Quantity of SARS-CoV-2 RNA copies exhaled per minute during natural breathing over the course of COVID-19 infection.

SARS-CoV-2 is spread through exhaled breath of infected individuals. A fundamental question in understanding transmission of SARS-CoV-2 is how much virus an individual is exhaling into the environment while they breathe, over the course of their infection. Research on viral load dynamics during COVID-19 infection has focused on internal swab specimens, which provide a measure of viral loads inside the respiratory tract, but not on breath. Therefore, the dynamics of viral shedding on exhaled breath over the course of infection are poorly understood. Here, we collected exhaled breath specimens from COVID-19 patients and used RTq-PCR to show that numbers of exhaled SARS-CoV-2 RNA copies during COVID-19 infection do not decrease significantly until day 8 from symptom-onset. COVID-19-positive participants exhaled an average of 80 SARS-CoV-2 viral RNA copies per minute during the first 8 days of infection, with significant variability both between and within individuals, including spikes over 800 copies a minute in some patients. After day 8, there was a steep drop to levels nearing the limit of detection, persisting for up to 20 days. We further found that levels of exhaled viral RNA increased with self-rated symptom-severity, though individual variation was high. Levels of exhaled viral RNA did not differ across age, sex, time of day, vaccination status or viral variant. Our data provide a fine-grained, direct measure of the number of SARS-CoV-2 viral copies exhaled per minute during natural breathing-including 312 breath specimens collected multiple times daily over the course of infection-in order to fill an important gap in our understanding of the time course of exhaled viral loads in COVID-19.

Validation of Whole Genome Methylation Profiling Classifier for Central Nervous System Tumors.

The 2021 WHO Classification of Tumors of the Central Nervous System includes several tumor types and subtypes for which the diagnosis is at least partially reliant on utilization of whole genome methylation profiling. The current approach to array DNA methylation profiling utilizes a reference library of tumor DNA methylation data, and a machine learning-based tumor classifier. This approach was pioneered and popularized by the German Cancer Research Network (DKFZ) and University Hospital Heidelberg. This research group has kindly made their classifier for central nervous system tumors freely available as a research tool via a web-based portal. However, their classifier is not maintained in a clinical testing environment. Therefore, the Northwestern Medicine (NM) classifier was developed and validated. The NM classifier was validated using the same training and validation data sets as the DKFZ group. Using the DKFZ validation data set, the NM classifier's performance showed high concordance (92%) and comparable accuracy (specificity 94.0% versus 84.9% for DKFZ, sensitivity 88.6% versus 94.7% for DKFZ). Receiver-operator characteristic curves showed areas under the curve of 0.964 versus 0.966 for NM and DKFZ classifiers, respectively. In addition, in-house validation was performed and performance was compared using both classifiers. The NM classifier performed comparably well and is currently offered for clinical testing.

Pulsed-field gel electrophoresis genotyping of Taylorella equigenitalis isolates collected in the United States from 1978 to 2010.

Taylorella equigenitalis is the etiologic agent of contagious equine metritis (CEM), a venereal disease of horses. A total of 82 strains of T. equigenitalis isolated in the United States were analyzed by pulsed-field gel electrophoresis (PFGE) after digestion of genomic DNA with restriction enzyme ApaI. Twenty-eight of those strains isolated from horses in the 2009 U.S. outbreak (CEM09) were further analyzed with NotI and NaeI enzymes. When ApaI alone was used for analysis, the 82 isolates clustered into 15 different genotypes that clearly defined groups of horses with known epidemiological connections. The PFGE profiles of the CEM09 isolates were indistinguishable after digestion with ApaI, NotI, and NaeI and did not match those of isolates from previous U.S. outbreaks in 1978 and 2006 or of any other isolate from the National Veterinary Services Laboratories (NVSL) culture library. Coupled with the fact that the CEM09 isolates are epidemiologically related, these results suggest a common source for the outbreak not linked to previous occurrences of CEM in the United States.

Diagnostic and epidemiologic analysis of the 2008-2010 investigation of a multi-year outbreak of contagious equine metritis in the United States.

Contagious equine metritis (CEM) is a highly contagious venereal disease of horses caused by Taylorella equigenitalis. During testing for semen export purposes, a stallion in Kentucky was found to be T. equigenitalis culture positive in December of 2008. This finding triggered an extensive regulatory investigation to search for additional positive horses, determine the extent of the outbreak, identify the potential source of the outbreak, and ultimately return the United States to CEM-free status. The investigation included over 1000 horses located in 48 states. Diagnostic testing found a total of 22 stallions, 1 gelding and 5 mares culture positive for T. equigenitalis. Epidemiologic analysis indicated that all of the positive horses were linked to a single common source, most likely a Fjord stallion imported into the United States in 2000. The T. equigenitalis strain subsequently spread to other stallions via undetermined indirect mechanisms at shared breeding facilities, and to mares via artificial insemination and live breeding. This CEM outbreak and investigation represent the largest ever in the United States based on the number of exposed horses tested and their geographic distribution.