Schmidt Hanno, Lemmermann Niels, Linke Matthias, Bikár Sven-Ernö, Runkel Stefan, Schweiger-Seemann Susann, Gerber Susanne, Michel André, Hankeln Thomas, Veith Marina, Kohnen Wolfgang, Plachter Bodo
SARS-CoV-2 Sequencing Consortium, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Institute of Virology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Infect Prev Pract. 2024 Jul 6;6(3):100383. doi: 10.1016/j.infpip.2024.100383. eCollection 2024 Sep.
During the SARS-CoV-2 pandemic, dominant viral variants were repeatedly replaced by new variants with altered properties, frequently changing the dynamics of the infection event, as well as the effectiveness of vaccines and therapeutics. SARS-CoV-2 variant monitoring by whole genome sequencing was established at the University Medical Center Mainz, Germany to support patient management during the pandemic.
SARS-CoV-2 RNA samples from the University Medical Center were analysed weekly with whole genome sequencing. The genome sequences obtained were aligned with sequences from public databases to perform variant assignment. For classification purposes, phylogenetic trees were constructed to map the variant distribution in the clinical settings and the current outbreak events at that time. We describe the surveillance procedures using an example from a geriatric ward.
For monitoring, a time series was created covering two years of the pandemic. The changes from the Alpha to the Delta and the Omicron variants of SARS-CoV-2 could thus be precisely observed. The increasingly rapid switch of Omicron subvariants in the recent past could be tracked. The elucidation of phylogenetic relationships between circulating strains allowed conclusions about transmission pathways. Using an example from a geriatric ward, we demonstrated how variant monitoring by whole genome sequencing supported the infection prevention and control procedures on a ward and contribute to the control of outbreaks.
This example of SARS-CoV-2 demonstrates the effectiveness of targeted, local monitoring by molecular variant analysis. The program proved to be instrumental in controlling an outbreak on a geriatric ward.
在新冠病毒大流行期间,占主导地位的病毒变体不断被具有不同特性的新变体所取代,这经常改变感染事件的动态,以及疫苗和治疗方法的有效性。德国美因茨大学医学中心建立了通过全基因组测序监测新冠病毒变体的方法,以在大流行期间支持患者管理。
每周对美因茨大学医学中心的新冠病毒RNA样本进行全基因组测序分析。将获得的基因组序列与公共数据库中的序列进行比对,以进行变体分类。为了分类目的,构建系统发育树以描绘临床环境和当时当前疫情中的变体分布。我们以一个老年病房为例描述监测程序。
为了进行监测,创建了一个涵盖大流行两年时间的时间序列。由此可以精确观察到新冠病毒从阿尔法变体到德尔塔变体再到奥密克戎变体的变化。可以追踪最近奥密克戎亚变体越来越快的更替情况。对流行毒株之间系统发育关系的阐明有助于推断传播途径。以一个老年病房为例,我们展示了通过全基因组测序进行变体监测如何支持病房的感染预防和控制程序,并有助于控制疫情。
这个新冠病毒的例子证明了通过分子变体分析进行有针对性的本地监测的有效性。该计划被证明有助于控制老年病房的疫情。