| Literature DB >> 31315667 |
Hudan Pan1, Ruijin Guo1,2,3, Yanmei Ju2,3, Qi Wang2,3,4, Jie Zhu2,3, Ying Xie1, Yanfang Zheng1,5, Ting Li1, Zhongqiu Liu6, Linlin Lu6, Fei Li2,3,4, Bin Tong2,3, Liang Xiao2,3,7, Xun Xu2,3, Elaine Lai-Han Leung1, Runze Li1, Huanming Yang2,3,8, Jian Wang2,3,8, Hua Zhou1, Huijue Jia9,10, Liang Liu11.
Abstract
BACKGROUND: Early treatment is key for optimizing the therapeutic success of drugs, and the current initiating treatment that blocks the progression of bone destruction during the pre-arthritic stages remains unsatisfactory. The microbial disorder in rheumatoid arthritis (RA) patients is significantly reversed with effective treatment. Modulating aberrant gut microbiomes into a healthy state is a potential therapeutic approach for preventing bone damage.Entities:
Year: 2019 PMID: 31315667 PMCID: PMC6637628 DOI: 10.1186/s40168-019-0719-1
Source DB: PubMed Journal: Microbiome ISSN: 2049-2618 Impact factor: 14.650
Fig. 1L. casei alleviates the adjuvant-induced arthritis of rats. Effects of L. casei on arthritis score (a) and increased hind paw volume (b) are shown (n = 7 for each group). Data in a, b are shown as mean ± s.e.m. Differences between groups are analyzed by two-way ANOVA (*P < 0.05, **P < 0.01, ***P < 0.001 VS model). The photographs, X-ray, and micro-CT images of ankles are shown in c. Representative images of pathological sections of knees in rats in different groups are shown in d. The pathological improvements are assessed by pathological score e. Radiological score and micro-CT score are evaluated using the micro-CT image and micro-CT analyzer, respectively (f, g). Data in e, f, and g are shown as mean ± s.e.m. Differences among groups are analyzed by one-way ANOVA. (*P < 0.05, **P < 0.01, ***P < 0.001 VS model). The integral assessments of the bone destruction levels are shown in (h). Data are shown as mean and classified into several levels. 0–0.2: normal; 0.2–0.4: light (Lig); 0.4–0.6: moderate (Mod); 0.6–0.8: severe (Sev); 0.8 and above: very severe. Normal, normal control; model, disease control; MTX, methotrexate
Fig. 2Dynamic changes of the gut microbiota composition in the L. casei/MTX-treated rats over time. Distances from healthy plane (HP) and model plane (DP) for each sample of the L. casei-/MTX-treated rats on the five time points are shown. The colors of lines correspond to different samples and the thickness reflects the severity of arthritis. Difference between HP and DP is analyzed by paired t tests
Fig. 3Log10 fold change of the relative abundance of arthritis-correlated species at TP5 in comparison with samples of TP1. Boxes represent the median and interquartile ranges (IQRs) between the first and third quartiles; whiskers represent the lowest or highest values within 1.5 times IQR from the first or third quartiles. Circles represent samples. Significant fold change is marked with an asterisk
Fig. 4L. casei inhibits pro-inflammatory cytokines expression via resurrection of L. acidophilus. a The expressions of cytokines (IL-17, IL-1β, TNFα, IL-6, IFN-γ, IL-2) in serum are assessed using ELISA. Data are shown as mean ± s.e.m and min, max. Differences between groups are analyzed by one-way ANOVA. (*P < 0.05, **P < 0.01, ***P < 0.001 VS model). b Associations of the abundance of L. acidophilus with plasmatic cytokines. cc, Spearman’s correlation coefficient after adjustment for weight, group, and arthritis score
Fig. 5L. casei maintains the redox balance of oxidative stress. Mean log2 fold changes in the abundance of immune-related KEGG modules at TP5 in comparison with samples of TP1 from MTX, L. casei, and model group. The KEGG orthology group modules and groups are ordered by unsupervised hierarchical clustering. Cyan, reduced modules; red, increased modules. Modules missing from one or more groups are not plotted