Gas6-Axl signal promotes indoor VOCs exposure-induced pulmonary fibrosis via pulmonary microvascular endothelial cells-fibroblasts cross-talk.

Volatile organic compounds (VOCs) as environmental pollutants were associated with respiratory diseases. Pulmonary fibrosis (PF) was characterized by an increase of extracellular matrix, leading to deterioration of lung function. The adverse effects on lung and the potential mechanism underlying VOCs induced PF had not been elucidated clearly. In this study, the indoor VOCs exposure mouse model along with an ex vivo biosensor assay was established. Based on scRNA-seq analysis, the adverse effects on lung and potential molecular mechanism were studied. Herein, the results showed that VOCs exposure from indoor decoration contributed to decreased lung function and facilitated pulmonary fibrosis in mice. Then, the whole lung cell atlas after VOCs exposure and the heterogeneity of fibroblasts were revealed. We explored the molecular interactions among various pulmonary cells, suggesting that endothelial cells contributed to fibroblasts activation in response to VOCs exposure. Mechanistically, pulmonary microvascular endothelial cells (MPVECs) secreted Gas6 after VOCs-induced PANoptosis phenotype, bound to the Axl in fibroblasts, and then activated fibroblasts. Moreover, Atf3 as the key gene negatively regulated PANoptosis phenotype to ameliorate fibrosis induced by VOCs exposure. These novel findings provided a new perspective about MPVECs could serve as the initiating factor of PF induced by VOCs exposure.

Hub gene ELK3-mediated reprogramming lipid metabolism regulates phenotypic switching of pulmonary artery smooth muscle cells to develop pulmonary arterial hypertension induced by PM2.5.

Fine particulate matter (PM2.5) as an environmental pollutant is related with respiratory and cardiovascular diseases. Pulmonary arterial hypertension (PAH) was characterized by incremental pulmonary artery pressure and pulmonary arterial remodeling, leading to right ventricular hypertrophy, and finally cardiac failure and death. The adverse effects on pulmonary artery and the molecular biological mechanism underlying PM2.5-caused PAH has not been elaborated clearly. In the current study, the ambient PM2.5 exposure mice model along with HPASMCs models were established. Based on bioinformatic methods and machine learning algorithms, the hub genes in PAH were screened and then adverse effects on pulmonary artery and potential mechanism was studied. Our results showed that chronic PM2.5 exposure contributed to increased pulmonary artery pressure, pulmonary arterial remodeling and right ventricular hypertrophy in mice. In vitro, PM2.5 induced phenotypic switching in HPASMCs, which served as the early stage of PAH. In mechanism, we investigated that PM2.5-mediated mitochondrial dysfunction could induce phenotypic switching in HPASMCs, which was possibly through reprogramming lipid metabolism. Next, we used machine learning algorithm to identify ELK3 as potential hub gene for mitochondrial fission. Besides, the effect of DNA methylation on ELK3 was further detected in HPASMCs after PM2.5 exposure. The results provided novel directions for protection of pulmonary vasculature injury, against adverse environmental stimuli. This work also provided a new idea for the prevention of PAH, as well as provided experimental evidence for the targeted therapy of PAH.

Toxic elements pollution risk as affected by various input sources in soils of greenhouses, kiwifruit orchards, cereal fields, and forest/grassland.

Increasing food demand has led to more intensive farming, which threatens our ecosystem and human health due to toxic elements accumulation. This study aimed to estimate the vulnerability of different agricultural systems with unequal high fertilizer input practices regarding toxic element pollution in the greenhouse, kiwifruit orchard, cereal field, and forest/grassland. Soil samples were collected from 181 sites across Shaanxi Province, China, and analyzed for selected characteristics and toxic elements (As, Cd, Cr, Cu, Hg, Pb, and Zn). The contamination factor (CFx) represents the ratio of the measured value of the toxic element in the soil over the soil background values. The CFx values of all the toxic elements were above background values, while Cd and Hg contamination levels were more severe than those of Zn, Cu, As, Cr, and Pb. Kiwifruit orchards and greenhouse soils were contaminated with Cd, Hg, Cu, and Zn, but cereal fields and forest/grassland soils were contaminated with As, Cd, Hg, and Hg. Overall, the cumulative pollution load (PLI) of toxic elements indicated moderate contamination. The cumulative ecological risk (RI) results indicated that greenhouse (178.81) and forest/grassland (156.25) soils were at moderate ecological risks, whereas kiwifruit orchards (120.97) and cereal field (139.72) soils were at low ecological risks. According to a Pearson correlation analysis, Cd, Hg, Cu, and Zn were substantially linked with soil organic matter (SOM), total nitrogen (TN), total phosphorous (TP), and total potassium (TK). The primary sources of toxic elements were phosphate and potash fertilizers, manure, composts, and pesticides in a greenhouse, kiwifruit orchards, and cereal fields, whereas, in forest/grassland soils parent material and atmospheric deposition were the sources identified by positive matrix factorization (PMF). Furthermore, the partial least square structural equation model (PLS-SEM) demonstrated that agriculture inputs largely influenced toxic elements accumulation. We conclude that high fertilizer inputs in greenhouse soils should be considered carefully so that toxic element pollution may be minimized.

Respecting catalytic efficiency of soil arylsulfatase as soil Sb contamination bio-indicator by enzyme kinetic strategy.

Antimony (Sb), a toxic metalloid, is ubiquitous in the environment and threatens human and ecological health. Soil arylsulfatase (ARS) activity indicates heavy metal pollution. However, the enzyme's substrate concentration can affect the toxicity evaluation of heavy metals using enzyme activity. Enzyme kinetic parameters directly reflect the potency of heavy metals, and the magnitude of these parameters does not change with the substrate concentration of soil enzyme. In this work, seventeen soils were exposed to Sb contamination to investigate the change of kinetic parameters of soil arylsulfatase under Sb stress. Results showed that Sb inhibited soil arylsulfatase activity. The maximum reaction rate (Vmax) of soil arylsulfatase was reduced by 11.58-46.72% in 16 tested soils and unchanged in S15 when exposed to Sb. The Michaelis constant (Km) presented three trends: unchanged, increased by 28.46-41.27%, and decreased by 19.71-29.91% under Sb stress. The catalytic efficiency (Ka as the ratio of Vmax to Km) decreased by 12.56-55.17% in all soils except for S12 and S16. Antimony acted as a non-competitive and linear mixed inhibitor by decreasing ARS activity in S1-S12, S14, and S17-S18 soils, as an uncompetitive inhibitor in S13 and S16 soils and as a competitive inhibitor in S15. The competitive and uncompetitive inhibition constants (Kic and Kiu) were 0.058-0.142 mM and 0.075-0.503 mM. The ecological dose values of Sb to catalytic efficiency (Ka) of ARS (ED10-Ka) ranged from 50 to 1315 mg kg-1. Soil pH and total phosphorus (TP) contents were the dominant factors responsible for Sb toxicity on Ka by affecting the interaction of inhibitor (Sb) with enzyme-substrate (ES) complex. The findings of this study advance the current knowledge on Sb toxicity to soil enzymes and have significant implications for the risk assessment of Sb in soils.

Dynamics of fungal and bacterial communities in different types of soil ageing with different dosages of cadmium.

This study investigated the structure of fungal and bacterial communities in different types of Cd-contaminated soils. The results showed that obvious variations in microbial structure between contaminated alkaline soils and acidic soils. Proteobacteria, Gemmatimonadetes, Bacteroidetes and Basidiomycota dominated the studied communities in the alkaline soils, whereas Actinobacteria, Chloroflexi, Firmicutes, Acidobacteria, Saccharibacteria and Ascomycota were more abundant in the acidic soils. Additionally, Cd tolerant (Proteobacteria, Bacteroidetes, Ascomycota) and sensitive (Actinobacteria, Acidobacteria, Basidiomycota) in alkaline soils and JL-soils, Cd tolerant (Actinobacteria, Acidobacteria, Basidiomycota) and sensitive (Saccharibacteria, Proteobacteria, Bacteroidetes, Ascomycota, Mucoromycota) in the acidic soils were identified. Redundancy analysis and correlation analysis demonstrated that it was significantly affected by different environment parameters in alkaline soils and acidic soils. Varied bacterial community structures in all soils were dominantly influenced by pH and SOM. The similarities among different groups indicated the effect of soil type on microbial community structure was greater than that of Cd level. The above conclusions may provide a new perspective for the bio-remediation of Cd in different types of soils.