Response of C:N:P stoichiometry to long-term drainage of peatlands: Evidence from plant, soil, and enzyme.

Drought induced by climate warming and human activities regulates carbon (C) cycling of peatlands by changing plant community composition and soil properties. Estimating the responses of peatlands C cycling to environmental changes requires further study of C: nitrogen (N): phosphorus (P) stoichiometric ratios of soil, plants, and enzyme activities. However, systematic studies on the stoichiometry of above-ground and below-ground ecosystems of peatlands post drainage remain scarce. This study compared stoichimetric ratios of plant and soil and stoichimetric ratios of enzyme activities with different functions in two different parts of a minerotrophic peatland, a natural undisturbed part and a part that had been drained for almost 50 years, in Northern China. For the shrub plants, the average C:N:P ratios of leaf in natural and drained peatland were 448:17:1 and 393:15:1, respectively. This indicated that the growth rate of shrub plants is higher in the drained peatland than in the natural peatland, which makes P element more concentrated in the photosynthetic site. However, from the perspective of the dominant plant, the mean C:N:P ratio of Carex leaf was 650:25:1 in the natural peatland, but was 1028:50:1 for Dasiphora fruticosa in drained peatland. This indicated that the intensification of P-limitation of plant growth after drainage. Soil C:N:P ratios of above water table depth (AWT) were 238:15:1 and 277:12:1, but were 383:17:1 and 404:19:1 for below water table depth (BWT) in the natural and the drained peatland, respectively. Soil C:P ratios were greater than the threshold elemental ratio of C:P (174:1), but the soil C:N ratios were less than the threshold elemental ratio of C:N (23:1), which suggested that P was the most limiting nutrient of soil. The soil microbial activities were co-limited by C&P in Baijianghe peatlands. However, the microbial metabolic P limitation was intensified, but the C limitation was weakened for the above water table depth soil after long-term drainage. There are connection between plant-microbe P limitation in peatlands. The P limitation of microbial metabolism was significant positively correlated with soil C:N but negatively with soil moisture. The increase in the lignocelluloses index suggested considerable decomposition of soil organic matter after peatland drainage. These results of stoichiometric ratios from above- to below ground could provide scientific base for the C cycling of peatland undergone climate change.

Untargeted lipidomics reveals specific lipid abnormalities in systemic lupus erythematosus.

OBJECTIVES: To identify potential lipid biomarkers by studying changes in the blood lipid profile of patients with systemic lupus erythematosus (SLE) using lipidomics. METHODS: Serum samples were collected from 115 SLE patients and 115 age- and sex-matched healthy controls (HCs). Lipid profiles were assessed using ultrahigh-performance liquid chromatography coupled with Q Exactive spectrometry, and possible lipid biomarkers were screened and evaluated by univariate and multivariate analyses. RESULTS: Metabolic phenotypes related to SLE disease activity index (SLEDAI) scores were detected in the serum of SLE patients, and these phenotypes indicated the activity of the disease. Alterations in energy metabolism, fatty acid metabolism and other pathways were observed in patients with SLE. Phosphatidylethanolamine (16:0/18:2), lysophosphatidylethanolamine (18:0), and acylcarnitine (11:0) can be used as biomarkers for the clinical diagnosis of SLE, and receiver operating characteristic (ROC) analysis indicated their effectiveness in diagnosing this disease. CONCLUSIONS: Our study identified serum biomarkers related to disease activity in patients with SLE, providing a basis for its clinical diagnosis.

Serum lipidomics reveals distinct metabolic profiles for asymptomatic hyperuricemic and gout patients.

OBJECTIVES: This study aimed to characterize the systemic lipid profile of patients with asymptomatic hyperuricemia (HUA) and gout using lipidomics, and to find potential underlying pathological mechanisms therefrom. METHODS: Sera were collected from Affiliated Hospital of Nanjing University of Chinese Medicine as centre 1 (discovery and internal validation sets) and Suzhou Hospital of Traditional Chinese Medicine as centre 2 (external validation set), including 88 normal subjects, 157 HUA and 183 gout patients. Lipidomics was performed by ultra high performance liquid chromatography plus Q-Exactive mass spectrometry (UHPLC-Q Exactive MS). Differential metabolites were identifed by both variable importance in the projection ≥1 in orthogonal partial least-squares discriminant analysis mode and false discovery rate adjusted P ≤ 0.05. Biomarkers were found by logistic regression and receiver operating characteristic (ROC) analysis. RESULTS: In the discovery set, a total of 245 and 150 metabolites, respectively, were found for normal subjects vs HUA and normal subjects vs gout. The disturbed metabolites included diacylglycerol, triacylglycerol (TAG), phosphatidylcholine, phosphatidylethanolamine, phosphatidylinositol, etc. We also found 116 differential metabolites for HUA vs gout. Among them, the biomarker panel of TAG 18:1-20:0-22:1 and TAG 14:0-16:0-16:1 could differentiate well between HUA and gout. The area under the receiver operating characteristic ROC curve was 0.8288, the sensitivity was 82% and the specificity was 78%, at a 95% CI 0.747, 0.9106. In the internal validation set, the predictive accuracy of TAG 18:1-20:0-22:1 and TAG 14:0-16:0-16:1 panel for differentiation of HUA and gout reached 74.38%, while it was 84.03% in external validation set. CONCLUSION: We identified serum biomarkers panel that have the potential to predict and diagnose HUA and gout patients.

Untargeted Lipidomics Reveals Characteristic Biomarkers in Patients with Ankylosing Spondylitis Disease.

Objective. Ankylosing spondylitis (AS) is a chronic inflammatory disease of the axial skeleton. Early and accurate diagnosis is necessary for the timely and effective treatment of this disease and its common complications. Lipid metabolites form various kinds of bioactive molecules that regulate the initiation and progression of inflammation. However, there are currently few studies that investigate the alteration of serum lipid in AS patients. Methods. Blood samples were collected from 115 AS patients and 108 healthy controls (HCs). Serum-untargeted lipidomics were performed using ultrahigh-performance liquid chromatography coupled with Q-Exactive spectrometry, and the data were determined by multivariate statistical methods to explore potential lipid biomarkers. Results. Lipid phenotypes associated with disease activity were detected in the serum of patients with AS. Of all 586 identified lipids, there are 297 differential lipid metabolites between the AS and HC groups, of which 15 lipid metabolites are significant. In the AS groups, the levels of triacylglycerol (TAG) (18:0/18:1/20:0) were increased, and the levels of phosphatidylcholine (PC) (16:0e/26:4) and PC (18:1/22:6) were decreased. The areas under the receiver operating characteristic curve (AUC) of TAG (18:0/18:1/20:0), PC (16:0e/26:4), and PC (18:1/22:6) were 0.919, 0.843, and 0.907, respectively. Conclusion. Our findings uncovered that lipid deregulation is a crucial hallmark of AS, thereby providing new insights into the early diagnosis of AS.