Centre for Healthy Eating and Food Innovation, Maastricht University-Campus Venlo, 5900 AA, Venlo, The Netherlands.
Agrobiotechnology Center, Faculty "Bioengineering and Veterinary Medicine", Don State Technical University, Rostov-On-Don, 344000, Russia.
Sci Rep. 2023 Feb 9;13(1):2306. doi: 10.1038/s41598-023-29099-6.
Coronaviruses (CoVs) pose a huge threat to public health as emerging viruses. Bat-borne CoVs are especially unpredictable in their evolution due to some unique features of bat physiology boosting the rate of mutations in CoVs, which is already high by itself compared to other viruses. Among bats, a meta-analysis of overall CoVs epizootiology identified a nucleic acid observed prevalence of 9.8% (95% CI 8.7-10.9%). The main objectives of our study were to conduct a qPCR screening of CoVs' prevalence in the insectivorous bat population of Fore-Caucasus and perform their characterization based on the metagenomic NGS of samples with detected CoV RNA. According to the qPCR screening, CoV RNA was detected in 5 samples, resulting in a 3.33% (95% CI 1.1-7.6%) prevalence of CoVs in bats from these studied locations. BetaCoVs reads were identified in raw metagenomic NGS data, however, detailed characterization was not possible due to relatively low RNA concentration in samples. Our results correspond to other studies, although a lower prevalence in qPCR studies was observed compared to other regions and countries. Further studies should require deeper metagenomic NGS investigation, as a supplementary method, which will allow detailed CoV characterization.
冠状病毒(CoVs)作为新兴病毒,对公共卫生构成了巨大威胁。由于蝙蝠生理学的一些独特特征,蝙蝠携带的 CoVs 在进化中特别不可预测,这增加了 CoVs 的突变率,与其他病毒相比,CoVs 的突变率已经很高。在蝙蝠中,对 CoVs 总体流行性病学的荟萃分析确定了观察到的核酸阳性率为 9.8%(95%CI8.7-10.9%)。我们研究的主要目的是对 Fore-Caucasus 地区食虫蝙蝠种群中的 CoV 流行情况进行 qPCR 筛查,并根据检测到 CoV RNA 的样本的宏基因组 NGS 对其进行特征分析。根据 qPCR 筛查,在 5 个样本中检测到 CoV RNA,导致这些研究地点的蝙蝠 CoV 阳性率为 3.33%(95%CI1.1-7.6%)。在原始宏基因组 NGS 数据中鉴定出了β冠状病毒读数,但由于样本中 RNA 浓度相对较低,因此无法进行详细的特征分析。我们的结果与其他研究相符,尽管与其他地区和国家相比,qPCR 研究中的阳性率较低。进一步的研究需要更深入的宏基因组 NGS 调查作为补充方法,这将允许对 CoV 进行详细的特征分析。