A peer-reviewed research article published last month in Science Translational Medicine highlights a study of phylogenetic analysis of 345 SARS-CoV-2 genomes from Austrian cases and over 7000 global genomes from the GISAID (Global Initiative on Sharing All Influenza Data) database. Austria has a highly developed public health infrastructure, and at the time of journal review had performed contact tracing on 100% of 21,821 cases linking 10,385 cases to specific epidemiological clusters. Samples obtained from a subset of these patients (345) in Austria were analyzed with the majority being from cases between February 26th and March 23rd revealing 273 mutations. Of the mutational profiles and the time of infection, six clusters could be linked to specific geographic locations to the Tyrol region (Tyrol-1, Tyrol-2, and Tyrol-3), and Vienna (Vienna-1, Vienna-2, and Vienna-3). These clusters are related to the global clades 19A, 20A, 20B, and 20C of the widely used Nextstrain classification.
Not surprisingly one cluster, the Tyrol 1 sequences, could be traced to individuals that were residents or visitors to the ski resort Ischgl or the related valley Paznaun. The authors further noted these strains were closely related to sequences collected previously in France and northern Italy, and later in Iceland, suggested origin of introduction and later spreading events. Soon the 20C strain would be isolated by other researchers in New York City. As Ischgl is a popular international ski destination, additional cases were spread to Denmark, Germany, Belgium, Switzerland, and Norway. The Tyrol 1 transmission cluster event is now traced to an indoor Apré ski bar. The Vienna 1 cluster transmission event was traced to an indoor sports class. Bars and gyms are now commonly known as high-risk SARS-CoV-2 areas.
Interesting to me was the contact tracing and sequencing data that showed direct links of more rare/low-frequency mutations transmitting through individuals and 11 families who attended funerals, birthday parties, work meetings, and choir practice. These are included in Figure 5 below.
As the authors conclude:
“Together, these results from two superspreading events (Tyrol-1 and Vienna-1) demonstrate the power of deep viral genome sequencing in combination with detailed epidemiological data for observing viral mutation on their way from emergence at low frequency to fixation.”
The entire article and supplementary materials can be viewed here.
ABSTRACT
Tracking and tracing SARS-CoV-2 mutations
Austria was an early hotspot of SARS-CoV-2 transmission due to winter tourism. By integrating viral genomic and phylogenetic analyses with time-resolved contact tracing data, Popa et al. examined the fine-scale dynamics of viral spread within and from Austria in the spring of 2020. Epidemiologically defined phylogenetic clusters and viral mutational profiles provided evidence of the ongoing fixation of two viral alleles within transmission chains and enabled estimation of the SARS-CoV-2 bottleneck size. This study provides an epidemiologically contextualized, high-resolution picture of SARS-CoV-2 mutational dynamics in an early international transmission hub.
The entire article and supplementary materials can be viewed here.
FIGURE 5:
Fig. 5 Impact of transmission bottlenecks and intrahost evolution on SARS-CoV-2 mutational dynamics.
(A) Schematics of time-related patient interactions across epidemiological clusters A and AL. Each node represents a case, and links between the nodes are epidemiologically confirmed direct transmissions. Samples sequenced from the same individual are reported under the corresponding node. Cases corresponding to the same family are color coded accordingly. Additional families, unrelated to clusters A/AL, and their epidemiological transmission details are also reported. (B) Bottleneck size (number of virions that initiate the infection in an infectee) estimation across infector-infectee pairs based on the transmission network depicted in (A), ordered according to the timeline of cluster A for the respective pairs, and with a cutoff of [0.01, 0.95] for alternative allele frequency. For patients with multiple samples, the earliest sample was considered for bottleneck size inference. Centered dots are maximum likelihood estimates, with 95% confidence intervals. A star (*) for family 4 indicates that the transmission line was inferred as detailed in Materials and Methods. The histogram (yellow bars) of all the bottleneck values is provided on the right side of the graph. (C) Alternative allele frequency (y axis) of mutations across available time points (x axis) for patient 5. Only variants with frequencies ≥0.02 and shared between at least two time points are shown. Two mutations increasing in frequency are color coded. (D) Genetic distance values of mutation frequencies between infector-infectee pairs (A and B) (transmission chains) and intrapatient consecutive time points [(C) and fig. S5D]. Only variants detected in two same-patient samples were considered.