摘要
Ticks harbor multiple pathogens, most of which can be transmitted to humans. The ensuing zoonoses display non-specific symptoms that make definitive diagnosis difficult. We report here the development and evaluation of multiplex real time polymerase chain reaction (qPCR) assays for eight tick-borne zoonoses (TBZ). The assays were organized in duo formats of 4-plex each. Format 1 was optimized for Anaplasma phagocytophilum, Coxiella burnetii, Borrelia burgdoferi and Ehrlichia chaffeensis. Format 2 was optimized for Rickettsia species (spp.), Bartonella spp., Borrelia spp. other than B. burgdoferi and Babesia spp. Synthetic plasmids were used to show that the assays can specifically detect all target sequences in the same reaction tube. Assays were assayed eight times to determine assay performance and the limit of detection was determined as the lowest plasmid concentration that was amplified for all the targets. Standard curves of threshold cycle (Ct) versus copy numbers were generated and used to determine linearity and efficiency of the assays. Pairwise comparison of singleplex and multiplex assays was done using Bland-Altman plots. Prevalence was calculated as overall percentage of positive patients to each TBZ tested Assay 1 had a limit of detection of 2 copy numbers for all targets. Assay 2 was less sensitive and on average had a limit of detection of 18 gene copies. In replicate tests, both assays had intra-assay variation of less than two cycles. Multiplex assays performance was comparable to respective singleplex assays. Evaluation of 512 clinical samples collected between 2008 and 2016 from acute febrile illness patients attending hospitals in different counties in Kenya revealed a 20% prevalence of tick-borne pathogens comprising B. burgdorferi (6%), non B. burgdorferi Borrelia spp. (3%), C. burnetii (5%), A. phagocytophilum (5%), Rickettsia spp. (2%), E. chaffeensis (0.8%), Bartonella spp. (0.8%), and Babesia spp. (0.4%). The high analytical sensitivity suggests potential for the duo 4-plex qPCR for de
Ticks harbor multiple pathogens, most of which can be transmitted to humans. The ensuing zoonoses display non-specific symptoms that make definitive diagnosis difficult. We report here the development and evaluation of multiplex real time polymerase chain reaction (qPCR) assays for eight tick-borne zoonoses (TBZ). The assays were organized in duo formats of 4-plex each. Format 1 was optimized for Anaplasma phagocytophilum, Coxiella burnetii, Borrelia burgdoferi and Ehrlichia chaffeensis. Format 2 was optimized for Rickettsia species (spp.), Bartonella spp., Borrelia spp. other than B. burgdoferi and Babesia spp. Synthetic plasmids were used to show that the assays can specifically detect all target sequences in the same reaction tube. Assays were assayed eight times to determine assay performance and the limit of detection was determined as the lowest plasmid concentration that was amplified for all the targets. Standard curves of threshold cycle (Ct) versus copy numbers were generated and used to determine linearity and efficiency of the assays. Pairwise comparison of singleplex and multiplex assays was done using Bland-Altman plots. Prevalence was calculated as overall percentage of positive patients to each TBZ tested Assay 1 had a limit of detection of 2 copy numbers for all targets. Assay 2 was less sensitive and on average had a limit of detection of 18 gene copies. In replicate tests, both assays had intra-assay variation of less than two cycles. Multiplex assays performance was comparable to respective singleplex assays. Evaluation of 512 clinical samples collected between 2008 and 2016 from acute febrile illness patients attending hospitals in different counties in Kenya revealed a 20% prevalence of tick-borne pathogens comprising B. burgdorferi (6%), non B. burgdorferi Borrelia spp. (3%), C. burnetii (5%), A. phagocytophilum (5%), Rickettsia spp. (2%), E. chaffeensis (0.8%), Bartonella spp. (0.8%), and Babesia spp. (0.4%). The high analytical sensitivity suggests potential for the duo 4-plex qPCR for de
