The mechanisms underlying pathophysiological regulation of tissue macrophage (Mφ) subsets remain poorly understood. From the expression of 207 Mφ genes comprising 31 markers for 10 subsets, 45 transcription factors (TFs), 56 immunometabolism enzymes, 23 trained immunity (innate immune memory) enzymes, and 52 other genes in microarray data, we made the following findings. (1) When 34 inflammation diseases and tumor types were grouped into eight categories, there was differential expression of the 31 Mφ markers and 45 Mφ TFs, highlighted by 12 shared and 20 group-specific disease pathways. (2) Mφ in lung, liver, spleen, and intestine (LLSI-Mφ) express higher M1 Mφ markers than lean adipose tissue Mφ (ATMφ) physiologically. (3) Pro-adipogenic TFs C/EBPα and PPARγ and proinflammatory adipokine leptin upregulate the expression of M1 Mφ markers. (4) Among 10 immune checkpoint receptors (ICRs), LLSI-Mφ and bone marrow (BM) Mφ express higher levels of CD274 (PDL-1) than ATMφ, presumably to counteract the M1 dominant status via its reverse signaling behavior. (5) Among 24 intercellular communication exosome mediators, LLSI- and BM- Mφ prefer to use RAB27A and STX3 than RAB31 and YKT6, suggesting new inflammatory exosome mediators for propagating inflammation. (6) Mφ in peritoneal tissue and LLSI-Mφ upregulate higher levels of immunometabolism enzymes than does ATMφ. (7) Mφ from peritoneum and LLSI-Mφ upregulate more trained immunity enzyme genes than does ATMφ. Our results suggest that multiple new mechanisms including the cell surface, intracellular immunometabolism, trained immunity, and TFs may be responsible for disease group-specific and shared pathways. Our findings have provided novel insights on the pathophysiological regulation of tissue Mφ, the disease group-specific and shared pathways of Mφ, and novel therapeutic targets for cancers and inflammations.
We reported that microRNA-155 (miR-155) deficiency in ApoE-/- mice yields a novel metabolically healthy obese (MHO) model, which exhibits improved atherosclerosis but results in obesity, non-alcoholic fatty liver disease (NAFLD) without insulin resistance. Using experimental data mining approaches combined with experiments, we found that, among 109 miRNAs, miR-155, and miR-221 are significantly modulated in all four hyperlipidemia-related diseases (HRDs), namely atherosclerosis, NAFLD, obesity and type II diabetes (T2DM). MiR-155 is significantly upregulated in atherosclerosis and decreased in other HRDs. MiR-221 is increased in three HRDs but reduced in obesity. These findings led to our new classification of types I and II MHOs, which are regulated by miR-221 and miR-155, respectively. Western blots showed that the proinflammatory adipokine, resistin, is significantly increased in white adipose tissues (WAT) of the MHO mice, revealing our newly proposed, miR-155-suppressed “secondary wave inflammatory state (SWIS),” characteristic of MHO transition to classical obesity (CO). Taken together, we are first to show that MHO may have heterogeneity in comorbidities, and is therefore classified into type I, and type II MHOs; and that increased expression of resistin in miR-155-/- white adipose tissues may be a driver for SWIS in MHO transition to CO. Our findings provide novel insights into the pathogenesis of MHO, MHO transition to CO, hyperlipidemic pathways related to cancer, and new therapeutic targets.
Both adenine base editors (ABEs) and cytosine base editors (CBEs) have been recently revealed to induce transcriptome-wide RNA off-target editing in a guide RNA-independent manner. Here we construct a reporter system containing E.coli Hokb gene with a tRNA-like motif for robust detection of RNA editing activities as the optimized ABE, ABEmax, induces highly efficient A-to-I (inosine) editing within an E.coli tRNA-like structure. Then, we design mutations to disrupt the potential interaction between TadA and tRNAs in structure-guided principles and find that Arginine 153 (R153) within TadA is essential for deaminating RNAs with core tRNA-like structures. Two ABEmax or mini ABEmax variants (TadA* fused with Cas9n) with deletion of R153 within TadA and/or TadA* (named as del153/del153* and mini del153) are successfully engineered, showing minimized RNA off-targeting, but comparable DNA on-targeting activities. Moreover, R153 deletion in recently reported ABE8e or ABE8s can also largely reduce their RNA off-targeting activities. Taken together, we develop a strategy to generate engineered ABEs (eABEs) with minimized RNA off-targeting activities.
Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease around the world. However, there is still no drug for NAFLD in the market, the study of potential therapeutic drugs on NAFLD is extraordinarily pressing and urgent. The rodent models for NAFLD drugs' study are always with a long time cost. Therefore, we aim to establish a short-time NAFLD drug screening model. A laboratory-made high cholesterol diet was used on larval zebrafish for 3 weeks to establish the NAFLD screen model. Lipid metabolism, oxidant stress, and pathology were studied to comprehensively demonstrate the whole spectrum of NAFLD on this model. Bezafibrate and pioglitazone were used to evaluate the model. Moreover, mechanism research was performed on this model.The NAFLD larval zebrafish model was established with the comprehensive process of NAFLD. Moreover, multiple index on lipid metabolism, oxidant stress, hepatic steatosis, and hepatic inflammation can be easily tested for drug screening. Furthermore, this model can be used to perform the mechanism research by testing mRNA expression. The NAFLD larval zebrafish model is a comprehensive short-time screening method for NAFLD drugs.
Background: The mechanisms underlying low intensity ultrasound (LIUS) mediated suppression of inflammation and tumorigenesis remain poorly determined. Methods: We used microarray datasets from NCBI GEO Dataset databases and conducted a comprehensive data mining analyses, where we studied the gene expression of 299 cell death regulators that regulate 13 different cell death types (cell death regulatome) in cells treated with LIUS. Results: We made the following findings: (1) LIUS exerts a profound effect on the expression of cell death regulatome in cancer cells and non-cancer cells. Of note, LIUS has the tendency to downregulate the gene expression of cell death regulators in non-cancer cells. Most of the cell death regulator genes downregulated by LIUS in non-cancer cells are responsible for mediating inflammatory signaling pathways; (2) LIUS activates different cell death transcription factors in cancer and non-cancer cells. Transcription factors TP-53 and SRF- were induced by LIUS exposure in cancer cells and non-cancer cells, respectively; (3) As two well-accepted mechanisms of LIUS, mild hyperthermia and oscillatory shear stress induce changes in the expression of cell death regulators, therefore, may be responsible for inducing LIUS mediated changes in gene expression patterns of cell death regulators in cells; (4) LIUS exposure may change the redox status of the cells. LIUS may induce more of antioxidant effects in non-cancer cells compared to cancer cells; and (5) The genes modulated by LIUS in cancer cells have distinct chromatin long range interaction (CLRI) patterns to that of non-cancer cells. Conclusions: Our analysis suggests novel molecular mechanisms that may be utilized by LIUS to induce tumor suppression and inflammation inhibition. Our findings may lead to development of new treatment protocols for cancers and chronic inflammation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.