Identification of a Pharmacological Biomarker for the Bioassay-Based Quality Control of a Thirteen-Component TCM Formula (Lianhua Qingwen) Used in Treating Influenza A Virus (H1N1) Infection.
Front Pharmacol
; 11: 746, 2020.
Article
en En
| MEDLINE
| ID: mdl-32523531
ABSTRACT
As chemical analysis for quality control (QC) of traditional Chinese medicine (TCM) formula is difficult to guarantee the effectiveness, a bioassay method that combines QC with evaluation of therapeutic effects has been developed to assess the TCM quality. Here, we chose a thirteen-component TCM formula, Lianhua Qingwen capsule (LHQW), as a representative sample, to explore the pivotal biomarkers for a bioassay and to investigate close association between QC and pharmacological actions. Initially, our results showed that chemical fingerprinting could not effectively distinguish batches of LHQW. Pharmacological experiments indicated that LHQW could treat influenza A virus (H1N1) infection in the H1N1 mouse model, as claimed in clinical trials, by improving pathologic alterations and bodyweight loss, and decreasing virus replication, lung lesions and inflammation. Furthermore, by using serum metabolomics analysis, we identified two important metabolites, prostaglandin F2α and arachidonic acid, and their metabolic pathway, arachidonic acid metabolism, as vital indicators of LHQW in treatment of influenza. Subsequently, macrophages transcriptomics highlighted the prominent role of cyclooxygenase-2 (COX-2) as the major rate-limiting enzyme in the arachidonic acid metabolism pathway. Finally, COX-2 was validated by in vivo gene expression and in vitro enzymatic activity with 43 batches of LHQW as a viable pharmacological biomarker for the establishment of bioassay-based QC. Our study provides systematic methodology in the pharmacological biomarker exploration for establishing the bioassay-based QC of LHQW or other TCM formulas relating to their pharmacological activities and mechanism.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Tipo de estudio:
Diagnostic_studies
Idioma:
En
Revista:
Front Pharmacol
Año:
2020
Tipo del documento:
Article