Metformin reduces airway glucose permeability and hyperglycaemia-induced Staphylococcus aureus load independently of effects on blood glucose

Background Diabetes is a risk factor for respiratory infection, and hyperglycaemia is associated with increased glucose in airway surface liquid and risk of Staphylococcus aureus infection. Objectives To investigate whether elevation of basolateral/blood glucose concentration promotes airway Staphylococcus aureus growth and whether pretreatment with the antidiabetic drug metformin affects this relationship. Methods Human airway epithelial cells grown at air–liquid interface (±18 h pre-treatment, 30 μM–1 mM metformin) were inoculated with 5×105 colony-forming units (CFU)/cm2 S aureus 8325-4 or JE2 or Pseudomonas aeruginosa PA01 on the apical surface and incubated for 7 h. Wild-type C57BL/6 or db/db (leptin receptor-deficient) mice, 6–10 weeks old, were treated with intraperitoneal phosphate-buffered saline or 40 mg/kg metformin for 2 days before intranasal inoculation with 1×107 CFU S aureus. Mice were culled 24 h after infection and bronchoalveolar lavage fluid collected. Results Apical S aureus growth increased with basolateral glucose concentration in an in vitro airway epithelia–bacteria co-culture model. S aureus reduced transepithelial electrical resistance (RT) and increased paracellular glucose flux. Metformin inhibited the glucose-induced growth of S aureus, increased RT and decreased glucose flux. Diabetic (db/db) mice infected with S aureus exhibited a higher bacterial load in their airways than control mice after 2 days and metformin treatment reversed this effect. Metformin did not decrease blood glucose but reduced paracellular flux across ex vivo murine tracheas. Conclusions Hyperglycaemia promotes respiratory S aureus infection, and metformin modifies glucose flux across the airway epithelium to limit hyperglycaemia-induced bacterial growth. Metformin might, therefore, be of additional benefit in the prevention and treatment of respiratory infection

Establishment and Culture of Patient-Derived Breast Organoids

Breast cancer is a complex disease that has been classified into several different histological and molecular subtypes. Patient-derived breast tumor organoids developed in our laboratory consist of a mix of multiple tumor-derived cell populations, and thus represent a better approximation of tumor cell diversity and milieu than the established 2D cancer cell lines. Organoids serve as an ideal in vitro model, allowing for cell-extracellular matrix interactions, known to play an important role in cell-cell interactions and cancer progression. Patient-derived organoids also have advantages over mouse models as they are of human origin. Furthermore, they have been shown to recapitulate the genomic, transcriptomic as well as metabolic heterogeneity of patient tumors; thus, they are capable of representing tumor complexity as well as patient diversity. As a result, they are poised to provide more accurate insights into target discovery and validation and drug sensitivity assays. In this protocol, we provide a detailed demonstration of how patient-derived breast organoids are established from resected breast tumors (cancer organoids) or reductive mammoplasty-derived breast tissue (normal organoids). This is followed by a comprehensive account of 3D organoid culture, expansion, passaging, freezing, as well as thawing of patient-derived breast organoid cultures

Patient-derived triple-negative breast cancer organoids provide robust model systems that recapitulate tumor-intrinsic characteristics

Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer with poor patient outcomes, highlighting the unmet clinical need for targeted therapies and better model systems. Here, we developed and comprehensively characterized a diverse biobank of normal and breast cancer patient-derived organoids (PDO) with a focus on TNBC. PDOs recapitulated patient tumor-intrinsic properties, and a subset of PDOs were propagated for long-term culture (LT-TNBCs). Single cell profiling of PDOs identified cell types and gene candidates affiliated with different aspects of cancer progression. The LT-TNBC organoids exhibited signatures of aggressive MYC-driven, basal-like breast cancers and largely comprised luminal progenitor (LP)-like cells. The TNBC LP-like cells were distinct from normal LPs and exhibited hyperactivation of NOTCH and MYC signaling. Overall, this study validates TNBC PDOs as robust models for understanding breast cancer biology and progression, paving the way for personalized medicine and tailored treatment options

The surfaceome of multiple myeloma cells suggests potential immunotherapeutic strategies and protein markers of drug resistance.

The myeloma surface proteome (surfaceome) determines tumor interaction with the microenvironment and serves as an emerging arena for therapeutic development. Here, we use glycoprotein capture proteomics to define the myeloma surfaceome at baseline, in drug resistance, and in response to acute drug treatment. We provide a scoring system for surface antigens and identify CCR10 as a promising target in this disease expressed widely on malignant plasma cells. We engineer proof-of-principle chimeric antigen receptor (CAR) T-cells targeting CCR10 using its natural ligand CCL27. In myeloma models we identify proteins that could serve as markers of resistance to bortezomib and lenalidomide, including CD53, CD10, EVI2B, and CD33. We find that acute lenalidomide treatment increases activity of MUC1-targeting CAR-T cells through antigen upregulation. Finally, we develop a miniaturized surface proteomic protocol for profiling primary plasma cell samples with low inputs. These approaches and datasets may contribute to the biological, therapeutic, and diagnostic understanding of myeloma

Role for Mechanotransduction in Macrophage and Dendritic Cell Immunobiology

Item does not contain fulltextTissue homeostasis is not only controlled by biochemical signals but also through mechanical forces that act on cells. Yet, while it has long been known that biochemical signals have profound effects on cell biology, the importance of mechanical forces has only been recognized much more recently. The types of mechanical stress that cells experience include stretch, compression, and shear stress, which are mainly induced by the extracellular matrix, cell-cell contacts, and fluid flow. Importantly, macroscale tissue deformation through stretch or compression also affects cellular function.Immune cells such as macrophages and dendritic cells are present in almost all peripheral tissues, and monocytes populate the vasculature throughout the body. These cells are unique in the sense that they are subject to a large variety of different mechanical environments, and it is therefore not surprising that key immune effector functions are altered by mechanical stimuli. In this chapter, we describe the different types of mechanical signals that cells encounter within the body and review the current knowledge on the role of mechanical signals in regulating macrophage, monocyte, and dendritic cell function