Background Rapid, reliable, and widespread testing is required to curtail the ongoing COVID-19 pandemic. Current gold standard nucleic acid tests are hampered by supply shortages in critical reagents including nasal swabs, RNA extraction kits, personal protective equipment, instrumentation, and labor. Methods To overcome these challenges, we developed a rapid colorimetric assay using reverse-transcription loop-mediated isothermal amplification (RT-LAMP) optimized on human saliva samples without an RNA purification step. We describe the optimization of saliva pretreatment protocols to enable analytically sensitive viral detection by RT-LAMP. We optimized the RT-LAMP reaction conditions and implemented high-throughput unbiased methods for assay interpretation. We tested whether saliva pretreatment could also enable viral detection by conventional reverse-transcription quantitative polymerase chain reaction (RT-qPCR). Finally, we validated these assays on clinical samples. Results The optimized saliva pretreatment protocol enabled analytically sensitive extraction-free detection of SARS-CoV-2 from saliva by colorimetric RT-LAMP or RT-qPCR. In simulated samples, the optimized RT-LAMP assay had a limit of detection of 59 (95% confidence interval: 44-104) particle copies per reaction. We highlighted the flexibility of LAMP assay implementation using three readouts: naked-eye colorimetry, spectrophotometry, and real-time fluorescence. In a set of 30 clinical saliva samples, colorimetric RT-LAMP and RT-qPCR assays performed directly on pretreated saliva samples without RNA extraction had accuracies greater than 90%. Conclusions Rapid and extraction-free detection of SARS-CoV-2 from saliva by colorimetric RT-LAMP is a simple, sensitive, and cost-effective approach with broad potential to expand diagnostic testing for the virus causing COVID-19.

Currently, oncology testing includes molecular studies and cytogenetic analysis to detect genetic aberrations of clinical significance. Next-generation sequencing (NGS) allows rapid analysis of multiple genes for clinically actionable somatic variants. The WUCaMP assay uses targeted capture for NGS analysis of 25 cancerassociated genes to detect mutations at actionable loci. We present clinical validation of the assay and a detailed framework for design and validation of similar clinical assays. Deep sequencing of 78 tumor specimens (!1000Â average unique coverage across the capture region) achieved high sensitivity for detecting somatic variants at low allele fraction (AF). Validation revealed sensitivities and specificities of 100% for detection of single-nucleotide variants (SNVs) within coding regions, compared with SNP array sequence data (95% CI Z 83.4e100.0 for sensitivity and 94.2e100.0 for specificity) or whole-genome sequencing (95% CI Z 89.1e100.0 for sensitivity and 99.9e100.0 for specificity) of HapMap samples. Sensitivity for detecting variants at an observed 10% AF was 100% (95% CI Z 93.2e100.0) in HapMap mixes. Analysis of 15 masked specimens harboring clinically reported variants yielded concordant calls for 13/13 variants at AF of !15%. The WUCaMP assay is a robust and sensitive method to detect somatic variants of clinical significance in molecular oncology laboratories, with reduced time and cost of genetic analysis allowing for strategic patient management. (J Mol Diagn 2014, 16: 89e105; http://dx.doi.org/10.1016/j.jmoldx.2013 Traditional approaches to the genetic characterization of clinical oncology specimens include cytogenetic analysis, fluorescence in situ hybridization (FISH), and molecular studies of single genes. These methodologies are complementary to each other and generate information of diagnostic and prognostic relevance. However, as new insight is gained into the complexities of cancer at the molecular level, the need emerges to obtain a more detailed cancer genetic profile for improved patient management. As illustrated by recent studies, identifying DNA mutations in cancer may aid in understanding clonal evolution, 1 risk stratification, 2 and therapeutic strategies. 3,4 With the advent of next-generation sequencing (NGS), a more complete biological characterization of a tumor can be attained at the molecular level. 5

Rapid, reliable, and widespread testing is required to curtail the ongoing COVID-19 pandemic. Current gold standard diagnostic assays are hampered by supply shortages in critical reagents including nasal swabs, RNA extraction kits, personal protective equipment (PPE), instrumentation, and labor. Here we present an approach to overcome these challenges with the development of a rapid colorimetric assay using reverse-transcription loop-mediated isothermal amplification (RT-LAMP) optimized on human saliva samples without an RNA purification step. We describe our optimizations of the LAMP reaction and saliva pre-treatment protocols that enabled rapid and sensitive detection of < 10 2 viral genomes per reaction in contrived saliva controls. We also observed high performance of this assay on a limited number of clinical saliva samples. While thorough validation on additional clinical samples will be needed before such an assay can be widely used, these preliminary results demonstrate a promising approach to overcome the current bottlenecks limiting widespread testing.

Metagenomic sequencing of bacterial samples has become the gold standard for profiling microbial populations, but 16S rRNA profiling remains widely used due to advantages in sample throughput, cost, and sensitivity even though the approach is hampered by primer bias and lack of specificity. We hypothesized that a hybrid approach, that combined targeted PCR amplification with high-throughput sequencing of multiple regions of the genome, would capture many of the advantages of both approaches. We developed a method that identifies and quantifies members of bacterial communities through simultaneous analysis of multiple variable regions of the bacterial 16S rRNA gene. The method combines high-throughput microfluidics for PCR amplification, short read DNA sequencing, and a custom algorithm named MVRSION (Multiple 16S Variable Region Species-Level IdentificatiON) for optimizing taxonomic assignment. MVRSION performance was compared to single variable region analyses (V3 or V4) of five synthetic mixtures of human gut bacterial strains using existing software (QIIME), and the results of community profiling by shotgun sequencing (COPRO-Seq) of fecal DNA samples collected from gnotobiotic mice colonized with a defined, phylogenetically diverse consortium of human gut bacterial strains. Positive predictive values for MVSION ranged from 65%−91% versus 44%−61% for single region QIIME analyses (p<0.01, p<0.001), while the abundance estimate r2 for MVRSION compared to COPRO-Seq was 0.77 vs. 0.46 and 0.45 for V3-QIIME and V4-QIIME, respectively. MVRSION represents a generally applicable tool for taxonomic classification that is superior to singleregion 16S rRNA methods, resource efficient, highly scalable for assessing the microbial composition of up to thousands of samples concurrently, with multiple applications ranging from whole community profiling to targeted tracking of organisms of interest in diverse habitats as a function of specified variables/perturbations.

Lansbery, Kristan L., Lauren C. Burcea, Margaretta L. Mendenhall, and Robert W. Mercer. Cytoplasmic targeting signals mediate delivery of phospholemman to the plasma membrane.