Mycoplasma hyorhinis is a frequently observed contaminant in cell cultures, and its detection and purification pose considerable challenges. Fragments or other cell components are similar in size to those of Mycoplasma; therefore, distinguishing them is difficult. In this study, we used Hoechst staining in combination with carboxyfluorescein succinimidyl ester (CFSE) to label Mycoplasma. The trigger threshold was set in the Hoechst Blue channel rather than in the default forward scatter channel, utilizing the differences in DNA content between Mycoplasma and fragments. Subsequently, we identified and isolated it at single-cell resolution via flow cytometry and successfully sorted infectious Mycoplasma in cell culture. Simultaneously, we validated the accuracy and feasibility of this approach using polymerase chain reaction, fluorescence confocal microscopy, and cryo-electron microscopy. This methodology enabled the diagnosis of Mycoplasma at extremely low concentrations, significantly enhancing the detection efficiency and facilitating the isolation and purification of parasitic Mycoplasma in cell culture instead of pure Mycoplasma culture in artificial media for subsequent studies.

Imaging flow cytometry (IFC) provides single-cell imaging data at a high acquisition rate. It is increasingly used in image-based profiling experiments consisting of hundreds of thousands of multi-channel images of cells. Currently available software solutions for processing microscopy data can provide good results in downstream analysis, but are limited in efficiency and scalability, and often ill-adapted to IFC data. In this work, we propose Scalable Cytometry Image Processing (SCIP), a Python software that efficiently processes images from IFC and standard microscopy datasets. We also propose a file format for efficiently storing IFC data. We showcase our contributions on two large-scale microscopy and one IFC datasets, all of which are publicly available. Our results show that SCIP can extract the same kind of information as other tools, in a much shorter time and in a more scalable manner.

The need for more in-depth exploration of the human immune system has moved the flow cytometry field forward with advances in instrumentation, reagent development and availability, and user-friendly implementation of data analysis methods. We developed a high-quality human 45-color panel, for comprehensive characterization of major cell lineages present in circulation including T cells, γδ T cells, NKT-like cells, B cells, NK cells, monocytes, basophils, dendritic cells, and ILCs. Assay optimization steps are described in detail to ensure that each marker in the panel was optimally resolved. In addition, we highlight the outstanding discernment of cell activation, exhaustion, memory, and differentiation states of CD4+ and CD8+ T cells using this 45-color panel. The panel enabled an in-depth description of very distinct phenotypes associated with the complexity of the T cell memory response. Furthermore, we present how this panel can be effectively used for cell sorting on instruments with a similar optical layout to achieve the same level of resolution. Functional evaluation of sorted specific rare cell subsets demonstrated significantly different patterns of immunological responses to stimulation, supporting functional and phenotypic differences within the T cell memory subsets. In summary, the combination of full spectrum profiling technology and careful assay design and optimization results in a high resolution multiparametric 45-color assay. This panel offers the opportunity to fully characterize immunological profiles present in peripheral blood in the context of infectious diseases, autoimmunity, neurodegeneration, immunotherapy, and biomarker discovery.

The fixation and permeabilization of cells are essential for labeling intracellular biomarkers in flow cytometry. However, these chemical treatments often alter fragile targets, such as cell surface and fluorescent proteins (FPs), and can destroy chemically-sensitive fluorescent labels. This reduces measurement accuracy and introduces compromises into sample workflows, leading to losses in data quality. Here, we demonstrate a novel multi-pass flow cytometry approach to address this long-standing problem. Our technique utilizes individual cell barcoding with laser particles, enabling sequential analysis of the same cells with single-cell resolution maintained. Chemically-fragile protein markers and their fluorochrome conjugates are measured prior to destructive sample processing and adjoined to subsequent measurements of intracellular markers after fixation and permeabilization. We demonstrate the effectiveness of our technique in accurately measuring intracellular FPs and methanol-sensitive antigens and fluorophores, along with various surface and intracellular markers. This approach significantly enhances assay flexibility, enabling accurate and comprehensive cellular analysis without the constraints of conventional one-time measurement flow cytometry. This innovation paves new avenues in flow cytometry for a wide range of applications in immuno-oncology, stem cell research, and cell biology.

Mass cytometry enables deep profiling of biological samples at single-cell resolution. This technology is more than relevant in cancer research due to high cellular heterogeneity and complexity. Downstream analysis of high-dimensional datasets increasingly relies on machine learning (ML) to extract clinically relevant information, including supervised algorithms for classification and regression purposes. In cancer research, they are used to develop predictive models that will guide clinical decision making. However, the development of supervised algorithms faces major challenges, such as sufficient validation, before being translated into the clinics. In this work, we provide a framework for the analysis of mass cytometry data with a specific focus on supervised algorithms and practical examples of their applications. We also raise awareness on key issues regarding good practices for researchers curious to implement supervised ML on their mass cytometry data. Finally, we discuss the challenges of supervised ML application to cancer research.

Liquid biopsies developed into a range of sensitive technologies aiming to analyze for example, circulating tumor cells (CTCs) in peripheral blood, which significantly deepens understanding of the metastatic process. Nevertheless, examination of CTCs is mostly limited to their enumeration and usually only 2-3 markers-based phenotyping, not offering yet sufficient insight into their biology. In contrast, quantitative analysis of their morphological details might extend our knowledge about dissemination and even improve CTC isolation or label-free identification methods dependent on their physical features such as size, and deformability. Current study was conducted to describe CTCs' and their size, shape, presence of protrusions, and micronuclei across various types of cancers (lung, n = 29; ovarian, n = 24, breast, n = 54; and prostate, n = 33). Epithelial (pan-keratins), mesenchymal (vimentin), and two exclusion markers were used to identify CTCs and classify them into four epithelial and epithelial-mesenchymal transition-related phenotypes using standardized and throughput method, imaging flow cytometry. The morphological characteristics of CTCs, including their nuclei, such as circularity, the maximum, and minimum diagonal values were determined using an open-source software QuPath. On average, detected CTCs (n = 1156) were larger, and more irregular in shape compared to leukocytes/endothelial cells (n = 400). Epithelial and mesenchymal CTCs had the largest (median = 18.2 μm) and the smallest diameter (median = 10.4 μm), respectively. In terms of cancer-specific variations, the largest CTCs were identified in lung cancer, whereas the smallest-in prostate and breast cancers. Epithelial CTCs and those negative for both epithelial and mesenchymal markers exhibited the highest degree of elongation, whereas mesenchymal CTCs were the most irregular in shape. Protrusions and micronuclei were observed extremely rarely within CTCs of breast and prostate cancer (0.6%-0.8% of CTCs). Micronuclei were observed only in epithelial and epithelial-mesenchymal CTCs. This study underscores the significant variability in the morphological features of CTCs in relation to their phenotypic classification or even the particular organ of origin, potentially influencing for example, size-dependent CTC isolation methods. It demonstrates for the first time the morphological measurements of CTCs undergoing epithelial-mesenchymal transition, and some specific morphological details (i.e., protrusions, micronuclei) within CTCs in general.

The water channel aquaporin 4 (AQP4) contributes to water flow and waste removal across the blood-brain barrier and its levels, organization and localization are perturbed in various neurological diseases, including Alzheimer's Disease. This renders AQP4 a potentially valuable therapeutic target. However, most functional assays aimed at identifying modulators of AQP4 function are performed with primary rodent cells and do not consider inter-cellular variations in AQP4 abundance and presentation. To address this, we have established and applied a robust live cell microscopy assay that captures the contribution of AQP4 in the osmotically driven (de-)quenching of the vital dye Calcein-AM with single-cell resolution. Using human astrocytoma cells, we found that performing measurements on cellular regions instead of whole fields of view yielded a more sensitive readout of the osmotic response, which correlated with AQP4 abundance. Stable co-expression of the two major AQP4 isoforms, but not of the individual isoforms, provoked a faster adaptation to osmotic changes, while siRNA-mediated knockdown of AQP4 had the opposite effect. Post-hoc correlation with the canonical membrane marker CD44 revealed that the speed of the osmotic response scaled with AQP4 membrane enrichment. Coating the substrate with laminin promoted AQP4 membrane enrichment, while cell confinement with fixed-size micropatterns further increased the speed of osmoregulation, underscoring the influence of extracellular factors. The osmotic response of primary fetal astrocytes and human iPSC-derived astrocyte models was comparable to AQP4-deficient astrocytoma cells, in line with their low AQP4 levels and indicative of their immature state. In conclusion, a correlative single-cell approach based on the quantification of Calcein-AM quenching capacity, AQP4 abundance and AQP4 membrane enrichment, allows resolving osmoregulation in a more sensitive manner and reveals heterogeneity between and within human astrocyte (-like) cultures, which could prove crucial for future screens aimed at identifying AQP4 modulators.

Cationic lipids are widely used for gene delivery. Here, we report the transient formation of nuclear actin filaments in mammalian cells transfected with commercially available transfection reagents regardless of the proteins transfected. Readily detectable with phalloidin, nuclear actin ranges from short filaments to a fully developed network. Nuclear actin filaments persist for hours, peak 20 h after transfection, and may be involved in DNA damage repair.

Barcoding viable cells combined with pooled sample staining is an effective technique that eliminates batch effects from serial cell staining and facilitates uninterrupted data acquisition. We describe three novel and isotopically pure selenium-containing compounds (SeMals) that are useful cellular labeling tools. The maleimide-functionalized selenophenes (SeMal, SeMal, and SeMal) covalently react with cellular sulfhydryl groups and uniquely label cell samples. The SeMal reagents label viable and paraformaldehyde-fixed peripheral blood mononuclear cells (PBMC), are well resolved by the mass cytometer, and have little spill into adjacent channels. They appear non-toxic to viable cells at working concentrations. We used SeMal reagents in combination with four isotopically pure tellurium maleimide reagents (TeMal, TeMal, TeMal, and TeMal) to label 21 individual PBMC samples with unique combinations of selenium and tellurium isotopes (seven donors with three replicates using a 7 isotope pick 2 combinatorial schema). The individually barcoded samples were pooled, stained with an antibody cocktail as a pool, and acquired on the mass cytometer as a single suspension. The single-cell data were de-barcoded into separate sample-specific files after data acquisition, enabling an uninterrupted instrument run. Each donor sample retained its unique phenotypic profile with excellent replicate reproducibility. Unlike current live cell barcoding methods, this approach does not require antibodies to surface markers, allowing for the labeling of all cells regardless of surface antigen expression. Additionally, since selenium and tellurium isotopes are not currently utilized in CyTOF antibody panels, this method expands barcoding options and frees up commonly used isotopes for more detailed cell profiling.

Although spectral flow cytometry has become a ubiquitous tool for cell analysis, the use of spectral cytometry on cell sorters requires additional considerations arising from the unique requirements of sorting workflows. Here, we show that care should be taken when ascertaining the purity of a sort on a spectral cell sorter, as the mismatch of buffers used for initial sample suspension and the buffers used for sort collection can affect the unmixing of the data, potentially giving rise to erroneous purity check results.

Clinical biomarker strategies increasingly integrate translational research to gain new insights into disease mechanisms or to define better biomarkers in clinical trials. High-dimensional flow cytometry (HDFCM) holds the promise to enhance the exploratory potential beyond traditional, targeted biomarker strategies. However, the increased complexity of HDFCM poses several challenges, which need to be addressed in order to fully leverage its potential and to align with current regulatory requirements in clinical flow cytometry. These challenges include among others extended timelines for assay development and validation, the necessity for extensive knowledge in HDFCM, and sophisticated data analysis strategies. However, no guidelines exist on how to manage such challenges in adopting clinical HDFCM. Our CYTO 2024 workshop "Potential and challenges of clinical high-dimensional flow cytometry" aimed to find consensus across the pharmaceutical industry and broader scientific community on the overall benefits and most urgent challenges of HDFCM in clinical trials. Here, we summarize the insights we gained from our workshop. While this report does not provide a blueprint, it is a first step in defining and summarizing the most pressing challenges in implementing HDFCM in clinical trials. Furthermore, we compile current efforts with the goal to overcome some of these challenges. As such we bring the scientific community and health authorities together to build solutions, which will accelerate and simplify the full adoption of HDFCM in clinical trials.

Single-cell sorting (index sorting) is a widely used method to isolate one cell at a time using fluorescence-activated cell sorting (FACS) for downstream applications such as single-cell sequencing or single-cell expansion. Despite widespread use, few assays are available to evaluate the proteomic features of the sorted single cell and further confirm the accuracy of single-cell sorting. With this caveat, we developed a novel assay to confirm the protein expression of sorted single cells by co-staining cells with the same marker using both antibody-derived tags (ADTs) and fluorescent antibodies. After single-cell sorting, we amplified the oligo of the ADT reagent as a surrogate signal for the protein expression using multiplex TaqMan™ qPCR on sorted cells. This assay is not only useful for confirming the identity of a sorted single cell but also an efficient method to profile proteomic features at the single-cell level. Finally, we applied this assay to characterize protein expression on whole cell lysate. Because of the sensitivity of the TaqMan™ qPCR, we can detect protein expression from a small number of cells. In summary, the ADT-based qPCR assay developed here can be utilized to confirm single-cell sorting accuracy and characterizing protein expression on both single cells and whole cell lysate.

Logic-gated engineered cells are an emerging therapeutic modality that can take advantage of molecular profiles to focus medical interventions on specific tissues in the body. However, the increased complexity of these engineered systems may pose a challenge for prediction and optimization of their behavior. Here we describe the design and testing of a flow cytometry-based screening system to rapidly select functional inhibitory receptors from a pooled library of candidate constructs. In proof-of-concept experiments, this approach identifies inhibitory receptors that can operate as NOT gates when paired with activating receptors. The method may be used to generate large datasets to train machine learning models to better predict and optimize the function of logic-gated cell therapeutics.

Acute myeloid leukemia (AML) is the most common form of acute leukemia diagnosed in adults. Despite advances in medical care, the treatment of AML still faces many challenges, such as treatment-related toxicities, that limit the use of high-intensity chemotherapy, especially in elderly patients. Currently, various immunotherapeutic approaches, that is, CAR-T cells, BiTEs, and immune checkpoint inhibitors, are being tested in clinical trials to prolong remission and improve the overall survival of AML patients. However, early reports show only limited benefits of these interventions and only in a subset of patients, showing the need for better patient stratification based on immunological markers. We have therefore developed and optimized a 30-color panel for evaluation of effector immune cell (NK cells, γδ T cells, NKT-like T cells, and classical T cells) infiltration into the bone marrow and analysis of their phenotype with regard to their differentiation, expression of inhibitory (PD-1, TIGIT, Tim3, NKG2A) and activating receptors (DNAM-1, NKG2D). We also evaluate the immune evasive phenotype of CD33 myeloid cells, CD34CD38, and CD34CD38 hematopoietic stem and progenitor cells by analyzing the expression of inhibitory ligands such as PD-L1, CD112, CD155, and CD200. Our panel can be a valuable tool for patient stratification in clinical trials and can also be used to broaden our understanding of check-point inhibitory networks in AML.

Imaging flow cytometry (IFCM) is a technique that can detect, size, and phenotype extracellular vesicles (EVs) at high throughput (thousands/minute) in complex biofluids without prior EV isolation. However, the generated signals are expressed in arbitrary units, which hinders data interpretation and comparison of measurement results between instruments and institutes. While fluorescence calibration can be readily achieved, calibration of side scatter (SSC) signals presents an ongoing challenge for IFCM. Here, we present an approach to relate the SSC signals to particle size for IFCM, and perform a comparability study between three different IFCMs using a plasma EV test sample (PEVTES). SSC signals for different sizes of polystyrene (PS) and hollow organosilica beads (HOBs) were acquired with a 405 nm 120 mW laser without a notch filter before detection. Mie theory was applied to relate scatter signals to particle size. Fluorescence calibration was accomplished with 2 μm phycoerythrin (PE) and allophycocyanin (APC) MESF beads. Size and fluorescence calibration was performed for three IFCMs in two laboratories. CD235a-PE and CD61-APC stained PEVTES were used as EV-containing samples. EV concentrations were compared between instruments within a size range of 100-1000 nm and a fluorescence intensity range of 3-10,000 MESF. 81 nm PS beads could be readily discerned from background based on their SSC signals. Fitting of the obtained PS bead SSC signals with Mie theory resulted in a coefficient of determination >0.99 between theory and data for all three IFCMs. 216 nm HOBs were detected with all instruments, and confirmed the sensitivity to detect EVs by SSC. The lower limit of detection regarding EV-size for this study was determined to be ~100 nm for all instruments. Size and fluorescence calibration of IFCM data increased cross-instrument data comparability with the coefficient of variation decreasing from 33% to 21%. Here we demonstrate - for the first time - scatter calibration of an IFCM using the 405 nm laser. The quality of the scatter-to-diameter relation and scatter sensitivity of the IFCMs are similar to the most sensitive commercially available flow cytometers. This development will support the reliability of EV research with IFCM by providing robust standardization and reproducibility, which are pre-requisites for understanding the biological significance of EVs.

Erythrophagocytosis is a process consisting of recognition, engulfment and digestion by phagocytes of antibody-coated or damaged erythrocytes. Understanding the dynamics that are behind erythrophagocytosis is fundamental to comprehend this cellular process under specific circumstances. Several techniques have been used to study phagocytosis. Among these, an interesting approach is the use of Imaging Flow Cytometry (IFC) to distinguish internalization and binding of cells or particles. However, this method requires laborious analysis. Here, we introduce a novel approach to analyze the phagocytosis process by combining Artificial Intelligence (AI) with IFC. Our study demonstrates that this approach is highly suitable to study erythrophagocytosis, categorizing internalized, bound and non-bound erythrocytes. Validation experiments showed that our pipeline performs with high accuracy and reproducibility.

We developed this whole blood immunophenotyping panel with the aim to monitor and quantify major lymphocyte subsets (CD4, CD8, CD4CD8 αβ T cells, γδ-T cells, B and NK cells) and monocytes in pigs. The panel involved the use of commercially available reagents, avoiding secondary antibody staining or in-house antibody conjugations, with the aim to make the assay accessible and reproducible across laboratories. The assay is accurate, robust and represents a useful tool for immune monitoring of swine in the pharmacology and toxicology fields, or to monitor the immune status in response to vaccination and diseases.

This panel was designed to characterize the immune cell landscape in the mouse tumor microenvironment as well as mouse lymphoid tissues (e.g., spleen). As an example, using the MC-38 mouse syngeneic tumor model, we demonstrated that we could measure the frequency and characterize the functional status of CD4 T cells, CD8 T cells, regulatory T cells, NK cells, B cells, macrophages, granulocytes, monocytes, and dendritic cells. This panel is especially useful for understanding the immune landscape in "cold" preclinical tumor models with very low immune cell infiltration and for investigating how therapeutic treatments may modulate the immune landscape.