Field and Molecular Epidemiology: How Viral Sequencing Changed Transmission Inferences in the First Portuguese SARS-CoV-2 Infection Cluster

Unraveling the hurdles of a large COVID-19 epidemiological investigation by viral genomics

COVID-19 local outbreak response relies on subjective information to reconstruct transmission chains. We assessed the concordance between epidemiologically linked cases and viral genetic profiles, in the Baixo Vouga Region (Portugal), from March to June 2020. A total of 1925 COVID-19 cases were identified, with 1143 being assigned to 154 epiclusters. Viral genomic data was available for 128 cases. Public health authorities identified two large epiclusters (280 and 101 cases each) with a central role on the spread of the disease. Still, the genomic data revealed that each epicluster included two distinct SARS-CoV-2 genetic profiles and thus more than one transmission network. We were able to show that the initial transmission dynamics reconstruction was most likely accurate, but the increasing dimension of the epiclusters and its extension to densely populated settings (healthcare and nursing home settings) triggered the misidentification of links. Genomics was also key to resolve some sporadic cases and misidentified direction of transmission. The epidemiological investigation showed a sensitivity of 70%-86% to detect transmission chains. This study contributes to the understanding of the hurdles and caveats associated with the epidemiological investigation of hundreds of community cases in the context of a massive outbreak caused by a highly transmissible and new respiratory virus.

Analysis of the Transmission of SARS-CoV-2 Delta VOC in Yantai, China, August 2021

Objective

Starting 31 July 2021, a SARS-CoV-2 outbreak occurred in Yantai, Shandong Province. The investigation showed that this outbreak was closely related to the epidemic at Nanjing Lukou Airport. In view of the fact that there were many people involved in this outbreak and these people had a complex activity area, the transmission route cannot be analyzed by simple epidemiological investigation. Here we combined the SARS-COV-2 whole-genome sequencing with epidemiology to determine the epidemic transmission route of Yantai.

Methods

Thirteen samples of SARS-CoV-2 outbreak cases from 31 July to 4 August 2021 were collected and identified by fluorescence quantitative PCR, then whole-genome deep sequencing based on NGS was performed, and the data were analyzed and processed by biological software.

Results

All sequences were over 29,000 bases in length and all belonged to B.1.617.2, which was the Delta strain. All sequences shared two amino acid deletions and 9 amino acid mutations in Spike protein compared with reference sequence NC_045512.2 (Wuhan virus strain). Compared with the sequence of Lukou Airport Delta strain, the homology was 99.99%. In order to confirm the transmission relationship between patients, we performed a phylogenetic tree analysis. The results showed that patient 1, patient 2, and patient 9 belong to an independent branch, and other patients have a close relationship. Combined with the epidemiological investigation, we speculated that the epidemic of Yantai was transmitted by two routes at the same time. Based on this information, our prevention and control work was carried out in two ways and effectively prevented the further spread of this epidemic.

InfectionCMA: A Cell MicroArray Approach for Efficient Biomarker Screening in In Vitro Infection Assays

The recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has forced the scientific community to acquire knowledge in real-time, when total lockdowns and the interruption of flights severely limited access to reagents as the global pandemic became established. This unique reality made researchers aware of the importance of designing efficient in vitro set-ups to evaluate infectious kinetics. Here, we propose a histology-based method to evaluate infection kinetics grounded in cell microarray (CMA) construction, immunocytochemistry and in situ hybridization techniques. We demonstrate that the chip-like organization of the InfectionCMA has several advantages, allowing side-by-side comparisons between diverse cell lines, infection time points, and biomarker expression and cytolocalization evaluation in the same slide. In addition, this methodology has the potential to be easily adapted for drug screening.