TRBC1 in flow cytometry: Assay development, validation, and reporting considerations

The assessment of T-cell clonality by flow cytometry has long been suboptimal, relying on aberrant marker expression and/or intensity. The introduction of TRBC1 shows much promise for improving the diagnosis of T-cell neoplasms in the clinical flow laboratory. Most laboratories considering this marker already have existing panels designed for T-cell workups and will be determining how best to incorporate TRBC1. We present this comprehensive summary of TRBC1 and supplemental case examples to familiarize the flow cytometry community with its potential for routine application, provide examples of how to incorporate it into T-cell panels, and signal caution in interpreting the results in certain diagnostic scenarios where appropriate.

Current Status of Flow Cytometric Immunophenotyping of Hematolymphoid Neoplasms in Korea

Background

Flow cytometric immunophenotyping of hematolymphoid neoplasms (FCI-HLN) is essential for diagnosis, classification, and minimal residual disease (MRD) monitoring. FCI-HLN is typically performed using in-house protocols, raising the need for standardization. Therefore, we surveyed the current status of FCI-HLN in Korea to obtain fundamental data for quality improvement and standardization.

Methods

Eight university hospitals actively conducting FCI-HLN participated in our survey. We analyzed responses to a questionnaire that included inquiries regarding test items, reagent antibodies (RAs), fluorophores, sample amounts (SAs), reagent antibody amounts (RAAs), acquisition cell number (ACN), isotype control (IC) usage, positive/negative criteria, and reporting.

Results

Most hospitals used acute HLN, chronic HLN, plasma cell neoplasm (PCN), and MRD panels. The numbers of RAs were heterogeneous, with a maximum of 32, 26, 12, 14, and 10 antibodies used for acute HLN, chronic HLN, PCN, ALL-MRD, and multiple myeloma-MRD, respectively. The number of fluorophores ranged from 4 to 10. RAs, SAs, RAAs, and ACN were diverse. Most hospitals used a positive criterion of 20%, whereas one used 10% for acute and chronic HLN panels. Five hospitals used ICs for the negative criterion. Positive/negative assignments, percentages, and general opinions were commonly reported. In MRD reporting, the limit of detection and lower limit of quantification were included.

Conclusions

This is the first comprehensive study on the current status of FCI-HLN in Korea, confirming the high heterogeneity and complexity of FCI-HLN practices. Standardization of FCI-HLN is urgently needed. The findings provide a reference for establishing standard FCI-HLN guidelines.

A novel sorting method for the enrichment of early human spermatocytes from clinical biopsies

OBJECTIVE

To determine if early spermatocytes can be enriched from a human testis biopsy using fluorescence-activated cell sorting (FACS).

DESIGN

Potential surface markers for early spermatocytes were identified using bioinformatics analysis of single-cell RNA-sequenced human testis tissue. Testicular sperm extraction samples from three participants with normal spermatogenesis were digested into single-cell suspensions and cryopreserved. Two to four million cells were obtained from each and sorted by FACS as separate biologic replicates using antibodies for the identified surface markers. A portion from each biopsy remained unsorted to serve as controls. The sorted cells were then characterized for enrichment of early spermatocytes.

SETTING

A laboratory study.

PATIENTS

Three men with a diagnosis of obstructive azoospermia (age range, 30-40 years).

INTERVENTION

None.

MAIN OUTCOME MEASURES

Sorted cells were characterized for RNA expression of markers encompassing the stages of spermatogenesis. Sorting markers were validated by their reactivity on human testis formalin-fixed paraffin-embedded tissue.

RESULTS

Serine protease 50 (TSP50) and SWI5-dependent homologous recombination repair protein 1 were identified as potential surface proteins specific for early spermatocytes. After FACS sorting, the TSP50-sorted populations accounted for 1.6%-8.9% of total populations and exhibited the greatest average-fold increases in RNA expression for the premeiotic marker stimulated by retinoic acid (STRA8), by 23-fold. Immunohistochemistry showed the staining pattern for TSP50 to be strong in premeiotic undifferentiated embryonic cell transcription factor 1-/doublesex and Mab-3 related transcription factor 1-/STRA8+ spermatogonia as well as SYCP3+/protamine 2- spermatocytes.

CONCLUSION

This work shows that TSP50 can be used to enrich early STRA8-expressing spermatocytes from human testicular biopsies, providing a means for targeted single-cell RNA sequencing analysis and in vitro functional interrogation of germ cells during the onset of meiosis. This could enable investigation into details of the regulatory pathways underlying this critical stage of spermatogenesis, previously difficult to enrich from whole tissue samples.

The performance of a Fully Automated Urine Particle Analyzer, Sysmex UF-5000, in detecting fastidious bacteria in urine samples

Several types of fastidious bacteria can cause tract infections. We evaluated the performance of counting fastidious bacteria using a Fully Automated Urine Particle Analyzer UF-5000. The results showed that UF-5000 counts fastidious bacteria in urine without the need for culture using measurement principles based on flow cytometry.

Convolutional neuronal network for identifying single-cell-platelet-platelet-aggregates in human whole blood using imaging flow cytometry

Imaging flow cytometry is an attractive method to investigate individual cells by optical properties. However, imaging flow cytometry applications with clinical relevance are scarce so far. Platelet aggregation naturally occurs during blood coagulation to form a clot. However, aberrant platelet aggregation is associated with cardiovascular disease under steady-state conditions in the blood. Several types of so-called antiplatelet drugs are frequently described to reduce the risk of stroke or cardiovascular diseases. However, an efficient monitoring method is missing to identify the presence and frequency of platelet-platelet aggregates in whole blood on a single cell level. In this work, we employed imaging flow cytometry to identify fluorescently labeled platelets in whole blood with a conditional gating strategy. Images were post-processed and aligned. A convolutional neural network was designed to identify platelet-platelet aggregates of two, three, and more than three platelets, and results were validated against various data set properties. In addition, the neural network excluded erythrocyte-platelet aggregates from the results. Based on the results, a parameter for detecting platelet-platelet aggregates, the weighted platelet aggregation, was developed. If employed on a broad scale with proband and patient samples, our method could aid in building a future diagnostic marker for cardiovascular disease and monitoring parameters to optimize drug prescriptions in such patient groups.

Streamlined measurement of chimeric antigen receptor T-cell concentration, size, viability and two-color phenotyping during manufacturing

BACKGROUND AIMS

The successful development of CD19-targeted chimeric antigen receptor (CAR) T-cell therapies has led to an exponential increase in the number of patients recieving treatment and the advancement of novel CAR T products. Therefore, there is a strong need to develop streamlined platforms that allow rapid, cost-effective, and accurate measurement of the key characteristics of CAR T cells during manufacturing (i.e., cell number, cell size, viability, and basic phenotype).

METHODS

In this study, we compared the novel benchtop cell analyzer Moxi GO II (ORFLO Technologies), which enables simultaneous evaluation of all the aforementioned parameters, with current gold standards in the field: the Multisizer Coulter Counter (cell counter) and the BD LSRFortessa (flow cytometer).

RESULTS

Our results demonstrated that the Moxi GO II can accurately measure cell number and cell size (i.e., cell volume) while simultaneously assessing simple two-color flow cytometry parameters, such as CAR T-cell viability and CD4 or CAR expression.

CONCLUSIONS

These measurements are comparable with those of gold standard instruments, demonstrating that the Moxi GO II is a promising platform for quickly monitoring CAR T-cell growth and phenotype in research-grade and clinical samples.

Clustering of spermatozoa examined through flow cytometry provides more information than the conventional assessment: a resilience to osmotic stress example

Context Conventional sperm quality tests may not be sufficient to predict the fertilising ability of a given ejaculate; thus, rapid, reliable and sensitive tests are necessary to measure sperm function. Aims This study sought to address whether a cluster analysis approach based on flow cytometry variables could provide more information about sperm function. Methods Spermatozoa were exposed to either isotonic (300mOsm/kg) or hypotonic (180mOsm/kg) media for 5 and 20min, and were then stained with SYBR14 and propidium iodide (PI). Based on flow cytometry dot plots, spermatozoa were classified as either viable (SYBR14+ /PI- ) or with different degrees of plasma membrane alteration (SYBR14+ /PI+ and SYBR14- /PI+ ). Moreover, individual values of electronic volume (EV), side scattering (SS), green (FL1) and red (FL3) fluorescence were recorded and used to classify sperm cells through cluster analysis. Two strategies of this approach were run. The first one was based on EV and the FL3/FL1 quotient, and the second was based on EV, SS and the FL3/FL1 quotient. Key results The two strategies led to the identification of more than three sperm populations. In the first strategy, EV did not differ between membrane-intact and membrane-damaged sperm, but it was significantly (P P P Conclusions Cluster analysis based on flow cytometry variables provides more information about sperm function than conventional assessment does. Implications Combining flow cytometry with cluster analysis is a more robust approach for sperm evaluation.

Diagnosis of rare entity CD138 negative plasma cell multiple myeloma: the synergy between laboratory and clinician makes the difference

Plasma cell multiple myeloma (MM) is a multiform clinical entity characterized by different laboratory hallmarks. This case shows a rare entity of plasma cell myeloma: the entire plasma cell population lack the CD138 expression. In this case, a careful analysis of laboratory finding, particular flow cytometry gating strategies and the use of other ancillary laboratory tests, guide the clinicians to correct diagnosis. The correct evaluation of pre-analytical phase and the correct gating strategy are the necessary conditions to produce robust and solid flow cytometric results. The diagnostic implications of CD138-negative plasma cell are strictly linked to stem cell-like clonogenic features, such as possible more aggressive clinical behaviour and increasing probability of chemotherapy resistance. At this time, clinical laboratory remains the main reference point to MM diagnosis.

The challenge of standardizing CAR-T cell monitoring: A comparison of two flow-cytometry methods and correlation with qPCR technique

Chimeric antigen receptor (CAR) T-cell therapy is a breakthrough in hematologic malignancies, such as acute B lymphoblastic leukemia (B-ALL). Monitoring this treatment is recommended, although standardized protocols have not been developed yet. This work compares two flow cytometry monitoring strategies and correlates this technique with qPCR method. CAR-T cells were detected by two different flow-cytometry protocols (A and B) in nine blood samples from one healthy donor and five B-ALL patients treated with Tisagenlecleucel (Kymriah®, USA). HIV-1 viral load allowed CAR detection by qPCR, using samples from seven healthy donors and nine B-ALL patients. CAR detection by protocol A and B did not yield statistically significant differences (1.9% vs. 11.8% CD3 + CAR+, p = 0.07). However, protocol B showed a better discrimination of the CD3 + CAR+ population. A strong correlation was observed between protocol B and qPCR (r = 0.7, p < 0.0001). CD3 + CAR+ cells were detected by flow cytometry only when HIV-1 viral load was above 104 copies/mL. In conclusion, protocol B was the most specific flow-cytometry procedure for the identification of CAR-T cells and showed a high correlation with qPCR. Further efforts are needed to achieve a standardized monitoring approach.

Combinatorial antibody titrations for high-parameter flow cytometry

The objective of titrating fluorochrome-labeled antibodies is to identify the optimal concentration for a given marker-fluorochrome pair that results in the best possible separation between the positive and negative cell populations, while minimizing the background within the negative population. Best practices in flow cytometry dictate that each new lot of antibody should be titrated on the sample of interest. However, many researchers routinely use large (30+) color panels due to recent technical advancements in fluorescence-based cytometry instrumentation which quickly leads to an unmanageable number of individual titrations. In this technical note, we provide evidence that antibodies can be effectively titrated in groups rather than individually, resulting in considerable time and cost savings. This approach streamlines the process, without compromising data quality, thereby enhancing the efficiency of setting up high-parameter cytometry experiments.

Microwave Flow Cytometric Detection and Differentiation of Escherichia coli

Label-free measurement and analysis of single bacterial cells are essential for food safety monitoring and microbial disease diagnosis. We report a microwave flow cytometric sensor with a microstrip sensing device with reduced channel height for bacterial cell measurement. Escherichia coli B and Escherichia coli K-12 were measured with the sensor at frequencies between 500 MHz and 8 GHz. The results show microwave properties of E. coli cells are frequency-dependent. A LightGBM model was developed to classify cell types at a high accuracy of 0.96 at 1 GHz. Thus, the sensor provides a promising label-free method to rapidly detect and differentiate bacterial cells. Nevertheless, the method needs to be further developed by comprehensively measuring different types of cells and demonstrating accurate cell classification with improved machine-learning techniques.

The Evolving Landscape of Flowcytometric Minimal Residual Disease Monitoring in B-Cell Precursor Acute Lymphoblastic Leukemia

Detection of minimal residual disease (MRD) is a major independent prognostic marker in the clinical management of pediatric and adult B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL), and risk stratification nowadays heavily relies on MRD diagnostics. MRD can be detected using flow cytometry based on aberrant expression of markers (antigens) during malignant B-cell maturation. Recent advances highlight the significance of novel markers (e.g., CD58, CD81, CD304, CD73, CD66c, and CD123), improving MRD identification. Second and next-generation flow cytometry, such as the EuroFlow consortium's eight-color protocol, can achieve sensitivities down to 10-5 (comparable with the PCR-based method) if sufficient cells are acquired. The introduction of targeted therapies (especially those targeting CD19, such as blinatumomab or CAR-T19) introduces several challenges for flow cytometric MRD analysis, such as the occurrence of CD19-negative relapses. Therefore, innovative flow cytometry panels, including alternative B-cell markers (e.g., CD22 and CD24), have been designed. (Semi-)automated MRD assessment, employing machine learning algorithms and clustering tools, shows promise but does not yet allow robust and sensitive automated analysis of MRD. Future directions involve integrating artificial intelligence, further automation, and exploring multicolor spectral flow cytometry to standardize MRD assessment and enhance diagnostic and prognostic robustness of MRD diagnostics in BCP-ALL.

Comprehensive analysis of human monocyte subsets using full-spectrum flow cytometry and hierarchical marker clustering

Introduction

Exploring monocytes' roles within the tumor microenvironment is crucial for crafting targeted cancer treatments.

Methods

This study unveils a novel methodology utilizing four 20-color flow cytometry panels for comprehensive peripheral immune system phenotyping, specifically targeting classical, intermediate, and non-classical monocyte subsets.

Results

By applying advanced dimensionality reduction techniques like t-distributed stochastic neighbor embedding (tSNE) and FlowSom analysis, we performed an extensive profiling of monocytes, assessing 50 unique cell surface markers related to a wide range of immunological functions, including activation, differentiation, and immune checkpoint regulation.

Discussion

This in-depth approach significantly refines the identification of monocyte subsets, directly supporting the development of personalized immunotherapies and enhancing diagnostic precision. Our pioneering panel for monocyte phenotyping marks a substantial leap in understanding monocyte biology, with profound implications for the accuracy of disease diagnostics and the success of checkpoint-inhibitor therapies. Key findings include revealing distinct marker expression patterns linked to tumor progression and providing new avenues for targeted therapeutic interventions.

Interlaboratory comparison of high-throughput protein biomarker assay quantifications for radiation exposure classification

In the event of a widespread radiological incident, thousands of individuals will require rapid assessment of exposure using validated biodosimetry assays to inform clinical triage. In this scenario, multiple biodosimetry laboratories may be necessary for large-volume sample processing. To meet this need, we have developed a high-throughput assay for the rapid measurement of intracellular protein biomarkers in human peripheral blood samples using an Imaging Flow Cytometry (IFC) platform. The objective of this work was to harmonize and validate the reproducibility of our blood biomarker assay for radiation exposure across three IFC instruments, two located at Columbia University (CU) and the third at Health Canada. The Center for Radiological Research (CRR) at CU served as the central laboratory and reference instrument, where samples were prepared in triplicate, labeled with two radiation responsive leukocyte biomarkers (BAX and phosphor-p53 (Ser37)), and distributed for simultaneous interrogation by each IFC. Initial tests showed that significantly different baseline biomarker measurements were generated on each instrument when using the same acquisition settings, suggesting that harmonization of signal intensities is necessary. Subsequent tests harmonized biomarker measurements after irradiation by modulating laser intensity using two reference materials: unstained samples and standardized rainbow beads. Both methods generated measurements on each instrument without significant differences between the new and references instruments, allowing for the use of one master template to quantify biomarker expression across multiple instruments. Deming regression analyses of 0-5 Gy dose-response curves showed overall good correlation of BAX and p53 values across new and reference instruments. While Bland-Altman analyses indicated low to moderate instrument biases, ROC Curve analyses ultimately show successful discrimination between exposed and unexposed samples on each instrument (AUC values > 0.85).

Basophil activation in insect venom allergy: comparison of an established test using liquid reagents with a test using 5-color tubes with dried antibody reagents

BACKGROUND

Flow cytometry-based basophil activation tests (BAT) have been performed with various modifications, differing in the use of distinct identification and activation markers. Established tests use liquid reagents while a new development involves the use of tubes with dried antibody reagents. The aim of this pilot study was to compare these two techniques in patients with insect venom allergy.

METHODS

Seventeen patients with an insect venom allergy were included in the study. The established "BAT 1" utilizes conventional antibody solutions of anti-CCR3 for basophil identification and anti-CD63 to assess basophil activation, whereas "BAT 2" uses dried anti-CD45, anti-CD3, anti-CRTH2, anti-203c and anti-CD63 for identification and activation measurement of basophils. Negative and positive controls as well as incubations with honey bee venom and yellow jacket venom at three concentrations were performed.

RESULTS

Seven patients had to be excluded due to low basophil counts, high values in negative controls or negative positive controls. For the remaining 10 patients the overall mean (± SD) difference in activated basophils between the two tests was 0.2 (± 12.2) %P. In a Bland-Altman plot, the limit of agreement (LoA) ranged from 24.0 to -23.7. In the qualitative evaluation (value below/above cut-off) Cohen's kappa was 0.77 indicating substantial agreement. BAT 2 took longer to perform than BAT 1 and was more expensive.

CONCLUSION

The BAT 2 technique represents an interesting innovation, however, it was found to be less suitable compared to an established BAT for the routine diagnosis of insect venom allergies.

Accessing Early Differentiation of Virus-Specific Follicular Helper CD4+ T Cell in Acute LCMV-Infected Mice

Follicular Helper T (TFH) cells are perceived as an independent CD4+ T cell lineage that assists cognate B cells in producing high-affinity antibodies, thus establishing long-term humoral immunity. During acute viral infection, the fate commitment of virus-specific TFH cells is determined in the early infection phase, and investigations of the early-differentiated TFH cells are crucial in understanding T cell-dependent humoral immunity and optimizing vaccine design. In the study, using a mouse model of acute lymphocytic choriomeningitis virus (LCMV) infection and the TCR-transgenic SMARTA (SM) mouse with CD4+ T cells specifically recognizing LCMV glycoprotein epitope I-AbGP66-77, we described procedures to access the early fate commitment of virus-specific TFH cells based on flow cytometry stainings. Furthermore, by exploiting retroviral transduction of SM CD4+ T cells, methods to manipulate gene expression in early-differentiated virus-specific TFH cells are also provided. Hence, these methods will help in studies exploring the mechanism(s) underlying the early commitment of virus-specific TFH cells.

A Multi-Faceted Binding Assessment of Aptamers Targeting the SARS-CoV-2 Spike Protein

The COVID-19 pandemic has underscored the critical need for the advancement of diagnostic and therapeutic platforms. These platforms rely on the rapid development of molecular binders that should facilitate surveillance and swift intervention against viral infections. In this study, we have evaluated by three independent research groups the binding characteristics of various published RNA and DNA aptamers targeting the spike protein of the SARS-CoV-2 virus. For this comparative analysis, we have employed different techniques such as biolayer interferometry (BLI), enzyme-linked oligonucleotide assay (ELONA), and flow cytometry. Our data show discrepancies in the reported specificity and affinity among several of the published aptamers and underline the importance of standardized methods, the impact of biophysical techniques, and the controls used for aptamer characterization. We expect our results to contribute to the selection and application of suitable aptamers for the detection of SARS-CoV-2.

Characterization of Human B Cell Hematological Malignancies Using Protein-Based Approaches

The maturation of B cells is a complex, multi-step process. During B cell differentiation, errors can occur, leading to the emergence of aberrant versions of B cells that, finally, constitute a malignant tumor. These B cell malignancies are classified into three main groups: leukemias, myelomas, and lymphomas, the latter being the most heterogeneous type. Since their discovery, multiple biological studies have been performed to characterize these diseases, aiming to define their specific features and determine potential biomarkers for diagnosis, stratification, and prognosis. The rise of advanced -omics approaches has significantly contributed to this end. Notably, proteomics strategies appear as promising tools to comprehensively profile the final molecular effector of these cells. In this narrative review, we first introduce the main B cell malignancies together with the most relevant proteomics approaches. Then, we describe the core studies conducted in the field and their main findings and, finally, we evaluate the advantages and drawbacks of flow cytometry, mass cytometry, and mass spectrometry for the profiling of human B cell disorders.

Comparative analysis of feature-based ML and CNN for binucleated erythroblast quantification in myelodysplastic syndrome patients using imaging flow cytometry data

Myelodysplastic syndrome is primarily characterized by dysplasia in the bone marrow (BM), presenting a challenge in consistent morphology interpretation. Accurate diagnosis through traditional slide-based analysis is difficult, necessitating a standardized objective technique. Over the past two decades, imaging flow cytometry (IFC) has proven effective in combining image-based morphometric analyses with high-parameter phenotyping. We have previously demonstrated the effectiveness of combining IFC with a feature-based machine learning algorithm to accurately identify and quantify rare binucleated erythroblasts (BNEs) in dyserythropoietic BM cells. However, a feature-based workflow poses challenges requiring software-specific expertise. Here we employ a Convolutional Neural Network (CNN) algorithm for BNE identification and differentiation from doublets and cells with irregular nuclear morphology in IFC data. We demonstrate that this simplified AI workflow, coupled with a powerful CNN algorithm, achieves comparable BNE quantification accuracy to manual and feature-based analysis with substantial time savings, eliminating workflow complexity. This streamlined approach holds significant clinical value, enhancing IFC accessibility for routine diagnostic purposes.

Comparison of techniques for corneal epithelium cell culture for the collection of conditioned medium

PURPOSES

To determine the best protocol in obtaining the higher yield of conditioned culture medium to be used for the bone marrow mesenchymal stem cell differentiation into corneal epithelial cells, five techniques for the primary culture of human corneal epithelial cells were evaluated.

METHODS

The studied culture techniques of corneal epithelial cells were: explants in culture flasks with and without hydrophilic surface treatment, on amniotic membrane, with enzymatic digestion, and by corneal scraping. The conditioned culture medium collected from these cultures was used to differentiate human bone marrow mesenchymal stem cells into corneal epithelial cells, which were characterized using flow cytometry with pan-cytokeratin and the corneal-specific markers, cytokeratin 3 and cytokeratin 12.

RESULTS

The culture technique using flasks with hydrophilic surface treatment resulted in the highest yield of conditioned culture medium. Flasks without surface treatment resulted to a very low success rate. Enzymatic digestion and corneal scraping showed contamination with corneal fibroblasts. The culture on amniotic membranes only allowed the collection of culture medium during the 1st cell confluence. The effectiveness of cell differentiation was confirmed by cytometry analysis using the collected conditioned culture medium, as demonstrated by the expressions of cytokeratin 3 (95.3%), cytokeratin 12 (93.4%), and pan-cytokeratin (95.3%).

CONCLUSION

The culture of corneal epithelial cell explants in flasks with hydrophilic surface treatment is the best technique for collecting a higher yield of conditioned culture medium to be used to differentiate mesenchymal stem cells.

Surrogate gradient learning in spiking networks trained on event-based cytometry dataset

Spiking neural networks (SNNs) are bio-inspired neural networks that - to an extent - mimic the workings of our brains. In a similar fashion, event-based vision sensors try to replicate a biological eye as closely as possible. In this work, we integrate both technologies for the purpose of classifying micro-particles in the context of label-free flow cytometry. We follow up on our previous work in which we used simple logistic regression with binary labels. Although this model was able to achieve an accuracy of over 98%, our goal is to utilize the system for a wider variety of cells, some of which may have less noticeable morphological variations. Therefore, a more advanced machine learning model like the SNNs discussed here would be required. This comes with the challenge of training such networks, since they typically suffer from vanishing gradients. We effectively apply the surrogate gradient method to overcome this issue achieving over 99% classification accuracy on test data for a four-class problem. Finally, rather than treating the neural network as a black box, we explore the dynamics inside the network and make use of that to enhance its accuracy and sparsity.

Flow Cytometry-Based Assay to Detect Alpha Galactosidase Enzymatic Activity at the Cellular Level

BACKGROUND

Fabry disease is a progressive, X chromosome-linked lysosomal storage disorder with multiple organ dysfunction. Due to the absence or reduced activity of alpha-galactosidase A (AGAL), glycosphingolipids, primarily globotriaosyl-ceramide (Gb3), concentrate in cells. In heterozygous women, symptomatology is heterogenous and currently routinely used fluorometry-based assays measuring mean activity mostly fail to uncover AGAL dysfunction. The aim was the development of a flow cytometry assay to measure AGAL activity in individual cells.

METHODS

Conventional and multispectral imaging flow cytometry was used to detect AGAL activity. Specificity was validated using the GLA knockout (KO) Jurkat cell line and AGAL inhibitor 1-deoxygalactonojirimycin. The GLA KO cell line was generated via CRISPR-Cas9-based transfection, validated with exome sequencing, gene expression and substrate accumulation.

RESULTS

Flow cytometric detection of specific AGAL activity is feasible with fluorescently labelled Gb3. In the case of Jurkat cells, a substrate concentration of 2.83 nmol/mL and 6 h of incubation are required. Quenching of the aspecific exofacial binding of Gb3 with 20% trypan blue solution is necessary for the specific detection of lysosomal substrate accumulation.

CONCLUSION

A flow cytometry-based assay was developed for the quantitative detection of AGAL activity at the single-cell level, which may contribute to the diagnosis of Fabry patients.

Unravelling B cell heterogeneity: insights into flow cytometry-gated B cells from single-cell multi-omics data

Introduction

B cells play a pivotal role in adaptive immunity which has been extensively characterised primarily via flow cytometry-based gating strategies. This study addresses the discrepancies between flow cytometry-defined B cell subsets and their high-confidence molecular signatures using single-cell multi-omics approaches.

Methods

By analysing multi-omics single-cell data from healthy individuals and patients across diseases, we characterised the level and nature of cellular contamination within standard flow cytometric-based gating, resolved some of the ambiguities in the literature surrounding unconventional B cell subsets, and demonstrated the variable effects of flow cytometric-based gating cellular heterogeneity across diseases.

Results

We showed that flow cytometric-defined B cell populations are heterogenous, and the composition varies significantly between disease states thus affecting the implications of functional studies performed on these populations. Importantly, this paper draws caution on findings about B cell selection and function of flow cytometric-sorted populations, and their roles in disease. As a solution, we developed a simple tool to identify additional markers that can be used to increase the purity of flow-cytometric gated immune cell populations based on multi-omics data (AlliGateR). Here, we demonstrate that additional non-linear CD20, CD21 and CD24 gating can increase the purity of both naïve and memory populations.

Discussion

These findings underscore the need to reconsider B cell subset definitions within the literature and propose leveraging single-cell multi-omics data for refined characterisation. We show that single-cell multi-omics technologies represent a powerful tool to bridge the gap between surface marker-based annotations and the intricate molecular characteristics of B cell subsets.

Classification of Neural Stem Cell Activation State In Vitro using Autofluorescence

Neural stem cells (NSCs) divide and produce newborn neurons in the adult brain through a process called adult neurogenesis. Adult NSCs are primarily quiescent, a reversible cell state where they have exited the cell cycle (G0) yet remain responsive to the environment. In the first step of adult neurogenesis, quiescent NSCs (qNSCs) receive a signal and activate, exiting quiescence and re-entering the cell cycle. Thus, understanding the regulators of NSC quiescence and quiescence exit is critical for future strategies targeting adult neurogenesis. However, our understanding of NSC quiescence is limited by technical constraints in identifying quiescent NSCs (qNSCs) and activated NSCs (aNSCs). This protocol describes a new approach to identify and enrich qNSCs and aNSCs generated in in vitro cultures by imaging NSC autofluorescence. First, this protocol describes how to use a confocal microscope to identify autofluorescent markers of qNSCs and aNSCs to classify NSC activation state using autofluorescence intensity. Second, this protocol describes how to use a fluorescent activated cell sorter (FACS) to classify NSC activation state and enrich samples for qNSCs or aNSCs using autofluorescence intensity. Third, this protocol describes how to use a multiphoton microscope to perform fluorescence lifetime imaging (FLIM) at single-cell resolution, classify NSC activation state, and track the dynamics of quiescent exit using both autofluorescence intensities and fluorescence lifetimes. Thus, this protocol provides a live-cell, label-free, single-cell resolution toolkit for studying NSC quiescence and quiescence exit.