Dataset Information

Prevalence and genotypes of Anaplasma species and habitat suitability for ticks in a Mediterranean ecosystem.

ABSTRACT: Anaplasma species are tick-transmitted pathogens that impact veterinary and human health. Sicily is one of the locations where these pathogens are endemic. Sicily represents a typical Mediterranean ecosystem to study Anaplasma infection and tick habitat suitability. The aims of this study were (i) to characterize by 16S rRNA and species-specific msp4 gene PCR the prevalence and genotypes of A. marginale, A. phagocytophilum, and A. ovis in the most abundant host species in Sicilian provinces and (ii) to correlate differences between hosts and between western and eastern Sicily with the habitat suitability for ticks in these regions. Differences were found in the prevalence of Anaplasma spp. between different hosts and between western and eastern provinces. The differences in Anaplasma prevalence between different hosts may be explained by pathogen host tropism. The differences between western and eastern provinces correlated with the tick habitat suitability in these regions. The analysis of Anaplasma genotypes suggested a higher host and regional specificity for A. phagocytophilum than for A. marginale and A. ovis strains, a finding probably associated with the broader host range of A. phagocytophilum. The presence of identical A. marginale genotypes in the two regions may reflect cattle movement. The results for A. ovis suggested the possibility of some genotypes being host specific. These results provide information potentially useful for the management of tick-borne diseases caused by Anaplasma spp. in Sicily and other Mediterranean regions and may contribute to the development of models to predict the risks for these tick-borne pathogens.

SUBMITTER: Torina A

PROVIDER: S-EPMC2607149 | biostudies-literature | 2008 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prevalence and genotypes of Anaplasma species and habitat suitability for ticks in a Mediterranean ecosystem.

Torina Alessandra A Alongi Angelina A Naranjo Victoria V Estrada-Peña Agustín A Vicente Joaquín J Scimeca Salvatore S Marino Anna M F AM Salina Felice F Caracappa Santo S de la Fuente José J

Applied and environmental microbiology 20081031 24

Anaplasma species are tick-transmitted pathogens that impact veterinary and human health. Sicily is one of the locations where these pathogens are endemic. Sicily represents a typical Mediterranean ecosystem to study Anaplasma infection and tick habitat suitability. The aims of this study were (i) to characterize by 16S rRNA and species-specific msp4 gene PCR the prevalence and genotypes of A. marginale, A. phagocytophilum, and A. ovis in the most abundant host species in Sicilian provinces and ...[more]

PMID: 18978093

Similar Datasets

Project description:BackgroundTicks are responsible for transmitting several notable pathogens worldwide. Finland lies in a zone where two human-biting tick species co-occur: Ixodes ricinus and Ixodes persulcatus. Tick densities have increased in boreal regions worldwide during past decades, and tick-borne pathogens have been identified as one of the major threats to public health in the face of climate change.MethodsWe used species distribution modelling techniques to predict the distributions of I. ricinus and I. persulcatus, using aggregated historical data from 2014 to 2020 and new tick occurrence data from 2021. By aiming to fill the gaps in tick occurrence data, we created a new sampling strategy across Finland. We also screened for tick-borne encephalitis virus (TBEV) and Borrelia from the newly collected ticks. Climate, land use and vegetation data, and population densities of the tick hosts were used in various combinations on four data sets to estimate tick species' distributions across mainland Finland with a 1-km resolution.ResultsIn the 2021 survey, 89 new locations were sampled of which 25 new presences and 63 absences were found for I. ricinus and one new presence and 88 absences for I. persulcatus. A total of 502 ticks were collected and analysed; no ticks were positive for TBEV, while 56 (47%) of the 120 pools, including adult, nymph, and larva pools, were positive for Borrelia (minimum infection rate 11.2%, respectively). Our prediction results demonstrate that two combined predictor data sets based on ensemble mean models yielded the highest predictive accuracy for both I. ricinus (AUC = 0.91, 0.94) and I. persulcatus (AUC = 0.93, 0.96). The suitable habitats for I. ricinus were determined by higher relative humidity, air temperature, precipitation sum, and middle-infrared reflectance levels and higher densities of white-tailed deer, European hare, and red fox. For I. persulcatus, locations with greater precipitation and air temperature and higher white-tailed deer, roe deer, and mountain hare densities were associated with higher occurrence probabilities. Suitable habitats for I. ricinus ranged from southern Finland up to Central Ostrobothnia and North Karelia, excluding areas in Ostrobothnia and Pirkanmaa. For I. persulcatus, suitable areas were located along the western coast from Ostrobothnia to southern Lapland, in North Karelia, North Savo, Kainuu, and areas in Pirkanmaa and Päijät-Häme.ConclusionsThis is the first study conducted in Finland that estimates potential tick species distributions using environmental and host data. Our results can be utilized in vector control strategies, as supporting material in recommendations issued by public health authorities, and as predictor data for modelling the risk for tick-borne diseases.

Project description:Technological advances increase opportunities for novel wildlife survey methods. With increased detection methods, many organizations and agencies are creating habitat suitability models (HSMs) to identify critical habitats and prioritize conservation measures. However, multiple occurrence data types are used independently to create these HSMs with little understanding of how biases inherent to those data might impact HSM efficacy. We sought to understand how different data types can influence HSMs using three bat species (Lasiurus borealis, Lasiurus cinereus, and Perimyotis subflavus). We compared the overlap of models created from passive-only (acoustics), active-only (mist-netting and wind turbine mortalities), and combined occurrences to identify the effect of multiple data types and detection bias. For each species, the active-only models had the highest discriminatory ability to tell occurrence from background points and for two of the three species, active-only models preformed best at maximizing the discrimination between presence and absence values. By comparing the niche overlaps of HSMs between data types, we found a high amount of variation with no species having over 45% overlap between the models. Passive models showed more suitable habitat in agricultural lands, while active models showed higher suitability in forested land, reflecting sampling bias. Overall, our results emphasize the need to carefully consider the influences of detection and survey biases on modeling, especially when combining multiple data types or using single data types to inform management interventions. Biases from sampling, behavior at the time of detection, false positive rates, and species life history intertwine to create striking differences among models. The final model output should consider biases of each detection type, particularly when the goal is to inform management decisions, as one data type may support very different management strategies than another.

Project description:Geospatial habitat suitability index (HSI) models have emerged as powerful tools that integrate pertinent spatial information to guide habitat restoration efforts, but have rarely accounted for spatial variation in ecosystem service provision. In this study, we utilized satellite-derived chlorophyll a concentrations for Pamlico Sound, North Carolina, USA in conjunction with data on water flow velocities and dissolved oxygen concentrations to identify potential restoration locations that would maximize the oyster reef-associated ecosystem service of water filtration. We integrated these novel factors associated with oyster water filtration ecosystem services within an existing, 'Metapopulation Persistence' focused GIS-based, HSI model containing biophysical (e.g., salinity, oyster larval connectivity) and logistical (e.g., distance to nearest restoration material stockpile site) factors to identify suitable locations for oyster restoration that maximize long-term persistence of restored oyster populations and water filtration ecosystem service provision. Furthermore, we compared the 'Water Filtration' optimized HSI with the HSI optimized for 'Metapopulation Persistence,' as well as a hybrid model that optimized for both water filtration and metapopulation persistence. Optimal restoration locations (i.e., locations corresponding to the top 1% of suitability scores) were identified that were consistent among the three HSI scenarios (i.e., "win-win" locations), as well as optimal locations unique to a given HSI scenario (i.e., "tradeoff" locations). The modeling framework utilized in this study can provide guidance to restoration practitioners to maximize the cost-efficiency and ecosystem services value of habitat restoration efforts. Furthermore, the functional relationships between oyster water filtration and chlorophyll a concentrations, water flow velocities, and dissolved oxygen applied in this study can guide field- and lab-testing of hypotheses related to optimal conditions for oyster reef restoration to maximize water quality enhancement benefits.

Dataset Information

Prevalence and genotypes of Anaplasma species and habitat suitability for ticks in a Mediterranean ecosystem.

Publications

Prevalence and genotypes of Anaplasma species and habitat suitability for ticks in a Mediterranean ecosystem.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets