Altered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease

Dynamic network modeling of gut microbiota during Alzheimer's disease progression in mice

The intimate association between the gut microbiota (GM) and the central nervous system points to potential intervention strategies for neurological diseases. Nevertheless, there is currently no theoretical framework for selecting the window period and target bacteria for GM interventions owing to the complexity of the gut microecosystem. In this study, we constructed a complex network-based modeling approach to evaluate the topological features of the GM and infer the window period and bacterial candidates for GM interventions. We used Alzheimer's disease (AD) as an example and traced the GM dynamic changes in AD and wild-type mice at one, two, three, six, and nine months of age. The results revealed alterations of the topological features of the GM from a scale-free network into a random network during AD progression, indicating severe GM disequilibrium at the late stage of AD. Through stability and vulnerability assessments of the GM networks, we identified the third month after birth as the optimal window period for GM interventions in AD mice. Further computational simulations and robustness evaluations determined that the hub bacteria were potential candidates for GM interventions. Moreover, our GM functional analysis suggested that Lachnospiraceae UCG-001 - the hub and enriched bacterium in AD mice - was the keystone bacterium for GM interventions owing to its contributions to quinolinic acid synthesis. In conclusion, this study established a complex network-based modeling approach as a practical strategy for disease interventions from the perspective of the gut microecosystem.

The gut metagenomics and metabolomics signature in patients with inflammatory bowel disease

Inflammatory bowel disease (IBD), a chronic gut immune dysregulation and dysbiosis condition is rapidly increasing in global incidence. Regardless, there is a lack of ideal diagnostic markers, while conventional treatment provides scarce desired results, thus, the exploration for better options. Changes in the gut microbial composition and metabolites either lead to or are caused by the immune dysregulation that characterizes IBD. This study examined the fecal metagenomics and metabolomic changes in IBD patients. A total of 30 fecal samples were collected from 15 IBD patients and 15 healthy controls for 16S rDNA gene sequencing and UHPLC/Q-TOF-MS detection of metabolomics. Results showed that there was a severe perturbation of gut bacteria community composition, diversity, metabolites, and associated functions and metabolic pathways in IBD. This included a significantly decreased abundance of Bacteroidetes and Firmicutes, increased disease-associated phyla such as Proteobacteria and Actinobacteria, and increased Escherichiacoli and Klebsiellapneumoniae in IBD. A total of 3146 metabolites were detected out of which 135 were differentially expressed between IBD and controls. Metabolites with high sensitivity and specificity in differentiating IBD from healthy individuals included 6,7,4′-trihydroxyisoflavone and thyroxine 4′-o-.beta.-d-glucuronide (AUC = 0.92), normorphine and salvinorin a (AUC = 0.90), and trichostachine (AUC = 0.91). Moreover, the IBD group had significantly affected pathways including primary bile acid biosynthesis, vitamin digestion and absorption, and carbohydrate metabolism. This study reveals that the combined evaluation of metabolites and fecal microbiome can be useful to discriminate between healthy subjects and IBD patients and consequently serve as therapeutic and diagnostic targets.