Compatibility Interactions between Anopheles gambiae and Plasmodium falciparum in a Malaria Endemic Region in Kisumu, Kenya 

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Onyango, Maxwell G. Machani, Kevin O. Ochwedo, Robin M. Oriango, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4711223/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Feb, 2025 Read the published version in Scientific Reports → Version 1 posted 14 You are reading this latest preprint version Abstract Insecticide resistance and outdoor transmission have reduced the effectiveness of existing malaria transmission prevention strategies. As a result, targeted approaches to support continuing malaria therapies, such as transmission-blocking vaccines, are required. Cross-sectional mass blood screening in children between 5 and 15 years was conducted in Chulaimbo, Kisumu, during the dry and wet seasons in 2018 and 2019. Plasmodium falciparum gametocyte carriers were identified by Microscopy. Subsequently, carries were used to feed colony bred Anopheles gambiae females in serum replacement and whole blood membrane feeding experiments. The infection prevalence was 19.7% (95% Cl: 0.003–0.007) with 95% of the infections being caused by P. falciparum . Of all confirmed P. falciparum infections, 16.9% were gametocytes. Thirty-seven paired experiments showed infection rates of 0.9% and 0.5% in the serum replacement and whole blood experiments, respectively, with no significant difference (P = 0.738). Six Pfs47 haplotypes were identified from 24 sequenced infectious blood samples. Hap_1 (E27D and L240I), Hap_2 (S98T0); Hap_3 (E27D); Hap_4 (L240I); Hap_5 (E188D); and Hap_6 without mutations. Haplotype 4 had the highest frequency of 29.2% followed by Hap_3 and Hap_6 at 20.8% each then Hap_1 with a frequency of 16.7%, whereas Hap_5 and Hap_2 had frequencies of 8.3% and 4.2% respectively. Varying frequencies of infectious Pfs47 haplotypes observed from genetically heterogeneous parasite populations in endemic regions illuminates vector compatibility to refracting P. falciparum using the hypothesized lock and key analogy. This acts as a bottleneck that increases the frequency of P. falciparum haplotypes that escape elimination by vector immune responses. The interaction can be used as a potential target for transmission blocking through a refractory host. Biological sciences/Evolution Biological sciences/Genetics Biological sciences/Molecular biology P. falciparum Pfs47 An gambiae compatibility geographic regions Figures Figure 1 Figure 2 Background Insecticide resistance 1–4 and outdoor transmission 5–8 have compromised the efficacy of primary malaria control interventions, necessitating the development of new or improved targeted strategies that could complement the control of malaria, such as transmission-blocking approaches. Molecular mechanisms underlying Plasmodium infections and mosquito genotypes influencing parasite adaptations to diverse Anopheles species are critical in understanding malaria transmission dynamics and for developing targeted vector control interventions that may compliment already existing ones. Malaria transmission primarily depends on competent vectors and compatible infectious parasites to influence susceptibility in local Anopheles populations 9 . The mosquito immune factors, including recognition receptors, cellular and humoral components, influence the infectiousness of gametocytes in vectors 10 . The likelihood of infection after ingesting gametocytes from an infected person is determined by a combination of factors like the mosquito's immune responses among others 10–13 . The thioester-containing protein 1 (TEP1) is an important immunological gene that exhibits allele-linked variations 14 and also inhibits pathogens including Plasmodium infections in mosquitoes 15 , hence altering vector competence and malaria infectivity 16,17 . In contrast, the malaria parasite P. falciparum has evolved to circumvent the vectors' immune responses mediated by the Pfs47 18,19 . The Pfs47 gene displays haplotypes that naturally select specific mosquito midgut receptors resulting in significant transmission variability 9 . According to Sinka et al 20 , around 70 Anopheles species now transmit P. falciparum malaria around the world. Recent studies have revealed that compatible Pfs47 haplotypes are selected by specific vector receptors in the midgut, eluding the immune system and increasing the likelihood of infection. However, incompatible haplotypes are detected and eliminated by the vector's immune defenses 18 . Furthermore, selection pressures imposed by local Anopheles populations dominant in a given region may have altered the genetic diversity of Pfs47 haplotypes, resulting in parasite adaptations to native vector species. Therefore, the associations between the TEP1 immunity gene in Anopheles and Pfs47 in P. falciparum may be an important determinant of malaria infections and could be targeted in blocking malaria transmission in primary vectors efficient in transmitting malaria from a molecular perspective. Moreover, Anopheles-Plasmodium interactions are complex and have not been clearly understood yet, form a basis for increasing the knowledge gaps of host factors on vector competence. Also, these interactions are potential targets for developing malaria transmission-blocking interventions. The aim of this study is to determine the incidence of malaria in school-aged children, Anopheles vector feeding and infection rates, parasite genotypes, their associations with mosquito infectivity, and mosquito-parasite interactions in a malaria-endemic region in western Kenya. Materials and methods Study site and population Consented children aged 5 -15 years were screened following a cross-sectional study design from sub locations in Chulaimbo, Kisumu County (Figure 1), during the wet season from October to December 2019 and October to December 2020, and the dry season (January to March 2020). Chulaimbo is a rural site 19 km north-west of Kisumu City, located at 0.03572°S, 34.621°E, and an altitude range of 1328-1458 meters above sea level 21 . The region has a mean annual temperature range of 12 0 C - 35°C. This region experiences an average annual rainfall of 1352 mm and an average relative humidity between 66 and 83%. Malaria transmission in this area is endemic, with Plasmodium falciparum as the dominant parasite species in the area 22 . Most residents are small-scale subsistence farmers. M osq uitoes used for the study Laboratory reared Anopheles gambiae female mosquitoes (Kisumu strain) between 3-5 days post-emergence were used for membrane feeding assays. This colony was selected and maintained at the Center of Excellence for Malaria Research in Homa Bay, Western Kenya. They were reared at temperatures of 27 - 29 0 C, 69 - 80% relative humidity (RH), and a 12 hours light and 12 hours dark cycle. The colony was then constantly maintained on 10% sucrose 23 after the blood meal until the dissection day. Identifying gametocyte carriers Parasitological assessments to detect P. falciparum gametocyte carriers were conducted in school-aged children between the ages of 5 and 15 years, who had assented and had their guardians' consent to participate in the study. Blood samples were obtained from the children using finger pricks on well-labeled Whatman® 903 Protein Saver Cards (GE Healthcare WB100014) with the participants' information. A total of 50 µl of blood were collected and placed onto the cards, which were then air dried before being stored and stored at -20 o C for further molecular analyses. As the blood was being collected on cards, thick and thin smears were also prepared for the same participant. The blood films were stained with 10% Giemsa and read after drying. Parasites were viewed under a compound microscope and Plasmodium species identified in thick smears Malaria parasites counts were read against 500 white blood cells. Gametocyte densities were determined in slides for all P. falciparum positive participants by counting the number of gametocytes per 500 leukocytes by microscopy and expressed as parasites per μl assuming a standard white blood cell (WBC) concentration of 8000/μl 24 . Two trained microscopists took two readings per slide smear, and 20% of the slides were randomly selected for quality control verification by a senior external microscopist. Membrane feeding was limited to slides of gametocyte positive subjects only. Individuals who tested positive for malaria and had symptoms were referred to a local health center and treated according to Ministry of Health recommendations. 25 Mosquito infections using membrane feeding assays Individuals identified as carriers among screened volunteers, who tested positive for P. falciparum gametocytes donated blood for whole blood and serum replaced experiments in the laboratory. Blood was drawn intravenously by a professional phlebotomist using butterfly needles. Approximately 3ml of blood was collected by venipuncture in heparinized tubes for each volunteer. An aliquot of 1ml of blood was immediately placed into pre-warmed hemotek feeders (1ml capacity) at 37°C, while another 1.5ml was transferred into 2ml Eppendorf tubes and centrifuged at 2000 rounds per minute for 2 minutes before adding it to the hemotek feeders. The supernatant of serum was discarded and replaced with a naïve human serum type AB (Bio Whittaker, Cambrex Bio Science Walkersville, MD, USA). Replaced blood was then quickly transferred to the feeders to allow the starved mosquitoes to feed. Participants’ blood positive for gametocytes was used to feed the insectary reared Anopheles gambiae mosquitoes using membrane feeding assays (serum replacement and whole blood experiments) 26 . Aggressive 3-5 day old female Anopheles gambiae mosquitoes were starved for 6 to 8 hours prior to feeding on infected blood. Whole blood and serum replacement experiments were conducted for each participant. A total of 37 paired experiments were conducted. Each feeding cup contained 100 mosquitoes. The mosquitoes were allowed to feed from different feeders of the same infected blood for 15-30 minutes through a parafilm membrane. All membrane feeding procedures were conducted at 37 0 C using the hemotek system. Only fully engorged blood-fed mosquitoes were selected and maintained at 27-29 0 C temperatures and 69-80% relative humidity following a 12 hours light and 12 hours dark cycle. They were given 10% sucrose for 9 days post-feeding and the ones that survived were dissected for midgut oocysts enumeration. The unfed and partially fed mosquitoes were discarded by freezing them for 15 minutes at -20 0 C. After membrane feeding, volunteers were treated with artemether-lumefantrine (Coartem®) according to the Ministry of Health guideline 25 . Oocysts counts All fully engorged mosquitoes that survived on day 8 or 9 post-feeding were dissected under a dissecting microscope as described by Afrane et al 27 . Briefly, each mosquito gut was carefully pulled out from the abdomen in 0.5% mercurochrome and allowed to stain for 10 minutes. The midguts were then examined for the presence of oocysts under a light microscope. The number of oocysts observed were counted and recorded per mosquito gut. The oocysts load was expressed as the number of oocysts per infected mosquito. Mosquito carcasses corresponding to their infected midguts were labeled and preserved for further molecular assays to determine TEP1 genotypes 28 . Briefly, TEP1 was genotyped using a nested PCR-RFLP targeting 892 base pairs for nest 1 and a final fragment length of 758 base pairs after nest 2. Both PCR reaction conditions were set as denaturation at 95 °C for 3 min, 35 cycles of 94°C for 30s, annealing at 55°C for 30s, extension at 72°C for 30s, and a final step at 72 °C for 6 min using Dream Taq Green Master Mix (Thermo Fisher Scientific). PCR products were then digested using restriction enzymes Bam HI, Hind III, or Bse NI (New England Biolabs Inc) according to the manufacturer’s instructions and the result analyzed on 2.5% agarose gel electrophoresis. The TEP1 allelic classes were determined by fragment size of restriction enzyme digestion. A subset was also randomly selected for the genotype confirmatory purposes by sequencing. DNA extraction and parasite genotyping The Chelex technique was used to obtain Plasmodium parasite DNA from the dried blood spots 29 . As previously reported 30 , a multiplex real-time PCR (RT-PCR) was utilized to identify Plasmodium species. Pfs47 was genotyped using PCR and Sanger sequencing, as previously published 30 . Ethical approval The ethical review board of the Maseno University, Kenya (MSU/DRPI/MUERC/00456/17) reviewed and approved the protocol for screening of P. falciparum gametocyte carriers and subsequent intravenous blood drawing. A detailed written informed assent and consent to participate in the study was provided by all study volunteers and their parents or guardians. Feeding of mosquitoes was conducted in a secure, insect-proof room at the Chulaimbo health center. All experiments and methods were performed in accordance with the institution’s guidelines and regulations. Statistical analysis Data from the participants was tabulated in Microsoft Excel V16. Computing descriptive statistics (sum, mean, standard deviation, standard error, and 95% confidence interval) and comparing means were done using Graph Pad Prism v.8.0.1 and SPSS version 25 for Windows software. The Shapiro–Wilk normality test was used to check data normality before performing multiple mean comparisons and chi-square tests. Data were considered statistically significant at P< 0.05. The codoncode Aligner 11.0.1 (CodonCode Corp., Centerville, MA) was used to check the sequence quality and trim low-quality bases. Bio-Edit software was used to align the sequences and determine the nonsynonymous mutations and codon changes based on reference sequence (Pf3D7_1346800). MEGA software was used to construct the UPGMA (unweighted pair group method with arithmetic mean) tree based on the Kimura 2-parameter (K2P) distance model with 1,000 bootstrap replicates. Results Parasitological surveys A total of 4481 children that were tested for malaria, 885 tested positive, representing a 19.7% infection prevalence (95% CI: 0.003-0.007). Most positive cases were attributed to P. falciparum infections, accounting for 95% (841) of the total infections. Other Plasmodium species identified in the study area were P . malariae (1.6%), P. ovale (0.3%), and mixed infections involving P. falciparum and P. malariae ( Pf/Pm ) or P. ovale ( Pf/Po ), each accounting for 2.7% of the infections. Out of the 841 confirmed P. falciparum positive infections, (142/841) 16.9% of the participants had P. falciparum gametocytes that were confirmed by microscopy. The overall gametocyte density was 37.3 gametocytes/ µl of blood. The gametocyte prevalence was 6.9% whereas the density ranged from 16-176 gametocytes/ µl of blood treating each infection as an individual entity. The odds of finding microscopic gametocyte infections were significantly high during the dry season (OR 1.37, 95% CI, P=0.001) compared to the wet season (Table 1). Males were 1.23 times more likely than females to harbor microscopic gametocyte infections. Mosquito infections A total of 109 children out of 142 who tested positive for P. falciparum gametocytes were subjected to membrane feeding experiments. Only 34% of those who had gametocytes infected mosquitoes on day 9 post-feeding. A total of 3894 mosquitoes were dissected, 1960 in serum replacement and 1934 in whole blood to evaluate infection rates. Thirty-seven paired membrane feeding experiments from the same donor had infection rates of 0.8% (15/1960) and 0.5% (9/1934), with oocyst densities of 1 and 1.8 in serum replacement and whole blood, respectively. (Table 2). The difference in both experiments was however not significant (P=0.738). Plasmodium falciparum Pfs47 haplotypes Six infectious haplotypes were identified from the 24 sequenced gametocyte containing dried blood spots (DBS). Haplotype 1 (Hap_1) had dimorphic codon E27D and L240I, Hap_2, Hap_3, Hap_4, Hap_5 had S98T, E27D, L240I, and E188D mutations respectively, whereas, Hap_6 was conserved or had no polymorphic site (Fig 2). Genotyped parasite DNA from blood infected with Hap_4 with the dimorphic codon L2401 was frequent at 29.2% (7) with positive oocyst results followed by Hap_3 (E27D) and Hap_6, each with 20.8% (5). Infectious haplotypes with E27D and L240I mutations (Hap_1) were at a frequency of 16.7% (4) whereas Hap_2 (S98T0) and Hap_5 (E188D) was each present at a frequency of 4.2% (1) and 8.3% (2) respectively. Discussion Malaria vector and parasite interaction is a key determinant towards successful transmission 9 , 31 . For an established or localized transmission system, there is need for susceptible vector genotype populations and infectious Plasmodium haplotypes that evoke endogenous compatible immune evasive elements that circumvent them. This study shows the compatibility of probable infectious Pfs47 haplotypes characterized by specific codon variants that may influence infectivity to An. gambiae mosquitoes. These results may have implications on the parasites capacity to evade the vectors’ immune defenses effectively completing its transmission cycle. Haplotype 4 with codon L240I had the highest frequency among the infectious haplotypes that progressed to detectable oocyst in the midgut and could be linked to increased infectivity or transmission potential to vectors followed by haplotypes; Hap_3 (E27D) and Hap_6 (without polymorphic sites) then Hap_1(E27D and L240I). Despite Hap_1 having two dimorphic sites E27D and L240I, the genotypic combination did not appear to increase its frequency or malaria transmission in the region. The other haplotypes Hap_2(S98T) and Hap_5(E188D) also infected mosquitoes displaying a probable limited compatibility. Furthermore, the observed levels of infection of An. gambiae s. s. by the six identified Pfs47 haplotypes implies different levels of compatibility that could facilitate malaria transmission. The six haplotypes should further be evaluated using field-collected Anopheles vectors common in a specific endemic location as well as their potential to spread disease in natural vector populations. A previous study conducted from western Kenya identified thirteen Pfs47 haplotypes, with haplotypes harboring the mutation codon E27D having the highest frequency of over 50%, followed by conserved Pfs47 haplotypes whereas the rest occurred at a frequency of 6.7% or lower 30 . Even though haplotypes with E27D were most common, haplotypes with L240I were more infectious to An. gambiae s. s. which may imply that it has enhanced evasion of the vector immune defenses. Also, all An. gambiae s. s used were reared in the insectary and harbored the homozygous TEP1* S1/S1 genotypes. The high prevalence of TEP1* S1/S1 observed in this mosquitoes is an indication of populations being susceptible to Plasmodium gametocytes 32 , 33 and may have been highly compatible with gametocytes containing the L240I dimorphism following the “lock-and-key” analogy described by Molina-Cruz et al 9 unlike the other infectious haplotypes that were identified in the region. The Pfs47 gene has undergone natural selection as a result of adaptations to diverse anopheline species found in different continents hence a strong population structure 9 , 31 , 34 . Furthermore, parasites with compatible Pfs47 haplotypes can elude complement activation and survive within invaded midgut cells 35 . To evaluate the possible influence on the dynamics of malaria transmission, it is essential to understand the frequency and distribution of these haplotypes. Higher transmission rates might result from some haplotypes’ greater ability to overcome mosquito immune responses. Apart from vectors and gametocyte compatibility human antibodies against gametocytes play a critical role in transmission blocking or reduction capabilities in addition to their compatibility 36-38 . As a result, high gametocyte densities may not always indicate successful mosquito infection. Low gametocyte densities, on the other hand, do not also exclude infectiousness 39 . A weak association between gametocyte density and infection rates was observed despite exposing numerous mosquitoes with infected blood. The low infection rates in the mosquito may have been an indication that serum replacement and whole blood experiments used in this study did not have a significant impact on infection rates or other factors including the gametocyte densities, sex ratios of male to female gametocytes, the genetic makeup of the gametocytes, and the immune factors may have inhibited infections in the mosquito. This finding corroborated previous investigations 40 that also documented low infection rates, and weak association between gametocyte densities and mosquito infection rates which varied with low gametocyte densities. Conclusion Molecular interactions underlying mosquito immune responses to P. falciparum infections and the immune evasion tactics is of importance. Recombinant P. falciparum parasites with Pfs47 haplotypes from diverse locations across the world but with a similar genetic makeup were utilized to test the hypothesis that Pfs47 haplotypes impact parasite survival in local vectors from distinct geographical regions. These results confirm that changing the Pfs47 haplotype by itself was sufficient to change compatibility with various vectors as a potential target for inhibiting transmission in the mosquito host 9 , 41 . The functional importance of these genetic differences in Pfs47 and their associations with vector immunological genes, as well as how these changes affect the efficacy of malaria control strategies, may require further research. Overall, this research sheds significant insight into the genetic diversity of parasites of malaria and its potential impact on efforts to prevent the disease. These findings suggest a potent approach for controlling the spread of the malaria parasite by targeting Pfs47 haplotypes linked to increased mosquito infection rates. Abbreviations DBS Dried blood spots Pfs47 Plasmodium falciparum surface protein 47 TEP1 Thioester containing protein RT-PCR Real time polymerase chain reaction PCR-RFLP Polymerase chain reaction restriction fragment length polymorphism Declarations Ethics approval and consent to participate: This study was approved by the University of California, Irvine Institutional Review Board (UCI IRB) and Maseno University Ethics Review Committee (MUERC protocol No. 00456) and authorized by the Ministry of Health. Acknowledgments We express our sincere gratitude to the village elders, residents and participants for their continued support, all community health workers, field assistants and the entire ICEMR staff who participated in this research. Authors’ contribution Project conceptualization: SAO, KOO and DZ, Project implementation: SAO, DZ, YAA and AKG, Data collection and sample analysis: SAO, MGM, and RMO, Formal analysis: SAO, KOO, and DZ. Drafting manuscript: SAO. Editing and revising manuscript: KOO, MGM, AKG, ML, EK, YAA, DZ, and GY. Funded project: GY Availability of data and materials Data supporting the conclusions of this study is included within the article and its supplementary information files. Competing interest The authors have declared that no competing interest. Funding This study was supported by grants from the National Institute of Health (R01 AI123074, U19 AI129326, R01 AI050243, D43 TW001505). There was no additional external funding received for this study. References Huijben, S. & Paaijmans, K. P. Putting evolution in elimination: winning our ongoing battle with evolving malaria mosquitoes and parasites. Evolutionary applications 11, 415–430 (2018). Ondeto, B. M. et al. 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Tables Table.1: Chi-square, Odds Ratios, and 95% Confidence Intervals (CIs) for gametocyte prevalence by season and gender Parameter Number screened Gametocyte Density/µl Gametocyte Prevalence n (%) χ 2 P value OR (95% CI) Season Wet 3690 30.88 (26.67 - 35.74) 682 (18.5) 11.09 0.001 1.37 (1.14-1.64) Dry 791* 44.11(28.43 - 68.42) 187 (23.6) Gender Female 2262 32.03 (26.15 -39.23) 403 (17.8) 7.27 0.007 1.23 (1.06-1.42) Male 2219* 31.97 (26.30 - 38.84) 466 (21) *Reference categories Table 2 Infection prevalence for paired experiments (n=37) Experiment types Number of mosquitoes exposed Feeding rate (%) Number of mosquitoes Dissected (%) Number of mosquitoes Infected Prevalence of infection (%) Total oocysts count Oocyst density/midgut Serum replacement 3760 65.20% 1960 (82.2) 15 0.8 15 1 Whole blood 3760 56.60% 1934 (80.2) 9 0.5 16 1.8 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 24 Feb, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 26 Aug, 2024 Reviews received at journal 19 Aug, 2024 Reviews received at journal 18 Aug, 2024 Reviews received at journal 29 Jul, 2024 Reviews received at journal 19 Jul, 2024 Reviewers agreed at journal 19 Jul, 2024 Reviewers agreed at journal 17 Jul, 2024 Reviewers agreed at journal 17 Jul, 2024 Reviewers agreed at journal 17 Jul, 2024 Reviewers invited by journal 16 Jul, 2024 Editor assigned by journal 12 Jul, 2024 Editor invited by journal 11 Jul, 2024 Submission checks completed at journal 11 Jul, 2024 First submitted to journal 09 Jul, 2024 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4711223","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":335461873,"identity":"40e774b5-fadc-45da-8b54-50dc1cd92621","order_by":0,"name":"Shirley A. Onyango","email":"","orcid":"","institution":"Kenyatta University","correspondingAuthor":false,"prefix":"","firstName":"Shirley","middleName":"A.","lastName":"Onyango","suffix":""},{"id":335461874,"identity":"c2ae6107-af2f-4a27-b34d-6ea67f880e01","order_by":1,"name":"Maxwell G. Machani","email":"","orcid":"","institution":"Kenya Medical Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Maxwell","middleName":"G.","lastName":"Machani","suffix":""},{"id":335461875,"identity":"bc84b5aa-4172-499f-832a-1bd8b3e168d4","order_by":2,"name":"Kevin O. Ochwedo","email":"","orcid":"","institution":"University of Nairobi","correspondingAuthor":false,"prefix":"","firstName":"Kevin","middleName":"O.","lastName":"Ochwedo","suffix":""},{"id":335461876,"identity":"89233e1a-2dd3-49b1-8718-58afa54d156c","order_by":3,"name":"Robin M. Oriango","email":"","orcid":"","institution":"International Centre of Excellence for Malaria Research, Tom Mboya University","correspondingAuthor":false,"prefix":"","firstName":"Robin","middleName":"M.","lastName":"Oriango","suffix":""},{"id":335461877,"identity":"241d384f-faf1-44d1-ac60-b274db028677","order_by":4,"name":"Ming-Chieh Lee","email":"","orcid":"","institution":"University of California at Irvine","correspondingAuthor":false,"prefix":"","firstName":"Ming-Chieh","middleName":"","lastName":"Lee","suffix":""},{"id":335461878,"identity":"a51af05b-9dab-40b2-9976-4a8c64eab14b","order_by":5,"name":"Elizabeth Kokwaro","email":"","orcid":"","institution":"Kenyatta University","correspondingAuthor":false,"prefix":"","firstName":"Elizabeth","middleName":"","lastName":"Kokwaro","suffix":""},{"id":335461879,"identity":"87ff64b8-c7b6-453e-8c17-e4b4d64590e8","order_by":6,"name":"Yaw A. Afrane","email":"","orcid":"","institution":"University of Ghana","correspondingAuthor":false,"prefix":"","firstName":"Yaw","middleName":"A.","lastName":"Afrane","suffix":""},{"id":335461880,"identity":"ecb2b0b7-a8ea-481f-983e-a6b13f9de9cb","order_by":7,"name":"Andrew K. Githeko","email":"","orcid":"","institution":"Kenya Medical Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"K.","lastName":"Githeko","suffix":""},{"id":335461881,"identity":"0b1122ea-d212-4782-b403-95801c36041e","order_by":8,"name":"Daibin Zhong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYDCCAzwg0iYBzAGSjA1EakkjXcvhBBifsBa+82cPPi74dT5PvoHH8MMDBhvZDQcIaJE8cC7ZeGbf7WKDAzzGEgkMacYEtRgc7DGT5u25nbiBgccM6JfDiYS1HOYBaTmXOL8BrOU/EVqOAbXw/DiQ2HAArOUAYS2SZ3iMjXkbkhM3HGYrlkgwAHqMkBa+82cMH/P8sUuc39688eOPCjvZPkJawICxDUgwg91JjHIw+EO0ylEwCkbBKBiJAABRU0S/za7PuwAAAABJRU5ErkJggg==","orcid":"","institution":"University of California at Irvine","correspondingAuthor":true,"prefix":"","firstName":"Daibin","middleName":"","lastName":"Zhong","suffix":""},{"id":335461882,"identity":"7ebfde5e-a1a0-4320-b542-b58668c41f13","order_by":9,"name":"Guiyun Yan","email":"","orcid":"","institution":"University of California at Irvine","correspondingAuthor":false,"prefix":"","firstName":"Guiyun","middleName":"","lastName":"Yan","suffix":""}],"badges":[],"createdAt":"2024-07-09 10:21:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4711223/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4711223/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-84847-6","type":"published","date":"2025-02-24T15:58:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62184715,"identity":"70f2cf96-1eb0-45a3-b134-29e16bf74373","added_by":"auto","created_at":"2024-08-10 11:46:58","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":108627,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMap of Chulaimbo, Kisumu County showing the sampling locations. \u003c/strong\u003eThe map was generated using ArcGIS Pro 2.6 software. Map source: ESRI, CGIAR, and USGS (available at: www.esri.com).\u003c/p\u003e","description":"","filename":"Slide1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4711223/v1/f9cb27f1990ffd8632bcaa1a.jpg"},{"id":62184716,"identity":"55cefeac-ebc5-4983-b459-a5dba0fe3d04","added_by":"auto","created_at":"2024-08-10 11:46:59","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":52925,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFrequency of infectious Pfs47 haplotypes in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ePlasmodium falciparum\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003eThe graph displays parasite haplotypes identified from infectious blood samples that infected and progressed to oocyst in the \u003cem\u003eAn. gambiae\u003c/em\u003e midgut. Haplotype­ 4 with mutation L240I (purple) had the highest frequency (most infectious), followed by haplotype 3 with E27D (green) and haplotype 6 that was conserved (black), haplotype 1 with dimorphic sites E27D and L240I (blue), haplotype 5 with dimorphic site E188D (orange) and lastly haplotype 2 with dimorphic site S98T (red).\u003c/p\u003e","description":"","filename":"Slide1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4711223/v1/8dae0e0153ebf2e8fd16f1aa.jpg"},{"id":77622525,"identity":"92e52960-5f99-4fe8-8dcb-630699264949","added_by":"auto","created_at":"2025-03-03 16:07:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1116000,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4711223/v1/4a9758cb-a98f-4f4e-8c14-dcd3836725fc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Compatibility Interactions between Anopheles gambiae and Plasmodium falciparum in a Malaria Endemic Region in Kisumu, Kenya ","fulltext":[{"header":"Background","content":"\u003cp\u003eInsecticide resistance \u003csup\u003e1\u0026ndash;4\u003c/sup\u003e and outdoor transmission \u003csup\u003e5\u0026ndash;8\u003c/sup\u003e have compromised the efficacy of primary malaria control interventions, necessitating the development of new or improved targeted strategies that could complement the control of malaria, such as transmission-blocking approaches. Molecular mechanisms underlying \u003cem\u003ePlasmodium\u003c/em\u003e infections and mosquito genotypes influencing parasite adaptations to diverse \u003cem\u003eAnopheles\u003c/em\u003e species are critical in understanding malaria transmission dynamics and for developing targeted vector control interventions that may compliment already existing ones.\u003c/p\u003e \u003cp\u003eMalaria transmission primarily depends on competent vectors and compatible infectious parasites to influence susceptibility in local \u003cem\u003eAnopheles\u003c/em\u003e populations\u003csup\u003e9\u003c/sup\u003e. The mosquito immune factors, including recognition receptors, cellular and humoral components, influence the infectiousness of gametocytes in vectors \u003csup\u003e10\u003c/sup\u003e. The likelihood of infection after ingesting gametocytes from an infected person is determined by a combination of factors like the mosquito's immune responses among others \u003csup\u003e10\u0026ndash;13\u003c/sup\u003e. The thioester-containing protein 1 (TEP1) is an important immunological gene that exhibits allele-linked variations \u003csup\u003e14\u003c/sup\u003e and also inhibits pathogens including \u003cem\u003ePlasmodium\u003c/em\u003e infections in mosquitoes \u003csup\u003e15\u003c/sup\u003e, hence altering vector competence and malaria infectivity \u003csup\u003e16,17\u003c/sup\u003e. In contrast, the malaria parasite \u003cem\u003eP. falciparum\u003c/em\u003e has evolved to circumvent the vectors' immune responses mediated by the Pfs47 \u003csup\u003e18,19\u003c/sup\u003e. The Pfs47 gene displays haplotypes that naturally select specific mosquito midgut receptors resulting in significant transmission variability \u003csup\u003e9\u003c/sup\u003e. According to Sinka \u003cem\u003eet al\u003c/em\u003e \u003csup\u003e20\u003c/sup\u003e, around 70 \u003cem\u003eAnopheles\u003c/em\u003e species now transmit \u003cem\u003eP. falciparum\u003c/em\u003e malaria around the world.\u003c/p\u003e \u003cp\u003eRecent studies have revealed that compatible Pfs47 haplotypes are selected by specific vector receptors in the midgut, eluding the immune system and increasing the likelihood of infection. However, incompatible haplotypes are detected and eliminated by the vector's immune defenses \u003csup\u003e18\u003c/sup\u003e. Furthermore, selection pressures imposed by local \u003cem\u003eAnopheles\u003c/em\u003e populations dominant in a given region may have altered the genetic diversity of Pfs47 haplotypes, resulting in parasite adaptations to native vector species. Therefore, the associations between the TEP1 immunity gene in \u003cem\u003eAnopheles\u003c/em\u003e and Pfs47 in \u003cem\u003eP. falciparum\u003c/em\u003e may be an important determinant of malaria infections and could be targeted in blocking malaria transmission in primary vectors efficient in transmitting malaria from a molecular perspective. Moreover, \u003cem\u003eAnopheles-Plasmodium\u003c/em\u003e interactions are complex and have not been clearly understood yet, form a basis for increasing the knowledge gaps of host factors on vector competence. Also, these interactions are potential targets for developing malaria transmission-blocking interventions. The aim of this study is to determine the incidence of malaria in school-aged children, \u003cem\u003eAnopheles\u003c/em\u003e vector feeding and infection rates, parasite genotypes, their associations with mosquito infectivity, and mosquito-parasite interactions in a malaria-endemic region in western Kenya.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eStudy site and population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsented children aged 5 -15 years were screened following a cross-sectional study design from sub locations in Chulaimbo, Kisumu County (Figure 1), during the wet season from October to December 2019 and October to December 2020, and the dry season (January to March 2020). Chulaimbo is a rural site 19 km north-west of Kisumu City, located at 0.03572\u0026deg;S, 34.621\u0026deg;E, and an altitude range of 1328-1458 meters above sea level \u003csup\u003e21\u003c/sup\u003e. The region has a mean annual temperature range of 12\u003csup\u003e0\u003c/sup\u003eC - 35\u0026deg;C. This region experiences an average annual rainfall of 1352 mm and an average relative humidity between 66 and 83%. Malaria transmission in this area is endemic, with \u003cem\u003ePlasmodium falciparum \u003c/em\u003eas\u003cem\u003e \u003c/em\u003ethe dominant parasite species in the area \u003csup\u003e22\u003c/sup\u003e. Most residents are small-scale subsistence farmers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eM\u003c/strong\u003e\u003cstrong\u003eosq\u003c/strong\u003e\u003cstrong\u003euitoes used for the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLaboratory reared \u003cem\u003eAnopheles gambiae\u003c/em\u003e female mosquitoes (Kisumu strain) between 3-5 days post-emergence were used for membrane feeding assays. This colony was selected and maintained at the Center of Excellence for Malaria Research in Homa Bay, Western Kenya. They were reared at temperatures of 27 - 29\u003csup\u003e0\u003c/sup\u003eC, 69 - 80% relative humidity (RH), and a 12 hours light and 12 hours dark cycle. The colony was then constantly maintained on 10% sucrose \u003csup\u003e23\u003c/sup\u003e after the blood meal until the dissection day. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIdentifying gametocyte carriers\u003c/strong\u003e \u003c/p\u003e\n\u003cp\u003eParasitological assessments to detect \u003cem\u003eP. falciparum\u003c/em\u003e gametocyte carriers were conducted in school-aged children between the ages of 5 and 15 years, who had assented and had their guardians\u0026apos; consent to participate in the study. Blood samples were obtained from the children using finger pricks on well-labeled Whatman\u0026reg; 903 Protein Saver Cards (GE Healthcare WB100014) with the participants\u0026apos; information. A total of 50 \u0026micro;l of blood were collected and placed onto the cards, which were then air dried before being stored and stored at -20\u003csup\u003eo\u003c/sup\u003eC for further molecular analyses. As the blood was being collected on cards, thick and thin smears were also prepared for the same participant. The blood films were stained with 10% Giemsa and read after drying. Parasites were viewed under a compound microscope and \u003cem\u003ePlasmodium\u003c/em\u003e species identified in thick smears Malaria parasites counts were read against 500 white blood cells. Gametocyte densities were determined in slides for all \u003cem\u003eP. falciparum\u003c/em\u003e positive participants by counting the number of gametocytes per 500 leukocytes by microscopy and expressed as parasites per \u0026mu;l assuming a standard white blood cell (WBC) concentration of 8000/\u0026mu;l \u003csup\u003e24\u003c/sup\u003e. Two trained microscopists took two readings per slide smear, and 20% of the slides were randomly selected for quality control verification by a senior external microscopist. Membrane feeding was limited to slides of gametocyte positive subjects only. Individuals who tested positive for malaria and had symptoms were referred to a local health center and treated according to Ministry of Health recommendations.\u003csup\u003e25\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMosquito infections using membrane feeding assays\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIndividuals identified as carriers among screened volunteers, who tested positive for \u003cem\u003eP. falciparum\u003c/em\u003e gametocytes donated blood for whole blood and serum replaced experiments in the laboratory. Blood was drawn intravenously by a professional phlebotomist using butterfly needles. Approximately 3ml of blood was collected by venipuncture in heparinized tubes for each volunteer. An aliquot of 1ml of blood was immediately placed into pre-warmed hemotek feeders (1ml capacity) at 37\u0026deg;C, while another 1.5ml was transferred into 2ml Eppendorf tubes and centrifuged at 2000 rounds per minute for 2 minutes before adding it to the hemotek feeders. The supernatant of serum was discarded and replaced with a na\u0026iuml;ve human serum type AB (Bio Whittaker, Cambrex Bio Science Walkersville, MD, USA). Replaced blood was then quickly transferred to the feeders to allow the starved mosquitoes to feed. \u003c/p\u003e\n\u003cp\u003eParticipants\u0026rsquo; blood positive for gametocytes was used to feed the insectary reared \u003cem\u003eAnopheles gambiae\u003c/em\u003e mosquitoes using membrane feeding assays (serum replacement and whole blood experiments) \u003csup\u003e26\u003c/sup\u003e. Aggressive 3-5 day old female \u003cem\u003eAnopheles gambiae \u003c/em\u003emosquitoes were starved for 6 to 8 hours prior to feeding on infected blood. Whole blood and serum replacement experiments were conducted for each participant. A total of 37 paired experiments were conducted. Each feeding cup contained 100 mosquitoes. The mosquitoes were allowed to feed from different feeders of the same infected blood for 15-30 minutes through a parafilm membrane. All membrane feeding procedures were conducted at 37\u003csup\u003e0\u003c/sup\u003eC using the hemotek system. Only fully engorged blood-fed mosquitoes were selected and maintained at 27-29\u003csup\u003e0\u003c/sup\u003eC temperatures and 69-80% relative humidity following a 12 hours light and 12 hours dark cycle. They were given 10% sucrose for 9 days post-feeding and the ones that survived were dissected for midgut oocysts enumeration. The unfed and partially fed mosquitoes were discarded by freezing them for 15 minutes at -20\u003csup\u003e0\u003c/sup\u003eC. After membrane feeding, volunteers were treated with artemether-lumefantrine (Coartem\u0026reg;) according to the Ministry of Health guideline \u003csup\u003e25\u003c/sup\u003e. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOocysts counts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll fully engorged mosquitoes that survived on day 8 or 9 post-feeding were dissected under a dissecting microscope as described by Afrane \u003cem\u003eet al\u003c/em\u003e \u003csup\u003e27\u003c/sup\u003e. Briefly, each mosquito gut was carefully pulled out from the abdomen in 0.5% mercurochrome and allowed to stain for 10 minutes. The midguts were then examined for the presence of oocysts under a light microscope. The number of oocysts observed were counted and recorded per mosquito gut. The oocysts load was expressed as the number of oocysts per infected mosquito. Mosquito carcasses corresponding to their infected midguts were labeled and preserved for further molecular assays to determine TEP1 genotypes\u003csup\u003e28\u003c/sup\u003e. Briefly, TEP1 was genotyped using a nested PCR-RFLP targeting 892 base pairs for nest 1 and a final fragment length of 758 base pairs after nest 2. Both PCR reaction conditions were set as denaturation at 95 \u0026deg;C for 3 min, 35 cycles of 94\u0026deg;C for 30s, annealing at 55\u0026deg;C for 30s, extension at 72\u0026deg;C for 30s, and a final step at 72 \u0026deg;C for 6 min using Dream Taq Green Master Mix (Thermo Fisher Scientific). PCR products were then digested using restriction enzymes Bam HI, Hind III, or Bse NI (New England Biolabs Inc) according to the manufacturer\u0026rsquo;s instructions and the result analyzed on 2.5% agarose gel electrophoresis. The TEP1 allelic classes were determined by fragment size of restriction enzyme digestion. A subset was also randomly selected for the genotype confirmatory purposes by sequencing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA extraction and parasite genotyping\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Chelex technique was used to obtain \u003cem\u003ePlasmodium\u003c/em\u003e parasite DNA from the dried blood spots \u003csup\u003e29\u003c/sup\u003e. As previously reported \u003csup\u003e30\u003c/sup\u003e, a multiplex real-time PCR (RT-PCR) was utilized to identify \u003cem\u003ePlasmodium\u003c/em\u003e species. Pfs47 was genotyped using PCR and Sanger sequencing, as previously published \u003csup\u003e30\u003c/sup\u003e. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ethical review board of the Maseno University, Kenya (MSU/DRPI/MUERC/00456/17) reviewed and approved the protocol for screening of \u003cem\u003eP. falciparum \u003c/em\u003egametocyte carriers and subsequent intravenous blood drawing. A detailed written informed assent and consent to participate in the study was provided by all study volunteers and their parents or guardians. Feeding of mosquitoes was conducted in a secure, insect-proof room at the Chulaimbo health center. All experiments and methods were performed in accordance with the institution\u0026rsquo;s guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData from the participants was tabulated in Microsoft Excel V16. Computing descriptive statistics (sum, mean, standard deviation, standard error, and 95% confidence interval) and comparing means were done using Graph Pad Prism v.8.0.1 and SPSS version 25 for Windows software. The Shapiro\u0026ndash;Wilk normality test was used to check data normality before performing multiple mean comparisons and chi-square tests. Data were considered statistically significant at P\u0026lt;\u0026thinsp;0.05. The codoncode Aligner 11.0.1 (CodonCode Corp., Centerville, MA) was used to check the sequence quality and trim low-quality bases. Bio-Edit software was used to align the sequences and determine the nonsynonymous mutations and codon changes based on reference sequence (Pf3D7_1346800). MEGA software was used to construct the UPGMA (unweighted pair group method with arithmetic mean) tree based on the Kimura 2-parameter (K2P) distance model with 1,000 bootstrap replicates.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eParasitological surveys\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 4481 children that were tested for malaria, 885 tested positive, representing a 19.7% infection prevalence (95% CI: 0.003-0.007).\u0026nbsp;Most positive cases were attributed to \u003cem\u003eP. falciparum\u003c/em\u003e infections, accounting for 95% (841) of the total infections. Other \u003cem\u003ePlasmodium\u003c/em\u003e species identified in the study area were \u003cem\u003eP\u003c/em\u003e. \u003cem\u003emalariae\u003c/em\u003e (1.6%), \u003cem\u003eP. ovale\u0026nbsp;\u003c/em\u003e(0.3%), and mixed infections involving \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP. malariae\u003c/em\u003e (\u003cem\u003ePf/Pm\u003c/em\u003e) or \u003cem\u003eP. ovale\u003c/em\u003e (\u003cem\u003ePf/Po\u003c/em\u003e), each accounting for 2.7% of the infections. Out of the 841 confirmed \u003cem\u003eP. falciparum\u003c/em\u003e positive infections, (142/841) 16.9% of the participants had \u003cem\u003eP. falciparum\u003c/em\u003e gametocytes that were confirmed by microscopy. \u0026nbsp;The overall gametocyte density was 37.3 gametocytes/ \u0026micro;l of blood. The gametocyte prevalence was 6.9% whereas the density ranged from 16-176\u0026nbsp;gametocytes/ \u0026micro;l of blood treating each infection as an individual entity. The odds of finding microscopic gametocyte infections were significantly high during the dry season (OR 1.37, 95% CI, P=0.001) compared to the wet season (Table 1). Males were 1.23 times more likely than females to harbor microscopic gametocyte infections.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMosquito infections\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 109 children out of 142 who tested positive for \u003cem\u003eP. falciparum\u003c/em\u003e gametocytes were subjected to membrane feeding experiments. Only 34% of those who had gametocytes infected mosquitoes on day 9 post-feeding. A total of 3894 mosquitoes were dissected, 1960 in serum replacement and 1934 in whole blood to evaluate infection rates. Thirty-seven paired membrane feeding experiments from the same donor had infection rates of 0.8% (15/1960) and 0.5% (9/1934), with oocyst densities of 1 and 1.8 in serum replacement and whole blood, respectively. (Table 2). The difference in both experiments was however not significant (P=0.738).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePlasmodium falciparum\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Pfs47 haplotypes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSix infectious haplotypes were identified from the 24 sequenced gametocyte containing dried blood spots (DBS). Haplotype 1 (Hap_1) had dimorphic codon E27D and L240I, Hap_2, Hap_3, Hap_4, Hap_5 had S98T, E27D, L240I, and E188D mutations respectively, whereas, Hap_6 was conserved or had no polymorphic site (Fig 2). Genotyped parasite DNA from blood infected with Hap_4 with the dimorphic codon L2401 was frequent at 29.2% (7) with positive oocyst results followed by Hap_3 (E27D) and Hap_6, each with 20.8% (5). Infectious haplotypes with E27D and L240I mutations (Hap_1) were at a frequency of 16.7% (4) whereas Hap_2 (S98T0) and Hap_5 (E188D) was each present at a frequency of 4.2% (1) and 8.3% (2) respectively.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMalaria vector and parasite interaction is a key determinant towards successful transmission \u003csup\u003e9\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e31\u003c/sup\u003e. For an established or localized transmission system, there is need for susceptible vector genotype populations and infectious \u003cem\u003ePlasmodium\u003c/em\u003e haplotypes that evoke endogenous compatible immune evasive elements that circumvent them. This study shows the compatibility of probable infectious \u003cem\u003ePfs47\u003c/em\u003e haplotypes characterized by specific codon variants that may influence infectivity to \u003cem\u003eAn. gambiae\u003c/em\u003e mosquitoes. These results may have implications on the parasites capacity to evade the vectors\u0026rsquo; immune defenses effectively completing its transmission cycle. Haplotype 4 with codon L240I had the highest frequency among the infectious haplotypes that progressed to detectable oocyst in the midgut and could be linked to increased infectivity or transmission potential to vectors followed by haplotypes; Hap_3 (E27D) and Hap_6 (without polymorphic sites) then Hap_1(E27D and L240I). Despite Hap_1 having two dimorphic sites E27D and L240I, the genotypic combination did not appear to increase its frequency or malaria transmission in the region. The other haplotypes Hap_2(S98T) and Hap_5(E188D) also infected mosquitoes displaying a probable limited compatibility. Furthermore, the observed levels of infection of \u003cem\u003eAn. gambiae s. s.\u003c/em\u003e by the six identified Pfs47 haplotypes implies different levels of compatibility that could facilitate malaria transmission. The six haplotypes should further be evaluated using field-collected \u003cem\u003eAnopheles\u003c/em\u003e vectors common in a specific endemic location as well as their potential to spread disease in natural vector populations.\u003c/p\u003e\n\u003cp\u003eA previous study conducted from western Kenya identified thirteen Pfs47 haplotypes, with haplotypes harboring the mutation codon E27D having the highest frequency of over 50%, followed by conserved Pfs47 haplotypes whereas the rest occurred at a frequency of 6.7% or lower \u003csup\u003e30\u003c/sup\u003e. Even though haplotypes with E27D were most common, haplotypes with L240I were more infectious to \u003cem\u003eAn. gambiae s. s.\u003c/em\u003e which may imply that it has enhanced evasion of the vector immune defenses. Also, all \u003cem\u003eAn. gambiae s. s\u003c/em\u003e used were reared in the insectary and harbored the homozygous TEP1* S1/S1 genotypes. The high prevalence of TEP1* S1/S1 observed in this mosquitoes is an indication of populations being susceptible to \u003cem\u003ePlasmodium\u003c/em\u003e gametocytes \u003csup\u003e32\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e33\u003c/sup\u003e and may have been highly compatible with gametocytes containing the L240I dimorphism following the \u0026ldquo;lock-and-key\u0026rdquo; analogy described by Molina-Cruz et al \u003csup\u003e9\u003c/sup\u003e unlike the other infectious haplotypes that were identified in the region. The \u003cem\u003ePfs47\u003c/em\u003e gene has undergone natural selection as a result of adaptations to diverse anopheline species found in different continents hence a strong population structure \u003csup\u003e9\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e31\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e34\u003c/sup\u003e. Furthermore, parasites with compatible Pfs47 haplotypes can elude complement activation and survive within invaded midgut cells \u003csup\u003e35\u003c/sup\u003e. To evaluate the possible influence on the dynamics of malaria transmission, it is essential to understand the frequency and distribution of these haplotypes. Higher transmission rates might result from some haplotypes\u0026rsquo; greater ability to overcome mosquito immune responses.\u003c/p\u003e\n\u003cp\u003eApart from vectors and gametocyte compatibility human antibodies against gametocytes play a critical role in transmission blocking or reduction capabilities in addition to their compatibility \u003csup\u003e36-38\u003c/sup\u003e. As a result, high gametocyte densities may not always indicate successful mosquito infection. Low gametocyte densities, on the other hand, do not also exclude infectiousness \u003csup\u003e39\u003c/sup\u003e. A weak association between gametocyte density and infection rates was observed despite exposing numerous mosquitoes with infected blood. The low infection rates in the mosquito may have been an indication that serum replacement and whole blood experiments used in this study did not have a significant impact on infection rates or other factors including the gametocyte densities, sex ratios of male to female gametocytes, the genetic makeup of the gametocytes, and the immune factors may have inhibited infections in the mosquito. This finding corroborated previous investigations \u003csup\u003e40\u003c/sup\u003e that also documented low infection rates, and weak association between gametocyte densities and mosquito infection rates which varied with low gametocyte densities.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eMolecular interactions underlying mosquito immune responses to \u003cem\u003eP. falciparum\u003c/em\u003e infections and the immune evasion tactics is of importance. Recombinant \u003cem\u003eP. falciparum\u003c/em\u003e parasites with Pfs47 haplotypes from diverse locations across the world but with a similar genetic makeup were utilized to test the hypothesis that Pfs47 haplotypes impact parasite survival in local vectors from distinct geographical regions. These results confirm that changing the Pfs47 haplotype by itself was sufficient to change compatibility with various vectors as a potential target for inhibiting transmission in the mosquito host \u003csup\u003e9\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e41\u003c/sup\u003e. The functional importance of these genetic differences in Pfs47 and their associations with vector immunological genes, as well as how these changes affect the efficacy of malaria control strategies, may require further research. Overall, this research sheds significant insight into the genetic diversity of parasites of malaria and its potential impact on efforts to prevent the disease. These findings suggest a potent approach for controlling the spread of the malaria parasite by targeting Pfs47 haplotypes linked to increased mosquito infection rates.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDBS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDried blood spots\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePfs47\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003ePlasmodium falciparum\u003c/em\u003e surface protein 47\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eTEP1\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThioester containing protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRT-PCR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReal time polymerase chain reaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePCR-RFLP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePolymerase chain reaction restriction fragment length polymorphism\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the University of California, Irvine Institutional Review Board (UCI IRB) and Maseno University Ethics Review Committee (MUERC protocol No. 00456) and\u003c/p\u003e\n\u003cp\u003eauthorized by the Ministry of Health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe express our sincere gratitude to the village elders, residents and participants for their continued support, all community health workers, field assistants and the entire ICEMR staff who participated in this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProject conceptualization: SAO, KOO and DZ, Project implementation: SAO, DZ, YAA and AKG, Data collection and sample analysis: SAO, MGM, and RMO, Formal analysis: SAO, KOO, and DZ. Drafting manuscript: SAO. Editing and revising manuscript: KOO, MGM, AKG, ML, EK, YAA, DZ, and GY. Funded project: GY\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData supporting the conclusions of this study is included within the article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors have declared that no competing interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from the National Institute of Health (R01 AI123074, U19 AI129326, R01 AI050243, D43 TW001505). 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PLoS One 11, e0168279, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0168279\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0168279\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable.1: Chi-square, Odds Ratios, and 95% Confidence Intervals (CIs) for gametocyte prevalence by season and gender\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"668\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.55688622754491%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber screened\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.7125748502994%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGametocyte Density/\u0026micro;l\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.065868263473053%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGametocyte Prevalence\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.580838323353293%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.730538922155688%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.826347305389222%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.826347305389222%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeason\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.730538922155688%\" valign=\"top\"\u003e\n \u003cp\u003eWet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e3690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.7125748502994%\" valign=\"top\"\u003e\n \u003cp\u003e30.88 (26.67 - 35.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.065868263473053%\" valign=\"top\"\u003e\n \u003cp\u003e682 (18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.580838323353293%\" valign=\"top\"\u003e\n \u003cp\u003e11.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.730538922155688%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.826347305389222%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1.37 (1.14-1.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.606741573033707%\" valign=\"top\"\u003e\n \u003cp\u003eDry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.303370786516854%\" valign=\"top\"\u003e\n \u003cp\u003e791*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.089887640449437%\" valign=\"top\"\u003e\n \u003cp\u003e44.11(28.43 - 68.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.617977528089888%\" valign=\"top\"\u003e\n \u003cp\u003e187 (23.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.382022471910112%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.826347305389222%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.730538922155688%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.52694610778443%\" valign=\"top\"\u003e\n \u003cp\u003e2262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.7125748502994%\" valign=\"top\"\u003e\n \u003cp\u003e32.03 (26.15 -39.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.065868263473053%\" valign=\"top\"\u003e\n \u003cp\u003e403 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.580838323353293%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e7.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.730538922155688%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.826347305389222%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1.23 (1.06-1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.060367454068242%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.20997375328084%\" valign=\"top\"\u003e\n \u003cp\u003e2219*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.808398950131235%\" valign=\"top\"\u003e\n \u003cp\u003e31.97 (26.30 - 38.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.921259842519685%\" valign=\"top\"\u003e\n \u003cp\u003e466 (21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Reference categories\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Infection prevalence for paired experiments (n=37)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"698\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.878397711015737%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;Experiment types\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.872675250357654%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of mosquitoes exposed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.015736766809729%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFeeding rate (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.7310443490701%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of mosquitoes Dissected (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.589413447782546%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of mosquitoes \u0026nbsp;Infected\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.874105865522175%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence of infection (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal oocysts count\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.453505007153076%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOocyst density/midgut\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.878397711015737%\"\u003e\n \u003cp\u003eSerum replacement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.872675250357654%\"\u003e\n \u003cp\u003e3760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.015736766809729%\"\u003e\n \u003cp\u003e65.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.7310443490701%\"\u003e\n \u003cp\u003e1960 (82.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.589413447782546%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.874105865522175%\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.453505007153076%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.878397711015737%\"\u003e\n \u003cp\u003eWhole blood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.872675250357654%\"\u003e\n \u003cp\u003e3760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.015736766809729%\"\u003e\n \u003cp\u003e56.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.7310443490701%\"\u003e\n \u003cp\u003e1934 (80.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.589413447782546%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.874105865522175%\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.585121602288984%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.453505007153076%\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n 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falciparum, Pfs47, An, gambiae, compatibility, geographic regions","lastPublishedDoi":"10.21203/rs.3.rs-4711223/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4711223/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eInsecticide resistance and outdoor transmission have reduced the effectiveness of existing malaria transmission prevention strategies. As a result, targeted approaches to support continuing malaria therapies, such as transmission-blocking vaccines, are required. Cross-sectional mass blood screening in children between 5 and 15 years was conducted in Chulaimbo, Kisumu, during the dry and wet seasons in 2018 and 2019. \u003cem\u003ePlasmodium falciparum\u003c/em\u003e gametocyte carriers were identified by Microscopy. Subsequently, carries were used to feed colony bred \u003cem\u003eAnopheles gambiae\u003c/em\u003e females in serum replacement and whole blood membrane feeding experiments. The infection prevalence was 19.7% (95% Cl: 0.003\u0026ndash;0.007) with 95% of the infections being caused by \u003cem\u003eP. falciparum\u003c/em\u003e. Of all confirmed \u003cem\u003eP. falciparum\u003c/em\u003e infections, 16.9% were gametocytes. Thirty-seven paired experiments showed infection rates of 0.9% and 0.5% in the serum replacement and whole blood experiments, respectively, with no significant difference (P\u0026thinsp;=\u0026thinsp;0.738). Six Pfs47 haplotypes were identified from 24 sequenced infectious blood samples. Hap_1 (E27D and L240I), Hap_2 (S98T0); Hap_3 (E27D); Hap_4 (L240I); Hap_5 (E188D); and Hap_6 without mutations. Haplotype 4 had the highest frequency of 29.2% followed by Hap_3 and Hap_6 at 20.8% each then Hap_1 with a frequency of 16.7%, whereas Hap_5 and Hap_2 had frequencies of 8.3% and 4.2% respectively. Varying frequencies of infectious Pfs47 haplotypes observed from genetically heterogeneous parasite populations in endemic regions illuminates vector compatibility to refracting \u003cem\u003eP. falciparum\u003c/em\u003e using the hypothesized lock and key analogy. This acts as a bottleneck that increases the frequency of \u003cem\u003eP. falciparum\u003c/em\u003e haplotypes that escape elimination by vector immune responses. The interaction can be used as a potential target for transmission blocking through a refractory host.\u003c/p\u003e","manuscriptTitle":"Compatibility Interactions between Anopheles gambiae and Plasmodium falciparum in a Malaria Endemic Region in Kisumu, Kenya ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-10 11:46:54","doi":"10.21203/rs.3.rs-4711223/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-26T05:11:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-19T10:50:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-19T01:26:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-29T17:30:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-19T16:25:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"105135549979890445953288973663790820050","date":"2024-07-19T05:49:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"334970098979032892806503672332805572975","date":"2024-07-18T03:15:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"211090183049361286675132415120110671931","date":"2024-07-17T08:32:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"127005362075898179649934851644679978066","date":"2024-07-17T04:51:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-17T01:24:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-12T05:18:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-12T03:35:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-11T04:13:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-07-09T10:18:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b418855b-422d-4d06-af43-8bcb9f6c3419","owner":[],"postedDate":"August 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":35530670,"name":"Biological sciences/Evolution"},{"id":35530671,"name":"Biological sciences/Genetics"},{"id":35530672,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2025-03-03T16:02:32+00:00","versionOfRecord":{"articleIdentity":"rs-4711223","link":"https://doi.org/10.1038/s41598-024-84847-6","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-02-24 15:58:00","publishedOnDateReadable":"February 24th, 2025"},"versionCreatedAt":"2024-08-10 11:46:54","video":"","vorDoi":"10.1038/s41598-024-84847-6","vorDoiUrl":"https://doi.org/10.1038/s41598-024-84847-6","workflowStages":[]},"version":"v1","identity":"rs-4711223","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4711223","identity":"rs-4711223","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}