mice [ 54 ]. Additional studies demonstrated altered expression of 12 miRNAs, including miR-21-5p,-18a-5p,-19a-3p, -20b-5p, -142-3p, -27a-5p, -152-3p, -193a-5p, -155-5p,-218-1-3p, -543, and − 411-5p, in mice with CM compared with mice with non-CM. These miRNAs are significantly involved in some cerebral malaria-like adherens junctions and the FoxO, TGF-β, and endocytosis pathways [ 54 ]. Brain miR-27a, miR-150 and let7i are upregulated in Plasmodium berghei -infected mice, which develop CM, in comparison to mice with non-CM and uninfected mice [ 55 ]. A prior study of a human patient demonstrated that whole blood miR-150-5p was downregulated in an adult infected with P. vivax [ 56 ]. Contrastingly, in the present study, we identified that a miR-150-5p isomiR was significantly upregulated in brain ECs exposed to iRBCs. Consistent with our findings, a prior study identified upregulation of miR-150-5p in plasma-derived EVs from patients infected with P. vivax [ 57 ]. Activation of the endocytosis pathway in brain ECs exposed to iRBCs We previously demonstrated that iRBCs secrete miRNA-containing EVs [ 34 ] that are presumably taken up by recipient cells, in which cargo miRNAs suppress gene expression. Activation of the endocytosis pathway identified in the present study could indicate EV uptake in brain ECs. EVs are generally internalized into recipient cells by clathrin-dependent endocytosis, which was also increased in brain ECs exposed to iRBCs [ 58 , 59 ]. The endocytic system consists primarily of clathrin-containing endocytic vesicles, early and late endosomes. However, clathrin-independent endocytosis, which is less-characterized, also occurs in ECs. The clathrin-dependent pathway is responsible for transporting transferrin in brain ECs. Clathrin-coated buds are localized to the central zone of ECs, with well-developed necks, in contrast to clathrin-coated dome-shaped invaginations on the PM. ECs likely use both clathrin-dependent and clathrin-independent endocytosis pathways. After budding, clathrin-dependent endocytic vesicles fuse with one another or pre-existing early endosomes, causing the vesicles to split and release their coating. The majority of lipid and protein vesicle components destined for recycling to the PM accumulate in the vacuolar head, while soluble contents are concentrated in vesicular regions due to their larger fractional volume [ 60 – 62 ]. Lung EC-specific alterations in miRNA /mRNA profiles in response to iRBC exposure Severe malaria is associated with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). The human host responds to infection by initiating a complex inflammatory response in the lungs. This includes cytokine production, neutrophil activation and macrophage activation. Permeability of the alveolar capillary membrane subsequently increases, causing ventilation perfusion mismatch and oedematous lung. These interactions compromise lung function [ 63 , 64 ]. To our knowledge, we present for the first time, the acute response of lung ECs to initial stimulation with iRBCs under physiological shear stress. We identified that co-incubation with iRBCs prominently increased expression of genes encoding ETC components in lung ECs. The ETC consists of multimeric protein complexes I–IV, on the inner mitochondrial membrane. Complex I generates reactive oxygen species (ROS), and recent studies have identified critical roles for this interaction in inflammatory macrophages and T helper 17 cells (TH17). Complex II is the site of reverse electron transport in inflammatory macrophages and regulates fumarate levels, which are linked to epigenetic changes. Complex III also produces ROS that activate hypoxia-inducible factor 1-alpha (HIF-1α) and contribute to regulatory T cell (Treg) function. Complex IV is required for T cell activation, differentiation, and Treg subset development. Complex V is required for TH17 differentiation and is sometimes expressed on the surface of tumor cells, where it is recognized by anti-tumor T and NK cells [ 65 ]. miRNA expression profiling identified that miR126 was significantly upregulated in lung ECs exposed to iRBCs under physiological shear stress conditions. miR126 is a well-established pro-angiogenic, pro-survival, and reparative master regulator of ECs lining the extensive pulmonary and systemic vasculature [ 66 ]. miR126 inhibits the migration, proliferation, and survival of human lung microvascular ECs [ 67 ]. Together, the findings presented here newly reveal tissue-specific acute responses of brain and lung ECs stimulated by iRBCs. These findings lay the groundwork for further studies investigating the EC micromechanics that regulate malaria pathogenesis. Material and Methods Endothelial cell culture Primary endothelial cells: HBMEC (brain ECs) (Cell Biologics®- # H-6023) cultivated in complete human endothelial cell kit (Cell Biologics®- #H1168) according to Cell Biologics® guidelines. HMVEC-L (lung ECs) (Provitro®- #1210144) cultivated in microvascular endothelial cell growth medium (Provitro®- #2010102) according to Provitro® guidelines. Plasmodium culture P. falciparum isolate IT4/FCR3S1.2 (long-term laboratory adapted), cultivated in RPMI medium with 10% human serum (A+) and 5% hematocrit (0+). The culture was incubated at 37°C in 5% CO2, 1% O2, and 94% N2. Medium was changed daily, and the culture was split according to the experiments’ requirements [ 68 , 69 ]. Gelatine flotation was used on the day of flow experiments to isolate P. falciparum knobby iRBCs. iRBCs must be highly synchronized (ring/trophozoite/schizont stage). Gelatine flotation [ 70 ] is used to select the trophozoite/schizont stages on the day of assay or 1 day before the assay to obtain synchronized ring stages iRBCs. On the day of assay, the ring-stage iRBCs were resuspended in 1 mL serum-free RMPI medium to estimate the cell count. Microfluidic pump and shear stress application As we published previously [ 70 , 71 ], the following steps were performed. A total of 2x10 5 ECs in one laminar flow slide were seeded 2 days before the assay. ECs were left to adhere for about 2 h. Then 14 mL of ECs culture medium was added into the fluidic unit. One day before the assay, the perfusion set was connected and then air bubbles were removed from the system. The flow was then started with shear stress 1.5 dyne/cm 2 . The fluidic unit and slides were then incubated at 37°C for at least 24 h. On the day of the assay, the medium was then changed to serum-free RPMI medium. Then a total of 2 x 10 7 highly synchronized iRBCs were transferred to the fluidic unit. As a control, RBCS was used in a separate fluidic unit. After the 8 h co-incubation the experiment was stopped. The ECs were then washed with PBS (Phosphate buffer solution) and add detached with 200 µL Accutase™. The ECs were then collected using serum-free medium and then 500µL TRIzol™, was added to the pellet and keept at 80°C until further isolation of RNA/miRNA. EVs purification ECs-EVs were isolated from cell culture with as previously described [ 34 , 72 ]. In brief, the medium was changed to vesicle depleted ECs medium (depletion was done by centrifugation at 100,000 x g for 18 hrs at 4°C). On the next day, (24 h after changing the medium), the cell culture supernatants (15 ml/ T75 flask) were collected and sequentially centrifuged at 600 x g, 1600 x g, 3600 x g and 10,000 x g for 15 min each. After each step, the respective supernatant was collected for the next centrifugation step. To concentrate the EVs, the suspension was passed through ultrafiltration units (100,000 MWCO PES; Sartorius, Göttingen, Germany) for 30 min at 3000 x g. The EVs contained in the concentrated supernatant were dissolved in PBS, layered on top of a 60% sucrose cushion, and centrifuged at 100,000 g for 16 h at 4°C. The interphase was collected and washed with PBS twice at 100,000 x g for 60 min at 4°C. EVs were resuspended and pooled in 1000 µL PBS (0.2 µm filtered) and stored in 200 µL aliquots at -80°C. Protein concentration of EV samples was determined using the QUBIT Protein Assay Kit (ThermoFisher Scientific, Waltham, USA) according to manufacturer’s instructions and by measuring the A 280 content on a Nanodrop2000 (ThermoFisher Scientific, Waltham, USA). Electron microscopy Glow-discharged carbon- and formvar-coated nickel grids (Plano GmbH, Wetzlar, Germany) were incubated with aliquots of freshly isolated EVs. After washing with PBS and incubation in the blocking buffer (0.5% BSA in PBS), the EVs on the grids were labelled with the primary antibody (α human CD29 (integrin beta1), Biolegend, San Diego, USA) at a concentration of 1:100 v/v in PBS (PAA-Laboratories GmbH, Pasching, Austria) containing 0.5% BSA (Sigma-Aldrich, Steinheim, Germany) for at least 21 h at 4°C. The controls for antibody specificity included omitting the primary antibody from the incubating solution. After the incubation period, the grids were rinsed in buffer and further incubated with a goat-anti-mouse colloidal gold-conjugated secondary antibody (12 nm gold particles from Jackson Immuno Research, Cambridgeshire, UK) at a dilution of 1:100 v/v for at least 21 h at 4°C. Nickel grids were rinsed in buffer and stained with 2% aqueous uranyl acetate (Electron Microscopy Sciences, Hatfield, USA) for 15 sec. Grids were finally observed under a Tecnai Spirit electron microscope (Thermo Fisher Scientific, Waltham, USA) operating at 80 kV, and images were recorded with a digital CCD camera. Nanoparticle tracking analysis (NTA) with Nanosight LM10 The pellet of purified EVs was diluted 1:300 in PBS. The following settings were set according to the manufacturer’s software manual (NanoSight LM10 User Manual, MAN0510-04-EN, 2015): the camera level was increased until all particles were distinctly visible (level16 and gain = 20). A total number of 900 frames was recorded in each session (camera: CCD). The autofocus was adjusted to avoid indistinct particles. For each measurement, five 1-min videos were captured under the following conditions: cell temperature: 25°C; Frame rate/FBS: 30. After capture, the videos were analysed by the in-build NanoSight Software (NTA3 0064) with a detection threshold of 6 and screen gain of 10. Immunofluorescence assays ECs were seeded on glass slides. The slides with ECs monolayers were fixed in acetone for 30 min and then rehydrated with 1x PBS for 5 min. The first antibody (1:50 in 3% BSA/PBS; α human CD29 (mouse monoclonal), CBL-162, MM2-57, Millipore) was then added and the slides were incubated for one hour in a humid dark box. The smears were washed 5x with 1X PBS and then labelled with AlexaFluor (1:1000) (Thermo Fisher # A28175) and DAPI (1mg/ml) (1:1000) (Roche # 10236276001) for 1 h in a humid dark box. After a 5x wash with 50 µl 1x PBS, the smears were air dried and Moviol was added before they were covered with a plastic cover slip. Images were taken through a EVOS FL auto-inverted microscope (Thermo Fisher Scientific, Waltham, USA) and analysed using ImageJ 1.53K. To calculate the corrected total cell fluorescence (CTCF), the following formula was used: Integrated Density – (Area of selected cell X Mean fluorescence of background readings). mRNA purification and sequencing Samples in Trizol were thawed before adding 200 µl chloroform and centrifugation for 30 min at 4°C and 800 x g. The miRNeasy mini-Kit- (Qiagen, Hilden, Germany) was used according to the manufacturer’s instructions. The quality of mRNA/miRNA was assessed using the Agilent 2100® bioanalyzer system. According to the manufacturer’s instructions, Ribosomal RNA was removed using QIAseq FastSelect RNA Removal Kit. The QIAseq Stranded mRNA Select Kit was used for mRNA enrichment. mRNA was sequenced using NextSeq 500/550 Mid Output Kit v2.5 (150 Cycles). miRNA purification and sequencing Samples in Trizol were thawed before adding 140 µl chloroform and centrifugation for 15 min at 4°C and 800 x g. The miRNeasy mini-Kit- (Qiagen, Hilden, Germany) was used according to the manufacturer’s instructions. The quality of mRNA/miRNA was assessed using the Agilent 2100® bioanalyzer system. miRNA library preparation was performed in BGI Genomics - China. The small RNAs (18–30 nucleotides) were purified by PAGE. For adapter ligation, the purified RNA was incubated with 3’ adapter followed by the 5’ adapter. Reverse transcription PCR was then performed, and the PCR product was purified by PAGE. After denaturation and circularizing the DNA product, single-stranded circular DNA molecules were replicated via rolling cycle amplification, and a DNA nanoball (DNB) containing multiple copies of DNA was generated. DNBseq-UMI was then performed and about 18 M reads were generated per sample. UMI is known to correct the quantitative bias caused by PCR amplification of more than 70% small RNAs. • DATA ANALYSIS Bioinformatics analysis was conducted using CLC genomics work bench version 21 (Qiagen, Aarhus). Clean reads were imported, and miRNA was quantified and annotated on the miRbase v22. Differential expression was performed, and P-values were adjusted using FDR 10%. miRNAs with extremely low abundance were excluded from our analysis. Hsg38 was used as a mRNA reference. CLC Parameters(miRNA-Quantification): miRBase: miRBase-Release_v22 / Prioritized species = Homo sapiens / Allow length based isomiRs = Yes / Additional upstream bases = 2 / Maximum mismatches = 2 / Strand specific = Yes / Minimum sequence length = 18 / Maximum sequence length = 25 CLC differential expression Parameters (miRNA/mRNA): Whole transcriptome RNA-seq / Normalization Method = TMM / Filter on Average expression for FDR correction / Result Handling = Save CLC Trim Parameters (mRNA): Trim using quality scores = Yes / Quality limit = 0.05 / Trim ambiguous nucleotides = Yes / Maximum number of ambiguities = 2 / Automatic read-through adapter trimming = Yes / Remove 5' terminal nucleotides = No / Remove 3' terminal nucleotides = No / Trim to a fixed length = No / Maximum length = 150 / Trim end = Trim from 3'-end / Discard short reads = No / Discard long reads = No / Save discarded sequences = No / Save broken pairs = No / Create report = Yes CLC RNA-seq Parameters (mRNA): Enable spike-ins = No / Database files = Homo sapiens (hg38) sequence / Maximum cost = 2 / Similarity fraction = 0.8 / Auto-detect paired distances = Yes / Maximum number of hits for a read = 10 / Strand setting = Both / Minimum supporting count = 5 / Create report = Yes / Unmapped reads = No / Expression value = Total count IPA miRNA target identification parameters: QIAGEN Ingenuity Pathway Analysis Software, copyright 2023, was utilized for miRNA target filtration and canonical pathway analysis. This software is web-based and gathers information from publicly available databases containing published relationships, mechanisms, biological functions, canonical pathways, and networks. IPA predicts miRNA regulation of target mRNAs based on data from miRBase, TargetScan, and the QIAGEN Knowledge Base. The filters were based on high-confidence predicted and experimentally validated data only. The included canonical pathways were cellular immune responses, cytokine signaling, and pathogen-influenced signaling. Declarations Data and code availability RNA-sequencing data has been deposited to NCBI and will be publicly available as of the date of publication. The bioproject number is PRJNA1066103. All other original data reported in the paper will be made available by the lead contact upon reasonable request. This paper does not report original code. Any additional information required to re-interrogate the data reported in this paper is available from the lead contact upon request. Author contributions Conceptualization, N.G.M., methodology, M.P.M.T.; H.T.; J.A., S.M., M.B., P.B, Y.W., T. S.; K.H.; and N.G.M, software, N.G.M.; validation, K.H.; B.H.; and N.G.M, formal analysis, N.G.M., writing, original draft preparation, N.G.M; review, and editing, M.P.M.T.; H.T.; B.H.; H.H.; I.B.; and N.G.M. All authors have read and agreed to the published version of the manuscript. Acknowledgments We would like to thank Prof. Egbert Tannich (BNITM) for substantial support at the beginning of the project also special thanks to Dr. Daniel Cadar and Heike Baum (BNITM) for support with NGS sequencing. We also thank Mohsin Shafiq (Institute for Neuropathology, Medical center Hamburg-Eppendorf-Germany) for help and support with Nanosight measurements. We extend special thanks to Monika Rottstegge for the help with the IPA license. This work was supported by Leibniz Center Infection, Jürgen Manchot Stiftung and German research foundation (BR 1744/20-1). 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Nat Rev Mol Cell Biol 12:517–533 Charoenpan P, Indraprasit S, Kiatboonsri S, Suvachittanont O, Tanomsup S (1990) Pulmonary edema in severe falciparum malaria. Hemodynamic study and clinicophysiologic correlation. Chest. ;97(5):1190-7. 10.1378/chest.97.5.1190 . PMID: 2184996 Taylor T, Olola C, Valim C, Agbenyega T, Kremsner P, Krishna S, Kwiatkowski D, Newton C, Missinou M, Pinder M, Wypij D (2006) Standardized data collection for multi-center clinical studies of severe malaria in African children: establishing the SMAC network. Trans R Soc Trop Med Hyg 100(7):615–622 Epub 2006 Mar 23. PMID: 16551469; PMCID: PMC1459261 Andrieux P, Chevillard C, Cunha-Neto E, Nunes JPS (2021) Mitochondria as a Cellular Hub in Infection and Inflammation. Int J Mol Sci 22(21):11338. 10.3390/ijms222111338 PMID: 34768767; PMCID: PMC8583510 Fish JE, Santoro MM, Morton SU, Yu S, Yeh RF, Wythe JD et al (2008) miR126 regulates angiogenic signaling and vascular integrity. Dev Cell 15(2):272–284 Cao D, Mikosz AM, Ringsby AJ, Anderson KC, Beatman EL, Koike K et al (2020) MicroRNA-126-3p inhibits angiogenic function of human lung microvascular endothelial cells via LAT1 (L-type amino acid transporter 1)-mediated mTOR (mammalian target of rapamycin) signaling. Arterioscler Thromb Vasc Biol 40(5):1195–1206 Metwally NG, Tilly AK, Lubiana P, Roth LK, Dörpinghaus M, Lorenzen S, Schuldt K, Witt S, Bachmann A, Tidow H, Gutsmann T, Burmester T, Roeder T, Tannich E, Bruchhaus I (2017) Characterisation of Plasmodium falciparum populations selected on the human endothelial receptors P-selectin, E-selectin, CD9 and CD151. Sci Rep 7(1):4069. 10.1038/s41598-017-04241-3 PMID: 28642573; PMCID: PMC5481354 Trager W, Jensen JB (2005) Human malaria parasites in continuous culture. 1976. J Parasitol 91:484–486 Wu Y, Bouws P, Lorenzen S, Bruchhaus I, Metwally NG (2021) Analysis of the Interaction Between Plasmodium falciparum -Infected Erythrocytes and Human Endothelial Cells Using a Laminar Flow System, Bioinformatic Tracking and Transcriptome Analysis. Methods Mol Biol. ;2369:187–197. 10.1007/978-1-0716-1681- 9_11 . PMID: 34313990 Lubiana P, Bouws P, Roth LK, Dörpinghaus M, Rehn T, Brehmer J, Wichers JS, Bachmann A, Höhn K, Roeder T, Thye T, Gutsmann T, Burmester T, Bruchhaus I, Metwally NG (2020) Adhesion between P. falciparum infected erythrocytes and human endothelial receptors follows alternative binding dynamics under flow and febrile conditions. Sci Rep 10(1):4548. 10.1038/s41598-020-61388-2 PMID: 32161335; PMCID: PMC7066226 Mantel PY, Hoang AN, Goldowitz I, Potashnikova D, Hamza B, Vorobjev I, Ghiran I, Toner M, Irimia D, Ivanov AR et al (2013) Malaria-infected erythrocytederived microvesicles mediate cellular communication within the parasite population and with the host immune system Tables Table 1 is available in the Supplementary Files section. Additional Declarations There is NO Competing Interest. Supplementary Files MetwallyetalSupplementaryFigure1.pdf Figure 1 MetwallyetalSupplementaryFigure2.pdf Figure 2 Supplement1.xlsx Supplementary Table 1 Supplement2.xlsx Supplementary Table 2 Supplement3.xlsx Supplementary Table 3 Supplement4.xlsx Supplementary Table 4 Supplement5.xlsx Supplementary Table 5 Supplement6.xlsx Supplementary Table 6 Supplement7.xlsx Supplementary Table 7 Supplement8.xlsx Supplementary Table 8 Supplement9.xlsx Supplementary Dataset 9 Supplement10.xls Supplementary Table 10 Supplement11.xlsx Supplementary Dataset 11 Supplement12.xlsx Supplementary Table 12 MetwallyetalTable1.png Table 1: Top significantly regulated miRNA candidates and their target mRNAs within the HBMEC 1.5 SupplementFiguresandTablesLegends.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4222036","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":287915127,"identity":"13d0323a-0dec-4cf4-a0fe-3f1f86d11a18","order_by":0,"name":"Nahla 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Medicine","correspondingAuthor":false,"prefix":"","firstName":"Iris","middleName":"","lastName":"Bruchhaus","suffix":""}],"badges":[],"createdAt":"2024-04-05 09:35:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4222036/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4222036/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54265823,"identity":"5635e8a3-1e98-4f17-80f7-4ef8ab9a5f21","added_by":"auto","created_at":"2024-04-08 04:59:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":147291,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic overview of study workflow.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003e Primary brain endothelial cells (ECs) were cultured under static conditions without TNFα (HBMEC\u003csup\u003estatic\u003c/sup\u003e) or with TNFα (HBMEC\u003csup\u003estatic+TNF\u003c/sup\u003e) as were primary lung ECs (HMVEC-L\u003csup\u003estatic \u003c/sup\u003eor HMVEC-L\u003csup\u003estatic+TNF\u003c/sup\u003e). Culture supernatants containing EVs were harvested and sequentially centrifuged to isolate EVs. \u003cstrong\u003e(B)\u003c/strong\u003e Transmission electron microscopy was performed to confirm the presence of EVs after purification. \u003cstrong\u003e(C)\u003c/strong\u003e A laminar flow system was used to apply shear stress of 1.5 dyne/cm\u003csup\u003e2\u003c/sup\u003e. Stimuli were then added to the fluidic unit: i) incubation at 40°C (ECs\u003csup\u003e1.5+40°C\u003c/sup\u003e), ii) non-infected red blood cells (RBCs) (ECs\u003csup\u003e1.5+RBCs\u003c/sup\u003e), and iii) infected RBCs (iRBCs) (ECs\u003csup\u003e1.5+Rings\u003c/sup\u003e). \u003cstrong\u003e(D) \u003c/strong\u003emRNA/miRNA was then isolated from ECs and purified EVs and subjected to NGS sequencing \u003cstrong\u003e(E)\u003c/strong\u003e Raw data was extracted and subjected to RNA-seq analysis and miRNA counting using CLC genomics workbench. Subsequently, differential expression comparisons were performed. Finally, miRNA target filtration was performed followed by pathway analysis using reactome and KEGG pathway analysis.\u003c/p\u003e","description":"","filename":"MetwallyetalFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/0257356514521c5584af85c5.png"},{"id":54265821,"identity":"72938497-21ae-4945-a0fb-9199ed8e0ef8","added_by":"auto","created_at":"2024-04-08 04:59:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":268478,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHMVEC-L\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003estatic \u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003eversus HBMEC\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003estatic\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e gene expression analysis.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003e Heatmap representing expression levels of the most differentially expressed miRNAs between HBMEC \u003csup\u003estatic\u003c/sup\u003e and HMVEC-L\u003csup\u003estatic \u003c/sup\u003ecells. \u003cstrong\u003e(B)\u003c/strong\u003e The nine most highly-expressed miRNAs in HBMEC\u003csup\u003estatic\u003c/sup\u003e cells relative to HMVEC-L\u003csup\u003estatic \u003c/sup\u003ecells. \u003cstrong\u003e(C)\u003c/strong\u003e The 12 most highly expressed miRNAs HMVEC-L\u003csup\u003estatic\u003c/sup\u003e relative to HBMEC\u003csup\u003estatic\u003c/sup\u003e. \u003cstrong\u003e(D) \u003c/strong\u003e\u0026nbsp;Transmission electron microscopy (TEM) images confirming the presence of EVs after purification from HBMEC\u003csup\u003estatic\u003c/sup\u003e culture supernatant. \u003cstrong\u003e(E) \u003c/strong\u003e\u0026nbsp;HBMEC-EVs were incubated with anti-CD29 antibody and subjected to immunogold labelling.\u003cstrong\u003e (F) \u003c/strong\u003eTEM images confirming the presence of EVs after purification from HMVEC-L\u003csup\u003estatic \u003c/sup\u003eculture supernatant. \u003cstrong\u003e(G) \u003c/strong\u003e\u0026nbsp;HMVEC-L-EVs were incubated with anti-CD29 antibody and subjected to immunogold labelling. \u003cstrong\u003e(H)\u003c/strong\u003e Heatmap representing expression levels of most differentially expressed miRNAs in HBMEC-EVs and HMVEC-L-EVs. \u003cstrong\u003e(I)\u003c/strong\u003e The six most highly-expressed miRNAs in HBMEC EVs and relative expression, if any, in HMVEC-L-EVs. \u003cstrong\u003e(J)\u003c/strong\u003e The 12 most highly-expressed miRNAs in HMVEC-L-EVs and relative expression, if any, in HBMEC-EVs. Comparisons were performed using the differential expression function in CLC Genomics software V22. Statistical significance was calculated based on an FDR-adjusted p-value.\u003c/p\u003e","description":"","filename":"MetwallyetalFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/00471f943329f779cf865f97.png"},{"id":54265829,"identity":"1b93cf74-481d-4e68-8b3d-bdc1cae975b3","added_by":"auto","created_at":"2024-04-08 04:59:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":73802,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of shear stress on HMBEC miRNA profile.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003e Heatmap representing expression levels of the most differentially expressed miRNAs between HBMEC\u003csup\u003e1.5\u003c/sup\u003e and HBMEC\u003csup\u003estatic\u003c/sup\u003e\u003cstrong\u003e (B-S)\u003c/strong\u003e The 18 most differentially expressed miRNAs in HBMEC\u003csup\u003e1.5 \u003c/sup\u003erelative to HBMEC\u003csup\u003estatic\u003c/sup\u003e. \u003cstrong\u003e(T) \u003c/strong\u003ePathways most affected by shear stress in HBMEC\u003csup\u003e1.5 \u003c/sup\u003erelative to HBMEC\u003csup\u003estatic\u003c/sup\u003e. Comparisons were performed using the differential expression function in CLC Genomics software V22. Statistical significance was calculated based on the FDR-adjusted p-value.\u003c/p\u003e","description":"","filename":"MetwallyetalFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/44c4c13285b1ce99abbcea08.png"},{"id":54265826,"identity":"ad35691f-32a3-4696-90bf-9acec2b7d8de","added_by":"auto","created_at":"2024-04-08 04:59:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":108468,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePathways significantly affected by shear stress in HBMECs.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003e Effects of physiological shear stress (1.5 dyne/cm\u003csup\u003e2\u003c/sup\u003e) on calcium channel pathway signalling, as identified by mRNA-sequencing. \u003cstrong\u003e(B)\u003c/strong\u003e Effects of shear stress on genes encoding tight junction components. \u003cstrong\u003e(C)\u003c/strong\u003e Effect of shear stress on complement and coagulation cascade pathways. \u003cstrong\u003e(D)\u003c/strong\u003e Effects of shear stress on leukocyte transmigration signalling.\u003cstrong\u003e (E)\u003c/strong\u003e Effect of shear stress on CXC subfamily signalling.\u003c/p\u003e","description":"","filename":"MetwallyetalFigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/08fe4db6cc789a9ba576b429.png"},{"id":54266409,"identity":"27ce259e-2242-407c-a847-3814e98543e3","added_by":"auto","created_at":"2024-04-08 05:07:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":63724,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of iRBC exposure on HMBEC miRNA profile.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003e Heatmap representing expression levels miRNAs differentially expressed miRNAs in HBMEC\u003csup\u003e1.5+Rings\u003c/sup\u003e relative to HBMEC\u003csup\u003e1.5+RBCs\u003c/sup\u003e\u003cstrong\u003e (B-I)\u003c/strong\u003e The eight miRNAs most differentially expressed in HBMEC\u003csup\u003e1.5+Rings \u003c/sup\u003erelative to HBMEC\u003csup\u003e1.5+RBCs\u003c/sup\u003e. \u003cstrong\u003e(J) \u003c/strong\u003eTarget\u003cstrong\u003e \u003c/strong\u003epathways most affected by exposure to iRBCs. Comparisons were performed using the differential expression function in CLC Genomics software V22. Statistical significance was calculated based on an FDR-adjusted p-value.\u003c/p\u003e","description":"","filename":"MetwallyetalFigure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/a90fa0f261f553359022070d.png"},{"id":54265831,"identity":"ddda76f0-9582-42cd-9b99-62065a981fe1","added_by":"auto","created_at":"2024-04-08 04:59:02","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":622177,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePathways significantly affected by iRBC exposure in HMBECs.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003e The endosomal signalling pathway was affected by co-incubation with ring stage iRBCs and shear stress (1.5 dyne/cm\u003csup\u003e2\u003c/sup\u003e), as demonstrated by mRNA-sequencing. \u003cstrong\u003e(B)\u003c/strong\u003e The CXC subfamily signalling pathway was affected by co-incubation with ring stage iRBCs and shear stress 1.5 dyne/cm\u003csup\u003e2\u003c/sup\u003e,with six genes downregulated and one gene upregulated.\u003cstrong\u003e (C)\u003c/strong\u003e Co-incubation with ring stage iRBCs affected expression of genes encoding tight unction components in HBMECs,\u003csup\u003e \u003c/sup\u003ewith most genes downregulated in HBMEC\u003csup\u003e1.5+Rings\u003c/sup\u003e compared with HBMEC\u003csup\u003e1.5+RBCs\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"MetwallyetalFigure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/f9e1e32025bc8e93d90789eb.jpg"},{"id":54265833,"identity":"234cffad-b896-4ecb-92ee-15e1bb5ad9a0","added_by":"auto","created_at":"2024-04-08 04:59:02","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":163934,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of iRBC exposure on the electon transport chain in HMVEC-Ls.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003e Heatmap representing expression levels of the most differentially expressed miRNAs in HMVEC-L\u003csup\u003e1.5+Rings\u003c/sup\u003e relative to HMVEC-L\u003csup\u003e1.5-RBCs\u003c/sup\u003e\u003cstrong\u003e (B-J)\u003c/strong\u003e The nine miRNAs most significantly affected in HMVEC-L\u003csup\u003e1.5+Rings\u003c/sup\u003e. Comparisons were performed using the differential expression function in CLC Genomics software V22. Statistical significance was calculated based on an FDR-adjusted p-value. \u003cstrong\u003e(K)\u003c/strong\u003e Genes encoding components of the electron transport chain were differentially expressed in HMVEC-L\u003csup\u003e1.5+Rings\u003c/sup\u003e relative to HMVEC-L\u003csup\u003e1.5-RBCs\u003c/sup\u003e, with most genes upregulated.\u003c/p\u003e","description":"","filename":"MetwallyetalFigure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/36479808b041ec163fb25967.png"},{"id":54426756,"identity":"3318f888-d4c4-4bb9-8947-9b47a4be5a18","added_by":"auto","created_at":"2024-04-10 09:34:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1654923,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/4b798f0d-a4d5-486c-9827-e651c3a829cf.pdf"},{"id":54266408,"identity":"0dab9a9a-93c8-477e-a3fe-55ac9638962b","added_by":"auto","created_at":"2024-04-08 05:07:01","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":123310,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 1\u003c/p\u003e","description":"","filename":"MetwallyetalSupplementaryFigure1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/7d308b74b3e7beb4cf101aa3.pdf"},{"id":54266410,"identity":"1f416d8f-eef1-4bf7-bdec-f1e9776b76c0","added_by":"auto","created_at":"2024-04-08 05:07:02","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":465751,"visible":true,"origin":"","legend":"Figure 2","description":"","filename":"MetwallyetalSupplementaryFigure2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/760c41eaa324086d71112b09.pdf"},{"id":54265824,"identity":"dc9ec943-7510-4810-bb81-2ce7fb517f0a","added_by":"auto","created_at":"2024-04-08 04:59:02","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":546043,"visible":true,"origin":"","legend":"Supplementary Table 1","description":"","filename":"Supplement1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/4a312b6287bb4e83f973160b.xlsx"},{"id":54265843,"identity":"58195f76-a054-4d08-a046-404e13b51909","added_by":"auto","created_at":"2024-04-08 04:59:03","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":3399087,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 2\u003c/p\u003e","description":"","filename":"Supplement2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/4f5c97a55d36b0cc4f10e498.xlsx"},{"id":54265836,"identity":"b3d3624e-b635-4cbb-88c6-5dd34f565b5a","added_by":"auto","created_at":"2024-04-08 04:59:02","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1702974,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 3\u003c/p\u003e","description":"","filename":"Supplement3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/59016d6539f23d706d8b4b6e.xlsx"},{"id":54265825,"identity":"40146ace-9172-4320-8c50-ac4ef23232d4","added_by":"auto","created_at":"2024-04-08 04:59:02","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":431290,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 4\u003c/p\u003e","description":"","filename":"Supplement4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/c469f441e0325f8d8957d86b.xlsx"},{"id":54265834,"identity":"04dd1b20-2577-4da4-b4a4-0354743fd7f8","added_by":"auto","created_at":"2024-04-08 04:59:02","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":2696256,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 5\u003c/p\u003e","description":"","filename":"Supplement5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/1e73bb442f6e26f631b73444.xlsx"},{"id":54265828,"identity":"837bff1d-fcf0-4fd9-a305-56baa5ab5ff8","added_by":"auto","created_at":"2024-04-08 04:59:02","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":120996,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 6\u003c/p\u003e","description":"","filename":"Supplement6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/d6a76895b06a28823879ab57.xlsx"},{"id":54265835,"identity":"3599c674-d5c9-47e7-a5ed-0a35d3cb2891","added_by":"auto","created_at":"2024-04-08 04:59:02","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":420460,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 7\u003c/p\u003e","description":"","filename":"Supplement7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/212661b6efe2126999072f7b.xlsx"},{"id":54265842,"identity":"4dce4a55-34dd-4320-be2b-6b0bd728f6a2","added_by":"auto","created_at":"2024-04-08 04:59:03","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":2891884,"visible":true,"origin":"","legend":"Supplementary Table 8","description":"","filename":"Supplement8.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/e462985fe20543b3dea184ce.xlsx"},{"id":54265841,"identity":"9d72eb25-6c0a-4e85-af85-9ead3f207d7e","added_by":"auto","created_at":"2024-04-08 04:59:03","extension":"xlsx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":2886590,"visible":true,"origin":"","legend":"Supplementary Dataset 9","description":"","filename":"Supplement9.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/3f3bdf31bf9d3405d04535e4.xlsx"},{"id":54265838,"identity":"257155d8-99ce-40e1-abdb-ae6e4a973ddc","added_by":"auto","created_at":"2024-04-08 04:59:03","extension":"xls","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":478720,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Table 10\u003c/p\u003e","description":"","filename":"Supplement10.xls","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/755cf1d7dd4174dcd2186d0f.xls"},{"id":54266411,"identity":"02b7d1d2-2e3d-478c-8dfc-ce7305135f92","added_by":"auto","created_at":"2024-04-08 05:07:02","extension":"xlsx","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":4376108,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Dataset 11\u003c/p\u003e","description":"","filename":"Supplement11.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/4f3d374359d6d9db218a60b1.xlsx"},{"id":54265844,"identity":"a4ca874f-b9be-4925-9af2-d626920a73f4","added_by":"auto","created_at":"2024-04-08 04:59:03","extension":"xlsx","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":5235365,"visible":true,"origin":"","legend":"Supplementary Table 12","description":"","filename":"Supplement12.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/44741c6c85138401323ee74c.xlsx"},{"id":54265840,"identity":"d9833117-eff6-40c2-bec9-9fdcd048eeb0","added_by":"auto","created_at":"2024-04-08 04:59:03","extension":"png","order_by":15,"title":"","display":"","copyAsset":false,"role":"supplement","size":93322,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;1: Top significantly regulated miRNA candidates and their target mRNAs within the HBMEC\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e1.5\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e","description":"","filename":"MetwallyetalTable1.png","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/32fac887c2a1fe43ecebc2bc.png"},{"id":54265837,"identity":"03bebb71-120f-49a3-bcfd-27008021ebd7","added_by":"auto","created_at":"2024-04-08 04:59:02","extension":"docx","order_by":16,"title":"","display":"","copyAsset":false,"role":"supplement","size":14499,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementFiguresandTablesLegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-4222036/v1/991317b7b94ed9f25dc47825.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Tissue-specific responses of brain and lung endothelial cell miRNA and mRNA profiles to the ring-stage Plasmodium falciparum-infected red blood cells","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWidespread parasite resistance to artemisinin therapy is hampering malaria eradication programs, and more research into the host response to infection is needed to develop adjuvant therapies that minimize complications. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Malaria deaths reached 608,000 cases in 2022 with 249\u0026nbsp;million clinical malaria infections. Pregnant women and children under 5 years of age are most likely to develop severe malaria, with children\u0026thinsp;\u0026lt;\u0026thinsp;5 years of age accounting for 67% of all malaria deaths [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Five parasite species cause malaria, and \u003cem\u003ePlasmodium falciparum\u003c/em\u003e (\u003cem\u003eP. falciparum\u003c/em\u003e) is the most virulent, responsible for 95% of malaria deaths and 200\u0026nbsp;million annual clinical infections. The life cycle of \u003cem\u003eP. falciparum\u003c/em\u003e is complex, including sexual and asexual stages in female \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes and human hosts. When a female Anopheles mosquito infected with \u003cem\u003eP. falciparum\u003c/em\u003e bites a person, it injects \u003cem\u003efalciparum\u003c/em\u003e sporozoites into the skin. These sporozoites then travel to the liver and invade a hepatocyte, where they undergo a cycle of asexual replication. This produces a hepatic schizont containing numerous merozoites. The merozoites then enter the bloodstream and infect red blood cells (RBCs), developing from ring stages to trophozoites and then to schizonts. Once mature, the schizonts rupture, releasing more merozoites that continue the replication cycle. Finally, some of the parasites produce male and female gametocytes. The mosquito takes these up to continue the cycle [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFatalities occur due to serious complications of malaria. These complications include cerebral malaria (CM), lung injury, renal failure, acidosis, and severe anemia [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The virulence of \u003cem\u003eP. falciparum\u003c/em\u003e is attributed to the parasites\u0026rsquo; ability to modify the erythrocyte surface to adhere and to evade the host immune attack. The major antigenic ligand found to be responsible for the cytoadhesive properties of the infected red blood cells (iRBC) are members of the \u003cem\u003eP. falciparum\u003c/em\u003e erythrocyte membrane protein-1 (\u003cem\u003ePf\u003c/em\u003eEMP1) family [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe pathogenesis of severe malaria is hotly debated; some researchers suggest that cytoadhesion is the overriding pathogenic mechanism, whilst others believe that inflammatory processes are more important. An accumulating body of evidence indicates that vascular endothelial dysfunction is also important and could be the interface between cytoadhesion and inflammation [\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. We concluded that establishing the causal role of any single mechanism in severe malaria in human is difficult. That\u0026rsquo;s why we planned to investigate more deeply into the host-parasite interaction mechanisms.\u003c/p\u003e \u003cp\u003eIn the human host, RBCs and endothelial cells (ECs) are the primary cells that interact with parasites during \u003cem\u003eP. falciparum\u003c/em\u003e infection. During this host-parasite interaction, biological material is exchanged. This includes the transfer of human microRNA (miRNA) between iRBCs and other non-infected cells within the human host, including non-infected RBCs, ECs, and immune cells [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Although miRNAs are known to control 60% of the human genes, but their role in malaria complications remains incompletely understood.\u003c/p\u003e\n\u003ch3\u003emiRNAs\u003c/h3\u003e\n\u003cp\u003emiRNAs are non-coding RNAs approximately 20 nucleotides in length, and are found in mammals, plants, and viruses. According to miRBase version 22, the human genome encodes\u0026thinsp;~\u0026thinsp;300 true mature miRNAs, of which 1,115 are currently annotated [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. An individual miRNA can repress tens to hundreds of genes, and miRNAs regulate nearly every cellular and metabolic process [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Since the discovery of miRNA in 1993, miRNA has been increasingly recognized as an essential post-transcriptional gene regulator [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Different steps of miRNA biogenesis occur in the nucleus and cytoplasm. In the nucleus, the corresponding region of the genome is transcribed by RNA polymerase II to produce primary miRNA (pri-miRNA)\u0026thinsp;\u0026gt;\u0026thinsp;200 nucleotides in length. The DiGeorge Syndrome Critical Region 8 (Drosha/DGCR8) complex, which consists of RNase III family enzymes, crops the pri-miRNA into precursor miRNA (pre-miRNA) 70 nucleotides in length [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The pre-miRNA is then transported into the cytoplasm. The trans-activation responsive RNA-binding protein (TRBP)/dicer complex cuts the hairpin-like structure in pre-miRNA, processing pre-miRNA into a 14-21-nucleotide duplex mature miRNA structure comprised of two strands, the mature miRNA targeting strand and the miRNA passenger strand. mRNA target recognition occurs via binding of the short seed region (2\u0026ndash;8 nucleotides) at the 5\u0026rsquo; miRNA end (guide strand) and a partially or perfectly complementary region on the target mRNA 3\u0026rsquo; untranslated region (UTR). This binding interaction represses translation of target mRNA and in some cases targets mRNA for degradation. The passenger strand was thought to be degraded, but recent research has shown that both miRNA strands have functional significance [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. It was previously thought that miRNAs only negatively regulate target mRNA, but recent observations suggest that miRNAs can both repress and stimulate gene expression depending on various factors such as cellular conditions, sequences, and cofactors [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eisomiRs\u003c/h3\u003e\n\u003cp\u003eThe discovery of miRNA isoforms, or isomiRs, was facilitated by high-throughput technologies such as deep RNA sequencing. IsomiRs differ from canonical miRNAs in length and/or sequence and are generated via RNA modifications catalyzed by enzymes such as deaminases and exonucleases. These molecules were initially hypothesized to be RNA-sequencing/mapping errors. However, subsequent studies demonstrated that small RNA-sequencing data contained a significantly higher percentage of untemplated nucleotide additions (%NTA) than the expected sequencing error rate calculated using small artificial RNAs. These studies confirm that canonical microRNA sequence modifications are physiological events that occur \u003cem\u003ein vivo\u003c/em\u003e rather than experimental artifacts, which has been supported by the development of more advanced analysis algorithms. IsomiRs, like their canonical counterparts, have distinct functional roles. isomiRs bind Argonaute (Ago) proteins, as demonstrated by co-immunoprecipitation assays, and inhibit target gene expression, as demonstrated by \u003cem\u003ein vitro\u003c/em\u003e luciferase assays [\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eVascular endothelium\u003c/h3\u003e\n\u003cp\u003eApproximately 96,000 km of blood vessels contained in the human body are maintained by ECs, a heterogeneous cell type that responds to signals in the microenvironment. ECs line the blood and lymph vessels except for the placenta, and form a physical barrier between the blood and tissue. ECs consist of a luminal membrane in direct contact with blood and circulating cells [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and a basolateral surface. The basolateral surface is separated from the surrounding tissue by a basement membrane consisting of glycoproteins produced by ECs and anchored to their cell membrane. ECs perform numerous functions that depend on their location and activation status. These include maintaining vascular tone, controlling homeostasis, transporting hormones, and recruiting immune cells. ECs initiate and amplify the inflammatory response to vascular insults. ECs exhibit tissue type-specific heterogeneity. For example, tight junctions, absence of fenestrae, reduced pinocytic activity, and carrier-mediated transport systems are unique features of ECs that maintain the blood-brain barrier (BBB). The BBB protects the central nervous system from pathogens and toxic substances and restricts entry of antibodies and immune cells [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eEndothelial shear stress\u003c/h2\u003e \u003cp\u003eVascular ECs sense hemodynamic changes and signals transmitted by the blood and respond by releasing vasoactive substances [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Shear stress affects EC morphology, electrochemical activities, and gene expression. Most importantly, NO release increases in response to shear stress, which is regulated by rapid activation of endothelial nitric oxide synthase 3 (eNOS) and upregulation of eNOS gene expression and transcriptional activation [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUnder physiological conditions, endothelium-derived relaxation and contraction factors are in equilibrium. Vascular homeostasis is maintained with a slight bias in favor of vasodilation [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The endothelium is exposed to radial forces caused by intravascular pressure, tangential forces in the vessel wall caused by the balance between cell-cell contacts and vessel movement, and axial shear forces caused by the friction of blood flowing against the vessel wall. ECs are typically exposed to shear stress of 1\u0026ndash;100 dyne/cm\u003csup\u003e2\u003c/sup\u003e in the form of steady or pulsatile unidirectional shear. In culture, ECs are different from cells that grow in static conditions, forming a functionally confluent monolayer of cells. ECs can sense and respond to many stimuli, including the shear force of blood flowing through cell-cell junctions, heterotrimeric G proteins, primary cilia, caveolae, integrins, and the glycocalyx (GCX) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eExtracellular vesicles\u003c/h2\u003e \u003cp\u003eExtracellular vesicles (EVs) are tiny lipid particles released by every living cell. They contain proteins, lipids, RNA, and DNA and can transport bioactive molecules. EVs also act as carriers that facilitate cell-to-cell communication, including antigen presentation and inflammatory activation [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Recently, there has been a lot of interest in studying the biology and functions of EVs, particularly in immune regulation and host-pathogen interactions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eVascular cell-pathogen interactions\u003c/h2\u003e \u003cp\u003eJambusaria et al. referred to the genetic signature of ECs as \u0026ldquo;postal codes\u0026rdquo; for organ-specific drugs. Identifying the differences in genetic signatures between ECs in different organs provides insight into the molecular underpinnings of EC heterogenicity [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Prior studies have explored the transcriptional landscape of brain ECs, and a smaller number of studies have evaluated the transcriptional profiles of lung ECs, but very few studies have explored the organ-specific heterogenicity of EC miRNA profiles. Lung ECs are in contact with the external environment due to their gas exchange function, and thus must initiate a rapid immune response in the event of infection. Lung ECs also facilitate the entrance of immune cells into the lungs to fight invading bacteria and viruses. Contrastingly, brain ECs prevent toxic molecules from entering the brain and maintain a much tighter barrier structure [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Understanding how ECs of different organs respond to stimuli contributes to drug design for infectious disease.\u003c/p\u003e \u003cp\u003eIn the present study, we investigated intrinsic immune pathways in the brain and lungs ECs that might contribute to complications or protect the host. To pursue these scientific questions, we designed experiments to investigate the mRNA and miRNA profiles of primary human brain and lung ECs exposed to iRBCs. First, we compared the profiles of both ECs and EVs secreted by ECs to characterize the intrinsic heterogeneity between brain and lung ECs. Second, we exposed brain and lung ECs to authentic shear stress stimulation with similar stress levels to microvessels to create a physiologically relevant model. We subsequently evaluated the cellular response to shear stress and iRBC exposure to identify affected pathways and identify miRNAs that could potentially regulate these pathways. We demonstrated that shear stress activated multiple processes in brain ECs, including IL-8 signalling and strengthening of tight junctions. miRNAs differentially expressed in the ECs potentially controlled these pathways. Incubation with ring-stage iRBCs results in the activation of endocytic pathways in brain ECs. Contrastingly, in lung ECs, the most prominent activated pathway was the electron transport chain. \u003cem\u003eIn silico\u003c/em\u003e analyses identified that in the context of malaria exposure, endocytosis and electron transport pathways were potentially targeted by candidate miRNAs. The candidate miRNAs were significantly altered following 8 hours of co-incubation with ring-stage iRBCs at a shear stress of 1.5 dyne/cm\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eExperimental Models\u003c/h2\u003e \u003cp\u003eExperiments were conducted in brain and lung human primary ECs. Cellular miRNA and mRNA sequencing were performed after exposing both cell types to multiple stimuli (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA): a) shear stress of 1.5 dyne/cm\u003csup\u003e2\u003c/sup\u003e (ECs\u003csup\u003e1.5\u003c/sup\u003e), b) shear stress plus fever (40\u0026deg;C) (ECs\u003csup\u003e1.5+40\u0026deg;C\u003c/sup\u003e), c) shear stress plus uninfected RBCs (ECs\u003csup\u003e1.5+RBCs\u003c/sup\u003e), and d) shear stress plus ring stage-iRBCs, or iRBCs (ECs\u003csup\u003e1.5+Rings\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). The supernatant of static culture was also collected for EV purification and subsequent miRNA isolation and sequencing (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Deep NGS sequencing was then conducted, and data were extracted (20\u0026nbsp;million reads for miRNA and 6\u0026ndash;10\u0026nbsp;million reads for mRNA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). The obtained data were analysed by CLC genomics, Ingenuity Pathway Analysis (IPA), KEGG, and Reactome analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). Raw data are uploaded to the NCBI platform (PRJNA1066103).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eHeterogeneity of miRNA and mRNA in brain and lung ECs and secreted EVs\u003c/h2\u003e \u003cp\u003eTo characterize intrinsic differences between primary brain ECs (HBMECs) and primary lung ECs (HMVEC-L), we performed miRNA/mRNA-seq on both HBMECs and HMVEC-L (Supplementary Tables S1 and S2). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA shows a heat map of miRNAs differentially expressed in lung and brain ECs. Brain ECs exhibited higher expression of 118 mature miRNAs relative to lung ECs, while 152 mature miRNAs were more highly expressed in lung ECs relative to brain ECs (Supplementary Table S1). Seed miRNAs differentially expressed in lung and brain ECs are blotted in the lower part of the heatmap (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The most significantly altered nine miRNAs with increased brain EC expression level are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB. The most significantly altered mature miRNAs that were more highly expressed in lung ECs are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC. Subsequently, we stained brain and lung ECs with the EC marker CD29 to confirm its expression on EC surfaces (Supplementary Figure S1).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe then purified and prepared EVs as previously described [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] for analysis with transmission electron microscopy (TEM). Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD shows TEM images of EVs purified from primary brain ECs (HBMEC-EVs). We then labelled EVs with CD29 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE), thus confirming that these EVs originated from ECs. We also purified and labelled EVs from primary lung ECs (HMVEC-L-EVs) (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF-G). Both EV populations retained the normal characteristics of EVs [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Differential miRNA expression analysis revealed 19 mature and 180 seed miRNAs differentially expressed between brain (HBMEC-EVs) and lung (HMVEC-L-EVs) EVs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH and Supplementary Table S3). The six mature miRNAs with significantly higher expression in HBMEC-EVs are plotted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eI. The twelve mature miRNAs with significantly higher expression in HMVEC-L-EVs are plotted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eJ.\u003c/p\u003e \u003cp\u003eIn parallel, we scanned the mRNA profiles for HBMECs and HMVEC-L (Supplementary Table S2). A total of 3,497 genes were differentially expressed between HBMECs and HMVEC-L. A total of 1,601 genes were exclusively expressed in lung ECs, while 1,896 genes were exclusively expressed in brain ECs.\u003c/p\u003e \u003cp\u003eReactome pathway analysis revealed three prominent clusters of genes highly regulated in each cell type. In brain ECs, the primary clusters were intercellular communication, signal transduction, and the immune response. In lung ECs, the most prominent clusters were extracellular matrix organisation, cellular response to stimuli, and haemostasis (Supplementary Figure S2A-S2B).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEffect of shear stress on HBMEC miRNA and mRNA profiles\u003c/h2\u003e \u003cp\u003eThe EC response to shear stress is involved in multiple developmental and physiological vascular processes such as angiogenesis, vascular morphogenesis, vascular remodelling, and vascular tone. To identify miRNAs affected by physiological shear stress (1.5 dyne/cm\u003csup\u003e2\u003c/sup\u003e), we compared miRNA expression between HBMECs exposed to 1.5 dyne/cm\u003csup\u003e2\u003c/sup\u003e shear stress (HBMEC\u003csup\u003e1.5\u003c/sup\u003e) and HBMECs cultivated under static conditions (HBMEC\u003csup\u003estatic\u003c/sup\u003e) (Supplementary Table S4). Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA shows a heatmap representing differentially expressed mature and seed miRNAs in HBMEC\u003csup\u003e1.5\u003c/sup\u003e cells relative to HBMEC\u003csup\u003estatic\u003c/sup\u003e cells. The 18 most differentially expressed miRNAs are plotted in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB-\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eS. In parallel, mRNA from the same samples was sequenced (Supplementary Table S5). A total of 6,182 genes were affected by shear stress, with 3,693 genes upregulated and 2,489 genes downregulated. Subsequently, we identified the target genes of differentially expressed miRNAs (Supplementary Table S6). Respectively, pathway analysis identified that miRNAs targeting eleven major pathways were affected by shear stress, with differential miRNA expression in HBMEC\u003csup\u003e1.5\u003c/sup\u003e relative to HBMEC\u003csup\u003estatic\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eT). The most affected pathways were cytokine-cytokine receptor interaction, actin cytoskeleton, calcium signalling, and cell adhesion molecules.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA shows which components of the calcium channel pathway were upregulated by shear stress (red), downregulated by shear stress (green), and unchanged (blue), as identified by mRNA-sequencing. This was consistent with prior reports of mechanosensitive calcium-permeable channels in ECs in response to shear stress [\u003cspan additionalcitationids=\"CR37 CR38 CR39 CR40 CR41\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSubsequently, we determined which miRNA candidates within the ECs could affect differentially regulated pathways. We identified 33 candidate miRNAs that target genes in calcium channel pathways (Table\u0026nbsp;1). ECs have a low resting intracellular calcium concentration, which is maintained by plasma membrane calcium-ATPase (PMCA) and sarco/endoplasmic reticulum Ca2\u003csup\u003e+\u0026minus;\u003c/sup\u003eATPase (SERCA) channels. PMCAs are localized to EC plasma membranes and SERCAs are localized to endoplasmic reticulum membranes. Both classes of ATPases actively transport calcium ions from the cytoplasm to the extracellular space or ER to maintain low intracellular calcium concentrations. Stimulation of G protein-coupled receptors (GPCRs) activates phospholipase C (PLC), triggering hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP2) to diacylglycerol (DAG) and inositol triphosphate (IP3). IP3 facilitates calcium entry from the sarcoplasmic reticulum and extracellular space. Store-operated cation channels and receptor-operated cation channels facilitate calcium entry from the extracellular space. During stimulation, calcium influx into ECs facilitates dephosphorylation of nuclear factor of activated T-cells (NFAT) from phospho-NFAT (pNFAT) to NFAT. NFAT then translocates to the nucleus [\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], activating transcription of \u003cem\u003eICAM1\u003c/em\u003e (Intracellular adhesion molecule \u0026minus;\u0026thinsp;1).\u003c/p\u003e \u003cp\u003eSecondly, we investigated the effects of shear stress on tight junction (TJ) components in HBMEC\u003csup\u003e1.5\u003c/sup\u003e. TJs are formed by homophilic interactions between transmembrane proteins and junctional adhesion molecules on neighbouring cells. TJs determine the tightness of the endothelial barrier by regulating diffusion of fluids, ions, and small plasma proteins and penetration of cells such as leukocytes, neutrophils, and lymphocytes. We identified that out of nine genes encoding TJ components, six were significantly upregulated by exposure to shear stress, including \u003cem\u003eCLDN, JAM1, JAM3, ESAM, PECAM1\u003c/em\u003e, and \u003cem\u003eCD99\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Analysis of differentially expressed miRNAs identified that hsa-miR-625-5p, which targets CLDN, and has-miR-154-5p, which targets \u003cem\u003eJAM3\u003c/em\u003e, are significantly expressed in brain ECs subjected to shear stress (Table\u0026nbsp;1) (Supplementary Tables S4, S5, and S6). Shear stress also affected the complement and coagulation cascade, with upregulation of \u003cem\u003eJAM1, CD40, and PECAM1\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD shows genes involved in the leucocyte transmigration pathway. \u003cem\u003eICAM-1\u003c/em\u003e was upregulated by shear stress, and is targeted by hsa-miR-431-5p. PVR, which was also upregulated by shear stress, is targeted by hsa-miR-193a-5p (Table\u0026nbsp;1) (Supplementary Tables S4, S5 and S6). We then evaluated the CxC subfamily pathway, in which seven genes were upregulated by shear stress in brain ECs, including \u003cem\u003eCXCL1, CXCL8, CXCL8, CXCL16, CXCR5, and CXCR4\u003c/em\u003e, while only one gene, \u003cem\u003eCXCR7\u003c/em\u003e, was downregulated. miRNA target analysis identified that both hsa-miR-493-5p and hsa-miR-889-3p target \u003cem\u003eCXCL8\u003c/em\u003e, while hsa-654-5p targets \u003cem\u003eCXCL16\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003cb\u003emRNA and miRNA profiles of HBMECs exposed to iRBCs under physiological shear stress.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe initial molecular response of ECs to malaria infection remains incompletely understood. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA shows a heatmap comparing the miRNA profiles of HBMECs exposed to shear stress and incubated with ring-stage iRBCs (HBMEC\u003csup\u003e1.5+Rings\u003c/sup\u003e) HBMECs exposed to shear stress and co-incubated with non-infected RBCs (HBMEC\u003csup\u003e1.5+RBCs\u003c/sup\u003e) were used. Considering only mature miRNAs, three miRNAs were significantly downregulated and three miRNAs were upregulated under these conditions. Analysis of miRNA isomers identified 33 miRNA candidates significantly upregulated by exposure to iRBCs and 18 candidate miRNAs significantly downregulated (HBMEC\u003csup\u003e1.5+Rings\u003c/sup\u003e relative to HBMEC\u003csup\u003e1.5+RBCs\u003c/sup\u003e) (Supplementary Table S7). Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB-I shows the top miRNAs that are significantly expressed as a response to the HBMEC\u003csup\u003e1.5+Rings\u003c/sup\u003e. The mRNA target showed that miRNAs regulating the endocytosis, TNF signalling, NF-Kappa B and cytokine-cytokine receptor interaction pathways were affected by iRBC exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eJ).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA shows the endocytosis pathway, with genes upregulated by iRBC exposure indicated in red, downregulated genes indicated in green, and unaffected genes indicated in blue, as demonstrated by mRNA-sequencing analysis. Endocytosis is the cellular process by which substances are taken into cells. The material to be internalized is surrounded by an area of the cell membrane, which then buds off inside the cell to form a vesicle containing the material that has been taken up. Endocytosis is a form of intracellular active substance transport. Endocytic pathways fall into four major categories: receptor-mediated endocytosis (or clathrin-dependent endocytosis), caveolae, pinocytosis, and phagocytosis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThirteen genes encoding components of clathrin-dependent endocytosis were upregulated by exposure to iRBCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Only two genes involved in clathrin-independent endocytosis (ARF6 and MHC I) were upregulated. Genes encoding components of early endosome regulation were also upregulated (10 genes), as were genes encoding components of late endosomes and multivesicular bodies (14 genes) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, Supplementary Table S7). Immune response pathways, including the CXC subfamily, were also affected in HBMEC\u003csup\u003e1.5+Rings\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Six genes, including \u003cem\u003eCXCL1, CXCL6, CXCL8\u003c/em\u003e, \u003cem\u003eCXCL3, CXCL2 and CXCR4\u003c/em\u003e were downregulated in HBMEC\u003csup\u003e1.5+Rings\u003c/sup\u003e, while only \u003cem\u003eCXCL12\u003c/em\u003e was upregulated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEffect of shear stress on HMVEC-Ls miRNA and mRNA profiles\u003c/h2\u003e \u003cp\u003eWe investigated the effects of shear stress on HMVEC-L cells by applying shear stress of 1.5 dyne/cm2. A total of 1174 genes were significantly regulated when we compared the cells exposed to shear stress to those that were cultivated under static conditions (Supplementary Table S8). One of the main pathways that were stimulated due to shear stress was Interleukin 10 signaling (high expression of \u003cem\u003eICAM-1, CXCL2, IL6, CXCL8, PTGS2\u003c/em\u003e, and \u003cem\u003eCXCL3\u003c/em\u003e). Also, both Interleukin 4 and 13 signaling pathways were also turned on. Adding to this some of the genes in the potassium channel pathway were downregulated (\u003cem\u003eKCNN2, KCNJ8, KCND2\u003c/em\u003e and \u003cem\u003eKCNK2\u003c/em\u003e) (Supplementary Table S8). In contrast to the brain ECs, the tight junction genes were not affected by shear stress in the lung ECs. In the miRNA profile of the HMVEC-L cells, only 12 isomiRs were significantly regulated. The following candidates were highly regulated: hsa-miR-4797-3p, hsa-miR-4670-3p, hsa-miR-6813-3p, has-miR-1286, hsa-miR-6828-5p, hsa-miR-7154-3p, hsa-miR-2467-3p and hsa-miR-4661-5p. On the other hand, the following isomiRs\u003c/p\u003e \u003cp\u003ewere downregulated: hsa-miR-555, hsa-miR-6873-5p, hsa-miR-4725-5p and hsa-miR-6792-5p.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003emRNA and miRNA profiles of HMVEC-Ls exposed to iRBCs under shear stress\u003c/h2\u003e \u003cp\u003eTo determine how lung ECs are affected by the presence of malaria parasites, we incubated lung ECs with infected or uninfected RBCs under shear stress conditions (HMVEC-L\u003csup\u003e1.5+RBCs\u003c/sup\u003e vs. HMVEC-L\u003csup\u003e1.5+Rings\u003c/sup\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA shows a heat map of miRNAs differentially expressed in HMVEC-L\u003csup\u003e1.5+Rings\u003c/sup\u003e cells relative to HMVEC-L\u003csup\u003e1.5+RBCs\u003c/sup\u003e cells. Eighteen mature miRNAs were significantly upregulated and 36 mature miRNAs were significantly downregulated in HMVEC-L\u003csup\u003e1.5+Rings\u003c/sup\u003e relative to HMVEC-L\u003csup\u003e1.5+RBCs\u003c/sup\u003e. Among isomiRs, 219 miRNAs were differentially expressed in HMVEC-\u003csup\u003eL1.5+Rings\u003c/sup\u003e relative to HMVEC-L\u003csup\u003e1.5+RBCs\u003c/sup\u003e, with 126 miRNAs upregulated and 93 miRNAS downregulated (Supplementary Table S9). The miRNAs were then strictly filtered to the nine most significantly affected miRNAs (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB-J). We used predictive modelling to identify the target genes of differentially expressed miRNAs (Supplementary Table S10).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePathway analysis of mRNA-sequencing data identified that the primary gene set differentially expressed in HMVEC-L\u003csup\u003e1.5+Rings\u003c/sup\u003e relative to HMVEC-L\u003csup\u003e1.5+RBCs\u003c/sup\u003e was the electron transport chain (ETC) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ek). Out of 35 genes in the ETC pathway, 30 genes were upregulated in HMVEC-L\u003csup\u003e1.5+Rings\u003c/sup\u003e relative to HMVEC-L\u003csup\u003e1.5+RBCs\u003c/sup\u003e. A recent study reported that the ETC plays a role in immune cell activation, proliferation, and differentiation [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Supplementary Table S10 shows miRNA candidates that target genes in the ETC pathway.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHow fever (40\u0026deg;C) affects the mRNA and miRNA profiles of HBMEC and HMVEC-Ls under shear stress\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe brain ECs reacted to fever by highly regulating 97 genes that are involved mainly in the regulation of the HSF1-mediated heat shock response pathway and the cellular response to heat stress pathway (Supplementary Table S11). In addition, 59 genes were downregulated in response to heat stress. Those were involved mainly in the interferon Alpha, beta, and gamma signaling pathways. The miRNA profiles of those cells showed a down-regulation of about 300 mature miRNAs in response to fever, in addition to significant regulation of 225 isomiRs (Supplementary Table S11). IPA miRNA target filter analyses showed that the affected miRNAs and isomiRs target mostly the above-mentioned genes within the mRNA profile (Supplementary Table S11).\u003c/p\u003e \u003cp\u003eConsidering the Lung ECs, they reacted to fever by regulating 169 genes involved mainly in the cellular response to stress pathways (Supplementary Table S12). The miRNA profiles of those cells only 8 isomiRs that reacted to fever. hsa-miR-4442, hsa-miR-6814-5p, hsa-miR-3197, hsa-miR-4501, hsa-miR-491-3p and hsa-miR-3135a were significantly downregulated. On the other hand, hsa-miR-3606-3p and hsa-miR-520a-5p were highly significantly regulated.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study investigated the initial response of host ECs to malaria infection. Recent studies have identified significant innate immune functions of ECs, including cytokine secretion, phagocytosis, and antigen presentation [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. ECs can also detect pathogen-associated molecular patterns and damage-associated molecular patterns (DAMPs) and elicit pro-inflammatory immune-enhancing responses and anti-inflammatory immunosuppressive responses [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eBrain EC-specific alterations in miRNA/mRNA profiles in response to shear stress and infectious stimuli\u003c/h2\u003e \u003cp\u003eOur findings demonstrate that a subset of microRNAs are highly expressed in brain ECs and their secreted EVs under normal static conditions. This miRNA set was affected by shear stress and malaria infection stimuli.\u003c/p\u003e \u003cp\u003eShear stress of 1.5 dyne/cm\u003csup\u003e2\u003c/sup\u003e, which is similar to that of physiological shear stress in microvessels, significantly altered expression of 18 miRNA candidates significantly, including miR-196b-5p,-224-5p,-369-5p, -411-5p, -127-3p, -100-5p, -379-5p, -204-5p, -199a-3p, -99a-5p, -652-5p,-154-5p, -431-5p, -193-5p, -654-5p,-493-5p, -889-3p and \u0026minus;\u0026thinsp;181a-2-3p. A prior study reported six mechano-sensitive endothelial miRNAs, including hsa‐miR‐8060,‐4534,‐630,‐5703, 1587,‐1268a and ‐4788,197‐5p [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. However, these miRNAs were not affected by shear stress in the present study. This could be because the investigators subjected ECs to higher shear levels (4 dyne/cm\u003csup\u003e2\u003c/sup\u003e and 100 dyne/cm\u003csup\u003e2\u003c/sup\u003e) than that used in the present study (1.5 dyne/cm\u003csup\u003e2\u003c/sup\u003e), which is similar to physiological shear stress in microvessels. This highlights the potential roles of other miRNAs that will be investigated in our future studies.\u003c/p\u003e \u003cp\u003eConsistent with our findings, prior studies have demonstrated that shear stress decreases expression of mechanosensitive miR-181b-5p, which suppresses NLRP3 inflammasome-dependent pyroptosis. Clinical data are also consistent with this notion, revealing that miR-181b acts in combination with the lncRNA ANRIL to mediate NF-κB signalling [\u003cspan additionalcitationids=\"CR49 CR50\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe demonstrated that shear stress increased expression of genes encoding TJ components in brain ECs, which are likely targeted by miR-625-5p and \u0026minus;\u0026thinsp;154-5p. These results are consistent with a recent study demonstrating that laminar flow protects vascular endothelial junctions [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. We also found that shear stress upregulated CXCL1,8,2,3, and 16 in brain ECs. These genes were likely targeted by hsa-miR-493-5p, -889-3p and 654-5p, consistent with a prior study from Shaik et al. reporting that exposure to shear stress increases EC secretion of CXC chemokines [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eExposure to parasite-infected RBCs altered expression of eight miRNAs in brain ECs, including miR-4509, -142-5p,-144-3p, -342-3p, -497-5p, -103b, -4485-3p, and \u0026minus;\u0026thinsp;4289. A prior study analysed EV miRNA profiles in EVs mice infected with \u003cem\u003ePlasmodium ANKA\u003c/em\u003e and \u003cem\u003eP. yoelii\u003c/em\u003e. The study identified high levels of miR-146a and miR-193b in EVs from cerebral malaria-infected mice compared with EVs from non-cerebral malaria-infected mice and non-infected mice [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Additional studies demonstrated altered expression of 12 miRNAs, including miR-21-5p,-18a-5p,-19a-3p, -20b-5p, -142-3p, -27a-5p, -152-3p, -193a-5p, -155-5p,-218-1-3p, -543, and \u0026minus;\u0026thinsp;411-5p, in mice with CM compared with mice with non-CM. These miRNAs are significantly involved in some cerebral malaria-like adherens junctions and the FoxO, TGF-β, and endocytosis pathways [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Brain miR-27a, miR-150 and let7i are upregulated in \u003cem\u003ePlasmodium berghei\u003c/em\u003e-infected mice, which develop CM, in comparison to mice with non-CM and uninfected mice [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. A prior study of a human patient demonstrated that whole blood miR-150-5p was downregulated in an adult infected with \u003cem\u003eP. vivax\u003c/em\u003e [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Contrastingly, in the present study, we identified that a miR-150-5p isomiR was significantly upregulated in brain ECs exposed to iRBCs. Consistent with our findings, a prior study identified upregulation of miR-150-5p in plasma-derived EVs from patients infected with \u003cem\u003eP. vivax\u003c/em\u003e [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eActivation of the endocytosis pathway in brain ECs exposed to iRBCs\u003c/h2\u003e \u003cp\u003eWe previously demonstrated that iRBCs secrete miRNA-containing EVs [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] that are presumably taken up by recipient cells, in which cargo miRNAs suppress gene expression. Activation of the endocytosis pathway identified in the present study could indicate EV uptake in brain ECs. EVs are generally internalized into recipient cells by clathrin-dependent endocytosis, which was also increased in brain ECs exposed to iRBCs [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe endocytic system consists primarily of clathrin-containing endocytic vesicles, early and late endosomes. However, clathrin-independent endocytosis, which is less-characterized, also occurs in ECs. The clathrin-dependent pathway is responsible for transporting transferrin in brain ECs. Clathrin-coated buds are localized to the central zone of ECs, with well-developed necks, in contrast to clathrin-coated dome-shaped invaginations on the PM. ECs likely use both clathrin-dependent and clathrin-independent endocytosis pathways. After budding, clathrin-dependent endocytic vesicles fuse with one another or pre-existing early endosomes, causing the vesicles to split and release their coating. The majority of lipid and protein vesicle components destined for recycling to the PM accumulate in the vacuolar head, while soluble contents are concentrated in vesicular regions due to their larger fractional volume [\u003cspan additionalcitationids=\"CR61\" citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eLung EC-specific alterations in miRNA /mRNA profiles in response to iRBC exposure\u003c/h2\u003e \u003cp\u003eSevere malaria is associated with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). The human host responds to infection by initiating a complex inflammatory response in the lungs. This includes cytokine production, neutrophil activation and macrophage activation. Permeability of the alveolar capillary membrane subsequently increases, causing ventilation perfusion mismatch and oedematous lung. These interactions compromise lung function [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo our knowledge, we present for the first time, the acute response of lung ECs to initial stimulation with iRBCs under physiological shear stress. We identified that co-incubation with iRBCs prominently increased expression of genes encoding ETC components in lung ECs. The ETC consists of multimeric protein complexes I\u0026ndash;IV, on the inner mitochondrial membrane. Complex I generates reactive oxygen species (ROS), and recent studies have identified critical roles for this interaction in inflammatory macrophages and T helper 17 cells (TH17). Complex II is the site of reverse electron transport in inflammatory macrophages and regulates fumarate levels, which are linked to epigenetic changes. Complex III also produces ROS that activate hypoxia-inducible factor 1-alpha (HIF-1α) and contribute to regulatory T cell (Treg) function. Complex IV is required for T cell activation, differentiation, and Treg subset development. Complex V is required for TH17 differentiation and is sometimes expressed on the surface of tumor cells, where it is recognized by anti-tumor T and NK cells [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e \u003cp\u003emiRNA expression profiling identified that miR126 was significantly upregulated in lung ECs exposed to iRBCs under physiological shear stress conditions. miR126 is a well-established pro-angiogenic, pro-survival, and reparative master regulator of ECs lining the extensive pulmonary and systemic vasculature [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. miR126 inhibits the migration, proliferation, and survival of human lung microvascular ECs [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTogether, the findings presented here newly reveal tissue-specific acute responses of brain and lung ECs stimulated by iRBCs. These findings lay the groundwork for further studies investigating the EC micromechanics that regulate malaria pathogenesis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eEndothelial cell culture\u003c/h2\u003e \u003cp\u003ePrimary endothelial cells: HBMEC (brain ECs) (Cell Biologics\u0026reg;- # H-6023) cultivated in complete human endothelial cell kit (Cell Biologics\u0026reg;- #H1168) according to Cell Biologics\u0026reg; guidelines. HMVEC-L (lung ECs) (Provitro\u0026reg;- #1210144) cultivated in microvascular endothelial cell growth medium (Provitro\u0026reg;- #2010102) according to Provitro\u0026reg; guidelines.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cb\u003ePlasmodium\u003c/b\u003e \u003cb\u003eculture\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eP. falciparum\u003c/em\u003e isolate IT4/FCR3S1.2 (long-term laboratory adapted), cultivated in RPMI medium with 10% human serum (A+) and 5% hematocrit (0+). The culture was incubated at 37\u0026deg;C in 5% CO2, 1% O2, and 94% N2. Medium was changed daily, and the culture was split according to the experiments\u0026rsquo; requirements [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Gelatine flotation was used on the day of flow experiments to isolate \u003cem\u003eP. falciparum\u003c/em\u003e knobby iRBCs. iRBCs must be highly synchronized (ring/trophozoite/schizont stage). Gelatine flotation [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] is used to select the trophozoite/schizont stages on the day of assay or 1 day before the assay to obtain synchronized ring stages iRBCs. On the day of assay, the ring-stage iRBCs were resuspended in 1 mL serum-free RMPI medium to estimate the cell count.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eMicrofluidic pump and shear stress application\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAs we published previously [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e], the following steps were performed. A total of 2x10\u003csup\u003e5\u003c/sup\u003e ECs in one laminar flow slide were seeded 2 days before the assay. ECs were left to adhere for about 2 h. Then 14 mL of ECs culture medium was added into the fluidic unit. One day before the assay, the perfusion set was connected and then air bubbles were removed from the system. The flow was then started with shear stress 1.5 dyne/cm\u003csup\u003e2\u003c/sup\u003e. The fluidic unit and slides were then incubated at 37\u0026deg;C for at least 24 h. On the day of the assay, the medium was then changed to serum-free RPMI medium. Then a total of 2 x 10\u003csup\u003e7\u003c/sup\u003e highly synchronized iRBCs were transferred to the fluidic unit. As a control, RBCS was used in a separate fluidic unit. After the 8 h co-incubation the experiment was stopped. The ECs were then washed with PBS (Phosphate buffer solution) and add detached with 200 \u0026micro;L Accutase\u0026trade;. The ECs were then collected using serum-free medium and then 500\u0026micro;L TRIzol\u0026trade;, was added to the pellet and keept at 80\u0026deg;C until further isolation of RNA/miRNA.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eEVs purification\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eECs-EVs were isolated from cell culture with as previously described [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. In brief, the medium was changed to vesicle depleted ECs medium (depletion was done by centrifugation at 100,000 x g for 18 hrs at 4\u0026deg;C). On the next day, (24 h after changing the medium), the cell culture supernatants (15 ml/ T75 flask) were collected and sequentially centrifuged at 600 x g, 1600 x g, 3600 x g and 10,000 x g for 15 min each. After each step, the respective supernatant was collected for the next centrifugation step. To concentrate the EVs, the suspension was passed through ultrafiltration units (100,000 MWCO PES; Sartorius, G\u0026ouml;ttingen, Germany) for 30 min at 3000 x g. The EVs contained in the concentrated supernatant were dissolved in PBS, layered on top of a 60% sucrose cushion, and centrifuged at 100,000 g for 16 h at 4\u0026deg;C. The interphase was collected and washed with PBS twice at 100,000 x g for 60 min at 4\u0026deg;C. EVs were resuspended and pooled in 1000 \u0026micro;L PBS (0.2 \u0026micro;m filtered) and stored in 200 \u0026micro;L aliquots at -80\u0026deg;C. Protein concentration of EV samples was determined using the QUBIT Protein Assay Kit (ThermoFisher Scientific, Waltham, USA) according to manufacturer\u0026rsquo;s instructions and by measuring the A\u003csub\u003e280\u003c/sub\u003e content on a Nanodrop2000 (ThermoFisher Scientific, Waltham, USA).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eElectron microscopy\u003c/h2\u003e \u003cp\u003eGlow-discharged carbon- and formvar-coated nickel grids (Plano GmbH, Wetzlar, Germany) were incubated with aliquots of freshly isolated EVs. After washing with PBS and incubation in the blocking buffer (0.5% BSA in PBS), the EVs on the grids were labelled with the primary antibody (α human CD29 (integrin beta1), Biolegend, San Diego, USA) at a concentration of 1:100 v/v in PBS (PAA-Laboratories GmbH, Pasching, Austria) containing 0.5% BSA (Sigma-Aldrich, Steinheim, Germany) for at least 21 h at 4\u0026deg;C. The controls for antibody specificity included omitting the primary antibody from the incubating solution. After the incubation period, the grids were rinsed in buffer and further incubated with a goat-anti-mouse colloidal gold-conjugated secondary antibody (12 nm gold particles from Jackson Immuno Research, Cambridgeshire, UK) at a dilution of 1:100 v/v for at least 21 h at 4\u0026deg;C. Nickel grids were rinsed in buffer and stained with 2% aqueous uranyl acetate (Electron Microscopy Sciences, Hatfield, USA) for 15 sec. Grids were finally observed under a Tecnai Spirit electron microscope (Thermo Fisher Scientific, Waltham, USA) operating at 80 kV, and images were recorded with a digital CCD camera.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eNanoparticle tracking analysis (NTA) with Nanosight LM10\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe pellet of purified EVs was diluted 1:300 in PBS. The following settings were set according to the manufacturer\u0026rsquo;s software manual (NanoSight LM10 User Manual, MAN0510-04-EN, 2015): the camera level was increased until all particles were distinctly visible (level16 and gain\u0026thinsp;=\u0026thinsp;20). A total number of 900 frames was recorded in each session (camera: CCD). The autofocus was adjusted to avoid indistinct particles. For each measurement, five 1-min videos were captured under the following conditions: cell temperature: 25\u0026deg;C; Frame rate/FBS: 30. After capture, the videos were analysed by the in-build NanoSight Software (NTA3 0064) with a detection threshold of 6 and screen gain of 10.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eImmunofluorescence assays\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eECs were seeded on glass slides. The slides with ECs monolayers were fixed in acetone for 30 min and then rehydrated with 1x PBS for 5 min. The first antibody (1:50 in 3% BSA/PBS; α human CD29 (mouse monoclonal), CBL-162, MM2-57, Millipore) was then added and the slides were incubated for one hour in a humid dark box. The smears were washed 5x with 1X PBS and then labelled with AlexaFluor (1:1000) (Thermo Fisher # A28175) and DAPI (1mg/ml) (1:1000) (Roche # 10236276001) for 1 h in a humid dark box. After a 5x wash with 50 \u0026micro;l 1x PBS, the smears were air dried and Moviol was added before they were covered with a plastic cover slip. Images were taken through a EVOS FL auto-inverted microscope (Thermo Fisher Scientific, Waltham, USA) and analysed using ImageJ 1.53K. To calculate the corrected total cell fluorescence (CTCF), the following formula was used: Integrated Density \u0026ndash; (Area of selected cell X Mean fluorescence of background readings).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003emRNA purification and sequencing\u003c/h2\u003e \u003cp\u003eSamples in Trizol were thawed before adding 200 \u0026micro;l chloroform and centrifugation for 30 min at 4\u0026deg;C and 800 x g. The miRNeasy mini-Kit- (Qiagen, Hilden, Germany) was used according to the manufacturer\u0026rsquo;s instructions. The quality of mRNA/miRNA was assessed using the Agilent 2100\u0026reg; bioanalyzer system. According to the manufacturer\u0026rsquo;s instructions, Ribosomal RNA was removed using QIAseq FastSelect RNA Removal Kit. The QIAseq Stranded mRNA Select Kit was used for mRNA enrichment. mRNA was sequenced using NextSeq 500/550 Mid Output Kit v2.5 (150 Cycles).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003emiRNA purification and sequencing\u003c/h2\u003e \u003cp\u003eSamples in Trizol were thawed before adding 140 \u0026micro;l chloroform and centrifugation for 15 min at 4\u0026deg;C and 800 x g. The miRNeasy mini-Kit- (Qiagen, Hilden, Germany) was used according to the manufacturer\u0026rsquo;s instructions. The quality of mRNA/miRNA was assessed using the Agilent 2100\u0026reg; bioanalyzer system. miRNA library preparation was performed in BGI Genomics - China. The small RNAs (18\u0026ndash;30 nucleotides) were purified by PAGE. For adapter ligation, the purified RNA was incubated with 3\u0026rsquo; adapter followed by the 5\u0026rsquo; adapter. Reverse transcription PCR was then performed, and the PCR product was purified by PAGE. After denaturation and circularizing the DNA product, single-stranded circular DNA molecules were replicated via rolling cycle amplification, and a DNA nanoball (DNB) containing multiple copies of DNA was generated. DNBseq-UMI was then performed and about 18 M reads were generated per sample. UMI is known to correct the quantitative bias caused by PCR amplification of more than 70% small RNAs.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e\u0026bull; DATA ANALYSIS\u003c/h2\u003e \u003cp\u003eBioinformatics analysis was conducted using CLC genomics work bench version 21 (Qiagen, Aarhus). Clean reads were imported, and miRNA was quantified and annotated on the miRbase v22. Differential expression was performed, and P-values were adjusted using FDR 10%. miRNAs with extremely low abundance were excluded from our analysis.\u003c/p\u003e \u003cp\u003eHsg38 was used as a mRNA reference.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eCLC Parameters(miRNA-Quantification):\u003c/h2\u003e \u003cp\u003emiRBase: miRBase-Release_v22 / Prioritized species\u0026thinsp;=\u0026thinsp;Homo sapiens / Allow length based isomiRs\u0026thinsp;=\u0026thinsp;Yes / Additional upstream bases\u0026thinsp;=\u0026thinsp;2 / Maximum mismatches\u0026thinsp;=\u0026thinsp;2 / Strand specific\u0026thinsp;=\u0026thinsp;Yes / Minimum sequence length\u0026thinsp;=\u0026thinsp;18 / Maximum sequence length\u0026thinsp;=\u0026thinsp;25\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eCLC differential expression Parameters (miRNA/mRNA):\u003c/h2\u003e \u003cp\u003eWhole transcriptome RNA-seq / Normalization Method\u0026thinsp;=\u0026thinsp;TMM / Filter on Average expression for FDR correction / Result Handling\u0026thinsp;=\u0026thinsp;Save\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCLC Trim Parameters (mRNA):\u003c/h3\u003e\n\u003cp\u003eTrim using quality scores\u0026thinsp;=\u0026thinsp;Yes / Quality limit\u0026thinsp;=\u0026thinsp;0.05 / Trim ambiguous nucleotides\u0026thinsp;=\u0026thinsp;Yes / Maximum number of ambiguities\u0026thinsp;=\u0026thinsp;2 / Automatic read-through adapter trimming\u0026thinsp;=\u0026thinsp;Yes / Remove 5' terminal nucleotides\u0026thinsp;=\u0026thinsp;No / Remove 3' terminal nucleotides\u0026thinsp;=\u0026thinsp;No / Trim to a fixed length\u0026thinsp;=\u0026thinsp;No / Maximum length\u0026thinsp;=\u0026thinsp;150 / Trim end\u0026thinsp;=\u0026thinsp;Trim from 3'-end / Discard short reads\u0026thinsp;=\u0026thinsp;No / Discard long reads\u0026thinsp;=\u0026thinsp;No / Save discarded sequences\u0026thinsp;=\u0026thinsp;No / Save broken pairs\u0026thinsp;=\u0026thinsp;No / Create report\u0026thinsp;=\u0026thinsp;Yes\u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eCLC RNA-seq Parameters (mRNA):\u003c/h2\u003e \u003cp\u003eEnable spike-ins\u0026thinsp;=\u0026thinsp;No / Database files\u0026thinsp;=\u0026thinsp;Homo sapiens (hg38) sequence / Maximum cost\u0026thinsp;=\u0026thinsp;2 / Similarity fraction\u0026thinsp;=\u0026thinsp;0.8 / Auto-detect paired distances\u0026thinsp;=\u0026thinsp;Yes / Maximum number of hits for a read\u0026thinsp;=\u0026thinsp;10 / Strand setting\u0026thinsp;=\u0026thinsp;Both / Minimum supporting count\u0026thinsp;=\u0026thinsp;5 / Create report\u0026thinsp;=\u0026thinsp;Yes / Unmapped reads\u0026thinsp;=\u0026thinsp;No / Expression value\u0026thinsp;=\u0026thinsp;Total count\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003eIPA miRNA target identification parameters:\u003c/h2\u003e \u003cp\u003eQIAGEN Ingenuity Pathway Analysis Software, copyright 2023, was utilized for miRNA target filtration and canonical pathway analysis. This software is web-based and gathers information from publicly available databases containing published relationships, mechanisms, biological functions, canonical pathways, and networks. IPA predicts miRNA regulation of target mRNAs based on data from miRBase, TargetScan, and the QIAGEN Knowledge Base. The filters were based on high-confidence predicted and experimentally validated data only. The included canonical pathways were cellular immune responses, cytokine signaling, and pathogen-influenced signaling.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData and code availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA-sequencing data has been deposited to\u0026nbsp;NCBI\u0026nbsp;and will be publicly available as of the date of publication.\u0026nbsp;The\u0026nbsp;bioproject number is\u0026nbsp;PRJNA1066103. All other original data reported in the paper will be made available by the lead contact upon reasonable request. This paper does not report original code. Any additional information required to re-interrogate the data reported in this paper is available from the lead contact upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, N.G.M., methodology, M.P.M.T.; H.T.; J.A., S.M., M.B., P.B, Y.W., T. S.; K.H.; and N.G.M, software, N.G.M.; validation, K.H.; B.H.; and N.G.M, formal analysis, N.G.M., writing, original draft preparation, N.G.M; review, and editing, M.P.M.T.; H.T.; B.H.; H.H.; I.B.; and N.G.M. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Prof. Egbert Tannich (BNITM) for substantial support at the beginning of the project also special thanks to Dr. Daniel Cadar and Heike Baum (BNITM) for support with NGS sequencing. We also thank Mohsin Shafiq (Institute for Neuropathology, Medical center Hamburg-Eppendorf-Germany) for help and support with Nanosight measurements. We extend special thanks to Monika Rottstegge for the help with the IPA license.\u003c/p\u003e\n\u003cp\u003eThis work was supported by Leibniz Center Infection, J\u0026uuml;rgen Manchot Stiftung and German research foundation (BR 1744/20-1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion and diversity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne or more of the authors of this paper self-identifies as an underrepresented ethnic minority in their field of research or within their geographical location.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eIppolito MM, Moser KA, Kabuya JB, Cunningham C, Juliano JJ (2021) Antimalarial Drug Resistance and Implications for the WHO Global Technical Strategy. 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Sci Rep 10(1):4548. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-020-61388-2\u003c/span\u003e\u003cspan address=\"10.1038/s41598-020-61388-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003ePMID: 32161335; PMCID: PMC7066226\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMantel PY, Hoang AN, Goldowitz I, Potashnikova D, Hamza B, Vorobjev I, Ghiran I, Toner M, Irimia D, Ivanov AR et al (2013) Malaria-infected erythrocytederived microvesicles mediate cellular communication within the parasite population and with the host immune system\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Brain endothelial cells, lung endothelial cells, miRNA, mRNA, NGS, shear stress, endocytosis, malaria","lastPublishedDoi":"10.21203/rs.3.rs-4222036/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4222036/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMicroRNAs (miRNAs) control 60% of genes expressed in the human body, but their role in malaria pathogenesis is incompletely understood. For the first time, we demonstrate cell type-specific alterations to the miRNA profiles during the early response to malaria infection in brain and lung endothelial cells (ECs). In brain ECs, incubation with \u003cem\u003ePlasmodium falciparum\u003c/em\u003e-infected red blood cells in the ring stage (iRBCs) most significantly affected endocytosis-related miRNAs and mRNAs. Contrastingly, in lung ECs, iRBCs altered electron transport chain-related miRNAs and mRNAs. We also present a novel dataset of inherent differences between microRNA profiles in brain and lung ECs and their secreted extracellular vesicles (EVs). We demonstrated that shear stress affected multiple pathways in brain ECs, which were controlled by numerous human miRNAs. Together, these findings demonstrate that host miRNAs respond to parasite exposure; this is accompanied by stimulation of downstream signaling pathways within the ECs. Therefore, we consider miRNAs to be the initial spark (Code of duty) for the early host-parasite interaction events.\u003c/p\u003e","manuscriptTitle":"Tissue-specific responses of brain and lung endothelial cell miRNA and mRNA profiles to the ring-stage Plasmodium falciparum-infected red blood cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-08 04:58:56","doi":"10.21203/rs.3.rs-4222036/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eb67eba3-fa80-4c9b-8ff0-2cb2030e2350","owner":[],"postedDate":"April 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":30314084,"name":"Health sciences/Pathogenesis/Infection"},{"id":30314085,"name":"Biological sciences/Microbiology/Parasitology/Parasite host response"}],"tags":[],"updatedAt":"2024-04-24T15:16:26+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-08 04:58:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4222036","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4222036","identity":"rs-4222036","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}