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

Characterization of murine lymphocyte activation and exhaustion markers by a 14-color flow cytometry panel

Previously designed flow cytometry panels have provided a framework to analyze T-cell activation; however, few provide an extensive view of lymphocyte populations, and none are optimized for murine models. This article describes a panel designed specifically to assess the expression of activation and exhaustion markers in expanding lymphocyte populations in tumor-bearing mice across two distinct genetic backgrounds: BALB/c and C57BL/6. This comprehensive panel enables the assessment of multiple functional states and immune checkpoint markers across cytotoxic CD8⁺ T cells, helper and regulatory CD4⁺ T cells and NK cells in murine whole blood, lymph nodes and tumor.

SigPrimedNet: A Signaling-Informed Neural Network for scRNA-seq Annotation of Known and Unknown Cell Types

Single-cell RNA sequencing is increasing our understanding of the behavior of complex tissues or organs, by providing unprecedented details on the complex cell type landscape at the level of individual cells. Cell type definition and functional annotation are key steps to understanding the molecular processes behind the underlying cellular communication machinery. However, the exponential growth of scRNA-seq data has made the task of manually annotating cells unfeasible, due not only to an unparalleled resolution of the technology but to an ever-increasing heterogeneity of the data. Many supervised and unsupervised methods have been proposed to automatically annotate cells. Supervised approaches for cell-type annotation outperform unsupervised methods except when new (unknown) cell types are present. Here, we introduce SigPrimedNet an artificial neural network approach that leverages (i) efficient training by means of a sparsity-inducing signaling circuits-informed layer, (ii) feature representation learning through supervised training, and (iii) unknown cell-type identification by fitting an anomaly detection method on the learned representation. We show that SigPrimedNet can efficiently annotate known cell types while keeping a low false-positive rate for unseen cells across a set of publicly available datasets. In addition, the learned representation acts as a proxy for signaling circuit activity measurements, which provide useful estimations of the cell functionalities.

COVID-19: Using high-throughput flow cytometry to dissect clinical heterogeneity

Here we consider how high-content flow cytometric methodology at appropriate scale and throughput rapidly provided meaningful biological data in our recent studies of COVID-19, which we discuss in the context of other similar investigations. In our work, high-throughput flow cytometry was instrumental to identify a consensus immune signature in COVID-19 patients, and to investigate the impact of SARS-CoV-2 exposure on patients with either solid or hematological cancers. We provide here some examples of our 'holistic' approach, in which flow cytometry data generated by lymphocyte and myelomonocyte panels were integrated with other analytical metrics, including SARS-CoV-2-specific serum antibody titers, plasma cytokine/chemokine levels, and in-depth clinical annotation. We report how selective differences between T cell subsets were revealed by a newly described flow cytometric TDS assay to distinguish actively cycling T cells in the peripheral blood. By such approaches, our and others' high-content flow cytometry studies collectively identified overt abnormalities and subtle but critical changes that discriminate the immuno-signature of COVID-19 patients from those of healthy donors and patients with non-COVID respiratory infections. Thereby, these studies offered several meaningful biomarkers of COVID-19 severity that have the potential to improve the management of patients and of hospital resources. In sum, flow cytometry provides an important means for rapidly obtaining data that can guide clinical decision-making without requiring highly expensive, sophisticated equipment, and/or "-omics" capabilities. We consider how this approach might be further developed.

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 post-prime, 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-specific CD8 T cell 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.

Osteoblasts Promote Prostate Cancer Cell Proliferation Through Androgen Receptor Independent Mechanisms

Patients with metastatic prostate cancer frequently develop bone metastases that elicit significant skeletal morbidity and increased mortality. The high tropism of prostate cancer cells for bone and their tendency to induce the osteoblastic-like phenotype are a result of a complex interplay between tumor cells and osteoblasts. Although the role of osteoblasts in supporting prostate cancer cell proliferation has been reported by previous studies, their precise contribution in tumor growth remains to be fully elucidated. Here, we tried to dissect the molecular signaling underlining the interactions between castration-resistant prostate cancer (CRPC) cells and osteoblasts using in vitro co-culture models. Transcriptomic analysis showed that osteoblast-conditioned media (OCM) induced the overexpression of genes related to cell cycle in the CRPC cell line C4-2B but, surprisingly, reduced androgen receptor (AR) transcript levels. In-depth analysis of AR expression in C4-2B cells after OCM treatment showed an AR reduction at the mRNA (p = 0.0047), protein (p = 0.0247), and functional level (p = 0.0029) and, concomitantly, an increase of C4-2B cells in S-G2-M cell cycle phases (p = 0.0185). An extensive proteomic analysis revealed in OCM the presence of some molecules that reduced AR activation, and among these, Matrix metalloproteinase-1 (MMP-1) was the only one able to block AR function (0.1 ng/ml p = 0.006; 1 ng/ml p = 0.002; 10 ng/ml p = 0.0001) and, at the same time, enhance CRPC proliferation (1 ng/ml p = 0.009; 10 ng/ml p = 0.033). Although the increase of C4-2B cell growth induced by MMP-1 did not reach the proliferation levels observed after OCM treatment, the addition of Vorapaxar, an MMP-1 receptor inhibitor (Protease-activated receptor-1, PAR-1), significantly reduced C4-2B cell cycle (0.1 μM p = 0.014; 1 μM p = 0.0087). Overall, our results provide a novel AR-independent mechanism of CRPC proliferation and suggest that MMP-1/PAR-1 could be one of the potential pathways involved in this process.

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.

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: G₀ (Ki67⁻, with 2n DNA), G₁ (Ki67⁺, with 2n DNA), and S‐G₂/M (Ki67⁺, with 2n < DNA ≤ 4n). This panel was established for the analysis of mouse (C57BL/6J) spleen.

A flow cytometric journey into cell cycle analysis

Cell cycle involves a series of changes that lead to cell growth and division. Cell cycle analysis is crucial to understand cellular responses to changing environmental conditions. Since its inception, flow cytometry has been particularly useful for cell cycle analysis at single cell level due to its speed and precision. Previously, flow cytometric cell cycle analysis relied solely on the measurement of cellular DNA content. Later, methods were developed for multiparametric analysis. This review explains the journey of flow cytometry to understand different molecular and cellular events underlying cell cycle using various protocols. Recent advances in the field that overcome the shortcomings of traditional flow cytometry and expand its scope for cell cycle studies are also discussed.

To Ki or Not to Ki: Re-Evaluating the Use and Potentials of Ki-67 for T Cell Analysis

This study discusses substantive advances in T cell proliferation analysis, with the aim to provoke a re-evaluation of the generally-held view that Ki-67 is a reliable proliferation marker per se, and to offer a more sensitive and effective method for T cell cycle analysis, with informative examples in mouse and human settings. We summarize recent experimental work from our labs showing that, by Ki-67/DNA dual staining and refined flow cytometric methods, we were able to identify T cells in the S-G₂/M phases of the cell-cycle in the peripheral blood (collectively termed “T Double S” for T cells in S-phase in Sanguine: in short “T_DS” cells). Without our refinement, such cells may be excluded from conventional lymphocyte analyses. Specifically, we analyzed clonal expansion of antigen-specific CD8 T cells in vaccinated mice, and demonstrated the potential of T_DS cells to reflect immune dynamics in human blood samples from healthy donors, and patients with type 1 diabetes, infectious mononucleosis, and COVID-19. The Ki-67/DNA dual staining, or T_DS assay, provides a reliable approach by which human peripheral blood can be used to reflect the dynamics of human lymphocytes, rather than providing mere steady-state phenotypic snapshots. The method does not require highly sophisticated “-omics” capabilities, so it should be widely-applicable to health care in diverse settings. Furthermore, our results argue that the T_DS assay can provide a window on immune dynamics in extra-lymphoid tissues, a long-sought potential of peripheral blood monitoring, for example in relation to organ-specific autoimmune diseases and infections, and cancer immunotherapy.

A dynamic COVID-19 immune signature includes associations with poor prognosis

Improved understanding and management of COVID-19, a potentially life-threatening disease, could greatly reduce the threat posed by its etiologic agent, SARS-CoV-2. Toward this end, we have identified a core peripheral blood immune signature across 63 hospital-treated patients with COVID-19 who were otherwise highly heterogeneous. The signature includes discrete changes in B and myelomonocytic cell composition, profoundly altered T cell phenotypes, selective cytokine/chemokine upregulation and SARS-CoV-2-specific antibodies. Some signature traits identify links with other settings of immunoprotection and immunopathology; others, including basophil and plasmacytoid dendritic cell depletion, correlate strongly with disease severity; while a third set of traits, including a triad of IP-10, interleukin-10 and interleukin-6, anticipate subsequent clinical progression. Hence, contingent upon independent validation in other COVID-19 cohorts, individual traits within this signature may collectively and individually guide treatment options; offer insights into COVID-19 pathogenesis; and aid early, risk-based patient stratification that is particularly beneficial in phasic diseases such as COVID-19.

Author Correction: A dynamic COVID-19 immune signature includes associations with poor prognosis

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Tracking immunodynamics by identification of S-G2/M-phase T cells in human peripheral blood

The ready availability of human blood makes it the first choice for immuno-monitoring. However, this has been largely confined to static metrics, particularly resting T cell phenotypes. Conversely, dynamic assessments have mostly relied on cell stimulation in vitro which is subject to multiple variables. Here, immunodynamic insights from the peripheral blood are shown to be obtainable by applying a revised approach to cell-cycle analysis. Specifically, refined flow cytometric protocols were employed, assuring the reliable quantification of T cells in the S-G2/M phases of the cell-cycle (collectively termed "T Double S" for T cells in S-phase in Sanguine: in short "TDS" cells). Without protocol refinement, TDS could be either missed, as most of them layed out of the conventional lymphocyte gates, or confused with cell doublets artefactually displaying high DNA-content. To illustrate the nature of TDS cells, and their relationship to different immunodynamic scenarios, we examined them in healthy donors (HD); infectious mononucleosis (IM) patients versus asymptomatic EBV+ carriers; and recently-diagnosed T1D patients. TDS were reproducibly more abundant among CD8+ T cells and a defined subset of T-regulatory CD4+ T cells, and were substantially increased in IM and a subset of T1D patients. Of note, islet antigen-reactive TDS cell frequencies were associated with an aggressive T cell effector phenotype, suggesting that peripheral blood can reflect immune events within tissues in T1D, and possibly in other organ-specific autoimmune diseases. Our results suggest that tracking TDS cells may provide a widely applicable means of gaining insight into ongoing immune response dynamics in a variety of settings, including tissue immunopathologies where the peripheral blood has often not been considered insightful.

Recirculation and Residency of T Cells and Tregs: Lessons Learnt in Anacapri

"Location, location, and location": according to this mantra, the place where living beings settle has a key impact on the success of their activities; in turn, the living beings can, in many ways, modify their environment. This idea has now become more and more true for T cells. The ability of T cells to recirculate throughout blood or lymph, or to stably reside in certain tissues, turned out to determine immunity to pathogens, and tumors. If location matters also for human beings, the inspiring environment of Capri Island has contributed to the success of the EFIS-EJI Ruggero Ceppellini Advanced School of Immunology focused on "T cell memory," held in Anacapri from October 12, 2018 to October 15, 2018. In this minireview, we would like to highlight some novel concepts about T cell migration and residency and discuss their implications in relation to recent advances in the field, including the mechanisms regulating compartmentalization and cell cycle entry of T cells during activation, the role of mitochondrial metabolism in T cell movement, and the residency of regulatory T cells.

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.