Global analysis of the eukaryotic pathways and networks regulated by Salmonella typhimurium in mouse intestinal infection in vivo

<p>Abstract</p> <p>Background</p> <p>Acute enteritis caused by <it>Salmonella </it>is a public health concern. <it>Salmonella </it>infection is also known to increase the risk of inflammatory bowel diseases and cancer. Therefore, it is important to understand how <it>Salmonella </it>works in targeting eukaryotic pathways in intestinal infection. However, the global physiological function of <it>Salmonella </it>typhimurium in intestinal mucosa <it>in vivo </it>is unclear. In this study, a whole genome approach combined with bioinformatics assays was used to investigate the <it>in vivo </it>genetic responses of the mouse colon to <it>Salmonella</it>. We focused on the intestinal responses in the early stage (8 hours) and late stage (4 days) after <it>Salmonella </it>infection.</p> <p>Results</p> <p>Of the 28,000 genes represented on the array, our analysis of mRNA expression in mouse colon mucosa showed that a total of 856 genes were expressed differentially at 8 hours post-infection. At 4 days post-infection, a total of 7558 genes were expressed differentially. 23 differentially expressed genes from the microarray data was further examined by real-time PCR. Ingenuity Pathways Analysis identified that the most significant pathway associated with the differentially expressed genes in 8 hours post-infection is oxidative phosphorylation, which targets the mitochondria. At the late stage of infection, a series of pathways associated with immune and inflammatory response, proliferation, and apoptosis were identified, whereas the oxidative phosphorylation was shut off. Histology analysis confirmed the biological role of <it>Salmonella</it>, which induced a physiological state of inflammation and proliferation in the colon mucosa through the regulation of multiple signaling pathways. Most of the metabolism-related pathways were targeted by down-regulated genes, and a general repression process of metabolic pathways was observed. Network analysis supported IFN-γ and TNF-α function as mediators of the immune/inflammatory response for host defense against pathogen.</p> <p>Conclusion</p> <p>Our study provides novel genome-wide transcriptional profiling data on the mouse colon mucosa's response to the <it>Salmonella typhimurium </it>infection. Building the pathways and networks of interactions between these genes help us to understand the complex interplay in the mice colon during <it>Salmonella </it>infection, and further provide new insights into the molecular cascade, which is mobilized to combat <it>Salmonella</it>-associated colon infection <it>in vivo</it>.</p

Vitamin D receptor protects against dysbiosis and tumorigenesis via the JAK/STAT pathway in intestine

BACKGROUND & AIMS: Vitamin D exerts regulatory roles via vitamin D receptor (VDR) in mucosal immunity, host defense, and inflammation involving host factors and microbiome. Human Vdr gene variation shapes the microbiome and VDR deletion leads to dysbiosis. Low VDR expression and diminished vitamin D/VDR signaling are observed in colon cancer. Nevertheless, how intestinal epithelial VDR is involved in tumorigenesis through gut microbiota remains unknown. We hypothesized that intestinal VDR protects mice against dysbiosis via modulating the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway in tumorigenesis. METHODS: To test our hypothesis, we used an azoxymethane/dextran sulfate sodium-induced cancer model in intestinal VDR conditional knockout (VDR RESULTS: VDR CONCLUSIONS: We provide insights into the mechanism of VDR dysfunction leading to dysbiosis and tumorigenesis. It indicates a new target: microbiome and VDR for the prevention of cancer

Chronic Effects of a Salmonella Type III Secretion Effector Protein AvrA In Vivo

Salmonella infection is a common public health problem that can become chronic and increase the risk of inflammatory bowel diseases and cancer. AvrA is a Salmonella bacterial type III secretion effector protein. Increasing evidence demonstrates that AvrA is a multi-functional enzyme with critical roles in inhibiting inflammation, regulating apoptosis, and enhancing proliferation. However, the chronic effects of Salmonella and effector AvrA in vivo are still unknown. Moreover, alive, mutated, non-invasive Salmonella is used as a vector to specifically target cancer cells. However, studies are lacking on chronic infection with non-pathogenic or mutated Salmonella in the host.We infected mice with Salmonella Typhimurium for 27 weeks and investigated the physiological effects as well as the role of AvrA in intestinal inflammation. We found altered body weight, intestinal pathology, and bacterial translocation in spleen, liver, and gallbladder in chronically Salmonella-infected mice. Moreover, AvrA suppressed intestinal inflammation and inhibited the secretion of cytokines IL-12, IFN-gamma, and TNF-alpha. AvrA expression in Salmonella enhanced its invasion ability. Liver abscess and Salmonella translocation in the gallbladder were observed and may be associated with AvrA expression in Salmonella.We created a mouse model with persistent Salmonella infection in vivo. Our study further emphasizes the importance of the Salmonella effector protein AvrA in intestinal inflammation, bacterial translocation, and chronic infection in vivo

MaskCLIP: Masked Self-Distillation Advances Contrastive Language-Image Pretraining

This paper presents a simple yet effective framework MaskCLIP, which incorporates a newly proposed masked self-distillation into contrastive language-image pretraining. The core idea of masked self-distillation is to distill representation from a full image to the representation predicted from a masked image. Such incorporation enjoys two vital benefits. First, masked self-distillation targets local patch representation learning, which is complementary to vision-language contrastive focusing on text-related representation. Second, masked self-distillation is also consistent with vision-language contrastive from the perspective of training objective as both utilize the visual encoder for feature aligning, and thus is able to learn local semantics getting indirect supervision from the language. We provide specially designed experiments with a comprehensive analysis to validate the two benefits. Symmetrically, we also introduce the local semantic supervision into the text branch, which further improves the pretraining performance. With extensive experiments, we show that MaskCLIP, when applied to various challenging downstream tasks, achieves superior results in linear probing, finetuning, and zero-shot performance with the guidance of the language encoder. Code will be release at \url{https://github.com/LightDXY/MaskCLIP}.Comment: CVPR 2023, code is available at https://github.com/LightDXY/MaskCLI

Wnt2 inhibits enteric bacterial-induced inflammation in intestinal epithelial cells:

Wnt signaling plays an essential role in gastrointestinal epithelial proliferation. Most investigations have focused on developmental and immune responses. Bacterial infection can be chronic and increases the risk of inflammatory bowel disease and colitis-associated cancer. However, we lack studies on how bacteria regulate Wnt proteins and how Wnts modulate the host responses to enteric bacteria. This study investigated the effects of Salmonella and E. coli on Wnt2, one of the Wnt family members, in intestinal epithelia cells

A Physically-Based Plastic Constitutive Model Considering Nanoparticle Cluster Effect for Metal Matrix Nanocomposites

As a type of emerging nanomaterials, lightweight metal matrix nanocomposites (MMNCs) with enhanced strength are becoming more and more attractive in recent years. However, nano-sized ceramic particles tend to form clusters during processing. In this paper, we established a physically-based plastic constitutive model to consider the detrimental effect of nanoparticle clusters on strength of MMNCs. We amended the particle size in the constitutive model with an equivalent size of both dispersed and clustered nanoparticles, which was deduced by introducing a probability density function of random distribution and a clustering extent function of nanoparticles. The model was validated by the data from literatures. The model was applied to determine important variables to improve the mechanical properties of MMNCs, including the effects of particle volume fraction, particle size, temperature, and strain rate sensitivities on the strength and flow stress of MMNCs. The model suggests that there exists a maximum strength in MMNCs versus the volume fraction of nanoparticles due to the cluster effect since it is very difficult for current processing techniques to achieve a perfectly uniform dispersion of nanoparticles in MMNCs