RESUMO
BACKGROUND: Rheumatoid arthritis (RA) is a chronic and refractory autoimmune disease. Deficiency pattern (DP) and excess pattern (EP), as crucial types of Chinese medicine pattern diagnoses published by International Classification of Diseases 11th Revision (ICD-11), could provide new strategies for RA diagnosis. However, the biological basis of DP and EP of RA is not explicit. METHODS: 19 female RA DP patients, 41 female RA EP patients and 30 female healthy participants were included in the study. The serums of participants were collected and analyzed by metabolomics based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry to profile metabolic characteristics of RA DP and EP. Furthermore, bioinformatics analysis results were obtained by using Ingenuity Pathway Analysis (IPA) and statistical analysis was performed by SAS version 9.4 for further identification of potential biomarkers. RESULTS: Serum metabolic profiling revealed 25 and 24 differential metabolites in RA DP and EP respectively, and 19 metabolites were common to RA DP and EP. Compared with DP group, L-Homocysteic acid, LysoPE(P-16:0/0:0), N(omega)-Hydroxyarginine and LysoPC(16:0/0:0) decreased (P < 0.05), and Pyruvic acid, D-Ribose, Gamma-Glutamylserine, PE(22:0/24:1(15Z)), Inosinic acid increased (P < 0.05) in EP group. Menawhile, S-Nitrosoglutathione, 5-Thymidylic acid, SN38 glucuronide, PE(22:0/24:0), PC(24:0/24:1(15Z)) and Bisdiphosphoinositol tetrakisphosphate increased significantly in DP group compared to EP group (P < 0.05). For the unique metabolites, bioinformatics analysis results showed that 5-Methoxytryptamine involved in Melatonin Degradation II and Superpathway of Melatonin Degradation is the key metabolite to RA DP. Meanwhile, GABA is the key metabolite in EP group, which involved in Glutamate Dependent Acid Resistance, GABA Receptor Signaling, Glutamate Degradation III (via 4-aminobutyrate) and 4-aminobutyrate Degradation I. Bioinformatics analysis between unique metabolites of RA DP and EP groups with human target genes for RA showed that 5-methoxytryptamine and LysoPC(18:1(9Z)/0:0), the unique metabolites of RA DP, might participate in colorectal cancer metastasis signaling, tumor microenvironment pathway, apoptosis signaling, MYC mediated apoptosis signaling, erythropoietin signaling pathway and LXR/RXR activation. Simultaneously, GABA, LysoPA(18:1(9Z)/0:0) and L-Targinine, the unique metabolites of RA EP, might participate in neuroinflammation signaling pathway, osteoarthritis pathway, glucocorticoid receptor signaling, ILK signaling, IL-17 signaling and HIF1α signaling. CONCLUSIONS: The study indicates that serum metabolomics preliminarily revealed the biological basis of RA DP and EP. 5-methoxytryptamine, LysoPC(18:1(9Z)/0:0) and GABA, LysoPA(18:1(9Z)/0:0), L-Targinine might be the predictors to distinguish the DP and EP of RA respectively. These interesting results provide thoughts for further study of traditional medicine patterns of ICD-11. It also contributes to provide strategy for personalized precision treatment of RA and further validation is needed.
RESUMO
KEY MESSAGE: Two homologous, chloroplast located CAAX proteases were identified to be functional redundancy in determining soybean leaf color, and they probably play essential roles in regulating light harvesting and absorption during photosynthesis process. Leaf color mutants are ideal materials for studying photosynthesis and chlorophyll metabolism. The soybean [Glycine max (L.) Merr.] yellowing leaf (yl) variation is a recombinant mutant characterized by yellow foliage, which derived from the specific cross between green seed-coated and yellow seed-coated soybean varieties. Molecular cloning and subsequent gene silencing revealed that the yellow leaf trait of yl was controlled by two recessive nuclear genes, glyma11g04660 and glyma01g40650, named as YL1 and YL2 respectively, and the latter was confirmed to be same as the earlier reported green seed-coat gene G. Both YL1 and YL2 belonged to chloroplast-located proteases possessing Abi domain, and these genes were expressed in various tissues, especially in young leaves. In yl, the expression of YL1 and YL2 were suppressed in most tissues, and the young leaf of yl presented an increased maximal photochemical efficiency (Fv/Fm) as well as enhanced net photosynthesis activity (Pn), indicating that YL1 and YL2 are involved in light absorption regulation during photosynthesis process. Collectively, the identification and description of YL1 and YL2 in our study provides insights for the regulatory mechanism of photosynthesis process, and these findings will further assist to clarify the close relationship between photosynthesis and chlorophyll metabolism.