Biology subjects

Heitmann, A.

Publications and source records attributed to Heitmann, A..

3 recordsLinked to original sources

bioRxiv2026

Invasive mosquito species Aedes aegypti and Aedes albopictus are competent vectors for Barmah Forest Virus

Barmah Forest Virus (BFV), an arthropod-born virus transmitted by mosquitoes, is of significant public health concern in Australia and regions in the Pacific. Recent climate change and globalization raise the potential for BFV to extend its geographic distribution. Despite the rising importance of BFV, its vector dynamics remain poorly understood, particularly concerning the vector competence of different mosquito species. This study aims to investigate the vector competence of BFV across various mosquito species, beyond those endemic to the Australasian region, especially focusing on global relevant vector species. No transmission was observed for Culex quinquefasciatus and Cx. torrentium as well as Anopheles stephensi. In contrast, both investigated Aedes species, Ae. aegypti as well as Ae. albopictus, exhibited BFV-positive saliva across all four temperature profiles (18{degrees}C, 21{degrees}C, 24{degrees}C or 27{degrees}C) examined. These two invasive mosquito species must therefore be classified as potential vectors for BFV, indicating the potential risk of BFV transmission outside of Australia.

molecular biology↗

bioRxiv2026

Not all West Nile virus lineages behave alike: vector competence and minimum infectious dose differences between lineages 1 and 2

The globally distributed arbovirus West Nile virus (WNV) continues to expand across Europe, with rising numbers of human cases and an increasingly broad geographic distribution. WNV is primarily transmitted by mosquitoes of the genus Culex. Out of nine WNV lineages, human pathogenicity has been clearly established for lineages 1 and 2, but differences in their transmission dynamics, such as minimal infectious dose and transmission efficiency, remain poorly understood. In this study, we investigated how viral lineage, mosquito species, and blood meal titer influence the vector competence of two primary WNV vectors from Europe, Cx. pipiens biotype pipiens and Cx. torrentium, as well as the invasive mosquito species Aedes albopictus. Female mosquitoes were fed with increasing blood meal titers containing either of the WNV lineages. After an incubation period of 14 days at a mean temperature of 24{degrees}C, mosquito body titers were quantified, and the presence of infectious viral particles in the saliva was assessed. Our results revealed clear differences between the two lineages. Lineage 2 resulted in higher transmission efficiencies across all three species and required lower infectious doses to cause transmission. Among the tested species, Cx. torrentium proved to be a highly competent vector (max. transmission efficiency = 30%, minimum infectious dose = 105 TCID50/mL), despite its underrepresentation in research. These findings provide detailed insights into how viral lineage, mosquito species, and blood meal titer might shape WNV transmission, informing future risk assessments and efforts to mitigate WNV transmission in Europe.

microbiology↗

bioRxiv2024

Mosquito Wing Image Repository for Advancing Research on Geometric Morphometric- and AI-Based Identification

Accurate identification of mosquito species is essential for effective vector control and mitigation of mosquito-borne disease outbreaks. Traditional morphological identification requires highly specialized personnel and is time-consuming, while molecular techniques can be cost-effective and dependent on comprehensive genetic information. Wing geometric morphometry has emerged as a promising alternative, leveraging detailed geometric measurements of wing shapes and vein patterns to distinguish between species and detect intraspecies variations. This paper presents a curated dataset of 18,104 mosquito wing images, collected from 10,500 mosquito specimens, annotated with extensive meta-information, designed to support research in wing geometric morphometry and the development of machine learning models, ultimately supporting efforts in vector surveillance and research.

ecology↗