Midgut cell atlas and virome of four important mosquito species and immune landscapes of dengue virus infection

Midgut cell atlas and virome of four important mosquito species and immune landscapes of dengue virus infection | 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 Resource Midgut cell atlas and virome of four important mosquito species and immune landscapes of dengue virus infection Han Xia, Shunlong Wang, Ying Huang, Xiaoyu Wang, Qun Wu, Wahid Zaman, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7214530/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 Mosquitoes are the most important arthropod vectors of human diseases globally, with their midgut serving as both a digestive organ and the primary site of viral infection. Single-cell RNA sequencing (scRNA-seq) studies in insects, including mosquitoes, remain limited due to the absence of established protocols. Here, we fill this gap by developing a compatible microwell-based scRNA-seq workflow, and generated midgut cell atlas and virome for four important mosquito species: Aedes aegypti, Aedes albopictus, Culex pipiens pallens and Culex tritaeniorhynchus. Eight distinct cell types were identified, and the cell composition was inter-generic conserved in types but divergent in proportions. Culex mosquitoes exhibited higher proportions of intestinal stem cells/enteroblasts (ISC/EBs) than Aedes mosquitoes. In response to dengue virus 2 (DENV-2) infection, stress-associated genes were broadly downregulated, whereas endoenterocytes (EEs) and ISC/EBs showed marked upregulation of diverse immune related genes. Notably, we identified a novel midgut cell cluster (termed SV2/UNC-93) characterized by high expression of synaptic vesicle protein-2 and UNC-93, along with broad upregulation of apical-basal polarity-related genes linked to viral infection. The midguts of Aedes and Culex mosquitoes harbored diverse virome belonging to 5 viral families and one unclassified group. Hanko iflavirus 1 (HKIFV1) was the most common virus, distributed in all four mosquito species, while Tiger mosquito bi-segmented tombus-like virus (TMBSTLV) was the most abundant virus in Ae. albopictus and exhibited strong tropism in hemocytes. DENV-2 only detected in experimental infected Ae. aegypti, with no obvious midgut cell tropism but highest viral reads occurred in enterocytes (ECs) and EEs.Our study provides fundamental insights into the cellular composition of these four medically important mosquitoes and facilitate future research on virus-midgut interactions. Biological sciences/Biological techniques/Sequencing/RNA sequencing Biological sciences/Zoology Biological sciences/Microbiology/Virology/Virus–host interactions Mosquito Aedes aegypti Aedes albopictus Culex pipiens pallens Culex tritaeniorhynchus dengue virus scRNA-seq midgut virome Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Mosquitoes (Culicidae) are the most important hematophagous arthropods in the world 1,2 . Mosquito-borne viruses (MBVs) caused millions of infection cases annually, posing severe threat to global public health 1 . The Family Culicidae consists of several genera, including Aedes , Culex , and Anopheles , with the former two being the major vectors for transmitting various mosquito-borne viral diseases (MBDs) 3,4 . Among these, Ae. aegypti is the major species that transmits MBVs including Dengue (DENV), Zika (ZIKV) and Chikungunya virus in tropical regions 5 . With the influence of the climate warming, Ae. aegypti has the potential to expand its range into colder regions, thereby may lead to more severe situation 6,7 . Similarly, Ae. albopictus is cable to carry MBVs in temperate regions, including Europe and Asia 8,9 , further extending the region of these diseases. In addition, Cx. tritaeniorhynchus is the primary vector of Japanese encephalitis virus (JEV) from temperate Asia to Europe 10,11 . Cx. pipiens pallens is the most common mosquito in human habitations across the temperate Northern Hemisphere and serves as the vector of West Nile virus (WNV), Usutu virus (USUV), and JEV 12–14 . Upon ingesting an infectious viral blood meal, viruses can infect midgut, hemocyte, fat body and salivary gland of the mosquitoes, then can be transmitted to hosts through subsequent blood feeding. The midgut is the initial infection site and forms two infection barriers that impact viral pathogenesis 15 . In addition to its roles in food digestion and nutrition absorption, midgut also participates in many physiological processes such as epithelium replenishment, signaling regulation, microbial shaping, and immune reactions 16,17 . Moreover, the various cell types exhibit differential proviral or antiviral effects, highlighting the cell-specific tropism of MBVs 18,19 . Rapidly developed single-cell RNA sequencing (scRNA-seq) technologies make it possible to reveal transcriptomic heterogeneity at single-cell level 20 . Currently, scRNA-seq technologies are primarily categorized into microfluidic-based and microwell-based methods, both of which have been well-established in mammalian cell studies, demonstrating their robustness and reliability 21–24 . Accumulating evidence has highlighted the potential of scRNA-seq in identifying cell subtypes and annotating virus-infected mosquitoes 25–27 . This technology has enabled researchers to dissect the complex cellular landscapes of mosquito tissues with unprecedented resolution. To date, however, the application of scRNA-seq to mosquito midgut research remains limited to few species. Midgut cell atlases generated by scRNA-seq are only available for Ae. aegypti , Anopheles gambiae, and Cx. tarsalis 25–28 . For other medically important vector mosquitoes, such comprehensive cellular resources are still absent, representing a significant gap in our understanding of mosquito biology and vector competence. Furthermore, unlike well-established animal models, there are no relatively standardized single-cell preparation protocols for scRNA-seq workflow in insects. Variations in the in-house developed protocols across studies may lead to different data quality metrics, thereby introducing bias in cross-dataset comparisons. For instance, in the context of midgut viral infection dynamics, a scRNA-seq study on WNV-infected Cx. tarsalis demonstrated a correlation between immune gene expression levels and viral RNA loads in individual midgut cells, while another scRNA-seq investigation on Ae. aegypti revealed the transcriptomic differences among midgut cell subtypes following ZIKV infection 26,27 . Similarly, midgut cell populations in Ae. aegypti exhibited heterogeneous transcriptomes when exposed to DENV infection, however, a comprehensive understanding of the specific cell types and genes involved in the DENV-midgut interface at the cellular level is still lacking. To date, all scRNA-seq studies on mosquitoes have relied on microfluidic-base methods, yet our previous research has highlighted a notable limitation in handling low-input or low-quality samples 25 . Furthermore, emerging evidence suggests that the shear forces generated by microfluidics in RNA capture may also compromise the transcript quality 29 . In contrast, the microwell-based methods exhibited its compatibility with low-quality input samples and more efficient high-quality RNA capture 29–31 . Given the challenges in preparing high-quality single-cell suspension from mosquitoes 24 , the microwell-based methods may offer significant advantages for mosquito studies, thereby facilitating more accurate and comprehensive analyses of mosquito cell transcriptomes. In this study, we aimed to facilitate cross-species analysis by developing a compatible single-cell preparation protocol for both Aedes and Culex mosquitoes. Utilizing a microwell-based platform, we successfully established the midgut cell atlases for four important mosquito species: Ae. aegypti , Ae. albopictus , Cx. p. pallens and Cx. tritaeniorhynchus . Based on these, the DENV-2 infection dynamics in Ae. aegypti midgut at cellular level have been conducted to identify the critical cell clusters and genes associated with infection. Virome profies in the midguts of Aedes and Culex mosquito were also investigated. Our study provides fundamental insights into the cellular composition of four important mosquito species and facilitates research on virus-midgut interactions. Results The midgut cell atlases of four mosquito species To compare the cellular composition among Ae. aegypti , Ae. albopictus , Cx. p. pallens and Cx. tritaeniorhynchus , we performed scRNA-seq experiments with the midgut of glucose-fed female adults at 7 days post eclosion (dpe)(Fig. 1a). The valid cells were recovered and clustered into distinct types using Scanpy 32 . Given the limited comparative data on midgut cellular composition in diverse vector mosquitoes, we implemented a multi-faceted strategy for cell type annotation: (I) For Ae. aegypti , we used the marker genes defined by the previous studies on the midgut of Drosophila and Ae. aegypti (Supplementary Table 1). (II) For the other mosquito species, we referred the marker genes of Ae. aegypti , as well as the top unique gene in the clusters identified in this study (Supplementary Table 1). This approach ensured consistency and comparability across species. Our analysis revealed that the known midgut cell types, including intestinal stem cells (ISC), enteroblasts (EB), cardia cells, enterocytes (EC), EC-like cells, enteroendocrine cells (EE), and visceral muscle cells (VM), were conserved among the four mosquito species, except for that some of them lacked several subdivided EC-like or EE populations (Fig. 1b-e). The midgut cells of Ae. aegypti were clustered into 12 distinct cell types (Fig. 1b, f). Two ISC/EB clusters were identified using the marker gene fibulin 1 and C-type lysozyme A( LYSC11 ), with one of the clusters named ISC/EB-prol was distinguished by high expression of the gene proliferating cell nuclear antigen ( PCNA ) 27,33,34 . Cardia clusters were identified based on high expression of the antimicrobial peptides (AMPs) gene Gambicin ( GAM1 ) 33,34 . Cardia-1 was identified by enrichment for C-type lysozyme ( LYSC ) 27,33,35 . EC cluster was identified by expression of Nubbin , a key marker for mature enterocytes 33,35 . EC-like clusters are identified mainly by high expression of carbonic anhydrase 7 ( CAH7 ) and Chitinase 10 ( Cht10 ), but low expression of Nubbin , in which EC-like-3 was distinguished by high expression of sodium-dependent nutrient amino acid transporter 1 ( NAAT ) 33,34 . We further identified three EE clusters based on the expression of prospero 33,35 . The EE-1 and EE-2 cluster were distinguished by strong expression of the gene orcokinin and neuropeptide F ( NPF ), respectively 33–35 . The former gene is involved in positive regulation of oogenesis and the latter gene is involved in metabolic pathways, indicating their distinct functions in regulating the physiological activity in mosquitoes 36,37 . The EE-3 cluster was identified by exhibiting a deficiency in the expression of both of the aforementioned genes. VM cluster was identified by high expression of actin instead of titin 25,33,34 . For Ae. albopictus , the midgut cells were clustered into 10 distinct populations (Fig. 1c, f). Two ISC/EB clusters were identified by fibulin 1 alone 33,34 , yet ISC/EB-prol cluster was distinguished by high expression of PCNA 27 . We identified Cardia-1 by specific expression of GAM1 , chymotrypsin-2 ( CHYM2 ) and LYSC , while Cardia-2 was defined by high expression of GAM1 , CHYM2 33,34 . EC was identified by significant expression of Nubbin , while EC-like clusters were distinguished by high expression of CAH7 but low expression of Nubbin . VM was characterized by expression of actin . There were two EE clusters identified by Calexcitin-1 , which encoded a memory-related protein in Drosophila 38 . The EE-1 population was distinguished by enrichment for prospero , orcokinin and NPF 33–35 . Interestingly, the marker gene NAAT was highly expressed in EE-2 but lowly expressed in EC-like populations. Finally, HC population was also identified by significant high expression of LRIM16 without Nimrod B2 ( NimB2) 25,27,28,34 . In Cx. p. pallens , there are 10 annotated midgut cell clusters (Fig. 1d, f), in which ISC/EB, Cardia, EE and VM were identified by homologous marker gene consistent with those employed in Ae. aegypti . A single EE population (EE-1) was identified, which lack expression of Calexcitin-1 that is absent in Cx. p. pallens . The Cardia clusters share a common marker GAM1 , yet Cardia-1 and Cardia-2 are distinguished using the expression level of GAM1 instead of LYSC . We identified the EC cluster based on high expression of Nubbin and proton-coupled amino acid transporter protein ( CG1139 ), whose gene ortholog in Drosophila participates in both the insulin signaling pathway and hemolymph amino acids release 39 . Due to the absence of CPA-VII orthologs in Cx. p. pallens , EC-like populations were identified by significant high expression of Cht10 coupled with low expression of Nubbin . These EC-like clusters could be further refined by expression of NAAT and BTBD3 33,34 . For Cx. tritaeniorhynchus , the midgut cell populations were divided into 11 clusters (Fig. 1e, f). ISC/EB clusters were identified using significant high expression of fibulin 1 and esg , with ISC/EB-prol was distinguished by high expression of PCNA 27 . The presence of low Klu but high esg expression was observed in the ISC/EB clusters of Cx. tritaeniorhynchus, indicating the ISC/EB clusters might be composed primarily of ISCs 33–35 . EC and VM were identified by significant high expression of Nubbin and actin , respectively 25,33 . Due to the absence of GAM1 and LYSC orthologs in Cx. tritaeniorhynchus , Cardia populations were identified by high expression of CHYM2 40 . EC-like clusters were identified by significant high expression of Cht10 but low expression of Nubbin , with the absence of EC-like-2. EC-like-1 differentiated from EC-like-3 on expression of KLK7 , MAP7 and NAAT 33,34 . Since the canonical marker genes such as prospero and NPF were absent, we identified EE populations using neuropeptide CCHamide-2 ( CCHa2 ), SCG5 , CABP and FBG/G 33,35 . CCHa2 coded a sugar-sensitive peptide that could induce insulin-like peptides production and release to promote growth 41–43 . HC cluster was identified by significant high expression of NimB2 without LRIM16 27,34 . Additionally, we compared the cellular proportions of each cell populations among the mosquito species. Except for VM, other midgut cell clusters had significantly different cellular proportions between the genus Aedes and Culex (Fig. 1g). Notably, the two genera showed opposite proportions between Cardia clusters: the Culex mosquitoes have the higher percentage of Cardia-1 cells, while the Aedes mosquitoes have an approximate 5-fold higher of Cardia-2 (Fig. 1g). Both ISC/EB-1 and ISC/EB-prol clusters of Culex mosquitoes have higher proportions than that of Aedes mosquitoes (Fig. 1g). Further cross-species comparisons exhibit significant differences in the percentage of all midgut cell populations in any two mosquito species (Fig. 1h). The cluster ISC/EB-1 is more abundant in both Ae. aegypti (20.41%) and Cx. p. pallens (24.28%), while the cluster Cardia-2 and EC are the biggest cell populations in Ae. albopictus and Cx. tritaeniorhynchus , respectively (Fig. 1h). The transcriptomic features of midgut cell populations among the four mosquito species (531 words) To further elucidate the functional diversity of midgut cells across the four mosquito species, we characterized the transcriptional profiles of each cell population and compared their gene expression features among the mosquito species. This analysis was performed by integrating the single-cell transcriptomes of all mosquitoes using scvi-tools 44 . To ensure robust comparability, orthologous genes from different species were manually curated and classified to unified gene clusters, which were used as dimensional framework for the analysis (Supplementary Dataset 1). Single-cell integration revealed not only conserved cell subpopulations among different mosquito species, but also similar midgut cell composition (Fig. 2a-e). All the cell populations pre-/post-integration remained consistent, except that the EE populations no longer formed distinct subclusters (Fig. 2f-g). Across the genera Aedes and Culex , we performed comparisons on the midgut cell clusters that exist in all the mosquito species given the absence of several cell clusters. The analysis revealed that these clusters (Cardia-2, EE-1, and VM) respectively exhibited conserved transcriptomic features, in which the most proportion of cells were integrated into corresponding clusters (Fig. 2f). Transcriptional profiles are conserved in the ISC/EB populations but divergent in their subclusters ISC/EB-1 and ISC/EB-prol, suggesting both intrageneric and intrageneric transcriptomic similarity between the two clusters. Similar conserved patterns are also observed among EC and EC-like-1 clusters (Fig. 2f). Notably, cluster Cardia-1 of two genera were annotated as two different Cardia clusters post-integration (Cardia-1 for Aedes , Cardia-2 for Culex , Fig. 2f). At species level, the transcriptional profiles of the intergeneric conserved clusters and the EC-like-2, EC-like-3 and HC clusters, which existed in a subset of species, remained conserved among all the mosquito species (Fig. 2g). In the case of Ae. aegypti and Cx. tritaeniorhynchus , their EE-2 remained conserved, but the EE-2 cluster of Ae. albopictus has similar transcriptomic features to the cluster EC-like-3 rather than EE (Fig. 2g). Interestingly, the EE-3 cluster of Cx. tritaeniorhynchus showed transcriptomic divergences with that of Ae. aegypti , yet it exhibited similarity to the Cardia-1 cluster post integration (Fig. 2g). In addition, HC clusters are transcriptomic conserved across these two mosquito species. Subsequently, we focused on identifying top DEGs in cell populations exhibiting or inter-specific differences on transcriptomic features by performing pairwise comparisons across the four mosquito species (Supplementary Dataset 2). While DEGs across non-EE clusters were predominantly enriched in digestive enzymes, the EE cluster exhibited inter-specific differences in both metabolic genes and pathogen-associated genes, with the most pronounced differences between Ae. aegypti and two Culex mosquitoes (Fig. 2h). When comparing the EE clusters of Ae. aegypti with that of Cx. tritaeniorhynchus , Ae. aegypti exhibited significantly higher expression levels of the IA-2 gene, which is involved in digestive tract development and regulation of secretion (Fig. 2h). Two ATP-dependent RNA helicase dbp2 are highly expressed in Ae. aegypti (Fig. 2h). These genes are involved in mRNA splicing and RNP complex assembly, with some family members potentially play roles in viral RNA recognition and cellular antiviral responses 45,46 . In addition, the CCHa1 is also highly expressed in Ae. aegypti (Fig. 2h). It was reported that CCHa1 can be upregulated by protein-rich food and might participate in water-ion homeostasis maintenance post-bloodmeal 43 . This change was also detected in the EE clusters between Ae. aegypti and Cx. p. pallens (Fig. 2h). Dynamics of midgut cell populations post-bloodmeal in Ae. aegypti and Cx. tritaeniorhynchus To characterize the cellular composition and gene expression signatures of midgut cell populations caused by bloodmeal, the scRNA-seq data of midguts of two representative mosquitoes, Ae. aegypti and Cx. tritaeniorhynchus at 7 days post bloodmeal (dpb, bloodmeal at 7 dpe), were integrated with their corresponding cell atlases (glucose mock). For Ae. aegypti , we identified a new EE cluster named EE-4, characterized by significant high expression of the CCHa2 compared to the other EE subclusters (Fig. 3a-c, Supplementary Fig. 1a). And the HC cluster absent in its glucose mock cell atlas by significant high expression of LRIM16 and NimB2 (Fig. 3a-c). The marker gene used for the other cell populations at 7 dpb were consistent with the glucose mock. Except for EC-like-1, EE-4 and HC clusters, the proportions of most cell populations of Ae. aegypti at 7 dpb were significantly different compared to the glucose mock, in which the ISC/EB-1 and EC clusters showed the most pronounced dynamics, which substantially increased and decreased at 7 dpb, respectively (Fig. 3d). For Cx. tritaeniorhynchus , both the cell populations and their marker genes at 7 dpb remained consistent with the mock (Fig. 3g-h). The absent cell cluster EC-like-2 was identified by the consistent markers but different expression levels with EC-like-1 (Fig. 3i, Supplementary Fig. 1b). Different from Ae. aegypti , only the proportions of ISC/EB, EC and EC-like clusters varied between Cx. tritaeniorhynchus at 7 dpb and the mock (Fig. 3j). Interestingly, at 7 dpb, the shared clusters ISC/EB-1, ISC/EB-prol and EC exhibited opposing trends between Ae. aegypti and Cx. tritaeniorhynchus . We then characterized the top upregulated/downregulated DEGs of each cell cluster between the mosquitoes pre- and post-bloodmeal, respectively (Supplementary Dataset 3). For Ae. aegypti, the broadly significant downregulation of the gene family that are involved in stress response including the gene families of protein lethal(2)essential for life [ l(2)efl ] and heat shock protein 70 ( hsp70 ) were observed across the cell clusters after bloodmeal(Supplementary Fig. 1c). A broadly significant increase of the gene neurogenic locus notch homolog protein 1 ( Notch1 ) was observed across the cell clusters post-bloodmeal (Supplementary Fig. 1c). The notch pathway plays an important role in EB differentiation into EC and EE in Drosophila 47 . The upregulation of mitochondrial genes in the EC and EC-like clusters further reflects enhanced metabolic activity (Fig. 3e). Additionally, the peptidoglycan recognition protein LB ( PGRPLB ) involved immune pathway was upregulated in the EC and EC-like clusters. In the Cardia clusters, two genes lysozyme C-1 ( LYSC4 ) and glutathione S-transferase 1 ( GSTD4 ) were upregulated following a bloodmeal (Fig. 3f). For Cx. tritaeniorhynchus , the similar downregulation of genes involved in stress response was also observed after bloodmeal (Supplementary Fig. 1d). Notably, the ISC/EB, EE-1 and EC-like-1 clusters exhibited the significantly upregulated gene esg , which is the marker gene of ISC (Fig. 3k), suggesting that bloodmeal might induce the differentiation of ISC to ECs. The gene PCNA also showed the significantly higher expression level in two ISC/EB clusters (Fig. 3i), indicating their proliferative states 27,48 . Metabolism across the uninfected mosquito midguts (319 words) The mosquito midgut plays a crucial role in the metabolism of various nutrients. To compare the differences of digestive functions across the uninfected mosquito midguts, we examined the gene expression associated with metabolism (Fig. 4a). Regarding sugar metabolism, the expression of amylases and maltases (AAEL000647 and AAEL000667) was inter-generic different; for Aedes mosquitoes, both of them showed a broad expression across the cell clusters such as Cardia, EC and EE clusters; for Culex mosquitoes, these two genes are only highly expressed in the Cardia clusters (Fig. 4a). Interestingly, a glucosidase gene (AAEL020371) was highly expressed in Ae. albopictus and Cx. tritaeniorhynchus , but lowly expressed in Ae. aegypti and Cx. p. pallens (Fig. 4a). For lipid metabolism, all cell clusters exhibited low expression of lipid-related enzymes, with higher expression in EC and EC-like clusters (Fig. 4a). In Ae. aegypti post-bloodmeal, the expression level of the lipase genes Glllspla2 and AAEL001837 was obviously higher than that pre-bloodmeal (Fig. 4a). For peptide metabolism, similar expression patterns of the most peptidases are observed among the mosquito samples (Fig. 4a). Broad expression of specific members was detectable across most peptidase categories, especially in the serine endopeptidase (Fig. 4a). In Aedes mosquito, the serine endopeptidase AAEL003060 is highly expressed by all the clusters. In addition, the enrichment of peptidase genes is observed in EC and EC-like clusters (Fig. 4a). Except for digestive functions, midguts also broadly anticipate other physiological processes. To characterize the biological functions of each cluster across the mosquito samples, we manually collected and categorized the GO terms into distinct groups (Fig. 4b). For Aedes mosquitoes, the EC and EC-like clusters mainly contribute to metabolism, while the EE clusters perform signaling functions (Fig. 4b). However, two ISC/EB clusters in Ae. aegypti shows no enrichment in cell proliferation. Midgut epithelial cells broadly show enrichment in transmembrane transport both in pre- and post-bloodmeal, suggesting the robust maintenance of water-ion homeostasis in Cx. tritaeniorhynchus (Fig. 4b). Dynamics of midgut cell populations in DENV-infected Aedes aegypti (909) To investigate the dynamic changes in midgut cell populations caused by DENV infection, we examined Ae. aegypti at 7 days post infection (dpi, infectious bloodmeal at 7 dpe). We integrated and analyzed the midgut cell data of Ae. aegypti from the glucose mock, the uninfectious bloodmeal mock, and the DENV infection (Fig. 5a-b). Comparing the uninfectious and infectious bloodmeal groups at the same time point (7 dpi / 14 dpe), most cell clusters and their marker genes are consistent (Supplementary Fig. 2a). Notably, a new cluster (SV2/UNC-93) was identified by significant high expression of the synaptic vesicle protein-2 ( SV2 ) and UNC-93 , the former is a homolog of mammalian SV2 and participate in regulation of vesicle transport and exocytosis and the latter is involved in regulating potassium channels (Fig. 5c) 49 . Proportion of the SV2/UNC-93 cluster of the DENV infection is significantly higher than that of the bloodmeal mock (Fig. 5d). For ISC/EB and EC-like-2 clusters of the DENV infection, the proportions of cell populations are significantly higher than those of the bloodmeal mock, while Cardia and EC-like-1 clusters are opposite (Fig. 5d). The percentages of all EE populations of the DENV infection are lower than their counterparts of the bloodmeal mock (Fig. 5d). In addition, two cell populations including HC and Fat Body Cell (FBC) clusters were also identified with low proportions (Fig. 5d). The FBC cluster was identified by significant expression of apolipophorin-3 ( Apo3 ) 26,27 . To explore the cellular populations and their associated genes involved in the response to DENV infection in Ae. aegypti , the analysis of DEGs was performed on each cell clusters between the bloodmeal mock and DENV infection. A total of 987 significant DEGs (|de_coef| >= 0.693 / |log 2 FC| >= 1, p < 0.05) were identified, of which 281 and 706 were upregulated and downregulated, respectively (Supplementary Dataset 4). The upregulated DEGs of each cluster were fewer than their corresponding downregulated DEGs (Supplementary Fig. 2b). This pattern suggests a predominant downregulation of gene expression across various cell types in response to DENV infection. The expression dynamics of the DEGs in the corresponding cell clusters were further investigated (Fig. 5e-h). In each cell cluster post infection, downregulated genes showed larger changes of mean expression levels compared to upregulated genes (Supplementary Dataset 4). The gene families of hsp70, l(2)efl , trp and GAAD45 associated with stress response were broadly shared in the downregulated DEGs across all midgut cell clusters (Fig. 5e, Supplementary Dataset 4). In the EC cluster, one of the antimicrobial peptide genes— GAM1 —was broadly expressed across the cells pre-infection and showed a significant upregulation post-infection (Fig. 5e). In the EC-like-1 cluster, the significant upregulation of the component of the signal peptide complex (SPC), spc22/23 was observed (Fig. 5e), the SPC is vital for the cleavage of structural protein and virion release of orthoflaviviruses 50 . In two ISC/EB populations, the expression of gene FK506-binding protein 39kD (Fkbp39) significantly increased post-infection (Fig. 5f). For EE clusters, genes associated with signal transduction such as NPF , Mip , sNPF , boca and mbc were significantly upregulated in the EE clusters, while a significant increase of the expression of Hlc in the EE-3 cluster—an orthologous gene of Drosophila DEAD box ATP-dependent RNA helicase 56 ( DDX56 ) (Fig. 5g) 46 . In addition, mitochondria-related genes ACADSB and Chchd3 were significantly upregulated in the EE-4 cluster (Fig. 5g). In the newly discovered cluster SV2/UNC-93, it was notable that a series of Vacuolar-type proton ATPase ( vATPase ) subunit genes ( vATPase-1 , vATPase-d1 , vATPase-F , vATPase-G , Vha16-1 , VhaPPA1 and VhaSFD ) were observed to be post-infection (Fig. 5h). The gene E3 ubiquitin-protein ligase RFWD2 ( RFWD2 ) was also significantly upregulated (Fig. 5h). To further understand the immune response in DENV-infected Ae. aegypti , we compiled a list of canonical and potential immune genes from previous studies and examined the gene expression of them 17 . The majority of immune genes exhibited downregulation in response to viral infection (Fig. 5i). Components of the Toll, IMD and PGRP pathways exhibited broad expression across midgut cell clusters pre- versus post-infection, with high enrichment in EC, EC-like-1 and EE clusters (Fig. 5i). The gene PGRPLB is dominant in the Cardia-2 cluster (Fig. 5i). Interestingly, expression of the gene AAEL000200 involved in JAK-STAT pathway increased in the FBC cluster but decreased in the SV2/UNC-93 cluster (Fig. 5i). Among AMPs, the gene GAM1 was broadly expressed in all the cell clusters, predominant in the Cardia clusters, and GAM1 expression showed an increase in SV2/UNC-93 cluster post infection (Fig. 5i). Notably, the SV2/UNC-93 cluster exhibited highly specific expression of defensin C ( DEFC ) and abdomen-specific antimicrobial peptide holotricin ( GRRP ) pre-infection, which was dramatically reduced post-infection 17,34 . For lysozymes, LYSC7B is primarily expressed in the Cardia-1 cluster, while LYSC11 is dominant in the ISC/EB clusters. In addition, there was also a dramatic decrease of LYSC4 in the SV2/UNC-93 cluster post-infection (Fig. 5i). Previous studies have demonstrated that vector competence for the same virus varies among mosquito species, implying that host factors playing important role in virus transmisision 51,52 . Notably, comparative analyses of Ae. aegypti strains revealed distinct host factor signatures between susceptible and refractory phenotypes, suggesting that basal-level gene expression profiles could contribute to the divergence 53,54 . Therefore, we compared the basal-level expression of the genes orthologous with DEGs identified in DENV-infected Ae. aegypti in all vector mosquitoes (Fig. 5j, Supplementary Dataset 5). A series of vATPase subunit genes upregulated in DENV-infected Ae. aegypti showed the highest basal expression in Cx. tritaeniorhynchus compared to other mosquitoes except vATPase-G (Fig. 5j). Viromes of mosquito midguts Previous studies have documented viral communities in various mosquito species (using single or pooled mosquito samples), including both field collected and lab reared populations, yet the midgut—where arboviruses first establish infection—has seldom been examined in isolation 55,56 . To characterize the viral composition within mosquito midguts, virome profiling was performed in this study. The top 10 most abundant viruses identified across samples belong to 5 recognized families ( Iflaviridae , Flaviviridae , Tombusviridae, Totiviridae, and Rhabdoviridae ), together with an unclassified group (Fig. 6a). With the exception of DENV-2 (an arbovirus), the other detected viruses are either arthropod-specific viruses (ASVs) or of unknown hosts. Notably, DENV-2 was only detected in experimentally infected samples. Hanko iflavirus 1 (HKIFV1) and L-A virus were widespread across all samples, particularly in Ae. aegypti and Cx. tritaeniorhynchus (Fig. 6a-b), and the virome of Ae. albopictus was featured by a predominant proportion of Tombusviridae (Fig. 6a). Minimal changes in virome composition were observed between glucose-fed and uninfected bloodmeal groups for both Ae. aegypti and Cx. tritaeniorhynchus (Fig. 6a). Following DENV-2 infection, both the expression level and infection rate of HKIFV1 significantly decreased in Ae. aegypti (Fig. 6b). DENV-2 was broadly distributed across all midgut cell clusters without obvious tropism, although the highest viral loads occurred in the EC and EE clusters (Fig. 6a,c). Tiger mosquito bi-segmented tombus-like virus (TMBSTLV) is widely distributed in Ae. albopictus across Asia, America and Europe, with the capacity to readily induce dsRNA and siRNA generation in mosquitoes 57,58 . Here, TMBSTLV was widely detected at low levels across all midgut cells in Ae. albopictus , but showed the obvious tropism to the HC cluster(Fig. 6d). Discussion In this study, we constructed comprehensive midgut cell atlas and virome for four major vector mosquitoes, providing detailed insights into the cellular composition, physiological, and infection-driven features of mosquito midgut. Current scRNA-seq technologies for single-cell capture and isolation are primarily divided into two categories, microfluidic-based and microwell-based method 21,59 . The microwell-based methods capture single cells by distributing them into chips containing millions of microwell arrays through physiological settlement 21,60 , which have been extensively applied in research associated with vertebrate demonstrating its capability to capture high-quality RNA and reduce microfluidics-induced stress 29,31,61–63 . For the first time, we implemented the microwell-based scRNA-seq to mosquito midgut, achieving satisfactory performance in key data metrics. Our dataset of Ae. aegypti in this study exhibited improved quality in mitochondrial gene proportion, mean UMIs and genes per cell compared to our previous microfluidics-based scRNA-seq study on the same species 25 . Importantly, the three additional mosquito species showed comparable data quality to Ae. aegypti. To our knowledge, this study provided the first evidence of inter-generic and inter-specific mosquito midgut cell population differences under identical experimental conditions. Despite anatomical and cell type composition similarities across the four mosquito species examined, notable differences were observed in the proportions of specific cell clusters. Culex mosquitoes showed a higher proportion of ISC/EB clusters than Aedes mosquitoes, suggesting Culex may possess enhanced intestinal regenerative capacity 33 . Furthermore, the expanded ISC/EB populations in Cx. tritaeniorhynchus may represent an evolutionary adaptation for rapid epithelial repair following a bloodmeal. Spatially, Cardia cells were localized in the anterior midgut, whereas EC and EC-like cells predominantly resided in the posterior midgut 33 . Previous studies reported that carbohydrate digestion primarily occurred in the anterior region, while protein processing is concentrated in the posterior area 17 . Our findings of digestive enzyme expression heterogeneity across midgut cell populations further corroborate the functional specialization of midgut. Interestingly, the significantly higher proportion of Cardia cells in Ae. albopictus might indicate an enhanced requirement for carbohydrate metabolism than other mosquitoes. This observation may reflect species-specific adaptations to different feeding behaviors or ecological niches. Compared to well-established model organisms (human, mouse or Drosophila ), mosquitoes have relatively underdeveloped genome annotations and limited scRNA-seq studies. This gap is further compounded by the scarcity of marker genes for mosquito cell types, with only Ae. aegypti possessing a higher-quality genomic reference. Therefore, the incomplete genomic annotation or the absence of orthologous markers in the mosquitoes pose a challenge for cell type annotation. In previous study, the canonical markers for ISC/EB clusters in Ae. aegypti and that for Cardia clusters in Cx. tarsalis are absent 27,34 , and we encountered similar challenges. To address this issue, we employed previously established non-canonical marker genes or the top expressed marker genes to annotate cell clusters lacking canonical markers. The marker genes used in the ISC/EB and EE clusters of Ae. aegypti were different. The two ISC/EB clusters showed low expression of canonical marker genes ( Klu , Delta and esg ) but were distinctly labeled by fibulin 1 and LYSC11 . These alternative marker genes were previously identified among the top ISC/EB marker genes in the study of Cui et al . and aligned with another scRNA-seq study conducted on Ae. aegypti 33,34 . The expression of the canonical marker prospero is observed among all three EE clusters. For Ae. albopictus , the gene Calexcitin-1 was used to identify the EE clusters due to the fact that the canonical marker gene prospero was exclusively expressed in the EE-1 cluster. In each mosquito species, only the cluster that exhibited the highest expression level of the canonical marker Nubbin was identified as the EC cluster 33,34 . Therefore, the markers of EC-like clusters were characterized by a series of highly expressed digestive enzyme genes that varied among different mosquito species 27,33,34 . The marker genes of several cell populations such as Cardia and EE used in Cx. tritaeniorhynchus were markedly different from others. This discrepancy is likely due to the absence of homologous genes, highlighting the potential for species-specific adaptations in midgut cell populations. We observed a similar pattern on the top downregulated DEGs among the cell clusters in Ae. aegypti post DENV infection. The broadly shared genes are concentrated in the hsp70 and l(2)efl gene families. These genes play protective roles and respond to various stress 64–66 . The downregulation of hsp70 genes was also observed in the previous study on Ae. aegypti Rockfeller strain, suggesting the DENV may suppress oxidative stress responsive system 67 . The decrease of the l(2)efl genes in this study was different with a bulk RNA-seq study on DENV-infected Ae. aegypti LVP INB strain at 14 dpi, in which the l(2)efl genes showed bidirectional changes during infection 68 . The discrepancy may stem from variations sampling timepoints, the age may compromise the efficacy and intensity of immune response to infection 69 . The pervasive downregulation of the genes may imply a shared host response mechanism to DENV midgut infection. The ISCs and EBs differentiated to renew the epithelium, thereby maintaining the midgut homeostasis and responding to stressors 70 . Notably, the broad observation of the enrichment of two immune-related genes LRIM16 and Apo3 in the ISC/EB clusters among the various species in both this and other mosquito midgut scRNA-seq study 27,34 , with LRIM16 being a leucine-rich immune protein and Apo3 being a pro-ZIKV factor in mosquito midgut 26,28 . It suggests that ISC/EB populations may play complex roles in the infection process. Following an infectious bloodmeal, the proportion of ISC/EB clusters markedly increased versus the bloodmeal group, without significant EC changes, indicating that the trend is specifically stimulated by viral infection rather than by blood feeding alone 19,71 . The resistance to pathogen infection enhanced by ISC proliferation was also observed in DENV-infected Ae. aegypti and Plasmodium -infected Anopheles stephensi 19,72 . The upregulated gene Fkbp39 in the ISC/EB-prol cluster post-infection is an orthologs of Drosophila Fkbp39 that binds juvenile hormone response elements 73 . A study reported that juvenile hormone could suppress the AMP production in Drosophila following bacterial infection and participate the antimicrobial immune system in Ae. aegypti 74,75 . It would be interesting to clarify its potential function in immune response against viral infection. EEs are potentially key sites for viral infection in Ae. aegypti 18,76 . The cellular proportions of each EE clusters significantly decreased post-infection, suggesting the virus-induced modulation of these cells. Similar changes were also observed in a previous RNA-seq study of ZIKV-infected Ae. aegypti 26 . Notably, we observed a significant increase of the gene Hlc in the EE-3 cluster post-infection. The gene is an ortholog of Drosophila DDX56 , a conserved antiviral protein that could control Alphavirus infection 46 . Given its antiviral role, the upregulation of Hlc in EE-3 suggests a potential defense mechanism against viral infection. The EE-4 cluster post-infection was characterized by the upregulation of multiple mitochondria-related genes, especially the gene CHCHD3 that was involved in mitochondrial fusion 77 . Previous studies reported that DENV could impair mitochondrial fusion and fission to induce mitochondrial elongation to promote infection 78,79 . However, since our study did not detect vRNAs in the cells, whether the phenomenon is caused by metabolic alterations or the regulation of antiviral RLR signaling remains to be studied 79 . The cluster termed “SV2/UNC-93” markedly increased in cellular proportion post-infection. It displayed distinct transcriptional features from the known midgut cell types and was uniquely defined by the significant expression of SV2 and UNC-93 , thus representing a novel cell cluster within the mosquito midgut. The two genes played multiple proviral roles in Ae. aegypti : silencing both of them increased midgut infection rates while suppressing viral dissemination from midgut to hemolymph 49 . Midgut epithelial cells have apical-basal polarity maintained by an ion gradient across membrane surfaces. Genes involved in maintaining the gradient might be potential viral host factors 49,80 . Several studies indicated that vATPase is an Ae. aegypti pro-DENV factor that showed impacts on viral fusion and entry by endosomal acidification and viral egress by DENV PrM— vATPase binding 81,82 . We observed significant upregulation of multiple vATPase genes in this cluster, accompanied by marked expression of the gene RFWD2 . A study on ZIKV-infected Ae. aegypti indicated that the ubiquitination of viral NS1 protein could promote viral replication by a mammalian E3 ubiquitin ligase WWP2 homolog Su (dx) 83 . Although RFWD2 was not a homolog of Su (dx) , its upregulation in the SV2/UNC-93 cluster suggests a potential role in viral infection. Moreover, the bidirectional changes observed in canonical pathways in this cluster reflected the complexity of the innate immune response upon viral challenge. These findings suggest that this cell cluster may be a novel epithelial cell type that supports the viral dissemination from lumen to hemolymph. This possibility remains to be further studied. Taken together, this study presented a comprehensive single-cell atlas and virome of the midgut across four medically important vector mosquitoes and the transcriptomic changes of midgut cell populations following bloodmeal feeding. Evolutionarily conserved and species-specific cellular signatures across mosquito midguts will enhance our fundamental understanding of mosquito physiology, offering new frameworks for comparative hematophagous arthropod biology. Furthermore, our study delineated the dynamic response of Ae. aegypti midgut to DENV infection at single-cell resolution. In conclusion, these findings provide deeper insights into the mosquito midgut and MBV-midgut interactions, offering the potential target by disrupting virus dissemination in mosquitoes to combat mosquito-borne diseases. Methods Mosquito Four mosquito species used in this study were Ae. aegypti (Rockefeller strain), Ae. albopictus (Jiangsu strain), Cx. p. pallens (Beijing strain) and Cx. tritaeniorhynchus (Yingcheng strain). All mosquitoes were maintained under 28 °C, 75% relative humidity (RH) with 12h:12h light/dark cycles. Cell and virus Vero E6 cells were infected at a multiplicity of infection (MOI) of 0.01 with DENV2 (strain D2Y98P), then cultured at 37 °C with 5% CO 2 in Dulbecco’s Modified Eagle’s Medium (DMEM, Gibco, USA) supplemented with 2% fetal bovine serum (FBS, Gibco, USA) and 1% penicillin-streptomycin (Gibco, USA). The culture supernatant was harvested at 7 dpi and then filtered through a 0.2 μm filter (Merck, German) to remove cellular debris for virus titration as described in the previous study 84 . Biocontainment All procedures for in vitro work involving DENV-2 propagation and infection were carried out in the biosafety level 2 (BSL-2) laboratory. Mosquito oral infection, maintenance, and dissection after DENV-2 infection were conducted in the arthropod containment level 2 (ACL-2) laboratory. Blood feeding and DENV infection of mosquitoes To explore the midgut cell dynamics of mosquitoes post-bloodmeal, 7-day-old Ae. aegypti and Cx. tritaeniorhynchus mosquitoes fed with noninfectious pig blood.To explore the midgut cell dynamics of mosquitoes post-infection, 7-day-old Ae. aegypti mosquitoes were fed with DENV-2 bloodmeal (a final viral concentration of 1.5×10 6 PFU/mL). The oral fed and infection was performed with artificial membrane system as described in previous study 85 . The fully engorged females were selected and maintained until dissection. Collection of midgut samples The midgut was dissected from 50-100 females from Ae. aegypti , Ae. albopictus , Cx. p. pallens and Cx. tritaeniorhynchus that were fed with glucose at 7 dpe. For female Ae. aegypti and Cx. tritaeniorhynchus mosquitoes that were previously fed with noninfectious bloodmeal, the midguts were collected at 7 dpb. Additionally, the DENV2 infected midgut were collected from female Ae. aegypti mosquitoes at 7 dpi. Detailed information regarding the sampling schedule and experimental groups can be found in Supplementary Dataset 6 and Fig 1a. Single-cell preparation from midguts The midguts were washed and temporarily stored in Schneider’s Drosophila Medium (SDM, Gibco, USA) within a microcentrifuge tube on ice, then minced in 300 μl of dissociation buffer from SCelLiVe Tissue Dissociation Kit (Singleron, China). The tissue fragments were resuspended in 700 μl of dissociation buffer and then incubated in a 28 °C water bath for 15-25 min. During incubation, the suspension was periodically mixed, and the cell concentration, viability and aggregation were measured every five minutes by staining with 0.4% trypan blue to ensure the quality of the cells. Once the quality control (QC) criteria were met, the suspension was loaded into a 50 ml centrifuge tube equipped with a pre-wetted 40 μm filter to remove larger cell debris, and then washed with 1× PBS (Gibco, USA) until the final volume reached 15 ml. The resulting cell suspension was centrifuged at 350× g, 4 °C for 5 min. A viable cell band was typically observed near or at the bottom of the tube, and 100-200 μl of the supernatant was retained to avoid disturbing the pellet. The cell pellet was then suspended, followed by a second counting with 0.4% trypan blue. Only cell suspension samples with viability ≥ 80% and were used for subsequent scRNA-seq. Library construction and sequencing According to the manufacturer’s guidelines, the single-cell suspension was adjusted to ~200 cells/μl prior to loading onto a microfluidic microwell SCOPE-chip (Singleron, China). The cDNA synthesis of captured cells and sequencing library construction were performed with GEXSCOPE Single Cell RNA Library Kit (Singleron, China). The constructed libraries were sequenced with NovaSeq 6000 system (Illumina, USA) in accordance with the manufacturer’s instructions. The sequencing quality metrics could be found in Supplementary Dataset 6. Data analysis The workflow for data analysis was showed in Supplementary Fig. 3. (1) Single-cell RNA-seq analysis The mosquito genomes ( Ae. aegypti : assembly AaegL5.0, Ae. albopictus : assembly AalbF5, Cx. p. pallens : assembly TS_CPP_V2 were obtained from NCBI of USA; the genome of the Cx tritaeniorhynchus was sequenced and annotated by our laboratory) and their gene feature files were converted to references by CeleScope (v2.1.0) 86 . Mosquito mitochondrial genes were manually annotated with “MT-” prefix. To perform single-cell integration among mosquito species, BLASTP (2.15.0+) 87 with default parameters was used. The protein sequences of Ae. aegypti were used as the reference to calculate the similarity between the protein sequences encoded by the genes of other mosquito species and those of Ae. aegypti. The genes corresponding to the protein sequences with the best hit and e-value ≤ 1e-6 were identified as the orthologous genes. For gene abbreviations in this study, we adopted the following strategies: (I) We prioritized the abbreviations, acronyms or names of Ae. aegypti annotated by VectorBase 88 . (II) Where applicable, we also used the names of Drosophila orthologs annotated by FlyBase 89 . (III) If no suitable abbreviation or ortholog name was available, the gene name was left blank. The comparison table of NCBI gene ID, Entrez ID and VectorBase ID could be found in Supplementary Dataset 7. The raw sequencing data were aligned to the genome references and the expression matrices were calculated by CeleScope. To ensure data quality, cells with fewer than 100 genes or more than 2,500 genes were excluded 28 , as were cells with a mitochondrial proportion exceeding 15%. Subsequent scRNA-seq analysis was performed with Scanpy (v1.11.1) 32 . DoubletFinder (v2.0.3) 90 was used to identify doublets. The filtered data were log-normalized and the top 4000 highly variable genes were used for PCA dimension reduction. The optimal parameters (n_neighbors = 50, n_pca = 30 and resolution = 1.2) were used for UMAP dimension reduction and Leiden clustering. For Ae. aegypti and Cx. tritaeniorhynchus , the single-cell data from the same mosquito species pre- and post-bloodmeal were integrated by Harmony (v0.0.10) 91 . The optimal parameters (n_neighbors = 100, n_pca = 30 and resolution = 1.8) were used for UMAP dimension reduction and Leiden clustering.Harmony was used to integrate the single-cell data from Ae. aegypti with glucose group, bloodmeal group, and DENV-infection group. The optimal parameters (n_neighbors = 100, n_pca = 30 and resolution = 1.8) were used for UMAP dimension reduction and Leiden clustering.All single-cell transcriptomic DEGs were calculated using Memento (v0.1.1) 92 with default parameters. Genes with de_pval ≤ 0.05 were considered DEGs. Among them, genes with de_coef > 0 are significantly high expressed genes, and genes with de_coef < 0 are significantly low expressed genes. (2) Inter-generic and inter-specific data integration According to the instructions specified in the official documentation, the scvi-tools (1.3.0) 44 with default parameters was used to integrate single-cell data based on orthologs across different mosquito species. Scanpy with the same parameters as above was used for dimension reduction and clustering. Comparisons among mosquito species were performed by integrating single-cell data for each mosquito species as a batch. Comparisons between mosquito genera were performed by integrating single-cell data for each mosquito genus as a batch. (3) Single cell virome analysis To characterize the virome composition in our samples, we utilized a pseudo-metagenomic method for both bulk and cellular virome analysis. For bulk analysis, in each sample, reads unmapped to the host genome by CeleScope was extracted., followed by additional quality filtering using Fastp (v 0.23.4) 93 with polyN tail trimming. A custom reference library was constructed by the following strategy: The sequences of the mosquito-associated viral families and negeviruses detected in previous studies were extracted from NCBI virus database 34,94 . Then, the pathogenetic viral sequences were excluded except for DENV strain D2Y98P used in this study according to our arbovirus dataset 95 . Then, the reads were annotated against the reference library using Bowtie2 (2.4.5) 96 and the viral abundance matrix was generated by custom scripts. For cellular analysis, the abundance data of the viruses including Hanko iflavirus 1 (ON949933.1), DENV2 strain D2Y98P (JF327392.1), Tiger mosquito bi-segmented tombus-like virus (BK059489.1 and BK059490.1), L-A virus (MW174761.1) was extracted and mapped to the cells by the corresponding cell barcodes. The vial abundance was calculated by UMI counts and only partial viral reads could be mapped to cells. Statistical analysis and data visualization Statistical analyses were performed using custom R and Python scripts. Data visualization was performed by Scanpy, OmicVerse (v1.7.1) 97 and custom R scripts. Declarations Data availability The raw data and processed scRNA-seq data are available on the NCBI GEO database with accession GSE301762 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE301762), the access password: utqdaqkovxopxer. Another copy is available on the CNCB (China National Center for Bioinformation) GSA (Genome Sequence Archive) database with accession CRA027708 and CNCB OMIX (Open Archive for Miscellaneous Data) with accession MIX010740. The genome assembly of Cx. tritaeniorhynchus Yingcheng strain is available on CNCB GWH (Genome Warehouse) database with accession GWHGEEU00000000.1. Code Availability The codes for analysis are available on GitHub: https://github.com/paddle-salted-fish/midgut_cell_atlas_and_virome_of_mosquito_project Acknowledgements This work was supported by the National Key Research and Development Program of China (2024YFC231000 and 2023YFC2305900), the National Natural Science Foundation of China (U22A20363, 32400379), and Zhejiang Provincial Natural Science Foundation of China (LQN25C040001). 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OmicVerse: a framework for bridging and deepening insights across bulk and single-cell sequencing. Nat. Commun. 15 , 5983 (2024). Additional Declarations There is NO Competing Interest. Supplementary Files STable1.docx Supplementary Table 1 SFigures20250725.docx Supplementary Figures 1-3 SDataset1Othologousgenecomparisontable.csv Supplementary Dataset 1 SDataset2PairwiseDEGoffourmosquitospecies.xlsx Supplementary Dataset 2 SDataset3DEGofeachclustersofmosquitoespreandpostbloodmeal.xlsx Supplementary Dataset 3 SDataset4DEGofeachclustersofAeaegyptiwithbloodmealmockversusDENVinfection.xlsx Supplementary Dataset 4 SDataset5MeanExpressionofDEGorthologsintheotherthreemosquitospeciescomparedwithAeaegypti.xlsx Supplementary Dataset 5 SDataset6scRNAseqdatametrics.xlsx Supplementary Dataset 6 SDataset7AeaegyptiNCBIEntrezVectorBasegeneidcomparisontable.csv Supplementary Dataset 7 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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13:00:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7214530/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7214530/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88750677,"identity":"c7786e19-5df7-4c86-8202-5f804a73493b","added_by":"auto","created_at":"2025-08-11 06:05:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":658143,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe midgut cell atlas of four mosquito species: \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAe. aegypti\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e, \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAe. albopictus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e, \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCx. p. pallens\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCx. tritaeniorhynchus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. a,\u003c/strong\u003e Schematic overview of the experimental workflow in this study. Midgut samples from different mosquito species were collected and subjected to scRNA-seq experiments. The resulting data were then integrated for different analyses (See the section Methods for the detailed information). \u003cstrong\u003eb-e,\u003c/strong\u003eUMAP visualization of the cell clusters for each mosquito species, \u003cem\u003eAe. aegypti \u003c/em\u003e(b)\u003cem\u003e, Ae. albopictus \u003c/em\u003e(c)\u003cem\u003e, Cx. p. pallens \u003c/em\u003e(d)\u003cem\u003e and Cx. tritaeniorhynchus \u003c/em\u003e(e). Each dot represents a single cell and the color indicates different cell clusters identified in each species. \u003cstrong\u003ef, \u003c/strong\u003eExpression of marker genes in cell clusters for four mosquito species. Dot size represents the percentages of cells expressing each gene and color shows the mean gene expression. The absence of dots means lacking of the corresponding gene in the species. The cell type named as grey stands for the absence of this cell type in the species. \u003cstrong\u003eg,\u003c/strong\u003e The proportion of each cell clusters between \u003cem\u003eAedes\u003c/em\u003eand \u003cem\u003eCulex \u003c/em\u003emosquitoes. \u003cstrong\u003eh,\u003c/strong\u003e The proportion of each cell clusters among four mosquito species. The inter-generic and inter-specific comparisons were analyzed using Fisher’s Exact test. P value ≤ 0.05 was considered as significantly different. *: p \u0026lt; 0.05, **: p \u0026lt; 0.01, ***: p \u0026lt; 0.001. Abbreviations: Intestinal stem cells/enteroblasts (ISC/EB), cardia cells (Cardia), enterocytes (EC), enterocytes-like (EC-like), enteroendocrine cells (EE), visceral muscle (VM), fat body cells (FBC) and hemocytes (HC).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/5886a1b6f099d7606afb1b43.png"},{"id":88750522,"identity":"91acf0db-6465-4dba-a649-e0aa56b07791","added_by":"auto","created_at":"2025-08-11 05:57:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":583550,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe integrated comparisons of midgut cell atlas for four mosquito species. a,\u003c/strong\u003e UMAP visualization of the integrated cell clusters grouped by cell clusters for four mosquito species. \u003cstrong\u003eb,\u003c/strong\u003eUMAP visualization of the integrated cell clusters grouped by each species. \u003cstrong\u003ec, \u003c/strong\u003eUMAP visualization of the two integrated \u003cem\u003eAedes\u003c/em\u003e species. \u003cstrong\u003ed,\u003c/strong\u003eUMAP visualization of the two integrated \u003cem\u003eCulex\u003c/em\u003e species. Each dot represents a single cell (a-d), and the color indicates different cell clusters (a) or mosquito species (b-d). \u003cstrong\u003ee, \u003c/strong\u003eThe cell number and inter-specific proportion of each integrated cell cluster for four mosquito species. \u003cstrong\u003ef, \u003c/strong\u003eThe heatmap of inter-generic cell type correspondence before and after homology-based integration between \u003cem\u003eAedes\u003c/em\u003e and \u003cem\u003eCulex\u003c/em\u003e mosquitoes. \u003cstrong\u003eg, \u003c/strong\u003eThe heatmap of inter-specific cell type correspondence before and after homology-based integration among the four mosquito species. The color represents the percentage of cells from each original cell cluster that were classified into an integrated cluster (column-normalized). (h) Dot plot shows the expression of DEGs in the EE clusters across the four mosquito species. Dot size represents the percentages of cells expressing each gene and the color shows the relative mean gene expression in \u003cem\u003eAedes\u003c/em\u003e (red) and \u003cem\u003eCulex\u003c/em\u003e(blue) mosquitoes. The right annotation shows gene names and their corresponding accession (“AAEL0” prefix) in \u003cem\u003eAe. aegypti\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/de65a746b662557a9dae914a.png"},{"id":88750525,"identity":"e98b3737-17f3-4d9e-964f-31a6b791da3a","added_by":"auto","created_at":"2025-08-11 05:57:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":723785,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDynamics of midgut cell populations post-bloodmeal in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAe. aegypti\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eCx. tritaeniorhynchus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e \u003cstrong\u003ea-b, \u003c/strong\u003eUMAP visualization of the cell clusters pre- and post-bloodmeal for \u003cem\u003eAe. aegypti.\u003c/em\u003e\u003cstrong\u003ec, \u003c/strong\u003eExpression of marker genes in the EE-4 cell cluster of \u003cem\u003eAe. aegypti. \u003c/em\u003e\u003cstrong\u003ed,\u003c/strong\u003eThe proportion of each cell clusters in \u003cem\u003eAe. aegypti. \u003c/em\u003e\u003cstrong\u003ee-f,\u003c/strong\u003e DEGs in specific cell clusters in \u003cem\u003eAe. aegypti.\u003c/em\u003e \u003cstrong\u003eg-h,\u003c/strong\u003e UMAP visualization of the cell clusters pre- and post-bloodmeal for \u003cem\u003eCx. tritaeniorhynchus. \u003c/em\u003e\u003cstrong\u003ei,\u003c/strong\u003eExpression of marker genes in the EC-like-2 cluster of \u003cem\u003eCx. tritaeniorhynchus.\u003c/em\u003e\u003cstrong\u003e j,\u003c/strong\u003e\u003cem\u003e \u003c/em\u003eThe proportion of each cell clusters in \u003cem\u003eCx. tritaeniorhynchus.\u003c/em\u003e \u003cstrong\u003ek-l,\u003c/strong\u003e DEGs in specific cell clusters in \u003cem\u003eCx. tritaeniorhynchus.\u003c/em\u003e Each dot represents a single cell and is colored by cell clusters (a,b,g,h). Dot size represents the percentages of cells expressing each gene and color shows the relative mean gene expression for pre- (red) and post-bloodmeal (blue) (c,e,f,i,k,l). The darker and lighter color represent pre- and post-bloodmeal, respectively (d,j). The comparisons were analyzed using Fisher’s Exact test. P value ≤ 0.05 was considered as significantly different. *: p \u0026lt; 0.05, **: p \u0026lt; 0.01, ***: p \u0026lt; 0.001. The bottom (c,i) and right (e,f,k,l) annotation lists gene names and their corresponding accession in \u003cem\u003eAe. aegypti \u003c/em\u003e(“AAEL0” prefix) and \u003cem\u003eCx. tritaeniorhynchus \u003c/em\u003e(“CTRY0” prefix).\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/b4598b0237f8d3ca6fa13273.png"},{"id":88750679,"identity":"c3bc911a-dc79-4d3c-a2fd-f62dfc226383","added_by":"auto","created_at":"2025-08-11 06:05:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":558377,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMetabolic gene expression and GO ontology across the uninfected mosquito midguts. a,\u003c/strong\u003e Metabolic genes with the proportion ≥ 20% in at least one cluster were retained. The color shows the percentage of the cells that express a certain gene in a cluster. The top annotation shows the cell clusters and cell types in each sample. The left annotation shows the metabolic gene categories and the right annotation lists the gene names and their corresponding accession in \u003cem\u003eAe. aegypti \u003c/em\u003e(“AAEL0” prefix). \u003cstrong\u003eb,\u003c/strong\u003e The gene ontology of top 20 expressed genes in each cell clusters. GO terms of the other mosquitoes were manually annotated by \u003cem\u003eAe. aegypti\u003c/em\u003e orthologous GO terms. “Unknown” represents the genes not involved in the above GO categories or without GO terms.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/0906f2ea8cd50e8f84bad638.png"},{"id":88750678,"identity":"bcebc5d3-05aa-44b3-9160-336a4f878f55","added_by":"auto","created_at":"2025-08-11 06:05:47","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":986449,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDynamics of midgut cell populations in DENV-infected \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAe.\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eaegypti\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. a-b,\u003c/strong\u003e UMAP visualization of the cell clusters between bloodmeal mock versus DENV-infection. Each dot represents a single cell. The newly found cluster SV-2/UNC93 is labeled. \u003cstrong\u003ec, \u003c/strong\u003eExpression of marker genes in the SV-2/UNC93 cluster. Dot size represents the percentages of cells expressing the corresponding gene, and color shows the relative mean gene expression level between the bloodmeal mock (red) versus DENV-infection (blue). \u003cstrong\u003ed,\u003c/strong\u003e The proportion of each cell cluster between bloodmeal group versus DENV-infection. The comparisons were analyzed using Fisher’s Exact test. P value ≤ 0.05 was considered as significantly different. *: p\u0026lt;0.05, **: p\u0026lt;0.01, ***: p\u0026lt;0.001. \u003cstrong\u003ee-h, \u003c/strong\u003eThe UMAPs show the specific cell clusters and the dot plots show DEGs in the corresponding cell clusters in \u003cem\u003eAe. aegypti\u003c/em\u003e. Dot size represents the percentages of cells expressing each gene and color shows the relative mean gene expression between the bloodmeal group (red) versus DENV-infection (blue). The right annotation lists gene names and their corresponding accession in \u003cem\u003eAe. aegypti \u003c/em\u003e(“AAEL0” prefix). \u003cstrong\u003ei,\u003c/strong\u003eCanonical immune pathways in DENV-infected \u003cem\u003eAe. aegypti\u003c/em\u003e. The left annotation showed the immune pathways and the right annotation showed the canonical genes involved in the pathways. The color shows the percentage of the cells that express a certain gene in a cluster. \u003cstrong\u003ej, \u003c/strong\u003eThe expression of a series of vATPase subunit genes across the four mosquito species. The violin plot shows the distribution of gene expression levels per cell. The center line in the middle of the boxplot represents the mean read counts in each sample. The comparisons were analyzed using Mann-Whitney U test. P value ≤ 0.05 was considered as significantly different. *: p \u0026lt; 0.05, **: p \u0026lt; 0.01, ***: p \u0026lt; 0.001, ****: p \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/af073121221ec65001f657bf.png"},{"id":88750531,"identity":"3af753d3-dbc0-4bbc-b4ef-9269db5b142b","added_by":"auto","created_at":"2025-08-11 05:57:47","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":373338,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eViromes in mosquito midguts.\u003c/strong\u003e \u003cstrong\u003ea,\u003c/strong\u003eHeatmap of midgut viromes in each sample. Viral reads were normalized by RPM. Left and right annotations are the family and the name of the virus, respectively. \u003cstrong\u003eb,\u003c/strong\u003e Expression level (the upper) and positive rate (the lower) of \u003cem\u003eHanko iflavirus 1\u003c/em\u003e across all the mosquito samples. The thickened bar in the boxplot represents the mean read counts per cell in each sample. Except for those marked, all other pairwise comparisons showed significant differences. The expression level and positive rate were analyzed using Mann-Whitney U test and Fisher’s exact test, respectively. P value ≤ 0.05 was considered as significantly different. *: p \u0026lt; 0.05, **: p \u0026lt; 0.01, ***: p \u0026lt; 0.001, ****: p \u0026lt; 0.0001. \u003cstrong\u003ec-d,\u003c/strong\u003e The expression of DENV-2 in DENV-infected \u003cem\u003eAe. aegypti\u003c/em\u003eand \u003cem\u003eTiger mosquito bi-segmented tombus-like virus\u003c/em\u003e (TMBSTLV) in \u003cem\u003eAe. albopictus\u003c/em\u003e, respectively. The UMAPs show the viral abundance in cell clusters. Each dot represents a cell and the dot color represents the read counts. The barplots represent both the mean abundance per cell and positive rate in each cell clusters. alb: \u003cem\u003eAe. albopictus\u003c/em\u003e; aae: \u003cem\u003eAe. aegypti\u003c/em\u003e; aae_bl: \u003cem\u003eAe. aegypti\u003c/em\u003e with bloodmeal; aae_denv: DENV-infected \u003cem\u003eAe. aegypti\u003c/em\u003e; cxpip: \u003cem\u003eCx. p. pallens\u003c/em\u003e; cxtri: \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e; cxtri_bl: \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e with bloodmeal.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/a84fbff383d497e7a265fa07.png"},{"id":90475939,"identity":"273ee6c7-232b-4eaa-ad8b-2cc48ab12ebc","added_by":"auto","created_at":"2025-09-03 07:04:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5307272,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/771079fc-2be0-4b1d-86ca-3bc7ebdc4122.pdf"},{"id":88750524,"identity":"c66b3bec-9856-4e18-8b80-43e4900d4f23","added_by":"auto","created_at":"2025-08-11 05:57:47","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19324,"visible":true,"origin":"","legend":"Supplementary Table 1","description":"","filename":"STable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/65a70fc698e05fdd594d0108.docx"},{"id":88750526,"identity":"464dcc79-fce9-4ba7-b6a5-6f873398c502","added_by":"auto","created_at":"2025-08-11 05:57:47","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":515029,"visible":true,"origin":"","legend":"Supplementary Figures 1-3","description":"","filename":"SFigures20250725.docx","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/0116d4be33d914b98cd8da0b.docx"},{"id":88750527,"identity":"a1b1301f-634f-4a0e-ad92-de20f6e01a3a","added_by":"auto","created_at":"2025-08-11 05:57:47","extension":"csv","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":401864,"visible":true,"origin":"","legend":"Supplementary Dataset 1","description":"","filename":"SDataset1Othologousgenecomparisontable.csv","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/38b118714ff1fdb779b95c0d.csv"},{"id":88750536,"identity":"4f4b81aa-87ce-4d16-9e6b-53570cba1af8","added_by":"auto","created_at":"2025-08-11 05:57:47","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":5130366,"visible":true,"origin":"","legend":"Supplementary Dataset 2","description":"","filename":"SDataset2PairwiseDEGoffourmosquitospecies.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/c5f5af7793c51ba66b6447e2.xlsx"},{"id":88750681,"identity":"5316a2fd-04f5-49d7-b1ed-ad662f72e1cb","added_by":"auto","created_at":"2025-08-11 06:05:47","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":2756311,"visible":true,"origin":"","legend":"Supplementary Dataset 3","description":"","filename":"SDataset3DEGofeachclustersofmosquitoespreandpostbloodmeal.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/f4c63a6354de2b56f1746919.xlsx"},{"id":88750680,"identity":"ff7317ca-c0cd-4dca-ad97-a1dfa0f19260","added_by":"auto","created_at":"2025-08-11 06:05:47","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":734781,"visible":true,"origin":"","legend":"Supplementary Dataset 4","description":"","filename":"SDataset4DEGofeachclustersofAeaegyptiwithbloodmealmockversusDENVinfection.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/ead9f2ee44b182dd40cb7319.xlsx"},{"id":88750534,"identity":"bf5d1e1e-301d-47fa-a0da-822fe0c4d95f","added_by":"auto","created_at":"2025-08-11 05:57:47","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":260894,"visible":true,"origin":"","legend":"Supplementary Dataset 5","description":"","filename":"SDataset5MeanExpressionofDEGorthologsintheotherthreemosquitospeciescomparedwithAeaegypti.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/c3e775c376f1145b06f4353c.xlsx"},{"id":88750529,"identity":"6106f5d8-0e01-4bc6-bec5-a40cdd87f3c7","added_by":"auto","created_at":"2025-08-11 05:57:47","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":10984,"visible":true,"origin":"","legend":"Supplementary Dataset 6","description":"","filename":"SDataset6scRNAseqdatametrics.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/1edf89e10764c57f0c0a0a22.xlsx"},{"id":88750533,"identity":"0072aa14-ae2c-47ee-9235-08b10295bc52","added_by":"auto","created_at":"2025-08-11 05:57:47","extension":"csv","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":285990,"visible":true,"origin":"","legend":"Supplementary Dataset 7","description":"","filename":"SDataset7AeaegyptiNCBIEntrezVectorBasegeneidcomparisontable.csv","url":"https://assets-eu.researchsquare.com/files/rs-7214530/v1/86ec62d4d7071a494fe6650f.csv"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Midgut cell atlas and virome of four important mosquito species and immune landscapes of dengue virus infection","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMosquitoes (Culicidae) are the most important hematophagous arthropods in the world\u003csup\u003e1,2\u003c/sup\u003e. Mosquito-borne viruses (MBVs) caused millions of infection cases annually, posing severe threat to global public health\u003csup\u003e1\u003c/sup\u003e. The Family Culicidae consists of several genera, including \u003cem\u003eAedes\u003c/em\u003e, \u003cem\u003eCulex\u003c/em\u003e, and \u003cem\u003eAnopheles\u003c/em\u003e, with the former two being the major vectors for transmitting various mosquito-borne viral diseases (MBDs)\u003csup\u003e3,4\u003c/sup\u003e. Among these, \u003cem\u003eAe. aegypti\u003c/em\u003e is the major species that transmits MBVs including Dengue (DENV), Zika (ZIKV) and Chikungunya virus in tropical regions\u003csup\u003e5\u003c/sup\u003e. With the influence of the climate warming,\u003cem\u003e\u0026nbsp;Ae. aegypti\u003c/em\u003e has the potential to expand its range into colder regions, thereby may lead to more severe situation\u003csup\u003e6,7\u003c/sup\u003e. Similarly, \u003cem\u003eAe. albopictus\u0026nbsp;\u003c/em\u003eis cable to carry MBVs in temperate regions, including Europe and Asia\u003csup\u003e8,9\u003c/sup\u003e, further extending the region of these diseases. In addition, \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e is the primary vector of Japanese encephalitis virus (JEV) from temperate Asia to Europe\u003csup\u003e10,11\u003c/sup\u003e. \u003cem\u003eCx. pipiens pallens\u003c/em\u003e is the most common mosquito in human habitations across the temperate Northern Hemisphere and serves as the vector of West Nile virus (WNV), Usutu virus (USUV), and JEV\u003csup\u003e12–14\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eUpon ingesting an infectious viral blood meal, viruses can infect midgut, hemocyte, fat body and salivary gland of the mosquitoes, then can be transmitted to hosts through subsequent blood feeding. The midgut is the initial infection site and forms two infection barriers that impact viral pathogenesis\u003csup\u003e15\u003c/sup\u003e. In addition to its roles in food digestion and nutrition absorption, midgut also participates in many physiological processes such as epithelium replenishment, signaling regulation, microbial shaping, and immune reactions\u003csup\u003e16,17\u003c/sup\u003e. Moreover, the various cell types exhibit differential proviral or antiviral effects, highlighting the cell-specific tropism of MBVs\u003csup\u003e18,19\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRapidly developed single-cell RNA sequencing (scRNA-seq) technologies make it possible to reveal transcriptomic heterogeneity at single-cell level\u003csup\u003e20\u003c/sup\u003e. Currently, scRNA-seq technologies are primarily categorized into microfluidic-based and microwell-based methods, both of which have been well-established in mammalian cell studies, demonstrating their robustness and reliability\u003csup\u003e21–24\u003c/sup\u003e. Accumulating evidence has highlighted the potential of scRNA-seq in identifying cell subtypes and annotating virus-infected mosquitoes\u003csup\u003e25–27\u003c/sup\u003e. This technology has enabled researchers to dissect the complex cellular landscapes of mosquito tissues with unprecedented resolution. To date, however, the application of scRNA-seq to mosquito midgut research remains limited to few species. Midgut cell atlases generated by scRNA-seq are only available for \u003cem\u003eAe. aegypti\u003c/em\u003e, \u003cem\u003eAnopheles gambiae,\u003c/em\u003e and \u003cem\u003eCx. tarsalis\u003c/em\u003e\u003csup\u003e25–28\u003c/sup\u003e. For other medically important vector mosquitoes, such comprehensive cellular resources are still absent, representing a significant gap in our understanding of mosquito biology and vector competence. Furthermore, unlike well-established animal models, there are no relatively standardized single-cell preparation protocols for scRNA-seq workflow in insects. Variations in the in-house developed protocols across studies may lead to different data quality metrics, thereby introducing bias in cross-dataset comparisons. For instance, in the context of midgut viral infection dynamics, a scRNA-seq study on WNV-infected \u003cem\u003eCx. tarsalis\u0026nbsp;\u003c/em\u003edemonstrated a correlation between immune gene expression levels and viral RNA loads in individual midgut cells, while another scRNA-seq investigation on \u003cem\u003eAe. aegypti\u003c/em\u003e revealed the transcriptomic differences among midgut cell subtypes following ZIKV infection\u003csup\u003e26,27\u003c/sup\u003e. Similarly, midgut cell populations in \u003cem\u003eAe. aegypti\u003c/em\u003e exhibited heterogeneous transcriptomes when exposed to DENV infection, however, a comprehensive understanding of the specific cell types and genes involved in the DENV-midgut interface at the cellular level is still lacking. To date, all scRNA-seq studies on mosquitoes have relied on microfluidic-base methods, yet our previous research has highlighted a notable limitation in handling low-input or low-quality samples\u003csup\u003e25\u003c/sup\u003e. Furthermore, emerging evidence suggests that the shear forces generated by microfluidics in RNA capture may also compromise the transcript quality\u0026nbsp;\u003csup\u003e29\u003c/sup\u003e. In contrast, the microwell-based methods exhibited its compatibility with low-quality input samples and more efficient high-quality RNA capture\u003csup\u003e29–31\u003c/sup\u003e. Given the challenges in preparing high-quality single-cell suspension from mosquitoes\u003csup\u003e24\u003c/sup\u003e, the microwell-based methods may offer significant advantages for mosquito studies, thereby facilitating more accurate and comprehensive analyses of mosquito cell transcriptomes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this study, we aimed to facilitate cross-species analysis by developing a compatible single-cell preparation protocol for both \u003cem\u003eAedes\u003c/em\u003e and \u003cem\u003eCulex\u003c/em\u003e mosquitoes. Utilizing a microwell-based platform, we successfully established the midgut cell atlases for four important mosquito species: \u003cem\u003eAe. aegypti\u003c/em\u003e, \u003cem\u003eAe. albopictus\u003c/em\u003e, \u003cem\u003eCx. p. pallens\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e. Based on these, the DENV-2 infection dynamics in \u003cem\u003eAe. aegypti\u003c/em\u003e midgut at cellular level have been conducted to identify the critical cell clusters and genes associated with infection. Virome profies in the midguts of \u003cem\u003eAedes\u003c/em\u003e and \u003cem\u003eCulex\u003c/em\u003e mosquito were also investigated. Our study provides fundamental insights into the cellular composition of four important mosquito species and facilitates research on virus-midgut interactions.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eThe midgut cell atlases of four mosquito species\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo compare the cellular composition among \u003cem\u003eAe. aegypti\u003c/em\u003e, \u003cem\u003eAe. albopictus\u003c/em\u003e, \u003cem\u003eCx. p. pallens\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e, we performed scRNA-seq experiments with the midgut of glucose-fed female adults at 7 days post eclosion (dpe)(Fig. 1a). The valid cells were recovered and clustered into distinct types using Scanpy\u003csup\u003e32\u003c/sup\u003e. Given the limited comparative data on midgut cellular composition in diverse vector mosquitoes, we implemented a multi-faceted strategy for cell type annotation: (I) For \u003cem\u003eAe. aegypti\u003c/em\u003e, we used the marker genes defined by the previous studies on the midgut of \u003cem\u003eDrosophila\u003c/em\u003e and \u003cem\u003eAe. aegypti\u003c/em\u003e (Supplementary Table 1). (II) For the other mosquito species, we referred the marker genes of \u003cem\u003eAe. aegypti\u003c/em\u003e, as well as the top unique gene in the clusters identified in this study (Supplementary Table 1). This approach ensured consistency and comparability across species. Our analysis revealed that the known midgut cell types, including intestinal stem cells (ISC), enteroblasts (EB), cardia cells, enterocytes (EC), EC-like cells, enteroendocrine cells (EE), and visceral muscle cells (VM), were conserved among the four mosquito species, except for that some of them lacked several subdivided EC-like or EE populations (Fig. 1b-e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe midgut cells of \u003cem\u003eAe. aegypti\u003c/em\u003e were clustered into 12 distinct cell types (Fig. 1b, f). Two ISC/EB clusters were identified using the marker gene \u003cem\u003efibulin 1\u003c/em\u003e and C-type lysozyme A(\u003cem\u003eLYSC11\u003c/em\u003e), with one of the clusters named ISC/EB-prol was distinguished by high expression of the gene proliferating cell nuclear antigen (\u003cem\u003ePCNA\u003c/em\u003e)\u003csup\u003e27,33,34\u003c/sup\u003e. Cardia clusters were identified based on high expression of the antimicrobial peptides (AMPs) gene Gambicin (\u003cem\u003eGAM1\u003c/em\u003e)\u003csup\u003e33,34\u003c/sup\u003e. Cardia-1 was identified by enrichment for C-type lysozyme (\u003cem\u003eLYSC\u003c/em\u003e)\u003csup\u003e27,33,35\u003c/sup\u003e. EC cluster was identified by expression of \u003cem\u003eNubbin\u003c/em\u003e, a key marker for mature enterocytes\u003csup\u003e33,35\u003c/sup\u003e. EC-like clusters are identified mainly by high expression of carbonic anhydrase 7 (\u003cem\u003eCAH7\u003c/em\u003e) and Chitinase 10 (\u003cem\u003eCht10\u003c/em\u003e), but low expression of \u003cem\u003eNubbin\u003c/em\u003e, in which EC-like-3 was distinguished by high expression of sodium-dependent nutrient amino acid transporter 1 (\u003cem\u003eNAAT\u003c/em\u003e)\u003csup\u003e33,34\u003c/sup\u003e. We further identified three EE clusters based on the expression of \u003cem\u003eprospero\u003c/em\u003e\u003csup\u003e33,35\u003c/sup\u003e. The EE-1 and EE-2 cluster were distinguished by strong expression of the gene \u003cem\u003eorcokinin\u003c/em\u003e and neuropeptide F (\u003cem\u003eNPF\u003c/em\u003e), respectively\u003csup\u003e33\u0026ndash;35\u003c/sup\u003e. The former gene is involved in positive regulation of oogenesis and the latter gene is involved in metabolic pathways, indicating their distinct functions in regulating the physiological activity in mosquitoes\u003csup\u003e36,37\u003c/sup\u003e. The EE-3 cluster was identified by exhibiting a deficiency in the expression of both of the aforementioned genes. VM cluster was identified by high expression of \u003cem\u003eactin\u003c/em\u003e instead of \u003cem\u003etitin\u003c/em\u003e\u003csup\u003e25,33,34\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFor \u003cem\u003eAe. albopictus\u003c/em\u003e, the midgut cells were clustered into 10 distinct populations (Fig. 1c, f). Two ISC/EB clusters were identified by \u003cem\u003efibulin 1\u003c/em\u003e alone\u003csup\u003e33,34\u003c/sup\u003e, yet ISC/EB-prol cluster was distinguished by high expression of \u003cem\u003ePCNA\u003c/em\u003e\u003csup\u003e27\u003c/sup\u003e. We identified Cardia-1 by specific expression of \u003cem\u003eGAM1\u003c/em\u003e, chymotrypsin-2 (\u003cem\u003eCHYM2\u003c/em\u003e) and \u003cem\u003eLYSC\u003c/em\u003e, while Cardia-2 was defined by high expression of \u003cem\u003eGAM1\u003c/em\u003e, \u003cem\u003eCHYM2\u003c/em\u003e\u003csup\u003e33,34\u003c/sup\u003e. EC was identified by significant expression of \u003cem\u003eNubbin\u003c/em\u003e, while EC-like clusters were distinguished by high expression of \u003cem\u003eCAH7\u003c/em\u003e but low expression of \u003cem\u003eNubbin\u003c/em\u003e. VM was characterized by expression of \u003cem\u003eactin\u003c/em\u003e. There were two EE clusters identified by \u003cem\u003eCalexcitin-1\u003c/em\u003e, which encoded a memory-related protein in \u003cem\u003eDrosophila\u003c/em\u003e\u003csup\u003e38\u003c/sup\u003e. The EE-1 population was distinguished by enrichment for \u003cem\u003eprospero\u003c/em\u003e, \u003cem\u003eorcokinin\u003c/em\u003e and \u003cem\u003eNPF\u003c/em\u003e\u003csup\u003e33\u0026ndash;35\u003c/sup\u003e. Interestingly, the marker gene \u003cem\u003eNAAT\u003c/em\u003e was highly expressed in EE-2 but lowly expressed in EC-like populations. Finally, HC population was also identified by significant high expression of \u003cem\u003eLRIM16\u003c/em\u003e without Nimrod B2 (\u003cem\u003eNimB2)\u003c/em\u003e \u003csup\u003e25,27,28,34\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn \u003cem\u003eCx. p. pallens\u003c/em\u003e, there are 10 annotated midgut cell clusters (Fig. 1d, f), in which ISC/EB, Cardia, EE and VM were identified by homologous marker gene consistent with those employed in \u003cem\u003eAe. aegypti\u003c/em\u003e. A single EE population (EE-1) was identified, which lack expression of \u003cem\u003eCalexcitin-1\u003c/em\u003e that is absent in \u003cem\u003eCx. p. pallens\u003c/em\u003e. The Cardia clusters share a common marker \u003cem\u003eGAM1\u003c/em\u003e, yet Cardia-1 and Cardia-2 are distinguished using the expression level of \u003cem\u003eGAM1\u003c/em\u003e instead of \u003cem\u003eLYSC\u003c/em\u003e. We identified the EC cluster based on high expression of \u003cem\u003eNubbin\u003c/em\u003e and proton-coupled amino acid transporter protein (\u003cem\u003eCG1139\u003c/em\u003e), whose gene ortholog in \u003cem\u003eDrosophila\u003c/em\u003e participates in both the insulin signaling pathway and hemolymph amino acids release\u003csup\u003e39\u003c/sup\u003e. Due to the absence of \u003cem\u003eCPA-VII\u003c/em\u003e orthologs in \u003cem\u003eCx. p. pallens\u003c/em\u003e, EC-like populations were identified by significant high expression of \u003cem\u003eCht10\u003c/em\u003e coupled with low expression of \u003cem\u003eNubbin\u003c/em\u003e. These EC-like clusters could be further refined by expression of \u003cem\u003eNAAT\u003c/em\u003e and \u003cem\u003eBTBD3\u003c/em\u003e\u003csup\u003e33,34\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFor \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e, the midgut cell populations were divided into 11 clusters (Fig. 1e, f). ISC/EB clusters were identified using significant high expression of \u003cem\u003efibulin 1\u003c/em\u003e and \u003cem\u003eesg\u003c/em\u003e, with ISC/EB-prol was distinguished by high expression of \u003cem\u003ePCNA\u003c/em\u003e\u003csup\u003e27\u003c/sup\u003e. The presence of low \u003cem\u003eKlu\u003c/em\u003e but high \u003cem\u003eesg\u003c/em\u003e expression was observed in the ISC/EB clusters of \u003cem\u003eCx. tritaeniorhynchus,\u003c/em\u003e indicating the ISC/EB clusters might be composed primarily of ISCs\u003csup\u003e33\u0026ndash;35\u003c/sup\u003e. EC and VM were identified by significant high expression of \u003cem\u003eNubbin\u003c/em\u003e and \u003cem\u003eactin\u003c/em\u003e, respectively\u003csup\u003e25,33\u003c/sup\u003e. Due to the absence of \u003cem\u003eGAM1\u003c/em\u003e and \u003cem\u003eLYSC\u003c/em\u003e orthologs in \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e, Cardia populations were identified by high expression of \u003cem\u003eCHYM2\u003c/em\u003e\u003csup\u003e40\u003c/sup\u003e. EC-like clusters were identified by significant high expression of \u003cem\u003eCht10\u003c/em\u003e but low expression of \u003cem\u003eNubbin\u003c/em\u003e, with the absence of EC-like-2. EC-like-1 differentiated from EC-like-3 on expression of \u003cem\u003eKLK7\u003c/em\u003e, \u003cem\u003eMAP7\u003c/em\u003e and NAAT\u003csup\u003e33,34\u003c/sup\u003e. Since the canonical marker genes such as \u003cem\u003eprospero\u003c/em\u003e and \u003cem\u003eNPF\u003c/em\u003e were absent, we identified EE populations using neuropeptide CCHamide-2 (\u003cem\u003eCCHa2\u003c/em\u003e), \u003cem\u003eSCG5\u003c/em\u003e, \u003cem\u003eCABP\u003c/em\u003e and \u003cem\u003eFBG/G\u003c/em\u003e\u003csup\u003e33,35\u003c/sup\u003e. CCHa2 coded a sugar-sensitive peptide that could induce insulin-like peptides production and release to promote growth\u003csup\u003e41\u0026ndash;43\u003c/sup\u003e. HC cluster was identified by significant high expression of \u003cem\u003eNimB2\u003c/em\u003e without \u003cem\u003eLRIM16\u003c/em\u003e\u003csup\u003e27,34\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAdditionally, we compared the cellular proportions of each cell populations among the mosquito species. Except for VM, other midgut cell clusters had significantly different cellular proportions between the genus \u003cem\u003eAedes\u003c/em\u003e and \u003cem\u003eCulex\u003c/em\u003e (Fig. 1g). Notably, the two genera showed opposite proportions between Cardia clusters: the \u003cem\u003eCulex\u003c/em\u003e mosquitoes have the higher percentage of Cardia-1 cells, while the \u003cem\u003eAedes\u003c/em\u003e mosquitoes have an approximate 5-fold higher of Cardia-2 (Fig. 1g). Both ISC/EB-1 and ISC/EB-prol clusters of \u003cem\u003eCulex\u003c/em\u003e mosquitoes have higher proportions than that of \u003cem\u003eAedes\u003c/em\u003e mosquitoes (Fig. 1g). Further cross-species comparisons exhibit significant differences in the percentage of all midgut cell populations in any two mosquito species (Fig. 1h). The cluster ISC/EB-1 is more abundant in both \u003cem\u003eAe. aegypti\u003c/em\u003e (20.41%) and \u003cem\u003eCx. p. pallens\u003c/em\u003e (24.28%), while the cluster Cardia-2 and EC are the biggest cell populations in \u003cem\u003eAe. albopictus\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e, respectively (Fig. 1h).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe transcriptomic features of midgut cell populations among the four mosquito species (531 words)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further elucidate the functional diversity of midgut cells across the four mosquito species, we characterized the transcriptional profiles of each cell population and compared their gene expression features among the mosquito species. This analysis was performed by integrating the single-cell transcriptomes of all mosquitoes using scvi-tools\u003csup\u003e44\u003c/sup\u003e. To ensure robust comparability, orthologous genes from different species were manually curated and classified to unified gene clusters, which were used as dimensional framework for the analysis (Supplementary Dataset 1). Single-cell integration revealed not only conserved cell subpopulations among different mosquito species, but also similar midgut cell composition (Fig. 2a-e). All the cell populations pre-/post-integration remained consistent, except that the EE populations no longer formed distinct subclusters (Fig. 2f-g). Across the genera \u003cem\u003eAedes\u003c/em\u003e and \u003cem\u003eCulex\u003c/em\u003e, we performed comparisons on the midgut cell clusters that exist in all the mosquito species given the absence of several cell clusters. The analysis revealed that these clusters (Cardia-2, EE-1, and VM) respectively exhibited conserved transcriptomic features, in which the most proportion of cells were integrated into corresponding clusters (Fig. 2f). Transcriptional profiles are conserved in the ISC/EB populations but divergent in their subclusters ISC/EB-1 and ISC/EB-prol, suggesting both intrageneric and intrageneric transcriptomic similarity between the two clusters. Similar conserved patterns are also observed among EC and EC-like-1 clusters (Fig. 2f). Notably, cluster Cardia-1 of two genera were annotated as two different Cardia clusters post-integration (Cardia-1 for \u003cem\u003eAedes\u003c/em\u003e, Cardia-2 for \u003cem\u003eCulex\u003c/em\u003e, Fig. 2f). At species level, the transcriptional profiles of the intergeneric conserved clusters and the EC-like-2, EC-like-3 and HC clusters, which existed in a subset of species, remained conserved among all the mosquito species (Fig. 2g). In the case of \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e, their EE-2 remained conserved, but the EE-2 cluster of \u003cem\u003eAe. albopictus\u003c/em\u003e has similar transcriptomic features to the cluster EC-like-3 rather than EE (Fig. 2g). Interestingly, the EE-3 cluster of \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e showed transcriptomic divergences with that of \u003cem\u003eAe. aegypti\u003c/em\u003e, yet it exhibited similarity to the Cardia-1 cluster post integration (Fig. 2g). In addition, HC clusters are transcriptomic conserved across these two mosquito species.\u003c/p\u003e\n\u003cp\u003eSubsequently, we focused on identifying top DEGs in cell populations exhibiting or inter-specific differences on transcriptomic features by performing pairwise comparisons across the four mosquito species (Supplementary Dataset 2). While DEGs across non-EE clusters were predominantly enriched in digestive enzymes, the EE cluster exhibited inter-specific differences in both metabolic genes and pathogen-associated genes, with the most pronounced differences between\u003cem\u003e\u0026nbsp;Ae. aegypti\u003c/em\u003e and two \u003cem\u003eCulex\u0026nbsp;\u003c/em\u003emosquitoes (Fig. 2h). When comparing the EE clusters of \u003cem\u003eAe. aegypti\u003c/em\u003e with that of \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e, \u003cem\u003eAe. aegypti\u003c/em\u003e exhibited significantly higher expression levels of the \u003cem\u003eIA-2\u003c/em\u003e gene, which is involved in digestive tract development and regulation of secretion (Fig. 2h). Two ATP-dependent RNA helicase dbp2 are highly expressed in \u003cem\u003eAe. aegypti\u003c/em\u003e (Fig. 2h). These genes are involved in mRNA splicing and RNP complex assembly, with some family members potentially play roles in viral RNA recognition and cellular antiviral responses\u003csup\u003e45,46\u003c/sup\u003e. In addition, the \u003cem\u003eCCHa1\u003c/em\u003e is also highly expressed in \u003cem\u003eAe. aegypti\u003c/em\u003e (Fig. 2h). It was reported that \u003cem\u003eCCHa1\u003c/em\u003e can be upregulated by protein-rich food and might participate in water-ion homeostasis maintenance post-bloodmeal\u003csup\u003e43\u003c/sup\u003e. This change was also detected in the EE clusters between \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. p. pallens\u003c/em\u003e (Fig. 2h).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDynamics of midgut cell populations post-bloodmeal in \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo characterize the cellular composition and gene expression signatures of midgut cell populations caused by bloodmeal, the scRNA-seq data of midguts of two representative mosquitoes, \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e at 7 days post bloodmeal (dpb, bloodmeal at 7 dpe), were integrated with their corresponding cell atlases (glucose mock). For \u003cem\u003eAe. aegypti\u003c/em\u003e, we identified a new EE cluster named EE-4, characterized by significant high expression of the \u003cem\u003eCCHa2\u003c/em\u003e compared to the other EE subclusters (Fig. 3a-c, Supplementary Fig. 1a). And the HC cluster absent in its glucose mock cell atlas by significant high expression of \u003cem\u003eLRIM16\u003c/em\u003e and \u003cem\u003eNimB2\u003c/em\u003e (Fig. 3a-c). The marker gene used for the other cell populations at 7 dpb were consistent with the glucose mock. Except for EC-like-1, EE-4 and HC clusters, the proportions of most cell populations of \u003cem\u003eAe. aegypti\u003c/em\u003e at 7 dpb were significantly different compared to the glucose mock, in which the ISC/EB-1 and EC clusters showed the most pronounced dynamics, which substantially increased and decreased at 7 dpb, respectively (Fig. 3d). For \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e, both the cell populations and their marker genes at 7 dpb remained consistent with the mock (Fig. 3g-h). The absent cell cluster EC-like-2 was identified by the consistent markers but different expression levels with EC-like-1 (Fig. 3i, Supplementary Fig. 1b). Different from \u003cem\u003eAe. aegypti\u003c/em\u003e, only the proportions of ISC/EB, EC and EC-like clusters varied between \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e at 7 dpb and the mock (Fig. 3j). Interestingly, at 7 dpb, the shared clusters ISC/EB-1, ISC/EB-prol and EC exhibited opposing trends between \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eWe then characterized the top upregulated/downregulated DEGs of each cell cluster between the mosquitoes pre- and post-bloodmeal, respectively (Supplementary Dataset 3). For \u003cem\u003eAe. aegypti,\u0026nbsp;\u003c/em\u003ethe broadly significant downregulation of the gene family that are involved in stress response including the gene families of protein lethal(2)essential for life [\u003cem\u003el(2)efl\u003c/em\u003e] and heat shock protein 70 (\u003cem\u003ehsp70\u003c/em\u003e) were observed across the cell clusters after bloodmeal(Supplementary Fig. 1c). A broadly significant increase of the gene neurogenic locus notch homolog protein 1 (\u003cem\u003eNotch1\u003c/em\u003e) was observed across the cell clusters post-bloodmeal (Supplementary Fig. 1c). The notch pathway plays an important role in EB differentiation into EC and EE in \u003cem\u003eDrosophila\u003c/em\u003e\u003csup\u003e47\u003c/sup\u003e. The upregulation of mitochondrial genes in the EC and EC-like clusters further reflects enhanced metabolic activity (Fig. 3e).\u0026nbsp;Additionally, the peptidoglycan recognition protein LB (\u003cem\u003ePGRPLB\u003c/em\u003e) involved immune pathway was upregulated in the EC and EC-like clusters. In the Cardia clusters, two genes lysozyme C-1 (\u003cem\u003eLYSC4\u003c/em\u003e) and glutathione S-transferase 1 (\u003cem\u003eGSTD4\u003c/em\u003e) were upregulated following a bloodmeal (Fig. 3f). For \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e, the similar downregulation of genes involved in stress response was also observed after bloodmeal (Supplementary Fig. 1d). Notably, the ISC/EB, EE-1 and EC-like-1 clusters exhibited the significantly upregulated gene \u003cem\u003eesg\u003c/em\u003e, which is the marker gene of ISC (Fig. 3k), suggesting that bloodmeal might induce the differentiation of ISC to ECs. The gene \u003cem\u003ePCNA\u003c/em\u003e also showed the significantly higher expression level in two ISC/EB clusters (Fig. 3i), indicating their proliferative states\u003csup\u003e27,48\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMetabolism across the uninfected mosquito midguts (319 words)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mosquito midgut plays a crucial role in the metabolism of various nutrients. To compare the differences of digestive functions across the uninfected mosquito midguts, we examined the gene expression associated with metabolism (Fig. 4a). Regarding sugar metabolism, the expression of amylases and maltases (AAEL000647 and AAEL000667) was inter-generic different; for \u003cem\u003eAedes\u003c/em\u003e mosquitoes, both of them showed a broad expression across the cell clusters such as Cardia, EC and EE clusters; for \u003cem\u003eCulex\u003c/em\u003e mosquitoes, these two genes are only highly expressed in the Cardia clusters (Fig. 4a). Interestingly, a glucosidase gene (AAEL020371) was highly expressed in \u003cem\u003eAe. albopictus\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e, but lowly expressed in \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. p. pallens\u003c/em\u003e (Fig. 4a). For lipid metabolism, all cell clusters exhibited low expression of lipid-related enzymes, with higher expression in EC and EC-like clusters (Fig. 4a). In \u003cem\u003eAe. aegypti\u003c/em\u003e post-bloodmeal, the expression level of the lipase genes \u003cem\u003eGlllspla2\u003c/em\u003e and AAEL001837 was obviously higher than that pre-bloodmeal (Fig. 4a). For peptide metabolism, similar expression patterns of the most peptidases are observed among the mosquito samples (Fig. 4a). Broad expression of specific members was detectable across most peptidase categories, especially in the serine endopeptidase (Fig. 4a). In \u003cem\u003eAedes\u003c/em\u003e mosquito, the serine endopeptidase AAEL003060 is highly expressed by all the clusters. In addition, the enrichment of peptidase genes is observed in EC and EC-like clusters (Fig. 4a). Except for digestive functions, midguts also broadly anticipate other physiological processes. To characterize the biological functions of each cluster across the mosquito samples, we manually collected and categorized the GO terms into distinct groups (Fig. 4b). For \u003cem\u003eAedes\u003c/em\u003e mosquitoes, the EC and EC-like clusters mainly contribute to metabolism, while the EE clusters perform signaling functions (Fig. 4b). However, two ISC/EB clusters in \u003cem\u003eAe. aegypti\u003c/em\u003e shows no enrichment in cell proliferation. Midgut epithelial cells broadly show enrichment in transmembrane transport both in pre- and post-bloodmeal, suggesting the robust maintenance of water-ion homeostasis in \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e (Fig. 4b).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDynamics of midgut cell populations in DENV-infected \u003cem\u003eAedes\u003c/em\u003e \u003cem\u003eaegypti\u0026nbsp;\u003c/em\u003e(909)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the dynamic changes in midgut cell populations caused by DENV infection, we examined \u003cem\u003eAe. aegypti\u003c/em\u003e at 7 days post infection (dpi, infectious bloodmeal at 7 dpe). We integrated and analyzed the midgut cell data of \u003cem\u003eAe. aegypti\u003c/em\u003e from the glucose mock, the uninfectious bloodmeal mock, and the DENV infection (Fig. 5a-b). Comparing the uninfectious and infectious bloodmeal groups at the same time point (7 dpi / 14 dpe), most cell clusters and their marker genes are consistent (Supplementary Fig. 2a). Notably, a new cluster (SV2/UNC-93) was identified by significant high expression of the synaptic vesicle protein-2 (\u003cem\u003eSV2\u003c/em\u003e) and \u003cem\u003eUNC-93\u003c/em\u003e, the former is a homolog of mammalian SV2 and participate in regulation of vesicle transport and exocytosis and the latter is involved in regulating potassium channels (Fig. 5c)\u003csup\u003e49\u003c/sup\u003e. Proportion of the SV2/UNC-93 cluster of the DENV infection is significantly higher than that of the bloodmeal mock (Fig. 5d). For ISC/EB and EC-like-2 clusters of the DENV infection, the proportions of cell populations are significantly higher than those of the bloodmeal mock, while Cardia and EC-like-1 clusters are opposite (Fig. 5d). The percentages of all EE populations of the DENV infection are lower than their counterparts of the bloodmeal mock (Fig. 5d). In addition, two cell populations including HC and Fat Body Cell (FBC) clusters were also identified with low proportions (Fig. 5d). The FBC cluster was identified by significant expression of apolipophorin-3 (\u003cem\u003eApo3\u003c/em\u003e)\u003csup\u003e26,27\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eTo explore the cellular populations and their associated genes involved in the response to DENV infection in \u003cem\u003eAe. aegypti\u003c/em\u003e, the analysis of DEGs was performed on each cell clusters between the bloodmeal mock and DENV infection. A total of 987 significant DEGs (|de_coef| \u0026gt;= 0.693 / |log\u003csub\u003e2\u003c/sub\u003eFC| \u0026gt;= 1, p \u0026lt; 0.05) were identified, of which 281 and 706 were upregulated and downregulated, respectively (Supplementary Dataset 4). The upregulated DEGs of each cluster were fewer than their corresponding downregulated DEGs (Supplementary Fig. 2b). This pattern suggests a predominant downregulation of gene expression across various cell types in response to DENV infection. The expression dynamics of the DEGs in the corresponding cell clusters were further investigated (Fig. 5e-h). In each cell cluster post infection, downregulated genes showed larger changes of mean expression levels compared to upregulated genes (Supplementary Dataset 4). The gene families of \u003cem\u003ehsp70,\u003c/em\u003e \u003cem\u003el(2)efl\u003c/em\u003e, \u003cem\u003etrp\u003c/em\u003e and \u003cem\u003eGAAD45\u003c/em\u003e associated with stress response were broadly shared in the downregulated DEGs across all midgut cell clusters (Fig. 5e, Supplementary Dataset 4). In the EC cluster, one of the antimicrobial peptide genes\u0026mdash;\u003cem\u003eGAM1\u003c/em\u003e\u0026mdash;was broadly expressed across the cells pre-infection and showed a significant upregulation post-infection (Fig. 5e). In the EC-like-1 cluster, the significant upregulation of the component of the signal peptide complex (SPC), \u003cem\u003espc22/23\u003c/em\u003e was observed (Fig. 5e), the SPC is vital for the cleavage of structural protein and virion release of orthoflaviviruses\u003csup\u003e50\u003c/sup\u003e. In two ISC/EB populations, the expression of gene FK506-binding protein 39kD (Fkbp39) significantly increased post-infection (Fig. 5f). For EE clusters, genes associated with signal transduction such as \u003cem\u003eNPF\u003c/em\u003e, \u003cem\u003eMip\u003c/em\u003e, \u003cem\u003esNPF\u003c/em\u003e, \u003cem\u003eboca\u003c/em\u003e and \u003cem\u003embc\u003c/em\u003e were significantly upregulated in the EE clusters, while a significant increase of the expression of \u003cem\u003eHlc\u003c/em\u003e in the EE-3 cluster\u0026mdash;an orthologous gene of \u003cem\u003eDrosophila\u003c/em\u003e DEAD box ATP-dependent RNA helicase 56 (\u003cem\u003eDDX56\u003c/em\u003e) (Fig. 5g)\u003csup\u003e46\u003c/sup\u003e. In addition, mitochondria-related genes \u003cem\u003eACADSB\u003c/em\u003e and \u003cem\u003eChchd3\u003c/em\u003e were significantly upregulated in the EE-4 cluster (Fig. 5g). In the newly discovered cluster SV2/UNC-93, it was notable that a series of Vacuolar-type proton ATPase (\u003cem\u003evATPase\u003c/em\u003e) subunit genes (\u003cem\u003evATPase-1\u003c/em\u003e, \u003cem\u003evATPase-d1\u003c/em\u003e, \u003cem\u003evATPase-F\u003c/em\u003e, \u003cem\u003evATPase-G\u003c/em\u003e, \u003cem\u003eVha16-1\u003c/em\u003e, \u003cem\u003eVhaPPA1\u003c/em\u003e and \u003cem\u003eVhaSFD\u003c/em\u003e) were observed to be post-infection (Fig. 5h). The gene E3 ubiquitin-protein ligase RFWD2 (\u003cem\u003eRFWD2\u003c/em\u003e) was also significantly upregulated (Fig. 5h).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo further understand the immune response in DENV-infected \u003cem\u003eAe. aegypti\u003c/em\u003e, we compiled a list of canonical and potential immune genes from previous studies and examined the gene expression of them\u003csup\u003e17\u003c/sup\u003e. The majority of immune genes exhibited downregulation in response to viral infection (Fig. 5i). Components of the Toll, IMD and PGRP pathways exhibited broad expression across midgut cell clusters pre- versus post-infection, with high enrichment in EC, EC-like-1 and EE clusters (Fig. 5i). The gene \u003cem\u003ePGRPLB\u003c/em\u003e is dominant in the Cardia-2 cluster (Fig. 5i). Interestingly, expression of the gene AAEL000200 involved in JAK-STAT pathway increased in the FBC cluster but decreased in the SV2/UNC-93 cluster (Fig. 5i). Among AMPs, the gene \u003cem\u003eGAM1\u003c/em\u003e was broadly expressed in all the cell clusters, predominant in the Cardia clusters, and \u003cem\u003eGAM1\u003c/em\u003e expression showed an increase in SV2/UNC-93 cluster post infection (Fig. 5i). Notably, the SV2/UNC-93 cluster exhibited highly specific expression of defensin C (\u003cem\u003eDEFC\u003c/em\u003e) and abdomen-specific antimicrobial peptide holotricin (\u003cem\u003eGRRP\u003c/em\u003e) pre-infection, which was dramatically reduced post-infection\u003csup\u003e17,34\u003c/sup\u003e. For lysozymes, \u003cem\u003eLYSC7B\u003c/em\u003e is primarily expressed in the Cardia-1 cluster, while \u003cem\u003eLYSC11\u003c/em\u003e is dominant in the ISC/EB clusters. In addition, there was also a dramatic decrease of \u003cem\u003eLYSC4\u003c/em\u003e in the SV2/UNC-93 cluster post-infection (Fig. 5i).\u003c/p\u003e\n\u003cp\u003ePrevious studies have demonstrated that vector competence for the same virus varies among mosquito species, implying that host factors playing important role in virus transmisision\u003csup\u003e51,52\u003c/sup\u003e. Notably, comparative analyses of \u003cem\u003eAe. aegypti\u003c/em\u003e strains revealed distinct host factor signatures between susceptible and refractory phenotypes, suggesting that basal-level gene expression profiles could contribute to the divergence\u003csup\u003e53,54\u003c/sup\u003e. Therefore, we compared the basal-level expression of the genes orthologous with DEGs identified in DENV-infected \u003cem\u003eAe. aegypti\u003c/em\u003e in all vector mosquitoes (Fig. 5j, Supplementary Dataset 5). A series of vATPase subunit genes upregulated in DENV-infected \u003cem\u003eAe. aegypti\u003c/em\u003e showed the highest basal expression in \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e compared to other mosquitoes except \u003cem\u003evATPase-G\u003c/em\u003e (Fig. 5j).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eViromes of mosquito midguts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrevious studies have documented viral communities in various mosquito species (using single or pooled mosquito samples), including both field collected and lab reared populations, yet the midgut\u0026mdash;where arboviruses first establish infection\u0026mdash;has seldom been examined in isolation\u003csup\u003e55,56\u003c/sup\u003e. To characterize the viral composition within mosquito midguts, virome profiling was performed in this study. The top 10 most abundant viruses identified across samples belong to 5 recognized families (\u003cem\u003eIflaviridae\u003c/em\u003e, \u003cem\u003eFlaviviridae\u003c/em\u003e, \u003cem\u003eTombusviridae, Totiviridae,\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;Rhabdoviridae\u003c/em\u003e), together with an unclassified group (Fig. 6a). With the exception of DENV-2 (an arbovirus), the other detected viruses are either arthropod-specific viruses (ASVs) or of unknown hosts. Notably, DENV-2 was only detected in experimentally infected samples. Hanko iflavirus 1 (HKIFV1) and L-A virus were widespread across all samples, particularly in \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e (Fig. 6a-b), and the virome of \u003cem\u003eAe. albopictus\u003c/em\u003e was featured by a predominant proportion of \u003cem\u003eTombusviridae\u003c/em\u003e (Fig. 6a).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMinimal changes in virome composition were observed between glucose-fed and uninfected bloodmeal groups for both \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e (Fig. 6a). Following DENV-2 infection, both the expression level and infection rate of HKIFV1 significantly decreased in \u003cem\u003eAe. aegypti\u003c/em\u003e (Fig. 6b). DENV-2 was broadly distributed across all midgut cell clusters without obvious tropism, although the highest viral loads occurred in the EC and EE clusters (Fig. 6a,c). Tiger mosquito bi-segmented tombus-like virus (TMBSTLV) is widely distributed in \u003cem\u003eAe. albopictus\u003c/em\u003e across Asia, America and Europe, with the capacity to readily induce dsRNA and siRNA generation in mosquitoes\u003csup\u003e57,58\u003c/sup\u003e. Here, TMBSTLV was widely detected at low levels across all midgut cells in \u003cem\u003eAe. albopictus\u003c/em\u003e, but showed the obvious tropism to the HC cluster(Fig. 6d).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we constructed comprehensive midgut cell atlas and virome for four major vector mosquitoes, providing detailed insights into the cellular composition, physiological, and infection-driven features of mosquito midgut.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCurrent scRNA-seq technologies for single-cell capture and isolation are primarily divided into two categories, microfluidic-based and microwell-based method\u003csup\u003e21,59\u003c/sup\u003e. The microwell-based methods capture single cells by distributing them into chips containing millions of microwell arrays through physiological settlement\u003csup\u003e21,60\u003c/sup\u003e, which have been extensively applied in research associated with vertebrate demonstrating its capability to capture high-quality RNA and reduce microfluidics-induced stress\u003csup\u003e29,31,61–63\u003c/sup\u003e. For the first time, we implemented the microwell-based scRNA-seq to mosquito midgut, achieving satisfactory performance in key data metrics. Our dataset of \u003cem\u003eAe. aegypti\u003c/em\u003e in this study exhibited improved quality in mitochondrial gene proportion, mean UMIs and genes per cell compared to our previous microfluidics-based scRNA-seq study on the same species\u003csup\u003e25\u003c/sup\u003e. Importantly, the three additional mosquito species showed comparable data quality to \u003cem\u003eAe. aegypti.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo our knowledge, this study provided the first evidence of inter-generic and inter-specific mosquito midgut cell population differences under identical experimental conditions. Despite anatomical and cell type composition similarities across the four mosquito species examined, notable differences were observed in the proportions of specific cell clusters. \u003cem\u003eCulex\u003c/em\u003e mosquitoes showed a higher proportion of ISC/EB clusters than \u003cem\u003eAedes\u003c/em\u003e mosquitoes, suggesting \u003cem\u003eCulex\u003c/em\u003e may possess enhanced intestinal regenerative capacity\u003csup\u003e33\u003c/sup\u003e. Furthermore, the expanded ISC/EB populations in \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e may represent an evolutionary adaptation for rapid epithelial repair following a bloodmeal. Spatially, Cardia cells were localized in the anterior midgut, whereas EC and EC-like cells predominantly resided in the posterior midgut\u003csup\u003e33\u003c/sup\u003e. Previous studies reported that carbohydrate digestion primarily occurred in the anterior region, while protein processing is concentrated in the posterior area\u003csup\u003e17\u003c/sup\u003e. Our findings of digestive enzyme expression heterogeneity across midgut cell populations further corroborate the functional specialization of midgut. Interestingly, the significantly higher proportion of Cardia cells in \u003cem\u003eAe. albopictus\u003c/em\u003e might indicate an enhanced requirement for carbohydrate metabolism than other mosquitoes. This observation may reflect species-specific adaptations to different feeding behaviors or ecological niches.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompared to well-established model organisms (human, mouse or \u003cem\u003eDrosophila\u003c/em\u003e), mosquitoes have relatively underdeveloped genome annotations and limited scRNA-seq studies. This gap is further compounded by the scarcity of marker genes for mosquito cell types, with only \u003cem\u003eAe. aegypti\u003c/em\u003e possessing a higher-quality genomic reference. Therefore, the incomplete genomic annotation or the absence of orthologous markers in the mosquitoes pose a challenge for cell type annotation. In previous study, the canonical markers for ISC/EB clusters in \u003cem\u003eAe. aegypti\u003c/em\u003e and that for Cardia clusters in \u003cem\u003eCx. tarsalis\u003c/em\u003e are absent\u003csup\u003e27,34\u003c/sup\u003e, and we encountered similar challenges. To address this issue, we employed previously established non-canonical marker genes or the top expressed marker genes to annotate cell clusters lacking canonical markers. The marker genes used in the ISC/EB and EE clusters of \u003cem\u003eAe. aegypti\u003c/em\u003e were different. The two ISC/EB clusters showed low expression of canonical marker genes (\u003cem\u003eKlu\u003c/em\u003e, \u003cem\u003eDelta\u003c/em\u003e and \u003cem\u003eesg\u003c/em\u003e) but were distinctly labeled by \u003cem\u003efibulin 1\u003c/em\u003e and \u003cem\u003eLYSC11\u003c/em\u003e. These alternative marker genes were previously identified among the top ISC/EB marker genes in the study of \u003cem\u003eCui et al\u003c/em\u003e. and aligned with another scRNA-seq study conducted on \u003cem\u003eAe. aegypti\u003c/em\u003e\u003csup\u003e33,34\u003c/sup\u003e. The expression of the canonical marker prospero is observed among all three EE clusters. For \u003cem\u003eAe. albopictus\u003c/em\u003e, the gene \u003cem\u003eCalexcitin-1\u003c/em\u003e was used to identify the EE clusters due to the fact that the canonical marker gene \u003cem\u003eprospero\u003c/em\u003e was exclusively expressed in the EE-1 cluster. In each mosquito species, only the cluster that exhibited the highest expression level of the canonical marker \u003cem\u003eNubbin\u003c/em\u003e was identified as the EC cluster\u003csup\u003e33,34\u003c/sup\u003e. Therefore, the markers of EC-like clusters were characterized by a series of highly expressed digestive enzyme genes that varied among different mosquito species \u003csup\u003e27,33,34\u003c/sup\u003e. The marker genes of several cell populations such as Cardia and EE used in \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e were markedly different from others. This discrepancy is likely due to the absence of homologous genes, highlighting the potential for species-specific adaptations in midgut cell populations.\u003c/p\u003e\n\u003cp\u003eWe observed a similar pattern on the top downregulated DEGs among the cell clusters in \u003cem\u003eAe. aegypti\u003c/em\u003e post DENV infection. The broadly shared genes are concentrated in the \u003cem\u003ehsp70\u003c/em\u003e and \u003cem\u003el(2)efl\u003c/em\u003e gene families. These genes play protective roles and respond to various stress\u003csup\u003e64–66\u003c/sup\u003e. The downregulation of \u003cem\u003ehsp70\u003c/em\u003e genes was also observed in the previous study on \u003cem\u003eAe. aegypti\u003c/em\u003e Rockfeller strain, suggesting the DENV may suppress oxidative stress responsive system\u003csup\u003e67\u003c/sup\u003e. The decrease of the \u003cem\u003el(2)efl\u003c/em\u003e genes in this study was different with a bulk RNA-seq study on DENV-infected \u003cem\u003eAe. aegypti\u003c/em\u003e LVP INB strain at 14 dpi, in which the \u003cem\u003el(2)efl\u003c/em\u003e genes showed bidirectional changes during infection\u003csup\u003e68\u003c/sup\u003e. The discrepancy may stem from variations sampling timepoints, the age may compromise the efficacy and intensity of immune response to infection\u003csup\u003e69\u003c/sup\u003e. The pervasive downregulation of the genes may imply a shared host response mechanism to DENV midgut infection.\u003c/p\u003e\n\u003cp\u003eThe ISCs and EBs differentiated to renew the epithelium, thereby maintaining the midgut homeostasis and responding to stressors\u003csup\u003e70\u003c/sup\u003e. Notably, the broad observation of the enrichment of two immune-related genes \u003cem\u003eLRIM16\u003c/em\u003e and \u003cem\u003eApo3\u003c/em\u003e in the ISC/EB clusters among the various species in both this and other mosquito midgut scRNA-seq study\u003csup\u003e27,34\u003c/sup\u003e, with LRIM16 being a leucine-rich immune protein and \u003cem\u003eApo3\u003c/em\u003e being a pro-ZIKV factor in mosquito midgut\u003csup\u003e26,28\u003c/sup\u003e. It suggests that ISC/EB populations may play complex roles in the infection process. Following an infectious bloodmeal, \u0026nbsp;the proportion of ISC/EB clusters markedly increased versus the bloodmeal group, without significant EC changes, indicating that the trend is specifically stimulated by viral infection rather than by blood feeding alone\u003csup\u003e19,71\u003c/sup\u003e. The resistance to pathogen infection enhanced by ISC proliferation was also observed in DENV-infected \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003ePlasmodium\u003c/em\u003e-infected\u003cem\u003e\u0026nbsp;Anopheles stephensi\u003c/em\u003e\u003csup\u003e19,72\u003c/sup\u003e. The upregulated gene \u003cem\u003eFkbp39\u003c/em\u003e in the ISC/EB-prol cluster post-infection is an orthologs of \u003cem\u003eDrosophila Fkbp39\u003c/em\u003e that binds juvenile hormone response elements\u003csup\u003e73\u003c/sup\u003e. A study reported that juvenile hormone could suppress the AMP production in \u003cem\u003eDrosophila\u003c/em\u003e following bacterial infection and participate the antimicrobial immune system in \u003cem\u003eAe. aegypti\u003c/em\u003e\u003csup\u003e74,75\u003c/sup\u003e. It would be interesting to clarify its potential function in immune response against viral infection.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEEs are potentially key sites for viral infection in \u003cem\u003eAe. aegypti\u003c/em\u003e\u003csup\u003e18,76\u003c/sup\u003e. The cellular proportions of each EE clusters significantly decreased post-infection, suggesting the virus-induced modulation of these cells. Similar changes were also observed in a previous RNA-seq study of ZIKV-infected \u003cem\u003eAe. aegypti\u003c/em\u003e\u003csup\u003e26\u003c/sup\u003e. Notably, we observed a significant increase of the gene \u003cem\u003eHlc\u003c/em\u003e in the EE-3 cluster post-infection. The gene is an ortholog of \u003cem\u003eDrosophila DDX56\u003c/em\u003e, a conserved antiviral protein that could control \u003cem\u003eAlphavirus\u003c/em\u003e infection\u003csup\u003e46\u003c/sup\u003e. Given its antiviral role, the upregulation of \u003cem\u003eHlc\u003c/em\u003e in EE-3 suggests a potential defense mechanism against viral infection. The EE-4 cluster post-infection was characterized by the upregulation of multiple mitochondria-related genes, especially the gene \u003cem\u003eCHCHD3\u003c/em\u003e that was involved in mitochondrial fusion\u003csup\u003e77\u003c/sup\u003e. Previous studies reported that DENV could impair mitochondrial fusion and fission to induce mitochondrial elongation to promote infection\u003csup\u003e78,79\u003c/sup\u003e. However, since our study did not detect vRNAs in the cells, whether the phenomenon is caused by metabolic alterations or the regulation of antiviral RLR signaling remains to be studied\u003csup\u003e79\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe cluster termed “SV2/UNC-93” markedly increased in cellular proportion post-infection. It displayed distinct transcriptional features from the known midgut cell types and was uniquely defined by the significant expression of \u003cem\u003eSV2\u003c/em\u003e and \u003cem\u003eUNC-93\u003c/em\u003e, thus representing a novel cell cluster within the mosquito midgut. The two genes played multiple proviral roles in \u003cem\u003eAe. aegypti\u003c/em\u003e: silencing both of them increased midgut infection rates while suppressing viral dissemination from midgut to hemolymph\u003csup\u003e49\u003c/sup\u003e. Midgut epithelial cells have apical-basal polarity maintained by an ion gradient across membrane surfaces. Genes involved in maintaining the gradient might be potential viral host factors\u003csup\u003e49,80\u003c/sup\u003e. Several studies indicated that \u003cem\u003evATPase\u003c/em\u003e is an \u003cem\u003eAe. aegypti\u003c/em\u003e pro-DENV factor that showed impacts on viral fusion and entry by endosomal acidification and viral egress by DENV PrM—\u003cem\u003evATPase\u003c/em\u003e binding\u003csup\u003e81,82\u003c/sup\u003e. We observed significant upregulation of multiple vATPase genes in this cluster, accompanied by marked expression of the gene \u003cem\u003eRFWD2\u003c/em\u003e. A study on ZIKV-infected \u003cem\u003eAe. aegypti\u003c/em\u003e indicated that the ubiquitination of viral NS1 protein could promote viral replication by a mammalian E3 ubiquitin ligase WWP2 homolog \u003cem\u003eSu (dx)\u003c/em\u003e\u003csup\u003e83\u003c/sup\u003e. Although \u003cem\u003eRFWD2\u003c/em\u003e was not a homolog of \u003cem\u003eSu (dx)\u003c/em\u003e, its upregulation in the SV2/UNC-93 cluster suggests a potential role in viral infection. Moreover, the bidirectional changes observed in canonical pathways in this cluster reflected the complexity of the innate immune response upon viral challenge. These findings suggest that this cell cluster may be a novel epithelial cell type that supports the viral dissemination from lumen to hemolymph. This possibility remains to be further studied.\u003c/p\u003e\n\u003cp\u003eTaken together, this study presented a comprehensive single-cell atlas and virome of the midgut across four medically important vector mosquitoes and the transcriptomic changes of midgut cell populations following bloodmeal feeding. Evolutionarily conserved and species-specific cellular signatures across mosquito midguts will enhance our fundamental understanding of mosquito physiology, offering new frameworks for comparative hematophagous arthropod biology. Furthermore, our study delineated the dynamic response of \u003cem\u003eAe. aegypti\u003c/em\u003e midgut to DENV infection at single-cell resolution. In conclusion, these findings provide deeper insights into the mosquito midgut and MBV-midgut interactions, offering the potential target by disrupting virus dissemination in mosquitoes to combat mosquito-borne diseases.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eMosquito\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFour mosquito species used in this study were \u003cem\u003eAe. aegypti\u003c/em\u003e (Rockefeller strain), \u003cem\u003eAe. albopictus\u003c/em\u003e (Jiangsu strain), \u003cem\u003eCx. p. pallens\u003c/em\u003e (Beijing strain) and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e (Yingcheng strain). All mosquitoes were maintained under 28 \u0026deg;C, 75% relative humidity (RH) with 12h:12h light/dark cycles.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell and virus\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVero E6 cells were infected at a multiplicity of infection (MOI) of 0.01 with DENV2 (strain D2Y98P), then cultured at 37 \u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e in Dulbecco\u0026rsquo;s Modified Eagle\u0026rsquo;s Medium (DMEM, Gibco, USA) supplemented with 2% fetal bovine serum (FBS, Gibco, USA) and 1% penicillin-streptomycin (Gibco, USA). The culture supernatant was harvested at 7 dpi and then filtered through a 0.2 \u0026mu;m filter (Merck, German) to remove cellular debris for virus titration as described in the previous study\u003csup\u003e84\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiocontainment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures for in vitro work involving DENV-2 propagation and infection were carried out in the biosafety level 2 (BSL-2) laboratory. Mosquito oral infection, maintenance, and dissection after DENV-2 infection were conducted in the arthropod containment level 2 (ACL-2) laboratory.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBlood feeding and DENV infection of mosquitoes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo explore the midgut cell dynamics of mosquitoes post-bloodmeal, 7-day-old \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e mosquitoes fed with noninfectious pig blood.To explore the midgut cell dynamics of mosquitoes post-infection, 7-day-old\u003cem\u003e\u0026nbsp;Ae. aegypti\u003c/em\u003e mosquitoes were fed with DENV-2 bloodmeal (a final viral concentration of 1.5\u0026times;10\u003csup\u003e6\u003c/sup\u003e PFU/mL). The oral fed and infection was performed with artificial membrane system as described in previous study\u003csup\u003e85\u003c/sup\u003e. The fully engorged females were selected and maintained until dissection.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCollection of midgut samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe midgut was dissected from 50-100 females from \u003cem\u003eAe. aegypti\u003c/em\u003e, \u003cem\u003eAe. albopictus\u003c/em\u003e, \u003cem\u003eCx. p. pallens\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e that were fed with glucose at 7 dpe. For female \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e mosquitoes that were previously fed with noninfectious bloodmeal, the midguts were collected at 7 dpb. Additionally, the DENV2 infected midgut were collected from female \u003cem\u003eAe. aegypti\u003c/em\u003e mosquitoes at 7 dpi. Detailed information regarding the sampling schedule and experimental groups can be found in Supplementary Dataset 6 and Fig 1a.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle-cell preparation from midguts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe midguts were washed and temporarily stored in Schneider\u0026rsquo;s Drosophila Medium (SDM, Gibco, USA) within a microcentrifuge tube on ice, then minced in 300 \u0026mu;l of dissociation buffer from SCelLiVe Tissue Dissociation Kit (Singleron, China). The tissue fragments were resuspended in 700 \u0026mu;l of dissociation buffer and then incubated in a 28 \u0026deg;C water bath for 15-25 min. During incubation, the suspension was periodically mixed, and the cell concentration, viability and aggregation were measured every five minutes by staining with 0.4% trypan blue to ensure the quality of the cells. Once the quality control (QC) criteria were met, the suspension was loaded into a 50 ml centrifuge tube equipped with a pre-wetted 40 \u0026mu;m filter to remove larger cell debris, and then washed with 1\u0026times; PBS (Gibco, USA) until the final volume reached 15 ml. The resulting cell suspension was centrifuged at 350\u0026times; g, 4 \u0026deg;C for 5 min. A viable cell band was typically observed near or at the bottom of the tube, and 100-200 \u0026mu;l of the supernatant was retained to avoid disturbing the pellet. The cell pellet was then suspended, followed by a second counting with 0.4% trypan blue. Only cell suspension samples with viability \u0026ge; 80% and were used for subsequent scRNA-seq.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLibrary construction and sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the manufacturer\u0026rsquo;s guidelines, the single-cell suspension was adjusted to ~200 cells/\u0026mu;l prior to loading onto a microfluidic microwell SCOPE-chip (Singleron, China). The cDNA synthesis of captured cells and sequencing library construction were performed with GEXSCOPE Single Cell RNA Library Kit (Singleron, China). The constructed libraries were sequenced with NovaSeq 6000 system (Illumina, USA) in accordance with the manufacturer\u0026rsquo;s instructions. The sequencing quality metrics could be found in Supplementary Dataset 6.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe workflow for data analysis was showed in Supplementary Fig. 3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(1) Single-cell RNA-seq analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mosquito genomes (\u003cem\u003eAe. aegypti\u003c/em\u003e: assembly AaegL5.0, \u003cem\u003eAe. albopictus\u003c/em\u003e: assembly AalbF5, \u003cem\u003eCx. p. pallens\u003c/em\u003e: assembly TS_CPP_V2 were obtained from NCBI of USA; the genome of the \u003cem\u003eCx tritaeniorhynchus\u003c/em\u003e was sequenced and annotated by our laboratory) and their gene feature files were converted to references by CeleScope (v2.1.0)\u003csup\u003e86\u003c/sup\u003e. Mosquito mitochondrial genes were manually annotated with \u0026ldquo;MT-\u0026rdquo; prefix. To perform single-cell integration among mosquito species, BLASTP (2.15.0+)\u003csup\u003e87\u003c/sup\u003e with default parameters was used. The protein sequences of \u003cem\u003eAe. aegypti\u003c/em\u003e were used as the reference to calculate the similarity between the protein sequences encoded by the genes of other mosquito species and those of Ae. aegypti. The genes corresponding to the protein sequences with the best hit and e-value\u0026nbsp;\u0026le;\u0026nbsp;1e-6 were identified as the orthologous genes. For gene abbreviations in this study, we adopted the following strategies: (I) We prioritized the abbreviations, acronyms or names of \u003cem\u003eAe. aegypti\u003c/em\u003e annotated by VectorBase\u003csup\u003e88\u003c/sup\u003e. (II) Where applicable, we also used the names of \u003cem\u003eDrosophila\u003c/em\u003e orthologs annotated by FlyBase\u003csup\u003e89\u003c/sup\u003e. (III) If no suitable abbreviation or ortholog name was available, the gene name was left blank. The comparison table of NCBI gene ID, Entrez ID and VectorBase ID could be found in Supplementary Dataset 7.\u003c/p\u003e\n\u003cp\u003eThe raw sequencing data were aligned to the genome references and the expression matrices were calculated by CeleScope. To ensure data quality, cells with fewer than 100 genes or more than 2,500 genes were excluded\u003csup\u003e28\u003c/sup\u003e, as were cells with a mitochondrial proportion exceeding 15%. Subsequent scRNA-seq analysis was performed with Scanpy (v1.11.1)\u003csup\u003e32\u003c/sup\u003e. DoubletFinder (v2.0.3)\u003csup\u003e90\u003c/sup\u003e was used to identify doublets. The filtered data were log-normalized and the top 4000 highly variable genes were used for PCA dimension reduction. The optimal parameters (n_neighbors = 50, n_pca = 30 and resolution\u0026thinsp;=\u0026thinsp;1.2) were used for UMAP dimension reduction and Leiden clustering.\u003c/p\u003e\n\u003cp\u003eFor \u003cem\u003eAe. aegypti\u003c/em\u003e and \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e, the single-cell data from the same mosquito species pre- and post-bloodmeal were integrated by Harmony (v0.0.10)\u003csup\u003e91\u003c/sup\u003e. The optimal parameters (n_neighbors = 100, n_pca = 30 and resolution\u0026thinsp;=\u0026thinsp;1.8) were used for UMAP dimension reduction and Leiden clustering.Harmony was used to integrate the single-cell data from \u003cem\u003eAe. aegypti\u0026nbsp;\u003c/em\u003ewith glucose group, bloodmeal group, and DENV-infection group. The optimal parameters (n_neighbors = 100, n_pca = 30 and resolution\u0026thinsp;=\u0026thinsp;1.8) were used for UMAP dimension reduction and Leiden clustering.All single-cell transcriptomic DEGs were calculated using Memento (v0.1.1)\u003csup\u003e92\u003c/sup\u003e with default parameters. Genes with de_pval \u0026le; 0.05 were considered DEGs. Among them, genes with de_coef \u0026gt; 0 are significantly high expressed genes, and genes with de_coef \u0026lt; 0 are significantly low expressed genes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(2) Inter-generic and inter-specific data integration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the instructions specified in the official documentation, the scvi-tools (1.3.0)\u003csup\u003e44\u003c/sup\u003e with default parameters was used to integrate single-cell data based on orthologs across different mosquito species. Scanpy with the same parameters as above was used for dimension reduction and clustering. Comparisons among mosquito species were performed by integrating single-cell data for each mosquito species as a batch. Comparisons between mosquito genera were performed by integrating single-cell data for each mosquito genus as a batch.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(3) Single cell virome analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo characterize the virome composition in our samples, we utilized a pseudo-metagenomic method for both bulk and cellular virome analysis. For bulk analysis, in each sample, reads unmapped to the host genome by CeleScope was extracted., followed by additional quality filtering using Fastp (v 0.23.4)\u003csup\u003e93\u003c/sup\u003e with polyN tail trimming. A custom reference library was constructed by the following strategy: The sequences of the mosquito-associated viral families and negeviruses detected in previous studies were extracted from NCBI virus database\u003csup\u003e34,94\u003c/sup\u003e. Then, the pathogenetic viral sequences were excluded except for DENV strain D2Y98P used in this study according to our arbovirus dataset\u003csup\u003e95\u003c/sup\u003e. Then, the reads were annotated against the reference library using Bowtie2 (2.4.5)\u003csup\u003e96\u003c/sup\u003e and the viral abundance matrix was generated by custom scripts. For cellular analysis, the abundance data of the viruses including \u003cem\u003eHanko iflavirus 1\u003c/em\u003e (ON949933.1), DENV2 strain D2Y98P (JF327392.1), \u003cem\u003eTiger mosquito bi-segmented tombus-like virus\u003c/em\u003e (BK059489.1 and BK059490.1), \u003cem\u003eL-A virus\u003c/em\u003e (MW174761.1) was extracted and mapped to the cells by the corresponding cell barcodes. The vial abundance was calculated by UMI counts and only partial viral reads could be mapped to cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis and data visualization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analyses were performed using custom R and Python scripts. Data visualization was performed by Scanpy, OmicVerse (v1.7.1)\u003csup\u003e97\u003c/sup\u003e and custom R scripts.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data and processed scRNA-seq data are available on the NCBI GEO database with accession GSE301762 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE301762), the access password: utqdaqkovxopxer. Another copy is available on the CNCB (China National Center for Bioinformation) GSA (Genome Sequence Archive) database with accession\u0026nbsp;CRA027708\u0026nbsp;and CNCB OMIX (Open Archive for Miscellaneous Data) with accession MIX010740. The genome assembly of \u003cem\u003eCx. tritaeniorhynchus\u003c/em\u003e Yingcheng strain is available on CNCB GWH (Genome Warehouse) database with accession GWHGEEU00000000.1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe codes for analysis are available on GitHub: https://github.com/paddle-salted-fish/midgut_cell_atlas_and_virome_of_mosquito_project\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Key Research and Development Program of China (2024YFC231000 and 2023YFC2305900), the National Natural Science Foundation of China (U22A20363, 32400379), and Zhejiang Provincial Natural Science Foundation of China (LQN25C040001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors thank the Department of Vector Biology and Control, National Institute for Communicable Disease Control and Prevention, China CDC, for kindly providing the \u003cem\u003eAe. albopictus\u003c/em\u003e and \u003cem\u003eCx. pipiens pallens\u003c/em\u003e mosquitoes. Furthermore, we thank the Institutional Center for Shared Technologies and Facilities of Wuhan Institute of Virology, CAS.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMiao, Q. \u003cem\u003eet al.\u003c/em\u003e Genetic and Antiviral Potential Characterization of Four Insect-Specific Viruses Identified and Isolated from Mosquitoes in Yunnan Province. \u003cem\u003eViruses\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 596 (2025).\u003c/li\u003e\n\u003cli\u003eWiśniewska, M. M. \u003cem\u003eet al.\u003c/em\u003e Ovarian transcriptome analyses indicate that weak juvenile hormone signaling underlies the molecular basis of oogenesis deficiencies in mosquitoes. \u003cem\u003eBMC Biol.\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e, 160 (2025).\u003c/li\u003e\n\u003cli\u003eCarvalho, V. L. \u0026amp; Long, M. T. 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Commun.\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 5983 (2024).\u003c/li\u003e\n\u003c/ol\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":"Mosquito, Aedes aegypti, Aedes albopictus, Culex pipiens pallens, Culex tritaeniorhynchus, dengue virus, scRNA-seq, midgut, virome","lastPublishedDoi":"10.21203/rs.3.rs-7214530/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7214530/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Mosquitoes are the most important arthropod vectors of human diseases globally, with their midgut serving as both a digestive organ and the primary site of viral infection. Single-cell RNA sequencing (scRNA-seq) studies in insects, including mosquitoes, remain limited due to the absence of established protocols. Here, we fill this gap by developing a compatible microwell-based scRNA-seq workflow, and generated midgut cell atlas and virome for four important mosquito species: Aedes aegypti, Aedes albopictus, Culex pipiens pallens and Culex tritaeniorhynchus. Eight distinct cell types were identified, and the cell composition was inter-generic conserved in types but divergent in proportions. Culex mosquitoes exhibited higher proportions of intestinal stem cells/enteroblasts (ISC/EBs) than Aedes mosquitoes. In response to dengue virus 2 (DENV-2) infection, stress-associated genes were broadly downregulated, whereas endoenterocytes (EEs) and ISC/EBs showed marked upregulation of diverse immune related genes. Notably, we identified a novel midgut cell cluster (termed SV2/UNC-93) characterized by high expression of synaptic vesicle protein-2 and UNC-93, along with broad upregulation of apical-basal polarity-related genes linked to viral infection. The midguts of Aedes and Culex mosquitoes harbored diverse virome belonging to 5 viral families and one unclassified group. Hanko iflavirus 1 (HKIFV1) was the most common virus, distributed in all four mosquito species, while Tiger mosquito bi-segmented tombus-like virus (TMBSTLV) was the most abundant virus in Ae. albopictus and exhibited strong tropism in hemocytes. DENV-2 only detected in experimental infected Ae. aegypti, with no obvious midgut cell tropism but highest viral reads occurred in enterocytes (ECs) and EEs.Our study provides fundamental insights into the cellular composition of these four medically important mosquitoes and facilitate future research on virus-midgut interactions.","manuscriptTitle":"Midgut cell atlas and virome of four important mosquito species and immune landscapes of dengue virus infection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-11 05:57:42","doi":"10.21203/rs.3.rs-7214530/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":"a3df48a0-4ab1-46d7-bea8-e4430fed4b81","owner":[],"postedDate":"August 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":52835737,"name":"Biological sciences/Biological techniques/Sequencing/RNA sequencing"},{"id":52835738,"name":"Biological sciences/Zoology"},{"id":52835739,"name":"Biological sciences/Microbiology/Virology/Virus\u0026#x2013;host interactions"}],"tags":[],"updatedAt":"2025-09-09T06:05:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-11 05:57:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7214530","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7214530","identity":"rs-7214530","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}