Optimized quantification of intra-host viral diversity in SARS-CoV-2 and influenza virus sequence data.

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant-calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller and use of replicate sequencing have the most significant impact on single-nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false-negative rates. When replicates are not available, using a combination of multiple callers with more stringent cutoffs is recommended. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intra-host viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intra-host variation, viral diversity, and viral evolution. IMPORTANCE When viruses replicate inside a host cell, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus nor strongly beneficial can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in the inclusion of false-positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant-calling tools. We used simulated and synthetic data to test their performance against a true set of variants and then used these studies to inform variant identification in data from SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.

Optimized Quantification of Intrahost Viral Diversity in SARS-CoV-2 and Influenza Virus Sequence Data.

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller, and use of replicate sequencing have the most significant impact on single nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false negative rates. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intrahost viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intrahost variation, viral diversity, and viral evolution. IMPORTANCE: When viruses replicate inside a host, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus, nor strongly beneficial, can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in inclusion of false positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant calling tools. We used simulated and synthetic data to test their performance against a true set of variants, and then used these studies to inform variant identification in data from clinical SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.

Reduced postprandial bone resorption and greater rise in GLP-1 in overweight and obese individuals after an α-glucosidase inhibitor: a double-blinded randomized crossover trial.

When taken with a meal, α-glucosidase inhibitors (α-GI) reduce the rise in postprandial glucose and increase glucagon-like peptide-1 (GLP-1), and this may lower bone turnover. In this study, a salacinol-type α-GI increased GLP-1 and markedly reduced postprandial bone resorption compared to placebo, suggesting it could have implications for bone health. INTRODUCTION: Animal and clinical trials indicate that α-glucosidase inhibitors attenuate postprandial glycemic indices and increase secretion of GLP-1. In addition, GLP-1 acts on bone by inhibiting resorption. The goal in this study was to determine if a salacinol α-GI alters postprandial bone turnover and can be explained by changes in serum GLP-1. METHODS: In this double-blind, placebo-controlled crossover study, healthy overweight/obese adults (body mass index 29.0 ± 3.8 kg/m2; 21-59 years; n = 21) received a fixed breakfast and, in random order, were administered Salacia chinensis (SC; 500 mg) or placebo. A fasting blood sample was taken before and at regular intervals for 3 h after the meal. Serum was measured for bone turnover markers, C-terminal telopeptide of type I collagen (CTX) and osteocalcin, and for glycemic indices and gut peptides. RESULTS: Compared to placebo, SC attenuated the bone resorption marker, CTX, at 60, 90, and 120 min (p < 0.05) after the meal, and decreased osteocalcin, at 180 min (p < 0.05). As expected, SC attenuated the postprandial rise in glucose compared with placebo, whereas GLP-1 was increased at 60 min (p < 0.05) with SC. Serum GLP-1 explained 41% of the variance for change in postprandial CTX (p < 0.05). CONCLUSION: This study indicates that attenuating postprandial glycemic indices, with an α-GI, markedly decreases postprandial bone resorption and can be explained by the rise in GLP-1. Future studies should determine whether longer term α-GI use benefits bone health.