Validation and Establishment of the SARS-CoV-2 Lentivirus Surrogate Neutralization Assay as a Prescreening Tool for the Plaque Reduction Neutralization Test.

Neutralization assays are important for understanding and quantifying neutralizing antibody responses toward severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The SARS-CoV-2 lentivirus surrogate neutralization assay (SCLSNA) can be used in biosafety level 2 (BSL-2) laboratories and has been shown to be a reliable alternative approach to the plaque reduction neutralization test (PRNT). In this study, we optimized and validated the SCLSNA to assess its ability as a comparator and prescreening method to support the PRNT. Comparability between the PRNT and SCLSNA was determined through clinical sensitivity and specificity evaluations. Clinical sensitivity and specificity assays produced acceptable results, with 100% (95% confidence interval [CI], 94% to 100%) specificity and 100% (95% CI, 94% to 100%) sensitivity against ancestral Wuhan spike-pseudotyped lentivirus. The sensitivity and specificity against B.1.1.7 spike-pseudotyped lentivirus were 88.3% (95% CI, 77.8% to 94.2%) and 100% (95% CI, 94% to 100%), respectively. Assay precision measuring intra-assay variability produced acceptable results for high (50% PRNT [PRNT50], 1:≥640), mid (PRNT50, 1:160), and low (PRNT50, 1:40) antibody titer concentration ranges based on the PRNT50, with coefficients of variation (CVs) of 14.21%, 12.47%, and 13.28%, respectively. Intermediate precision indicated acceptable ranges for the high and mid concentrations, with CVs of 15.52% and 16.09%, respectively. However, the low concentration did not meet the acceptance criteria, with a CV of 26.42%. Acceptable ranges were found in the robustness evaluation for both intra-assay and interassay variability. In summary, the validation parameters tested met the acceptance criteria, making the SCLSNA method fit for its intended purpose, which can be used to support the PRNT. IMPORTANCE Neutralization studies play an important role in providing guidance and justification for vaccine administration and helping prevent the spread of diseases. The neutralization data generated in our laboratory have been included in the decision-making process of the National Advisory Committee on Immunization (NACI) in Canada. During the coronavirus 2019 (COVID-19) pandemic, the plaque reduction neutralization test (PRNT) has been the gold standard for determining neutralization of SARS-CoV-2. We validated a SARS-CoV-2 lentivirus surrogate neutralization assay (SCLSNA) as an alternative method to help support the PRNT. The advantages of using the SCLSNA is that it can process more samples, is less tedious to perform, and can be used in laboratories with a lower biosafety level. The use of the SCLSNA can further expand our capabilities to help fulfill the requirements for NACI and other important collaborations.

Human Papillomavirus 16 E6 and E7 Oncoproteins Alter the Abundance of Proteins Associated with DNA Damage Response, Immune Signaling and Epidermal Differentiation.

The high-risk human papillomaviruses are oncogenic viruses associated with almost all cases of cervical carcinomas, and increasing numbers of anal, and oral cancers. Two oncogenic HPV proteins, E6 and E7, are capable of immortalizing keratinocytes and are required for HPV associated cell transformation. Currently, the influence of these oncoproteins on the global regulation of the host proteome is not well defined. Liquid chromatography coupled with quantitative tandem mass spectrometry using isobaric-tagged peptides was used to investigate the effects of the HPV16 oncoproteins E6 and E7 on protein levels in human neonatal keratinocytes (HEKn). Pathway and gene ontology enrichment analyses revealed that the cells expressing the HPV oncoproteins have elevated levels of proteins related to interferon response, inflammation and DNA damage response, while the proteins related to cell organization and epithelial development are downregulated. This study identifies dysregulated pathways and potential biomarkers associated with HPV oncoproteins in primary keratinocytes which may have therapeutic implications. Most notably, DNA damage response pathways, DNA replication, and interferon signaling pathways were affected in cells transduced with HPV16 E6 and E7 lentiviruses. Moreover, proteins associated with cell organization and differentiation were significantly downregulated in keratinocytes expressing HPV16 E6 + E7. High-risk HPV E6 and E7 oncoproteins are necessary for the HPV-associated transformation of keratinocytes. However their influence on the global dysregulation of keratinocyte proteome is not well documented. Here shotgun proteomics using TMT-labeling detected over 2500 significantly dysregulated proteins associated with E6 and E7 expression. Networks of proteins related to interferon response, inflammation and DNA damage repair pathways were altered.

Clinical Metagenomics Is Increasingly Accurate and Affordable to Detect Enteric Bacterial Pathogens in Stool.

Stool culture is the gold standard method to diagnose enteric bacterial infections; however, many clinical laboratories are transitioning to syndromic multiplex PCR panels. PCR is rapid, accurate, and affordable, yet does not yield subtyping information critical for foodborne disease surveillance. A metagenomics-based stool testing approach could simultaneously provide diagnostic and public health information. Here, we evaluated shotgun metagenomics to assess the detection of common enteric bacterial pathogens in stool. We sequenced 304 stool specimens from 285 patients alongside routine diagnostic testing for Salmonella spp., Campylobacter spp., Shigella spp., and shiga-toxin producing Escherichia coli. Five analytical approaches were assessed for pathogen detection: microbiome profiling, Kraken2, MetaPhlAn, SRST2, and KAT-SECT. Among analysis tools and databases compared, KAT-SECT analysis provided the best sensitivity and specificity for all pathogens tested compared to culture (91.2% and 96.2%, respectively). Where metagenomics detected a pathogen in culture-negative specimens, standard PCR was positive 85% of the time. The cost of metagenomics is approaching the current combined cost of PCR, reflex culture, and whole genome sequencing for pathogen detection and subtyping. As cost, speed, and analytics for single-approach metagenomics improve, it may be more routinely applied in clinical and public health laboratories.

Evaluation of a commercially-available surrogate virus neutralization test for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).

There remains an urgent need for assays to quantify humoral protective immunity to SARS-CoV-2 to understand the immune responses of COVID-19 patients, evaluate efficacy of vaccine candidates in clinical trials, and conduct large-scale epidemiological studies. The plaque-reduction neutralization test (PRNT) is the reference-standard for quantifying antibodies capable of neutralizing SARS-CoV-2. However, the PRNT is logistically demanding, time-consuming, and requires containment level-3 facilities to safely work with live virus. In contrast, a surrogate virus neutralization test (sVNT) manufactured by Genscript is a quick and simple assay that detects antibodies that inhibit the RBD-ACE2 interaction, crucial for virus entry into host cells. In this study, we evaluate the sensitivity, specificity, and cross-reactivity of the sVNT compared with the PRNT using both 50% and 90% SARS-CoV-2 neutralization as a reference-standard. We found that the sVNT provides a high-throughput screening tool prior to confirmatory PRNT testing for the evaluation of SARS-CoV-2 neutralizing antibodies.

Systematic evaluation of supervised machine learning for sample origin prediction using metagenomic sequencing data.

BACKGROUND: The advent of metagenomic sequencing provides microbial abundance patterns that can be leveraged for sample origin prediction. Supervised machine learning classification approaches have been reported to predict sample origin accurately when the origin has been previously sampled. Using metagenomic datasets provided by the 2019 CAMDA challenge, we evaluated the influence of variable technical, analytical and machine learning approaches for result interpretation and novel source prediction. RESULTS: Comparison between 16S rRNA amplicon and shotgun sequencing approaches as well as metagenomic analytical tools showed differences in normalized microbial abundance, especially for organisms present at low abundance. Shotgun sequence data analyzed using Kraken2 and Bracken, for taxonomic annotation, had higher detection sensitivity. As classification models are limited to labeling pre-trained origins, we took an alternative approach using Lasso-regularized multivariate regression to predict geographic coordinates for comparison. In both models, the prediction errors were much higher in Leave-1-city-out than in 10-fold cross validation, of which the former realistically forecasted the increased difficulty in accurately predicting samples from new origins. This challenge was further confirmed when applying the model to a set of samples obtained from new origins. Overall, the prediction performance of the regression and classification models, as measured by mean squared error, were comparable on mystery samples. Due to higher prediction error rates for samples from new origins, we provided an additional strategy based on prediction ambiguity to infer whether a sample is from a new origin. Lastly, we report increased prediction error when data from different sequencing protocols were included as training data. CONCLUSIONS: Herein, we highlight the capacity of predicting sample origin accurately with pre-trained origins and the challenge of predicting new origins through both regression and classification models. Overall, this work provides a summary of the impact of sequencing technique, protocol, taxonomic analytical approaches, and machine learning approaches on the use of metagenomics for prediction of sample origin.

MrBac: a web server for draft metabolic network reconstructions for bacteria.

Genome-scale metabolic network reconstruction can be used for simulating cellular behaviors by simultaneously monitoring thousands of biochemical reactions, and is therefore important for systems biology studies in microbes. However, the labor-intensive and time-consuming reconstruction process has hindered the progress of this important field. Here we present a web server, MrBac (Metabolic network Reconstructions for Bacteria), to streamline the network reconstruction process for draft genome-scale metabolic networks and to provide annotation information from multiple databases for further curation of the draft reconstructions. MrBac integrates comparative genomics, retrieval of genome annotations, and generation of standard systems biology file format ready for network analyses. We also used MrBac to automatically generate a draft metabolic model of Salmonella enteric serovar Typhimurium LT2. The high similarity between this automatic model and the experimentally validated models further supports the usefulness and accuracy of MrBac. The high efficiency and accuracy of MrBac may accelerate the advances of systems biology studies on microbiology. MrBac is freely available at http://sb.nhri.org.tw/MrBac.