Mist1 promoted inflammation in colitis model via K+-ATPase NLRP3 inflammasome by SNAI1

In vitro models and ex vivo systems used in inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic, relapsing gastrointestinal condition. Ulcerative colitis and Crohn’s disease are types of inflammatory bowel disease. Over many decades, the disease has been a topic of study, with experts still trying to figure out its cause and pathology. Researchers have established many in vivo animal models, in vitro cell lines, and ex vivo systems to understand its cause ultimately and adequately identify a therapy. However, in vivo animal models cannot be regarded as good models for studying IBD since they cannot completely simulate the disease. Furthermore, because species differences are a crucial subject of concern, in vitro cell lines and ex vivo systems can be employed to recreate the condition properly. In vitro models serve as the starting point for biological and medical research. Ex vivo and in vitro models for replicating gut physiology have been developed. This review aims to present a clear understanding of several in vitro and ex vivo models of IBD and provide insights into their benefits and limits and their value in understanding intestinal physiology.

Tectoridin alleviates lipopolysaccharide -induced inflammaion via inhibiting TLR4-NF-κB/NLRP3 signaling in vivo and in vitro

BACKGROUD

Tectoridin, widely extracted and separated from the rhizome of Iris tectorum Maxium, is extensively reported to have affluent bioactivity, but rarely reported to have anti-inflammatory effects. In this study, we aim to investigate the anti-inflammatory effects and the underlying mechanisms of tectoridin.

METHODS

Here, RAW264.7 macrophages were stimulated with Lipopolysaccharide (LPS) for the inflammation model in vitro. Experimental animals received tectoridin and Dexamethasone (DEX) before LPS injection for endotoxic shock mouse model in vivo. The pro-inflammatory mediators and cytokines in the cell supernatant and serum were detected by ELISA kits. The tissue damages were assessed by biochemical indexes and H&E staining. Immunohistochemistry and Western blot were performed for the detection of proteins.

RESULTS

Our data showed that tectoridin attenuated the LPS-up-regulated nitric oxide (NO), interleukin-6, (IL-6) and interleukin-18, (IL-18) from macrophages and tumor necrosis factor-α, (TNF-α); (IL-6) and (IL-1β) in the serum levels. Besides, our histopathological study showed that the damages caused by LPS in the lung, liver and kidney tissues were decreased. Furthermore, our results demonstrated that tectoridin inhibited the activation of TLR4-NF-κB/NLRP3 signaling proved by immunohistochemistry assay and Western blot.

CONCLUSION

Taken all together, tectoridin might have the potential ability of anti-inflammatory effects and the possible mechanism may be relevant to its inhibition of TLR4-NF-κB/NLRP3 signaling.

A systems genomics approach to uncover patient-specific pathogenic pathways and proteins in ulcerative colitis

We describe a precision medicine workflow, the integrated single nucleotide polymorphism network platform (iSNP), designed to determine the mechanisms by which SNPs affect cellular regulatory networks, and how SNP co-occurrences contribute to disease pathogenesis in ulcerative colitis (UC). Using SNP profiles of 378 UC patients we map the regulatory effects of the SNPs to a human signalling network containing protein-protein, miRNA-mRNA and transcription factor binding interactions. With unsupervised clustering algorithms we group these patient-specific networks into four distinct clusters driven by PRKCB, HLA, SNAI1/CEBPB/PTPN1 and VEGFA/XPO5/POLH hubs. The pathway analysis identifies calcium homeostasis, wound healing and cell motility as key processes in UC pathogenesis. Using transcriptomic data from an independent patient cohort, with three complementary validation approaches focusing on the SNP-affected genes, the patient specific modules and affected functions, we confirm the regulatory impact of non-coding SNPs. iSNP identified regulatory effects for disease-associated non-coding SNPs, and by predicting the patient-specific pathogenic processes, we propose a systems-level way to stratify patients.