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Suprunenko, Y. F.

Publications and source records attributed to Suprunenko, Y. F..

3 recordsLinked to original sources

New insights on the Feeding Site and Salivation by Lutzomyia longipalpis (Diptera: Psychodidae) During Blood Ingestion on Host Skin

Phlebotomine sand flies are major vectors of Leishmania parasites, yet the mechanisms underlying their blood-feeding behavior remain poorly understood. In Lutzomyia longipalpis, the primary vector of Leishmania infantum in the Americas, feeding occurs via telmophagy, a pool-feeding method which is known by involving dermal laceration, salivation, and the creation of a blood pool. While the biochemical effects of sand fly saliva on host hemostasis, inflammation, and immunity are well studied, the dynamics of mouthpart movements and saliva at the feeding site remain to be systematically explored. Using intravital microscopy, fluorescent saliva labelling and image analysis, we characterized the mechanical actions of mouthparts and the spatial-temporal patterns of salivation during feeding on mammalian skin. Our recordings indicate that the labrum and hypopharynx are the most prominent mouthparts during feeding and exhibit scissor-like movements during probing. At specific moments, these structures close forcefully, generating small blood splashes in multiple directions. Feeding occurred in two distinct phases: an initial probing phase, often distinguished by ineffective blood intake, and a subsequent engorgement phase that was initiated exclusively upon the activation of small dermal "feeder vessels."Acridine Orange labelling showed abundant early salivation that penetrated progressively deeper into the dermis and remained detectable for over an hour, reflecting both the tissue damage and enzymatic effects. The analysis of images demonstrated the sequential salivation events, highlighting an initial high-frequency phase followed by a more gradual pattern during engorgement. These findings provide the first real-time, detailed view of the coordinated interactions between mouthpart mechanics, targeted salivation, and host microvascular responses in Lu. longipalpis. This study redefines sand fly telmophagy as a non-passive and coordinated process integrating mouthpart mechanics, salivation, and modulation of host vasculature. This work advances our understanding of sand fly vector-host interactions and underscores the potential of salivary molecules as targets for transmission-blocking strategies. Author SummaryPhlebotomine sand flies are the main vectors of Leishmania infantum, the parasite responsible for visceral leishmaniasis in the Americas. Although sand flies are traditionally classified as "pool feeders," meaning they lacerate the skin and feed from small pools of blood, the mechanics of how they obtain blood and deliver saliva into host skin have remained poorly understood. In this study, we used image analysis, intravital microscopy and fluorescent labeling of saliva to visualize, in real time, the feeding behavior of Lutzomyia longipalpis on mammalian skin. We show that blood feeding is not a passive process based solely on blood pooling. Instead, it involves coordinated movements of the mouthparts, modulation of host microvessels with the saliva contribution, and the recruitment of small dermal "feeder vessels" that supply blood directly to the insect. Our findings reveal that sand fly feeding is a highly orchestrated interaction between vector and host, integrating mechanical tissue disruption, salivary secretion, and vascular responses. These processes likely create a favorable microenvironment for Leishmania establishment and transmission. By providing a detailed characterization of mouthpart and salivation dynamics, this study advances our understanding of sand fly biology and highlights salivary components and feeding-site events as potential targets for transmission-blocking strategies.

microbiology↗

Relationship between spatial scale of pathogen dispersal and host landscape that minimizes infection rate in agricultural crops

ContextThe initial rate of pathogen invasion in crops is influenced by the spatial clustering of susceptible crops and the characteristics of pathogen dispersal. Previous studies have shown that various degrees of crop clustering can effectively reduce this invasion rate. However, the optimal degrees of clustering that minimize pathogen invasion have not previously been identified. ObjectivesThis study aims to determine analytically the range of crop clustering that minimizes the initial rate of pathogen invasion. MethodsWe studied artificial agricultural landscapes with crop areas arranged in identical square clusters on a regular square lattice. For pathogen dispersal, we used several common dispersal kernels, including Gaussian, negative exponential, and power-law. The optimal degree of clustering, defined by cluster size and separation distance, was calculated using a new analytical approximation for the pathogen invasion rate, which showed strong agreement with computer simulations. Additionally, we analysed a realistic cassava landscape at risk of invasion by cassava brown streak virus. ResultsWe identified a range of optimal cluster sizes and corresponding separation distances that minimize pathogen invasion rates for various dispersal kernels and landscapes with clusters of crop fields arranged on a regular square lattice. The methods can be extended to other geometrical configurations, such as long narrow fields. Using a cassava landscape as an example, we show how optimal crop clustering strategies can be derived to mitigate the potential invasion of cassava brown streak virus. ConclusionThe methods provides analytical insights that can help farmers and agricultural planners to optimize the spatial structure of agricultural landscapes to minimize initial pathogen invasion rates.

ecology↗

Where to refine spatial data to improve accuracy in crop disease modelling: an analytical approach with examples for cassava

Epidemiological modelling plays an important role in global food security by informing strategies for the control and management of invasion and spread of crop diseases. However, the underlying data on spatial locations of host crops that are susceptible to a pathogen are often incomplete and inaccurate, thus reducing the accuracy of model predictions. Obtaining and refining data sets that fully represent a host landscape across territories can be a major challenge when predicting disease outbreaks. Therefore, it would be an advantage to prioritise areas in which data refinement efforts should be directed to improve the accuracy of epidemic prediction. In this paper, we present an analytical method to identify areas where potential errors in mapped host data would have the largest impact on modelled pathogen invasion and short-term spread. The method is based on an analytical approximation for the rate at which susceptible host crops become infected at the start of an epidemic. We show how implementing spatial prioritisation for data refinement in a cassava-growing region in sub-Saharan Africa could be an effective means for improving accuracy when modelling the dispersal and spread of the crop pathogen cassava brown streak virus (CBSV).

ecology↗