Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 548 were “novel” SNVs that had not yet been identified in the global clinical-derived data as of 17 th June 2020 (the day after our last wastewater sampling date). However, between 17 th of June 2020 and 20 th November 2020, almost half of the novel SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 5680 were “novel” SNVs that had not yet been identified in the global clinical-derived data as of 17th June 2020 (the day after our last wastewater sampling date). However, between 17th of June 2020 and 20th November 2020, almost half of the SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.

This review summarises the presentations and discussions that took place during a European Science Foundation-funded workshop whose purpose was to gain current perspectives on the mutational mechanisms of simple sequence repeats and the contribution of localised hypermutation in such repeats to bacterial pathogenesis. In vitro biophysical and biochemical assays of mutational mechanisms were covered as well as genetic studies in various eukaryotic and prokaryotic organisms. Presentations on bacterial pathogenesis elaborated investigations of the use of repeats for typing of strains, epidemiological investigations of mutation rates and functions of loci whose expression is controlled by simple sequence repeats. This review tabulates current perspectives on the cis- and trans-acting factors for mutation of simple sequence repeats and the orientations of mononucleotide repeats in some bacterial species that utilise repeats for adaptation.

Simple sequence repeats located within reading frames mediate phase-variable ON/OFF switches in gene expression by generating frameshifts. Multiple translation initiation codons in different reading frames are found upstream of most Haemophilus influenzae tetranucleotide repeat tracts, raising the possibility of multiple active reading frames and more than two levels of gene expression for these loci. Phase variation between three levels of gene expression (strong, weak, and none) was observed when lic2A was fused to a lacZ reporter gene. The lic2A 5 CAAT repeat tract is preceded by four 5 ATG codons (x, y, z1, and z2) in two reading frames. Each of these initiation codons was inactivated by site-directed mutagenesis. Strong expression from frame 1 was associated with x but not y. Weak expression from frame 2 was mainly dependent on the z2 codon, and there was no expression from frame 3. Using monoclonal antibodies specific for a digalactoside epitope of lipopolysaccharide whose synthesis requires Lic2A, two levels (strong and undetectable) of antibody reactivity were detected, suggesting that weak expression of lic2A is not discernible at the phenotypic level. Inactivation of the x initiation codon resulted in loss of strong expression of the digalactoside epitope and elevated killing by human serum. The failure to detect more than two phenotypes for lic2A, despite clear evidence of weak expression from the z1/z2 initiation codons, leaves open the question of whether or not multiple initiation codons are associated with more complex patterns of phenotypic variation rather than classical phase-variable switching between two phenotypes.