In vitro-generated Tc17 cells present a memory phenotype and serve as a reservoir of Tc1 cells in vivo

Indexación: Scopus.Memory CD8+ T cells are ideal candidates for cancer immunotherapy because they can mediate long-term protection against tumors. However, the therapeutic potential of different in vitro-generated CD8+ T cell effector subsets to persist and become memory cells has not been fully characterized. Type 1 CD8+ T (Tc1) cells produce interferon-γ and are endowed with high cytotoxic capacity, whereas IL-17-producing CD8+ T (Tc17) cells are less cytotoxic but display enhanced self-renewal capacity. We sought to evaluate the functional properties of in vitro-generated Tc17 cells and elucidate their potential to become long lasting memory cells. Our results show that in vitro-generated Tc17 cells display a greater in vivo persistence and expansion in response to secondary antigen stimulation compared to Tc1 cells. When transferred into recipient mice, Tc17 cells persist in secondary lymphoid organs, present a recirculation behavior consistent with central memory T cells, and can shift to a Tc1 phenotype. Accordingly, Tc17 cells are endowed with a higher mitochondrial spare respiratory capacity than Tc1 cells and express higher levels of memory-related molecules than Tc1 cells. Together, these results demonstrate that in vitro-generated Tc17 cells acquire a central memory program and provide a lasting reservoir of Tc1 cells in vivo, thus supporting the use of Tc17 lymphocytes in the design of novel and more effective therapies.https://www.frontiersin.org/articles/10.3389/fimmu.2018.00209/ful

Tissue-resident memory CD8⁺ T cells amplify anti-tumor immunity by triggering antigen spreading through dendritic cells

Tissue-resident memory CD8⁺ T (Trm) cells mediate potent local innate and adaptive immune responses and play a central role against solid tumors. However, whether Trm cells cross-talk with dendritic cells (DCs) to support anti-tumor immunity remains unclear. Here we show that antigen-specific activation of skin Trm cells leads to maturation and migration to draining lymph nodes of cross-presenting dermal DCs. Tumor rejection mediated by Trm cells triggers the spread of cytotoxic CD8⁺ T cell responses against tumor-derived neo- and self-antigens via dermal DCs. These responses suppress the growth of intradermal tumors and disseminated melanoma lacking the Trm cell-targeted epitope. Moreover, analysis of RNA sequencing data from human melanoma tumors reveals that enrichment of a Trm cell gene signature associates with DC activation and improved survival. This work unveils the ability of Trm cells to amplify the breath of cytotoxic CD8⁺ T cell responses through DCs, thereby strengthening anti-tumor immunity

Exact distribution of a pattern in a set of random sequences generated by a Markov source: applications to biological data

<p>Abstract</p> <p>Background</p> <p>In bioinformatics it is common to search for a pattern of interest in a potentially large set of rather short sequences (upstream gene regions, proteins, exons, etc.). Although many methodological approaches allow practitioners to compute the distribution of a pattern count in a random sequence generated by a Markov source, no specific developments have taken into account the counting of occurrences in a set of independent sequences. We aim to address this problem by deriving efficient approaches and algorithms to perform these computations both for low and high complexity patterns in the framework of homogeneous or heterogeneous Markov models.</p> <p>Results</p> <p>The latest advances in the field allowed us to use a technique of optimal Markov chain embedding based on deterministic finite automata to introduce three innovative algorithms. Algorithm 1 is the only one able to deal with heterogeneous models. It also permits to avoid any product of convolution of the pattern distribution in individual sequences. When working with homogeneous models, Algorithm 2 yields a dramatic reduction in the complexity by taking advantage of previous computations to obtain moment generating functions efficiently. In the particular case of low or moderate complexity patterns, Algorithm 3 exploits power computation and binary decomposition to further reduce the time complexity to a logarithmic scale. All these algorithms and their relative interest in comparison with existing ones were then tested and discussed on a toy-example and three biological data sets: structural patterns in protein loop structures, PROSITE signatures in a bacterial proteome, and transcription factors in upstream gene regions. On these data sets, we also compared our exact approaches to the tempting approximation that consists in concatenating the sequences in the data set into a single sequence.</p> <p>Conclusions</p> <p>Our algorithms prove to be effective and able to handle real data sets with multiple sequences, as well as biological patterns of interest, even when the latter display a high complexity (PROSITE signatures for example). In addition, these exact algorithms allow us to avoid the edge effect observed under the single sequence approximation, which leads to erroneous results, especially when the marginal distribution of the model displays a slow convergence toward the stationary distribution. We end up with a discussion on our method and on its potential improvements.</p

A communal catalogue reveals Earth's multiscale microbial diversity

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.Peer reviewe

A communal catalogue reveals Earth’s multiscale microbial diversity

Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity

The function and dysfunction of memory CD8+ T cells in tumor immunity

The generation and maintenance of CD8+ T cell memory is crucial to long‐term host survival, yet the basic tenets of CD8+ T cell immunity are still being established. Recent work has led to the discovery of tissue‐resident memory cells and refined our understanding of the transcriptional and epigenetic basis of CD8+ T cell differentiation and dysregulation. In parallel, the unprecedented clinical success of immunotherapy has galvanized an intense, global research effort to decipher and de‐repress the anti‐tumor response. However, the progress of immunotherapy is at a critical juncture, since the efficacy of immuno‐oncology agents remains confined to a fraction of patients and often fails to provide durable benefit. Unlocking the potential of immunotherapy requires the design of strategies that both induce a potent effector response and reliably forge stable, functional memory T cell pools capable of protecting from recurrence or relapse. It is therefore essential that basic and emerging concepts of memory T cell biology are rapidly and faithfully transposed to advance therapeutic development in cancer immunotherapy. This review highlights seminal and recent reports in CD8+ T cell memory and tumor immunology, and evaluates recent data from solid cancer specimens in the context of the key paradigms from preclinical models. We elucidate the potential significance of circulating effector cells poised downstream of neoantigen recognition and upstream of T cell dysfunction and propose that cells in this immunological ‘sweet spot’ may be key anti‐tumor effectors