Luo Jin, Ren Qiaoyun, Liu Wenge, Li Xiangrui, Song Mingxin, Guan Guiquan, Luo Jianxun, Liu Guangyuan
State Key Laboratory of Veterinary Etiological Biology, Key Laboratory of Veterinary Parasitology of Gansu Province, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Science, Xujiaping 1, Lanzhou, Gansu, 730046, PR China.
MOE Joint International Research Laboratory of Animal Health and Food Safety, College of Veterinary Medicine, Nanjing Agricultural University, Nanjing, 210095, PR China.
Int J Parasitol Parasites Wildl. 2021 Jun 25;15:238-248. doi: 10.1016/j.ijppaw.2021.06.003. eCollection 2021 Aug.
Ticks are important vectors that facilitate the transmission of a broad range of micropathogens to vertebrates, including humans. Because of their role in disease transmission, it has become increasingly important to identify and characterize the micropathogen profiles of tick populations. The objective of the present study was to survey the micropathogens of ticks by third-generation metagenomic sequencing using the PacBio Sequel platform. Approximately 46.481 Gbp of raw micropathogen sequence data were obtained from samples from four different regions of Heilongjiang Province, China. The clean consensus sequences were compared with host sequences and filtered at 90% similarity. Most of the identified genomes represent previously unsequenced strains. The draft genomes contain an average of 397,746 proteins predicted to be associated with micropathogens, over 30% of which do not have an adequate match in public databases. In these data, and were detected in all samples, while was detected only in ticks from G1 samples. Viruses are a key component of micropathogen populations. In the present study, , and were detected in different samples, and more than 10-30% of the viral community in all samples comprised unknown viruses. Deep metagenomic shotgun sequencing has emerged as a powerful tool to investigate the composition and function of complex microbial communities. Thus, our dataset substantially improves the coverage of tick micropathogen genomes in public databases and represents a valuable resource for micropathogen discovery and for studies of tick-borne diseases.
蜱虫是重要的病媒,可促进多种微生物病原体向包括人类在内的脊椎动物传播。由于它们在疾病传播中的作用,识别和表征蜱虫种群的微生物病原体谱变得越来越重要。本研究的目的是使用PacBio Sequel平台通过第三代宏基因组测序来调查蜱虫的微生物病原体。从中国黑龙江省四个不同地区的样本中获得了约46.481 Gbp的原始微生物病原体序列数据。将干净的共有序列与宿主序列进行比较,并以90%的相似度进行筛选。大多数鉴定出的基因组代表以前未测序的菌株。草图基因组平均包含397,746种预测与微生物病原体相关的蛋白质,其中超过30%在公共数据库中没有合适的匹配。在这些数据中,所有样本中均检测到了[具体物质1]和[具体物质2],而仅在G1样本的蜱虫中检测到了[具体物质3]。病毒是微生物病原体群体的关键组成部分。在本研究中,不同样本中检测到了[具体病毒1]、[具体病毒2]和[具体病毒3],所有样本中超过10%-30%的病毒群落由未知病毒组成。深度宏基因组鸟枪法测序已成为研究复杂微生物群落组成和功能的有力工具。因此,我们的数据集大幅提高了公共数据库中蜱虫微生物病原体基因组的覆盖范围,是微生物病原体发现和蜱传疾病研究的宝贵资源。