Detection of Bacterial Agents inAmblyomma americanum(Acari: Ixodidae) From Georgia, USA, and the Use of a Multiplex Assay to DifferentiateEhrlichia chaffeensisandEhrlichia ewingii

Autor: M. L. Levin, Lindsay F. Killmaster, Amanda D. Loftis, Galina E. Zemtsova
Rok vydání: 2014
Předmět:
Zdroj: Journal of Medical Entomology. 51:868-872
ISSN: 1938-2928
0022-2585
DOI: 10.1603/me13225
Popis: Amblyomma americanum, the lone star tick, is the most common and most aggressive human biting tick in the Southeastern United States. It is known to transmit the agents of human ehrlichioses, Ehrlichia chaffeensis and Ehrlichia ewingii. In addition, it carries agents of unspecified pathogenicity to humans, including Rickettsia amblyommii, Borrelia lonestari, and the newly emerging Panola Mountain Ehrlichia (PME). Surveillance of these ticks for recognized or emerging pathogens is necessary for assessing the risk of human infection. From 2005 to 2009, we surveyed A. americanum ticks from four locations in the state of Georgia. Ticks (1,183 adults, 2,954 nymphs, and 99 larval batches) were tested using a multiplex real-time polymerase chain reaction (PCR) assay designed to detect and discriminate DNA from Rickettsia spp., E. chaffeensis, and E. ewingii. This assay was capable of detecting as few as 10 gene copies of the aforementioned agents. Ticks were also tested for PME and B. lonestari by nested PCR. The prevalence of infection ranged from 0 to 2.5% for E. chaffeensis, 0 to 3.9% for E. ewingii, 0 to 2.2% for PME, 17 to 83.1% for R. amblyommii, and 0 to 3.1% for B. lonestari. There were 46 (4.1%) individual adults positive for two agents, and two females that were each positive for three agents. Two larval batches were positive for both B. lonestari and R. amblyommii, indicating the potential for transovarial transmission of both agents from a single female. Although infrequent in occurrence, the dynamics of coinfections in individual ticks should be explored further, given the potential implications for differential diagnosis and severity of human illness.
Databáze: OpenAIRE