Taylor Abigail Dorothea, Trzebny Artur, Łośko Małgorzata, Michalik Jerzy Franciszek, Dabert Miroslawa
Molecular Biology Techniques Laboratory, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland.
Department of Animal Morphology, Faculty of Biology, Adam Mickiewicz University, 61-614 Poznan, Poland.
Pathogens. 2025 May 21;14(5):506. doi: 10.3390/pathogens14050506.
The increasing incidence of tick-borne diseases in Europe necessitates the development of accurate and high-throughput molecular tools for detecting pathogens in tick populations. In this study, we present a novel gene-based profiling method for the detection and identification of and species in ticks, combining newly designed primers with next-generation sequencing (NGS). The method was evaluated alongside conventional nested PCR targeting the gene, as well as microbial profiling based on the V4 region of the gene, using tick DNA extracted from 1088 specimens pooled into 94 samples. Our results demonstrate that the gene-based profiling approach was the highest-performing out of the three methods, detecting Borreliaceae DNA in 83 DNA pools, compared to 58 and 56 pools using nested PCR and V4 profiling, respectively. A total of 23 distinct sequence variants were identified, corresponding to five Borreliaceae species: , , , , and . Additionally, the method enabled putative strain-level discrimination within species. Our results highlight the value of gene-based profiling as a robust tool for ecological and epidemiological studies of Borreliaceae diversity in ticks.
欧洲蜱传疾病发病率的上升使得开发准确且高通量的分子工具以检测蜱虫种群中的病原体成为必要。在本研究中,我们提出了一种基于基因的新型分析方法,用于检测和鉴定蜱虫中的疏螺旋体属和巴贝斯虫属物种,该方法将新设计的引物与下一代测序(NGS)相结合。使用从1088个标本中提取的蜱虫DNA,将其合并为94个样本,对该方法与针对16S rRNA基因的传统巢式PCR以及基于16S rRNA基因V4区域的微生物分析方法进行了评估。我们的结果表明,基于16S rRNA基因的分析方法是这三种方法中性能最高的,在83个DNA样本池中检测到了疏螺旋体科DNA,相比之下,使用巢式PCR和V4分析分别检测到58个和56个样本池。总共鉴定出23种不同的16S rRNA序列变体,对应于五种疏螺旋体科物种:伯氏疏螺旋体、阿氏疏螺旋体、伽氏疏螺旋体、奋森疏螺旋体和赫氏疏螺旋体。此外,该方法能够在物种内进行假定的菌株水平区分。我们的结果突出了基于16S rRNA基因分析作为蜱虫中疏螺旋体科多样性生态和流行病学研究的强大工具的价值。