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ObjectiveGut fungi, as symbiosis with the human gastrointestinal tract, may regulate physiology via multiple interactions with host cells. The plausible role of fungi in systemic lupus erythematosus (SLE) is far from clear and need to be explored.MethodsA total of 64 subjects were recruited, including SLE, rheumatoid arthritis (RA), undifferentiated connective tissue diseases (UCTDs) patients and healthy controls (HCs). Fecal samples of subjects were collected. Gut fungi and bacteria were detected by ITS sequencing and 16S rRNA gene sequencing, respectively. Alpha and beta diversities of microbiota were analyzed. Linear discriminant analysis effect size analysis was performed to identify abundance of microbiota in different groups. The correlation network between bacterial and fungal microbiota was analyzed based on Spearman correlation.ResultsGut fungal diversity and community composition exhibited significant shifts in SLE compared with UCTDs, RA and HCs. Compared with HCs, the alpha and beta diversities of fungal microbiota decreased in SLE patients. According to principal coordinates analysis results, the constitution of fungal microbiota from SLE, RA, UCTDs patients and HCs exhibited distinct differences with a clear separation between fungal microbiota. There was dysbiosis in the compositions of fungal and bacterial microbiota in the SLE patients, compared to HCs. Pezizales, Cantharellales and Pseudaleuria were enriched in SLE compared with HCs, RA and UCTDs. There was a complex relationship network between bacterial and fungal microbiota, especially Candida which was related to a variety of bacteria.ConclusionThis study presents a pilot analysis of fungal microbiota with diversity and composition in SLE, and identifies several gut fungi with different abundance patterns taxa among SLE, RA, UCTDs and HCs. Furthermore, the gut bacterial-fungal association network in SLE patients was altered compared with HCs.

With the worldwide epidemics of hyperuricemia and associated gout, the diseases with purine metabolic disorders have become a serious threat to human public health. Accumulating evidence has shown that they have been linked to increased consumption of fructose in humans, we hereby made a timely review on the roles of fructose intake and the gut microbiota in regulating purine metabolism, together with the potential mechanisms by which excessive fructose intake contributes to hyperuricemia and gout. To this end, we focus on the understanding of the interaction between a fructose-rich diet and the gut microbiota in hyperuricemia and gout to seek for safe, cheap, and side-effect-free clinical interventions. Furthermore, fructose intake recommendations for hyperuricemia and gout patients, as well as the variety of probiotics and prebiotics with uric acid-lowering effects targeting the intestinal tract are also summarized to provide reference and guidance for the further research.

Objectives: To evaluate metagenomic next-generation sequencing (mNGS) as a diagnostic tool in detecting pathogens from osteoarticular infection (OAI) samples.Methods: 130 samples of joint fluid, sonicate fluid, and tissue were prospectively collected from 92 patients with OAI. The performance of mNGS and microbiology culture was compared pairwise.Results: The overall sensitivity of mNGS was 88.5% (115/130), significantly higher than that of microbiological culture, which had a sensitivity of 69.2% (90/130, p < 0.01). Sensitivity was significantly higher for joint fluid (mNGS: 86.7% vs. microbiology culture: 68.7%, p < 0.01) and sonicate fluid (mNGS: 100% vs. microbiology culture: 66.7%, p < 0.05) samples. mNGS detected 12 pathogenic strains undetected by microbiological culture. Additional pathogens detected by mNGS were Coagulase-negative Staphylococci, Gram-negative Bacillus, Streptococci, Anaerobe, non-tuberculosis mycobacterium, MTCP (p > 0.05), and Mycoplasma (OR = ∞, 95% confidence interval, 5.12–∞, p < 0.001). Additionally, sensitivity by mNGS was higher in antibiotic-treated samples compared to microbiological culture (89.7 vs. 61.5%, p < 0.01).Conclusions: mNGS is a robust diagnostic tool for pathogenic detection in samples from OAI patients, compared to routine cultures. The mNGS technique is particularly valuable to diagnose pathogens that are difficult to be cultured, or to test samples from patients previously treated with antibiotics.