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.

Murine Left Pulmonary Hilar Clamp Model of Lung Ischemia Reperfusion Injury

Ischemia reperfusion injury (IRI) during lung transplantation is a major risk factor for post-transplant complications, including primary graft dysfunction, acute and chronic rejection, and mortality. Efforts to study the underpinnings of IRI led to the development of a reliable and reproducible mouse model of left lung hilar clamping. This model involves a surgical procedure performed in an anesthetized and intubated mouse. A left thoracotomy is performed, followed by careful lung mobilization and dissection of the left pulmonary hilum. The hilar clamp involves reversible suture ligation of the pulmonary hilum with a slipknot, which stops the arterial inflow, venous outflow, and airflow through the left mainstem bronchus. Reperfusion is initiated by careful removal of the suture. Our laboratory uses 30 min of ischemia and 1 h of reperfusion for the experimental model in the current investigations. However, these time periods can be modified depending on the specific experimental question. Immediately prior to sacrifice, arterial blood gas can be obtained from the left ventricle after a 4 min period of right hilar clamping to ensure that the PaO2 values obtained are attributed to the injured left lung alone. We also describe a method to measure cell extravasation with flow cytometry, which involves intravenous injection of a fluorochrome-labeled antibody specific for the cell(s) to be studied prior to sacrifice. The left lung can then be harvested for flow cytometry, frozen or fixed, paraffin-embedded immunohistochemistry, and quantitative polymerase chain reaction. This hilar clamp technique allows for detailed study of the cellular and molecular mechanisms underlying IRI. Representative results reveal decreased left lung oxygenation and histologic evidence of lung injury following hilar clamping. This technique can be readily learned and reproduced by personnel with and without microsurgical experience, leading to reliable and consistent results and serving as a widely adoptable model for studying lung IRI.

Intraepithelial Lymphogram in the Diagnosis of Celiac Disease in Adult Patients: A Validation Cohort

BACKGROUND

Celiac disease is a gluten-related pathology, highly prevalent and heterogeneous in its clinical presentation, which leads to delays in diagnosis and misdiagnosis. The analysis of duodenal intraepithelial lymphocytes (IELs) by flow cytometry (lymphogram) is emerging as a discriminative tool in the diagnosis of various forms of celiac disease (CD).

AIMS

The aim of this study was to validate IEL lymphogram performance in the largest adult series to our knowledge, in support of its use as a diagnostic tool and as a biomarker of the dynamic celiac process.

METHODS

This was a retrospective study including 768 adult patients (217 with active CD, 195 on a gluten-free diet, 15 potential CD patients, and 411 non-celiac controls). The IEL subset cut-off values were established to calculate the diagnostic accuracy of the lymphogram.

RESULTS

A complete celiac lymphogram profile (≥14% increase in T cell receptor [TCR]γδ IELs and simultaneous ≤4% decrease in surface-negative CD3 [sCD3-] IELs) was strongly associated with active and potential forms in over 80% of the confirmed patients with CD, whereas the remaining patients with CD had partial lymphogram profiles (≥14% increase in TCRγδ or ≤4% decrease in sCD3- IELs), with lower diagnostic certainty. None of these patients had a non-celiac lymphogram. Quantifying the TCRγδ versus sCD3- imbalance as a ratio (≥5) is a discriminative index to discard or suspect CD at diagnosis.

CONCLUSIONS

We have validated the IEL lymphogram's diagnostic efficiency (79% sensitivity, 98% specificity), with an LR+ accuracy of 36.2. As expected, the increase in TCRγδ IELs is a reliable marker for celiac enteropathy, while changes in sCD3- IEL levels throughout the dynamic CD process are useful biomarkers of mucosal lesions.

Molecular cytometry for comprehensive immune profiling

Molecular cytometry refers to a group of high-parameter technologies for single-cell analysis that share the following traits: (1) combined (multimodal) measurement of protein and transcripts, (2) medium throughput (10-100K cells), and (3) the use of oligonucleotide-tagged antibodies to detect protein expression. The platform can measure over 100 proteins and either hundreds of targeted genes or the whole transcriptome, on a cell-by-cell basis. It is currently one of the most powerful technologies available for immune monitoring. Here, we describe the technology platform (which includes CITE-Seq, REAP-Seq, and AbSeq), provide guidance for its optimization, and discuss advantages and limitations. Finally, we provide some vignettes from studies that demonstrate the application and potential insight that can be gained from molecular cytometry studies.

Single-cell multi-parametric characterization of microbiota by flow cytometry

It has become evident, that the microbes colonizing the human body have a great impact on health and disease. Investigations of microbiota currently primarily rely on culturomics, high-throughput sequencing and metaproteomics which have considerably advanced our knowledge regarding the role of the microbiota in our environment and for our health. While single-cell phenotyping of immune cells and other somatic cells by flow cytometry has become widely used, the detailed analysis of bacterial cells such as the human microbiota on the single-cell level, is lagging behind. Here, we outline a protocol for the single-cell characterization of bacterial cells from complex microbiota samples, such as stool, by multi-parametric flow cytometry. Our protocol describes the isotype-specific detection of host-antibody coating of intestinal bacteria ex vivo, which together with quantitative DNA staining and light scatter detection comprise an individual's microbiota fingerprint. Cryoconservation and appropriate staining controls ensure reliable, reproducible data generation and analysis. We have automated the analysis of the multi-dimensional data using a segmentation approach by self-organizing map (SOM) algorithm for downstream comparative analyses. Our protocol can be adapted to integrate further phenotypic markers and uses the power of analytical cytometry for the characterization of bacteria on the single-cell level.

Deep learning assists in acute leukemia detection and cell classification via flow cytometry using the acute leukemia orientation tube

This study aimed to evaluate the sensitivity of AI in screening acute leukemia and its capability to classify either physiological or pathological cells. Utilizing an acute leukemia orientation tube (ALOT), one of the protocols of Euroflow, flow cytometry efficiently identifies various forms of acute leukemia. However, the analysis of flow cytometry can be time-consuming work. This retrospective study included 241 patients who underwent flow cytometry examination using ALOT between 2017 and 2022. The collected flow cytometry data were used to train an artificial intelligence using deep learning. The trained AI demonstrated a 94.6% sensitivity in detecting acute myeloid leukemia (AML) patients and a 98.2% sensitivity for B-lymphoblastic leukemia (B-ALL) patients. The sensitivities of physiological cells were at least 80%, with variable performance for pathological cells. In conclusion, the AI, trained with ResNet-50 and EverFlow, shows promising results in identifying patients with AML and B-ALL, as well as classifying physiological cells.

Spectral flow cytometry: Fundamentals and future impact

Spectral flow cytometry has emerged as a significant player in the cytometry marketplace, with the potential for rapid growth. Despite a slow start, the technology has made significant strides in advancing various areas of single-cell analysis utilized by the scientific community. The integration of spectral cytometry into clinical laboratories and diagnostic processes is currently underway and is expected to garner a significant level of widespread acceptance in the near future. However, incorporating a new methodological approach into existing research programs can lead to misunderstandings or even misuse. This chapter offers an introductory yet comprehensive explanation of the scientific principles that form the foundation of spectral cytometry. Specifically, it delves into the unmixing processes that are utilized for data analysis. This overview is designed for those who are new to the field and seeking an informative guide to this exciting emerging technology.

Development of multiplexed flow cytometry-based red blood cell antibody screen and identification assays

BACKGROUND AND OBJECTIVES

The purpose of this study was to develop a high-throughput method of performing red blood cell antibody screens and identification by utilizing flow cytometry and intracellular dyes to allow a multiplexed assay where three-cell screens can be performed in a single test well and 11-cell panels in three test wells.

MATERIALS AND METHODS

Reagent red blood cells were labelled using Violet Proliferation Dye 450 (V450) and Oregon Green fluorescent dyes, which bind intracellular proteins to allow up to four cells to be interrogated in a single test well. Sixteen 3-cell screen panels and ten 11-cell identification panels were tested using sera with known antibody specificity. Antibody binding was detected using secondary anti-immunoglobulin G and anti-immunoglobulin M fluorescently labelled antibodies.

RESULTS

Intracellular dyes allowed clear separation of the different screen and identification panel test cells. Three distinct populations of V450+, Oregon Green+ and negative for both stains were demonstrated in the screening panel and an additional double positive for V450 and Oregon Green was utilized to include a fourth cell in the identification panel testing to increase throughput. A total of 158 screen or identification panel RBC/serum combinations were tested against different known antibodies, and expected results were obtained with 100% concordance.

CONCLUSION

This study demonstrates the successful development of a high-throughput multiplexed flow cytometry-based red cell antibody screen and identification panel assays. This method could be implemented in clinical laboratories to complement existing antibody detection methods. The multiplexing enabled via intracellular staining could be utilized to further augment other flow cytometry-based transfusion assays.

FLAER as a standalone reagent for paroxysmal nocturnal hemoglobinuria: Do we need to reconsider the guidelines for testing?

INTRODUCTION

Flow cytometry-based paroxysmal nocturnal hemoglobinuria (PNH) testing involves utilization of monoclonal antibodies against GPI-linked proteins and FLAER. The ability of FLAER to bind to a wide variety of GPI-linked structures and to be utilized across different leukocyte subsets is remarkable. We hypothesize that FLAER as a standalone reagent may be equally effective for detecting PNH clones. The present study intends to compare the results of a FLAER alone-based strategy to the recommended FLAER+GPI-linked protein-based approach for applicability in clinical settings.

METHODS

EDTA-anticoagulated blood samples from patients for PNH workup were tested for PNH by multiparametric flow cytometry. A conventional panel comprising gating markers (CD45 for WBC, CD15 for granulocytes, and CD64 for monocytes) and a combination of FLAER and GPI-linked markers, such as CD24 and CD14, henceforth referred to as the "routine panel," was employed. Second, a "FLAER-only panel" comprising the gating markers and FLAER alone (excluding the GPI-linked markers CD24 and CD14) was set up. The samples were processed using the lyse-wash-stain-wash technique, and events were acquired on BC Navios Ex flow cytometer (Beckman Coulter, Inc., USA) and analyzed on Kaluza Software 2.1. The presence of a PNH clone was reported at a value of ≥0.01%.

RESULTS

A total of 209 patients were tested. Both panels found a PNH clone in 20.1% of patients (n = 42/209) with a 100% concordance rate. The PNH clone range for granulocytes was 0.01%-89.68%, and for monocyte was 0.04%-96.09% in the routine panel. The range in the FLAER-only panel for granulocytes was 0.01%-89.61%, and for monocytes, it was 0.01%-96.05%. Pearson correlation statistics revealed a significant correlation between the size of the PNH clone of granulocytes and monocytes among the two panels tested (granulocytes r = 0.9999, p < 0.0001, 95% CI = 0.9999 to 1.000; monocytes r = 0.9974, p < 0.0001, 95% CI = 0.9966-0.9980).

CONCLUSION

Based on our results, FLAER as a standalone marker is specific and sensitive for identifying PNH clones in granulocytes and monocytes, even for high-sensitivity PNH assay. The proposed "FLAER-only panel" panel is efficient and cost-effective for highly sensitive PNH testing in two different cell lineages, especially in resource-limited clinical settings.

True volumetric counting of CD34+ cells using flow cytometry

While the single-platform flow cytometric CD34+ cell counting method is the preferred choice to predict the yield of mobilized peripheral blood stem cells, most flow cytometers lack the ability of hematology counter analyzers to perform volumetric counting. However, one of the problems using reference microbeads is the vanishing counting bead phenomenon. This phenomenon results in a drop in microbeads concentration and reduces the total and relative number of beads in calibration procedures. In the last years, flow cytometers including a volumetric system to quantify cells have been developed and may represent a promising alternative to enumerate CD34+ cells avoiding the use of beads. In this study we have used a direct true volumetric counting of CD34+ cells under continuous flow pump to overcome potential drawbacks with impact in rare cell analysis. To confirm this hypothesis, we have compared the results of CD34+ cell enumeration using non-volumetric vs. volumetric systems with FC500 (Beckman Coulter) and Attune NxT (ThermoFisher) flow cytometers, respectively, in mobilized peripheral blood samples. No statistically significant differences were observed between measurements of CD34+ cells using beads, when the FC500 and Attune NxT absolute counting values were compared, or when CD34+ counts were compared on the Attune NxT, either using or not using beads. Linear regressions to study the relationship between volumetric and non-volumetric CD34+ counts confirmed the accuracy of each method. Bland-Altman test showed agreement between both methods. Our data showed that CD34+ cell enumeration using a volumetric system is comparable with current counting systems. This method represents an alternative with the advantage of the simplification of sample preparation and the reduction of the analysis subjectivity.

Comparative assessment of cytometry by time-of-flight and full spectral flow cytometry based on a 33-color antibody panel

Mass cytometry and full spectrum flow cytometry have recently emerged as new promising single cell proteomic analysis tools that can be exploited to decipher the extensive diversity of immune cell repertoires and their implication in human diseases. In this study, we evaluated the performance of mass cytometry against full spectrum flow cytometry using an identical 33-color antibody panel on four healthy individuals. Our data revealed an overall high concordance in the quantification of major immune cell populations between the two platforms using a semi-automated clustering approach. We further showed a strong correlation of cluster assignment when comparing manual and automated clustering. Both comparisons revealed minor disagreements in the quantification and assignment of rare cell subpopulations. Our study showed that both single cell proteomic technologies generate highly overlapping results and substantiate that the choice of technology is not a primary factor for successful biological assessment of cell profiles but must be considered in a broader design framework of clinical studies.

Flow cytometry for comprehensive assessment of platelet functional activity in response to ADP stimulation

OBJECTIVES

Flow cytometry with adenosine diphosphate (ADP) allows to characterize molecular changes of platelet function caused by this physiologically important activation, but the methodology has not been thoroughly investigated, standardized and characterized yet. We analyzed the influence of several major variables and chose optimal conditions for platelet function assessment.

METHODS

For activation, 2.5 μM CaCl2 , 5 μM ADP and antibodies were added to diluted blood and incubated for 15 min. We analyzed kinetics of antibody binding and effects of their addition sequence, agonist concentration, blood dilution, exogenous calcium addition and platelet fixation.

RESULTS

We tested our protocol on 11 healthy children, 22 healthy adult volunteers, 9 patients after a month on dual antiplatelet therapy after percutaneous coronary intervention (PCI), 7 adult patients and 14 children with immune thrombocytopenia (ITP). We found that our protocol is highly sensitive to ADP stimulation with low percentage of aggregates formation. The assay is also sensitive to platelet function inhibition in post-PCI patients. Finally, platelet preactivation with ITP plasma was stronger and caused increase in activation response to ADP stimulation compared to preactivation with low dose of ADP.

CONCLUSIONS

Our assay is sensitive to antiplatelet therapy and platelet preactivation in ITP patients under physiological conditions with minimal percentage of aggregates formation.

Predicting flow cytometry crossmatch results from single-antigen bead testing

The aim of this study was to devise an algorithm that would predict flow cytometry crossmatch (FCXM) results using single-antigen bead (SAB) mean fluorescent intensity (MFI) levels using samples received through the National External Quality Assurance Scheme (NEQAS) 2B external proficiency testing scheme between 2019 and 2023. A total of 159 serum samples were retrospectively screened using LABScreen Single Antigen Class I and II (SAB), and 40 peripheral blood samples were human leucocyte antigen (HLA) typed with LABType SSO. Donor-specific antibodies were identified for each cell-serum combination tested, and cumulative MFI values were calculated for each test before correlating the screening result with the consensus crossmatch results for this scheme. HLA Class I MFIs were combined to predict the T cell crossmatch. For the B cell crossmatch prediction, two options were considered: (i) HLA Class II MFI values alone and (ii) HLA Class I + Class II MFIs. Receiver operating characteristic analysis was carried out to identify the combined MFI threshold that predicted NEQAS consensus results with the greatest sensitivity and specificity. HLA Class I combined MFI >5000 predicted T cell crossmatch results with 96% sensitivity, 100% specificity, 100% positive predictive value (PPV) and 92% negative predictive value (NPV). For B cell results, HLA Class I + Class II combined MFIs >11,000 gave the best model, showing 97% sensitivity, 82% specificity, 96% PPV and 85% NPV. However, for samples with only HLA Class II sensitization, combined MFIs >13,000 improved the B cell crossmatch predictions: 92% sensitivity, 95% specificity, 96% PPV and 91% NPV. Using this model, combined MFI can be used to predict the immunological risk posed by donor-specific antibodies when it is not possible to carry out an FCXM.

Immunophenotyping of canine T cell activation and proliferation by combined protein and RNA flow cytometry

The limited availability of canine-reactive monoclonal antibodies restricts the analyses of immune cell subsets and their functions by flow cytometry. The PrimeFlow™ RNA Assay may serve as a potential solution to close this gap. Here we report a blood immunophenotyping method utilizing combined protein- and RNA-based flow cytometry to characterize canine T cell activation and proliferation within individual cells. In this assay, CD69 expression was detected by an RNA probe and CD25 and Ki67 were detected by antibodies. Canine peripheral blood mononuclear cells (PBMCs) were stimulated with three agents with different modes of action, anti-CD3/CD28 antibodies, phytohemagglutinin, or phorbol myristate acetate /ionomycin. Robust T cell activation (CD25+ and/or CD69+) and proliferation (Ki67+) were detected. Both CD69 and CD25 appear to be robust and sensitive T cell activation markers with early induction and low background expression. Upon stimulation, T cell proliferation occurred later than T cell activation and was associated with CD25 expression. This canine T cell activation and proliferation immunophenotyping method was evaluated in 5 independent experiments using PBMCs from 10 different beagle dogs with satisfactory assay performance. This method can greatly facilitate the evaluation of immune disease pathogenesis and immunotoxicity risk assessment in nonclinical drug development in canine.

Harmonized analysis of PBMC by mass cytometry

Mass cytometry permits the high dimensional analysis of cellular systems at single-cell resolution with high throughput in various areas of biomedical research. Here, we provide a state-of-the-art protocol for the analysis of human peripheral blood mononuclear cells (PBMC) by mass cytometry. We focus on the implementation of measures promoting the harmonization of large and complex studies to aid robustness and reproducibility of immune phenotyping data.

Flow cytometric minimal residual disease measurement accounting for cytogenetics in children with non-high-risk acute lymphoblastic leukemia treated according to the ALL-MB 2008 protocol

BACKGROUND

Quantitative measurement of minimal residual disease (MRD) is the "gold standard" for estimating the response to therapy in childhood B-cell precursor acute lymphoblastic leukemia (BCP-ALL). Nevertheless, the speed of the MRD response differs for different cytogenetic subgroups. Here we present results of MRD measurement in children with BCP-ALL, in terms of genetic subgroups with relation to clinically defined risk groups.

METHODS

A total of 485 children with non-high-risk BCP-ALL with available cytogenetic data and MRD studied at the end-of-induction (EOI) by multicolor flow cytometry (MFC) were included. All patients were treated with standard-risk (SR) of intermediate-risk (ImR) regimens of "ALL-MB 2008" reduced-intensity protocol.

RESULTS AND DISCUSSION

Among all study group patients, 203 were found to have low-risk cytogenetics (ETV6::RUNX1 or high hyperdiploidy), while remaining 282 children were classified in intermediate cytogenetic risk group. For the patients with favorable and intermediate risk cytogenetics, the most significant thresholds for MFC-MRD values were different: 0.03% and 0.04% respectively. Nevertheless, the most meaningful thresholds were different for clinically defined SR and ImR groups. For the SR group, irrespective to presence/absence of favorable genetic lesions, MFC-MRD threshold of 0.1% was the most clinically valuable, although for ImR group the most informative thresholds were different in patients from low-(0.03%) and intermediate (0.01%) cytogenetic risk groups.

CONCLUSION

Our data show that combining clinical risk factors with MFC-MRD measurement is the most useful tool for risk group stratification of children with BCP-ALL in the reduced-intensity protocols. However, this algorithm can be supplemented with cytogenetic data for part of the ImR group.

Immune signature and phagocytosis of circulating DC subsets in healthy adults during aging

Dendritic cells (DC) play a pivotal role in the onset and progression of immunosenescence-associated diseases, serving as a link between innate and adaptive immunity. Thus, there is a need to establish reference ranges for DC subset levels in healthy adults and investigate the potential impact of age on DC subset levels and phagocytic activity. Single-platform multi-color flow cytometry was performed to assess the proportions of circulating conventional type 1 DC (cDC1), conventional type 2 DC (cDC2), and plasmacytoid DC (pDC), as well as the percentages of CD80, CD86, CD83, PD-L1, and CD32 in cDC1, cDC2, and pDC. Reference ranges were established based on age and gender, and the percentage of circulating DC subsets in different age groups was compared. In addition, circulating DC were enriched using a magnetic bead sorting kit and co-cultured with polystyrene (PS) beads, categorized by age groups, followed by the evaluation of PS bead phagocytosis using light microscopy and flow cytometry. The results indicated that the percentages of circulating cDC1, cDC2, and CD32+cDC2 decreased with age (P < 0.05) and revealed age-related impairment in phagocytic percentage of cDC2 (P < 0.05). These findings provide a deeper understanding of the impact of age on the phenotype and phagocytic activity of DC subsets, shedding light on their role and function in immunosenescence.

Efficient cytometry analysis with FlowSOM in Python boosts interoperability with other single-cell tools

MOTIVATION

We describe a new Python implementation of FlowSOM, a clustering method for cytometry data.

RESULTS

This implementation is faster than the original version in R, better adapted to work with single-cell omics data including integration with current single-cell data structures and includes all the original visualizations, such as the star and pie plot.

AVAILABILITY AND IMPLEMENTATION

The FlowSOM Python implementation is freely available on GitHub: https://github.com/saeyslab/FlowSOM_Python.

Development of a customizable mouse backbone spectral flow cytometry panel to delineate immune cell populations in normal and tumor tissues

Introduction

In vivo studies of cancer biology and assessment of therapeutic efficacy are critical to advancing cancer research and ultimately improving patient outcomes. Murine cancer models have proven to be an invaluable tool in pre-clinical studies. In this context, multi-parameter flow cytometry is a powerful method for elucidating the profile of immune cells within the tumor microenvironment and/or play a role in hematological diseases. However, designing an appropriate multi-parameter panel to comprehensively profile the increasing diversity of immune cells across different murine tissues can be extremely challenging.

Methods

To address this issue, we designed a panel with 13 fixed markers that define the major immune populations -referred to as the backbone panel- that can be profiled in different tissues but with the option to incorporate up to seven additional fluorochromes, including any marker specific to the study in question.

Results

This backbone panel maintains its resolution across different spectral flow cytometers and organs, both hematopoietic and non-hematopoietic, as well as tumors with complex immune microenvironments.

Discussion

Having a robust backbone that can be easily customized with pre-validated drop-in fluorochromes saves time and resources and brings consistency and standardization, making it a versatile solution for immuno-oncology researchers. In addition, the approach presented here can serve as a guide to develop similar types of customizable backbone panels for different research questions requiring high-parameter flow cytometry panels.

SeParate: multiway fluorescence-activated droplet sorting based on integration of serial and parallel triaging concepts

Fluorescence-activated droplet sorting (FADS) has emerged as a versatile high-throughput sorting tool that is, unlike most fluorescence-activated cell sorting (FACS) platforms, capable of sorting droplet-compartmentalized cells, cell secretions, entire enzymatic reactions and more. Recently, multiplex FADS platforms have been developed for the sorting of multi-fluorophore populations towards different outlets in addition to the standard, more commonly used, 2-way FADS platform. These multiplex FADS platforms consist of either multiple 2-way junctions one after the other (i.e. serial sorters) or of one junction sorting droplets in more than 2 outlets (i.e. parallel sorters). In this work, we present SeParate, a novel platform based on integrating s̲e̲rial and p̲a̲r̲allel sorting principles for accura̲t̲e̲ multiplex droplet sorting that is able to mitigate limitations of current multiplex sorters. We show the SeParate platform and its capability in highly accurate 4-way sorting of a multi-fluorophore population into four subpopulations with the potential to expand to more. More specifically, the SeParate platform was thoroughly validated using mixed populations of fluorescent beads and picoinjected droplets, yielding sorting accuracies up to 100% and 99.9%, respectively. Finally, transfected HEK-293T cells were sorted employing two different optical setups, resulting in an accuracy up to 99.5%. SeParate's high accuracy for a diverse set of samples, including highly variable biological specimens, together with its scalability beyond the demonstrated 4-way sorting, warrants a broad applicability for multi-fluorophore studies in life sciences, environmental sciences and others.

Analysis of the multiparametric cell cycle data

This chapter was originally written in 2011. The idea was to give some history of cell cycle analysis before and after flow cytometry became widely accessible; provide references to educational material for single parameter DNA content analysis, introduce and discuss multiparameter cell cycle analysis in a methodological style, and in a casual style, discuss aspects of the work over the last 40years that we have given thought, performing some experiments, but didn't publish. It feels like there is a linear progression that moves from counting cells for growth curves, to counting labeled mitotic cells by autoradiography, to DNA content analysis, to cell cycle states defined by immunofluorescence plus DNA content analysis, to extraction of cell cycle expression profiles, and finally to probability state modeling, which should be the "right" way to analyze cytometric cell cycle data. This is the sense of this chapter. In 2023, we have updated it, but the exciting, expansive aspects brought about by spectral and mass cytometry are still young and developing, and thus have not been vetted, reviewed, and presented in mature form.

Cell metabolism: Functional and phenotypic single cell approaches

Several metabolic pathways are essential for the physiological regulation of immune cells, but their dysregulation can cause immune dysfunction. Hypermetabolic and hypometabolic states represent deviations in the magnitude and flexibility of effector cells in different contexts, for example in autoimmunity, infections or cancer. To study immunometabolism, most methods focus on bulk populations and rely on in vitro activation assays. Nowadays, thanks to the development of single-cell technologies, including multiparameter flow cytometry, mass cytometry, RNA cytometry, among others, the metabolic state of individual immune cells can be measured in a variety of samples obtained in basic, translational and clinical studies. Here, we provide an overview of different single-cell approaches that are employed to investigate both mitochondrial functions and cell dependence from mitochondria metabolism. Moreover, besides the description of the appropriate experimental settings, we discuss the strengths and weaknesses of different approaches with the aim to suggest how to study cell metabolism in the settings of interest.

Spectral Flow Cytometry Methods and Pipelines for Comprehensive Immunoprofiling of Human Peripheral Blood and Bone Marrow

Profiling hematopoietic and immune cells provides important information about disease risk, disease status, and therapeutic responses. Spectral flow cytometry enables high-dimensional single-cell evaluation of large cohorts in a high-throughput manner. Here, we designed, optimized, and implemented new methods for deep immunophenotyping of human peripheral blood and bone marrow by spectral flow cytometry. Two blood antibody panels capture 48 cell-surface markers to assess more than 58 cell phenotypes, including subsets of T cells, B cells, monocytes, natural killer (NK) cells, and dendritic cells, and their respective markers of exhaustion, activation, and differentiation in less than 2 mL of blood. A bone marrow antibody panel captures 32 markers for 35 cell phenotypes, including stem/progenitor populations, T-cell subsets, dendritic cells, NK cells, and myeloid cells in a single tube. We adapted and developed innovative flow cytometric analysis algorithms, originally developed for single-cell genomics, to improve data integration and visualization. We also highlight technical considerations for users to ensure data fidelity. Our protocol and analysis pipeline accurately identifies rare cell types, discerns differences in cell abundance and phenotype across donors, and shows concordant immune landscape trends in patients with known hematologic malignancy.

SIGNIFICANCE

This study introduces optimized methods and analysis algorithms that enhance capabilities in comprehensive immunophenotyping of human blood and bone marrow using spectral flow cytometry. This approach facilitates detection of rare cell types, enables measurement of cell variations across donors, and provides proof-of-concept in identifying known hematologic malignancies. By unlocking complexities of hematopoietic and immune landscapes at the single-cell level, this advancement holds potential for understanding disease states and therapeutic responses.

A Microflow Cytometer Enabled by Monolithic Integration of a Microreflector with an Acoustic Resonator

Current microflow cytometers suffer from complicated fluidic integration and low fluorescence collection efficiency, resulting in reduced portability and sensitivity. Herein, we demonstrated a new flow cell design based on an on-chip monolithically integrated microreflector with a bulk acoustic wave resonator (MBAW). It enables simultaneous 3D particle focusing and fluorescence enhancement without using shear flow. Benefited by the on-chip microreflector, the captured fluorescence intensity was 1.8-fold greater than that of the Si substrate and 8.3-fold greater than that of the SiO2 substrate, greatly improving the detection sensitivity. Combined with the contactless acoustic streaming-based focusing, particle sensing with a coefficient of variation as low as 6.1% was achieved. We also demonstrated the difference between live and dead cells and performed a cell cycle assay using the as-developed microflow cytometry. This monolithic integrated MBAW provides a new type of opto-acoustofluidic system and has the potential to be a highly integrated, highly sensitive flow cytometer for applications such as in vitro diagnostics and point of care.

An open-source FACS automation system for high-throughput cell biology

Recent advances in gene editing are enabling the engineering of cells with an unprecedented level of scale. To capitalize on this opportunity, new methods are needed to accelerate the different steps required to manufacture and handle engineered cells. Here, we describe the development of an integrated software and hardware platform to automate Fluorescence-Activated Cell Sorting (FACS), a central step for the selection of cells displaying desired molecular attributes. Sorting large numbers of samples is laborious, and, to date, no automated system exists to sequentially manage FACS samples, likely owing to the need to tailor sorting conditions ("gating") to each individual sample. Our platform is built around a commercial instrument and integrates the handling and transfer of samples to and from the instrument, autonomous control of the instrument's software, and the algorithmic generation of sorting gates, resulting in walkaway functionality. Automation eliminates operator errors, standardizes gating conditions by eliminating operator-to-operator variations, and reduces hands-on labor by 93%. Moreover, our strategy for automating the operation of a commercial instrument control software in the absence of an Application Program Interface (API) exemplifies a universal solution for other instruments that lack an API. Our software and hardware designs are fully open-source and include step-by-step build documentation to contribute to a growing open ecosystem of tools for high-throughput cell biology.