Laboratory of Cellular Differentiation & Metabolic Disorder, Department of Biotechnology, National Institute of Technology, Durgapur, India.
Gut Microbes. 2024 Jan-Dec;16(1):2304900. doi: 10.1080/19490976.2024.2304900. Epub 2024 Jan 24.
The majority of cohort-specific studies associating gut microbiota with obesity are often contradictory; thus, the replicability of the signature remains questionable. Moreover, the species that drive obesity-associated functional shifts and their replicability remain unexplored. Thus, we aimed to address these questions by analyzing gut microbial metagenome sequencing data to develop an in-depth understanding of obese host-gut microbiota interactions using 3329 samples (Obese, = 1494; Control, = 1835) from 17 different countries, including both 16S rRNA gene and metagenomic sequence data. Fecal metagenomic data from diverse geographical locations were curated, profiled, and pooled using a machine learning-based approach to identify robust global signatures of obesity. Furthermore, gut microbial species and pathways were systematically integrated through the genomic content of the species to identify contributors to obesity-associated functional shifts. The community structure of the obese gut microbiome was evaluated, and a reproducible depletion of diversity was observed in the obese compared to the lean gut. From this, we infer that the loss of diversity in the obese gut is responsible for perturbations in the healthy microbial functional repertoire. We identified 25 highly predictive species and 37 pathway associations as signatures of obesity, which were validated with remarkably high accuracy (AUC, Species: 0.85, and pathway: 0.80) with an independent validation dataset. We observed a reduction in short-chain fatty acid (SCFA) producers (several species, , etc.) and depletion of promoters of gut barrier integrity ( and ) in obese guts. Our analysis underlines SCFAs and purine/pyrimidine biosynthesis, carbohydrate metabolism pathways in control individuals, and amino acid, enzyme cofactor, and peptidoglycan biosynthesis pathway enrichment in obese individuals. We also mapped the contributors to important obesity-associated functional shifts and observed that these are both dataset-specific and shared across the datasets. In summary, a comprehensive analysis of diverse datasets unveils species specifically contributing to functional shifts and consistent gut microbial patterns associated to obesity.
大多数与肥胖相关的特定队列研究都将肠道微生物群与肥胖联系起来，但往往存在矛盾；因此，该特征的可复制性仍存在疑问。此外，驱动肥胖相关功能转变的物种及其可复制性仍未得到探索。因此，我们旨在通过分析肠道微生物宏基因组测序数据来解决这些问题，使用来自 17 个不同国家的 3329 个样本（肥胖组=1494，对照组=1835），包括 16S rRNA 基因和宏基因组序列数据，深入了解肥胖宿主-肠道微生物群的相互作用。从不同地理位置采集粪便宏基因组数据，使用基于机器学习的方法进行策展、分析和汇总，以确定肥胖的稳健全球特征。此外，通过对物种的基因组内容进行系统整合，确定与肥胖相关的功能转变的贡献者，对肠道微生物物种和途径进行了系统整合。评估了肥胖肠道微生物组的群落结构，并观察到与瘦肠相比，肥胖肠道的多样性呈可重复的耗竭。由此推断，肥胖肠道中多样性的丧失是导致健康微生物功能谱紊乱的原因。我们确定了 25 个高度预测性的物种和 37 个途径关联作为肥胖的特征，这些特征在具有独立验证数据集的情况下具有非常高的准确性（AUC，物种：0.85，途径：0.80）得到验证。我们观察到短链脂肪酸（SCFA）产生菌（多种 物种， 等）减少，肠道屏障完整性促进剂（ 和 ）耗竭。我们的分析强调了控制个体中 SCFA 和嘌呤/嘧啶生物合成、碳水化合物代谢途径，以及肥胖个体中氨基酸、酶辅因子和肽聚糖生物合成途径的富集。我们还映射了导致重要肥胖相关功能转变的贡献者，并观察到这些贡献者在数据集之间是特定的和共享的。总之，对不同数据集的综合分析揭示了特定于功能转变的物种以及与肥胖相关的一致肠道微生物模式。
