Treatment with soluble CD24 attenuates COVID-19-associated systemic immunopathology

Background Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19) through direct lysis of infected lung epithelial cells, which releases damage-associated molecular patterns and induces a pro-inflammatory cytokine milieu causing systemic inflammation. Anti-viral and anti-inflammatory agents have shown limited therapeutic efficacy. Soluble CD24 (CD24Fc) blunts the broad inflammatory response induced by damage-associated molecular patterns via binding to extracellular high mobility group box 1 and heat shock proteins, as well as regulating the downstream Siglec10-Src homology 2 domain–containing phosphatase 1 pathway. A recent randomized phase III trial evaluating CD24Fc for patients with severe COVID-19 (SAC-COVID; NCT04317040) demonstrated encouraging clinical efficacy. Methods Using a systems analytical approach, we studied peripheral blood samples obtained from patients enrolled at a single institution in the SAC-COVID trial to discern the impact of CD24Fc treatment on immune homeostasis. We performed high dimensional spectral flow cytometry and measured the levels of a broad array of cytokines and chemokines to discern the impact of CD24Fc treatment on immune homeostasis in patients with COVID-19. Results Twenty-two patients were enrolled, and the clinical characteristics from the CD24Fc vs. placebo groups were matched. Using high-content spectral flow cytometry and network-level analysis, we found that patients with severe COVID-19 had systemic hyper-activation of multiple cellular compartments, including CD8+ T cells, CD4+ T cells, and CD56+ natural killer cells. Treatment with CD24Fc blunted this systemic inflammation, inducing a return to homeostasis in NK and T cells without compromising the anti-Spike protein antibody response. CD24Fc significantly attenuated the systemic cytokine response and diminished the cytokine coexpression and network connectivity linked with COVID-19 severity and pathogenesis. Conclusions Our data demonstrate that CD24Fc rapidly down-modulates systemic inflammation and restores immune homeostasis in SARS-CoV-2-infected individuals, supporting further development of CD24Fc as a novel therapeutic against severe COVID-19.

Mapping and Characterization of HCMV-Specific Unconventional HLA-E-Restricted CD8 T Cell Populations and Associated NK and T Cell Responses Using HLA/Peptide Tetramers and Spectral Flow Cytometry

HCMV drives complex and multiple cellular immune responses, which causes a persistent immune imprint in hosts. This study aimed to achieve both a quantitative determination of the frequency for various anti-HCMV immune cell subsets, including CD8 T, γδT, NK cells, and a qualitative analysis of their phenotype. To map the various anti-HCMV cellular responses, we used a combination of three HLApeptide tetramer complexes (HLA-EVMAPRTLIL, HLA-EVMAPRSLLL, and HLA-A2NLVPMVATV) and antibodies for 18 surface markers (CD3, CD4, CD8, CD16, CD19, CD45RA, CD56, CD57, CD158, NKG2A, NKG2C, CCR7, TCRγδ, TCRγδ2, CX3CR1, KLRG1, 2B4, and PD-1) in a 20-color spectral flow cytometry analysis. This immunostaining protocol was applied to PBMCs isolated from HCMV- and HCMV+ individuals. Our workflow allows the efficient determination of events featuring HCMV infection such as CD4/CD8 ratio, CD8 inflation and differentiation, HCMV peptide-specific HLA-EUL40 and HLA-A2pp65CD8 T cells, and expansion of γδT and NK subsets including δ2-γT and memory-like NKG2C+CD57+ NK cells. Each subset can be further characterized by the expression of 2B4, PD-1, KLRG1, CD45RA, CCR7, CD158, and NKG2A to achieve a fine-tuned mapping of HCMV immune responses. This assay should be useful for the analysis and monitoring of T-and NK cell responses to HCMV infection or vaccines.

String correlators in AdS3 from FZZ duality

Motivated by recent works in which the FZZ duality plays an important role, we revisit the computation of correlation functions in the sine-Liouville field theory. We present a direct computation of the three-point function, the simplest to the best of our knowledge, and give expressions for the N-point functions in terms of integrated Liouville theory correlators. This leads us to discuss the relation to the $$ {H}_3^{+} $$ H 3 + WZW-Liouville correspondence, especially in the case in which spectral flow is taken into account. We explain how these results can be used to study scattering amplitudes of winding string states in AdS3.

How to Prepare Spectral Flow Cytometry Datasets for High Dimensional Data Analysis: A Practical Workflow

Spectral flow cytometry is an upcoming technique that allows for extensive multicolor panels, enabling simultaneous investigation of a large number of cellular parameters in a single experiment. To fully explore the resulting high-dimensional single cell datasets, high-dimensional analysis is needed, as opposed to the common practice of manual gating in conventional flow cytometry. However, preparing spectral flow cytometry data for high-dimensional analysis can be challenging, because of several technical aspects. In this article, we will give insight into the pitfalls of handling spectral flow cytometry datasets. Moreover, we will describe a workflow to properly prepare spectral flow cytometry data for high dimensional analysis and tools for integrating new data at later time points. Using healthy control data as example, we will go through the concepts of quality control, data cleaning, transformation, correcting for batch effects, subsampling, clustering and data integration. This methods article provides an R-based pipeline based on previously published packages, that are readily available to use. Application of our workflow will aid spectral flow cytometry users to obtain valid and reproducible results.

Bone Marrow GZMK +IL7R + Progenitor-Exhausted CD8 + T Cells Correlate with Sustained Clinical Remission in Patients with Acute Myeloid Leukemia (AML) Undergoing Chemotherapy

Introduction The role of T cells in chemotherapy response and maintenance of remission in acute myeloid leukemia (AML) patients is not fully understood. In solid tumors and chronic infections, exhaustion is a multistep process ranging from less differentiated progenitor exhausted (Tpex) to intermediate and terminally exhausted T cells (Beltra et al. 2020). High frequencies of Tpex correlate with response to immune-checkpoint blockade in solid tumors (Miller et al. 2019). In AML, where the backbone of treatment is chemotherapy, the role of dysfunctional T-cell subsets has yet to be elucidated. Methods Serial bone marrow (BM) samples from 16 AML patients (10 complete responders (Res) and 6 non-responders (NonRes)) at diagnosis and at response assessment after induction chemotherapy and 12 healthy donors (HD) were analyzed by flow cytometry using a 13-color panel. Moreover, we performed single-cell RNA sequencing (scRNAseq) (10X Genomics) on BM samples from 2 HD and 5 AML patients (3 Res, 2 NonRes) at baseline and after chemotherapy. Subsequently, we used a scRNAseq-guided 26-color spectral flow cytometry panel and explored T-cell phenotypes on BM of 22 AML patients (12 Res and 10 NonRes). Custom-made R scripts were employed for high-dimensional flow cytometry and scRNAseq analysis. Results Initial flow-cytometry analysis showed a significant increase in BM PD1 +CD28 + CD8 + T cell subset (p<0.01) in Res vs NonRes at baseline and post-chemotherapy (data not shown). To further investigate these results, we performed 5' VDJ scRNAseq and used gene signatures mapped in two dimensions via UMAP to annotate the T-cell clusters as naive, Tpex, T effector CX3CR1 + (Teff CX3CR1pos), Terminally exhausted 1 (Term_exh1) and Terminally exhausted 2 (Term_exh2) (Fig 1A). Of note, the two most upregulated genes in Tpex were GZMK and IL-7R. We then performed differential abundance analysis to investigate differences in terms of clusters' frequencies across the three conditions (Res, NonRes, HD). At both timepoints Res had an increased frequency of Tpex and Teff CX3CR1pos compared to NonRes. Conversely, Term_exh2 cells were more abundant in NonRes (Fig. 1B). Next, we measured the magnitude of clonal expansion in antigen-experienced CD8 + T cells in Res and NonRes generating an overlay of the position of clonally expanded cells projected onto the UMAP. The most clonally expanded subsets were Tpex and Teff CX3CR1pos in Res (Fig. 1C) and Term_exh2 in NonRes (Fig. 1D) revealing a strong relationship between abundance and clonal expansion of the CD8 + T-cell subsets. Our scRNAseq results were then confirmed at the protein level with spectral flow-cytometry. The FlowSOM algorithm identified a CD8 + GZMK +CD127 + subset to be increased at baseline in Res vs NonRes (Fig. 1E). Remarkably, this cluster was also characterized by the expression of TIGIT, PD1 and TCF-1. These results were subsequently reproduced by manual gating of the GZMK +CD127 + subset which was significantly enriched (p<0.01) in Res vs NonRes (Fig. 1F). Of note, patients with a higher-than-median frequency of GZMK +CD127 +CD8 + T cells experienced significantly (p<0.02) prolonged overall survival after therapy (Fig. 1G). Conclusion Improving our understanding of the immune microenvironment in AML is critical for the rational integration of novel treatment strategies that seek to increase the response rate and/or maintain remission. We identified GZMK +IL7R + CD8 + cells as a distinct entity in the early differentiated CD8 + memory T cell pool that is clonally expanded and more abundant in Res compared to NonRes. This subset has a stem-like signature and may be associated with longer in vivo CD8 + T cell persistence and long-term AML control. An in-depth functional characterization with in vitro experiments and in vivo mouse models is currently ongoing. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

The AdS3 × S1 chiral ring

We study AdS3× S1× Y supersymmetric string theory backgrounds with Neveu-Schwarz-Neveu-Schwarz flux that are dual to $$ \mathcal{N} $$ N = 2 superconformal theories on the boundary. We classify all worldsheet vertex operators that correspond to space-time chiral primaries. We compute space-time chiral ring structure constants for operators in the zero spectral flow sector using the operator product expansion in the worldsheet theory. We find that the structure constants take a universal form that depends only on the topological data of the $$ \mathcal{N} $$ N = 2 superconformal theory on Y.

The worldsheet dual of free super Yang-Mills in 4D

The worldsheet string theory dual to free 4d $$ \mathcal{N} $$ N = 4 super Yang-Mills theory was recently proposed in [1]. It is described by a free field sigma model on the twistor space of AdS5 × S5, and is a direct generalisation of the corresponding model for tensionless string theory on AdS3 × S3. As in the case of AdS3, the worldsheet theory contains spectrally flowed representations. We proposed in [1] that in each such sector only a finite set of generalised zero modes (‘wedge modes’) are physical. Here we show that after imposing the appropriate residual gauge conditions, this worldsheet description reproduces precisely the spectrum of the planar gauge theory. Specifically, the states in the sector with w units of spectral flow match with single trace operators built out of w super Yang-Mills fields (‘letters’). The resulting physical picture is a covariant version of the BMN light-cone string, now with a finite number of twistorial string bit constituents of an essentially topological worldsheet.

With great power comes great responsibility: high-dimensional spectral flow cytometry to support clinical trials

Flow cytometry is a powerful technology used in research, drug development and clinical sample analysis for cell identification and characterization, allowing for the simultaneous interrogation of multiple targets on various cell subsets from limited samples. Recent advancements in instrumentation and fluorochrome availability have resulted in significant increases in the complexity and dimensionality of flow cytometry panels. Though this increase in panel size allows for detection of a broader range of markers and sub-populations, even in restricted biological samples, it also comes with many challenges in panel design, optimization, and downstream data analysis and interpretation. In the current paper we describe the practices we established for development of high-dimensional panels on the Aurora spectral flow cytometer to aid clinical sample analysis.

Identification of fetal liver stromal subsets in spectral cytometry using the parameter autofluorescence

The fetal liver is the main hematopoietic organ during embryonic development. The fetal liver is also the unique anatomical site where hematopoietic stem cells expand before colonizing the bone marrow, where they ensure life-long blood cell production and become mostly resting. The identification of the different cell types that comprise the hematopoietic stroma in the fetal liver is essential to understand the signals required for the expansion and differentiation of the hematopoietic stem cells. We used a panel of monoclonal antibodies to identify fetal liver stromal cells in a 5-laser equipped spectral flow cytometry analyzer. The ″Autofluorescence Finder″ of SONY ID7000 software identified two distinct autofluorescence emission spectra. Using autofluorescence as a fluorescence parameter we could assign the two autofluorescent signals to three distinct cell types and identified surface markers that characterize these populations. We found that one autofluorescent population corresponds to hepatoblasts and cholangiocytes whereas the other expresses mesenchymal transcripts and was identified as stellate cells. Importantly, after birth, autofluorescence becomes the unique identifying property of hepatoblasts because mature cholangiocytes are no longer autofluorescent. These results show that autofluorescence used as a parameter in spectral flow cytometry is a useful tool to identify new cell subsets that are difficult to analyze in conventional flow cytometry.