Mouse dendritic cells in the steady state: Hypoxia, autophagy, and stem cell factor

Dendritic cells (DCs) are innate immune cells with a central role in immunity and tolerance. Under steady-state, DCs are scattered in tissues as resting cells. Upon infection or injury, DCs get activated and acquire the full capacity to prime antigen-specific CD4(+) and CD8(+) T cells, thus bridging innate and adaptive immunity. By secreting different sets of cytokines and chemokines, DCs orchestrate diverse types of immune responses, from a classical proinflammatory to an alternative pro-repair one. DCs are highly heterogeneous, and physiological differences in tissue microenvironments greatly contribute to variations in DC phenotype. Oxygen tension is normally low in some lymphoid areas, including bone marrow (BM) hematopoietic niches; nevertheless, the possible impact of tissue hypoxia on DC physiology has been poorly investigated. We assessed whether DCs are hypoxic in BM and spleen, by staining for hypoxia-inducible-factor-1 alpha subunit (HIF-1 alpha), the master regulator of hypoxia-induced response, and pimonidazole (PIM), a hypoxic marker, and by flow cytometric analysis. Indeed, we observed that mouse DCs have a hypoxic phenotype in spleen and BM, and showed some remarkable differences between DC subsets. Notably, DCs expressing membrane c-kit, the receptor for stem cell factor (SCF), had a higher PIM median fluorescence intensity (MFI) than c-kit(-) DCs, both in the spleen and in the BM. To determine whether SCF (a.k.a. kit ligand) has a role in DC hypoxia, we evaluated molecular pathways activated by SCF in c-kit(+) BM-derived DCs cultured in hypoxic conditions. Gene expression microarrays and gene set enrichment analysis supported the hypothesis that SCF had an impact on hypoxia response and inhibited autophagy-related gene sets. Our results suggest that hypoxic response and autophagy, and their modulation by SCF, can play a role in DC homeostasis at the steady state, in agreement with our previous findings on SCF's role in DC survival

Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)

The third edition of Flow Cytometry Guidelines provides the key aspects to consider when performing flow cytometry experiments and includes comprehensive sections describing phenotypes and functional assays of all major human and murine immune cell subsets. Notably, the Guidelines contain helpful tables highlighting phenotypes and key differences between human and murine cells. Another useful feature of this edition is the flow cytometry analysis of clinical samples with examples of flow cytometry applications in the context of autoimmune diseases, cancers as well as acute and chronic infectious diseases. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid. All sections are written and peer‐reviewed by leading flow cytometry experts and immunologists, making this edition an essential and state‐of‐the‐art handbook for basic and clinical researchers.DFG, 389687267, Kompartimentalisierung, Aufrechterhaltung und Reaktivierung humaner Gedächtnis-T-Lymphozyten aus Knochenmark und peripherem BlutDFG, 80750187, SFB 841: Leberentzündungen: Infektion, Immunregulation und KonsequenzenEC/H2020/800924/EU/International Cancer Research Fellowships - 2/iCARE-2DFG, 252623821, Die Rolle von follikulären T-Helferzellen in T-Helferzell-Differenzierung, Funktion und PlastizitätDFG, 390873048, EXC 2151: ImmunoSensation2 - the immune sensory syste

Different cell cycle stages characterize early and late phases of antigen-specific CD8 T cell response after vaccination

After infection, or vaccination, naïve CD8 T cells are activated by antigen presenting cells (APCs) in secondary lymphoid organs. Activated antigen-specific CD8 T cells undergo a strong proliferation (so-called clonal expansion) and differentiate, generating a progeny composed by short-lived effectors and long-lived memory cells. Once antigen is eliminated, most cells die in the contraction phase and only few cells persist as memory CD8 T cells. These cells are able to respond to a second antigenic challenge in a more effective and faster way than in the primary response. Several phases of T cell response are regulated by responding T cell entry and exit from cell cycle. Indeed, naïve T cells are quiescent cells in G0 and the acute phase of response is characterized by their fast entry in cell cycle (from G0 to G1) and progression into subsequent phases till cell division (S-G2/M). Several cell cycles characterize the clonal expansion of activated T cells. During the early phases of immune response, changes in cell cycle regulation of activated T cells could deeply affect the response, for example reduced clonal expansion could lead to decreased number of effector and memory cells. Moreover, it has been proposed that memory T cells are maintained over time by a fine balance between different cell cycle states, including a fine regulation of quiescence. According to this hypothesis quiescence represents an actively regulated process like other cell cycle phases and not a passive mechanism of cell persistence over time. Any perturbation of this balance could affect the ability to mount an efficient secondary response with consequent loss of protection. In this scenario, our hypothesis is that a fine balance between different cell cycle phases regulates T cell response both in the acute and in the memory phase of response. Thus, in this project we aimed to investigate the kinetic of cell cycle phases of antigen-specific CD8 T cells responding to heterologous prime/boost vaccination in a mouse model. By using a combination of DNA and Ki67 staining together with a novel strategy for analysis of flow cytometry data, we were able to discriminate antigen-specific CD8 T cells in G0, in G1 and in S-G2/M phases of cell cycle. At early times after vaccination we found a previously missed population of cycling cells characterized by high Forward and Side Scatter (FSC-SSC) parameters. Cells with these characteristics are usually excluded from the analysis of normal lymphocytes ex vivo. By including them, we discovered an “extra” population of cycling antigen-specific CD8 T cell in spleen, lymph nodes and also in the blood which is not expected to be a site for antigen-responding CD8 T cells proliferation. We found that antigen-specific CD8 T cells accumulated in lymph nodes and the bone marrow during memory phase. These cells switched to a quiescent phenotype and a few of them acquired a central memory phenotype at late times after priming. Interestingly, boosting when quiescent state was established resulted in a much higher frequency of antigen-specific CD8 T cells that persisted in different lymphoid organs, and accumulated in high numbers in the bone marrow. Our results have implications for prior and future immunological studies in animal models and in humans. Indeed, our results will be instrumental to track CD8 T cell response in humans after infections or vaccination, as well as in cancers, and will improve the design of new therapeutic approaches to cancer and immune-mediated diseases

The emerging interplay between recirculating and tissue-resident memory T cells in cancer immunity: lessons learned from PD-1/PD-L1 blockade therapy and remaining gaps

Remarkable progress has been made in the field of anti-tumor immunity, nevertheless many questions are still open. Thus, even though memory T cells have been implicated in long-term anti-tumor protection, particularly in prevention of cancer recurrence, the bases of their variable effectiveness in tumor patients are poorly understood. Two types of memory T cells have been described according to their traffic pathways: recirculating and tissue-resident memory T cells. Recirculating tumor-specific memory T cells are found in the cell infiltrate of solid tumors, in the lymph and in the peripheral blood, and they constantly migrate in and out of lymph nodes, spleen, and bone marrow. Tissue-resident tumor-specific memory T cells (TRM) permanently reside in the tumor, providing local protection. Anti-PD-1/PD-L1, a type of immune checkpoint blockade (ICB) therapy, can considerably re-invigorate T cell response and lead to successful tumor control, even in patients at advanced stages. Indeed, ICB has led to unprecedented successes against many types of cancers, starting a ground-breaking revolution in tumor therapy. Unfortunately, not all patients are responsive to such treatment, thus further improvements are urgently needed. The mechanisms underlying resistance to ICB are still largely unknown. A better knowledge of the dynamics of the immune response driven by the two types of memory T cells before and after anti-PD-1/PD-L1 would provide important insights on the variability of the outcomes. This would be instrumental to design new treatments to overcome resistance. Here we provide an overview of T cell contribution to immunity against solid tumors, focusing on memory T cells. We summarize recent evidence on the involvement of recirculating memory T cells and TRM in anti-PD-1/PD-L1-elicited antitumor immunity, outline the open questions in the field, and propose that a synergic action of the two types of memory T cells is required to achieve a full response. We argue that a T-centric vision focused on the specific roles and the possible interplay between TRM and recirculating memory T cells will lead to a better understanding of anti-PD-1/PD-L1 mechanism of action, and provide new tools for improving ICB therapeutic strategy

Antigen-specific CD8 T cells in cell cycle circulate in the blood after vaccination

Although clonal expansion is a hallmark of adaptive immunity, the location(s) where antigen-responding T cells enter cell cycle and complete it have been poorly explored. This lack of knowledge stems partially from the limited experimental approaches available. By using Ki67 plus DNA staining and a novel strategy for flow cytometry analysis, we distinguished antigen-specific CD8 T cells in G0 , in G1 and in S-G2 /M phases of cell cycle after intramuscular vaccination of BALB/c mice with antigen-expressing viral vectors. Antigen-specific cells in S-G2 /M were present at early times after vaccination in lymph nodes (LNs), spleen and, surprisingly, also in the blood, which is an unexpected site for cycling of normal non-leukaemic cells. Most proliferating cells had high scatter profile and were undetected by current criteria of analysis, which under-estimated up to 6 times antigen-specific cell frequency in LNs. Our discovery of cycling antigen-specific CD8 T cells in the blood opens promising translational perspectives

Immune-Mediated Drug-Induced Liver Injury: Immunogenetics and Experimental Models

Drug-induced liver injury (DILI) is a challenging clinical event in medicine, particularly because of its ability to present with a variety of phenotypes including that of autoimmune hepatitis or other immune mediated liver injuries. Limited diagnostic and therapeutic tools are available, mostly because its pathogenesis has remained poorly understood for decades. The recent scientific and technological advancements in genomics and immunology are paving the way for a better understanding of the molecular aspects of DILI. This review provides an updated overview of the genetic predisposition and immunological mechanisms behind the pathogenesis of DILI and presents the state-of-the-art experimental models to study DILI at the pre-clinical level.We acknowledge that this research was partially supported by the Italian Ministry of University and Research (MIUR)—Department of Excellence project PREMIA (PREcision MedIcine Approach: bringing biomarker research to clinic). Research in FD’s lab was funded by MIUR project: 2017K55HLC_006.Ye

OMIP-079:Cell cycle of CD4⁺ and CD8⁺ naïve/memory T cell subsets, and of Treg cells from mouse spleen

A multicolor flow cytometry panel was designed and optimized to define the following nine mouse T cell subsets: Treg (CD3(+) CD4(+) CD8(−) FoxP3(+)), CD4(+) T naïve (CD3(+) CD4(+) CD8(−)FoxP3(−) CD44(int/low) CD62L(+)), CD4(+) T central memory (CD3(+) CD4(+) CD8(−) FoxP3(−) CD44(high) CD62L(+)), CD4(+) T effector memory (CD3(+) CD4(+) CD8(−) FoxP3(−) CD44(high) CD62L(−)), CD4(+) T EMRA (CD3(+) CD4(+) CD8(−) FoxP3(−) CD44(int/low) CD62L(−)), CD8(+) T naïve (CD3(+) CD8(+) CD4(−) CD44(int/low) CD62L(+)), CD8(+) T central memory (CD3(+) CD8(+) CD4(−) CD44(high) CD62L(+)), CD8(+) T effector memory (CD3(+) CD8(+) CD4(−) CD44(high) CD62L(−)), and CD8(+) T EMRA (CD3(+) CD8(+) CD4(−) CD44(int/low) CD62L(−)). In each T cell subset, a dual staining for Ki‐67 expression and DNA content was employed to distinguish the following cell cycle phases: G(0) (Ki67(−), with 2n DNA), G(1) (Ki67(+), with 2n DNA), and S‐G(2)/M (Ki67(+), with 2n < DNA ≤ 4n). This panel was established for the analysis of mouse (C57BL/6J) spleen

Improved memory CD8 T cell response to delayed vaccine boost is associated with a distinct molecular signature.

Effective secondary response to antigen is a hallmark of immunological memory. However, the extent of memory CD8 T cell response to secondary boost varies at different times after a primary response. Considering the central role of memory CD8 T cells in long-lived protection against viral infections and tumors, a better understanding of the molecular mechanisms underlying the changing responsiveness of these cells to antigenic challenge would be beneficial. We examined here primed CD8 T cell response to boost in a BALB/c mouse model of intramuscular vaccination by priming with HIV-1 gag-encoding Chimpanzee adenovector, and boosting with HIV-1 gag-encoding Modified Vaccinia virus Ankara. We found that boost was more effective at day(d)100 than at d30 postprime, as evaluated at d45 post-boost by multi-lymphoid organ assessment of gag-specific CD8 T cell frequency, CD62L-expression (as a guide to memory status) and in vivo killing. RNA-sequencing of splenic gag-primed CD8 T cells at d100 revealed a quiescent, but highly responsive signature, that trended toward a central memory (CD62L+) phenotype. Interestingly, gag-specificCD8Tcell frequency selectively diminished in the blood at d100, relative to the spleen, lymph nodes and bone marrow. These results open the possibility to modify prime/ boost intervals to achieve an improved memory CD8 T cell secondary response

Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)

Cossarizza A, Chang H‐D, Radbruch A, et al. Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition). European Journal of Immunology. 2021;51(12):2708-3145.The third edition of Flow Cytometry Guidelines provides the key aspects to consider when performing flow cytometry experiments and includes comprehensive sections describing phenotypes and functional assays of all major human and murine immune cell subsets. Notably, the Guidelines contain helpful tables highlighting phenotypes and key differences between human and murine cells. Another useful feature of this edition is the flow cytometry analysis of clinical samples with examples of flow cytometry applications in the context of autoimmune diseases, cancers as well as acute and chronic infectious diseases. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid. All sections are written and peer-reviewed by leading flow cytometry experts and immunologists, making this edition an essential and state-of-the-art handbook for basic and clinical researchers

Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)

The third edition of Flow Cytometry Guidelines provides the key aspects to consider when performing flow cytometry experiments and includes comprehensive sections describing phenotypes and functional assays of all major human and murine immune cell subsets. Notably, the Guidelines contain helpful tables highlighting phenotypes and key differences between human and murine cells. Another useful feature of this edition is the flow cytometry analysis of clinical samples with examples of flow cytometry applications in the context of autoimmune diseases, cancers as well as acute and chronic infectious diseases. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid. All sections are written and peer-reviewed by leading flow cytometry experts and immunologists, making this edition an essential and state-of-the-art handbook for basic and clinical researchers.ISSN:0014-2980ISSN:1521-414