Microbiome-derived bile acids contribute to elevated antigenic response and bone erosion in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic, disabling and incurable autoimmune disease. It has been widely recognized that gut microbial dysbiosis is an important contributor to the pathogenesis of RA, although distinct alterations in microbiota have been associated with this disease. Yet, the metabolites that mediate the impacts of the gut microbiome on RA are less well understood. Here, with microbial profiling and non-targeted metabolomics, we revealed profound yet diverse perturbation of the gut microbiome and metabolome in RA patients in a discovery set. In the Bacteroides-dominated RA patients, differentiation of gut microbiome resulted in distinct bile acid profiles compared to healthy subjects. Predominated Bacteroides species expressing BSH and 7a-HSDH increased, leading to elevated secondary bile acid production in this subgroup of RA patients. Reduced serum fibroblast growth factor-19 and dysregulated bile acids were evidence of impaired farnesoid X receptor-mediated signaling in the patients. This gut microbiota-bile acid axis was correlated to ACPA. The patients from the validation sets demonstrated that ACPA-positive patients have more abundant bacteria expressing BSH and 7a-HSDH but less Clostridium scindens expressing 7a-dehydroxylation enzymes, together with dysregulated microbial bile acid metabolism and more severe bone erosion than ACPA-negative ones. Mediation analyses revealed putative causal relationships between the gut microbiome, bile acids, and ACPA-positive RA, supporting a potential causal effect of Bacteroides species in increasing levels of ACPA and bone erosion mediated via disturbing bile acid metabolism. These results provide insights into the role of gut dysbiosis in RA in a manifestation-specific manner, as well as the functions of bile acids in this gut-joint axis, which may be a potential intervention target for precisely controlling RA conditions.Comment: 38 pages, 6 figure

Persistent sulfate formation from London Fog to Chinese haze

Sulfate aerosols exert profound impacts on human and ecosystem health, weather, and climate, but their formation mechanism remains uncertain. Atmospheric models consistently underpredict sulfate levels under diverse environmental conditions. From atmospheric measurements in two Chinese megacities and complementary laboratory experiments, we show that the aqueous oxidation of SO2 by NO2 is key to efficient sulfate formation but is only feasible under two atmospheric conditions: on fine aerosols with high relative humidity and NH3 neutralization or under cloud conditions. Under polluted environments, this SO2 oxidation process leads to large sulfate production rates and promotes formation of nitrate and organic matter on aqueous particles, exacerbating severe haze development. Effective haze mitigation is achievable by intervening in the sulfate formation process with enforced NH3 and NO2 control measures. In addition to explaining the polluted episodes currently occurring in China and during the 1952 London Fog, this sulfate production mechanism is widespread, and our results suggest a way to tackle this growing problem in China and much of the developing world

Screening and Identification of the Host Proteins Interacting with Toxoplasma gondii Rhoptry Protein ROP16

Toxoplasma gondii, as a zoonotic protozoan parasite, develops sophisticated strategies to manipulate hosts for efficient intracellular survival. After successful invasion, T. gondii injects many effector proteins into host cells for various purposes. TgROP16 (T. gondii rhoptry protein 16), which is secreted from rhoptries into host cells, can activate the host STAT (signal transducer and activator of transcription) signaling pathway through phosphorylation of STAT3 and STAT6. However, whether there are other host proteins modulated by TgROP16 is currently unknown. In this study, yeast two-hybrid (Y2H) screen was used to look for additional host proteins interacting with TgROP16. Yeast cells expressing a mouse cDNA library cloned into the prey vector were used to mate with yeasts expressing ROP16 without signal peptide. Two mouse proteins, Dnaja1 (DnaJ heat shock protein family member A1) and Gabra4 (gamma-aminobutyric acid A receptor, subunit alpha 4) were identified to interact with ROP16 from this screen. Further analysis suggested that the Predomain of ROP16 played key roles in mediating interactions with these host proteins, whereas the contribution from the Kinase domain was minor. The interactions between Dnaja1 and different parts of ROP16 were also estimated in vivo by co-immunoprecipitation. The results showed that the Predomain of ROP16 was the major region to interact with Dnaja1, which is consistent with the Y2H results. Based on the gene ontology analysis, Dnaja1 is predicted to participate in stress response while Gabra4 is involved in the system development process. The discovery of new host proteins that interact with ROP16 of T. gondii will help us to further investigate the functions of this effector proteins during T. gondii infection

Detecting Fraudulent Financial Statements for the Sustainable Development of the Socio-Economy in China: A Multi-Analytic Approach

Identifying financial statement fraud activities is very important for the sustainable development of a socio-economy, especially in China’s emerging capital market. Although many scholars have paid attention to fraud detection in recent years, they have rarely focused on both financial and non-financial predictors by using a multi-analytic approach. The present study detected financial statement fraud activities based on 17 financial and 7 non-financial variables by using six data mining techniques including support vector machine (SVM), classification and regression tree (CART), back propagation neural network (BP-NN), logistic regression (LR), Bayes classifier (Bayes) and K-nearest neighbor (KNN). Specifically, the research period was from 2008 to 2017 and the sample is companies listed on the Shanghai stock exchange and Shenzhen stock exchange, with a total of 536 companies of which 134 companies were allegedly involved in fraud. The stepwise regression and principal component analysis (PCA) were also adopted for reducing variable dimensionality. The experimental results show that the SVM data mining technique has the highest accuracy across all conditions, and after using stepwise regression, 13 significant variables were screened and the classification accuracy of almost all data mining techniques was improved. However, the first 16 principal components transformed by PCA did not yield better classification results. Therefore, the combination of SVM and the stepwise regression dimensionality reduction method was found to be a good model for detecting fraudulent financial statements

A Cysteine-Reloading Process Initiating the Biosynthesis of the Bicyclic Scaffold of Dithiolopyrrolones

Dithiolopyrrolone antibiotics are well known for their outstanding biological activities, and their biosynthesis has been studied vigorously. However, the biosynthesis mechanism of the characteristic bicyclic scaffold is still unknown after years of research. To uncover this mechanism, a multi-domain non-ribosomal peptide synthase DtpB from the biosynthetic gene cluster of thiolutin was selected as an object to study. We discovered that its adenylation domain not only recognized and adenylated cysteine, but also played an essential role in the formation of the peptide bond. Notably, an eight-membered ring compound was also discovered as an intermediate during the formation of the bicyclic structure. Based on these findings, we propose a new mechanism for the biosynthesis of the bicyclic scaffold of dithiolopyrrolones, and unveil additional functions of the adenylation domain