Starke Svenja, Harris Danielle M M, Paulay Amandine, Aden Konrad, Waschina Silvio
Institute of Human Nutrition and Food Science, Department of Nutriinformatics, Kiel University, Kiel, 24118, Germany.
Institute of Clinical Molecular Biology, Kiel University, Rosalind-Franklin-Straße 12, Kiel, 24118, Germany.
Comput Struct Biotechnol J. 2025 Feb 12;27:821-831. doi: 10.1016/j.csbj.2025.02.004. eCollection 2025.
Small Intestinal Bacterial Overgrowth (SIBO) is linked to various diseases and has been associated with altered serum amino acid levels. However, the direct role of the gut microbiome in these changes remains unconfirmed. This study employs genome-scale metabolic modeling to predict amino acid auxotrophy and peptidase gene profiles in the small intestinal microbiomes of SIBO and non-SIBO subjects. Auxotrophy and peptidase gene profiles were further examined in the large intestinal microbiome under non-dysbiotic conditions to assess their similarity to the microbial SIBO profile. Our analysis revealed that the abundance of auxotrophic bacteria is higher in the microbiota of the small intestine than in the large intestine in non-dysbiotic controls. In patients with SIBO, the abundance of auxotrophies in the small intestine decreased compared to non-SIBO subjects. Peptidase gene profiles in non-dysbiotic individuals were distinct between small and large intestinal microbiomes, with fewer extracellular peptidase genes in small intestine microbiomes. In SIBO, extracellular peptidase genes increased compared to non-SIBO subjects. Further, there were more significant associations between the abundance of auxotrophies and peptidase genes in microbiomes of the small intestine compared to the large intestine. In conclusion, the auxotrophy and peptidase gene profiles of the small and large intestinal microbiomes were distinct. In SIBO, the small intestinal microbiome shifts towards a metabolic state resembling that of the large intestine, particularly in its increased abundance of extracellular peptidase genes. This highlights the potential of genome-scale metabolic modeling in identifying metabolic disruptions associated with SIBO, which could inform the development of targeted interventions.
小肠细菌过度生长（SIBO）与多种疾病相关，并且与血清氨基酸水平的改变有关。然而，肠道微生物群在这些变化中的直接作用仍未得到证实。本研究采用基因组规模的代谢模型来预测SIBO患者和非SIBO患者小肠微生物群中的氨基酸营养缺陷型和肽酶基因谱。在非失调状态下，进一步检测大肠微生物群中的营养缺陷型和肽酶基因谱，以评估它们与SIBO微生物谱的相似性。我们的分析表明，在非失调对照中，小肠微生物群中营养缺陷型细菌的丰度高于大肠。在SIBO患者中，小肠中营养缺陷型的丰度与非SIBO受试者相比有所下降。非失调个体的肽酶基因谱在小肠和大肠微生物群之间存在差异，小肠微生物群中的细胞外肽酶基因较少。在SIBO中，与非SIBO受试者相比，细胞外肽酶基因增加。此外，与大肠相比，小肠微生物群中营养缺陷型的丰度与肽酶基因之间的关联更为显著。总之，小肠和大肠微生物群的营养缺陷型和肽酶基因谱是不同的。在SIBO中，小肠微生物群向类似于大肠的代谢状态转变，特别是其细胞外肽酶基因丰度增加。这突出了基因组规模代谢模型在识别与SIBO相关的代谢紊乱方面的潜力，这可为靶向干预措施的开发提供信息。
