The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed millions of lives to date. Antigenic drift has resulted in viral variants with putatively greater transmissibility, virulence, or both. Early and near real-time detection of these variants of concern (VOC) and the ability to accurately follow their incidence and prevalence in communities is wanting. Wastewater-based epidemiology (WBE), which uses nucleic acid amplification tests to detect viral fragments, is a reliable proxy of COVID-19 incidence and prevalence, and thus offers the potential to monitor VOC viral load in a given population. Here, we describe and validate a primer extension PCR strategy targeting a signature mutation in the N gene of SARS-CoV-2. This allows quantification of B.1.1.7 versus non-B.1.1.7 allele frequency in wastewater without the need to employ quantitative RT-PCR standard curves. We show that the wastewater B.1.1.7 profile correlates with its clinical counterpart and benefits from a near real-time and facile data collection and reporting pipeline. This assay can be quickly implemented within a current SARS-CoV-2 WBE framework with minimal cost; allowing early and contemporaneous estimates of B.1.1.7 community transmission prior to, or in lieu of, clinical screening and identification. Our study demonstrates that this strategy can provide public health units with an additional and much needed tool to rapidly triangulate VOC incidence/prevalence with high sensitivity and lineage specificity.

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed millions of lives globally to date. Rapid accumulation of co-occurring mutations has led to the emergence of viral variants which appear to be more transmissible, virulent, or both. Variants of concern (VOC) now include those belonging to the B.1.1.7, B.1.351, and P.1 lineages. Early detection of VOC and the ability to retrospectively follow their respective, longitudinal prevalence in communities is wanting. Wastewater-based epidemiology (WBE) allows tracking of disease prevalence in the general population using RT-qPCR to detect viral fragments, but ongoing longitudinal studies have yet to differentiate between these variants. Here, we describe and validate a primer extension strategy to amplify and distinguish B.1.1.7-specific, from non-B.1.1.7 alleles by combining new forward, and existing CDC 2019-nCoV_N1 qPCR probes and reverse primers. This assay can be quickly implemented within a current SARS- CoV-2 WBE framework with minimal cost with the goal of providing early detection of increasing B.1.1.7 transmission in a community prior to identification through clinical testing and confirmation via secondary screening strategies. As such, this assay can provide public health units with an additional and much needed metric to be able to rapidly triangulate B.1.1.7 prevalence.

The evolution of antibiotic resistance is influenced by a variety of factors, including the availability of resistance mutations, and the pleiotropic effects of such mutations. Here, we isolate and characterize chromosomal quinolone resistance mutations in E. coli, in order to gain a systematic understanding of the rate and consequences of resistance to this important class of drugs. We isolated over fifty spontaneous resistance mutants on nalidixic acid, ciprofloxacin, and levofloxacin. This set of mutants includes known resistance mutations in gyrA, gyrB, and marR, as well as two novel gyrB mutations. We find that, for most mutations, resistance tends to be higher to nalidixic acid than relative to the other two drugs. Resistance mutations had deleterious impacts on one or more growth parameters, suggesting that quinolone resistance mutations are generally costly. Our findings suggest that the prevalence of specific gyrA alleles amongst clinical isolates are driven by high levels of resistance, at no more cost than other resistance alleles.

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In light of the rising prevalence of antimicrobial resistance (AMR) and the slow pace of new antimicrobial development, there has been increasing interest in the development of adjuvants that improve or restore the effectiveness of existing drugs. Here, we use a novel small RNA (sRNA) screening approach to identify genes whose knockdown increases ciprofloxacin (CIP) sensitivity in a resistant strain of Escherichia coli. 5000 sRNA constructs were initially screened on a gyrA S83L background, ultimately leading to 30 validated genes whose disruption reduces CIP resistance. This set includes genes involved in DNA replication, repair, recombination, efflux, and other regulatory systems. Our findings increase understanding of the functional interactions of DNA Gyrase, and may aid in the development of new therapeutic approaches for combating AMR.