RESUMO
In response to pathogenic threats, naive T cells rapidly transition from a quiescent to an activated state, yet the underlying mechanisms are incompletely understood. Using a pulsed SILAC approach, we investigated the dynamics of mRNA translation kinetics and protein turnover in human naive and activated T cells. Our datasets uncovered that transcription factors maintaining T cell quiescence had constitutively high turnover, which facilitated their depletion following activation. Furthermore, naive T cells maintained a surprisingly large number of idling ribosomes as well as 242 repressed mRNA species and a reservoir of glycolytic enzymes. These components were rapidly engaged following stimulation, promoting an immediate translational and glycolytic switch to ramp up the T cell activation program. Our data elucidate new insights into how T cells maintain a prepared state to mount a rapid immune response, and provide a resource of protein turnover, absolute translation kinetics and protein synthesis rates in T cells ( https://www.immunomics.ch ).
Assuntos
Ativação Linfocitária/fisiologia , Biossíntese de Proteínas/imunologia , Linfócitos T/imunologia , Humanos , RNA Mensageiro/imunologia , RNA Mensageiro/metabolismo , Fatores de Transcrição/imunologia , Fatores de Transcrição/metabolismoRESUMO
Metabolic activity is intimately linked to T cell fate and function. Using high-resolution mass spectrometry, we generated dynamic metabolome and proteome profiles of human primary naive T cells following activation. We discovered critical changes in the arginine metabolism that led to a drop in intracellular L-arginine concentration. Elevating L-arginine levels induced global metabolic changes including a shift from glycolysis to oxidative phosphorylation in activated T cells and promoted the generation of central memory-like cells endowed with higher survival capacity and, in a mouse model, anti-tumor activity. Proteome-wide probing of structural alterations, validated by the analysis of knockout T cell clones, identified three transcriptional regulators (BAZ1B, PSIP1, and TSN) that sensed L-arginine levels and promoted T cell survival. Thus, intracellular L-arginine concentrations directly impact the metabolic fitness and survival capacity of T cells that are crucial for anti-tumor responses.
Assuntos
Arginina/metabolismo , Linfócitos T CD4-Positivos/imunologia , Imunomodulação , Ativação Linfocitária , Melanoma Experimental/imunologia , Neoplasias Cutâneas/imunologia , Proteínas Adaptadoras de Transdução de Sinal/metabolismo , Animais , Linfócitos T CD4-Positivos/metabolismo , Proteínas de Ligação a DNA/metabolismo , Técnicas de Inativação de Genes , Glicólise , Humanos , Memória Imunológica , Metaboloma , Camundongos , Camundongos Endogâmicos BALB C , Fosforilação Oxidativa , Proteoma , Fatores de Transcrição/metabolismo , Transcrição GênicaRESUMO
The immune system is unique in its dynamic interplay between numerous cell types. However, a system-wide view of how immune cells communicate to protect against disease has not yet been established. We applied high-resolution mass-spectrometry-based proteomics to characterize 28 primary human hematopoietic cell populations in steady and activated states at a depth of >10,000 proteins in total. Protein copy numbers revealed a specialization of immune cells for ligand and receptor expression, thereby connecting distinct immune functions. By integrating total and secreted proteomes, we discovered fundamental intercellular communication structures and previously unknown connections between cell types. Our publicly accessible (http://www.immprot.org/) proteomic resource provides a framework for the orchestration of cellular interplay and a reference for altered communication associated with pathology.
Assuntos
Células Sanguíneas/fisiologia , Imunidade Celular , Mapas de Interação de Proteínas , Proteoma , Proteômica , Animais , Secreções Corporais , Comunicação Celular , Simulação por Computador , Humanos , Espectrometria de Massas , Apoio SocialRESUMO
Cytokines are signaling molecules secreted and sensed by immune and other cell types, enabling dynamic intercellular communication. Although a vast amount of data on these interactions exists, this information is not compiled, integrated or easily searchable. Here we report immuneXpresso, a text-mining engine that structures and standardizes knowledge of immune intercellular communication. We applied immuneXpresso to PubMed to identify relationships between 340 cell types and 140 cytokines across thousands of diseases. The method is able to distinguish between incoming and outgoing interactions, and it includes the effect of the interaction and the cellular function involved. These factors are assigned a confidence score and linked to the disease. By leveraging the breadth of this network, we predicted and experimentally verified previously unappreciated cell-cytokine interactions. We also built a global immune-centric view of diseases and used it to predict cytokine-disease associations. This standardized knowledgebase (http://www.immunexpresso.org) opens up new directions for interpretation of immune data and model-driven systems immunology.
Assuntos
Biologia Computacional/métodos , Citocinas/imunologia , Mineração de Dados/métodos , Imunidade/genética , Citocinas/genética , Regulação da Expressão Gênica/imunologia , Humanos , PubMedRESUMO
Localization of memory CD8(+) T cells to lymphoid or peripheral tissues is believed to correlate with proliferative capacity or effector function. Here we demonstrate that the fractalkine-receptor/CX3CR1 distinguishes memory CD8(+) T cells with cytotoxic effector function from those with proliferative capacity, independent of tissue-homing properties. CX3CR1-based transcriptome and proteome-profiling defines a core signature of memory CD8(+) T cells with effector function. We find CD62L(hi)CX3CR1(+) memory T cells that reside within lymph nodes. This population shows distinct migration patterns and positioning in proximity to pathogen entry sites. Virus-specific CX3CR1(+) memory CD8(+) T cells are scarce during chronic infection in humans and mice but increase when infection is controlled spontaneously or by therapeutic intervention. This CX3CR1-based functional classification will help to resolve the principles of protective CD8(+) T-cell memory.