Investigating gut microbiota-blood and urine metabolite correlations in early sepsis-induced acute kidney injury: insights from targeted KEGG analyses

• Published in: Frontiers in cellular and infection microbiology Vol. 14; p. 1375874
• Main Authors: Xu, Yaya, Xu, Jiayue, Zhu, Yueniu, Mao, Haoyun, Li, Jiru, Kong, Xiangmei, Zhu, Xiaodong, Zhang, Jianhua
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 03-06-2024
• Subjects: Acute Kidney Injury - metabolism; Aged; Bacteria - classification; Bacteria - genetics; Bacteria - isolation & purification; Bacteria - metabolism; blood metabolome; Cellular and Infection Microbiology; Female; Gastrointestinal Microbiome; gut microbiota; Humans; kidney injury; Male; Metabolome; Metabolomics - methods; Metagenomics - methods; Middle Aged; pediatric; Prospective Studies; sepsis; Sepsis - microbiology; Sepsis - urine; Urine - chemistry; Urine - microbiology; blood metabolome; kidney injury; gut microbiota; sepsis; pediatric
• ISSN: 2235-2988; 2235-2988
• DOI: 10.3389/fcimb.2024.1375874

The interplay between gut microbiota and metabolites in the early stages of sepsis-induced acute kidney injury (SA-AKI) is not yet clearly understood. This study explores the characteristics and interactions of gut microbiota, and blood and urinary metabolites in patients with SA-AKI.
Utilizing a prospective observational approach, we conducted comparative analyses of gut microbiota and metabolites via metabolomics and metagenomics in individuals diagnosed with SA-AKI compared to those without AKI (NCT06197828). Pearson correlations were used to identify associations between microbiota, metabolites, and clinical indicators. The Comprehensive Antibiotic Resistance Database was employed to detect antibiotic resistance genes (ARGs), while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways informed on metabolic processes and microbial resistance patterns.
Our study included analysis of four patients with SA-AKI and five without AKI. Significant disparities in bacterial composition were observed, illustrated by diversity indices (Shannon index: 2.0 ± 0.4 vs. 1.4 ± 0.6,
= 0.230; Simpson index: 0.8 ± 0.1 vs. 0.6 ± 0.2,
= 0.494) between the SA-AKI group and the non-AKI group. N6, N6, N6-Trimethyl-L-lysine was detected in both blood and urine metabolites, and also showed significant correlations with specific gut microbiota (Campylobacter hominis and Bacteroides caccae,
> 0,
< 0.05). Both blood and urine metabolites were enriched in the lysine degradation pathway. We also identified the citrate cycle (TCA cycle) as a KEGG pathway enriched in sets of differentially expressed ARGs in the gut microbiota, which exhibits an association with lysine degradation.
Significant differences in gut microbiota and metabolites were observed between the SA-AKI and non-AKI groups, uncovering potential biomarkers and metabolic changes linked to SA-AKI. The lysine degradation pathway may serve as a crucial link connecting gut microbiota and metabolites.