Biology subjects

Ferreira, L. M.

Publications and source records attributed to Ferreira, L. M..

3 recordsLinked to original sources

bioRxiv2025

Disease tolerant mice shelter a pathogenic intestinal microbiota able to trigger lethal disease in low tolerant hosts

Disease tolerance is a defensive strategy that limits tissue damage during infection. Macrophage migration inhibitory factor (MIF)-deficient mice (Mif-/-) are protected in different models of infection and intestinal inflammation due to unclear disease tolerance mechanisms, whereas low disease-tolerant Il10-/-mice develop microbiota-dependent spontaneous gut inflammation. Here, we examined whether IL-10 is required for the phenotype seen in Mif-/-mice and, conversely, the contribution of MIF during IL-10 deficiency. While breeding for double-deficient Mif-/-Il10-/- mice, we unexpectedly observed that Il10-/- individuals died within days after co-housing with Mif-/- mice. We found that healthy Mif-/-hosts endure a highly diverse, unique and dysbiotic-like microbiota composition, including antibiotic-resistant Enterobacteriaceae species, which were sufficient to cause acute and lethal Th1-driven colitis in Il10-/- recipients. The disease was characterized by increased frequencies of IFN{gamma}+ cells and neutrophils within colonic lamina propria. Mif-/-Il10-/-mice died prematurely, and survivors developed communicable disease, - indicating that lack of IL-10 is a dominant trait. These findings suggest that tolerant individuals harbor a gut microbiota enriched in pathogens/pathobionts, which can trigger disease in susceptible hosts.

immunology↗

bioRxiv2022

Continuous sensing of IFNα by hepatic endothelial cells shapes a vascular antimetastatic barrier

Hepatic metastases are a poor prognostic factor of colorectal carcinoma (CRC) and new strategies to reduce the risk of liver CRC colonization are highly needed. Herein, we used mouse models of hepatic metastatization to demonstrate that the continuous infusion of therapeutic doses of interferon-alpha (IFN) controls CRC invasion by acting on hepatic endothelial cells (HECs). Mechanistically, IFN promoted the development of a vascular antimetastatic niche characterized by liver sinusoidal endothelial cells (LSECs) defenestration extracellular matrix and glycocalyx deposition, thus strengthening the liver vascular barrier impairing CRC trans-sinusoidal migration, without requiring a direct action on tumor cells, hepatic stellate cells, hepatocytes, or liver dendritic cells (DCs), Kupffer cells (KCs) and liver capsular macrophages (LCMs). Moreover, IFN endowed LSECs with efficient cross-priming potential that, along with the early intravascular tumor burden reduction, supported the generation of antitumor CD8+ T cells and ultimately led to the establishment of a protective long-term memory T cell response. These findings provide a rationale for the use of continuous IFN therapy in perioperative settings to reduce CRC metastatic spreading to the liver.

cancer biology↗

bioRxiv2018

The identification of DNA binding regions of the σ54 factor using artificial neural network

Transcription of many bacterial genes is regulated by alternative RNA polymerase sigma factors as the sigma 54 ({sigma}54). A single essential {sigma} promotes transcription of thousands of genes and many alternative {sigma} factors promote transcription of multiple specialized genes required for coping with stress or development. Bacterial genomes have two families of sigma factors, sigma 70 ({sigma}70) and sigma 54 ({sigma}54). {sigma}54 uses a more complex mechanism with specialized enhancers-binding proteins and DNA melting and is well known for its role in regulation of nitrogen metabolism in proteobacteria. The identification of these regulatory elements is the main step to understand the metabolic networks. In this study, we propose a supervised pattern recognition model with neural network to identify Transcription Factor Binding Sites (TFBSs) for {sigma}54. This approach is capable of detecting {sigma}54 TFBSs with sensitivity higher than 98% in recent published data. False positives are reduced with the addition of ANN and feature extraction, which increase the specificity of the program. We also propose a free, fast and friendly tool for {sigma}54 recognition and a {sigma}54 related genes database, available for consult. S54Finder can analyze from short DNA sequences to complete genomes and is available online. The software was used to determine {sigma}54 TFBSs on the complete bacterial genomes database from NCBI and the result is available for comparison. S54Finder does the identification of {sigma}54 regulated genes for a large set of genomes allowing evolutionary and conservation studies of the regulation system between the organisms.

bioinformatics↗