Lipid A in outer membrane vesicles shields bacteria from polymyxins.

The continuous emergence of multidrug-resistant bacterial pathogens poses a major global healthcare challenge, with Klebsiella pneumoniae being a prominent threat. We conducted a comprehensive study on K. pneumoniae's antibiotic resistance mechanisms, focusing on outer membrane vesicles (OMVs) and polymyxin, a last-resort antibiotic. Our research demonstrates that OMVs protect bacteria from polymyxins. OMVs derived from Polymyxin B (PB)-stressed K. pneumoniae exhibited heightened protective efficacy due to increased vesiculation, compared to OMVs from unstressed Klebsiella. OMVs also shield bacteria from different bacterial families. This was validated ex vivo and in vivo using precision cut lung slices (PCLS) and Galleria mellonella. In all models, OMVs protected K. pneumoniae from PB and reduced the associated stress response on protein level. We observed significant changes in the lipid composition of OMVs upon PB treatment, affecting their binding capacity to PB. The altered binding capacity of single OMVs from PB stressed K. pneumoniae could be linked to a reduction in the lipid A amount of their released vesicles. Although the amount of lipid A per vesicle is reduced, the overall increase in the number of vesicles results in an increased protection because the sum of lipid A and therefore PB binding sites have increased. This unravels the mechanism of the altered PB protective efficacy of OMVs from PB stressed K. pneumoniae compared to control OMVs. The lipid A-dependent protective effect against PB was confirmed in vitro using artificial vesicles. Moreover, artificial vesicles successfully protected Klebsiella from PB ex vivo and in vivo. The findings indicate that OMVs act as protective shields for bacteria by binding to polymyxins, effectively serving as decoys and preventing antibiotic interaction with the cell surface. Our findings provide valuable insights into the mechanisms underlying antibiotic cross-protection and offer potential avenues for the development of novel therapeutic interventions to address the escalating threat of multidrug-resistant bacterial infections.

Subtyping non-small cell lung cancer by histology-guided spatial metabolomics.

PURPOSE: Most cancer-related deaths worldwide are associated with lung cancer. Subtyping of non-small cell lung cancer (NSCLC) into adenocarcinoma (AC) and squamous cell carcinoma (SqCC) is of importance, as therapy regimes differ. However, conventional staining and immunohistochemistry have their limitations. Therefore, a spatial metabolomics approach was aimed to detect differences between subtypes and to discriminate tumor and stroma regions in tissues. METHODS: Fresh-frozen NSCLC tissues (n = 35) were analyzed by matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) of small molecules (< m/z 1000). Measured samples were subsequently stained and histopathologically examined. A differentiation of subtypes and a discrimination of tumor and stroma regions was performed by receiver operating characteristic analysis and machine learning algorithms. RESULTS: Histology-guided spatial metabolomics revealed differences between AC and SqCC and between NSCLC tumor and tumor microenvironment. A diagnostic ability of 0.95 was achieved for the discrimination of AC and SqCC. Metabolomic contrast to the tumor microenvironment was revealed with an area under the curve of 0.96 due to differences in phospholipid profile. Furthermore, the detection of NSCLC with rarely arising mutations of the isocitrate dehydrogenase (IDH) gene was demonstrated through 45 times enhanced oncometabolite levels. CONCLUSION: MALDI-MSI of small molecules can contribute to NSCLC subtyping. Measurements can be performed intraoperatively on a single tissue section to support currently available approaches. Moreover, the technique can be beneficial in screening of IDH-mutants for the characterization of these seldom cases promoting the development of treatment strategies.