Dietary habits have been proven to help alter the composition of gut microbiota, and exploring the impact of nutritional patterns on gut microbiota changes can help protect gut health. However, few studies have focused on the dietary impact on the gut microbiota over an experimental timeframe. In this study, 16S rRNA gene sequencing was employed to investigate the gut microbiota of mice under different dietary patterns, including AIN-93G diet (Control), high protein diet (HPD), high fiber diet (HFD), and switch diet (Switch). The alpha diversity of the HPD group significantly decreased, but HFD can restore this decline. During HPD, some genera were significantly upregulated (e.g., Feacalibaculum) and downregulated (e.g., Parabacteroides). However, after receiving HFD, other genera were upregulated (e.g., Akkermansia) and downregulated (e.g., Lactobacillus). In addition, the interaction between pathogenic bacteria was more pronounced during HPD, while the main effect was probiotics during HFD. In conclusion, the plasticity exhibited by the gut microbiota was subject to dietary influences, wherein disparate dietary regimens hold pivotal significance in upholding the well-being of the host. Therefore, our findings provide new ideas and references for the relationship between diets and gut microbiota.
1 January 2024 in Brazilian Journal of Medical and Biological Research
Gastric cancer (GC) remains a global health challenge due to its heterogeneity and diverse regional epidemiology. Treatment for advanced GC often requires chemotherapy, whose effects are closely associated with the cell cycle. This association highlights the critical need to understand cell cycle regulators that can influence the effectiveness of chemotherapy. Bioinformatics analyses were performed on transcriptome data from a hospital cohort and on a publicly available database. Flow cytometry was used for cell cycle analysis. The interaction of PMEPA1 with 14-3-3σ was confirmed by coimmunoprecipitation and immunofluorescence staining. Western blot analysis was performed following inhibition of protein synthesis and degradation to assess 14-3-3σ protein stability, while ubiquitination was evaluated after treatment with the proteasome inhibitor MG132. High PMEPA1 expression was detected in GC tissues and was correlated with poor prognosis. In vitro overexpression of PMEPA1 promoted GC cell proliferation, while knockdown of PMEPA1 inhibited cell proliferation and induced G2/M arrest. In vivo study showed that overexpressing PMEPA1 promoted tumor growth, while knocking down PMEPA1 inhibited tumor growth, as indicated by the level of the proliferation marker Ki67. 14-3-3σ was identified as a downstream target of PMEPA1. PMEPA1 binds to 14-3-3σ and promoted its degradation by facilitating its ubiquitination. Overexpression of PMEPA1 increased its interactions with TTC3 and 14-3-3σ, increased 14-3-3σ ubiquitination, and reduced 14-3-3σ stability, and the opposite effects were observed after PMEPA1 knockdown. PMEPA1 recruited TTC3, allowing the ubiquitination of 14-3-3σ and leading to its degradation, thus promoting cell cycle progression in GC.
20 June 2023 in Journal of Gastroenterology and Hepatology
The majority of people in the U.S. manage health through at least one prescription drug. Drugs classified as non-antibiotics can adversely affect the gut microbiome and disrupt intestinal homeostasis. Here, we identified medications associated with an increased risk of GI infections across a population cohort of more than 1 million individuals monitored over 15 years. Notably, the cardiac glycoside digoxin and other drugs identified in this epidemiological study are sufficient to alter microbiome composition and risk of Salmonella enterica subsp. Typhimurium (S. Tm) infection in mice. The impact of digoxin treatment on S. Tm infection is transmissible via the microbiome, and characterization of this interaction highlights a digoxin-responsive β defensin that alters microbiome composition and consequent immune surveillance of the invading pathogen. Combining epidemiological and experimental approaches thus provides an opportunity to uncover drug-host-microbiome-pathogen interactions that increase infection risk in humans.