Alterations in purine and pyrimidine metabolism associated with latent tuberculosis infection: insights from gut microbiome and metabolomics analyses.

IF 5 2区 生物学 Q1 MICROBIOLOGY mSystems Pub Date : 2024-10-22 DOI:10.1128/msystems.00812-24
Boyi Yang, Xiaojing Guo, Chongyu Shi, Gang Liu, Xiaoling Qin, Shiyi Chen, Li Gan, Dongxu Liang, Kai Shao, Ruolan Xu, Jieqing Zhong, Yujie Mo, Hai Li, Dan Luo
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Abstract

Individuals with latent tuberculosis infection (LTBI) account for almost 30% of the population worldwide and have the potential to develop active tuberculosis (ATB). Despite this, the current understanding of the pathogenesis of LTBI is limited. The gut microbiome can be altered in tuberculosis patients, and an understanding of the changes associated with the progression from good health to LTBI to ATB can provide novel perspectives for understanding the pathogenesis of LTBI by identifying microbial and molecular biomarkers associated therewith. In this study, fecal samples from healthy controls (HC), individuals with LTBI and ATB patients were collected for gut microbiome and metabolomics analyses. Compared to HC and LTBI subjects, participants with ATB showed a significant decrease in gut bacterial α-diversity. Additionally, there were significant differences in gut microbial communities and metabolism among the HC, LTBI, and ATB groups. PICRUSt2 analysis revealed that microbiota metabolic pathways involving the degradation of purine and pyrimidine metabolites were upregulated in LTBI and ATB individuals relative to HCs. Metabolomic profiling similarly revealed that purine and pyrimidine metabolite levels were decreased in LTBI and ATB samples relative to those from HCs. Further correlation analyses revealed that the levels of purine and pyrimidine metabolites were negatively correlated with those of gut microbial genera represented by Ruminococcus_gnavus_group (R. gnavus), and the levels of R. gnavus were also positively correlated with adenosine nucleotide degradation II, which is a purine degradation pathway. Moreover, a combined signature including hypoxanthine and xanthine was found to effectively distinguish between LTBI and HC samples (area under the curve [AUC] of training set = 0.796; AUC of testing set = 0.924). Therefore, through gut microbiome and metabolomic analyses, these findings provide valuable clues regarding how alterations in gut purine and pyrimidine metabolism are linked to the pathogenesis of LTBI.IMPORTANCEThis study provides valuable insight into alterations in the gut microbiome and metabolomic profiles in a cohort of adults with LTBI and ATB. Perturbed gut purine and pyrimidine metabolism in LTBI was associated with the compositional alterations of gut microbiota, which may be an impetus for developing novel diagnostic strategies and interventions targeting LTBI.

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与肺结核潜伏感染相关的嘌呤和嘧啶代谢变化:肠道微生物组和代谢组学分析的启示。
全球潜伏肺结核感染者(LTBI)几乎占总人口的 30%,并有可能发展成活动性肺结核(ATB)。尽管如此,目前对 LTBI 发病机制的了解仍然有限。肺结核患者的肠道微生物组可能会发生改变,而了解从健康到LTBI再到ATB过程中的相关变化,可以通过确定与之相关的微生物和分子生物标记物,为了解LTBI的发病机制提供新的视角。本研究收集了健康对照组(HC)、LTBI 患者和 ATB 患者的粪便样本,进行肠道微生物组和代谢组学分析。与健康对照组和 LTBI 受试者相比,ATB 患者的肠道细菌 α 多样性显著下降。此外,HC 组、LTBI 组和 ATB 组的肠道微生物群落和代谢也存在显著差异。PICRUSt2 分析显示,相对于慢性阻塞性肺病患者,慢性阻塞性肺病患者和急性阻塞性肺病患者体内涉及嘌呤和嘧啶代谢物降解的微生物群代谢途径上调。代谢组学分析同样显示,与 HCs 样本相比,LTBI 和 ATB 样本中的嘌呤和嘧啶代谢物水平有所下降。进一步的相关性分析表明,嘌呤和嘧啶代谢物的水平与以反刍球菌属(R. gnavus)为代表的肠道微生物属的水平呈负相关,而反刍球菌属的水平还与腺苷核苷酸降解 II 呈正相关,腺苷核苷酸降解 II 是一种嘌呤降解途径。此外,研究还发现包括次黄嘌呤和黄嘌呤的组合特征能有效区分LTBI和HC样本(训练集的曲线下面积[AUC]=0.796;测试集的曲线下面积[AUC]=0.924)。因此,通过肠道微生物组和代谢组分析,这些发现为了解肠道嘌呤和嘧啶代谢的改变如何与 LTBI 的发病机制相关联提供了有价值的线索。重要意义这项研究为了解患有 LTBI 和 ATB 的成人队列中肠道微生物组和代谢组的改变提供了有价值的见解。LTBI患者肠道嘌呤和嘧啶代谢紊乱与肠道微生物群的组成改变有关,这可能会推动针对LTBI的新型诊断策略和干预措施的开发。
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来源期刊
mSystems
mSystems Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍: mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.
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