The Warburg effect in mycobacterial granulomas is dependent on the recruitment and activation of macrophages by interferon-γ

Granulomas are the hallmark of mycobacterial disease. Here, we demonstrate that both the cell recruitment and the increased glucose consumption in granulomatous infiltrates during Mycobacterium avium infection are highly dependent on interferon-y (IFN-y). Mycobacterium avium-infected mice lacking IFN-y signalling failed to developed significant inflammatory infiltrations and lacked the characteristic uptake of the glucose analogue fluorine-18-fluorodeoxyglucose (FDG). To assess the role of macrophages in glucose uptake we infected mice with a selective impairment of IFN-y signalling in the macrophage lineage (MIIG mice). Although only a partial reduction of the granulomatous areas was observed in infected MIIG mice, the insensitivity of macrophages to IFN-y reduced the accumulation of FDG. In vivo, ex vivo and in vitro assays showed that macrophage activated by IFN-y displayed increased rates of glucose uptake and in vitro studies showed also that they had increased lactate production and increased expression of key glycolytic enzymes. Overall, our results show that the activation of macrophages by IFN-y is responsible for the Warburg effect observed in organs infected with M. avium.

Lack of the transcription factor hypoxia-inducible factor (HIF)-1α in macrophages accelerates the necrosis of Mycobacterium avium-induced granulomas

Accepted Manuscript

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.

Polymicrobial interactions in infections: the case Pseudomonas aeruginosa and Candida albicans in ventilator-associated pneumonia

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Engenharia Clinica)

The relevance of bacterial interactions on oral health

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Engenharia Clínica)

Influence of oxygen conditions on bacterial interactions within biofilms related with cystic fibrosis

Dissertação de mestrado em Bioengineering