Characterization of Volatile Organic Compounds from Waterborne and Nectar-Dwelling Yeasts Attractive to Asian Tiger Mosquitoes

Characterization of Volatile Organic Compounds from Waterborne and Nectar-Dwelling Yeasts Attractive to Asian Tiger Mosquitoes | 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 Research Article Characterization of Volatile Organic Compounds from Waterborne and Nectar-Dwelling Yeasts Attractive to Asian Tiger Mosquitoes SIMON MALASSIGNÉ, LAURENT VALLON, EDWIGE MARTIN, PIERRE ANTONELLI, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7258136/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Jan, 2026 Read the published version in Journal of Chemical Ecology → Version 1 posted 9 You are reading this latest preprint version Abstract Volatile organic compounds (VOCs) emitted by floral scents and waterborne microorganisms can influence mosquito behavior. However, the role of nectar-dwelling yeasts and their VOCs in mosquito nectar seeking behavior, compared to waterborne microorganisms influencing oviposition, remains underexplored. To investigate this in Aedes albopictus , a species well adapted to urban environments, we characterized yeast communities from visited and non-visited flowers, as well as from colonized and non-colonized breeding-site waters in urban community gardens. We identified yeast species and their associated VOCs involved in mosquito behavioral responses. Yeast communities differed between floral and aquatic habitats, although several taxa, including generalist species frequently isolated from nectar, were shared between both environments, likely through insect transmission or pollen dissemination. Two nectar-dwelling yeasts, Metschnikowia reukaufii and Aureobasidium pullulans , attracted males and females through the emission of 3-methyl-1-butanol, ethanol, 2-methyl-1-butanol, and isobutyl alcohol, respectively. In contrast, two waterborne yeasts, Cystobasidium slooffiae and Rhodotorula mucilaginosa , which were preferentially associated with colonized breeding sites, attracted gravid females and produced blends characterized by lower VOC richness and reduced concentrations of 3-methyl-1-butanol and 2-methyl-1-butanol. These results highlight the importance of yeast-emitted VOCs as semiochemicals guiding nectar feeding and oviposition in mosquitoes and call for further investigation into their ecological relevance. Aedes albopictus breeding-site waters wild and ornamental flowers yeast communities volatile organic compounds nectar-seeking and oviposition behavior Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 INTRODUCTION Hematophagous mosquitoes, including species from the genera Aedes , Culex and Anopheles , are holometabolous insects that undergo complete metamorphosis (Truman 2019 ). After hatching, they pass through four larval instars before reaching the pupal stage and ultimately emerging as adults (Clements 1992). Immature and adult stages occupy distinct ecological niches, with larvae developing in aquatic habitats, whereas adults live in terrestrial environments. This spatial separation is a key ecological strategy to minimize intraspecific competition for resources (Truman 2019 ). Larvae primarily feed on organic matter in water, such as microorganisms and plant debris, using filtering, grazing, and shredding behaviors (Merrit et al. 1992; Yee et al. 2004 ; Souza et al. 2019 ). In contrast, although females require blood meals for egg production (Harrison et al. 2021 ), adult mosquitoes of both sexes rely on sugar-rich sources, such as flower nectar, to meet their energy and nutritional needs (Barredo and DeGennaro 2020 ; Sobhy and Berry 2024 ). Floral nectar, rich in natural sugars like sucrose, glucose, and fructose, is essential for adult mosquito survival, flight, and reproductive success (Foster 1995 ; Spitzen and Takken 2018 ). This energy source is particularly vital for males, which feed exclusively on plant-derived sugars. Without regular sugar intake, males typically survive only a few days post-emergence (Bellini et al. 2014 ; Chadee et al. 2014 ). The lack of sugar-derived energy reserves severely limits their ability to fly or copulate, with detrimental consequences for their reproductive potential (Bellini et al. 2014 ). While females are more resilient to sugar deprivation, their survival and fecundity are nonetheless compromised in its absence (Chadee et al. 2014 ). In Aedes aegypti and Ae. albopictus , for example, plant nectar consumption not only enhances female survival but also stimulates egg development and increases overall fecundity, thereby extending the oviposition period (Naziri et al. 2016 ; Nyasembe et al. 2021 ). Nectar quality varies considerably among flowering plant species, reflecting differences in the concentration and composition of sugars, essential amino acids, and other compounds (Venjakov et al. 2022). Due to its high sugar content, floral nectar is colonized by yeast and bacterial communities characterized by low species richness but high cell densities (Herrera et al. 2009 ; Pozo et al. 2011 ; Fenner et al. 2022 ; Quevedo-Caraballo et al. 2025 ). The metabolic activity of these nectar-dwelling microorganisms can alter nectar chemistry by modifying sugar and amino acid profiles, and by increasing both temperature and acidity (Herrera and Pozo 2010 ; Lenaerts et al. 2017 ; Sobhy et al. 2018 ; Vannette and Fukami 2018 ). As a result, not all flowering plants provide nectar of equal nutritional or energetic value. Microbially driven changes can influence the suitability of floral resources for nectar-feeding insects, including mosquitoes (Davis and Landolt 2013 ; Sobhy et al. 2018 ; Peach et al. 2021 ). These alterations may in turn influence mosquito fitness, foraging behavior, and plant preference (Gouagna et al. 2014 ; Manda et al. 2007 ; Nikbakhtzadeh et al. 2016 ; Paré et al. 2024 ). Similarly, mosquito breeding sites, enriched with organic matter derived from soil, decaying vegetation, animal cadavers, and excreta, promote the growth of diverse bacterial and fungal communities (Tawidian et al. 2021 ; Duval et al. 2024 ; Zhao et al. 2025 ). These microbial assemblages play a key role in shaping the mosquito microbiota and significantly influence larval development and major adult traits, such as body size and lifespan (Steyn et al. 2016 ; Dickson et al. 2017 ; Cansado-Utrilla et al. 2021 ; Zouache et al. 2022 ; Duval et al. 2024 ; Malassigné et al. 2025 ). In addition to serving as a primary food source, facultative symbionts acquired from the environment provide essential nutrients, such as B vitamins and amino acids, required for optimal larval development (Valzania et al. 2018 ; Wang et al. 2018 ; Malassigné et al. 2025 ). Besides predators and pathogens that negatively affect larval development, the variable nutritional value of microorganisms used as diet, along with the inconsistent supply of essential nutrients by facultative symbionts, differentially impact larval development and survival, thereby influencing breeding-site selection (Steyn et al. 2016 ; Souza et al. 2019 ; Girard et al. 2021 ; Malassigné et al. 2025 ; Raquin et al. 2025). Given that oviposition-site selection is strongly oriented toward maximizing offspring performance, gravid female mosquitoes from Aedes species preferentially select breeding sites colonized by conspecific larvae, while avoiding those where larvae are starved or infected with deleterious parasites (Reeves 2004 ; Shragai et al. 2019 ; Khan et al. 2023 ). To locate and select suitable nectar sugar meals and oviposition sites, mosquitoes rely on a combination of visual, gustatory, and olfactory cues (Wooding et al. 2020 ). An increasing number of studies highlight the role of volatile organic compounds (VOCs), whether present in floral scents or emitted by waterborne microorganisms, in mediating mosquito foraging and oviposition behaviors (Lahondère et al. 2020 ; Girard et al. 2021 ; Upshur et al. 2023 ; Malassigné et al. 2025 ). Nectar-inhabiting microorganisms, in particular, are known to significantly shape flower scent by producing and releasing various VOCs (Lenaerts et al. 2017 ; Rering et al. 2018 ; Sobhy et al. 2018 ; Schaeffer et al. 2019 ; Peach et al. 2021 ). These microbially derived compounds can sometimes act as honest signals of the quality of floral food source, thereby influencing the attractiveness and acceptability of flowers to nectar-visiting insects, including mosquitoes (Wright and Schiestl 2009 ; Davis et al. 2013 ; Rering et al. 2018 ; Sobhy et al. 2018 ; Crowley-Gall et al. 2021 ; Peach et al 2021 ). However, despite growing interest in the chemical ecology of mosquito-microbe interactions, the specific contribution of nectar-dwelling microorganisms and their emitted VOCs to mosquito nectar-seeking behavior remains poorly understood. Moreover, the extent to which these olfactory cues differ from those associated with waterborne microorganisms involved in oviposition-site selection remains largely unexplored (Girard et al. 2021 ; Sobhy and Berry 2024 ). In this context, we focused on yeast communities because Ae. albopictus mosquitoes harbor a diverse, environmentally acquired fungal community, with yeasts representing up to 84% of the mycobiota (Luis et al. 2019 ; Hedge et al. 2024). Yeasts abundantly present in floral nectar have been shown to significantly influence the nectar foraging preferences of insect pollinators, including mosquitoes, due to their consistent VOCs emissions (Becher et al. 2018 ; Sobhy et al. 2018 ; Rering et al. 2018 ; Yang et al. 2019 ; Peach et al. 2021 ). The Asian tiger mosquito Ae. albopictus is an invasive species that has become a global health concern due to its proliferation in urban and suburban areas worldwide as well as its involvement in several outbreaks (Solimini et al. 2018 ; Sherpa et al. 2019 ; Swan et al. 2022 ; Duval et al. 2023 ; Sansone et al. 2024 ; Cattaneo et al. 2025 ). Urban community gardens, established in European cities to enhance urban ecosystem health by increasing biodiversity, especially pollinators such as bees and butterflies, offer a wide variety of plant species and a high density of standing water containers. These conditions provide ideal sugar meal sources and oviposition habitats for Ae. albopictus (Ochoa et al. 2019 ; Jha et al. 2023 ; Schmack and Egerer 2023 ; Duval et al. 2024 ). In this study, we investigated the diversity and behavioral relevance of yeast communities associated with the nectar of flowers and oviposition sites foraged by Ae. albopictus. Specifically, we analyzed yeast assemblages from plants visited or not visited by adult mosquitoes, as well as from standing waters colonized or uncolonized by Ae. albopictus larvae. The sampling was conducted across 14 urban community gardens within the metropolitan area of Lyon in France, using a dual approach combining culture-based and sequencing methods to identify yeast taxa. Following yeast identification, we evaluated their impact on mosquito behavior related to nectar-seeking and oviposition. We subsequently characterized the VOCs they produce. Beyond providing new insight into the ecological role of microorganisms in shaping mosquito behavior, identifying VOCs that attract mosquitoes seeking nectar or oviposition sites may offer promising avenues for vector control. In particular, these microbially derived cues could serve as valuable complements to microbial human-skin attractants used in traps for host-seeking females (Akhoundi et al. 2018 ; Degener et al. 2019 ; Staunton et al. 2021 ), paving the way for the development of more efficient mass-trapping strategies. METHODS AND MATERIALS Sample collection. Field sampling was carried out in 14 community gardens across the Lyon metropolitan area (France) between July and September 2021. As previously described (Duval et al. 2024 ), to limit the impact of certain environmental factors such as precipitation and air temperature on water parameters and mosquito dynamics, all sampling was conducted in the morning during the same time window, ensuring that no rainfall had occurred in the preceding 48 hours. In each garden, two 50 mL water samples were collected from distinct breeding sites located within a 200 m radius: one from a site naturally colonized by Ae. albopictus larvae, and the other from a non-colonized site. These are hereafter referred to as C and NC, respectively (Table 1 ). Before sampling, each container was stirred to homogenize organic detritus. Water was then collected using a sterile plastic pipette and transferred into a 50 mL sterile conical tube (Greiner Bio-One). Table 1 List of water samples collected from 14 community gardens within the Lyon metropolitan area. Garden name (ID) GPS Coordinates Sampling date Colonized breeding site type (C) Non-colonized breeding site type (NC) Collected plant number Jardins du Mas de la Forêt (FOR) 45.727440, 4.912791 19/07/21 Rainwater collector 200L Watering can 8L 9 Jardins EDF (EDF) 45.716809, 4.843919 20/07/21 Rainwater collector 200L Rainwater collector 200L 8 Jardins de Sytral (SYT) 45.715090, 4.867798 21/07/21 Rainwater collector 150L Rainwater collector 50L 4 Jardins de Alstom (ALS) 45.781367, 4.900155 22/07/21 Rainwater collector 200L Rainwater collector 200L 12 Jardins de la Mouche (MOU) 45.694260, 4.811824 26/07/21 Rainwater collector 200L Rainwater collector 200L 6 Jardins du Billot (BIL) 45.723953, 4.890951 27/07/21 Rainwater collector 200L Rainwater collector 200L 10 Jardins de la Garaine (GAR) 45.689472, 4.883222 31/08/21 Rainwater collector 200L Rainwater collector 200L 11 Jardins du Mas Rebufer (REB) 45.727344, 4.914945 01/09/21 Rainwater collector 200L Rainwater collector 200L 9 Jardins des Quatre Saisons (QUA) 45.818453, 4.883150 06/09/21 Rainwater collector 200L Bucket 5L 13 Jardins du Perollier (PER) 45.796643, 4.773981 07/09/21 Rainwater collector 200L Rainwater collector 200L 11 Jardins Reculés (REC) 45.795975, 4.927420 13/09/21 Rainwater collector 200L Bucket 10L 11 Jardins SNCF Cordier (COR) 45.603220, 4.775615 21/09/21 Rainwater collector 200L Rainwater collector 200L 9 Jardins de la Tase (TAS) 45.760277, 4.930609 22/09/21 Bucket 5L Bucket 5L 6 Jardins de Francheville (FRA) 45.743647, 4.768156 30/09/21 Watering can 30L Rainwater collector 200L 11 In parallel, ornamental and wild flowering plants located within a 200 m perimeter around these breeding sites were also collected. Identification of the plants ( Table S1 ) was based on morphological characteristics and confirmed with genetic barcodes (see the “Bioinformatics analysis” section below). All samples were properly stored in an icebox and brought to the laboratory for immediate processing. As for the breeding sites, flowers were classified as visited (V) or non-visited (NV) based on visual observations ( i.e. , the presence or absence of Ae. albopictus mosquitoes on the flowers). Yeast isolation and morphotype-based characterization. Yeast isolation was carried out using selective Dichloran-Rose Bengal Chloramphenicol (DRBC) agar medium (Biokar Diagnostics). A 100 µL aliquot of each fresh homogenized water sample was plated onto a DRBC plate in triplicate. For each collected plant, a pool of two to four flowers was homogenized in 400 µL of sterile 1X PBS (Gibco) using sterile 1.5 ml microtube pestles. After brief vortex agitation, the homogenate was plated onto four DRBC plates (100 µL/plate). All plates were incubated at 22°C and monitored daily for two weeks, with a final observation three weeks after plating. Characterization of microbial strains was initially based on the macroscopic identification of colony morphotypes (similar color, shape, and size). Individual colonies representing each morphotype from each sample were selected and streaked onto CYM agar plates (maltose 10 g·L⁻¹, glucose 20 g·L⁻¹, yeast extract 2 g·L⁻¹, tryptone 2 g·L⁻¹, MgSO₄ 0.5 g·L⁻¹, KH₂PO₄ 4.6 g·L⁻¹, agar 20 g·L⁻¹), a non-selective medium suitable for the growth of most yeast strains. To ensure the purity of the colony-forming strains prior to molecular identification and storage in 15% glycerol at -80°C, the colonies were streaked once more onto fresh CYM agar plates. DNA extraction from isolated yeast strains and environmental samples . Genomic DNA from each yeast morphotype was extracted following the protocol of Liu et al. ( 2000 ), while environmental DNA (eDNA) from water and flower samples was purified using a method adapted from Duval et al. ( 2024 ). Briefly, the pellets obtained after centrifuging 8 mL of each water sample (10 min at 16,000 g) and the pools of two to four flowers from each collected plant were used for eDNA extractions. Flowers were crushed with 3-mm borosilicate beads (Sigma) for 30 s at a speed of 6 m.s − 1 using a FastPrep-24™ 5G (MP Biomedicals). Pellets and flower grinds were resuspended in 250 µL of CTAB buffer. The homogenates were incubated for 1 h at 60°C, followed by RNase treatment with 0.4 mg of enzyme at 37°C for 5 min. Proteins were removed through successive extractions with phenol:chloroform:isoamyl alcohol (25:24:1) and chloroform:isoamyl alcohol (24:1) mixtures. DNA was precipitated with isopropyl alcohol, washed with 75% ethanol, and dissolved in 24 µL of sterile water. The purity and concentration of all DNA extracts were assessed using the Nanophotometer NP80 (Implen) and the Qubit dsDNA High Sensitivity kit in combination with the Qubit 4 fluorometer (Invitrogen), respectively. PCR amplifications and sequencing . The internal transcribed spacer (ITS) or, alternatively, the D1/D2 region of the large subunit (LSU) ribosomal DNA (rDNA) was amplified from extracted genomic DNA from yeast isolates using the ITS1F (5′- CTT GGT CAT TTA GAG GAA GTA A -3′) / ITS4R (5′- TCC TCC GCT TAT TGA TAT GC -3′; White et al. 1990 ; Gardes and Bruns 1993 ) or NL1F (5′- GCA TAT CAA TAA GCG GAG GAA AAG − 3’) / NL4R (5′- GGT CCG TGT TTC AAG ACG G -3′; Kurtzman and Robnett 1998 ) primer pairs, respectively. A 25 µL PCR reaction mix containing 2.5 µL of 10X polymerase buffer (Invitrogen), 0.75 µL of MgCl 2 (50 mM, Invitrogen), 2.5 µL of dNTPs (2 mM each, ThermoFisher Scientific), 1 µL of each primer (20 µM, Invitrogen), 0.3 µL of BSA (20 mg.mL − 1 , New England BioLabs), 0.1 µL of Taq DNA polymerase (Invitrogen), and 60 ng of DNA was prepared. Cycling conditions, performed on a T100 Thermal Cycler (Bio-Rad), consisted of an initial denaturation at 94°C for 3 min, followed by 35 cycles of 45 sec at 94°C, 45 sec at 55°C, and 1 min at 72°C, with a final extension step at 72°C for 10 min. Control reactions without nucleic acid were systematically run in parallel. PCR products were purified and sequenced by Microsynth France SAS (Vaulx-en-Velin, France) using the Sanger method. Manually curated sequences were compared to reference sequences available in the NCBI GenBank using BLASTn. Cultivable yeast species preferentially associated with C and NC water samples or V and NV flowers were used to assess their impact on mosquito sugar-feeding and oviposition behavior. High-throughput sequencing was also used to detect environmental yeasts from water and flower DNA samples by amplifying the fungal rDNA ITS-2 region using the modified gITS7 (5’- GTG AAT CAT CGA RTC TTT G -3’) and ITS4 (5’- TCC TCC GCT TAT TGA TAT GC -3’) primers (Luis et al. 2019 ). The primers were tagged with the Illumina adapters 5’- TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG − 3’ and 5’- GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACA G -3’, enabling a two-step PCR construction of amplicon libraries. All PCR amplifications were carried out in duplicates on a T100 thermal cycler (Bio-Rad) in a 25 µL reaction volume. PCR reactions were performed using the 5X Hot FIREpol Blend Master Mix Ready to load with 12.5 mM MgCl 2 (Solis BioDyne), 1 µM of each primer and 20 ng DNA. Cycling conditions consisted of an initial denaturation at 94°C for 10 min, followed by 40 cycles of 45 sec at 94°C, 45 sec at 55°C, and 30 sec at 72°C, with a final extension step at 72°C for 5 min. Amplicons were checked by electrophoresis on 1.5% agarose after 20 min of migration at 100 V, followed by UV visualization. The PCR products were then sent to IGFL sequencing platform (Lyon, France) for purification and second-step PCR, followed by 2x300 bp Miseq sequencing (Illumina). High-throughput sequence analysis and taxonomy assignment . A total of 18,024,648 reads were obtained for the fungal ITS-2 Miseq raw dataset and paired-end reads were demultiplexed based on their corresponding sample indices by the IGFL sequencing platform. Quality control and sequence analysis were performed using the FROGS pipeline (Escudié et al. 2018 ). Briefly, R1 and R2 reads were merged using VSEARCH (Rognes et al. 2016 ) with default parameters. Denoising was carried out by discarding sequences outside of the expected length ( i.e. , expected size between 200 and 500 bp) and those containing ambiguous bases (N). Clustering was performed using SWARM (Mahé et al. 2014 ) based on an aggregation distance of 3 in order to generate the operational taxonomic units (OTUs). Chimeric OTUs were removed using VSEARCH and, as recommended by Bokulich et al. ( 2013 ), low abundance sequences accounting for less than 0.005% of the dataset were filtered out. Taxonomic assignment of OTUs was performed using the RDP Classifier (Wang et al. 2007 ) against the curated eukaryotic ITS UNITE database version 8.0 (Abarenkov et al. 2023). Contaminant OTUs detected in negative controls (blank extraction and PCR) were systematically removed. Non-fungal OTUs, such as plant OTUs that confirmed the identification of collected flowering plants ( Table S1 ), were also excluded from the final dataset. To allow sample comparison, normalization was performed by randomly resampling down to 4473 sequences. An abundance matrix was generated for yeast species isolated from the different sample types ( i.e. , C and NC waters, V and NV flowers). Mosquito colony rearing. The F13 generation of the laboratory-reared Ae. albopictus population (AeAlbSP) was used in all behavioral experiments. After hatching, mosquito larvae were reared at 28°C in plastic trays filled with dechlorinated water under a 16:8h Light:Dark (L:D) photoperiod. They were fed daily a crushed mixture of 75% tropical-fish flakes (TetraMin, Tetra) and 25% yeast tablets (Biover) until reaching the pupal stage. Adults were raised in large BugDorm cages (32.5 x 32.5 x 32.5 cm) within climatic chambers (Panasonic MLR-352) set at 28°C, 80% relative humidity, and a 16:8h L:D photoperiod. They were fed ad libitum a 10% sucrose solution. Once a week, adult females were fed defibrinated sheep blood (ThermoFisher Scientific) using a membrane feeding system (Hemotek Ltd) with pig intestine as membrane. Eggs were collected on blotting paper and stored for up to 3 months under dry conditions at 28°C. Yeast culture conditions. To formally identify and assess the role of attractive nectar-dwelling yeasts and their emitted VOCs on Ae. albopictus sugar-feeding preference, we used a synthetic medium mimicking the sugar composition of Lamiaceae nectar (18% sucrose, 6% glucose, 6% fructose, 0.5% peptone, 0.2% MgSO 4 and 0.3% KH 2 PO 4 ; Venjakov et al. 2022), which corresponds to that of the visited flowers. For each yeast species, two cell concentrations ( i.e. , 5.10 3 and 5.10 5 cells.ml − 1 ) were tested. The lower concentration reflected the average natural densities observed in flowers using plate counting, while the higher concentration represented 100 times these densities. The higher concentration accounted for potential underestimation of colony abundance on plates, which may result from interspecies competition affecting natural colony counts (Kolesidis et al. 2019 ). Moreover, it is well known that VOC concentrations, impacted by cell densities, modulate mosquito response (Kim et al. 2023 ). For each yeast species tested, a 3 mL overnight culture in Lamiaceae medium (28°C at 180 rpm) was used to inoculate 1L of fresh medium at a defined cell concentration ( i.e. , 5.10 3 or 5.10 5 cells.mL − 1 ). For the oviposition bioassays, each yeast species was instead cultivated in CYM medium. Briefly, an overnight culture of 3 mL in CYM medium (28°C at 180 rpm) was used to inoculate 1L of fresh medium at a specific cell concentration ( i.e. , 3.10 2 and 3.10 5 cells.mL − 1 ). As previously mentioned, the lower concentration corresponded to the average natural densities observed in breeding-site waters based on plate counting, while the higher concentration represented 100 times these densities. Sugar-feeding behavior experiments using locomotor activity monitoring systems. The impact of yeast species preferentially associated with the nectar of flowers visited by Ae. albopictus mosquitoes on their sugar-feeding behavior was evaluated using two Locomotor Activity Monitoring (LAM25) systems (Trikinetics Inc). As described by Giannoni-Guzmán et al. ( 2014 ), each LAM unit contains 32 independent activity channels. These channels detect mosquito movements using three infrared beams and multiple sensors to ensure accurate recordings (Fig. 1 A). After 7 hours of starvation and cold anesthesia, each 5-day-old mosquito ( i.e. , 16 males and 16 females) was placed at one end of one of the 25 mm Ø glass tubes, near the plastic connector (Fig. 1 B). Mosquitoes had the choice between cotton impregnated with 1 mL of sterile Lamiaceae medium and cotton impregnated with 1 mL of the same medium inoculated with a specific yeast concentration ( i.e. , 5.10 3 or 5.10 5 cells.mL − 1 ), both placed at opposite ends of each tube. The cotton pads were placed as close as possible to the activity channels of both units to ensure that moving mosquitoes would come into contact with them (Fig. 1 C). Mosquitoes were left to rest for 15 min before their activity was measured. As previously described (Girard et al. 2024 ), the system was placed on a rolling support in a shaded area of the insectarium, as mosquitoes tend to prefer such environments in nature. The total activity measured with LAM systems can be mostly attributed to flight, as walking accounts for less than 20% of mosquito activity (Ziegler et al. 2022 ). All experiments were conducted over 17 h (from 18h00 to 11h00 the following day) in a BSL2 insectary maintained at 26°C with an 18 h/6 h day/night cycle. Mosquito movements were recorded every two minutes. Choice preference was evaluated based on the difference in the number of passes between the sterile medium and the yeast-inoculated medium. For each microbial species and cell concentration tested, 16 independent replicates were performed for both female and male mosquitoes. To avoid positional effects, the control and the microbial suspension were alternated between the two glass-tube assemblies. Individuals that died before the end of the recording were excluded from the final dataset. Oviposition bioassays. The impact of different yeast species at two cell concentrations ( i.e. , 3.10 2 and 3.10 5 cells.mL − 1 ) on the oviposition behavior of 10-day-old gravid females was evaluated using two distinct and complementary laboratory bioassays, as previously described (Malassigné et al. 2025 ). The oviposition-site selection bioassays (hereafter referred to as oviposition preference) consisted of three-choice tests in small cages, where a single gravid female could choose among three Double Beaker Systems (DBS) as oviposition sites: a control containing sterile water and CYM medium, and two others each containing water and medium inoculated with one of the two tested yeast concentrations. These DBS provide an oviposition substrate with waterborne deterrent or stimulant substances (sterile water, inoculated or not with yeasts), combined with attractive or repellent olfactory cues (volatile organic compounds emitted by sterile CYM medium or yeast cultures) for a single gravid female. These oviposition preference bioassays assessed the short-range attractiveness or repellency of volatile compounds emitted by yeasts. They were systematically paired with oviposition stimulation bioassays conducted in conical tubes, where a single gravid female was exposed to either sterile water or water inoculated with one of the two tested yeast concentrations. This pairing allowed evaluation of the stimulant or deterrent effects of yeast-derived waterborne substances. It is important to note that oviposition preference bioassays, when considered alone, do not allow distinguishing between the effects of stimulant or deterrent waterborne substances and those of attractant or repellent volatile compounds derived from yeasts. This limitation arises because gravid females are simultaneously exposed to both types of cues: oviposition substrates containing waterborne substances (sterile water or sterile water inoculated with yeasts) and olfactory stimuli (volatile organic compounds emitted by either sterile CYM medium or yeast cultures). The presence of attractant or repellent volatiles derived from yeasts can only be confirmed by comparing the total number of eggs laid in both control and yeast-inoculated conditions across the two bioassays (preference vs stimulation). This approach enables the evaluation of the short-range attractiveness or repellency of volatile compounds emitted by yeasts during oviposition preference bioassays. Analysis of emitted volatile compounds. Volatile organic compounds emitted by yeast species that significantly impacted mosquito sugar-feeding and oviposition behavior were analyzed using an established protocol (Michalet et al. 2019 ). Volatile compounds emitted by yeasts that were attractive to sugar-feeding mosquitoes (males and females), or either attractive or repellent to gravid females, were analyzed as follows. Each yeast species was cultured in 75 mL of Lamiaceae medium for sugar-feeding experiments or in CYM medium for oviposition assays, and incubated at 28°C with constant shaking (130 rpm) for 16 h to reach the exponential phase. Then, 250 mL Erlenmeyer flasks containing 100 mL of either sterile Lamiaceae or CYM medium, or the same media inoculated with these precultures at the behaviorally relevant cell concentrations, were incubated under the same conditions for 18 h. Five independent replicates were systematically performed for each tested condition (i.e., sterile medium or yeast culture). Yeast VOCs, as well as compounds emitted by the Lamiaceae or CYM medium, were extracted by HeadSpace-Solid Phase Micro-Extraction (HS-SPME) using 65 µm PMS/DVB Stable Flex™ fibers (Supelco). On the day of analysis, each 250 mL Erlenmeyer flask containing 100 mL of yeast culture or sterile medium was sealed with two layers of parafilm and incubated under constant agitation for 15 min at room temperature. Cleaned fibers, previously subjected to a blank GC run, were then introduced into the headspace of each 250 mL Erlenmeyer flask and left open for 30 min with constant agitation. After incubation, volatile compounds adsorbed on the fiber were immediately analyzed by GC-MS using a Hewlett-Packard 6890N gas chromatograph coupled to an HP 5973 mass spectrometer (Agilent Technologies) equipped with an Agilent DB-5MS column (60 m long, 0.25 mm in diameter, 0.25 µm film thickness). Helium was used as the carrier gas at a constant flow rate of 2.3 mL.min − 1 (Agilent). The oven temperature program consisted of a 10°C.min − 1 ramp from 50°C to 280°C. The ionization source was an electron impact at 70 eV and mass spectra were recorded between 35 and 600 m/z at 1.29 scans.s − 1 . Emitted VOCs were manually integrated using the MassHunter software (Agilent) and aligned according to their retention time into a matrix. Medium related compounds were removed from the analysis. Key compounds were identified using NIST, Wiley, and aro.CRNS libraries, along with Kovats index calculation and manual interpretation of spectra. Statistical analysis. All statistical analyses were performed using R software version 4.2.0 and packages ade4 , MASS , emmeans , DHARMa , mixOmics , vegan , car , lem4 and glmmTMB (R core Team 2022 ). Fungal and yeast community dissimilarities among samples ( i.e ., ß-diversity) were represented using the Bray-Curtis index in a non-metric multidimensional scaling (NMDS). The differences in the composition of fungal and yeast communities related to the sample categories ( i.e. , flowering plants and breeding-site waters) and the presence of Ae. albopictus mosquitoes ( i.e. , flower visited by adults and water colonized by larvae) were tested using a nonparametric permutation-based multivariate analysis of variance (PERMANOVA). The impact of nectar-dwelling yeast species and cell concentration on the sugar-feeding behavior of Aedes albopictus mosquitoes was analyzed using a generalized linear mixed model (GLMM) with quasi-Poisson distribution. In this model, the number of movements was set as the response variable, with mosquito sex, yeast species, and cell concentration as explanatory variables, and individual mosquito as a random variable. The influence of waterborne yeast species and cell concentration on oviposition preference was analyzed using a zero inflated GLMM with a negative binomial distribution. The impact of waterborne yeast species and cell concentration on oviposition stimulation was analyzed using a GLMM with a negative binomial distribution. In both GLMM models, the total number of eggs laid by each female was set as the response variable, with yeast species and its concentration as explanatory variables, and individual mosquito as a random variable. For each model, the contribution of explanatory variables was evaluated using type II ANOVA or Wald χ 2 . Subsequent, Tukey-HSD post hoc tests were conducted to test pairwise differences between groups. Prior to this, the residuals of each model were verified for normality and variance homoscedasticity. To determine whether the composition of VOCs differed between attractive and repellent yeasts, a Heatmap was generated to illustrate the relative abundance of emitted compounds. RESULTS Composition of fungal and yeast communities associated with flowers and breeding-site waters according to their Aedes albopictus visitation or colonization status. A total of 130 flowering plants (ranging from 4 to 13 per garden), representing 53 species across 23 families, were collected from 14 community gardens (Table 1 , Table S1 ). Lamiaceae and Asteraceae were the most abundant families, accounting for 26% and 18% of the collected flowering plants, respectively (Fig. 2 A). Species richness within these two families was relatively low, with Erigeron annuus and Galinsoga parviflora each representing 26% of the Asteraceae, and Mentha spicata accounting for 44% of the collected Lamiaceae ( Table S1 ). Interestingly, mint species, including spearmint ( M. spicata ), were present in 93% and 79% of the sampled gardens, respectively. Field observations showed that Ae. albopictus individuals systematically visited mint flowers during the sampling period (Fig. 2 B). In contrast, no adult mosquitoes were observed on any of the other collected flowering plant species. Regarding breeding sites, whether colonized by Ae. albopictus larvae or not, the most common artificial containers sampled were plastic rainwater collectors (79%), followed by plastic buckets (14%), and plastic watering cans (4%) (Table 1 ). Yeast communities associated with these four sample categories ( i.e. , NV flowers, V flowers, NC waters, and C waters) were analyzed using both culture-based and high-throughput amplicon sequencing (fungal ITS-2 region) approaches. After removing plant sequences and normalizing to 4473 sequences per sample, the ITS-2 fungal dataset comprised 313,110 sequences representing 277 OTUs. The percentage of yeast sequences in this dataset did not significantly differ among sample categories (flowers vs waters; df = 1, F = 0.65, p = 0.423) or presence of Ae. albopictus mosquitoes (NV vs V and NC vs C; df = 1, F = 0.63, p = 0.429), with averages ranging from 26.36 ± 16.99 for C waters to 37.39 ± 29.90 for NV flowers (Fig. 3 A). Non-metric multidimensional scaling (NMDS) ordination based on Bray-Curtis distances showed that global fungal communities differed more between sample categories ( i.e ., flowers vs waters) than within the same sample category differing in mosquito presence (Fig. 3 B). A similar pattern was observed for yeast communities, with less separation between sample categories (Fig. 3 C). The difference in fungal and yeast composition, assessed through a permutational analysis of variance (PERMANONA), revealed the presence of significant variations between sample categories in terms of global fungal communities (df = 1, R 2 = 0.080, p = 0.001) and yeast communities (df = 1, R 2 = 0.043, p = 0.002). No noticeable difference was observed between samples with differential mosquito presence (df = 1, R 2 = 0.015, p = 0.261 for global fungal communities and df = 1, R 2 = 0.022, p = 0.062 for yeast communities). However, 89.2% of the variation in the global fungal communities and 91.9% of the variation in yeast communities were not attributed to any of these factors ( Table 2 ) . Table 2 Comparison of fungal and yeast community composition across sample categories (flowers and breeding-site waters) and presence/absence of Ae. albopictus (visited and non-visited flowers or colonized and non-colonized waters). Total fungal communities (Miseq) Yeast communities (Miseq) Cultivable yeast communities df a R² F b p-value df a R² F b p-value df a R² F b p-value Sample category 1 0.080 5.968 0.001 1 0.043 3.098 0.002 1 0.027 3.334 0.001 Aedes presence 1 0.015 1.116 0.261 1 0.022 1.587 0.062 1 0.007 0.843 0.743 Sample category x Aedes presence 1 0.012 0.936 0.505 1 0.015 1.102 0.315 1 0.006 0.675 0.953 Residuals 66 0.892 66 0.919 66 0.955 The differences between groups were tested using PERMANOVA analysis and bold text represents the significative results (p-value < 0.05). a degree of freedom b statistics value Among the 277 OTUs, 79.1% (219 OTUs) were shared between flowers and breeding-site waters, while 11 were specific to flowers and 47 to waters (Fig. 4 A). The OTUs specifically associated with flowers were primarily phytopathogenic fungi ( e.g. , Stemphylium sp., Ramularia cynarae , Ampelomyces sp., Golovinomyces _sp., and Paragibellulopsis chrysanthemi ), although two yeast species ( Rhodosporidiobolus sp., Rhodotorula babjevae ) were also recorded. Regarding the 230 OTUs detected in flowers, only 10 were specifically associated with the visit of Ae. albopictus mosquitoes (Fig. 4 A). Among them, two yeast species ( Hyphopichia pseudoburtonii and Wickerhamomyces anomalus ) and several filamentous fungi, including the mint pathogen Puccinia menthae , were identified. Among the 266 OTUs detected in the breeding-site waters, only 20 were specifically associated with Ae. albopictus larval colonization (Fig. 4 A). Nearly all were filamentous fungi, including chytrids like Betamyces sp., except for the yeast Dioszegia sp. Yeast species accounted for 31% (86 OTUs) of this ITS-2 fungal dataset and were shared between the two sample categories ( i.e. , waters and flowers) at 91.9% (79 OTUs) (Fig. 4 B). The five most abundant yeast OTUs shared by all sample categories, regardless of the presence of Ae. albopictus mosquitoes, were Aureobasidium pullulans (19.5% of all yeast sequences), Vishniacozyma victoriae (10.8%), Rhodotorula glutinis (8.2%), Filobasidium magnum (6%) and Bullera alba (5.5%). The culture-based approach yielded 383 isolates belonging to 78 different species. Only 14 species were simultaneously detected in both sample categories, while 23 and 41 species were specifically found in waters and flowers, respectively (Fig. 4 C). The species shared by all sample categories, regardless the presence of Ae. albopictus mosquitoes, were A. pullulans , R. glutinis, Rhodotorula mucilaginosa , Hanseniaspora uvarum , and Metschnikowia pulcherrima. Among the 23 waterborne species, 11 were specifically associated with Ae. albopictus larval colonization ( i.e., Candida sp., Clavispora lusitaniae, Cystobasidium sp., Goffeauzyma gastrica, Kurtzmaniella quercitrusa, Lectera nordwiniana, Moesziomyces aphidis , Pichia kudriavzevii, Rhodotorula dairenensis, Rhodotorula kratochvilovae and Tilletiopsis washingtonensis ). Among the 41 species detected in flowers, only 6 were specifically associated with the visit of Ae. albopictus mosquitoes ( i.e. , Candida oleophila, Diutina catenulata, Meyerozyma caribbica, Pichia sp., Starmerella caucasica and Trichosporon aquatile ). However, all these species were among the least abundant, representing less than 0.3% of the total observed colonies. The five most abundant yeast species were F. magnum (28.8%), Metschnikowia reukaufii (21%), R. glutinis (12.8%) and R. mucilaginosa (12%). The analysis of prevalence and abundance conducted on the cultivable yeast community highlighted a contrasting species composition between water and flower samples. Indeed, M. reukaufii , R. glutinis , and F. magnum prevailed in NV and V flowers, while R. mucilaginosa , Papiliotrema laurentii , Cystobasidium slooffiae , H. uvarum , and Torulaspora delbrueckii dominated NC and C waters (Fig. 5 ). Except for Pichia kluyveri , which was only detected in NC waters, all dominant cultivable species were associated with both the presence and absence of Ae. albopictus larvae. However, on average, their cell concentrations significantly differed between NC and C water samples. For instance, C. slooffiae and R. mucilaginosa were found to be 18 and 4 times more abundant in C waters, respectively (Fig. 5 , Table S2 ). Conversely, the cellular concentrations of H. uvarum, P. laurentii and T. delbrueckii were 2 and 1.5 times higher in NC waters respectively (Fig. 5 , Table S2 ). Similarly, NV and V flowers exhibited the same dominant yeast species but with contrasting cell concentrations. Indeed, while M. reukaufii , R. glutinis and A. pullulans were found to be 4 and 3 times more abundant in V flowers ( i.e ., mint flowers), F. magnum were 15 times higher in NV flowers ( Fig. 5 , Table S2 ). When examining the distribution of OTU sequences or cultivable species colonies across fungal phyla, both global fungal communities and cultivable yeast communities were dominated by Ascomycota (Fig. 6 ). Specifically, global fungal communities consisted of 62.62%, 64.69%, 64%, and 73.64% Ascomycota in NV, V, NC and C samples, respectively, and cultivable yeast communities comprised 52.14%, 66.23%, 51.40%, and 40.37% Ascomycota in these samples. Basidiomycota followed, making up 37.38%, 35.30%, 33.92% and 22,31% of global fungal communities, and 47.85%, 33.77%, 48.60%, and 59.63% of cultivable yeast communities in NV, V, NC and C, respectively. However, when focusing on the yeast fraction of the ITS-2 fungal dataset, Basidiomycota were notably predominant, comprising 70.61%, 67.67%, 87.42% and, 66.54% in NV, V, NC and C, respectively, compared to Ascomycota, which accounted for only 29.39%, 32.32%, 12.58%, and 33.45% in these samples (Fig. 6 ). Based on these observations, there appears to be a bias in the Miseq primers toward amplifying Basidiomycota yeasts, as evidenced by the absence of detection of M. reukaufii , which is known to be abundant in flower nectars, as shown for the culture-based approach. The subsequent selection of yeast species, preferentially associated with V and NV flowers or C and NC waters, was therefore based on cultivable yeast communities to assess their impact on sugar-feeding and mosquito oviposition behavior, respectively. This choice was supported by the consistency between observations made in both culture-based and sequencing approaches. Indeed, both approaches showed that C. slooffiae and R. mucilaginosa were more abundant in C waters ( i.e. , 18 and 4 times for the culture-based approach, and 3 times for the sequencing approach), while P. laurentii was more abundant in NC waters ( i.e. , 2 times for the culture-based and 8 times more for the sequencing approaches). Similarly, both approaches revealed that R. glutinis and A. pullulans were more abundant in V than in NV flowers ( i.e. , 4 and 3 times more for the culture-based approach, and 2 and 1.5 times for the sequencing approach). Thus, M. reukaufii, R. glutinis , and A. pullulans were selected as yeasts preferentially associated with V flowers ( i.e. , mint flowers), while F. magnum was selected as a yeast species preferentially associated with NV flowers (Fig. 5 A-B). Regarding breeding sites, C. slooffiae and R. mucilaginosa were selected as yeasts preferentially associated with C waters, and H. uvarum, P. laurentii , P. kluyveri , and T. delbrueckii were selected as yeasts preferentially associated with NC waters (Fig. 5 C-D). Nectar-dwelling yeasts and their associated emitted volatile compounds impact Ae. albopictus sugar-feeding preferences. The attractiveness of M. reukaufii, R. glutinis, A. pullulans and F. magnum at two cell concentrations (5.10 3 and 5.10 5 cells.ml − 1 ) toward male and female mosquitoes was assessed using a dual locomotor activity monitoring (LAM25) system. Each individual mosquito ( i.e ., 16 males or 16 females) was placed at the junction of two glass tubes offering a choice between a cotton soaked with a sterile Lamiaceae medium and cotton impregnated with the same medium inoculated with yeast at the specified concentration. These behavioral bioassays showed that the presence of M. reukaufii significantly increased male visits at both low (df = Inf; z.ratio = -3.030; p = 0.002) and high cell concentrations (df = Inf; z.ratio = -1.833; p = 0.043). In contrast, the presence of A. pullulans significantly increased female visits but only at high cell concentration (df = Inf; z.ratio = -2.278; p = 0.023) (Fig. 7 ; Table S3 ). No attractiveness was observed for R. glutinis , and as expected, F. magnum did not attract male or female Ae. albopictus (Fig. 7 ; Table S3 ). The analysis of VOCs emitted by M. reukaufii and A. pullulans that significantly attracted male and female Ae. albopictus at high cell concentrations (i.e., 5.10 5 cells.mL − 1 ), respectively, revealed distinct VOC profiles (Fig. 8 A). Of the nine detected compounds, eight were identified ( Table S4 ). The nectar-specialist yeast M. reukaufii emitted a greater diversity of VOCs compared to the generalist species A. pullulans frequently isolated from nectar (Fig. 8 A). Indeed, M. reukaufii specifically emitted four VOCs, namely 3-methyl-1-butanol acetate, 2-methyl-1-butanol acetate, ethyl acetate, and ethyl hexanoate ( Fig. 8 A ) . Additionally, M. reukaufii , which shared four VOCs with A. pullulans , emitted these compounds at significantly higher concentrations (Wilcoxon rank sum exact test; W = 0; p = 0.008). For instance, M. reukaufii produced, on average, six times more 3-methyl-1-butanol and 16 times more 2-methyl-1-butanol than A. pullulans (Fig. 8 B ). Waterborne yeasts with specific volatile profiles are impacting Ae. albopictus oviposition behavior. In a previous study, we have demonstrated that R. mucilaginosa, H. uvarum and T. delbrueckii , which differentially impact larval development, induced contrasting oviposition responses in Ae. albopictus females (Malassigné et al. 2025 ). In the present study, using the same experimental procedure, we compared C. slooffiae to R. mucilaginosa (two yeasts preferentially associated with C waters) as well as P. laurentii and P. kluyveri to H. uvarum and T. delbrueckii (four yeasts preferentially associated with NC waters). The impact of waterborne yeasts on gravid female oviposition behavior was then assessed through the same two distinct and complementary bioassays ( i.e. , oviposition preference and oviposition stimulation). These two bioassays differentiated attractant/repellent from stimulant/deterrent yeast effects. In the oviposition preference bioassay, conducted in cages, individual females chose among three oviposition sites ( i.e. , a yeast-free site, a site with 3.10 2 yeast cells.mL − 1 , and a site with 3.10 5 yeast cells.mL − 1 ). These sites provided both an oviposition substrate with potentially stimulant or deterrent waterborne substances and an olfactory stimulus acting as short-range attractant or repellent. Conversely, in oviposition stimulation bioassay, conducted in 50 mL tubes, each female was exposed only to stimulant or deterrent waterborne substances. Interestingly, all females laid eggs when C. slooffiae and R. mucilaginosa were present, while the percentage of females laying no eggs increased from 15.79–42.11% in presence of H. uvarum, T. delbrueckii, P. laurentii and P. kluyveri (Fig. 9 A). With 31.58% and 42.11%, P. laurentii and P. kluyveri showed the highest percentages of females that laid no eggs. Moreover, when R. mucilaginosa, H. uvarum , and C. slooffiae were present, individual females laid more eggs per cage compared to all other conditions, with averages of 42.11 ± 15.51, 39.53 ± 35.75, 34.79 ± 21.66 eggs, respectively ( Table S2 ). Conversely, P. laurentii , P. kluyveri , and T. delbrueckii caused a significant reduction in the total number of eggs laid per cage, with averages of 14.42 ± 21.25, 13.53 ± 21.61, 10.43 ± 14.08 eggs respectively ( Table S2 ). Both oviposition bioassays showed that yeast species and their cell concentrations significantly influenced not only the selection of oviposition sites but also egg stimulation ( Table 3 ). Table 3. Impact of yeast species on Aedes albopictus female oviposition behavior. Oviposition preference (n = 24) Oviposition Stimulation (n = 25) Variable Factor df a χ 2 b p-value df a χ2 b p-value Number of eggs laid Yeast species 5 36.325 8.17e-07 5 14860.716 < 2.20e-16 Yeast concentration 2 17.073 0.001 2 12.246 0.002 Yeast conc. x Yeast sp. 10 12.005 0.285 10 13.833 0.181 Data from 24 or 25 independent replicates for each modality were analyzed using a Generalized Linear Mixed Model (GLMM) with a quasi-poisson distribution. Statistically significant differences between groups were identified with Tukey-HSD post hoc tests (p < 0.05). a degree of freedom b statistics value When exposed to highest concentrations (3.10 5 yeast cells.mL -1 ) of R. mucilaginosa and C. slooffiae , female mosquitoes laid significantly more eggs, with averages of 19.11 ± 18.65 and 17.16 ± 15.48 eggs per female, respectively (Fig. 9 B; Table S3 ). The absence of egg stimulation at these cell concentrations suggests that these two yeasts, preferentially associated with C waters, attract gravid females at short-range distances (Fig. 9 C). A significant oviposition stimulation was observed for H. uvarum at high cell concentrations (Fig. 9 C; Table S3 ). However, at this concentration (3.10 5 yeast cells.mL -1 ), H. uvarum resulted in a reduced number of eggs laid (on average, 16 ± 18.23) and an increased proportion of females that did not lay eggs (15.79%) compared to R. mucilaginosa and C. slooffiae during oviposition preference bioassays. These findings suggest a short-range repellency effect of this yeast species, which was preferentially associated with NC waters. Regarding the other species preferentially associated with NC waters, no oviposition stimulation was observed for P. laurentii and P. kluyveri . The significant reduction in eggs laid at high concentrations (on average, 7.16 ± 15.23 and 4.74 ± 8.49, respectively) and the highest proportion of gravid females (31.58% and 42.11%) observed for P. laurentii and P. kluyveri during oviposition preference bioassays further emphasized the short-range repellency effect of both species. In contrast, at high cell concentrations, T. delbrueckii acted as deterrent (Fig. 9 C). The significant reduction in eggs laid (on average, 6.95 ± 12.33) and the high proportion of gravid females (28.57%) that did not lay eggs in the presence of T. delbrueckii during oviposition preference bioassays underscored a combination of short-range repellency and deterrence of this yeast species (Fig. 9 B). The presumed attractive ( C. slooffiae, R. mucilaginosa ) and repellent ( H. uvarum, P. laurentii , P. kluyveri and T. delbrueckii ) yeasts at high cell concentrations ( i.e ., 3.10 5 cells.mL − 1 ) showed two contrasting VOC profiles. Of the 22 detected compounds, 19 were identified ( Table S2 ), and repellent yeasts emitted a greater richness of VOCs compared to attractive yeasts. Indeed, only three compounds ( i.e. , 3-methyl-1-butanol, 2-methyl-1-butanol and 2,4,4,6,6,8,8-Heptamethyl-2-nonene) were shared between repellent and attractive yeasts. Conversely, several compounds ( i.e. , ethanol, 3-methyl-1-butanol acetate, 2-methyl-1-butanol acetate, ethyl acetate, ethyl propionate or ethyl octanoate) were specifically produced by repellent yeasts (Fig. 10 A). Finally, two compounds were produced by both yeast categories (the alcohols 3-methyl-1-butanol and 2-methyl-1-butanol), but at significantly higher concentrations for repellent ones (Fig. 10 B). With the exception of ethanol production, P. laurentii displayed a VOC profile similar to that of attractive yeasts (Fig. 10 A). DISCUSSION In this study, we characterized for the first time the yeast communities preferentially associated with plants visited or not by Ae. albopictus adults, as well as with breeding-site waters colonized or not by this species, using both culture-based and sequencing approaches. We also evaluated the impact of selected cultivable yeast species on nectar seeking and oviposition behaviors and characterized their emitted VOCs. While molecular or biochemical approaches, such as rbcL gene amplification and sequencing from DNA extracted from mosquito guts (Upshur et al. 2023 ; Cassone et al. 2024 ) or the analysis of ingested plant secondary metabolites (Cooper et al. 2025 ) offer valuable insights into flower visitation, we based our study on visual inspections during the sampling period. This method, based on the presence or absence of adult mosquitoes on flowers and larvae in breeding-site waters, allowed us to link yeast community composition to real-time mosquito activity under natural conditions. Only mint flowers, found in 93% of the sampled gardens, were observed to be visited by Ae. albopictus mosquitoes during the sampling period. This observation is consistent with the preference of Aedes mosquitoes for colorful flowers, including purple ones such as Buddleja davidii and Vitex agnus-castus (Müller et al. 2011 ; Dieng et al. 2018 ). Moreover, Davis et al. ( 2016 ) showed that Ae. albopictus lays significantly more eggs in containers adjacent to flowering butterfly bushes than in those without one. The proportion of yeast sequences within the total fungal communities did not differ significantly between flowers and breeding-site waters, despite previous studies indicating that floral nectar often harbors high yeast cell densities, ranging from 10 3 to 10 5 cells/mm 3 (Herrera et al. 2009 ; Pozo et al. 2011 ). This unexpected result may be explained by two main factors. Although the fungal primers used for the Miseq sequencing approach are currently among the most effective for amplifying fungal communities, including a broad range of yeast species, and are designed to minimize the amplification of plant sequences while avoiding mosquito DNA (Ihrmark et al. 2012 ; Luis et al. 2019 ), they still amplified a large number of sequences from herbaceous plants. Moreover, they failed to amplify certain nectar-dwelling yeasts, such as M. reukaufii , a nectar specialist known to be the most prevalent and abundant yeast in floral nectar (Pozo et al. 2011 ; Glushakova et al. 2014 ). These limitations may have led to an underestimation of yeast diversity and abundance in nectar samples. Interestingly, using culture-based approaches, we identified M. reukaufii as the most abundant and prevalent yeast species in the nectar of the collected plants. Our study showed that fungal communities in Ae. albopictus aquatic habitats are predominantly composed of Ascomycota species, consistent with their known prevalence in freshwater ecosystems (El-Elimat et al. 2021 ), including mosquito breeding sites (Zouache et al. 2022 ; Tawidian et al. 2022 ), and in line with previous findings (Tawidian et al. 2021 ; Duval et al. 2024 ). A similar pattern was observed for the cultivable fraction of the yeast communities, except in colonized breeding-site waters, where two basidiomycetous yeast species ( R. mucilaginosa and C. slooffiae ) were the most prevalent and abundant. Fungal and yeast communities, as well as the culturable subset of the latter, exhibited significant variation between sample categories ( i.e. , flowers vs breeding-site waters), but not within the same category based on mosquito presence. Differences in yeast communities between larval habitats and flowers likely result from contrasting physicochemical conditions. Variations in carbon source type and concentration, pH, osmotic conditions, and nitrogen availability strongly shape the yeast species able to thrive in each environment (Venjakov et al. 2022; Duval et al. 2024 ). The absence of significant differences in bacterial and fungal communities between breeding sites colonized and non-colonized by Ae. albopictus had already been observed in a larger number of containers sampled across various community gardens in the Lyon metropolitan area (Duval et al. 2024 ). The variations in fungal and yeast community composition between flowers and breeding-site waters were primarily driven by differences in species abundances, as evidenced by the high percentages of shared OTUs (79.1% and 91.9% respectively). In line with this observation, the culture-based approach showed that M. reukaufii , R. glutinis , F. magnum and to a lesser extend A. pullulans prevailed in flowers, while R. mucilaginosa , P. laurentii , C. slooffiae , H. uvarum , and T. delbrueckii dominated breeding-site waters. Interestingly, the nectar specialist M. reukaufii and the two generalist species A. pullulans and F. magnum were often found prevalent and abundant in floral nectars (Pozo et al. 2011 ; Sobhy et al. 2018 ; Agarbati et al. 2024 ). Among isolated yeasts, R. mucilaginosa and C. slooffiae are classified as aquatic yeasts due to their remarkable ability to survive in fresh or marine water (Gonçalves et al. 2017 ; Libkind et al. 2017 ). Furthermore, R. mucilaginosa, A. pullulans , H. uvarum and T. delbrueckii has already been found to be associated with breeding-site waters and larvae from Ae. albopictus (Hegde et al. 2024 ; Malassigné et al. 2025 ). The high percentages of shared yeast OTUs between flowers and breeding-site waters, along with the presence of two generalist species frequently isolated from nectar ( A. pullulans and F. magnum ) among the five most abundant taxa, suggest that adult mosquitoes, including gravid females, contribute to shaping yeast communities in breeding-site waters by introducing species during oviposition, defecation or death, as previously demonstrated for adult-associated bacteria (Mosquera et al. 2023 ). This hypothesis is further supported by the frequent detection of A. pullulans in female mosquitoes, as this species was detected in 90.5% of specimens collected in France, Madagascar, and Vietnam (Luis et al. 2019 ). However, the contribution of other dissemination sources such as pollen, around which nectar yeasts commonly aggregate, cannot be excluded at this stage (Pozo and Jacquemyn 2019 ). Since M. reukaufii , R. glutinis , F. magnum and A. pullulans were preferentially associated with the visited mint flowers ( i.e. , higher cell concentrations), we evaluated their impact on mosquito nectar-seeking preferences. To our knowledge, the study by Peach et al. ( 2021 ) is the only research linking VOCs produced by nectar-dwelling microorganisms to mosquito attractiveness. They demonstrated that the yeast Lachancea thermotolerans produces volatile compounds (hexanoic acid, dimethyl trisulfide, 2-phenyl ethanol, benzyl alcohol) that significantly attract female Culex pipiens mosquitoes. This yeast species, which appears to be absent from the nectar of flowers collected on the Eurasian continent (Pozo et al. 2011 ; Glushakova et al. 2014 ), was not detected in our samples. Our results showed that, regardless of yeast cell concentration, the nectar specialist M. reukaufii significantly attracted Ae. albopictus males, whereas the generalist species frequently isolated from nectar A. pullulans significantly attracted Ae. albopictus females, but only at high cell concentration. This attraction of females by A. pullulans may help explain its high prevalence in field-collected individuals (Luis et al. 2019 ). The nectar specialist M. reukaufii , which heavily relies on insects for dispersal and colonization of new habitats (Sobhy et al. 2018 ), is known to significantly increase nectar temperature (Herrera and Pozo 2010 ), potentially benefiting foraging insects by reducing viscosity and facilitating sugar intake (Nicolson et al. 2013 ), while maintaining a chemical composition that supports insect longevity, survival and reproduction (Sobhy et al. 2018 ; Yang et al. 2019 ). As these nectar specialists are specifically adapted to the physicochemical conditions of nectar, including high osmotic pressure, high sugar concentration and low nitrogen availability, they are unable to grow in other environments such as water (Sobhy and Berry 2024 ). Thus, M. reukaufii has been shown to produce the most attractive volatile blends among the microorganisms tested, attracting a wide range of insect pollinators, including Aphidius parasitoids, honeybees, and several bumblebee species (Schaeffer et al. 2017 ; Rering et al. 2018 ; Sobhy et al. 2018 ; Yang et al. 2019 ). In contrast, A. pullulans is a generalist species frequently isolated from nectar, capable of colonizing a wide range of habitats and thus less dependent on insects for dispersal and survival (Wehner et al. 2017 ; Sobhy et al. 2018 ). This species produces distinct volatile blends and tends to lower nectar quality by strongly reducing pH, decreasing sucrose concentration in favor of monosaccharides, and altering the amino acid profile (Sobhy et al. 2018 ). These changes can lead to reduced nectar consumption and shortened lifespan, resulting in lower attractiveness compared to M. reukaufii in some pollinator species, and even aversive responses in honeybees (Rering et al. 2018 ; Sobhy et al. 2018 ; Crowley-Gall et al. 2022 ). Our results revealed sex-specific responses in Ae. albopictus , likely linked to differences in nutritional requirements and reliance on sugar meals for survival between males and females (Müller et al. 2011 ; Bellini et al. 2014 ; Naziri et al. 2016 ). By attracting males, which visit flowers more frequently than females due to their higher dependence on sugar meals for survival, M. reukaufii could benefit from enhanced dispersal. In contrast, the generalist species A. pullulans , frequently isolated from flowers and known to inhabit diverse environments with less dependence on insect pollinators for dispersal and survival, may nonetheless facilitate colonization of a wide range of aquatic habitats by attracting females that exhibit skip oviposition behavior ( i.e. , they lay eggs in multiple containers) once gravid (Reinbold-Wasson and Reiskind 2018). Interestingly, M. reukaufii and A. pullulans produced contrasting VOC profiles, with M. reukaufii emitting higher amounts of four shared compounds ( i.e. , 3-methyl-1-butanol, ethanol, 2-methyl-1-butanol and isobutyl alcohol) as well as four additional compounds ( i.e. , 3-methyl-1-butanol acetate, 2-methyl-1-butanol acetate, ethyl hexanoate and ethyl acetate). By emitting a wide range of VOCs, including large quantities of ethanol and 2-methyl-1-butanol, followed by 2-methyl-1-propanol (isobutyl alcohol), 2-phenylethanol and ethyl acetate, M. reukaufii has been shown to attract bumblebee species and several others pollinators (Sobhy et al. 2018 ; Schaeffer et al. 2019 ; Yang et al. 2019 ). In contrast, and consistent with our results, A. pullulans was demonstrated to produce a lower diversity of VOCs, including 3-methyl-1-butanol, 2-methyl-1-butanol and 2-phenylethanol, which strongly attract dipterans, particularly hoverflies (Davis and Landolt 2013 ). Since mosquito larvae are gregarious and incapable of relocating between habitats, they cannot escape unfavorable conditions. As a result, female oviposition choices are often driven by the need to optimize offspring performance (Girard et al. 2024 ). Recently, we showed that yeasts like R. mucilaginosa and A. pullulans , which promote rapid larval development by providing high riboflavin intake and enhancing nitrogenous waste recycling, significantly attract gravid Ae. albopictus females (Malassigné et al. 2025 ). In contrast, yeasts such as M. asiatica and T. delbrueckii , which lack these capabilities are repellent (Malassigné et al. 2025 ). Interestingly, R. mucilaginosa and T. delbrueckii were preferentially associated with colonized and non-colonized breeding-site waters, respectively. In this study, we compared yeasts from these two habitats ( C. slooffiae to R. mucilaginosa in colonized waters, and P. laurentii , P. kluyveri to H. uvarum and T. delbrueckii in non-colonized waters) for their impact on female oviposition behavior and VOC profiles. Interestingly, similar to R. mucilaginosa , C. slooffiae significantly attracted gravid females at a high cell concentration without stimulating oviposition. Unlike T. delbrueckii , which acted as both a deterrent and a repellent at high cell concentrations, P. laurentii , P. kluyveri and H. uvarum only exhibited strong repellent effects against gravid females. Interestingly, with the exception of P. laurentii , the VOC profiles emitted by attractive yeasts ( R. mucilaginosa and C. slooffiae ) differed from those of repellent ones ( H. uvarum , P. kluyveri and T. delbrueckii ). Repellent yeasts emitted a greater diversity of VOCs compared to attractive ones. Among these specific VOCs, certain compounds such as the ethyl octanoate have been demonstrated to induce ovipositional repellency towards Culex quinquefasciatus (Hwang et al. 1982 ). Moreover, the two main volatile compounds ( i.e. , 3-methyl-1-butanol and 2-methyl-1-butanol), shared by both attractive and repellent yeasts were emitted at higher concentrations by the repellent ones. These compounds, when present in microbial volatile blends, have been associated with notable attractiveness for host-seeking mosquitoes (Verhulst et al. 2011 ; Mukabana et al. 2012 ; Michalet et al. 2019 ) and gravid females searching for oviposition sites (Lindh et al. 2008 ; Malassigné et al. 2025 ). However, high concentrations of these compounds within such blends have also been shown to induce repellency (Verhulst et al. 2011 ; Mukabana et al. 2012 ; Malassigné et al. 2025 ). This observation highlights the critical need to carefully manage the concentration of these VOCs when considering the use of these yeasts as attractants. Therefore, understanding the precise balance between the concentration and the repellent/attractive properties of VOCs is essential for optimizing their application in mosquito control strategies. Following the work of Aldridge et al. ( 2016 ), our study shows that repellent yeasts emit more complex VOC profiles, characterized by the presence of specific repellent compounds and attractive volatiles that shift to repellency at high concentrations. Furthermore, we observed differential responses between females and males based on the overall VOC profiles, with both nectar-seeking and gravid females responding positively to cues characterized by lower VOC diversity and abundance. Such a pattern has been already observed for host-seeking Aedes females (Lucas-Barbosa et al. 2023 ; Bourne et al. 2024 ; Malassigné et al. 2025 ). This could partly be explained by sexual dimorphisms observed in mosquitoes, where females possess three to four times more antennal (mostly olfactory) sensilla than males (Wooding et al. 2020 ). CONCLUSION This study expands our understanding of the chemical ecology underlying mosquito-environment associations, particularly regarding the microbial cues shaping the behavioral responses of the Asian tiger mosquito across different life stages. Advancing research on how environmental microbial communities influence mosquito feeding and oviposition behaviors could guide the development of more efficient vector control strategies. This study highlights the role of two nectar-dwelling yeasts, M. reukaufii and A. pullulans , in attracting male and female Ae. albopictus mosquitoes through the emission of specific VOCs, including 3-methyl-1-butanol, ethanol, 2-methyl-1-butanol, and isobutyl alcohol. It also showed that some waterborne yeasts, such as C. slooffiae and R. mucilaginosa , which are preferentially associated with colonized breeding-site waters, attract gravid females. This attraction is linked to the emission of volatile blends characterized by lower VOC richness and reduced concentrations of 3-methyl-1-butanol and 2-methyl-1-butanol. These findings contribute to the growing body of evidence identifying microbial VOCs as key mediators of mosquito attraction during both sugar-seeking and oviposition behaviors. While current trapping strategies mainly focus on mimicking human odors to target host-seeking females, our results emphasize the importance of broadening the chemical spectrum considered in vector control to include cues relevant to other critical mosquito behaviors, such as nectar foraging and oviposition. The inclusion of yeast-emitted kairomones into odor-baited traps could enhance the capture of males and newly emerged females searching for sugar, potentially leading to greater population reduction. Given the repeated implication of compounds such as 3-methyl-1-butanol and 2-methyl-1-butanol in multiple behavioral contexts ( i.e. , host seeking, nectar foraging, and oviposition), further investigation into their ecological relevance and potential synergistic effects is warranted. However, when targeting nectar-seeking insects, it is essential to identify specific compounds and concentrations that effectively attract mosquitoes without drawing in non-target species, such as pollinators like bees and bumblebees. Finally, seasonal shifts in floral resource availability may influence mosquito nectar preferences over time, suggesting that future studies should also consider the temporal dynamics of mosquito–microbe–plant interactions to optimize the deployment of VOC-based trapping tools. Declarations ACKNOWLEDGEMENTS We thank the CESN platform (University of Lyon, France) for providing access to the HS-SPME/GC-MS as well as for their valuable advice and discussions. We thank the IBIO platform (University of Lyon, France), and especially Danis Abrouk, for their advice and assistance with the analysis and submission of the MiSeq sequences. We would like to thank Christophe Bellet and Yves Rozier from the EID Rhône-Alpes for pointing out the locations with breeding sites specifically colonized by Aedes albopictus larvae. FUNDING S. Malassigné PhD was supported by a Research and Technology French National association ANRT and Dipteratech fellowship. Funding for this project was provided by The French National Research Program for Environmental and Occupational Health of Anses (ANSES-21-EST-018). This study was also partially funded by the French National program EC2CO (Ecosphère Continentale et Côtière). CONFLICT OF INTEREST STATEMENT All authors have approved the final version of this manuscript. One author declares the following financial interest, which may be considered a potential competing interest: S.M. was employed by Dipteratech during the course of his PhD. All other authors declare no competing interests and received no financial compensation from Dipteratech. DATA AVAILABILITY STATEMENT The ITS and LSU D1/D2 region sequences of yeast ribosomal DNA have been deposited in GenBank under the accession numbers PV471497 - PV471565 and PV471566 - PV471574, while the FastQ files are available under the project accession number PRJEB85671. All analysis codes and formatted data were deposited in the following site: https://zenodo.org/records/14723343. AUTHOR CONTRIBUTIONS All authors contributed intellectually to and agreed to this submission. S.M., C.V.M. and P.L. designed the experiments. P.L., P.D. and P.A. collected the field samples. S.M., L.V., E.M., G.M.E. and P.L. conducted the experiments and collected the data. 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Ziegler R, Blanckenhorn WU, Mathis A, Verhulst NO (2022) Video analysis of the locomotory behaviour of Aedes aegypti and Ae. japonicus mosquitoes under different temperature regimes in a laboratory setting. J Therm Biol 105:103205. https://doi.org/10.1016/j.jtherbio.2022.103205. Zouache K, Martin E, Rahola N, Gangue MF, Minard G, Dubost A, Van VT, Dickson L, Ayala D, Lambrechts L, Moro CV (2022) Larval habitat determines the bacterial and fungal microbiota of the mosquito vector Aedes aegypti . FEMS Microbiol Ecol 98:fiac016. https://doi.org/10.1093/femsec/fiac016. Additional Declarations Competing interest reported. All authors have approved the final version of this manuscript. One author declares the following financial interest, which may be considered a potential competing interest: S.M. was employed by Dipteratech during the course of his PhD. All other authors declare no competing interests and received no financial compensation from Dipteratech. Supplementary Files TableS1Flowertaxonomicidentification.xlsx TableS2.Detaileddescriptivestatistics.xlsx TableS3.Statisticalanalysis.xlsx TableS4.ListofmicrobialemittedVOCdetected.xlsx Cite Share Download PDF Status: Published Journal Publication published 09 Jan, 2026 Read the published version in Journal of Chemical Ecology → Version 1 posted Editorial decision: Revision requested 31 Aug, 2025 Reviews received at journal 27 Aug, 2025 Reviews received at journal 19 Aug, 2025 Reviewers agreed at journal 13 Aug, 2025 Reviewers agreed at journal 04 Aug, 2025 Reviewers invited by journal 03 Aug, 2025 Editor assigned by journal 02 Aug, 2025 Submission checks completed at journal 01 Aug, 2025 First submitted to journal 31 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7258136","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":496198398,"identity":"b639dd68-fc51-4ec0-b2c6-01b6d8b42dbc","order_by":0,"name":"SIMON MALASSIGNÉ","email":"","orcid":"","institution":"Université Claude Bernard Lyon 1, UMR CNRS 5557, UMR INRAE 1418, VetAgro Sup","correspondingAuthor":false,"prefix":"","firstName":"SIMON","middleName":"","lastName":"MALASSIGNÉ","suffix":""},{"id":496198399,"identity":"43879ac8-d043-4ce6-a767-87e4b221590e","order_by":1,"name":"LAURENT VALLON","email":"","orcid":"","institution":"Université Claude Bernard Lyon 1, UMR CNRS 5557, UMR INRAE 1418, VetAgro Sup","correspondingAuthor":false,"prefix":"","firstName":"LAURENT","middleName":"","lastName":"VALLON","suffix":""},{"id":496198400,"identity":"1d64391d-18b9-40b1-af24-938d876521cf","order_by":2,"name":"EDWIGE MARTIN","email":"","orcid":"","institution":"Université Claude Bernard Lyon 1, UMR CNRS 5557, UMR INRAE 1418, VetAgro Sup","correspondingAuthor":false,"prefix":"","firstName":"EDWIGE","middleName":"","lastName":"MARTIN","suffix":""},{"id":496198401,"identity":"202861a5-5a9b-4768-bfab-ec5fc20e6561","order_by":3,"name":"PIERRE ANTONELLI","email":"","orcid":"","institution":"Université Claude Bernard Lyon 1, UMR CNRS 5557, UMR INRAE 1418, VetAgro Sup","correspondingAuthor":false,"prefix":"","firstName":"PIERRE","middleName":"","lastName":"ANTONELLI","suffix":""},{"id":496198402,"identity":"4fb30aea-969f-4dc5-a681-9dd60abd273d","order_by":4,"name":"PÉNÉLOPE DUVAL","email":"","orcid":"","institution":"Université Claude Bernard Lyon 1, UMR CNRS 5557, UMR INRAE 1418, VetAgro Sup","correspondingAuthor":false,"prefix":"","firstName":"PÉNÉLOPE","middleName":"","lastName":"DUVAL","suffix":""},{"id":496198403,"identity":"711c0415-d530-45f6-9c36-26ee4e3b53e1","order_by":5,"name":"GUILLAUME MEIFFREN","email":"","orcid":"","institution":"Université Claude Bernard Lyon 1, UMR CNRS 5557, UMR INRAE 1418, VetAgro Sup","correspondingAuthor":false,"prefix":"","firstName":"GUILLAUME","middleName":"","lastName":"MEIFFREN","suffix":""},{"id":496198404,"identity":"3fe6d245-33e1-4619-b5ab-65577746792b","order_by":6,"name":"GUILLAUME MINARD","email":"","orcid":"","institution":"Université Claude Bernard Lyon 1, UMR CNRS 5557, UMR INRAE 1418, VetAgro Sup","correspondingAuthor":false,"prefix":"","firstName":"GUILLAUME","middleName":"","lastName":"MINARD","suffix":""},{"id":496198405,"identity":"5b5e8d44-1d68-4ec1-81fe-8083ece9da11","order_by":7,"name":"CLAIRE VALIENTE MORO","email":"","orcid":"","institution":"Université Claude Bernard Lyon 1, UMR CNRS 5557, UMR INRAE 1418, VetAgro Sup","correspondingAuthor":false,"prefix":"","firstName":"CLAIRE","middleName":"VALIENTE","lastName":"MORO","suffix":""},{"id":496198406,"identity":"f6206ea1-b8a3-42d3-a21c-ecdd7e9e5d4d","order_by":8,"name":"PATRICIA LUIS","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFklEQVRIie3PsUrDQBzH8d95cFkuds0g9BVSHNqi0lfJkcFNBJcMoQQKmQquHYo+hND5wkGmQFYHh0DAyaFu6WYuUaGScxa873LH3f9DLoDN9lcL4AEOIBEBDCCyPeSg0jBPPwnVpOgI9OwZWGAm3ytJ+70mlyYydcp8X8WzMSifZIcHdXPqBVA8euFgbjVE5uuQboLcmySU+8rdqTvWkeK1JY4/RHwZUojEIx0hOyVSXu6VmyqOcTr4ML+sO7LQJDtsNZHoCWPD5Ln/itBEuklLnOR3Mt/U52j/JUwpu1U8v+5Iti0UZwYyHYmaNPHy6t5ZPb038YV4XIFUb5FajEwP+9ocXZ/wnydD5CjSGMZtNpvtX/YB0FVWu9OBjpsAAAAASUVORK5CYII=","orcid":"","institution":"Université Claude Bernard Lyon 1, UMR CNRS 5557, UMR INRAE 1418, VetAgro Sup","correspondingAuthor":true,"prefix":"","firstName":"PATRICIA","middleName":"","lastName":"LUIS","suffix":""}],"badges":[],"createdAt":"2025-07-31 05:08:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7258136/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7258136/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10886-025-01685-0","type":"published","date":"2026-01-09T15:57:39+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88627834,"identity":"dd83ed22-145c-40fa-9fca-bc390dacbfbd","added_by":"auto","created_at":"2025-08-08 13:16:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":829973,"visible":true,"origin":"","legend":"\u003cp\u003eDescription of the experimental setup combining two locomotor activity monitoring systems to investigate the impact of yeast on mosquito sugar feeding behavior.\u003cstrong\u003e (A)\u003c/strong\u003e Locomotor activity monitor (LAM25) as sold by Trikinetics Inc. The LAM25 monitor contains 32 channels. Each channel contains three infrared beams and their corresponding receptor. The wiring of the internal board of the monitors is arranged such that the interruption of one or more beams on each channel counts as a single activity event. \u003cstrong\u003e(B) \u003c/strong\u003eTwo-glass-tube assembly ensuring that every individual has the choice between cotton impregnated with of sterile medium and cotton impregnated with the same medium inoculated at a specific yeast concentration. \u003cstrong\u003e(C)\u003c/strong\u003e Fully assembled experimental setup combining the two LAM25 systems, including the two-glass-tube assembly. Mosquito movements were recorded every two minutes.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/9f4dc7985621a6359c62f590.png"},{"id":88627838,"identity":"39bbc29c-9f4c-45db-a171-676fd64f1500","added_by":"auto","created_at":"2025-08-08 13:16:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":180583,"visible":true,"origin":"","legend":"\u003cp\u003eInformation relative to the 130 flowering plants collected from 14 community gardens in the Lyon metropolitan area. \u003cstrong\u003e(A)\u003c/strong\u003e Distribution of collected plants by taxonomic families. \u003cstrong\u003e(B)\u003c/strong\u003e Photograph showing an Asian tiger mosquito (\u003cem\u003eAedes albopictus\u003c/em\u003e) visiting a spearmint flower (\u003cem\u003eMentha spicata\u003c/em\u003e). Photo credit: P. Duval.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/0f1bc2adb72466e7e3f73396.png"},{"id":88627831,"identity":"40d11e29-2a6c-4c75-bb5f-c4d31d4f5cbf","added_by":"auto","created_at":"2025-08-08 13:16:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":187751,"visible":true,"origin":"","legend":"\u003cp\u003eFungal community composition and structure associated with flowering plants visited or not by \u003cem\u003eAedes albopictus\u003c/em\u003emosquitoes and breeding-site waters colonized or not by larvae using a metabarcoding approach. \u003cstrong\u003e(A) \u003c/strong\u003eRelative abundance of yeast sequences for each sample category. Statistically significant differences between groups were assessed using Tukey post-hoc tests (\u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.05).\u003cstrong\u003e (B)\u003c/strong\u003eNon-metric multidimensional scaling (NMDS) ordination displaying fungal ITS-2 Operational Taxonomic Units (OTUs) composition across the different sample categories (Stress = 0.22). \u003cstrong\u003e(C)\u003c/strong\u003e NMDS ordination displaying specifically the yeast OTU composition across the different sample categories. (Stress = 0.19). Each NMDS ordination was based on a Bray-Curtis dissimilarity matrix of square root-transformed abundance data obtained from sequence counts. To better distinguish between the sample categories, visited (V) and non-visited (NV) flowers are shaded in red and orange, respectively. In contrast, colonized (C) and non-colonized (NC) breeding-site waters are colored blue and black, respectively.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/eb8ef8e7f513c8ffd64eeba9.png"},{"id":88628871,"identity":"415ecc57-922e-4ec2-85a9-401a60da92aa","added_by":"auto","created_at":"2025-08-08 13:24:06","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":363578,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagrams illustrating the overlap of global fungal and yeast communities between sample categories (flowers and waters) and the presence or absence of \u003cem\u003eAe. albopictus\u003c/em\u003e mosquitoes (visited and non-visited flowers or colonized and non-colonized waters). \u003cstrong\u003e(A)\u003c/strong\u003eGlobal fungal communities detected through high-throughput amplicon sequencing approach (ITS-2 region). \u003cstrong\u003e(B) \u003c/strong\u003eYeast communities detected during this amplicon sequencing approach. \u003cstrong\u003e(C)\u003c/strong\u003e Yeast communities detected through a culture-based approached conducted on the same collected samples.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/53a21f180f6bb226c6c39254.png"},{"id":88627850,"identity":"93350b1c-83b9-4064-905b-ce1a4d09285a","added_by":"auto","created_at":"2025-08-08 13:16:06","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":153096,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence and average relative abundance of yeast species isolated from different environmental samples collected from 14 community gardens in the Lyon metropolitan area colonized by \u003cem\u003eAedes albopictus\u003c/em\u003e. \u003cstrong\u003e(A)\u003c/strong\u003e Non-visited flowers (NV, labelled in orange). \u003cstrong\u003e(B)\u003c/strong\u003eVisited flowers (V, labelled in red).\u003cstrong\u003e (C)\u003c/strong\u003e Non-colonized breeding-site waters (NC, labelled in black). \u003cstrong\u003e(D)\u003c/strong\u003e Colonized breeding-site waters (C, labelled in blue).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/4ec0f056bcdeb7aad67a3b8a.png"},{"id":88628872,"identity":"06b5f67c-fbc7-4ca6-bf3b-7a794dfac9e0","added_by":"auto","created_at":"2025-08-08 13:24:07","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":492594,"visible":true,"origin":"","legend":"\u003cp\u003eRelative abundance of Ascomycota within the total fungal and yeast communities associated with flowering plants visited (V) or not visited (NV) by \u003cem\u003eAedes albopictus\u003c/em\u003e mosquitoes and breeding-site waters colonized (C) or not colonized (NC) by larvae. Regarding the Miseq sequencing approach, the relative abundance of Ascomycota corresponds to the percentage of the total number of sequences affiliated with this phylum. In contrast, the relative abundance of Ascomycota in cultivable community represents the percentage of colonies belonging to this phylum. Statistically significant differences between groups were identified using the Dunn test. Modalities labelled with an asterisk (✱) or a dot (●) indicate a \u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.05 or \u0026lt; 0.1, respectively.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/106dbf9ce72337139591a9ec.png"},{"id":88627832,"identity":"2793398d-39cc-4e95-a30d-68c44b579adb","added_by":"auto","created_at":"2025-08-08 13:16:06","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":651864,"visible":true,"origin":"","legend":"\u003cp\u003eImpact of different nectar-dwelling yeast species and their cell concentrations on the sugar-feeding behavior of \u003cem\u003eAedes albopictus\u003c/em\u003e mosquitoes. The effect of four yeast species (\u003cem\u003eAureobasidium pullulans\u003c/em\u003e,\u003cem\u003e Filobasidium magnum\u003c/em\u003e, \u003cem\u003eMetschnikowia reukaufii \u003c/em\u003eand \u003cem\u003eRhodotorula glutinis\u003c/em\u003e) at two cell concentrations (5.10\u003csup\u003e3\u003c/sup\u003e and 5.10\u003csup\u003e5\u003c/sup\u003e cells.mL\u003csup\u003e-1\u003c/sup\u003e) on the sugar-feeding preferences of females and males was evaluated using a dual locomotor activity monitoring (LAM25) system behavioral bioassay. Mosquitoes were given a choice between cotton impregnated with Lamiaceae sterile medium and cotton impregnated with the same medium inoculated with the yeast at the specific cell concentration. Movements were recorded over 17 h at two-minute intervals by counting the number of times each individual crossed the infrared beam near the cotton impregnated with sterile medium or the opposite infrared beam near the cotton impregnated with yeast culture. The \u003cem\u003ep-value\u003c/em\u003e obtained from a pairwise Tukey test\u0026nbsp;(p \u0026lt; 0.05) following a GLMM model represents the significance of the difference in the number of movements between the medium and yeast culture, accounting for individual variability.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/4b4ca96e0cbfa4bac04ddcab.png"},{"id":88627856,"identity":"45c030f5-c60b-400e-83c2-8b12ca213e7f","added_by":"auto","created_at":"2025-08-08 13:16:06","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":663463,"visible":true,"origin":"","legend":"\u003cp\u003eVolatile organic compounds emitted by nectar-dwelling yeasts that significantly attracted \u003cem\u003eAedes albopictus\u003c/em\u003e mosquitoes. Each yeast culture was prepared in Lamiaceae medium at a final volume of 100 mL and an initial cell concentration of 5.10\u003csup\u003e5\u003c/sup\u003e cells.mL\u003csup\u003e-1\u003c/sup\u003e. Cultures were incubated under constant agitation (130 rpm) for 18 h prior VOC analysis. \u003cstrong\u003e(A)\u003c/strong\u003e Heatmap illustrating the relative abundance of emitted VOCs detected by HS-SPME/GC–MS from five independent replicates of each yeast culture. \u003cstrong\u003e(B)\u003c/strong\u003e Relative abundances of 3-Methyl-1-butanol, Ethanol, 2-Methyl-1-butanol and Isobutyl alcohol, four VOCs shared by nectar-dwelling yeasts that attracted females (\u003cem\u003eAureobasidium pullulans\u003c/em\u003e, in green) and males (\u003cem\u003eMetschnikowia reukaufii\u003c/em\u003e, in blue) mosquitoes. The median is indicated by a horizontal black line. Statistically significant differences between yeasts were determined using the Wilcoxon rank sum exact test (W = 0; \u003cem\u003ep-value\u003c/em\u003e = 0.008).\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/7f0596221a2ba97099201198.png"},{"id":88627828,"identity":"a812f125-ba52-4933-8d3a-d6ada546e45e","added_by":"auto","created_at":"2025-08-08 13:16:05","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":1010790,"visible":true,"origin":"","legend":"\u003cp\u003eImpact of yeast species and their cell concentrations on oviposition behavior of \u003cem\u003eAedes albopictus\u003c/em\u003e gravid females. The impact of six yeast species (\u003cem\u003eCystobasidium slooffiae, Rhodotorula mucilaginosa, Aureobasidium pullulans\u003c/em\u003e, \u003cem\u003ePapiliotrema laurentii, Pichia kluyveri \u003c/em\u003eand\u003cem\u003e Torulaspora delbrueckii\u003c/em\u003e) at two cell concentrations (3.10\u003csup\u003e2\u003c/sup\u003e and 3.10\u003csup\u003e5\u003c/sup\u003e cells.mL\u003csup\u003e-1\u003c/sup\u003e) on the oviposition behavior of gravid females was evaluated using two distinct and complementary laboratory bioassays. Oviposition preference bioassays, (corresponding to panels A and B) consisted of small-cage three-choice oviposition tests, in which each single gravid female (n = 24) was allowed to choose between three oviposition sites (double beaker systems) providing oviposition substrates containing waterborne substances that can act as deterrent or stimulant (sterile water or sterile water inoculated with yeasts) and olfactory stimuli that can act as attractant or repellent (volatile organic compounds emitted by sterile CYM medium or yeast cultures). \u003cstrong\u003e(A) \u003c/strong\u003ePercentages of females that have laid eggs (shown in gray) or have not laid eggs (shown in black). \u003cstrong\u003e(B)\u003c/strong\u003e Number of eggs laid by each female in each oviposition site during three-choice oviposition tests. These oviposition preference bioassays were used to assess short-range attractiveness or repellency of volatile compounds emitted by yeasts, but only because they were systematically paired with oviposition stimulation bioassays conducted in 50 mL conical tubes (panel C), where a single gravid female (n = 25) was specifically exposed to either sterile water or water inoculated with one of the two tested yeast concentrations to enable the evaluation of stimulant or deterrent effects of yeast-derived waterborne substances. \u003cstrong\u003e(C)\u003c/strong\u003e Number of eggs laid by each female according to each type of oviposition substrate in oviposition stimulation bioassays. Statistically significant differences between groups were identified with the Tukey post hoc tests. Columns labelled with different letters or with an asterisk (*) are significantly different with a \u003cem\u003ep-value \u003c/em\u003e\u0026lt; 0.05. Columns labelled with a dot (·) are almost significantly different with a \u003cem\u003ep-value \u003c/em\u003e\u0026lt; 0.1.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/0c3d8f6790258a9b51d69819.png"},{"id":88628873,"identity":"749f4ab2-e533-4119-887b-d8d6bc6e2eaf","added_by":"auto","created_at":"2025-08-08 13:24:07","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":1044157,"visible":true,"origin":"","legend":"\u003cp\u003eVolatile organic compounds emitted by waterborne yeasts that significantly impact oviposition behavior of gravid \u003cem\u003eAedes\u003c/em\u003e \u003cem\u003ealbopictus\u003c/em\u003e females.\u003cstrong\u003e \u003c/strong\u003eEach yeast culture was prepared in CYM medium at a final volume of 100 mL and an initial cell concentration of 3.10\u003csup\u003e5\u003c/sup\u003e cells.mL\u003csup\u003e-1\u003c/sup\u003e. Cultures were incubated under constant agitation (130 rpm) for 18\u0026nbsp;h prior VOC analysis. \u003cstrong\u003e(A) \u003c/strong\u003eHeatmap illustrating the relative abundance of emitted VOCs detected by HS-SPME/GC–MS from five independent replicates\u003cstrong\u003e \u003c/strong\u003eof each yeast culture. \u003cstrong\u003e(B) \u003c/strong\u003eRelative\u003cstrong\u003e \u003c/strong\u003eabundances of 3-Methyl-1-butanol and 2-Methyl-1-butanol, two VOCs shared by both repellent (\u003cem\u003eHanseniaspora uvarum \u003c/em\u003ein green, \u003cem\u003eTorulaspora delbrueckii\u003c/em\u003e in blue, and \u003cem\u003ePichia kluyveri\u003c/em\u003e in yellow) and attractive (\u003cem\u003ePapiliotrema laurentii \u003c/em\u003ein red\u003cem\u003e, Rhodotorula mucilaginosa\u003c/em\u003e in grey\u003cem\u003e, \u003c/em\u003eand\u003cem\u003e Cystobasidium slooffiae\u003c/em\u003e in light blue) yeast species. The median is indicated by a horizontal black line. Statistically significant differences between yeasts, labelled with different letters, were determined using Dunn's test with Bonferroni-Holm correction (\u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/ca243cad6113b2c42d14e92d.png"},{"id":100069217,"identity":"03743eb4-7b27-4b19-849e-107a67473eb9","added_by":"auto","created_at":"2026-01-12 16:11:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6822821,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/ce6ba49d-35f5-41f1-b4f6-a3c94cec7a7e.pdf"},{"id":88627837,"identity":"05a0e694-4b84-4c0a-8277-2b38d73e5531","added_by":"auto","created_at":"2025-08-08 13:16:06","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":14796,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1Flowertaxonomicidentification.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/8f9b0e089ef11266df1b7399.xlsx"},{"id":88627841,"identity":"ec441801-e9ea-4064-bd80-8eeef985785e","added_by":"auto","created_at":"2025-08-08 13:16:06","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15332,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.Detaileddescriptivestatistics.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/c6165221d25384b4ddad08b5.xlsx"},{"id":88627845,"identity":"58d54f49-4a92-4fb7-a07c-106fc9cd9ea5","added_by":"auto","created_at":"2025-08-08 13:16:06","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":24806,"visible":true,"origin":"","legend":"","description":"","filename":"TableS3.Statisticalanalysis.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/5cc53b7e5d9bd6d4dc1682c2.xlsx"},{"id":88627843,"identity":"8eb13881-955d-4c18-9b10-36359cdfad8c","added_by":"auto","created_at":"2025-08-08 13:16:06","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":13630,"visible":true,"origin":"","legend":"","description":"","filename":"TableS4.ListofmicrobialemittedVOCdetected.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7258136/v1/6d907bfb7225c5c18a62b33a.xlsx"}],"financialInterests":"Competing interest reported. All authors have approved the final version of this manuscript. One author declares the following financial interest, which may be considered a potential competing interest: S.M. was employed by Dipteratech during the course of his PhD. All other authors declare no competing interests and received no financial compensation from Dipteratech.","formattedTitle":"\u003cp\u003eCharacterization of Volatile Organic Compounds from Waterborne and Nectar-Dwelling Yeasts Attractive to Asian Tiger Mosquitoes\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eHematophagous mosquitoes, including species from the genera \u003cem\u003eAedes\u003c/em\u003e, \u003cem\u003eCulex\u003c/em\u003e and \u003cem\u003eAnopheles\u003c/em\u003e, are holometabolous insects that undergo complete metamorphosis (Truman \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). After hatching, they pass through four larval instars before reaching the pupal stage and ultimately emerging as adults (Clements 1992). Immature and adult stages occupy distinct ecological niches, with larvae developing in aquatic habitats, whereas adults live in terrestrial environments. This spatial separation is a key ecological strategy to minimize intraspecific competition for resources (Truman \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Larvae primarily feed on organic matter in water, such as microorganisms and plant debris, using filtering, grazing, and shredding behaviors (Merrit et al. 1992; Yee et al. \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Souza et al. \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In contrast, although females require blood meals for egg production (Harrison et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), adult mosquitoes of both sexes rely on sugar-rich sources, such as flower nectar, to meet their energy and nutritional needs (Barredo and DeGennaro \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sobhy and Berry \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Floral nectar, rich in natural sugars like sucrose, glucose, and fructose, is essential for adult mosquito survival, flight, and reproductive success (Foster \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Spitzen and Takken \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This energy source is particularly vital for males, which feed exclusively on plant-derived sugars. Without regular sugar intake, males typically survive only a few days post-emergence (Bellini et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Chadee et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The lack of sugar-derived energy reserves severely limits their ability to fly or copulate, with detrimental consequences for their reproductive potential (Bellini et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). While females are more resilient to sugar deprivation, their survival and fecundity are nonetheless compromised in its absence (Chadee et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In \u003cem\u003eAedes aegypti\u003c/em\u003e and \u003cem\u003eAe. albopictus\u003c/em\u003e, for example, plant nectar consumption not only enhances female survival but also stimulates egg development and increases overall fecundity, thereby extending the oviposition period (Naziri et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Nyasembe et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNectar quality varies considerably among flowering plant species, reflecting differences in the concentration and composition of sugars, essential amino acids, and other compounds (Venjakov et al. 2022). Due to its high sugar content, floral nectar is colonized by yeast and bacterial communities characterized by low species richness but high cell densities (Herrera et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Pozo et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Fenner et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Quevedo-Caraballo et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The metabolic activity of these nectar-dwelling microorganisms can alter nectar chemistry by modifying sugar and amino acid profiles, and by increasing both temperature and acidity (Herrera and Pozo \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Lenaerts et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Sobhy et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Vannette and Fukami \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). As a result, not all flowering plants provide nectar of equal nutritional or energetic value. Microbially driven changes can influence the suitability of floral resources for nectar-feeding insects, including mosquitoes (Davis and Landolt \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Sobhy et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Peach et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These alterations may in turn influence mosquito fitness, foraging behavior, and plant preference (Gouagna et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Manda et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Nikbakhtzadeh et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Paré et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Similarly, mosquito breeding sites, enriched with organic matter derived from soil, decaying vegetation, animal cadavers, and excreta, promote the growth of diverse bacterial and fungal communities (Tawidian et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Duval et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zhao et al. \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These microbial assemblages play a key role in shaping the mosquito microbiota and significantly influence larval development and major adult traits, such as body size and lifespan (Steyn et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Dickson et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Cansado-Utrilla et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zouache et al. \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Duval et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Malassigné et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In addition to serving as a primary food source, facultative symbionts acquired from the environment provide essential nutrients, such as B vitamins and amino acids, required for optimal larval development (Valzania et al. \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Malassigné et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Besides predators and pathogens that negatively affect larval development, the variable nutritional value of microorganisms used as diet, along with the inconsistent supply of essential nutrients by facultative symbionts, differentially impact larval development and survival, thereby influencing breeding-site selection (Steyn et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Souza et al. \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Girard et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Malassigné et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Raquin et al. 2025). Given that oviposition-site selection is strongly oriented toward maximizing offspring performance, gravid female mosquitoes from \u003cem\u003eAedes\u003c/em\u003e species preferentially select breeding sites colonized by conspecific larvae, while avoiding those where larvae are starved or infected with deleterious parasites (Reeves \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Shragai et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Khan et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo locate and select suitable nectar sugar meals and oviposition sites, mosquitoes rely on a combination of visual, gustatory, and olfactory cues (Wooding et al. \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). An increasing number of studies highlight the role of volatile organic compounds (VOCs), whether present in floral scents or emitted by waterborne microorganisms, in mediating mosquito foraging and oviposition behaviors (Lahondère et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Girard et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Upshur et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Malassigné et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Nectar-inhabiting microorganisms, in particular, are known to significantly shape flower scent by producing and releasing various VOCs (Lenaerts et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Rering et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sobhy et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Schaeffer et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Peach et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These microbially derived compounds can sometimes act as honest signals of the quality of floral food source, thereby influencing the attractiveness and acceptability of flowers to nectar-visiting insects, including mosquitoes (Wright and Schiestl \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Davis et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Rering et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sobhy et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Crowley-Gall et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Peach et al \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, despite growing interest in the chemical ecology of mosquito-microbe interactions, the specific contribution of nectar-dwelling microorganisms and their emitted VOCs to mosquito nectar-seeking behavior remains poorly understood. Moreover, the extent to which these olfactory cues differ from those associated with waterborne microorganisms involved in oviposition-site selection remains largely unexplored (Girard et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sobhy and Berry \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this context, we focused on yeast communities because \u003cem\u003eAe. albopictus\u003c/em\u003e mosquitoes harbor a diverse, environmentally acquired fungal community, with yeasts representing up to 84% of the mycobiota (Luis et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hedge et al. 2024). Yeasts abundantly present in floral nectar have been shown to significantly influence the nectar foraging preferences of insect pollinators, including mosquitoes, due to their consistent VOCs emissions (Becher et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sobhy et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Rering et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Peach et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The Asian tiger mosquito \u003cem\u003eAe. albopictus\u003c/em\u003e is an invasive species that has become a global health concern due to its proliferation in urban and suburban areas worldwide as well as its involvement in several outbreaks (Solimini et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sherpa et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Swan et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Duval et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sansone et al. \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Cattaneo et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Urban community gardens, established in European cities to enhance urban ecosystem health by increasing biodiversity, especially pollinators such as bees and butterflies, offer a wide variety of plant species and a high density of standing water containers. These conditions provide ideal sugar meal sources and oviposition habitats for \u003cem\u003eAe. albopictus\u003c/em\u003e (Ochoa et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Jha et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Schmack and Egerer \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Duval et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this study, we investigated the diversity and behavioral relevance of yeast communities associated with the nectar of flowers and oviposition sites foraged by \u003cem\u003eAe. albopictus.\u003c/em\u003e Specifically, we analyzed yeast assemblages from plants visited or not visited by adult mosquitoes, as well as from standing waters colonized or uncolonized by \u003cem\u003eAe. albopictus\u003c/em\u003e larvae. The sampling was conducted across 14 urban community gardens within the metropolitan area of Lyon in France, using a dual approach combining culture-based and sequencing methods to identify yeast taxa. Following yeast identification, we evaluated their impact on mosquito behavior related to nectar-seeking and oviposition. We subsequently characterized the VOCs they produce. Beyond providing new insight into the ecological role of microorganisms in shaping mosquito behavior, identifying VOCs that attract mosquitoes seeking nectar or oviposition sites may offer promising avenues for vector control. In particular, these microbially derived cues could serve as valuable complements to microbial human-skin attractants used in traps for host-seeking females (Akhoundi et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Degener et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Staunton et al. \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), paving the way for the development of more efficient mass-trapping strategies.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"METHODS AND MATERIALS","content":"\u003cp\u003e\u003cem\u003eSample collection.\u003c/em\u003e Field sampling was carried out in 14 community gardens across the Lyon metropolitan area (France) between July and September 2021. As previously described (Duval et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), to limit the impact of certain environmental factors such as precipitation and air temperature on water parameters and mosquito dynamics, all sampling was conducted in the morning during the same time window, ensuring that no rainfall had occurred in the preceding 48 hours. In each garden, two 50 mL water samples were collected from distinct breeding sites located within a 200 m radius: one from a site naturally colonized by \u003cem\u003eAe. albopictus\u003c/em\u003e larvae, and the other from a non-colonized site. These are hereafter referred to as C and NC, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Before sampling, each container was stirred to homogenize organic detritus. Water was then collected using a sterile plastic pipette and transferred into a 50 mL sterile conical tube (Greiner Bio-One).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eList of water samples collected from 14 community gardens within the Lyon metropolitan area.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGarden name (ID)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGPS\u003c/p\u003e\u003cp\u003eCoordinates\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSampling date\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eColonized\u003c/p\u003e\u003cp\u003ebreeding site type (C)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNon-colonized breeding site type (NC)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCollected plant number\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins du Mas de la Forêt (FOR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.727440, 4.912791\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19/07/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eWatering can 8L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins EDF (EDF)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.716809, 4.843919\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20/07/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins de Sytral (SYT)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.715090, 4.867798\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21/07/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRainwater collector 150L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRainwater collector 50L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins de Alstom (ALS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.781367, 4.900155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22/07/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins de la Mouche (MOU)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.694260, 4.811824\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26/07/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins du Billot (BIL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.723953, 4.890951\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27/07/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins de la Garaine (GAR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.689472, 4.883222\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31/08/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins du Mas Rebufer (REB)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.727344, 4.914945\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e01/09/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins des Quatre Saisons (QUA)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.818453, 4.883150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e06/09/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eBucket 5L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins du Perollier (PER)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.796643, 4.773981\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e07/09/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins Reculés (REC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.795975, 4.927420\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13/09/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eBucket 10L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins SNCF Cordier (COR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.603220, 4.775615\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21/09/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins de la Tase (TAS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.760277, 4.930609\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22/09/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBucket 5L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eBucket 5L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJardins de Francheville (FRA)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45.743647, 4.768156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30/09/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWatering can 30L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRainwater collector 200L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eIn parallel, ornamental and wild flowering plants located within a 200 m perimeter around these breeding sites were also collected. Identification of the plants (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e) was based on morphological characteristics and confirmed with genetic barcodes (see the “Bioinformatics analysis” section below). All samples were properly stored in an icebox and brought to the laboratory for immediate processing. As for the breeding sites, flowers were classified as visited (V) or non-visited (NV) based on visual observations (\u003cem\u003ei.e.\u003c/em\u003e, the presence or absence of \u003cem\u003eAe. albopictus\u003c/em\u003e mosquitoes on the flowers).\u003c/p\u003e\u003cp\u003e\u003cem\u003eYeast isolation and morphotype-based characterization.\u003c/em\u003e Yeast isolation was carried out using selective Dichloran-Rose Bengal Chloramphenicol (DRBC) agar medium (Biokar Diagnostics). A 100 µL aliquot of each fresh homogenized water sample was plated onto a DRBC plate in triplicate. For each collected plant, a pool of two to four flowers was homogenized in 400 µL of sterile 1X PBS (Gibco) using sterile 1.5 ml microtube pestles. After brief vortex agitation, the homogenate was plated onto four DRBC plates (100 µL/plate). All plates were incubated at 22°C and monitored daily for two weeks, with a final observation three weeks after plating. Characterization of microbial strains was initially based on the macroscopic identification of colony morphotypes (similar color, shape, and size). Individual colonies representing each morphotype from each sample were selected and streaked onto CYM agar plates (maltose 10 g·L⁻¹, glucose 20 g·L⁻¹, yeast extract 2 g·L⁻¹, tryptone 2 g·L⁻¹, MgSO₄ 0.5 g·L⁻¹, KH₂PO₄ 4.6 g·L⁻¹, agar 20 g·L⁻¹), a non-selective medium suitable for the growth of most yeast strains. To ensure the purity of the colony-forming strains prior to molecular identification and storage in 15% glycerol at -80°C, the colonies were streaked once more onto fresh CYM agar plates.\u003c/p\u003e\u003cp\u003e\u003cem\u003eDNA extraction from isolated yeast strains and environmental samples\u003c/em\u003e. Genomic DNA from each yeast morphotype was extracted following the protocol of Liu et al. (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), while environmental DNA (eDNA) from water and flower samples was purified using a method adapted from Duval et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Briefly, the pellets obtained after centrifuging 8 mL of each water sample (10 min at 16,000 g) and the pools of two to four flowers from each collected plant were used for eDNA extractions. Flowers were crushed with 3-mm borosilicate beads (Sigma) for 30 s at a speed of 6 m.s\u003csup\u003e− 1\u003c/sup\u003e using a FastPrep-24™ 5G (MP Biomedicals). Pellets and flower grinds were resuspended in 250 µL of CTAB buffer. The homogenates were incubated for 1 h at 60°C, followed by RNase treatment with 0.4 mg of enzyme at 37°C for 5 min. Proteins were removed through successive extractions with phenol:chloroform:isoamyl alcohol (25:24:1) and chloroform:isoamyl alcohol (24:1) mixtures. DNA was precipitated with isopropyl alcohol, washed with 75% ethanol, and dissolved in 24 µL of sterile water. The purity and concentration of all DNA extracts were assessed using the Nanophotometer NP80 (Implen) and the Qubit dsDNA High Sensitivity kit in combination with the Qubit 4 fluorometer (Invitrogen), respectively.\u003c/p\u003e\u003cp\u003e\u003cem\u003ePCR amplifications and sequencing\u003c/em\u003e. The internal transcribed spacer (ITS) or, alternatively, the D1/D2 region of the large subunit (LSU) ribosomal DNA (rDNA) was amplified from extracted genomic DNA from yeast isolates using the ITS1F (5′- CTT GGT CAT TTA GAG GAA GTA A -3′) / ITS4R (5′- TCC TCC GCT TAT TGA TAT GC -3′; White et al. \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Gardes and Bruns \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) or NL1F (5′- GCA TAT CAA TAA GCG GAG GAA AAG − 3’) / NL4R (5′- GGT CCG TGT TTC AAG ACG G -3′; Kurtzman and Robnett \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) primer pairs, respectively. A 25 µL PCR reaction mix containing 2.5 µL of 10X polymerase buffer (Invitrogen), 0.75 µL of MgCl\u003csub\u003e2\u003c/sub\u003e (50 mM, Invitrogen), 2.5 µL of dNTPs (2 mM each, ThermoFisher Scientific), 1 µL of each primer (20 µM, Invitrogen), 0.3 µL of BSA (20 mg.mL\u003csup\u003e− 1\u003c/sup\u003e, New England BioLabs), 0.1 µL of \u003cem\u003eTaq\u003c/em\u003e DNA polymerase (Invitrogen), and 60 ng of DNA was prepared. Cycling conditions, performed on a T100 Thermal Cycler (Bio-Rad), consisted of an initial denaturation at 94°C for 3 min, followed by 35 cycles of 45 sec at 94°C, 45 sec at 55°C, and 1 min at 72°C, with a final extension step at 72°C for 10 min. Control reactions without nucleic acid were systematically run in parallel. PCR products were purified and sequenced by Microsynth France SAS (Vaulx-en-Velin, France) using the Sanger method. Manually curated sequences were compared to reference sequences available in the NCBI GenBank using BLASTn. Cultivable yeast species preferentially associated with C and NC water samples or V and NV flowers were used to assess their impact on mosquito sugar-feeding and oviposition behavior. High-throughput sequencing was also used to detect environmental yeasts from water and flower DNA samples by amplifying the fungal rDNA ITS-2 region using the modified gITS7 (5’- GTG AAT CAT CGA RTC TTT G -3’) and ITS4 (5’- TCC TCC GCT TAT TGA TAT GC -3’) primers (Luis et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The primers were tagged with the Illumina adapters 5’- TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG − 3’ and 5’- GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACA G -3’, enabling a two-step PCR construction of amplicon libraries. All PCR amplifications were carried out in duplicates on a T100 thermal cycler (Bio-Rad) in a 25 µL reaction volume. PCR reactions were performed using the 5X Hot FIREpol Blend Master Mix Ready to load with 12.5 mM MgCl\u003csub\u003e2\u003c/sub\u003e (Solis BioDyne), 1 µM of each primer and 20 ng DNA. Cycling conditions consisted of an initial denaturation at 94°C for 10 min, followed by 40 cycles of 45 sec at 94°C, 45 sec at 55°C, and 30 sec at 72°C, with a final extension step at 72°C for 5 min. Amplicons were checked by electrophoresis on 1.5% agarose after 20 min of migration at 100 V, followed by UV visualization. The PCR products were then sent to IGFL sequencing platform (Lyon, France) for purification and second-step PCR, followed by 2x300 bp Miseq sequencing (Illumina).\u003c/p\u003e\u003cp\u003e\u003cem\u003eHigh-throughput sequence analysis and taxonomy assignment\u003c/em\u003e. A total of 18,024,648 reads were obtained for the fungal ITS-2 Miseq raw dataset and paired-end reads were demultiplexed based on their corresponding sample indices by the IGFL sequencing platform. Quality control and sequence analysis were performed using the FROGS pipeline (Escudié et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Briefly, R1 and R2 reads were merged using VSEARCH (Rognes et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) with default parameters. Denoising was carried out by discarding sequences outside of the expected length (\u003cem\u003ei.e.\u003c/em\u003e, expected size between 200 and 500 bp) and those containing ambiguous bases (N). Clustering was performed using SWARM (Mahé et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) based on an aggregation distance of 3 in order to generate the operational taxonomic units (OTUs). Chimeric OTUs were removed using VSEARCH and, as recommended by Bokulich et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), low abundance sequences accounting for less than 0.005% of the dataset were filtered out. Taxonomic assignment of OTUs was performed using the RDP Classifier (Wang et al. \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) against the curated eukaryotic ITS UNITE database version 8.0 (Abarenkov et al. 2023). Contaminant OTUs detected in negative controls (blank extraction and PCR) were systematically removed. Non-fungal OTUs, such as plant OTUs that confirmed the identification of collected flowering plants (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e), were also excluded from the final dataset. To allow sample comparison, normalization was performed by randomly resampling down to 4473 sequences. An abundance matrix was generated for yeast species isolated from the different sample types (\u003cem\u003ei.e.\u003c/em\u003e, C and NC waters, V and NV flowers).\u003c/p\u003e\u003cp\u003e\u003cem\u003eMosquito colony rearing.\u003c/em\u003e The F13 generation of the laboratory-reared \u003cem\u003eAe. albopictus\u003c/em\u003e population (AeAlbSP) was used in all behavioral experiments. After hatching, mosquito larvae were reared at 28°C in plastic trays filled with dechlorinated water under a 16:8h Light:Dark (L:D) photoperiod. They were fed daily a crushed mixture of 75% tropical-fish flakes (TetraMin, Tetra) and 25% yeast tablets (Biover) until reaching the pupal stage. Adults were raised in large BugDorm cages (32.5 x 32.5 x 32.5 cm) within climatic chambers (Panasonic MLR-352) set at 28°C, 80% relative humidity, and a 16:8h L:D photoperiod. They were fed \u003cem\u003ead libitum\u003c/em\u003e a 10% sucrose solution. Once a week, adult females were fed defibrinated sheep blood (ThermoFisher Scientific) using a membrane feeding system (Hemotek Ltd) with pig intestine as membrane. Eggs were collected on blotting paper and stored for up to 3 months under dry conditions at 28°C.\u003c/p\u003e\u003cp\u003e\u003cem\u003eYeast culture conditions.\u003c/em\u003e To formally identify and assess the role of attractive nectar-dwelling yeasts and their emitted VOCs on \u003cem\u003eAe. albopictus\u003c/em\u003e sugar-feeding preference, we used a synthetic medium mimicking the sugar composition of Lamiaceae nectar (18% sucrose, 6% glucose, 6% fructose, 0.5% peptone, 0.2% MgSO\u003csub\u003e4\u003c/sub\u003e and 0.3% KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e; Venjakov et al. 2022), which corresponds to that of the visited flowers. For each yeast species, two cell concentrations (\u003cem\u003ei.e.\u003c/em\u003e, 5.10\u003csup\u003e3\u003c/sup\u003e and 5.10\u003csup\u003e5\u003c/sup\u003e cells.ml\u003csup\u003e− 1\u003c/sup\u003e) were tested. The lower concentration reflected the average natural densities observed in flowers using plate counting, while the higher concentration represented 100 times these densities. The higher concentration accounted for potential underestimation of colony abundance on plates, which may result from interspecies competition affecting natural colony counts (Kolesidis et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Moreover, it is well known that VOC concentrations, impacted by cell densities, modulate mosquito response (Kim et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). For each yeast species tested, a 3 mL overnight culture in Lamiaceae medium (28°C at 180 rpm) was used to inoculate 1L of fresh medium at a defined cell concentration (\u003cem\u003ei.e.\u003c/em\u003e, 5.10\u003csup\u003e3\u003c/sup\u003e or 5.10\u003csup\u003e5\u003c/sup\u003e cells.mL\u003csup\u003e− 1\u003c/sup\u003e). For the oviposition bioassays, each yeast species was instead cultivated in CYM medium. Briefly, an overnight culture of 3 mL in CYM medium (28°C at 180 rpm) was used to inoculate 1L of fresh medium at a specific cell concentration (\u003cem\u003ei.e.\u003c/em\u003e, 3.10\u003csup\u003e2\u003c/sup\u003e and 3.10\u003csup\u003e5\u003c/sup\u003e cells.mL\u003csup\u003e− 1\u003c/sup\u003e). As previously mentioned, the lower concentration corresponded to the average natural densities observed in breeding-site waters based on plate counting, while the higher concentration represented 100 times these densities.\u003c/p\u003e\u003cp\u003e\u003cem\u003eSugar-feeding behavior experiments using locomotor activity monitoring systems.\u003c/em\u003e The impact of yeast species preferentially associated with the nectar of flowers visited by \u003cem\u003eAe. albopictus\u003c/em\u003e mosquitoes on their sugar-feeding behavior was evaluated using two Locomotor Activity Monitoring (LAM25) systems (Trikinetics Inc). As described by Giannoni-Guzmán et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), each LAM unit contains 32 independent activity channels. These channels detect mosquito movements using three infrared beams and multiple sensors to ensure accurate recordings (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). After 7 hours of starvation and cold anesthesia, each 5-day-old mosquito (\u003cem\u003ei.e.\u003c/em\u003e, 16 males and 16 females) was placed at one end of one of the 25 mm Ø glass tubes, near the plastic connector (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Mosquitoes had the choice between cotton impregnated with 1 mL of sterile Lamiaceae medium and cotton impregnated with 1 mL of the same medium inoculated with a specific yeast concentration (\u003cem\u003ei.e.\u003c/em\u003e, 5.10\u003csup\u003e3\u003c/sup\u003e or 5.10\u003csup\u003e5\u003c/sup\u003e cells.mL\u003csup\u003e− 1\u003c/sup\u003e), both placed at opposite ends of each tube. The cotton pads were placed as close as possible to the activity channels of both units to ensure that moving mosquitoes would come into contact with them (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Mosquitoes were left to rest for 15 min before their activity was measured. As previously described (Girard et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), the system was placed on a rolling support in a shaded area of the insectarium, as mosquitoes tend to prefer such environments in nature. The total activity measured with LAM systems can be mostly attributed to flight, as walking accounts for less than 20% of mosquito activity (Ziegler et al. \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). All experiments were conducted over 17 h (from 18h00 to 11h00 the following day) in a BSL2 insectary maintained at 26°C with an 18 h/6 h day/night cycle. Mosquito movements were recorded every two minutes.\u003c/p\u003e\u003cp\u003eChoice preference was evaluated based on the difference in the number of passes between the sterile medium and the yeast-inoculated medium. For each microbial species and cell concentration tested, 16 independent replicates were performed for both female and male mosquitoes. To avoid positional effects, the control and the microbial suspension were alternated between the two glass-tube assemblies. Individuals that died before the end of the recording were excluded from the final dataset.\u003c/p\u003e\u003cp\u003e\u003cem\u003eOviposition bioassays.\u003c/em\u003e The impact of different yeast species at two cell concentrations (\u003cem\u003ei.e.\u003c/em\u003e, 3.10\u003csup\u003e2\u003c/sup\u003e and 3.10\u003csup\u003e5\u003c/sup\u003e cells.mL\u003csup\u003e− 1\u003c/sup\u003e) on the oviposition behavior of 10-day-old gravid females was evaluated using two distinct and complementary laboratory bioassays, as previously described (Malassigné et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The oviposition-site selection bioassays (hereafter referred to as oviposition preference) consisted of three-choice tests in small cages, where a single gravid female could choose among three Double Beaker Systems (DBS) as oviposition sites: a control containing sterile water and CYM medium, and two others each containing water and medium inoculated with one of the two tested yeast concentrations. These DBS provide an oviposition substrate with waterborne deterrent or stimulant substances (sterile water, inoculated or not with yeasts), combined with attractive or repellent olfactory cues (volatile organic compounds emitted by sterile CYM medium or yeast cultures) for a single gravid female. These oviposition preference bioassays assessed the short-range attractiveness or repellency of volatile compounds emitted by yeasts. They were systematically paired with oviposition stimulation bioassays conducted in conical tubes, where a single gravid female was exposed to either sterile water or water inoculated with one of the two tested yeast concentrations. This pairing allowed evaluation of the stimulant or deterrent effects of yeast-derived waterborne substances. It is important to note that oviposition preference bioassays, when considered alone, do not allow distinguishing between the effects of stimulant or deterrent waterborne substances and those of attractant or repellent volatile compounds derived from yeasts. This limitation arises because gravid females are simultaneously exposed to both types of cues: oviposition substrates containing waterborne substances (sterile water or sterile water inoculated with yeasts) and olfactory stimuli (volatile organic compounds emitted by either sterile CYM medium or yeast cultures). The presence of attractant or repellent volatiles derived from yeasts can only be confirmed by comparing the total number of eggs laid in both control and yeast-inoculated conditions across the two bioassays (preference vs stimulation). This approach enables the evaluation of the short-range attractiveness or repellency of volatile compounds emitted by yeasts during oviposition preference bioassays.\u003c/p\u003e\u003cp\u003e\u003cem\u003eAnalysis of emitted volatile compounds.\u003c/em\u003e Volatile organic compounds emitted by yeast species that significantly impacted mosquito sugar-feeding and oviposition behavior were analyzed using an established protocol (Michalet et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Volatile compounds emitted by yeasts that were attractive to sugar-feeding mosquitoes (males and females), or either attractive or repellent to gravid females, were analyzed as follows. Each yeast species was cultured in 75 mL of Lamiaceae medium for sugar-feeding experiments or in CYM medium for oviposition assays, and incubated at 28°C with constant shaking (130 rpm) for 16 h to reach the exponential phase. Then, 250 mL Erlenmeyer flasks containing 100 mL of either sterile Lamiaceae or CYM medium, or the same media inoculated with these precultures at the behaviorally relevant cell concentrations, were incubated under the same conditions for 18 h. Five independent replicates were systematically performed for each tested condition (i.e., sterile medium or yeast culture). Yeast VOCs, as well as compounds emitted by the Lamiaceae or CYM medium, were extracted by HeadSpace-Solid Phase Micro-Extraction (HS-SPME) using 65 µm PMS/DVB Stable Flex™ fibers (Supelco). On the day of analysis, each 250 mL Erlenmeyer flask containing 100 mL of yeast culture or sterile medium was sealed with two layers of parafilm and incubated under constant agitation for 15 min at room temperature. Cleaned fibers, previously subjected to a blank GC run, were then introduced into the headspace of each 250 mL Erlenmeyer flask and left open for 30 min with constant agitation. After incubation, volatile compounds adsorbed on the fiber were immediately analyzed by GC-MS using a Hewlett-Packard 6890N gas chromatograph coupled to an HP 5973 mass spectrometer (Agilent Technologies) equipped with an Agilent DB-5MS column (60 m long, 0.25 mm in diameter, 0.25 µm film thickness). Helium was used as the carrier gas at a constant flow rate of 2.3 mL.min\u003csup\u003e− 1\u003c/sup\u003e (Agilent). The oven temperature program consisted of a 10°C.min\u003csup\u003e− 1\u003c/sup\u003e ramp from 50°C to 280°C. The ionization source was an electron impact at 70 eV and mass spectra were recorded between 35 and 600 m/z at 1.29 scans.s\u003csup\u003e− 1\u003c/sup\u003e. Emitted VOCs were manually integrated using the MassHunter software (Agilent) and aligned according to their retention time into a matrix. Medium related compounds were removed from the analysis. Key compounds were identified using NIST, Wiley, and aro.CRNS libraries, along with Kovats index calculation and manual interpretation of spectra.\u003c/p\u003e\u003cp\u003e\u003cem\u003eStatistical analysis.\u003c/em\u003e All statistical analyses were performed using R software version 4.2.0 and packages \u003cem\u003eade4\u003c/em\u003e, \u003cem\u003eMASS\u003c/em\u003e, \u003cem\u003eemmeans\u003c/em\u003e, \u003cem\u003eDHARMa\u003c/em\u003e, \u003cem\u003emixOmics\u003c/em\u003e, \u003cem\u003evegan\u003c/em\u003e, \u003cem\u003ecar\u003c/em\u003e, \u003cem\u003elem4\u003c/em\u003e and \u003cem\u003eglmmTMB\u003c/em\u003e (R core Team \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Fungal and yeast community dissimilarities among samples (\u003cem\u003ei.e\u003c/em\u003e., ß-diversity) were represented using the Bray-Curtis index in a non-metric multidimensional scaling (NMDS). The differences in the composition of fungal and yeast communities related to the sample categories (\u003cem\u003ei.e.\u003c/em\u003e, flowering plants and breeding-site waters) and the presence of \u003cem\u003eAe. albopictus\u003c/em\u003e mosquitoes (\u003cem\u003ei.e.\u003c/em\u003e, flower visited by adults and water colonized by larvae) were tested using a nonparametric permutation-based multivariate analysis of variance (PERMANOVA). The impact of nectar-dwelling yeast species and cell concentration on the sugar-feeding behavior of \u003cem\u003eAedes albopictus\u003c/em\u003e mosquitoes was analyzed using a generalized linear mixed model (GLMM) with quasi-Poisson distribution. In this model, the number of movements was set as the response variable, with mosquito sex, yeast species, and cell concentration as explanatory variables, and individual mosquito as a random variable. The influence of waterborne yeast species and cell concentration on oviposition preference was analyzed using a zero inflated GLMM with a negative binomial distribution. The impact of waterborne yeast species and cell concentration on oviposition stimulation was analyzed using a GLMM with a negative binomial distribution. In both GLMM models, the total number of eggs laid by each female was set as the response variable, with yeast species and its concentration as explanatory variables, and individual mosquito as a random variable. For each model, the contribution of explanatory variables was evaluated using type II ANOVA or Wald χ\u003csup\u003e2\u003c/sup\u003e. Subsequent, Tukey-HSD \u003cem\u003epost hoc\u003c/em\u003e tests were conducted to test pairwise differences between groups. Prior to this, the residuals of each model were verified for normality and variance homoscedasticity. To determine whether the composition of VOCs differed between attractive and repellent yeasts, a Heatmap was generated to illustrate the relative abundance of emitted compounds.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cem\u003eComposition of fungal and yeast communities associated with flowers and breeding-site waters according to their Aedes albopictus visitation or colonization status.\u003c/em\u003e A total of 130 flowering plants (ranging from 4 to 13 per garden), representing 53 species across 23 families, were collected from 14 community gardens (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). Lamiaceae and Asteraceae were the most abundant families, accounting for 26% and 18% of the collected flowering plants, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Species richness within these two families was relatively low, with \u003cem\u003eErigeron annuus\u003c/em\u003e and \u003cem\u003eGalinsoga parviflora\u003c/em\u003e each representing 26% of the Asteraceae, and \u003cem\u003eMentha spicata\u003c/em\u003e accounting for 44% of the collected Lamiaceae (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). Interestingly, mint species, including spearmint (\u003cem\u003eM. spicata\u003c/em\u003e), were present in 93% and 79% of the sampled gardens, respectively. Field observations showed that \u003cem\u003eAe. albopictus\u003c/em\u003e individuals systematically visited mint flowers during the sampling period (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). In contrast, no adult mosquitoes were observed on any of the other collected flowering plant species. Regarding breeding sites, whether colonized by \u003cem\u003eAe. albopictus\u003c/em\u003e larvae or not, the most common artificial containers sampled were plastic rainwater collectors (79%), followed by plastic buckets (14%), and plastic watering cans (4%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eYeast communities associated with these four sample categories (\u003cem\u003ei.e.\u003c/em\u003e, NV flowers, V flowers, NC waters, and C waters) were analyzed using both culture-based and high-throughput amplicon sequencing (fungal ITS-2 region) approaches. After removing plant sequences and normalizing to 4473 sequences per sample, the ITS-2 fungal dataset comprised 313,110 sequences representing 277 OTUs. The percentage of yeast sequences in this dataset did not significantly differ among sample categories (flowers vs waters; df\u0026thinsp;=\u0026thinsp;1, F\u0026thinsp;=\u0026thinsp;0.65, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.423) or presence of \u003cem\u003eAe. albopictus\u003c/em\u003e mosquitoes (NV vs V and NC vs C; df\u0026thinsp;=\u0026thinsp;1, F\u0026thinsp;=\u0026thinsp;0.63, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.429), with averages ranging from 26.36\u0026thinsp;\u0026plusmn;\u0026thinsp;16.99 for C waters to 37.39\u0026thinsp;\u0026plusmn;\u0026thinsp;29.90 for NV flowers (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNon-metric multidimensional scaling (NMDS) ordination based on Bray-Curtis distances showed that global fungal communities differed more between sample categories (\u003cem\u003ei.e\u003c/em\u003e., flowers vs waters) than within the same sample category differing in mosquito presence (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). A similar pattern was observed for yeast communities, with less separation between sample categories (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The difference in fungal and yeast composition, assessed through a permutational analysis of variance (PERMANONA), revealed the presence of significant variations between sample categories in terms of global fungal communities (df\u0026thinsp;=\u0026thinsp;1, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.080, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and yeast communities (df\u0026thinsp;=\u0026thinsp;1, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.043, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002). No noticeable difference was observed between samples with differential mosquito presence (df\u0026thinsp;=\u0026thinsp;1, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.015, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.261 for global fungal communities and df\u0026thinsp;=\u0026thinsp;1, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.022, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.062 for yeast communities). However, 89.2% of the variation in the global fungal communities and 91.9% of the variation in yeast communities were not attributed to any of these factors \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of fungal and yeast community composition across sample categories (flowers and breeding-site waters) and presence/absence of Ae. albopictus (visited and non-visited flowers or colonized and non-colonized waters).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"15\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eTotal fungal communities (Miseq)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e\u003cp\u003eYeast communities (Miseq)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c15\" namest=\"c12\"\u003e\u003cp\u003eCultivable yeast communities\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003edf \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eR\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003edf \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eR\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eF \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003edf \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eR\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003eF \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample category\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.080\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.968\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3.098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e3.334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAedes\u003c/em\u003e presence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.261\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.587\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e0.843\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e0.743\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample category x \u003cem\u003eAedes\u003c/em\u003e presence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.936\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.505\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0.315\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003e0.675\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u003cp\u003e0.953\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResiduals\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.892\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.919\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.955\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"15\" nameend=\"c15\" namest=\"c1\"\u003e\u003cp\u003eThe differences between groups were tested using PERMANOVA analysis and bold text represents the significative results (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e degree of freedom\u003c/p\u003e\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e statistics value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAmong the 277 OTUs, 79.1% (219 OTUs) were shared between flowers and breeding-site waters, while 11 were specific to flowers and 47 to waters (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). The OTUs specifically associated with flowers were primarily phytopathogenic fungi (\u003cem\u003ee.g.\u003c/em\u003e, \u003cem\u003eStemphylium\u003c/em\u003e sp., \u003cem\u003eRamularia cynarae\u003c/em\u003e, \u003cem\u003eAmpelomyces\u003c/em\u003e sp., \u003cem\u003eGolovinomyces\u003c/em\u003e_sp., and \u003cem\u003eParagibellulopsis chrysanthemi\u003c/em\u003e), although two yeast species (\u003cem\u003eRhodosporidiobolus\u003c/em\u003e sp., \u003cem\u003eRhodotorula babjevae\u003c/em\u003e) were also recorded. Regarding the 230 OTUs detected in flowers, only 10 were specifically associated with the visit of \u003cem\u003eAe. albopictus\u003c/em\u003e mosquitoes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Among them, two yeast species (\u003cem\u003eHyphopichia pseudoburtonii\u003c/em\u003e and \u003cem\u003eWickerhamomyces anomalus\u003c/em\u003e) and several filamentous fungi, including the mint pathogen \u003cem\u003ePuccinia menthae\u003c/em\u003e, were identified. Among the 266 OTUs detected in the breeding-site waters, only 20 were specifically associated with \u003cem\u003eAe. albopictus\u003c/em\u003e larval colonization (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Nearly all were filamentous fungi, including chytrids like \u003cem\u003eBetamyces\u003c/em\u003e sp., except for the yeast \u003cem\u003eDioszegia\u003c/em\u003e sp.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eYeast species accounted for 31% (86 OTUs) of this ITS-2 fungal dataset and were shared between the two sample categories (\u003cem\u003ei.e.\u003c/em\u003e, waters and flowers) at 91.9% (79 OTUs) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). The five most abundant yeast OTUs shared by all sample categories, regardless of the presence of \u003cem\u003eAe. albopictus\u003c/em\u003e mosquitoes, were \u003cem\u003eAureobasidium pullulans\u003c/em\u003e (19.5% of all yeast sequences), \u003cem\u003eVishniacozyma victoriae\u003c/em\u003e (10.8%), \u003cem\u003eRhodotorula glutinis\u003c/em\u003e (8.2%), \u003cem\u003eFilobasidium magnum\u003c/em\u003e (6%) and \u003cem\u003eBullera alba\u003c/em\u003e (5.5%). The culture-based approach yielded 383 isolates belonging to 78 different species. Only 14 species were simultaneously detected in both sample categories, while 23 and 41 species were specifically found in waters and flowers, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). The species shared by all sample categories, regardless the presence of \u003cem\u003eAe. albopictus\u003c/em\u003e mosquitoes, were \u003cem\u003eA. pullulans\u003c/em\u003e, \u003cem\u003eR. glutinis, Rhodotorula mucilaginosa\u003c/em\u003e, \u003cem\u003eHanseniaspora uvarum\u003c/em\u003e, and \u003cem\u003eMetschnikowia pulcherrima.\u003c/em\u003e Among the 23 waterborne species, 11 were specifically associated with \u003cem\u003eAe. albopictus\u003c/em\u003e larval colonization (\u003cem\u003ei.e., Candida\u003c/em\u003e sp., \u003cem\u003eClavispora lusitaniae, Cystobasidium\u003c/em\u003e sp., \u003cem\u003eGoffeauzyma gastrica, Kurtzmaniella quercitrusa, Lectera nordwiniana, Moesziomyces aphidis\u003c/em\u003e, \u003cem\u003ePichia kudriavzevii, Rhodotorula dairenensis, Rhodotorula kratochvilovae\u003c/em\u003e and \u003cem\u003eTilletiopsis washingtonensis\u003c/em\u003e). Among the 41 species detected in flowers, only 6 were specifically associated with the visit of \u003cem\u003eAe. albopictus\u003c/em\u003e mosquitoes (\u003cem\u003ei.e.\u003c/em\u003e, \u003cem\u003eCandida oleophila, Diutina catenulata, Meyerozyma caribbica, Pichia\u003c/em\u003e sp., \u003cem\u003eStarmerella caucasica\u003c/em\u003e and \u003cem\u003eTrichosporon aquatile\u003c/em\u003e). However, all these species were among the least abundant, representing less than 0.3% of the total observed colonies. The five most abundant yeast species were \u003cem\u003eF. magnum\u003c/em\u003e (28.8%), \u003cem\u003eMetschnikowia reukaufii\u003c/em\u003e (21%), \u003cem\u003eR. glutinis\u003c/em\u003e (12.8%) and \u003cem\u003eR. mucilaginosa\u003c/em\u003e (12%).\u003c/p\u003e\u003cp\u003eThe analysis of prevalence and abundance conducted on the cultivable yeast community highlighted a contrasting species composition between water and flower samples. Indeed, \u003cem\u003eM. reukaufii\u003c/em\u003e, \u003cem\u003eR. glutinis\u003c/em\u003e, and \u003cem\u003eF. magnum\u003c/em\u003e prevailed in NV and V flowers, while \u003cem\u003eR. mucilaginosa\u003c/em\u003e, \u003cem\u003ePapiliotrema laurentii\u003c/em\u003e, \u003cem\u003eCystobasidium slooffiae\u003c/em\u003e, \u003cem\u003eH. uvarum\u003c/em\u003e, and \u003cem\u003eTorulaspora delbrueckii\u003c/em\u003e dominated NC and C waters (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eExcept for \u003cem\u003ePichia kluyveri\u003c/em\u003e, which was only detected in NC waters, all dominant cultivable species were associated with both the presence and absence of \u003cem\u003eAe. albopictus\u003c/em\u003e larvae. However, on average, their cell concentrations significantly differed between NC and C water samples. For instance, \u003cem\u003eC. slooffiae\u003c/em\u003e and \u003cem\u003eR. mucilaginosa\u003c/em\u003e were found to be 18 and 4 times more abundant in C waters, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cb\u003eTable \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e). Conversely, the cellular concentrations of \u003cem\u003eH. uvarum, P. laurentii\u003c/em\u003e and \u003cem\u003eT. delbrueckii\u003c/em\u003e were 2 and 1.5 times higher in NC waters respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cb\u003eTable \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e). Similarly, NV and V flowers exhibited the same dominant yeast species but with contrasting cell concentrations. Indeed, while \u003cem\u003eM. reukaufii\u003c/em\u003e, \u003cem\u003eR. glutinis\u003c/em\u003e and \u003cem\u003eA. pullulans\u003c/em\u003e were found to be 4 and 3 times more abundant in V flowers (\u003cem\u003ei.e\u003c/em\u003e., mint flowers), \u003cem\u003eF. magnum\u003c/em\u003e were 15 times higher in NV flowers \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cb\u003eTable \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWhen examining the distribution of OTU sequences or cultivable species colonies across fungal phyla, both global fungal communities and cultivable yeast communities were dominated by Ascomycota (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Specifically, global fungal communities consisted of 62.62%, 64.69%, 64%, and 73.64% Ascomycota in NV, V, NC and C samples, respectively, and cultivable yeast communities comprised 52.14%, 66.23%, 51.40%, and 40.37% Ascomycota in these samples. Basidiomycota followed, making up 37.38%, 35.30%, 33.92% and 22,31% of global fungal communities, and 47.85%, 33.77%, 48.60%, and 59.63% of cultivable yeast communities in NV, V, NC and C, respectively. However, when focusing on the yeast fraction of the ITS-2 fungal dataset, Basidiomycota were notably predominant, comprising 70.61%, 67.67%, 87.42% and, 66.54% in NV, V, NC and C, respectively, compared to Ascomycota, which accounted for only 29.39%, 32.32%, 12.58%, and 33.45% in these samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBased on these observations, there appears to be a bias in the Miseq primers toward amplifying Basidiomycota yeasts, as evidenced by the absence of detection of \u003cem\u003eM. reukaufii\u003c/em\u003e, which is known to be abundant in flower nectars, as shown for the culture-based approach. The subsequent selection of yeast species, preferentially associated with V and NV flowers or C and NC waters, was therefore based on cultivable yeast communities to assess their impact on sugar-feeding and mosquito oviposition behavior, respectively. This choice was supported by the consistency between observations made in both culture-based and sequencing approaches. Indeed, both approaches showed that \u003cem\u003eC. slooffiae\u003c/em\u003e and \u003cem\u003eR. mucilaginosa\u003c/em\u003e were more abundant in C waters (\u003cem\u003ei.e.\u003c/em\u003e, 18 and 4 times for the culture-based approach, and 3 times for the sequencing approach), while \u003cem\u003eP. laurentii\u003c/em\u003e was more abundant in NC waters (\u003cem\u003ei.e.\u003c/em\u003e, 2 times for the culture-based and 8 times more for the sequencing approaches). Similarly, both approaches revealed that \u003cem\u003eR. glutinis\u003c/em\u003e and \u003cem\u003eA. pullulans\u003c/em\u003e were more abundant in V than in NV flowers (\u003cem\u003ei.e.\u003c/em\u003e, 4 and 3 times more for the culture-based approach, and 2 and 1.5 times for the sequencing approach). Thus, \u003cem\u003eM. reukaufii, R. glutinis\u003c/em\u003e, and \u003cem\u003eA. pullulans\u003c/em\u003e were selected as yeasts preferentially associated with V flowers (\u003cem\u003ei.e.\u003c/em\u003e, mint flowers), while \u003cem\u003eF. magnum\u003c/em\u003e was selected as a yeast species preferentially associated with NV flowers (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-B). Regarding breeding sites, \u003cem\u003eC. slooffiae\u003c/em\u003e and \u003cem\u003eR. mucilaginosa\u003c/em\u003e were selected as yeasts preferentially associated with C waters, and \u003cem\u003eH. uvarum, P. laurentii\u003c/em\u003e, \u003cem\u003eP. kluyveri\u003c/em\u003e, and \u003cem\u003eT. delbrueckii\u003c/em\u003e were selected as yeasts preferentially associated with NC waters (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC-D).\u003c/p\u003e\u003cp\u003e\u003cem\u003eNectar-dwelling yeasts and their associated emitted volatile compounds impact Ae. albopictus sugar-feeding preferences.\u003c/em\u003e The attractiveness of \u003cem\u003eM. reukaufii, R. glutinis, A. pullulans\u003c/em\u003e and \u003cem\u003eF. magnum\u003c/em\u003e at two cell concentrations (5.10\u003csup\u003e3\u003c/sup\u003e and 5.10\u003csup\u003e5\u003c/sup\u003e cells.ml\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) toward male and female mosquitoes was assessed using a dual locomotor activity monitoring (LAM25) system. Each individual mosquito (\u003cem\u003ei.e\u003c/em\u003e., 16 males or 16 females) was placed at the junction of two glass tubes offering a choice between a cotton soaked with a sterile Lamiaceae medium and cotton impregnated with the same medium inoculated with yeast at the specified concentration. These behavioral bioassays showed that the presence of \u003cem\u003eM. reukaufii\u003c/em\u003e significantly increased male visits at both low (df\u0026thinsp;=\u0026thinsp;Inf; z.ratio = -3.030; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) and high cell concentrations (df\u0026thinsp;=\u0026thinsp;Inf; z.ratio = -1.833; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043). In contrast, the presence of \u003cem\u003eA. pullulans\u003c/em\u003e significantly increased female visits but only at high cell concentration (df\u0026thinsp;=\u0026thinsp;Inf; z.ratio = -2.278; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e; \u003cb\u003eTable \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e\u003c/b\u003e). No attractiveness was observed for \u003cem\u003eR. glutinis\u003c/em\u003e, and as expected, \u003cem\u003eF. magnum\u003c/em\u003e did not attract male or female \u003cem\u003eAe. albopictus\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e; \u003cb\u003eTable \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe analysis of VOCs emitted by \u003cem\u003eM. reukaufii\u003c/em\u003e and \u003cem\u003eA. pullulans\u003c/em\u003e that significantly attracted male and female \u003cem\u003eAe. albopictus\u003c/em\u003e at high cell concentrations (i.e., 5.10\u003csup\u003e5\u003c/sup\u003e cells.mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), respectively, revealed distinct VOC profiles (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA). Of the nine detected compounds, eight were identified (\u003cb\u003eTable \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e\u003c/b\u003e). The nectar-specialist yeast \u003cem\u003eM. reukaufii\u003c/em\u003e emitted a greater diversity of VOCs compared to the generalist species \u003cem\u003eA. pullulans\u003c/em\u003e frequently isolated from nectar (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA). Indeed, \u003cem\u003eM. reukaufii\u003c/em\u003e specifically emitted four VOCs, namely 3-methyl-1-butanol acetate, 2-methyl-1-butanol acetate, ethyl acetate, and ethyl hexanoate \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Additionally, \u003cem\u003eM. reukaufii\u003c/em\u003e, which shared four VOCs with \u003cem\u003eA. pullulans\u003c/em\u003e, emitted these compounds at significantly higher concentrations (Wilcoxon rank sum exact test; W\u0026thinsp;=\u0026thinsp;0; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008). For instance, \u003cem\u003eM. reukaufii\u003c/em\u003e produced, on average, six times more 3-methyl-1-butanol and 16 times more 2-methyl-1-butanol than \u003cem\u003eA. pullulans\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eWaterborne yeasts with specific volatile profiles are impacting Ae. albopictus oviposition behavior.\u003c/em\u003e In a previous study, we have demonstrated that \u003cem\u003eR. mucilaginosa, H. uvarum\u003c/em\u003e and \u003cem\u003eT. delbrueckii\u003c/em\u003e, which differentially impact larval development, induced contrasting oviposition responses in \u003cem\u003eAe. albopictus\u003c/em\u003e females (Malassign\u0026eacute; et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In the present study, using the same experimental procedure, we compared \u003cem\u003eC. slooffiae\u003c/em\u003e to \u003cem\u003eR. mucilaginosa\u003c/em\u003e (two yeasts preferentially associated with C waters) as well as \u003cem\u003eP. laurentii\u003c/em\u003e and \u003cem\u003eP. kluyveri\u003c/em\u003e to \u003cem\u003eH. uvarum\u003c/em\u003e and \u003cem\u003eT. delbrueckii\u003c/em\u003e (four yeasts preferentially associated with NC waters). The impact of waterborne yeasts on gravid female oviposition behavior was then assessed through the same two distinct and complementary bioassays (\u003cem\u003ei.e.\u003c/em\u003e, oviposition preference and oviposition stimulation). These two bioassays differentiated attractant/repellent from stimulant/deterrent yeast effects. In the oviposition preference bioassay, conducted in cages, individual females chose among three oviposition sites (\u003cem\u003ei.e.\u003c/em\u003e, a yeast-free site, a site with 3.10\u003csup\u003e2\u003c/sup\u003e yeast cells.mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and a site with 3.10\u003csup\u003e5\u003c/sup\u003e yeast cells.mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). These sites provided both an oviposition substrate with potentially stimulant or deterrent waterborne substances and an olfactory stimulus acting as short-range attractant or repellent. Conversely, in oviposition stimulation bioassay, conducted in 50 mL tubes, each female was exposed only to stimulant or deterrent waterborne substances. Interestingly, all females laid eggs when \u003cem\u003eC. slooffiae\u003c/em\u003e and \u003cem\u003eR. mucilaginosa\u003c/em\u003e were present, while the percentage of females laying no eggs increased from 15.79\u0026ndash;42.11% in presence of \u003cem\u003eH. uvarum, T. delbrueckii, P. laurentii\u003c/em\u003e and \u003cem\u003eP. kluyveri\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eA). With 31.58% and 42.11%, \u003cem\u003eP. laurentii\u003c/em\u003e and \u003cem\u003eP. kluyveri\u003c/em\u003e showed the highest percentages of females that laid no eggs. Moreover, when \u003cem\u003eR. mucilaginosa, H. uvarum\u003c/em\u003e, and \u003cem\u003eC. slooffiae\u003c/em\u003e were present, individual females laid more eggs per cage compared to all other conditions, with averages of 42.11\u0026thinsp;\u0026plusmn;\u0026thinsp;15.51, 39.53\u0026thinsp;\u0026plusmn;\u0026thinsp;35.75, 34.79\u0026thinsp;\u0026plusmn;\u0026thinsp;21.66 eggs, respectively (\u003cb\u003eTable \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e). Conversely, \u003cem\u003eP. laurentii\u003c/em\u003e, \u003cem\u003eP. kluyveri\u003c/em\u003e, and \u003cem\u003eT. delbrueckii\u003c/em\u003e caused a significant reduction in the total number of eggs laid per cage, with averages of 14.42\u0026thinsp;\u0026plusmn;\u0026thinsp;21.25, 13.53\u0026thinsp;\u0026plusmn;\u0026thinsp;21.61, 10.43\u0026thinsp;\u0026plusmn;\u0026thinsp;14.08 eggs respectively (\u003cb\u003eTable \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e). Both oviposition bioassays showed that yeast species and their cell concentrations significantly influenced not only the selection of oviposition sites but also egg stimulation (\u003cb\u003eTable\u0026nbsp;3\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;3. Impact of yeast species on \u003cem\u003eAedes albopictus\u003c/em\u003e female oviposition behavior.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eOviposition preference (n\u0026thinsp;=\u0026thinsp;24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e\u003cp\u003eOviposition Stimulation (n\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVariable\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eFactor\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003edf\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eχ 2\u003c/b\u003e \u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003edf\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003eχ2\u003c/b\u003e \u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of eggs laid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYeast species\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e8.17e-07\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e14860.716\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;2.20e-16\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYeast concentration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17.073\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e12.246\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYeast conc. x Yeast sp.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.285\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e13.833\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003e0.181\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e\u003cp\u003eData from 24 or 25 independent replicates for each modality were analyzed using a Generalized Linear Mixed Model (GLMM) with a quasi-poisson distribution. Statistically significant differences between groups were identified with Tukey-HSD post hoc tests (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e degree of freedom\u003c/p\u003e\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e statistics value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhen exposed to highest concentrations (3.10\u003csup\u003e5\u003c/sup\u003e yeast cells.mL\u003csup\u003e-1\u003c/sup\u003e) of \u003cem\u003eR. mucilaginosa\u003c/em\u003e and \u003cem\u003eC. slooffiae\u003c/em\u003e, female mosquitoes laid significantly more eggs, with averages of 19.11\u0026thinsp;\u0026plusmn;\u0026thinsp;18.65 and 17.16\u0026thinsp;\u0026plusmn;\u0026thinsp;15.48 eggs per female, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eB; \u003cb\u003eTable \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e\u003c/b\u003e). The absence of egg stimulation at these cell concentrations suggests that these two yeasts, preferentially associated with C waters, attract gravid females at short-range distances (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA significant oviposition stimulation was observed for \u003cem\u003eH. uvarum\u003c/em\u003e at high cell concentrations (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eC; \u003cb\u003eTable \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e\u003c/b\u003e). However, at this concentration (3.10\u003csup\u003e5\u003c/sup\u003e yeast cells.mL\u003csup\u003e-1\u003c/sup\u003e), \u003cem\u003eH. uvarum\u003c/em\u003e resulted in a reduced number of eggs laid (on average, 16\u0026thinsp;\u0026plusmn;\u0026thinsp;18.23) and an increased proportion of females that did not lay eggs (15.79%) compared to \u003cem\u003eR. mucilaginosa\u003c/em\u003e and \u003cem\u003eC. slooffiae\u003c/em\u003e during oviposition preference bioassays. These findings suggest a short-range repellency effect of this yeast species, which was preferentially associated with NC waters. Regarding the other species preferentially associated with NC waters, no oviposition stimulation was observed for \u003cem\u003eP. laurentii\u003c/em\u003e and \u003cem\u003eP. kluyveri\u003c/em\u003e. The significant reduction in eggs laid at high concentrations (on average, 7.16\u0026thinsp;\u0026plusmn;\u0026thinsp;15.23 and 4.74\u0026thinsp;\u0026plusmn;\u0026thinsp;8.49, respectively) and the highest proportion of gravid females (31.58% and 42.11%) observed for \u003cem\u003eP. laurentii\u003c/em\u003e and \u003cem\u003eP. kluyveri\u003c/em\u003e during oviposition preference bioassays further emphasized the short-range repellency effect of both species. In contrast, at high cell concentrations, \u003cem\u003eT. delbrueckii\u003c/em\u003e acted as deterrent (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eC). The significant reduction in eggs laid (on average, 6.95\u0026thinsp;\u0026plusmn;\u0026thinsp;12.33) and the high proportion of gravid females (28.57%) that did not lay eggs in the presence of \u003cem\u003eT. delbrueckii\u003c/em\u003e during oviposition preference bioassays underscored a combination of short-range repellency and deterrence of this yeast species (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003eThe presumed attractive (\u003cem\u003eC. slooffiae, R. mucilaginosa\u003c/em\u003e) and repellent (\u003cem\u003eH. uvarum, P. laurentii\u003c/em\u003e, \u003cem\u003eP. kluyveri\u003c/em\u003e and \u003cem\u003eT. delbrueckii\u003c/em\u003e) yeasts at high cell concentrations (\u003cem\u003ei.e\u003c/em\u003e., 3.10\u003csup\u003e5\u003c/sup\u003e cells.mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) showed two contrasting VOC profiles. Of the 22 detected compounds, 19 were identified (\u003cb\u003eTable \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e), and repellent yeasts emitted a greater richness of VOCs compared to attractive yeasts. Indeed, only three compounds (\u003cem\u003ei.e.\u003c/em\u003e, 3-methyl-1-butanol, 2-methyl-1-butanol and 2,4,4,6,6,8,8-Heptamethyl-2-nonene) were shared between repellent and attractive yeasts. Conversely, several compounds (\u003cem\u003ei.e.\u003c/em\u003e, ethanol, 3-methyl-1-butanol acetate, 2-methyl-1-butanol acetate, ethyl acetate, ethyl propionate or ethyl octanoate) were specifically produced by repellent yeasts (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eA). Finally, two compounds were produced by both yeast categories (the alcohols 3-methyl-1-butanol and 2-methyl-1-butanol), but at significantly higher concentrations for repellent ones (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eB). With the exception of ethanol production, \u003cem\u003eP. laurentii\u003c/em\u003e displayed a VOC profile similar to that of attractive yeasts (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this study, we characterized for the first time the yeast communities preferentially associated with plants visited or not by \u003cem\u003eAe. albopictus\u003c/em\u003e adults, as well as with breeding-site waters colonized or not by this species, using both culture-based and sequencing approaches. We also evaluated the impact of selected cultivable yeast species on nectar seeking and oviposition behaviors and characterized their emitted VOCs. While molecular or biochemical approaches, such as \u003cem\u003erbcL\u003c/em\u003e gene amplification and sequencing from DNA extracted from mosquito guts (Upshur et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Cassone et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) or the analysis of ingested plant secondary metabolites (Cooper et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) offer valuable insights into flower visitation, we based our study on visual inspections during the sampling period. This method, based on the presence or absence of adult mosquitoes on flowers and larvae in breeding-site waters, allowed us to link yeast community composition to real-time mosquito activity under natural conditions. Only mint flowers, found in 93% of the sampled gardens, were observed to be visited by \u003cem\u003eAe. albopictus\u003c/em\u003e mosquitoes during the sampling period. This observation is consistent with the preference of \u003cem\u003eAedes\u003c/em\u003e mosquitoes for colorful flowers, including purple ones such as \u003cem\u003eBuddleja davidii\u003c/em\u003e and \u003cem\u003eVitex agnus-castus\u003c/em\u003e (M\u0026uuml;ller et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Dieng et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Moreover, Davis et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) showed that \u003cem\u003eAe. albopictus\u003c/em\u003e lays significantly more eggs in containers adjacent to flowering butterfly bushes than in those without one.\u003c/p\u003e\u003cp\u003eThe proportion of yeast sequences within the total fungal communities did not differ significantly between flowers and breeding-site waters, despite previous studies indicating that floral nectar often harbors high yeast cell densities, ranging from 10\u003csup\u003e3\u003c/sup\u003e to 10\u003csup\u003e5\u003c/sup\u003e cells/mm\u003csup\u003e3\u003c/sup\u003e (Herrera et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Pozo et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This unexpected result may be explained by two main factors. Although the fungal primers used for the Miseq sequencing approach are currently among the most effective for amplifying fungal communities, including a broad range of yeast species, and are designed to minimize the amplification of plant sequences while avoiding mosquito DNA (Ihrmark et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Luis et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), they still amplified a large number of sequences from herbaceous plants. Moreover, they failed to amplify certain nectar-dwelling yeasts, such as \u003cem\u003eM. reukaufii\u003c/em\u003e, a nectar specialist known to be the most prevalent and abundant yeast in floral nectar (Pozo et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Glushakova et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). These limitations may have led to an underestimation of yeast diversity and abundance in nectar samples. Interestingly, using culture-based approaches, we identified \u003cem\u003eM. reukaufii\u003c/em\u003e as the most abundant and prevalent yeast species in the nectar of the collected plants. Our study showed that fungal communities in \u003cem\u003eAe. albopictus\u003c/em\u003e aquatic habitats are predominantly composed of \u003cem\u003eAscomycota\u003c/em\u003e species, consistent with their known prevalence in freshwater ecosystems (El-Elimat et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), including mosquito breeding sites (Zouache et al. \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tawidian et al. \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and in line with previous findings (Tawidian et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Duval et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). A similar pattern was observed for the cultivable fraction of the yeast communities, except in colonized breeding-site waters, where two basidiomycetous yeast species (\u003cem\u003eR. mucilaginosa\u003c/em\u003e and \u003cem\u003eC. slooffiae\u003c/em\u003e) were the most prevalent and abundant.\u003c/p\u003e\u003cp\u003eFungal and yeast communities, as well as the culturable subset of the latter, exhibited significant variation between sample categories (\u003cem\u003ei.e.\u003c/em\u003e, flowers vs breeding-site waters), but not within the same category based on mosquito presence. Differences in yeast communities between larval habitats and flowers likely result from contrasting physicochemical conditions. Variations in carbon source type and concentration, pH, osmotic conditions, and nitrogen availability strongly shape the yeast species able to thrive in each environment (Venjakov et al. 2022; Duval et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The absence of significant differences in bacterial and fungal communities between breeding sites colonized and non-colonized by \u003cem\u003eAe. albopictus\u003c/em\u003e had already been observed in a larger number of containers sampled across various community gardens in the Lyon metropolitan area (Duval et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The variations in fungal and yeast community composition between flowers and breeding-site waters were primarily driven by differences in species abundances, as evidenced by the high percentages of shared OTUs (79.1% and 91.9% respectively). In line with this observation, the culture-based approach showed that \u003cem\u003eM. reukaufii\u003c/em\u003e, \u003cem\u003eR. glutinis\u003c/em\u003e, \u003cem\u003eF. magnum\u003c/em\u003e and to a lesser extend \u003cem\u003eA. pullulans\u003c/em\u003e prevailed in flowers, while \u003cem\u003eR. mucilaginosa\u003c/em\u003e, \u003cem\u003eP. laurentii\u003c/em\u003e, \u003cem\u003eC. slooffiae\u003c/em\u003e, \u003cem\u003eH. uvarum\u003c/em\u003e, and \u003cem\u003eT. delbrueckii\u003c/em\u003e dominated breeding-site waters. Interestingly, the nectar specialist \u003cem\u003eM. reukaufii\u003c/em\u003e and the two generalist species \u003cem\u003eA. pullulans\u003c/em\u003e and \u003cem\u003eF. magnum\u003c/em\u003e were often found prevalent and abundant in floral nectars (Pozo et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Sobhy et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Agarbati et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Among isolated yeasts, \u003cem\u003eR. mucilaginosa\u003c/em\u003e and \u003cem\u003eC. slooffiae\u003c/em\u003e are classified as aquatic yeasts due to their remarkable ability to survive in fresh or marine water (Gon\u0026ccedil;alves et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Libkind et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Furthermore, \u003cem\u003eR. mucilaginosa, A. pullulans\u003c/em\u003e, \u003cem\u003eH. uvarum\u003c/em\u003e and \u003cem\u003eT. delbrueckii\u003c/em\u003e has already been found to be associated with breeding-site waters and larvae from \u003cem\u003eAe. albopictus\u003c/em\u003e (Hegde et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Malassign\u0026eacute; et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The high percentages of shared yeast OTUs between flowers and breeding-site waters, along with the presence of two generalist species frequently isolated from nectar (\u003cem\u003eA. pullulans\u003c/em\u003e and \u003cem\u003eF. magnum\u003c/em\u003e) among the five most abundant taxa, suggest that adult mosquitoes, including gravid females, contribute to shaping yeast communities in breeding-site waters by introducing species during oviposition, defecation or death, as previously demonstrated for adult-associated bacteria (Mosquera et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This hypothesis is further supported by the frequent detection of \u003cem\u003eA. pullulans\u003c/em\u003e in female mosquitoes, as this species was detected in 90.5% of specimens collected in France, Madagascar, and Vietnam (Luis et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, the contribution of other dissemination sources such as pollen, around which nectar yeasts commonly aggregate, cannot be excluded at this stage (Pozo and Jacquemyn \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSince \u003cem\u003eM. reukaufii\u003c/em\u003e, \u003cem\u003eR. glutinis\u003c/em\u003e, \u003cem\u003eF. magnum\u003c/em\u003e and \u003cem\u003eA. pullulans\u003c/em\u003e were preferentially associated with the visited mint flowers (\u003cem\u003ei.e.\u003c/em\u003e, higher cell concentrations), we evaluated their impact on mosquito nectar-seeking preferences. To our knowledge, the study by Peach et al. (\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) is the only research linking VOCs produced by nectar-dwelling microorganisms to mosquito attractiveness. They demonstrated that the yeast \u003cem\u003eLachancea thermotolerans\u003c/em\u003e produces volatile compounds (hexanoic acid, dimethyl trisulfide, 2-phenyl ethanol, benzyl alcohol) that significantly attract female \u003cem\u003eCulex pipiens\u003c/em\u003e mosquitoes. This yeast species, which appears to be absent from the nectar of flowers collected on the Eurasian continent (Pozo et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Glushakova et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), was not detected in our samples. Our results showed that, regardless of yeast cell concentration, the nectar specialist \u003cem\u003eM. reukaufii\u003c/em\u003e significantly attracted \u003cem\u003eAe. albopictus\u003c/em\u003e males, whereas the generalist species frequently isolated from nectar \u003cem\u003eA. pullulans\u003c/em\u003e significantly attracted \u003cem\u003eAe. albopictus\u003c/em\u003e females, but only at high cell concentration. This attraction of females by \u003cem\u003eA. pullulans\u003c/em\u003e may help explain its high prevalence in field-collected individuals (Luis et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The nectar specialist \u003cem\u003eM. reukaufii\u003c/em\u003e, which heavily relies on insects for dispersal and colonization of new habitats (Sobhy et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), is known to significantly increase nectar temperature (Herrera and Pozo \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), potentially benefiting foraging insects by reducing viscosity and facilitating sugar intake (Nicolson et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), while maintaining a chemical composition that supports insect longevity, survival and reproduction (Sobhy et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). As these nectar specialists are specifically adapted to the physicochemical conditions of nectar, including high osmotic pressure, high sugar concentration and low nitrogen availability, they are unable to grow in other environments such as water (Sobhy and Berry \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Thus, \u003cem\u003eM. reukaufii\u003c/em\u003e has been shown to produce the most attractive volatile blends among the microorganisms tested, attracting a wide range of insect pollinators, including \u003cem\u003eAphidius\u003c/em\u003e parasitoids, honeybees, and several bumblebee species (Schaeffer et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Rering et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sobhy et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In contrast, \u003cem\u003eA. pullulans\u003c/em\u003e is a generalist species frequently isolated from nectar, capable of colonizing a wide range of habitats and thus less dependent on insects for dispersal and survival (Wehner et al. \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Sobhy et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This species produces distinct volatile blends and tends to lower nectar quality by strongly reducing pH, decreasing sucrose concentration in favor of monosaccharides, and altering the amino acid profile (Sobhy et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These changes can lead to reduced nectar consumption and shortened lifespan, resulting in lower attractiveness compared to \u003cem\u003eM. reukaufii\u003c/em\u003e in some pollinator species, and even aversive responses in honeybees (Rering et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sobhy et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Crowley-Gall et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Our results revealed sex-specific responses in \u003cem\u003eAe. albopictus\u003c/em\u003e, likely linked to differences in nutritional requirements and reliance on sugar meals for survival between males and females (M\u0026uuml;ller et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Bellini et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Naziri et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). By attracting males, which visit flowers more frequently than females due to their higher dependence on sugar meals for survival, \u003cem\u003eM. reukaufii\u003c/em\u003e could benefit from enhanced dispersal. In contrast, the generalist species \u003cem\u003eA. pullulans\u003c/em\u003e, frequently isolated from flowers and known to inhabit diverse environments with less dependence on insect pollinators for dispersal and survival, may nonetheless facilitate colonization of a wide range of aquatic habitats by attracting females that exhibit skip oviposition behavior (\u003cem\u003ei.e.\u003c/em\u003e, they lay eggs in multiple containers) once gravid (Reinbold-Wasson and Reiskind 2018). Interestingly, \u003cem\u003eM. reukaufii\u003c/em\u003e and \u003cem\u003eA. pullulans\u003c/em\u003e produced contrasting VOC profiles, with \u003cem\u003eM. reukaufii\u003c/em\u003e emitting higher amounts of four shared compounds (\u003cem\u003ei.e.\u003c/em\u003e, 3-methyl-1-butanol, ethanol, 2-methyl-1-butanol and isobutyl alcohol) as well as four additional compounds (\u003cem\u003ei.e.\u003c/em\u003e, 3-methyl-1-butanol acetate, 2-methyl-1-butanol acetate, ethyl hexanoate and ethyl acetate). By emitting a wide range of VOCs, including large quantities of ethanol and 2-methyl-1-butanol, followed by 2-methyl-1-propanol (isobutyl alcohol), 2-phenylethanol and ethyl acetate, \u003cem\u003eM. reukaufii\u003c/em\u003e has been shown to attract bumblebee species and several others pollinators (Sobhy et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Schaeffer et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Yang et al. \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In contrast, and consistent with our results, \u003cem\u003eA. pullulans\u003c/em\u003e was demonstrated to produce a lower diversity of VOCs, including 3-methyl-1-butanol, 2-methyl-1-butanol and 2-phenylethanol, which strongly attract dipterans, particularly hoverflies (Davis and Landolt \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSince mosquito larvae are gregarious and incapable of relocating between habitats, they cannot escape unfavorable conditions. As a result, female oviposition choices are often driven by the need to optimize offspring performance (Girard et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Recently, we showed that yeasts like \u003cem\u003eR. mucilaginosa\u003c/em\u003e and \u003cem\u003eA. pullulans\u003c/em\u003e, which promote rapid larval development by providing high riboflavin intake and enhancing nitrogenous waste recycling, significantly attract gravid \u003cem\u003eAe. albopictus\u003c/em\u003e females (Malassign\u0026eacute; et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In contrast, yeasts such as \u003cem\u003eM. asiatica\u003c/em\u003e and \u003cem\u003eT. delbrueckii\u003c/em\u003e, which lack these capabilities are repellent (Malassign\u0026eacute; et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Interestingly, \u003cem\u003eR. mucilaginosa\u003c/em\u003e and \u003cem\u003eT. delbrueckii\u003c/em\u003e were preferentially associated with colonized and non-colonized breeding-site waters, respectively. In this study, we compared yeasts from these two habitats (\u003cem\u003eC. slooffiae\u003c/em\u003e to \u003cem\u003eR. mucilaginosa\u003c/em\u003e in colonized waters, and \u003cem\u003eP. laurentii\u003c/em\u003e, \u003cem\u003eP. kluyveri\u003c/em\u003e to \u003cem\u003eH. uvarum\u003c/em\u003e and \u003cem\u003eT. delbrueckii\u003c/em\u003e in non-colonized waters) for their impact on female oviposition behavior and VOC profiles. Interestingly, similar to \u003cem\u003eR. mucilaginosa\u003c/em\u003e, \u003cem\u003eC. slooffiae\u003c/em\u003e significantly attracted gravid females at a high cell concentration without stimulating oviposition. Unlike \u003cem\u003eT. delbrueckii\u003c/em\u003e, which acted as both a deterrent and a repellent at high cell concentrations, \u003cem\u003eP. laurentii\u003c/em\u003e, \u003cem\u003eP. kluyveri\u003c/em\u003e and \u003cem\u003eH. uvarum\u003c/em\u003e only exhibited strong repellent effects against gravid females. Interestingly, with the exception of \u003cem\u003eP. laurentii\u003c/em\u003e, the VOC profiles emitted by attractive yeasts (\u003cem\u003eR. mucilaginosa\u003c/em\u003e and \u003cem\u003eC. slooffiae\u003c/em\u003e) differed from those of repellent ones (\u003cem\u003eH. uvarum\u003c/em\u003e, \u003cem\u003eP. kluyveri\u003c/em\u003e and \u003cem\u003eT. delbrueckii\u003c/em\u003e). Repellent yeasts emitted a greater diversity of VOCs compared to attractive ones. Among these specific VOCs, certain compounds such as the ethyl octanoate have been demonstrated to induce ovipositional repellency towards \u003cem\u003eCulex quinquefasciatus\u003c/em\u003e (Hwang et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1982\u003c/span\u003e). Moreover, the two main volatile compounds (\u003cem\u003ei.e.\u003c/em\u003e, 3-methyl-1-butanol and 2-methyl-1-butanol), shared by both attractive and repellent yeasts were emitted at higher concentrations by the repellent ones. These compounds, when present in microbial volatile blends, have been associated with notable attractiveness for host-seeking mosquitoes (Verhulst et al. \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Mukabana et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Michalet et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and gravid females searching for oviposition sites (Lindh et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Malassign\u0026eacute; et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, high concentrations of these compounds within such blends have also been shown to induce repellency (Verhulst et al. \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Mukabana et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Malassign\u0026eacute; et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This observation highlights the critical need to carefully manage the concentration of these VOCs when considering the use of these yeasts as attractants. Therefore, understanding the precise balance between the concentration and the repellent/attractive properties of VOCs is essential for optimizing their application in mosquito control strategies. Following the work of Aldridge et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), our study shows that repellent yeasts emit more complex VOC profiles, characterized by the presence of specific repellent compounds and attractive volatiles that shift to repellency at high concentrations. Furthermore, we observed differential responses between females and males based on the overall VOC profiles, with both nectar-seeking and gravid females responding positively to cues characterized by lower VOC diversity and abundance. Such a pattern has been already observed for host-seeking \u003cem\u003eAedes\u003c/em\u003e females (Lucas-Barbosa et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Bourne et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Malassign\u0026eacute; et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This could partly be explained by sexual dimorphisms observed in mosquitoes, where females possess three to four times more antennal (mostly olfactory) sensilla than males (Wooding et al. \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study expands our understanding of the chemical ecology underlying mosquito-environment associations, particularly regarding the microbial cues shaping the behavioral responses of the Asian tiger mosquito across different life stages. Advancing research on how environmental microbial communities influence mosquito feeding and oviposition behaviors could guide the development of more efficient vector control strategies. This study highlights the role of two nectar-dwelling yeasts, \u003cem\u003eM. reukaufii\u003c/em\u003e and \u003cem\u003eA. pullulans\u003c/em\u003e, in attracting male and female \u003cem\u003eAe. albopictus\u003c/em\u003e mosquitoes through the emission of specific VOCs, including 3-methyl-1-butanol, ethanol, 2-methyl-1-butanol, and isobutyl alcohol. It also showed that some waterborne yeasts, such as \u003cem\u003eC. slooffiae\u003c/em\u003e and \u003cem\u003eR. mucilaginosa\u003c/em\u003e, which are preferentially associated with colonized breeding-site waters, attract gravid females. This attraction is linked to the emission of volatile blends characterized by lower VOC richness and reduced concentrations of 3-methyl-1-butanol and 2-methyl-1-butanol. These findings contribute to the growing body of evidence identifying microbial VOCs as key mediators of mosquito attraction during both sugar-seeking and oviposition behaviors. While current trapping strategies mainly focus on mimicking human odors to target host-seeking females, our results emphasize the importance of broadening the chemical spectrum considered in vector control to include cues relevant to other critical mosquito behaviors, such as nectar foraging and oviposition. The inclusion of yeast-emitted kairomones into odor-baited traps could enhance the capture of males and newly emerged females searching for sugar, potentially leading to greater population reduction. Given the repeated implication of compounds such as 3-methyl-1-butanol and 2-methyl-1-butanol in multiple behavioral contexts (\u003cem\u003ei.e.\u003c/em\u003e, host seeking, nectar foraging, and oviposition), further investigation into their ecological relevance and potential synergistic effects is warranted. However, when targeting nectar-seeking insects, it is essential to identify specific compounds and concentrations that effectively attract mosquitoes without drawing in non-target species, such as pollinators like bees and bumblebees. Finally, seasonal shifts in floral resource availability may influence mosquito nectar preferences over time, suggesting that future studies should also consider the temporal dynamics of mosquito\u0026ndash;microbe\u0026ndash;plant interactions to optimize the deployment of VOC-based trapping tools.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eACKNOWLEDGEMENTS\u003c/p\u003e\n\u003cp\u003eWe thank the CESN platform (University of Lyon, France) for providing access to the\u0026nbsp;HS-SPME/GC-MS\u0026nbsp;as well as for their valuable advice and discussions. We thank the IBIO platform (University of Lyon, France), and especially Danis Abrouk, for their advice and assistance with the analysis and submission of the MiSeq sequences. We would like to thank Christophe Bellet and Yves Rozier from the EID Rhône-Alpes for pointing out the locations with breeding sites specifically colonized by \u003cem\u003eAedes albopictus\u003c/em\u003e larvae.\u003c/p\u003e\n\u003cp\u003eFUNDING\u003c/p\u003e\n\u003cp\u003eS. Malassigné PhD was supported by a Research and Technology French National association ANRT and Dipteratech fellowship. Funding for this project was provided by The French National Research Program for Environmental and Occupational Health of Anses (ANSES-21-EST-018). This study was also partially funded by the French National program EC2CO (Ecosphère Continentale et Côtière).\u003c/p\u003e\n\u003cp\u003eCONFLICT OF INTEREST STATEMENT\u003c/p\u003e\n\u003cp\u003eAll authors have approved the final version of this manuscript. One author declares the following financial interest, which may be considered a potential competing interest: S.M. was employed by Dipteratech during the course of his PhD. All other authors declare no competing interests and received no financial compensation from Dipteratech.\u003c/p\u003e\n\u003cp\u003eDATA AVAILABILITY STATEMENT\u003c/p\u003e\n\u003cp\u003eThe ITS and LSU D1/D2 region sequences of yeast ribosomal DNA have been deposited in GenBank under the accession numbers PV471497 -\u0026nbsp;PV471565\u0026nbsp;and PV471566 -\u0026nbsp;PV471574, while the FastQ files are available under the project accession number PRJEB85671. All analysis codes and formatted data were deposited in the following site: https://zenodo.org/records/14723343.\u003c/p\u003e\n\u003cp\u003eAUTHOR CONTRIBUTIONS\u003c/p\u003e\n\u003cp\u003eAll authors contributed intellectually to and agreed to this submission. S.M., C.V.M. and P.L. designed the experiments. P.L., P.D. and P.A. collected the field samples. S.M., L.V., E.M., G.M.E. and P.L. conducted the experiments and collected the data. S.M., L.V. and G.M. analyzed the data and made statistical analyses. S.M. and P.L. wrote the initial draft of the manuscript. The authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbarenkov K, Nilsson RH, Larsson KH, Taylor AFS, May TW, Fr\u0026oslash;slev TG, Pawlowska J, Lindahl B, P\u0026otilde;ldmaa K, Truong C, Vu D, Hosoya T, Niskanen T, Piirmann T, Ivanov F, Zirk A, Peterson M, Cheeke TE, Ishigami Y, Jansson AT, Jeppesen TS, Kristiansson E, Mikryukov V, Miller JT, Oono R, Ossandon FJ, Paup\u0026eacute;rio J, Saar I, Schigel D, Suija A, Tedersoo L, K\u0026otilde;ljalg U (2024) The UNITE database for molecular identification and taxonomic communication of fungi and other eukaryotes: sequences, taxa and classifications reconsidered. 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FEMS Microbiol Ecol 98:fiac016. https://doi.org/10.1093/femsec/fiac016.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-chemical-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joce","sideBox":"Learn more about [Journal of Chemical Ecology](https://www.springer.com/journal/10886)","snPcode":"10886","submissionUrl":"https://submission.nature.com/new-submission/10886/3","title":"Journal of Chemical Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Aedes albopictus, breeding-site waters, wild and ornamental flowers, yeast communities, volatile organic compounds, nectar-seeking and oviposition behavior","lastPublishedDoi":"10.21203/rs.3.rs-7258136/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7258136/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eVolatile organic compounds (VOCs) emitted by floral scents and waterborne microorganisms can influence mosquito behavior. However, the role of nectar-dwelling yeasts and their VOCs in mosquito nectar seeking behavior, compared to waterborne microorganisms influencing oviposition, remains underexplored. To investigate this in \u003cem\u003eAedes albopictus\u003c/em\u003e, a species well adapted to urban environments, we characterized yeast communities from visited and non-visited flowers, as well as from colonized and non-colonized breeding-site waters in urban community gardens. We identified yeast species and their associated VOCs involved in mosquito behavioral responses. Yeast communities differed between floral and aquatic habitats, although several taxa, including generalist species frequently isolated from nectar, were shared between both environments, likely through insect transmission or pollen dissemination. Two nectar-dwelling yeasts, \u003cem\u003eMetschnikowia reukaufii\u003c/em\u003e and \u003cem\u003eAureobasidium pullulans\u003c/em\u003e, attracted males and females through the emission of 3-methyl-1-butanol, ethanol, 2-methyl-1-butanol, and isobutyl alcohol, respectively. In contrast, two waterborne yeasts, \u003cem\u003eCystobasidium slooffiae\u003c/em\u003e and \u003cem\u003eRhodotorula mucilaginosa\u003c/em\u003e, which were preferentially associated with colonized breeding sites, attracted gravid females and produced blends characterized by lower VOC richness and reduced concentrations of 3-methyl-1-butanol and 2-methyl-1-butanol. These results highlight the importance of yeast-emitted VOCs as semiochemicals guiding nectar feeding and oviposition in mosquitoes and call for further investigation into their ecological relevance.\u003c/p\u003e","manuscriptTitle":"Characterization of Volatile Organic Compounds from Waterborne and Nectar-Dwelling Yeasts Attractive to Asian Tiger Mosquitoes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-08 13:15:59","doi":"10.21203/rs.3.rs-7258136/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-31T21:19:33+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-27T08:56:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-19T15:14:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"286522613560277141742655581512668077957","date":"2025-08-13T15:03:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33073898941146406044836353831102511368","date":"2025-08-04T14:34:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-03T18:06:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-02T16:18:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-01T07:06:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Chemical Ecology","date":"2025-07-31T05:06:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-chemical-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joce","sideBox":"Learn more about [Journal of Chemical Ecology](https://www.springer.com/journal/10886)","snPcode":"10886","submissionUrl":"https://submission.nature.com/new-submission/10886/3","title":"Journal of Chemical Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ed5c3eab-3d8d-4e3f-a0cd-c739327df596","owner":[],"postedDate":"August 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:02:04+00:00","versionOfRecord":{"articleIdentity":"rs-7258136","link":"https://doi.org/10.1007/s10886-025-01685-0","journal":{"identity":"journal-of-chemical-ecology","isVorOnly":false,"title":"Journal of Chemical Ecology"},"publishedOn":"2026-01-09 15:57:39","publishedOnDateReadable":"January 9th, 2026"},"versionCreatedAt":"2025-08-08 13:15:59","video":"","vorDoi":"10.1007/s10886-025-01685-0","vorDoiUrl":"https://doi.org/10.1007/s10886-025-01685-0","workflowStages":[]},"version":"v1","identity":"rs-7258136","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7258136","identity":"rs-7258136","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}