Phosphoproteome Analysis in Immune Cell Signaling

Usp9x contributes to the development of sepsis-induced acute kidney injury by promoting inflammation and apoptosis in renal tubular epithelial cells via activation of the TLR4/nf-κb pathway

As a pattern recognition receptor, Toll-like receptor 4 (TLR4) is crucial for the development and progression of acute kidney injury (AKI). This study aims to explore whether the deubiquitinase Usp9x influences the TLR4/NF-B pathway to cause sepsis-induced acute kidney injury (S-AKI). The model of AKI was established in Sprague-Dawley rats using the cecal ligation and puncture (CLP) method, while renal tubular epithelial cell NRK-52E was stimulated with lipopolysaccharide (LPS) in vitro. All plasmids were transfected into NRK-52E cells according to the indicated group. The deubiquitinase of TLR4 was predicted by the online prediction software Ubibrowser. Subsequently, Western blot and Pearson correlation analysis identified Usp9x protein as a potential candidate. Co-IP analysis verified the interaction between TLR4 and Usp9x. Further research revealed that overexpression of Usp9x inhibited degradation of TLR4 protein by downregulating its ubiquitination modification levels. Both in vivo and in vitro experiments observed that interference with Usp9x effectively alleviated the inflammatory response and apoptosis of renal tubular epithelial cells (RTECs) induced by CLP or LPS, whereas overexpression of TLR4 reversed this situation. Transfection with sh-Usp9x in NRK-52E cells suppressed the expression of proteins associated with the TLR4/NF-κB pathway induced by LPS. Moreover, the overexpression of TLR4 reversed the effect of sh-Usp9x transfection. Therefore, the deubiquitinase Usp9x interacts with TLR4, leading to the upregulation of its expression through deubiquitination modification, and the activation of the TLR4/NF-κB signaling pathway, thereby promoting inflammation and apoptosis in renal tubular epithelial cells and contributing to sepsis-induced acute kidney injury.

Human recombinant relaxin-2 (serelaxin) regulates the proteome, lipidome, lipid metabolism and inflammatory profile of rat visceral adipose tissue

Recombinant human relaxin-2 (serelaxin) has been widely proven as a novel drug with myriad effects at different cardiovascular levels, which support its potential therapeutic efficacy in several cardiovascular diseases (CVD). Considering these effects, together with the influence of relaxin-2 on adipocyte physiology and adipokine secretion, and the connection between visceral adipose tissue (VAT) dysfunction and the development of CVD, we could hypothesize that relaxin-2 may regulate VAT metabolism. Our objective was to evaluate the impact of a 2-week serelaxin treatment on the proteome and lipidome of VAT from Sprague-Dawley rats. We found that serelaxin increased 1 polyunsaturated fatty acid and 6 lysophosphatidylcholines and decreased 4 triglycerides in VAT employing ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) based platforms, and that regulates 47 phosphoproteins using SWATH/MS analysis. Through RT-PCR, we found that serelaxin treatment also caused an effect on VAT lipolysis through an increase in the mRNA expression of hormone-sensitive lipase (HSL) and a decrease in the expression of adipose triglyceride lipase (ATGL), together with a reduction in the VAT expression of the fatty acid transporter cluster of differentiation 36 (Cd36). Serelaxin also caused an anti-inflammatory effect in VAT by the decrease in the mRNA expression of tumor necrosis factor α (TNFα), interleukin-1β (IL-1β), chemerin, and its receptor. In conclusion, our results highlight the regulatory role of serelaxin in the VAT proteome and lipidome, lipolytic function, and inflammatory profile, suggesting the implication of several mechanisms supporting the potential benefit of serelaxin for the prevention of obesity and metabolic disorders.

Omics and systems view of innate immune pathways

Multiomics approaches to studying systems biology are very powerful techniques that can elucidate changes in the genomic, transcriptomic, proteomic, and metabolomic levels within a cell type in response to an infection. These approaches are valuable for understanding the mechanisms behind disease pathogenesis and how the immune system responds to being challenged. With the emergence of the COVID-19 pandemic, the importance and utility of these tools have become evident in garnering a better understanding of the systems biology within the innate and adaptive immune response and for developing treatments and preventative measures for new and emerging pathogens that pose a threat to human health. In this review, we focus on state-of-the-art omics technologies within the scope of innate immunity.

Association of TLR4 gene 2026A/G (rs1927914), 896A/G (rs4986790), and 1196C/T (rs4986791) polymorphisms and cancer susceptibility: Meta-analysis and trial sequential analysis

BACKGROUND

This study was performed to assess the association of TLR4 gene 2026A/G (rs1927914), 896A/G (rs4986790), and 1196C/T (rs4986791) polymorphisms and cancer susceptibility based on published case-control studies.

METHODS

Web of Science, PubMed, Embase, CBM, WanFang Data, CNKI, and VIP database were used for article retrieving. Then, these articles were screened according to the study inclusion and exclusion criteria. The data was extracted, and the study quality was evaluated according to the principle of Newcastle-Ottawa Scale. Meta-analysis was performed by RevMan 5.4 and Stata MP-17 software. Trial sequential analysis was performed by TSA 0.9.5.10 Beta software.

RESULTS

Eighty-seven case-control studies including 25,969 cases and 32,119 controls were included in the meta-analysis. The diseases involved in case groups include prostate cancer, lung cancer, gastric cancer, hepatocellular carcinoma, colorectal cancer, etc. A versus G model of rs1927914, A versus G model of rs4986790 and C versus T model of rs4986791 showed that odds ratio (OR) = 1.08, OR = 0.85, and OR = 0.74 respectively. All the 3 comparisons were statistically significant. Sensitivity analysis showed that the results were stable. Publication bias analysis and trial sequential analysis showed that no significant publication bias was found in the results of the meta-analysis, and the probability of false positives was small.

CONCLUSION

People with A allele of rs1927914, G allele of rs4986790, or T allele of rs4986791 have higher risks of cancer. The results of meta-analysis are stable and have less probability of false positives.

Interrogating Host Antiviral Environments Driven by Nuclear DNA Sensing: A Multiomic Perspective

Nuclear DNA sensors are critical components of the mammalian innate immune system, recognizing the presence of pathogens and initiating immune signaling. These proteins act in the nuclei of infected cells by binding to foreign DNA, such as the viral genomes of nuclear-replicating DNA viruses herpes simplex virus type 1 (HSV-1) and human cytomegalovirus (HCMV). Upon binding to pathogenic DNA, the nuclear DNA sensors were shown to initiate antiviral cytokines, as well as to suppress viral gene expression. These host defense responses involve complex signaling processes that, through protein–protein interactions (PPIs) and post-translational modifications (PTMs), drive extensive remodeling of the cellular transcriptome, proteome, and secretome to generate an antiviral environment. As such, a holistic understanding of these changes is required to understand the mechanisms through which nuclear DNA sensors act. The advent of omics techniques has revolutionized the speed and scale at which biological research is conducted and has been used to make great strides in uncovering the molecular underpinnings of DNA sensing. Here, we review the contribution of proteomics approaches to characterizing nuclear DNA sensors via the discovery of functional PPIs and PTMs, as well as proteome and secretome changes that define a host antiviral environment. We also highlight the value of and future need for integrative multiomic efforts to gain a systems-level understanding of DNA sensors and their influence on epigenetic and transcriptomic alterations during infection.