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DeHoff, P.

Publications and source records attributed to DeHoff, P..

2 recordsLinked to original sources

Comparison of heat-inactivated and infectious SARS-CoV-2 across indoor surface materials shows comparable RT-qPCR viral signal intensity and persistence

Environmental monitoring in public spaces can be used to identify surfaces contaminated by persons with COVID-19 and inform appropriate infection mitigation responses. Research groups have reported detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) on surfaces days or weeks after the virus has been deposited, making it difficult to estimate when an infected individual may have shed virus onto a SARS-CoV-2 positive surface, which in turn complicates the process of establishing effective quarantine measures. In this study, we determined that reverse transcription-quantitative polymerase chain reaction (RT-qPCR) detection of viral RNA from heat-inactivated particles experiences minimal decay over seven days of monitoring on eight out of nine surfaces tested. The properties of the studied surfaces result in RT-qPCR signatures that can be segregated into two material categories, rough and smooth, where smooth surfaces have a lower limit of detection. RT-qPCR signal intensity (average quantification cycle (Cq)) can be correlated to surface viral load using only one linear regression model per material category. The same experiment was performed with infectious viral particles on one surface from each category, with essentially identical results. The stability of RT-qPCR viral signal demonstrates the need to clean monitored surfaces after sampling to establish temporal resolution. Additionally, these findings can be used to minimize the number of materials and time points tested and allow for the use of heat-inactivated viral particles when optimizing environmental monitoring methods. ImportanceEnvironmental monitoring is an important tool for public health surveillance, particularly in settings with low rates of diagnostic testing. Time between sampling public environments, such as hospitals or schools, and notifying stakeholders of the results should be minimal, allowing decisions to be made towards containing outbreaks of coronavirus disease 2019 (COVID-19). The Safer At School Early Alert program (SASEA) [1], a large-scale environmental monitoring effort in elementary school and child care settings, has processed > 13,000 surface samples for SARS-CoV-2, detecting viral signals from 574 samples. However, consecutive detection events necessitated the present study to establish appropriate response practices around persistent viral signals on classroom surfaces. Other research groups and clinical labs developing environmental monitoring methods may need to establish their own correlation between RT - qPCR results and viral load, but this work provides evidence justifying simplified experimental designs, like reduced testing materials and the use of heat-inactivated viral particles.

microbiology↗

Comparison of miRNA profiling methods using synthetic miRNA pools and standardized exRNA samples reveals substantial performance differences

MicroRNAs (miRNAs) found in biofluids play functional roles in health and in disease pathogenesis, underpinning their potential as clinical biomarkers. Several platforms for measurement of extracellular RNAs have recently become available. We evaluated the reproducibility, accuracy, sensitivity, and specificity of four miRNA quantification platforms, including one widely used discovery approach (small RNA-seq) and three targeted platforms (FirePlex, EdgeSeq, and nCounter). Using pools of synthetic miRNAs, we observed that reproducibility was highest for RNA-seq and EdgeSeq, that all three targeted platforms had lower bias than RNA-seq, and that RNA-seq had the best ability to distinguish between present and absent sequences. Overall reproducibility was lower for plasma samples than synthetic miRNA pools. We compared expression of placental miRNAs in plasma from pregnant and non-pregnant women and observed expected differences with RNA-seq and EdgeSeq, but not FirePlex or nCounter. We conclude that differences in performance among miRNA profiling platforms impact their relative utility as potential assay systems for clinical biomarkers.

genomics↗