Dataset Information

Cell-to-cell transfer of M. tuberculosis antigens optimizes CD4 T cell priming.

ABSTRACT: During Mycobacterium tuberculosis and other respiratory infections, optimal T cell activation requires pathogen transport from the lung to a local draining lymph node (LN). However, the infected inflammatory monocyte-derived dendritic cells (DCs) that transport M. tuberculosis to the local lymph node are relatively inefficient at activating CD4 T cells, possibly due to bacterial inhibition of antigen presentation. We found that infected migratory DCs release M. tuberculosis antigens as soluble, unprocessed proteins for uptake and presentation by uninfected resident lymph node DCs. This transfer of bacterial proteins from migratory to local DCs results in optimal priming of antigen-specific CD4 T cells, which are essential in controlling tuberculosis. Additionally, this mechanism does not involve transfer of the whole bacterium and is distinct from apoptosis or exosome shedding. These findings reveal a mechanism that bypasses pathogen inhibition of antigen presentation by infected cells and generates CD4 T cell responses that control the infection.

SUBMITTER: Srivastava S

PROVIDER: S-EPMC4098643 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Cell-to-cell transfer of M. tuberculosis antigens optimizes CD4 T cell priming.

Srivastava Smita S Ernst Joel D JD

Cell host & microbe 20140601 6

During Mycobacterium tuberculosis and other respiratory infections, optimal T cell activation requires pathogen transport from the lung to a local draining lymph node (LN). However, the infected inflammatory monocyte-derived dendritic cells (DCs) that transport M. tuberculosis to the local lymph node are relatively inefficient at activating CD4 T cells, possibly due to bacterial inhibition of antigen presentation. We found that infected migratory DCs release M. tuberculosis antigens as soluble, ...[more]

PMID: 24922576

Similar Datasets

Project description:Lack of an effective vaccine results in 9 million new cases of tuberculosis (TB) every year and 1.8 million deaths worldwide. Although many infants are vaccinated at birth with BCG (an attenuated M. bovis), this does not prevent infection or development of TB after childhood. Immune responses necessary for prevention of infection or disease are still unknown, making development of effective vaccines against TB challenging. Several new vaccines are ready for human clinical trials, but these trials are difficult and expensive; especially challenging is determining the appropriate cellular response necessary for protection. The magnitude of an immune response is likely key to generating a successful vaccine. Characteristics such as numbers of central memory (CM) and effector memory (EM) T cells responsive to a diverse set of epitopes are also correlated with protection. Promising vaccines against TB contain mycobacterial subunit antigens (Ag) present during both active and latent infection. We hypothesize that protection against different key immunodominant antigens could require a vaccine that produces different levels of EM and CM for each Ag-specific memory population. We created a computational model to explore EM and CM values, and their ratio, within what we term Memory Design Space. Our model captures events involved in T cell priming within lymph nodes and tracks their circulation through blood to peripheral tissues. We used the model to test whether multiple Ag-specific memory cell populations could be generated with distinct locations within Memory Design Space at a specific time point post vaccination. Boosting can further shift memory populations to memory cell ratios unreachable by initial priming events. By strategically varying antigen load, properties of cellular interactions within the LN, and delivery parameters (e.g., number of boosts) of multi-subunit vaccines, we can generate multiple Ag-specific memory populations that cover a wide range of Memory Design Space. Given a set of desired characteristics for Ag-specific memory populations, we can use our model as a tool to predict vaccine formulations that will generate those populations.

Dataset Information

Cell-to-cell transfer of M. tuberculosis antigens optimizes CD4 T cell priming.

Publications

Cell-to-cell transfer of M. tuberculosis antigens optimizes CD4 T cell priming.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets