RESUMEN
The Lianhua Qingwen (LHQW) capsule is a popular traditional Chinese medicine for the treatment of viral respiratory diseases. In particular, it has been recently prescribed to treat infections caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, due to its complex composition, little attention has been directed toward the analysis of chemical constituents present in the LHQW capsule. This study presents a reliable and comprehensive approach to characterizing the chemical constituents present in LHQW by high-performance liquid chromatography-Q Exactive-Orbitrap mass spectrometry (HPLC-Q Exactive-Orbitrap-MS) coupled with gas chromatography-mass spectrometry (GC-MS). An automated library alignment method with a high mass accuracy (within 5 ppm) was used for the rapid identification of compounds. A total of 104 compounds, consisting of alkaloids, flavonoids, phenols, phenolic acids, phenylpropanoids, quinones, terpenoids, and other phytochemicals, were successfully characterized. In addition, the fragmentation pathways and characteristic fragments of some representative compounds were elucidated. GC-MS analysis was conducted to characterize the volatile compounds present in LHQW. In total, 17 compounds were putatively characterized by comparing the acquired data with that from the NIST library. The major constituent was menthol, and all the other compounds were terpenoids. This is the first comprehensive report on the identification of the major chemical constituents present in the LHQW capsule by HPLC-Q Exactive-Orbitrap-MS, coupled with GC-MS, and the results of this study can be used for the quality control and standardization of LHQW capsules.
RESUMEN
Qingfei Paidu (QFPD) granules have played a critical role during the Coronavirus Disease 2019 (COVID-19) in China. However, worldwide acceptance has been a problem because of the complex ingredients and unique theory of treatment. In this study, high-performance liquid chromatography (HPLC)-Q Exactive Orbitrap-mass spectrometry (MS) and the Orbitrap traditional Chinese medicine library (OTCML) were used to investigate the chemical constituents of QFPD granules. By comparing retention times, masses, isotope ion patterns, and MS2 profiles, 108 compounds were putatively identified using the OTCML combined with manual verification, including 12 alkaloids, 49 flavonoids, 13 terpenoids, 14 phenylpropanoids, 4 phenolic acids, 5 phenols, and 11 other phytochemicals. Of these compounds, 17 were confirmed using reference standards. In addition, representative compounds of these different chemical types were used as examples to analyze the fragmentation pathways and characteristic product ions. Moreover, 20 herbs within the QFPD granules were also identified to establish the sources of these chemical components. This is the first rapid profiling of the chemical constituents of QFPD granules using HPLC-Q Exactive Orbitrap-MS and yields valuable information for further quality control and mechanistic studies of QFPD granules. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10337-021-04085-0.
RESUMEN
The pandemic due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of coronavirus disease 2019 (COVID-19), has caused immense global disruption. With the rapid accumulation of SARS-CoV-2 genome sequences, however, thousands of genomic variants of SARS-CoV-2 are now publicly available. To improve the tracing of the viral genomes' evolution during the development of the pandemic, we analyzed single nucleotide variants (SNVs) in 121,618 high-quality SARS-CoV-2 genomes. We divided these viral genomes into two major lineages (L and S) based on variants at sites 8782 and 28144, and further divided the L lineage into two major sublineages (L1 and L2) using SNVs at sites 3037, 14408, and 23403. Subsequently, we categorized them into 130 sublineages (37 in S, 35 in L1, and 58 in L2) based on marker SNVs at 201 additional genomic sites. This lineage/sublineage designation system has a hierarchical structure and reflects the relatedness among the subclades of the major lineages. We also provide a companion website (www.covid19evolution.net) that allows users to visualize sublineage information and upload their own SARS-CoV-2 genomes for sublineage classification. Finally, we discussed the possible roles of compensatory mutations and natural selection during SARS-CoV-2's evolution. These efforts will improve our understanding of the temporal and spatial dynamics of SARS-CoV-2's genome evolution.
RESUMEN
The ongoing global novel coronavirus pneumonia COVID-19 outbreak has engendered numerous cases of infection and death. COVID-19 diagnosis relies upon nucleic acid detection; however, currently recommended methods exhibit high false-negative rates and are unable to identify other respiratory virus infections, thereby resulting in patient misdiagnosis and impeding epidemic containment. Combining the advantages of targeted amplification and long-read, real-time nanopore sequencing, herein, nanopore targeted sequencing (NTS) is developed to detect SARS-CoV-2 and other respiratory viruses simultaneously within 6-10 h, with a limit of detection of ten standard plasmid copies per reaction. Compared with its specificity for five common respiratory viruses, the specificity of NTS for SARS-CoV-2 reaches 100%. Parallel testing with approved real-time reverse transcription-polymerase chain reaction kits for SARS-CoV-2 and NTS using 61 nucleic acid samples from suspected COVID-19 cases show that NTS identifies more infected patients (22/61) as positive, while also effectively monitoring for mutated nucleic acid sequences, categorizing types of SARS-CoV-2, and detecting other respiratory viruses in the test sample. NTS is thus suitable for COVID-19 diagnosis; moreover, this platform can be further extended for diagnosing other viruses and pathogens.