Department of Information Engineering, University of Padova, 35131, Padova, Italy.
Department of Molecular Medicine, University of Padova, 35121, Padova, Italy.
Sci Rep. 2023 Oct 6;13(1):16867. doi: 10.1038/s41598-023-43040-x.
The outbreak of Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, forced us to face a pandemic with unprecedented social, economic, and public health consequences. Several nations have launched campaigns to immunize millions of people using various vaccines to prevent infections. Meanwhile, therapeutic approaches and discoveries continuously arise; however, identifying infected patients that are going to experience the more severe outcomes of COVID-19 is still a major need, to focus therapeutic efforts, reducing hospitalization and mitigating drug adverse effects. Microbial communities colonizing the respiratory tract exert significant effects on host immune responses, influencing the susceptibility to infectious agents. Through 16S rDNAseq we characterized the upper airways' microbiota of 192 subjects with nasopharyngeal swab positive for SARS-CoV-2. Patients were divided into groups based on the presence of symptoms, pneumonia severity, and need for oxygen therapy or intubation. Indeed, unlike most of the literature, our study focuses on identifying microbial signatures predictive of disease progression rather than on the probability of infection itself, for which a consensus is lacking. Diversity, differential abundance, and network analysis at different taxonomic levels were synergistically adopted, in a robust bioinformatic pipeline, highlighting novel possible taxa correlated with patients' disease progression to intubation.
2019 年冠状病毒病（COVID-19）的爆发是由 SARS-CoV-2 引起的，这迫使我们面对一场具有前所未有的社会、经济和公共卫生后果的大流行。许多国家已经开展了疫苗接种运动，为数百万人口接种疫苗以预防感染。与此同时，治疗方法和发现不断涌现；然而，确定哪些感染患者将经历 COVID-19 的更严重后果仍然是一个主要需求，以便集中治疗努力，减少住院治疗并减轻药物不良反应。定植在呼吸道中的微生物群落对宿主免疫反应产生重大影响，影响对感染因子的易感性。通过 16S rDNAseq，我们对 192 名鼻咽拭子检测出 SARS-CoV-2 阳性的患者的上呼吸道微生物群落进行了特征分析。根据症状、肺炎严重程度以及是否需要吸氧或插管，将患者分为不同的组。事实上，与大多数文献不同，我们的研究重点是确定预测疾病进展的微生物特征，而不是感染本身的可能性，因为这方面缺乏共识。在不同的分类学水平上，多样性、差异丰度和网络分析协同采用，在一个稳健的生物信息学管道中，突出了与患者插管进展相关的新型可能分类群。
