Comparison of analytical performance and economic value of two biosurveillance methods for tracking SARS-COV-2 variants of concern.

The development of biosurveillance programs with strong analytical performance and economically accessible protocols is essential for monitoring viral pathogens. Throughout the COVID-19 pandemic, whole-genome sequencing (WGS) has been the prevailing technology for SARS-CoV-2 variant of concern (VOC) detection. While WGS offers benefits, it is a lengthy process, financially and technically straining for scalable viral tracking. The aim of this study was to compare the analytical performance and economic feasibility of WGS and PCR mutation panels for distinguishing six known VOCs: Alpha (B.1.1.7 and Q.4), Gamma (P.1), Delta (B.1.617.2 and AY.4.2), and Omicron. (B.1.1.529.1). In all, 78 SARS-CoV-2-positive samples were collected from April to December 2021 at Northeastern University (Cabot Testing Site, Boston, MA, USA) for genotyping PCR and WGS analysis. MagMax Viral/Pathogen II Nucleic Acid Isolation and TaqPath COVID-19 Combo Kits were used for RNA extraction and SARS-CoV-2 confirmation. VOC discrimination was assessed using two TaqMan SARS-CoV-2 single nucleotide polymorphism (SNP) assay layouts, and Ion Torrent WGS. In November 2021, the mutation panel demonstrated marked versatility by detecting the emerging Omicron variant reported by South Africa. SNP panel analysis yielded the following 78 VOC identifications: Alpha B.1.1.7 (N = 20), Alpha Q.4 (N = 3), Gamma P.1 (N = 1), Delta B.1.617.2 (N = 30), Delta AY.4.2 (N = 3), and Omicron B.1.1.529.1 (N = 20) with one undetermined (N = 1) sample. Genotyping mutation panels designated lineages in 77 of 78 samples, 46/78 were confirmed by WGS, while 32 samples failed WGS lineage assignment. RT-PCR genotyping panels offer pronounced throughput and sensitivity and provide an economically advantageous technique for SARS-CoV-2 biosurveillance.IMPORTANCEThe results presented in our manuscript demonstrate how the value of simplistic and reliable molecular assays coupled with the core scientific principle of standardization can be overlooked by the charm of more sophisticated assays and instrumentation. This effect can often be amplified during tumultuous public health events, such as the COVID-19 pandemic. By adapting standardized PCR mutation panels to detect prominently circulating SARS-CoV-2 variants, we were able to better assess the potential health impacts of rising positivity rates and transmission clusters within the Northeastern University population. While several literature publications utilizing genotyping PCR and NGS have a similar scope to ours, many investigations lack sufficiently standardized genotyping PCR and NGS bioinformatics inclusionary/exclusionary criteria for SARS-CoV-2 variant identification. Finally, the economic benefits of standardized PCR mutation panels would allow for global implementation of biosurveillance, rather than reserving biosurveillance to more economically developed nations.

Expanded PCR Panel Testing for Identification of Respiratory Pathogens and Coinfections in Influenza-like Illness.

While COVID-19 has dominated Influenza-like illness (ILI) over the past few years, there are many other pathogens responsible for ILI. It is not uncommon to have coinfections with multiple pathogens in patients with ILI. The goal of this study was to identify the different organisms in symptomatic patients presenting with ILI using two different high throughput multiplex real time PCR platforms. Specimens were collected from 381 subjects presenting with ILI symptoms. All samples (nasal and nasopharyngeal swabs) were simultaneously tested on two expanded panel PCR platforms: Applied Biosystems™ TrueMark™ Respiratory Panel 2.0, OpenArray™ plate (OA) (32 viral and bacterial targets); and Applied Biosystems™ TrueMark™ Respiratory Panel 2.0, TaqMan™ Array card (TAC) (41 viral, fungal, and bacterial targets). Results were analyzed for concordance between the platforms and for identification of organisms responsible for the clinical presentation including possible coinfections. Very good agreement was observed between the two PCR platforms with 100% agreement for 12 viral and 3 bacterial pathogens. Of 381 specimens, approximately 58% of the samples showed the presence of at least one organism with an important incidence of co-infections (~36-40% of positive samples tested positive for two and more organisms). S. aureus was the most prevalent detected pathogen (~30%) followed by SARS-CoV-2 (~25%), Rhinovirus (~15%) and HHV6 (~10%). Co-infections between viruses and bacteria were the most common (~69%), followed by viral-viral (~23%) and bacterial-bacterial (~7%) co-infections. These results showed that coinfections are common in RTIs suggesting that syndromic panel based multiplex PCR tests could enable the identification of pathogens contributing to coinfections, help guide patient management thereby improving clinical outcomes and supporting antimicrobial stewardship.

Baseline procalcitonin as a predictor of bacterial infection and clinical outcomes in COVID-19: A case-control study.

PURPOSE: Coronavirus disease-2019 (COVID-19) is associated with a wide spectrum of clinical symptoms including acute respiratory failure. Biomarkers that can predict outcomes in patients with COVID-19 can assist with patient management. The aim of this study is to evaluate whether procalcitonin (PCT) can predict clinical outcome and bacterial superinfection in patients infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). METHODS: Adult patients diagnosed with SARS-CoV-2 by nasopharyngeal PCR who were admitted to a tertiary care center in Boston, MA with SARS-CoV-2 infection between March 17 and April 30, 2020 with a baseline PCT value were studied. Patients who were presumed positive for SARS-CoV-2, who lacked PCT levels, or who had a positive urinalysis with negative cultures were excluded. Demographics, clinical and laboratory data were extracted from the electronic medical records. RESULTS: 324 patient charts were reviewed and grouped by clinical and microbiologic outcomes by day 28. Baseline PCT levels were significantly higher for patients who were treated for true bacteremia (p = 0.0005) and bacterial pneumonia (p = 0.00077) compared with the non-bacterial infection group. Baseline PCT positively correlated with the NIAID ordinal scale and survival over time. When compared to other inflammatory biomarkers, PCT showed superiority in predicting bacteremia. CONCLUSIONS: Baseline PCT levels are associated with outcome and bacterial superinfection in patients hospitalized with SARS-CoV-2.