RESUMO
Depression is a prevalent psychological condition with limited treatment options. While its etiology is multifactorial, both chronic stress and changes in microbiome composition are associated with disease pathology. Stress is known to induce microbiome dysbiosis, defined here as a change in microbial composition associated with a pathological condition. This state of dysbiosis is known to feedback on depressive symptoms. While studies have demonstrated that targeted restoration of the microbiome can alleviate depressive-like symptoms in mice, translating these findings to human patients has proven challenging due to the complexity of the human microbiome. As such, there is an urgent need to identify factors upstream of microbial dysbiosis. Here we investigate the role of mucin 13 as an upstream mediator of microbiome composition changes in the context of stress. Using a model of chronic stress, we show that the glycocalyx protein, mucin 13, is selectively reduced after psychological stress exposure. We further demonstrate that the reduction of Muc13 is mediated by the Hnf4 transcription factor family. Finally, we determine that deleting Muc13 is sufficient to drive microbiome shifts and despair behaviors. These findings shed light on the mechanisms behind stress-induced microbial changes and reveal a novel regulator of mucin 13 expression.
Assuntos
Depressão , Disbiose , Microbioma Gastrointestinal , Estresse Psicológico , Animais , Masculino , Camundongos , Comportamento Animal/fisiologia , Depressão/metabolismo , Depressão/microbiologia , Disbiose/metabolismo , Disbiose/microbiologia , Microbioma Gastrointestinal/fisiologia , Fator 4 Nuclear de Hepatócito/metabolismo , Camundongos Endogâmicos C57BL , Camundongos Knockout , Mucinas/metabolismo , Estresse Psicológico/metabolismo , Estresse Psicológico/microbiologiaRESUMO
Mucin-domain glycoproteins are densely O-glycosylated and play critical roles in a host of biological functions. In particular, the T cell immunoglobulin and mucin-domain containing family of proteins (TIM-1, -3, -4) decorate immune cells and act as key regulators in cellular immunity. However, their dense O-glycosylation remains enigmatic, primarily due to the challenges associated with studying mucin domains. Here, we demonstrate that the mucinase SmE has a unique ability to cleave at residues bearing very complex glycans. SmE enables improved mass spectrometric analysis of several mucins, including the entire TIM family. With this information in-hand, we perform molecular dynamics (MD) simulations of TIM-3 and -4 to understand how glycosylation affects structural features of these proteins. Finally, we use these models to investigate the functional relevance of glycosylation for TIM-3 function and ligand binding. Overall, we present a powerful workflow to better understand the detailed molecular structures and functions of the mucinome.
Assuntos
Receptor Celular 2 do Vírus da Hepatite A , Mucinas , Mucinas/metabolismo , Polissacarídeo-Liases , Polissacarídeos/químicaRESUMO
Mucin-domain glycoproteins are densely O-glycosylated and play critical roles in a host of biological functions. In particular, the T cell immunoglobulin and mucin-domain containing family of proteins (TIM-1, -3, -4) decorate immune cells and act as key checkpoint inhibitors in cancer. However, their dense O-glycosylation remains enigmatic both in terms of glycoproteomic landscape and structural dynamics, primarily due to the challenges associated with studying mucin domains. Here, we present a mucinase (SmE) and demonstrate its ability to selectively cleave along the mucin glycoprotein backbone, similar to others of its kind. Unlike other mucinases, though, SmE harbors the unique ability to cleave at residues bearing extremely complex glycans which enabled improved mass spectrometric analysis of several mucins, including the entire TIM family. With this information in-hand, we performed molecular dynamics (MD) simulations of TIM-3 and -4 to demonstrate how glycosylation affects structural features of these proteins. Overall, we present a powerful workflow to better understand the detailed molecular structures of the mucinome.