Mycobacterium marinum mediates regulation of prostaglandin E2 expression on host immune response through cyclooxygenase pathway.

PURPOSE: Investigate the role of COX signaling in activating the PGE2-EP2 pathway. METHODS: Utilized a marine Mycobacterium infection model in zebrafish. Marine mycobacteria were stained with fluorescein isothiocyanate. The COX inhibitor indomethacin, EP2 receptor inhibitor AH6809, EP4 receptor inhibitor AH23848 and clodronate Liposomes were used to investigate the role of COX, EP2, EP4 and macrophage whether participating in combat marine mycobacterial infection. The expression level of the target gene was detected using real-time fluorescence quantitative PCR instrument. RESULTS: The findings revealed that larvae exposed to the COX inhibitor indomethacin or the EP2 receptor inhibitor AH6809 demonstrated a significantly higher mortality rate due to marine mycobacterium infection than those in the control group. Administration of exogenous prostaglandin E2 (PGE2) rescued the survival of zebrafish infected with marine mycobacteria and treated with indomethacin. Additionally, a significant reduction in survival rate was noted in macrophage-depleted zebrafish infected with marine mycobacteria. CONCLUSION: The host may combat marine mycobacterium infection via COX signaling, which activates the PGE2-EP2 pathway and mediates macrophage resistance.

Sputum microbiota as a potential diagnostic marker for multidrug-resistant tuberculosis.

The prevalence of drug-resistant Mycobacterium tuberculosis (Mtb) strains makes disease control more complicated, which is the main cause of death in tuberculosis (TB) patients. Early detection and timely standard treatment are the key to current prevention and control of drug-resistant TB. In recent years, despite the continuous advancement in drug-resistant TB diagnostic technology, the needs for clinical rapid and accurate diagnosis are still not fully met. With the development of sequencing technology, the research of human microecology has been intensified. This study aims to use 16 rRNA sequencing technology to detect and analyze upper respiratory flora of TB patients with anti-TB drug sensitivity (DS, n = 55), monoresistance isoniazide (MR-INH, n = 33), monoresistance rifampin (MR-RFP, n = 12), multidrug resistance (MDR, n = 26) and polyresistance (PR, n = 39) in southern China. Potential microbial diagnostic markers for different types of TB drug resistance are searched by screening differential flora, which provides certain guiding significance for drug resistance diagnosis and clinical drug use of TB. The results showed that the pulmonary microenvironment of TB patients was more susceptible to infection by external pathogens, and the infection of different drug-resistant Mtb leads to changes in different flora. Importantly, seven novel microorganisms (Leptotrichia, Granulicatella, Campylobacter, Delfitia, Kingella, Chlamydophila, Bordetella) were identified by 16S rRNA sequencing as diagnostic markers for different drug resistance types of TB. Leptotrichia, Granulicatella, Campylobacter were potential diagnostic marker for TB patients with INH single-resistance. Delftia was a potential diagnostic marker for TB patients with RFP single drug-resistance. Kingella and Chlamydophila can be used as diagnostic markers for TB patients with PR. Bordetella can be used as a potential diagnostic marker for identification of TB patients with MDR.

Tandem Mass Tag-Based Proteomic Analysis of Potential Biomarkers for Hepatocellular Carcinoma Differentiation.

PURPOSE: The poor prognosis of hepatocellular carcinoma (HCC) urgent us to discover early and effective biomarkers. In this study, we applied tandem mass tag (TMT)-based proteomic analysis to discover potential protein markers for HCC identification and differentiation. PATIENTS AND METHODS: Fifteen patients, well-differentiated (G1, N = 5), moderate-differentiated (G2, N = 5), and poorly differentiated (G3, N = 5), with 30 matched pair tissues (both tumor and adjacent non-tumor tissues derived from the same patient) were enrolled. All samples were subjected to TMT labeling and LC-MS/MS analysis. The identified proteins were subsequently assigned to GO and KEGG for predicting function. The identified protein candidates were validated using immunohistochemistry (IHC). RESULTS: A total of 1010 proteins were identified. Of these, 154 differentially expressed proteins (DEPs), 100 up-regulated and 54 down-regulated, were found between tumor and adjacent non-tumor tissues; 12 DEPs, 9 up-regulated and 3 down-regulated, were found between G1 and G3 tissues; 8 DEPs, 5 up-regulated and 3 down-regulated, were found between G1 and G2 tissues; 11 DEPs, 8 up-regulated and 3 down-regulated, were found between G2 and G3 tissues. Among them, ASS1 and CPS1 were significantly up-regulated while UROD and HBB were significantly down-regulated in G3 compared with G1 and G2 tumors. Three proteins, CYB5A, FKBP11 and YBX1, were significantly up-regulated in G1 compared with both G2 and G3 tumors. The 7 biomarker candidates were further verified by IHC. CONCLUSION: A variety of DEPs related to the histological differentiation of HCC were identified, among which ASS1, CPS1, URPD and HBB proteins were potential biomarkers for distinguishing poorly differentiated HCC, while CYB5A, FKBP11 and YBX1 were potential biomarkers for distinguishing well-differentiated HCC. Our findings may further provide a new insight facilitating the diagnosis and prognosis of HCC.

[Mass spectrometry-based identification of new serum biomarkers in patients with multidrug resistant pulmonary tuberculosis].

OBJECTIVE: To screen new serum metabolic biomarkers for different drug resistance profiles of pulmonary tuberculosis (TB) and explore their mechanisms and functions. METHODS: We collected serum samples from TB patients with drug sensitivity (DS), monoresistance to isoniazid (MR-INH), monoresistance to rifampin (MR-RFP), multidrug resistance (MDR), and polyresistance (PR). The metabolites in the serum samples were extracted by oscillatory and deproteinization for LC-MS/MS analysis, and the results were normalized by Pareto-scaling method and analyzed using Metaboanalyst 4.0 software to identify the differential metabolites. The differential metabolites were characterized by function enrichment and co-expression analysis to explore their function and possible pathological mechanisms. RESULTS: Compared with the DS group, 286 abnormally expressed metabolites were identified in MR-INH group, 362 in MR-RPF group, 277 in MDR group and 1208 in PR group by LC-MS/MS analysis. Acetylagmatine (P < 0.05), aminopentol (P < 0.05), and tetracosanyl oleate (P < 0.05) in MR-INH group; Ala His Pro Thr (P < 0.001) and glycinoprenol-9 (P < 0.05) in MR-RFP group; trimethylamine (P < 0.05), penaresidin A (P < 0.05), and verazine (P < 0.05) in MDR group; and PIP (18:1(11Z)/ 18:3(6Z, 9Z, 12Z)) (P < 0.001), Pro Arg Trp Tyr (P < 0.001), N-methyldioctylamine (P < 0.001), and phytolaccoside E (P < 0.05) in PR group all showed significant differential expressions. Significant differential expressions of phthalic acid mono-2-ethylhexyl ester (P < 0.05) and eicosanoyl-EA (P < 0.05) were found in all the drug resistant groups as compared with DS group. CONCLUSIONS: Acetylagmatine, aminopentol, tetracosanyl oleate, Ala His Pro Thr, glycinoprenol-9, trimethylamine, penaresidin A, verazine, PIP(18:1(11Z)/18:3(6Z, 9Z, 12Z)), Pro Arg Trp Tyr, N-methyldioctylamine, phytolaccoside E, phthalic acid mono-2-ethylhexyl ester, and eicosanoyl-EA are potentially new biomarkers that indicate monoresistance, multi-drug resistance and polyresistance of Mycobacterium tuberculosis. The combined use of these biomarkers potentially allows for assessment of drug resistance in TB and enhances the diagnostic sensitivity and specificity.