3 research outputs found
Candida albicans/Macrophage Biointerface on Human and Porcine Decellularized Adipose Matrices
Macrophages, cells effective in sensing, internalizing and killing Candida albicans, are intertwined
with the extracellular matrix (ECM) through different signals, which include the release of specific
cytokines. Due to the importance of these interactions, the employment of in vitro models mimicking
a fungal infection scenario is essential to evaluate the ECM effects on the macrophage response.
In this work, we have analyzed the effects of human and porcine decellularized adipose matrices
(DAMs), obtained by either enzymatic or organic solvent treatment, on the macrophage/Candida albicans
interface. The present study has allowed us to detect differences on the activation of macrophages
cultured on either human- or porcine-derived DAMs, evidencing changes in the macrophage actin
cytoskeleton, such as distinct F-actin-rich membrane structures to surround the pathogen. The
macrophage morphological changes observed on these four DAMs are key to understand the defense
capability of these cells against this fungal pathogen. This work has contributed to the knowledge of
the influence that the extracellular matrix and its components can exert on macrophage metabolism,
immunocompetence and capacity to respond to the microenvironment in a possible infection scenario.This work has been supported by the European Union’s Horizon 2020 Research and Innovation Programme (H2020-FETOPEN-2018-2020, NeuroStimSpinal Project, Grant AgreementNo. 829060). M.C. acknowledges the European Union0s Horizon 2020 Research and InnovationProgramme for her contract under the NeuroStimSpinal Project. LC is grateful to the Universidad Complutense de Madrid for a UCM fellowshi
Effects of Human and Porcine Adipose Extracellular Matrices Decellularized by Enzymatic or Chemical Methods on Macrophage Polarization and Immunocompetence
The decellularized extracellular matrix (ECM) obtained from human and porcine adipose tissue (AT) is currently used to prepare regenerative medicine bio-scaffolds. However, the influence of these natural biomaterials on host immune response is not yet deeply understood. Since macrophages play a key role in the inflammation/healing processes due to their high functional plasticity between M1 and M2 phenotypes, the evaluation of their response to decellularized ECM is mandatory. It is also necessary to analyze the immunocompetence of macrophages after contact with decellularized ECM materials to assess their functional role in a possible infection scenario. In this work, we studied the effect of four decellularized adipose matrices (DAMs) obtained from human and porcine AT by enzymatic or chemical methods on macrophage phenotypes and fungal phagocytosis. First, a thorough biochemical characterization of these biomaterials by quantification of remnant DNA, lipids, and proteins was performed, thus indicating the efficiency and reliability of both methods. The proteomic analysis evidenced that some proteins are differentially preserved depending on both the AT origin and the decellularization method employed. After exposure to the four DAMs, specific markers of M1 proinflammatory and M2 anti-inflammatory macrophages were analyzed. Porcine DAMs favor the M2 phenotype, independently of the decellularization method employed. Finally, a sensitive fungal phagocytosis assay allowed us to relate the macrophage phagocytosis capability with specific proteins differentially preserved in certain DAMs. The results obtained in this study highlight the close relationship between the ECM biochemical composition and the macrophage’s functional role.This work has been supported by the European Union’s Horizon 2020 Research and Innovation Programme (H2020-FETOPEN-2018-2020, NeuroStimSpinal Project, Grant Agreement No. 829060). M.C. acknowledges the European Union0s Horizon 2020 Research and Innovation Programme for her contract under the NeuroStimSpinal Project. LC is grateful to the Universidad Complutense de Madrid for an UCM fellowship