Making the most of high-dimensional cytometry data

High-dimensional spectral flow cytometry of activation and phagocytosis by peripheral human polymorphonuclear leukocytes

Polymorphonuclear lymphocytes (PMNs) are terminally differentiated phagocytes with pivotal roles in infection, inflammation, tissue injury, and resolution. PMNs can display a breadth of responses to diverse endogenous and exogenous stimuli, making understanding of these innate immune responders vital yet challenging to achieve. Here, we report a 22-color spectral flow cytometry panel to profile primary human PMNs on population and single cell levels for surface marker expression of activation, degranulation, phagocytosis, migration, chemotaxis, and interaction with fluorescently labeled cargo. We demonstrate the surface protein response of PMNs to phorbol ester stimulation compared to untreated controls in an adherent PMN model with additional analysis of intra- and inter-subject variability. PMNs challenged with the Gram-negative bacterial pathogen Neisseria gonorrhoeae revealed infectious dose-dependent changes in surface marker expression in bulk, population-level analysis. Imaging flow cytometry complemented spectral cytometry, demonstrating that fluorescence signal from labeled bacteria corresponded with bacterial burden on a per-cell basis. Spectral flow cytometry subsequently identified surface markers which varied with direct PMN-bacterium association as well as those which varied in the presence of bacteria but without phagocytosis. This spectral panel protocol highlights best practices for efficient customization and is compatible with downstream approaches such as spectral cell sorting and single-cell RNA-sequencing for applicability to diverse research questions in the field of PMN biology.

Dietary factors and their influence on immunotherapy strategies in oncology: a comprehensive review

Immunotherapy is emerging as a promising avenue in oncology, gaining increasing importance and offering substantial advantages when compared to chemotherapy or radiotherapy. However, in the context of immunotherapy, there is the potential for the immune system to either support or hinder the administered treatment. This review encompasses recent and pivotal studies that assess the influence of dietary elements, including vitamins, fatty acids, nutrients, small dietary molecules, dietary patterns, and caloric restriction, on the ability to modulate immune responses. Furthermore, the article underscores how these dietary factors have the potential to modify and enhance the effectiveness of anticancer immunotherapy. It emphasizes the necessity for additional research to comprehend the underlying mechanisms for optimizing the efficacy of anticancer therapy and defining dietary strategies that may reduce cancer-related morbidity and mortality. Persistent investigation in this field holds significant promise for improving cancer treatment outcomes and maximizing the benefits of immunotherapy.

Depleting myeloid-biased haematopoietic stem cells rejuvenates aged immunity

Ageing of the immune system is characterized by decreased lymphopoiesis and adaptive immunity, and increased inflammation and myeloid pathologies1,2. Age-related changes in populations of self-renewing haematopoietic stem cells (HSCs) are thought to underlie these phenomena3. During youth, HSCs with balanced output of lymphoid and myeloid cells (bal-HSCs) predominate over HSCs with myeloid-biased output (my-HSCs), thereby promoting the lymphopoiesis required for initiating adaptive immune responses, while limiting the production of myeloid cells, which can be pro-inflammatory4. Ageing is associated with increased proportions of my-HSCs, resulting in decreased lymphopoiesis and increased myelopoiesis3,5,6. Transfer of bal-HSCs results in abundant lymphoid and myeloid cells, a stable phenotype that is retained after secondary transfer; my-HSCs also retain their patterns of production after secondary transfer5. The origin and potential interconversion of these two subsets is still unclear. If they are separate subsets postnatally, it might be possible to reverse the ageing phenotype by eliminating my-HSCs in aged mice. Here we demonstrate that antibody-mediated depletion of my-HSCs in aged mice restores characteristic features of a more youthful immune system, including increasing common lymphocyte progenitors, naive T cells and B cells, while decreasing age-related markers of immune decline. Depletion of my-HSCs in aged mice improves primary and secondary adaptive immune responses to viral infection. These findings may have relevance to the understanding and intervention of diseases exacerbated or caused by dominance of the haematopoietic system by my-HSCs.

Flow cytometry: Aspects and application in plant and biological science

Flow cytometry is a potent method that enables the quick and concurrent investigation of several characteristics of single cells in solution. Photodiodes or photomultiplier tubes are employed to detect the dispersed and fluorescent light signals that are produced by the laser beam as it passes through the cells. Photodetectors transform the light signals produced by the laser into electrical impulses. A computer then analyses these electrical impulses to identify and measure the various cell populations depending on their fluorescence or light scattering characteristics. Based on their fluorescence or light scattering properties, cell populations can be examined and/or isolated. This review covers the basic principle, components, working and specific biological applications of flow cytometry, including studies on plant, cell and molecular biology and methods employed for data processing and interpretation as well as the potential future relevance of this methodology in light of retrospective analysis and recent advancements in flow cytometry.

CRUSTY: a versatile web platform for the rapid analysis and visualization of high-dimensional flow cytometry data

Flow cytometry (FCM) can investigate dozens of parameters from millions of cells and hundreds of specimens in a short time and at a reasonable cost, but the amount of data that is generated is considerable. Computational approaches are useful to identify novel subpopulations and molecular biomarkers, but generally require deep expertize in bioinformatics and the use of different platforms. To overcome these limitations, we introduce CRUSTY, an interactive, user-friendly webtool incorporating the most popular algorithms for FCM data analysis, and capable of visualizing graphical and tabular results and automatically generating publication-quality figures within minutes. CRUSTY also hosts an interactive interface for the exploration of results in real time. Thus, CRUSTY enables a large number of users to mine complex datasets and reduce the time required for data exploration and interpretation. CRUSTY is accessible at https://crusty.humanitas.it/ .

A new hybrid algorithm for three-stage gene selection based on whale optimization

In biomedical data mining, the gene dimension is often much larger than the sample size. To solve this problem, we need to use a feature selection algorithm to select feature gene subsets with a strong correlation with phenotype to ensure the accuracy of subsequent analysis. This paper presents a new three-stage hybrid feature gene selection method, that combines a variance filter, extremely randomized tree, and whale optimization algorithm. First, a variance filter is used to reduce the dimension of the feature gene space, and an extremely randomized tree is used to further reduce the feature gene set. Finally, the whale optimization algorithm is used to select the optimal feature gene subset. We evaluate the proposed method with three different classifiers in seven published gene expression profile datasets and compare it with other advanced feature selection algorithms. The results show that the proposed method has significant advantages in a variety of evaluation indicators.

Using mass cytometry for the analysis of samples of the human airways

Mass cytometry (MC) is a powerful method for mapping complex cellular systems at single-cell levels, based on the detection of cellular proteins. Numerous studies have been performed using human blood, but there is a lack of protocols describing the processing and labeling of bronchoalveolar lavage fluid (BALF) and nasal polyps (NP) for acquisition by MC. These specimens are essential in the investigation of immune cell characteristics in airway diseases such as asthma and chronic rhinosinusitis with NP (CRSwNP). Here we optimized a workflow for processing, labeling, and acquisition of BALF and NP cells by MC. Among three methods tested for NP digestion, combined enzymatic/mechanical processing yielded maximum cell recovery, viability and labeling patterns compared to the other methods. Treatment with DNAse improved sample acquisition by MC. In a final step, we performed a comparison of blood, BALF and NP cell composition using a 31-marker MC antibody panel, revealing expected differences between the different tissue but also heterogeneity among the BALF and NP samples. We here introduce an optimized workflow for the MC analysis of human NP and BALF, which enables comparative analysis of different samples in larger cohorts. A deeper understanding of immune cell characteristics in these samples may guide future researchers and clinicians to a better disease management.

Distinct pretreatment innate immune landscape and posttreatment T cell responses underlie immunotherapy-induced colitis

Immune-related adverse events represent a major hurdle to the success of immunotherapy. The immunological mechanisms underlying their development and relation to antitumor responses are poorly understood. By examining both systemic and tissue-specific immune changes induced by combination anti-CTLA-4 and anti-PD-1 immunotherapy, we found distinct repertoire changes in patients who developed moderate-severe colitis, irrespective of their antitumor response to therapy. The proportion of circulating monocytes were significantly increased at baseline in patients who subsequently developed colitis compared with patients who did not develop colitis, and biopsies from patients with colitis showed monocytic infiltration of both endoscopically and histopathologically normal and inflamed regions of colon. The magnitude of systemic expansion of T cells following commencement of immunotherapy was also greater in patients who developed colitis. Importantly, we show expansion of specific T cell subsets within inflamed regions of the colon, including tissue-resident memory CD8+ T cells and Th1 CD4+ T cells in patients who developed colitis. Our data also suggest that CD8+ T cell expansion was locally induced, while Th1 cell expansion was systemic. Together, our data show that exaggerated innate and T cell responses to combination immunotherapy synergize to propel colitis in susceptible patients.

Implementing High Dimensional Reduction Analysis on Histocytometric Data

In a previous protocol article, we demonstrated construction of a histocytometry pipeline that is capable of both segmenting highly aggregated cell populations and retaining the original intensity data range of the input microscopy images. In the protocol presented here, using the output from the aforementioned article, we demonstrate how to phenotype the data using the high dimensional reduction analysis technique optimized t-distributed stochastic neighbor embedding (opt-t-SNE) and compare it to traditional manual gating. Additionally, we present a protocol illustrating the advantage of the inclusion of cell junction/membrane markers for accurately segmenting highly aggregated cell populations in ilastik. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Phenotyping lymph node populations using manual gating Basic Protocol 2: Phenotyping lymph node populations using t-SNE dimensional reduction Support Protocol: ilastik segmentation using a pan marker.

Spectral flow cytometry cluster analysis of therapeutic donor lymphocyte infusions identifies T cell subsets associated with outcome in patients with AML relapse

Identification of immune phenotypes linked to durable graft-versus-leukemia (GVL) response following donor lymphocyte infusions (DLI) is of high clinical relevance. In this prospective observational study of 13 AML relapse patients receiving therapeutic DLI, we longitudinally investigated changes in differentiation stages and exhaustion markers of T cell subsets using cluster analysis of 30-color spectral flow cytometry during 24 months follow-up. DLI cell products and patient samples after DLI were analyzed and correlated to the clinical outcome. Analysis of DLI cell products revealed heterogeneity in the proportions of naïve and antigen experienced T cells. Cell products containing lower levels of effector memory (eff/m) cells and higher amounts of naïve CD4⁺ and CD8⁺ T cells were associated with long-term remission. Furthermore, investigation of patient blood samples early after DLI showed that patients relapsing during the study period, had higher levels of CD4⁺ eff/m T cells and expressed a mosaic of surface molecules implying an exhausted functional state. Of note, this observation preceded the clinical diagnosis of relapse by five months. On the other hand, patients with continuous remission retained lower levels of exhausted CD4⁺ eff/m T cells more than four months post DLI. Moreover, lower frequencies of exhausted CD8⁺ eff/m T cells as well as higher amounts of CD4⁺temra CD45RO⁺ T cells were present in this group. These results imply the formation of functional long-term memory pool of T cells. Finally, unbiased sample analysis showed that DLI cell products with low levels of eff/m cells both in CD4⁺ and CD8⁺ T cell subpopulations associate with a lower relapse incidence. Additionally, competing risk analysis of patient samples taken early after DLI revealed that patients with high amounts of exhausted CD4⁺ eff/m T cells in their blood exhibited significantly higher rates of relapse. In conclusion, differentially activated T cell clusters, both in the DLI product and in patients post infusion, were associated with AML relapse after DLI. Our study suggests that differences in DLI cell product composition might influence GVL. In-depth monitoring of T cell dynamics post DLI might increase safety and efficacy of this immunotherapy, while further studies are needed to assess the functionality of T cells found in the DLI.

Peripheral B-cell dysregulation is associated with relapse after long-term quiescence in patients with multiple sclerosis

B cells play a major role in multiple sclerosis (MS), with many successful therapeutics capable of removing them from circulation. One such therapy, alemtuzumab, is thought to reset the immune system without the need for ongoing therapy in a proportion of patients. The exact cells contributing to disease pathogenesis and quiescence remain to be identified. We utilized mass cytometry to analyze B cells from the blood of patients with relapse-remitting MS (RRMS) before and after alemtuzumab treatment, and during relapse. A complementary RRMS cohort was analyzed by single-cell RNA sequencing. The R package "Spectre" was used to analyze these data, incorporating FlowSOM clustering, sparse partial least squares-discriminant analysis and permutational multivariate analysis of variance. Immunoglobulin (Ig)A+ and IgG1 + B-cell numbers were altered, including higher IgG1 + B cells during relapse. B-cell linker protein (BLNK), CD40 and CD210 expression by B cells was lower in patients with RRMS compared with non-MS controls, with similar results at the transcriptomic level. Finally, alemtuzumab restored BLNK, CD40 and CD210 expression by IgA+ and IgG1 + B cells, which was altered again during relapse. These data suggest that impairment of IgA+ and IgG1 + B cells may contribute to MS pathogenesis, which can be restored by alemtuzumab.

Simplified mass cytometry protocol for in-plate staining, barcoding, and cryopreservation of human PBMC samples in clinical trials

With the increasing use of mass cytometry in clinical research, a simplified and standardized protocol for immunophenotyping human peripheral blood mononuclear cells (PBMCs) in clinical trials is needed. We present a simplified in-plate staining protocol for up to 80 samples, for laboratories of all mass cytometry expertise levels, aimed to generate reproducible datasets for large clinical cohorts. In this protocol, we provide details on the requirements to obtain meaningful results, spanning from sample quality, barcoding, and batch-freezing of stained samples.

CyTOF mass cytometry analysis of human memory CD4+ T cells and memory B cells

High-dimensional mass cytometry provides unparalleled insight into the cellular composition of the immune system. Here, we describe a mass-cytometry-based protocol to examine memory CD4⁺ T cell and memory B cell (MBC) responses in human peripheral blood. This approach allows for the identification of >50 distinct memory CD4⁺ T cell and MBC populations from a single clinical sample. This highly reproducible protocol has been successfully applied to multiple infectious disease settings to identify correlates of susceptibility or protection from infection.

For complete details on the use and execution of this protocol, please refer to Ioannidis et al. (2021).

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CyTOF mass-cytometry-based protocol to analyze human peripheral blood mononuclear cells

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Optimized protocol for clinical samples

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Allows in-depth analysis of human memory CD4⁺ T cell and memory B cell responses

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Applicable to multiple disease settings

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.