Life sciences · 2026
Investigating gut microbiome dysbiosis in adults with chronic kidney disease: Diabetes-induced alterations via metagenomics and qPCR.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Gunasekaran Rajalakshmi Saranya, K Ramesh Babu, Viswanathan Pragasam
Аннотация
BACKGROUND: Type 2 diabetes (T2D) is a major contributor to diabetic nephropathy, the leading cause of chronic kidney disease (CKD). This study investigated gut microbial dysbiosis and composition shift among healthy individuals and diabetic patients with or without CKD using a 16S rRNA metagenomic approach, validated by qRT-PCR and clinical data integration to identify the significant key genera associated with disease progression.
METHODS: Stool samples from 22 individuals were analysed using 16S rRNA amplicon sequencing to assess gut microbiota composition. Differential abundance analysis, LEfSe, and network-based methods were employed to identify key taxa. Significant features were validated by qRT-PCR. Integrated approaches, including Pearson correlation, WGCNA, random forest, and propensity score matching, were used to associate microbial features with clinical markers. Functional enrichment of microbial pathways was predicted using PICRUSt2.
KEY FINDINGS: A total of 1409 amplicon sequence variants (ASVs) were identified. Bray-Curtis dissimilarity showed significant microbial diversity differences between disease and healthy subjects (p < 0.031). Key taxa associated with eGFR and serum creatinine (sCr) included Bacteroidetes uniformis (LFC +9), Ruminococcus (LFC +8.1), and Dialister succinatiphilus (LFC +6.7), linked to disease progression and metabolic regulation. In contrast, protective taxa such as Bifidobacterium adolescentis (LFC -9.5), Faecalibacterium prausnitzii (LFC -6.39), Collinsella, and Megasphaera elsdenii were reduced. Integration of Pearson correlation, WGCNA, propensity score matching, and random forest classification revealed microbial features associated with clinical covariates.
SIGNIFICANCE: Our findings show the gut microbiome shifts begin in diabetics without CKD conditions but become more pronounced in diabetics with CKD, with a lower ratio of beneficial bacteria, reflecting a gradual microbial imbalance along disease progression.
METHODS: Stool samples from 22 individuals were analysed using 16S rRNA amplicon sequencing to assess gut microbiota composition. Differential abundance analysis, LEfSe, and network-based methods were employed to identify key taxa. Significant features were validated by qRT-PCR. Integrated approaches, including Pearson correlation, WGCNA, random forest, and propensity score matching, were used to associate microbial features with clinical markers. Functional enrichment of microbial pathways was predicted using PICRUSt2.
KEY FINDINGS: A total of 1409 amplicon sequence variants (ASVs) were identified. Bray-Curtis dissimilarity showed significant microbial diversity differences between disease and healthy subjects (p < 0.031). Key taxa associated with eGFR and serum creatinine (sCr) included Bacteroidetes uniformis (LFC +9), Ruminococcus (LFC +8.1), and Dialister succinatiphilus (LFC +6.7), linked to disease progression and metabolic regulation. In contrast, protective taxa such as Bifidobacterium adolescentis (LFC -9.5), Faecalibacterium prausnitzii (LFC -6.39), Collinsella, and Megasphaera elsdenii were reduced. Integration of Pearson correlation, WGCNA, propensity score matching, and random forest classification revealed microbial features associated with clinical covariates.
SIGNIFICANCE: Our findings show the gut microbiome shifts begin in diabetics without CKD conditions but become more pronounced in diabetics with CKD, with a lower ratio of beneficial bacteria, reflecting a gradual microbial imbalance along disease progression.