Digital PCR Discriminates between SARS-CoV-2 Omicron Variants and Immune Escape Mutations.

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve, mutations arise that will allow the virus to evade immune defenses and therapeutics. Assays that can identify these mutations can be used to guide personalized patient treatment plans. Digital PCR (dPCR) is a fast and reliable complement to whole-genome sequencing that can be used to discriminate single nucleotide polymorphisms (SNPs) in template molecules. Here, we developed a panel of SARS-CoV-2 dPCR assays and demonstrate its applications for typing variant lineages and therapeutic monoclonal antibody resistance. We first designed multiplexed dPCR assays for SNPs located at residue 3395 in the orf1ab gene that differentiate the Delta, Omicron BA.1, and Omicron BA.2 lineages. We demonstrate their effectiveness on 596 clinical saliva specimens that were sequence verified using Illumina whole-genome sequencing. Next, we developed dPCR assays for spike mutations R346T, K444T, N460K, F486V, and F486S, which are associated with host immune evasion and reduced therapeutic monoclonal antibody efficacy. We demonstrate that these assays can be run individually or multiplexed to detect the presence of up to 4 SNPs in a single assay. We perform these dPCR assays on 81 clinical saliva SARS-CoV-2-positive specimens and properly identify mutations in Omicron subvariants BA.2.75.2, BM.1.1, BN.1, BF.7, BQ.1, BQ.1.1, and XBB. Thus, dPCR could serve as a useful tool to determine if clinical specimens contain therapeutically relevant mutations and inform patient treatment. IMPORTANCE Spike mutations in the SARS-CoV-2 genome confer resistance to therapeutic monoclonal antibodies. Authorization for treatment options is typically guided by general trends of variant prevalence. For example, bebtelovimab is no longer authorized for emergency use in the United States due to the increased prevalence of antibody-resistant BQ.1, BQ.1.1, and XBB Omicron subvariants. However, this blanket approach limits access to life-saving treatment options to patients who are otherwise infected with susceptible variants. Digital PCR assays targeting specific mutations can complement whole-genome sequencing approaches to genotype the virus. In this study, we demonstrate the proof of concept that dPCR can be used to type lineage defining and monoclonal antibody resistance-associated mutations in saliva specimens. These findings show that digital PCR could be used as a personalized diagnostic tool to guide individual patient treatment.

Comparison of nucleocapsid and spike antibody ELISAs for determining SARS-CoV-2 seropositivity in Kenyan women and infants.

A multitude of enzyme-linked immunosorbent assays (ELISAs) has been developed to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies since the coronavirus disease 2019 pandemic started in late 2019. Assessing the reliability of these assays in diverse global populations is critical. This study compares the use of the commercially available Platelia Total Ab Assay (Bio-Rad) nucleocapsid ELISA to the widely used Mount Sinai spike IgG ELISA in a Kenyan population seroprevalence study. Using longitudinal plasma specimens collected from a mother-infant cohort living in Nairobi, Kenya between May 2019 and December 2020, this study demonstrates that the two assays have a high qualitative agreement (92.7%) and strong correlation of antibody levels (R2 = 0.973) in repeated measures. Within this cohort, seroprevalence detected by either ELISA closely resembled previously published seroprevalence estimates for Kenya during the sampling period and no significant difference in the incidence of SARS-CoV-2 antibody detection by either assay was observed. Assay comparability was not affected by HIV exposure status. These data support the use of the Platelia SARS-CoV-2 Total Ab ELISA as a suitable high-throughput method for seroprevalence studies in Kenya.

HIV and SARS-CoV-2 infection in postpartum Kenyan women and their infants.

BACKGROUND: HIV may increase SARS-CoV-2 infection risk and COVID-19 severity generally, but data are limited about its impact on postpartum women and their infants. As such, we characterized SARS-CoV-2 infection among mother-infant pairs in Nairobi, Kenya. METHODS: We conducted a nested study of 62 HIV-uninfected and 64 healthy women living with HIV, as well as their HIV-exposed uninfected (N = 61) and HIV-unexposed (N = 64) infants, participating in a prospective cohort. SARS-CoV-2 serology was performed on plasma collected between May 1, 2020-February 1, 2022 to determine the incidence, risk factors, and symptoms of infection. SARS-CoV-2 RNA PCR and sequencing was also performed on available stool samples from seropositive participants. RESULTS: SARS-CoV-2 seropositivity was found in 66% of the 126 mothers and in 44% of the 125 infants. There was no significant association between SARS-CoV-2 infection and maternal HIV (Hazard Ratio [HR] = 0.810, 95% CI: 0.517-1.27) or infant HIV exposure (HR = 1.47, 95% CI: 0.859-2.53). Maternal SARS-CoV-2 was associated with a two-fold increased risk of infant infection (HR = 2.31, 95% CI: 1.08-4.94). Few participants (13% mothers, 33% infants) had symptoms; no participant experienced severe COVID-19 or death. Seroreversion occurred in about half of mothers and infants. SARS-CoV-2 sequences obtained from stool were related to contemporaneously circulating variants. CONCLUSIONS: These data indicate that postpartum Kenyan women and their infants were at high risk for SARS-CoV-2 infection and that antibody responses waned over an average of 8-10 months. However, most cases were asymptomatic and healthy women living with HIV did not have a substantially increased risk of infection or severe COVID-19.

Baseline Sequencing Surveillance of Public Clinical Testing, Hospitals, and Community Wastewater Reveals Rapid Emergence of SARS-CoV-2 Omicron Variant of Concern in Arizona, USA.

The adaptive evolution of SARS-CoV-2 variants is driven by selection for increased viral fitness in transmissibility and immune evasion. Understanding the dynamics of how an emergent variant sweeps across populations can better inform public health response preparedness for future variants. Here, we investigated the state-level genomic epidemiology of SARS-CoV-2 through baseline genomic sequencing surveillance of 27,071 public testing specimens and 1,125 hospital inpatient specimens diagnosed between November 1, 2021, and January 31, 2022, in Arizona. We found that the Omicron variant rapidly displaced Delta variant in December 2021, leading to an "Omicron surge" of COVID-19 cases in early 2022. Wastewater sequencing surveillance of 370 samples supported the synchronous sweep of Omicron in the community. Hospital inpatient COVID-19 cases of Omicron variant presented to three major hospitals 10.51 days after its detection from public clinical testing. Nonsynonymous mutations in nsp3, nsp12, and nsp13 genes were significantly associated with Omicron hospital cases compared to community cases. To model SARS-CoV-2 transmissions across the state population, we developed a scalable sequence network methodology and showed that the Omicron variant spread through intracounty and intercounty transmissions. Finally, we demonstrated that the temporal emergence of Omicron BA.1 to become the dominant variant (17.02 days) was 2.3 times faster than the prior Delta variant (40.70 days) or subsequent Omicron sublineages BA.2 (39.65 days) and BA.5 (35.38 days). Our results demonstrate the uniquely rapid sweep of Omicron BA.1. These findings highlight how integrated public health surveillance can be used to enhance preparedness and response to future variants. IMPORTANCE SARS-CoV-2 continues to evolve new variants throughout the pandemic. However, the temporal dynamics of how SARS-CoV-2 variants emerge to become the dominant circulating variant is not precisely known. Genomic sequencing surveillance offers unique insights into how SARS-CoV-2 spreads in communities and the lead-up to hospital cases during a surge. Specifically, baseline sequencing surveillance through random selection of positive diagnostic specimens provides a representative outlook of the virus lineages circulating in a geographic region. Here, we investigated the emergence of the Omicron variant of concern in Arizona by leveraging baseline genomic sequence surveillance of public clinical testing, hospitals, and community wastewater. We tracked the spread and evolution of the Omicron variant as it first emerged in the general public, and its rapid shift in hospital admissions in the state health system. This study demonstrates the timescale of public health preparedness needed to respond to an antigenic shift in SARS-CoV-2.

Leveraging an established neighbourhood-level, open access wastewater monitoring network to address public health priorities: a population-based study.

BACKGROUND: Before the COVID-19 pandemic, the US opioid epidemic triggered a collaborative municipal and academic effort in Tempe, Arizona, which resulted in the world's first open access dashboard featuring neighbourhood-level trends informed by wastewater-based epidemiology (WBE). This study aimed to showcase how wastewater monitoring, once established and accepted by a community, could readily be adapted to respond to newly emerging public health priorities. METHODS: In this population-based study in Greater Tempe, Arizona, an existing opioid monitoring WBE network was modified to track SARS-CoV-2 transmission through the analysis of 11 contiguous wastewater catchments. Flow-weighted and time-weighted 24 h composite samples of untreated wastewater were collected at each sampling location within the wastewater collection system for 3 days each week (Tuesday, Thursday, and Saturday) from April 1, 2020, to March 31, 2021 (Area 7 and Tempe St Luke's Hospital were added in July, 2020). Reverse transcription quantitative PCR targeting the E gene of SARS-CoV-2 isolated from the wastewater samples was used to determine the number of genome copies in each catchment. Newly detected clinical cases of COVID-19 by zip code within the City of Tempe, Arizona were reported daily by the Arizona Department of Health Services from May 23, 2020. Maricopa County-level new positive cases, COVID-19-related hospitalisations, deaths, and long-term care facility deaths per day are publicly available and were collected from the Maricopa County Epidemic Curve Dashboard. Viral loads of SARS-CoV-2 (genome copies per day) measured in wastewater from each catchment were aggregated at the zip code level and city level and compared with the clinically reported data using root mean square error to investigate early warning capability of WBE. FINDINGS: Between April 1, 2020, and March 31, 2021, 1556 wastewater samples were analysed. Most locations showed two waves in viral levels peaking in June, 2020, and December, 2020-January, 2021. An additional wave of viral load was seen in catchments close to Arizona State University (Areas 6 and 7) at the beginning of the fall (autumn) semester in late August, 2020. Additionally, an early infection hotspot was detected in the Town of Guadalupe, Arizona, starting the week of May 4, 2020, that was successfully mitigated through targeted interventions. A shift in early warning potential of WBE was seen, from a leading (mean of 8·5 days [SD 2·1], June, 2020) to a lagging (-2·0 days [1·4], January, 2021) indicator compared with newly reported clinical cases. INTERPRETATION: Lessons learned from leveraging an existing neighbourhood-level WBE reporting dashboard include: (1) community buy-in is key, (2) public data sharing is effective, and (3) sub-ZIP-code (postal code) data can help to pinpoint populations at risk, track intervention success in real time, and reveal the effect of local clinical testing capacity on WBE's early warning capability. This successful demonstration of transitioning WBE efforts from opioids to COVID-19 encourages an expansion of WBE to tackle newly emerging and re-emerging threats (eg, mpox and polio). FUNDING: National Institutes of Health's RADx-rad initiative, National Science Foundation, Virginia G Piper Charitable Trust, J M Kaplan Fund, and The Flinn Foundation.

One health genomic surveillance and response to a university-based outbreak of the SARS-CoV-2 Delta AY.25 lineage, Arizona, 2021.

Genomic surveillance and wastewater tracking strategies were used to strengthen the public health response to an outbreak of the SARS-CoV-2 Delta AY.25 lineage associated with a university campus in Arizona. Epidemiologic and clinical data routinely gathered through contact tracing were matched to SARS-CoV-2 genomes belonging to an outbreak of AY.25 identified through ongoing phylogenomic analyses. Continued phylogenetic analyses were conducted to further describe the AY.25 outbreak. Wastewater collected twice weekly from sites across campus was tested for SARS-CoV-2 by RT-qPCR, and subsequently sequenced to identify variants. The AY.25 outbreak was defined by a single mutation (C18804T) and comprised 379 genomes from SARS-CoV-2 positive cases associated with the university and community. Several undergraduate student gatherings and congregate living settings on campus likely contributed to the rapid spread of COVID-19 across the university with secondary transmission into the community. The clade defining mutation was also found in wastewater samples collected from around student dormitories a week before the semester began, and 9 days before cases were identified. Genomic, epidemiologic, and wastewater surveillance provided evidence that an AY.25 clone was likely imported into the university setting just prior to the onset of the Fall 2021 semester, rapidly spread through a subset of the student population, and then subsequent spillover occurred in the surrounding community. The university and local public health department worked closely together to facilitate timely reporting of cases, identification of close contacts, and other necessary response and mitigation strategies. The emergence of new SARS-CoV-2 variants and potential threat of other infectious disease outbreaks on university campuses presents an opportunity for future comprehensive One Health genomic data driven, targeted interventions.

SARS-CoV-2 Delta Variant N Gene Mutations Reduce Sensitivity to the TaqPath COVID-19 Multiplex Molecular Diagnostic Assay.

As the SARS-CoV-2 virus evolves, mutations may result in diminished sensitivity to qRT-PCR diagnostic assays. We investigated four polymorphisms circulating in the SARS-CoV-2 Delta lineage that result in N gene target failure (NGTF) on the TaqPath COVID-19 Combo Kit. These mutations were detected from the SARS-CoV-2 genome sequences that matched with the diagnostic assay results of saliva specimens. Full length N genes from the samples displaying NGTF were cloned into plasmids and assayed using three SARS-CoV-2 qRT-PCR assays. These constructs resulted in reduced sensitivity to the TaqPath COVID-19 Combo Kit compared to the controls (mean Ct differences of 3.06, 7.70, 12.46, and 14.12), but were detected equivalently on the TaqPath COVID-19 Fast PCR Combo 2.0 or CDC 2019_nCoV_N2 assays. This work highlights the importance of genomic sequencing to monitor circulating mutations and provide guidance in improving diagnostic assays.

Extensive Wastewater-Based Epidemiology as a Resourceful Tool for SARS-CoV-2 Surveillance in a Low-to-Middle-Income Country through a Successful Collaborative Quest: WBE, Mobility, and Clinical Tests

The COVID-19 pandemic has challenged healthcare systems worldwide. Efforts in low-to-middle-income countries (LMICs) cannot keep stride with infection rates, especially during peaks. A strong international collaboration between Arizona State University (ASU), Tec de Monterrey (TEC), and Servicios de Agua y Drenaje de Monterrey (Local Water Utilities) is acting to integrate wastewater-based epidemiology (WBE) of SARS-CoV-2 in the region as a complementary approach to aid the healthcare system. Wastewater was collected from four sewer catchments in the Monterrey Metropolitan area in Mexico (pop. 4,643,232) from mid-April 2020 to February 2021 (44 weeks, n = 644). Raw wastewater was filtered and filter-concentrated, the RNA was extracted using columns, and the Charité/Berlin protocol was used for the RT-qPCR. The viral loads obtained between the first (June 2020) and second waves (February 2021) of the pandemic were similar;in contrast, the clinical cases were fewer during the first wave, indicating poor coverage. During the second wave of the pandemic, the SARS-CoV-2 quantification in wastewater increased 14 days earlier than the COVID-19 clinical cases reported. This is the first long-term WBE study in Mexico and demonstrates its value in pandemic management.

University-Associated SARS-CoV-2 Omicron BA.2 Infections, Maricopa County, Arizona, USA, 2022.

We investigated a university-affiliated cohort of SARS-CoV-2 Omicron BA.2 infections in Arizona, USA. Of 44 cases, 43 were among students; 26 persons were symptomatic, 8 sought medical care, but none were hospitalized. Most (55%) persons had completed a primary vaccine series; 8 received booster vaccines. BA.2 infection was mild in this young cohort.

Genomic Sequencing of SARS-CoV-2 E484K Variant B.1.243.1, Arizona, USA.

Genomic surveillance can provide early insights into new circulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. While conducting genomic surveillance (1,663 cases) from December 2020-April 2021 in Arizona, USA, we detected an emergent E484K-harboring variant, B.1.243.1. This finding demonstrates the importance of real-time SARS-CoV-2 surveillance to better inform public health responses.

High-throughput sequencing of SARS-CoV-2 in wastewater provides insights into circulating variants.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) likely 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 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 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.

An Early Pandemic Analysis of SARS-CoV-2 Population Structure and Dynamics in Arizona.

In December of 2019, a novel coronavirus, SARS-CoV-2, emerged in the city of Wuhan, China, causing severe morbidity and mortality. Since then, the virus has swept across the globe, causing millions of confirmed infections and hundreds of thousands of deaths. To better understand the nature of the pandemic and the introduction and spread of the virus in Arizona, we sequenced viral genomes from clinical samples tested at the TGen North Clinical Laboratory, the Arizona Department of Health Services, and those collected as part of community surveillance projects at Arizona State University and the University of Arizona. Phylogenetic analysis of 84 genomes from across Arizona revealed a minimum of 11 distinct introductions inferred to have occurred during February and March. We show that >80% of our sequences descend from strains that were initially circulating widely in Europe but have since dominated the outbreak in the United States. In addition, we show that the first reported case of community transmission in Arizona descended from the Washington state outbreak that was discovered in late February. Notably, none of the observed transmission clusters are epidemiologically linked to the original travel-related case in the state, suggesting successful early isolation and quarantine. Finally, we use molecular clock analyses to demonstrate a lack of identifiable, widespread cryptic transmission in Arizona prior to the middle of February 2020.IMPORTANCE As the COVID-19 pandemic swept across the United States, there was great differential impact on local and regional communities. One of the earliest and hardest hit regions was in New York, while at the same time Arizona (for example) had low incidence. That situation has changed dramatically, with Arizona now having the highest rate of disease increase in the country. Understanding the roots of the pandemic during the initial months is essential as the pandemic continues and reaches new heights. Genomic analysis and phylogenetic modeling of SARS-COV-2 in Arizona can help to reconstruct population composition and predict the earliest undetected introductions. This foundational work represents the basis for future analysis and understanding as the pandemic continues.