Myeloid-specific Hdac10 deletion protects against LPS-induced acute lung injury via P62 acetylation at lysine 165.

BACKGROUND: Aberrant activation of macrophages is associated with pathogenesis of acute lung injury (ALI). However, the potential pathogenesis has not been explored. OBJECTIVES: We aimed to identify whether histone deacetylase (HDAC) 10 is involved in lipopolysaccharide (LPS)-exposed ALI and reveal the underlying pathogenesis by which it promotes lung inflammation in LPS-exposed ALI via modifying P62 with deacetylation. METHODS: We constructed an ALI mice model stimulated with LPS to determine the positive effect of Hdac10 deficiency. Moreover, we cultured murine alveolar macrophage cell line (MH-S cells) and primary bone marrow-derived macrophages (BMDMs) to explore the pro-inflammatory activity and mechanism of HDAC10 after LPS challenge. RESULTS: HDAC10 expression was increased both in mice lung tissues and macrophage cell lines and promoted inflammatory cytokines production exposed to LPS. Hdac10 deficiency inhibited autophagy and inflammatory response after LPS stimulation. In vivo, Hdac10fl/fl-LysMCre mice considerably attenuated lung inflammation and inflammatory cytokines release exposed to LPS. Mechanistically, HDAC10 interacts with P62 and mediates P62 deacetylation at lysine 165 (K165), by which it promotes P62 expression and increases inflammatory cytokines production. Importantly, we identified that Salvianolic acid B (SAB), an HDAC10 inhibitor, reduces lung inflammatory response in LPS-stimulated ALI. CONCLUSION: These results uncover a previously unknown role for HDAC10 in regulating P62 deacetylation and aggravating lung inflammation in LPS-induced ALI, implicating that targeting HDAC10 is an effective therapy for LPS-exposed ALI.

Comprehensive analysis and identification of subtypes and hub genes of high immune response in lung adenocarcinoma.

BACKGROUND: The advent of immunotherapy targeting immune checkpoints has conferred significant clinical advantages to patients with lung adenocarcinoma (LUAD); However, only a limited subset of patients exhibit responsiveness to this treatment. Consequently, there is an imperative need to stratify LUAD patients based on their response to immunotherapy and enhance the therapeutic efficacy of these treatments. METHODS: The differentially co-expressed genes associated with CD8 + T cells were identified through weighted gene co-expression network analysis (WGCNA) and the Search Tool for the Retrieval of Interacting Genes (STRING) database. These gene signatures facilitated consensus clustering for TCGA-LUAD and GEO cohorts, categorizing them into distinct immune subtypes (C1, C2, C3, and C4). The Tumor Immune Dysfunction and Exclusion (TIDE) model and Immunophenoscore (IPS) analysis were employed to assess the immunotherapy response of these subtypes. Additionally, the impact of inhibitors targeting five hub genes on the interaction between CD8 + T cells and LUAD cells was evaluated using CCK8 and EDU assays. To ascertain the effects of these inhibitors on immune checkpoint genes and the cytotoxicity mediated by CD8 + T cells, flow cytometry, qPCR, and ELISA methods were utilized. RESULTS: Among the identified immune subtypes, subtypes C1 and C3 were characterized by an abundance of immune components and enhanced immunogenicity. Notably, both C1 and C3 exhibited higher T cell dysfunction scores and elevated expression of immune checkpoint genes. Multi-cohort analysis of Lung Adenocarcinoma (LUAD) suggested that these subtypes might elicit superior responses to immunotherapy and chemotherapy. In vitro experiments involved co-culturing LUAD cells with CD8 + T cells and implementing the inhibition of five pivotal genes to assess their function. The inhibition of these genes mitigated the immunosuppression on CD8 + T cells, reduced the levels of PD1 and PD-L1, and promoted the secretion of IFN-γ and IL-2. CONCLUSIONS: Collectively, this study delineated LUAD into four distinct subtypes and identified five hub genes correlated with CD8 + T cell activity. It lays the groundwork for refining personalized therapy and immunotherapy strategies for patients with LUAD.

Epithelial SIRT6 governs IL-17A pathogenicity and drives allergic airway inflammation and remodeling.

Dysregulation of IL-17A is closely associated with airway inflammation and remodeling in severe asthma. However, the molecular mechanisms by which IL-17A is regulated remain unclear. Here we identify epithelial sirtuin 6 (SIRT6) as an epigenetic regulator that governs IL-17A pathogenicity in severe asthma. Mice with airway epithelial cell-specific deletion of Sirt6 are protected against allergen-induced airway inflammation and remodeling via inhibiting IL-17A-mediated inflammatory chemokines and mesenchymal reprogramming. Mechanistically, SIRT6 directly interacts with RORγt and mediates RORγt deacetylation at lysine 192 via its PPXY motifs. SIRT6 promotes RORγt recruitment to the IL-17A gene promoter and enhances its transcription. In severe asthma patients, high expression of SIRT6 positively correlates with airway remodeling and disease severity. SIRT6 inhibitor (OSS_128167) treatment significantly attenuates airway inflammation and remodeling in mice. Collectively, these results uncover a function for SIRT6 in regulating IL-17A pathogenicity in severe asthma, implicating SIRT6 as a potential therapeutic target for severe asthma.

The HDAC10 instructs macrophage M2 program via deacetylation of STAT3 and promotes allergic airway inflammation.

Background: Perturbation of macrophage homeostasis is one of the key mechanisms of airway inflammation in asthma. However, the exact mechanisms remain poorly understood. Objectives: We sought to examine the role of histone deacetylase (HDAC) 10 as an epigenetic regulator that governs macrophage M2 program and promotes airway inflammation in asthma, and to elucidate the underlying mechanisms. Methods: Peripheral blood and airway biopsies were obtained from healthy individuals and asthmatic patients. Asthma was induced by exposure to allergen in mice with myeloid-specific deletion of Hdac10 (Hdac10fl/fl-LysMCre) mice. HDAC10 inhibitor Salvianolic acid B (SAB), STAT3 selective agonist Colivelin, and the specific PI3K/Akt activator 1,3-Dicaffeoylquinic acid (DA) were also used in asthmatic mice. For cell studies, THP1 cells, primary mouse bone marrow derived macrophage (BMDMs) were used and related signaling pathways was investigated. Results: HDAC10 expression was highly expressed by macrophages and promoted M2 macrophage activation and airway inflammation in asthmatic patients and mice. Hdac10fl/fl-LysMCre mice were protected from airway inflammation in experimental asthma model. Hdac10 deficiency significantly attenuated STAT3 expression and decreased M2 macrophage polarization following allergen exposure. Mechanistically, HDAC10 directly binds STAT3 for deacetylation in macrophages, by which it promotes STAT3 expression and activates the macrophage M2 program. Importantly, we identified SAB as a HDAC10 inhibitor that had protective effects against airway inflammation in mice. Conclusions: Our results revealed that HDAC10-STAT3 interaction governs macrophage polarization to promote airway inflammation in asthma, implicating HDAC10 as a therapeutic target.

Potential for aflatoxin B1 and B2 production by Aspergillus flavus strains isolated from rice samples.

In this study, we investigated the potential for aflatoxin B1 (AFB1) and B2 (AFB2) production in rice grain by 127 strains of Aspergillus flavus isolated from rice grains collected from China. These strains were inoculated onto rice grains and incubated at 28 °C for 21 days. AFB1 and AFB2 were extracted and quantified by high-performance liquid chromatography coupled with fluorescence detection. Among the tested strains, 37% produced AFB1 and AFB2 with levels ranging from 175 to 124 101 µg kg(-1) for AFB1 and from not detected to 10 329 µg kg(-1) for AFB2. The mean yields of these isolates were 5884 µg kg(-1) for AFB1 and 1968 µg kg(-1) for AFB2. Overall, most of the aflatoxigenic strains produced higher levels of AFB1 than AFB2 in rice. The obtained information is useful for assessing the risk of aflatoxin contamination in rice samples.

Application of ionic liquid-based dispersive liquid-liquid microextraction for the analysis of ochratoxin A in rice wines.

A novel and rapid ionic liquid-based dispersive liquid-liquid microextraction (IL-DLLME) method combined with liquid chromatography and a fluorescence detector for the analysis of ochratoxin A in rice wines is presented. The following parameters were systematically investigated: type and volume of ionic liquid, volume of dispersive solvent, salt addition, sample pH, and vortex time. Rice wine samples were first diluted to 18% alcohol with deionized water, and the pH was adjusted to 3.0. A DLLME procedure was followed that included IL ([HMIM][PF6]) and ethanol as the extraction and dispersive solvents, respectively. Under the optimized experimental conditions, good linearity was obtained with a correlation coefficient (r) of 0.9998 and a limit of detection (LOD) of 0.04µgL(-1). The recoveries ranged from 75.9% to 82.1% with an RSD below 10.4%. The proposed method was successfully applied to analyse OTA samples from several rice wine brands collected in Guangdong province, China.

Rapid analysis of aflatoxins B1, B2, and ochratoxin A in rice samples using dispersive liquid-liquid microextraction combined with HPLC.

A novel, simple, and rapid method is presented for the analysis of aflatoxin B1, aflatoxin B2, and ochratoxin A in rice samples by dispersive liquid-liquid microextraction combined with LC and fluorescence detection. After extraction of the rice samples with a mixture of acetonitrile/water/acetic acid, mycotoxins were rapidly partitioned into a small volume of organic solvent (chloroform) by dispersive liquid-liquid microextraction. The three mycotoxins were simultaneously determined by LC with fluorescence detection after precolumn derivatization for aflatoxin B1 and B2. Parameters affecting both extraction and dispersive liquid-liquid microextraction procedures, including the extraction solvent, the type and volume of extractant, the volume of dispersive solvent, the addition of salt, the pH and the extraction time, were optimized. The optimized protocol provided an enrichment factor of approximately 1.25 and with detection of limits (0.06-0.5 µg/kg) below the maximum levels imposed by current regulations for aflatoxins and ochratoxin A. The mean recovery of three mycotoxins ranged from 82.9-112%, with a RSD less than 7.9% in all cases. The method was successfully applied to measure mycotoxins in commercial rice samples collected from local supermarkets in China.