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Vector Signals

Vector Signals

著者： Maddy Chang McDonough
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 A private, AI-curated podcast delivering 15-20 minute deep dives into the latest Nature articles on mosquito-borne viruses and AI-driven therapeutic breakthroughs. Designed for the researchers of the Saleh Lab at Institut Pasteur, each episode distills cutting-edge science into accessible insights—so you can stay current, even during your busiest bench days.© 2025 Maddy Chang McDonough 生物科学 科学
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  • Medfly Gut Microbiota and Insecticide Resistance (September 2025)

    Medfly Gut Microbiota and Insecticide Resistance (September 2025)
    2025/10/01
    Gut Microbiota and Insecticide Resistance in the Mediterranean Fruit Fly (Ceratitis capitata)Source: Charaabi, K., Hamdene, H., Djobbi, W. et al. Assessing gut microbiota diversity and functional potential in resistant and susceptible strains of the mediterranean fruit fly. Sci Rep 15, 33456 (2025). https://doi.org/10.1038/s41598-025-01534-wDates: Received - 06 November 2024 | Accepted - 06 May 2025 | Published - 29 September 2025Executive SummaryThis briefing document synthesizes findings from a study investigating the link between gut microbiota and insecticide resistance in the Mediterranean fruit fly (Ceratitis capitata), a destructive agricultural pest. The research reveals a strong correlation between resistance to common insecticides (malathion, dimethoate, and spinosad) and significant alterations in the composition and functional potential of the fly's gut bacterial community.Resistant strains of the medfly, developed over 36 generations of insecticide exposure, exhibit significantly lower microbial diversity compared to their susceptible counterparts. This reduction in diversity is accompanied by a profound shift in the gut's bacterial landscape. Specifically, the phylum Bacillota and the genera Enterococcus and Klebsiella are substantially enriched in resistant flies. Conversely, the dominant phylum Pseudomonadota and the genera Serratia and Buttiauxella are sharply reduced.Functional analysis predicts that the gut microbiota of resistant flies possess enhanced metabolic capabilities for xenobiotic biodegradation. These enriched pathways are associated with the breakdown of various toxic environmental chemicals, suggesting a direct or indirect role in insecticide detoxification. The findings indicate that symbiont-mediated resistance is likely a key mechanism in the medfly, driven by the synergistic effect of multiple bacterial species rather than a single microbe. This research opens new avenues for pest management strategies that could target the gut microbiome to mitigate insecticide resistance.Background and Research ObjectivesThe Mediterranean fruit fly (Ceratitis capitata), or medfly, is a highly polyphagous pest that infests over 300 plant species, causing billions of dollars in annual economic losses worldwide. These losses stem from reduced agricultural production, costly control measures, and restricted market access. While methods like the Sterile Insect Technique (SIT) are used, the predominant control practice remains the application of chemical insecticides.The widespread and excessive use of insecticides has led to the development of significant resistance in medfly populations, undermining control efforts. While resistance is often linked to genetic traits in the insect, such as increased enzyme activity, recent evidence from other species suggests that symbiotic gut microorganisms can play a crucial role. These bacteria may contribute to resistance by directly metabolizing toxic substances or by modulating the host's detoxification gene expression.Despite extensive research on the medfly's gut microbiota in relation to its fitness and SIT applications, the connection to insecticide resistance has remained largely unexplored. This study aimed to address this gap by investigating the potential association between the medfly gut microbiota and insecticide resistance. The primary objectives were to:Characterize and compare the gut microbiota community structure between insecticide-susceptible (IS) and insecticide-resistant (IR) strains of the medfly.Identify specific bacterial taxa that correlate with resistance phenotypes.Predict the functional differences between the microbiomes of susceptible and resistant strains.Experimental Design and MethodologyTo achieve its objectives, the study employed a controlled laboratory selection process and advanced sequencing techniques.Strain Development: Three insecticide-resistant (IR) strains were developed from a susceptible parent strain (IS) originally from Egypt (Egypt II). For 36 successive generations, populations were exposed to increasing concentrations of one of three insecticides: malathion (ML-SEL strain), dimethoate (Dm-SEL strain), or spinosad (Sp-SEL strain). The selection pressure was calibrated to achieve 50-70% mortality in each generation.Resistance Confirmation: Toxicological bioassays were conducted on the 36th generation of each IR strain and the IS strain. The lethal concentration required to kill 50% of the population (LC50) was calculated to quantify the level of resistance. The results confirmed a significant increase in tolerance in the selected strains. | Strain | Insecticide | LC50 (ppm) | Resistance Ratio (RR) vs. IS Strain | IS | Malathion | 18.8 | - | ML-SEL (G36) | Malathion | 1872.2 | 99.23-fold | IS | Dimethoate | 0.85 | - | Dm-SEL (G36) | Dimethoate | 215.79 | 252.68-fold | IS | Spinosad | 0.55 | - | Sp-SEL (G36) | Spinosad | 133.79 | 241.49-foldMicrobiota Analysis: Gut tissues were dissected from adult...
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    13 分
  • Mosquito Diversity and Vector Distribution in Kerala, India (Aug 2025)

    Mosquito Diversity and Vector Distribution in Kerala, India (Aug 2025)
    2025/08/23
    Mosquito Diversity and Public Health Risk in Kerala, India: A Synthesis of a Multi-District SurveySource: Mathiarasan, L., Natarajan, R., Aswin, A. et al. Diversity and spatiotemporal distribution of mosquitoes (Diptera: Culicidae) with emphasis on disease vectors across agroecological areas of Kerala, India. Sci Rep 15, 30603 (2025). https://doi.org/10.1038/s41598-025-16357-yDate: Received - 29 May 2025 | Accepted - 14 August 2025 | Published - 20 August 2025Executive SummaryThis document synthesizes the findings of an extensive entomological survey conducted across five agroecological districts of Kerala, India. The research reveals a remarkably diverse mosquito fauna, identifying 108 species, including 14 known disease vectors, which underscores the region's complex public health challenges. The study highlights the overwhelming predominance of Stegomyia albopicta (54.82% of all collected specimens), a highly adaptable vector for dengue and chikungunya, posing a significant and ongoing threat.Key findings indicate that artificial, human-made habitats—such as discarded tires, plastic containers, and latex collection cups—are the primary breeding grounds, supporting greater species diversity than natural habitats and pointing to critical deficiencies in solid waste management. The Wayanad district was identified as a major biodiversity hotspot for mosquitoes, attributed to its unique ecological niches. The investigation also yielded significant scientific discoveries, including the description of a new species, Heizmannia rajagopalani, and the first regional records of several other species. The co-existence of multiple vectors for arboviruses, malaria, and filariasis creates a complex risk profile that necessitates comprehensive surveillance and targeted, ecologically-informed control strategies.1. Overview of the Entomological SurveyThe study was designed to conduct a comprehensive assessment of mosquito biodiversity, spatiotemporal distribution, and habitat preferences across diverse ecological settings in Kerala, India, a state known for its unique agro-geographical features and history of mosquito-borne disease (MBD) outbreaks.Objective: To evaluate mosquito species composition, spatial and temporal distribution, and ecological and habitat preferences to inform public health risk assessment and vector control strategies.Scope and Duration: The survey was conducted from February 2016 to September 2017 in five districts selected for their varied ecotypes: Wayanad (forested, high altitude) Ernakulam (coastal, plantation) Pathanamthitta (Western Ghats, plantation) Idukki (mountainous, tea cultivation) Thiruvananthapuram (capital, urban/rural/coastal) Methodology: The research employed a dual sampling approach, collecting both immature (larvae, pupae) and adult mosquitoes. Immature specimens were collected from 777 habitats, while 4,021 adult mosquitoes were collected from 422 sites. Species were identified using standard morphological and taxonomic keys.Total Collection: A total of 12,535 mosquito specimens were collected and identified.2. Species Composition and AbundanceThe survey revealed a rich and diverse mosquito fauna, highlighting a complex ecosystem of both nuisance species and medically important vectors.Overall DiversityA total of 108 mosquito species belonging to 28 genera were identified. The genus Culex exhibited the highest species richness (25.0%), followed by Anopheles (12.9%) and Stegomyia (10.2%).Dominant SpeciesThe vast majority of collected specimens were dominated by a few highly prevalent species: | Species | Percentage of Total Collection | Known Significance | Stegomyia albopicta | 54.82% | Primary vector for dengue, chikungunya, Zika | Culex quinquefasciatus | 6.92% | Vector for lymphatic filariasis | Hulecoeteomyia chrysolineata | 6.33% | Noted for diverse breeding patterns | Armigeres subalbatus | 5.03% | Nuisance mosquito, prefers polluted waterIdentified Disease VectorsThe study identified 14 known disease vector species, creating a multifaceted public health risk. The co-existence of primary and secondary vectors for various diseases complicates transmission dynamics.Arboviruses (Dengue, Chikungunya, Zika, Japanese Encephalitis): St. albopicta, St. aegypti, Fredwardsius vittatus, Cx. tritaeniorhynchus, Cx. bitaeniorhynchus, Cx. gelidus, Cx. vishnui, Cx. pseudovishnui.Malaria: Anopheles stephensi, An. culicifacies (primary vectors), and An. varuna (secondary vector).Filariasis: Cx. quinquefasciatus, Mansonia uniformis, An. barbirostris.While St. albopicta was abundant, other primary vectors were found in extremely low numbers, such as St. aegypti(1.43%), An. stephensi (0.06%), and An. culicifacies (0.01%). However, the study emphasizes that even low-density vector populations can sustain pathogen transmission cycles and cause outbreaks under favorable conditions.3. Spatiotemporal Distribution and Biodiversity HotspotsThe distribution of mosquito species ...
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    14 分
  • AI and Electric Fields for Automated Insect Monitoring (Aug 2025)

    AI and Electric Fields for Automated Insect Monitoring (Aug 2025)
    2025/08/16
    Briefing: Automated Insect Monitoring via AI and Electrical Field SensorsSource: Odgaard, F.B., Kjærbo, P.V., Poorjam, A.H. et al. Automated insect detection and biomass monitoring via AI and electrical field sensor technology. Sci Rep 15, 29858 (2025). https://doi.org/10.1038/s41598-025-15613-5Date: Received - 11 April 2025 | Accepted - 08 August 2025 | Published - 14 August 2025Executive SummaryThis document outlines a novel, automated insect monitoring system that uses electrical field sensors and artificial intelligence to provide a non-invasive, continuous alternative to traditional methods. The system addresses the critical need for improved insect monitoring in the face of global declines, aiming to overcome the labor-intensive, lethal, and temporally limited nature of conventional techniques like Malaise traps.The core technology detects atmospheric electrical field modulations caused by flying insects. A differential sensor design suppresses environmental noise, while a cloud-based AI pipeline processes the signals. This pipeline employs a Convolutional Neural Network (CNN) for insect detection, a probabilistic algorithm for Wing-Beat Frequency (WBF) analysis, and a lookup-based algorithm for biomass estimation.A field validation study conducted in a Danish nature reserve compared the system against standard Townes Malaise traps. The results demonstrated a moderate to strong positive correlation between sensor and trap data for insect counts (Spearman’s ρ up to 0.725). However, the correlation for biomass was weaker and not consistently significant. A major discrepancy in magnitude was observed, with sensors recording approximately three times more insect counts and 26 times more biomass than the traps. This is attributed to fundamental methodological differences (passive sensing vs. single capture) and significant uncertainty within the system's current biomass estimation algorithm.Notably, the sensor system exhibited higher measurement consistency between its own units (sensor-sensor correlation for biomass ρ = 0.867) than paired Malaise traps (Malaise-Malaise correlation for biomass ρ = 0.641), although this difference was not statistically significant (P = 0.057). The study concludes that while the technology shows significant promise for scalable, non-lethal insect monitoring, the biomass algorithm requires substantial refinement and calibration before it can be used for absolute estimation.1. The Challenge in Conventional Insect MonitoringInsects, comprising over half of all described species, are vital for ecosystem stability through functions like pollination, nutrient cycling, and pest control. Alarming reports of declines in insect abundance, biomass, and species richness underscore the urgent need for effective monitoring to support conservation and safeguard ecosystem services.However, conventional monitoring techniques present significant challenges:• Labor-Intensive: Methods such as pan, pit, light, and Malaise traps require substantial manual effort for insect collection, sorting, counting, and weighing.• Invasive and Lethal: These trap-based approaches remove insects from the local population, posing a potential threat to fragile species and raising ethical concerns. The validation study for this new system highlighted this impact, with 55,443 insects killed in just two Malaise traps during the sampling period.• Limited Granularity: Traditional methods typically provide data at coarse temporal intervals (e.g., daily or weekly), limiting insights into finer-scale activity patterns.Automation and non-invasive technologies are critical for overcoming these limitations, enabling continuous data collection across large areas without disrupting local ecosystems.2. A Novel Automated Monitoring SystemThe presented system offers a comprehensive, automated solution for non-invasive insect monitoring, from data acquisition in the field to data analysis in the cloud.2.1. Operating Principle and Sensor DesignThe system's core innovation is its ability to passively detect flying insects by exploiting natural electrical effects.• Detection Mechanism: As insects fly, they acquire a positive electrical charge through air friction (triboelectric effect) and disrupt the ambient atmospheric electric field. These combined effects create unique electrical signatures that the sensor detects.• Differential Probe Design: To function in noisy outdoor environments, the sensor employs two identical electrostatic probes spaced 28 cm apart. This differential measurement approach effectively mitigates distant, common-mode noise sources like atmospheric disturbances and radio signals.• Detection Volume: The design creates a detection volume sensitive to nearby insects. However, it also creates a "blind plane" of zero sensitivity on the symmetry plane directly between the two probes. The sensor's sensitivity is size-dependent, meaning larger insects are detectable at greater distances than ...
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    19 分
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