Fluorescence spectral overlap compensation for any number of flow cytometry parameters

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.

Side-by-Side Comparison of Compensation Beads Used in Polychromatic Flow Cytometry

Compensation or unmixing is essential in analyzing multiparameter flow cytometry data. Errors in data correction, either by compensation or unmixing, can completely change the outcome or mislead the researchers. Owing to limited cell numbers, researchers often use synthetic beads to generate the required single stains for the necessary calculation. In this study, the capacity of synthetic beads to influence data correction is evaluated. Corrected data for human peripheral blood cells were generated using cell-based compensation from the same cells or bead-based compensation to identify differences between the methods. These data suggest that correction with beads on full-spectrum and conventional cytometers does not always follow the basic flow compensation/unmixing expectations and alters the data. Overall, the best approach for bead-based correction for an experiment is to evaluate which beads and fluorochromes are most accurately compensated/unmixed.

Advances in Clinical Mass Cytometry

The advent of high-dimensional single-cell technologies has enabled detection of cellular heterogeneity and functional diversity of immune cells during health and disease conditions. Because of its multiplexing capabilities and limited compensation requirements, mass cytometry or cytometry by time of flight (CyTOF) has played a superior role in immune monitoring compared with flow cytometry. Further, it has higher throughput and lower cost compared with other single-cell techniques. Several published articles have utilized CyTOF to identify cellular phenotypes and features associated with disease outcomes. This article introduces CyTOF-based assays to profile immune cell-types, cell-states, and their applications in clinical research.

Flow Cytometry: The Next Revolution

Unmasking the subtleties of the immune system requires both a comprehensive knowledge base and the ability to interrogate that system with intimate sensitivity. That task, to a considerable extent, has been handled by an iterative expansion in flow cytometry methods, both in technological capability and also in accompanying advances in informatics. As the field of fluorescence-based cytomics matured, it reached a technological barrier at around 30 parameter analyses, which stalled the field until spectral flow cytometry created a fundamental transformation that will likely lead to the potential of 100 simultaneous parameter analyses within a few years. The simultaneous advance in informatics has now become a watershed moment for the field as it competes with mature systematic approaches such as genomics and proteomics, allowing cytomics to take a seat at the multi-omics table. In addition, recent technological advances try to combine the speed of flow systems with other detection methods, in addition to fluorescence alone, which will make flow-based instruments even more indispensable in any biological laboratory. This paper outlines current approaches in cell analysis and detection methods, discusses traditional and microfluidic sorting approaches as well as next-generation instruments, and provides an early look at future opportunities that are likely to arise.

Prism Design for Spectral Flow Cytometry

Flow cytometers are instruments used for the rapid quantitative analysis of cell suspension. Traditional flow cytometry uses multi-channel filters to detect fluorescence, whereas full-spectrum fluorescence based on dispersion detection is a more effective and accurate method. The application of various dispersion schemes in flow cytometry spectroscopy has been studied. From the perspective of modern detectors and demand for the miniaturization of flow cytometry, prism dispersion exhibits higher and more uniform light energy utilization, meaning that it is a more suitable dispersion method for small flow cytometers, such as microfluidic flow cytometers. Prism dispersion designs include the size, number, and placement of prisms. By deducing the formula of the final position of light passing through the prism and combining it with the formula of transmittance, the design criteria of the top angle and the incident angle of the prism in pursuit of the optimum transmittance and dispersion index can be obtained. Considering the case of multiple prisms, under the premise of pursuing a smaller size, the optimal design criteria for dispersion system composed of multiple prisms can be obtained. The design of prism dispersion fluorescence detection was demonstrated with a microfluidic flow cytometer, and the effectiveness of the design results was verified by microsphere experiments and practical biological experiments. This design criterion developed in this study is generally applicable to spectral flow cytometers.

Principles of Advanced Flow Cytometry: A Practical Guide

Recent advances have revolutionized the oldest high-throughput single-cell analytical tool, flow cytometry. Fluorescent analyzers and sorters with up to seven lasers and the potential to detect up to 50 parameters are changing the way flow cytometry is used, but old school practices which are inadequate for new technologies remain alive. This chapter summarizes recent advances, explains the most salient new features and offers a step-by-step guide to develop and successfully execute high-dimensional fluorescent flow cytometry experiments.

Development of Spectral Imaging Cytometry

Spectral flow cytometry is a new technology that enables measurements of fluorescent spectra and light scattering properties in diverse cellular populations with high precision. Modern instruments allow simultaneous determination of up to 40+ fluorescent dyes with heavily overlapping emission spectra, discrimination of autofluorescent signals in the stained specimens, and detailed analysis of diverse autofluorescence of different cells-from mammalian to chlorophyll-containing cells like cyanobacteria. In this paper, we review the history, compare modern conventional and spectral flow cytometers, and discuss several applications of spectral flow cytometry.

A comparison of spectral unmixing to conventional compensation for the calculation of fluorochrome abundances from flow cytometric data

Traditionally, flow cytometers acquired data using the same number of detectors as fluorochromes being measured in the experiment. More recently, spectral flow cytometers utilize a larger number of detectors than fluorochromes. This seemingly small difference opens the door to a wide variety of mathematical tools for the calculation of the true fluorochrome abundances from the raw detector values as compared with traditional compensation. This review will provide a brief overview of the mathematics and theory underlying traditional compensation and unmixing focusing on the differences between them and the additional information provided by unmixing approaches.

Mapping Cell Phenomics with Multiparametric Flow Cytometry Assays

Phenomics explores the complex interactions among genes, epigenetics, symbiotic microorganisms, diet, and environmental exposure based on the physical, chemical, and biological characteristics of individuals and groups. Increasingly efficient and comprehensive phenotyping techniques have been integrated into modern phenomics-related research. Multicolor flow cytometry technology provides more measurement parameters than conventional flow cytometry. Based on detailed descriptions of cell phenotypes, rare cell populations and cell subsets can be distinguished, new cell phenotypes can be discovered, and cell apoptosis characteristics can be detected, which will expand the potential of cell phenomics research. Based on the enhancements in multicolor flow cytometry hardware, software, reagents, and method design, the present review summarizes the recent advances and applications of multicolor flow cytometry in cell phenomics, illuminating the potential of applying phenomics in future studies.

CyTOF® for the Masses

Mass cytometry has revolutionized immunophenotyping, particularly in exploratory settings where simultaneous breadth and depth of characterization of immune populations is needed with limited samples such as in preclinical and clinical tumor immunotherapy. Mass cytometry is also a powerful tool for single-cell immunological assays, especially for complex and simultaneous characterization of diverse intratumoral immune subsets or immunotherapeutic cell populations. Through the elimination of spectral overlap seen in optical flow cytometry by replacement of fluorescent labels with metal isotopes, mass cytometry allows, on average, robust analysis of 60 individual parameters simultaneously. This is, however, associated with significantly increased complexity in the design, execution, and interpretation of mass cytometry experiments. To address the key pitfalls associated with the fragmentation, complexity, and analysis of data in mass cytometry for immunologists who are novices to these techniques, we have developed a comprehensive resource guide. Included in this review are experiment and panel design, antibody conjugations, sample staining, sample acquisition, and data pre-processing and analysis. Where feasible multiple resources for the same process are compared, allowing researchers experienced in flow cytometry but with minimal mass cytometry expertise to develop a data-driven and streamlined project workflow. It is our hope that this manuscript will prove a useful resource for both beginning and advanced users of mass cytometry.

Incorporating, Quantifying, and Leveraging Noncanonical Amino Acids in Yeast

Genetic code expansion has allowed for extraordinary advances in enhancing protein chemical diversity and functionality, but there remains a critical need for understanding and engineering genetic code expansion systems for improved efficiency. Incorporation of noncanonical amino acids (ncAAs) at stop codons provides a site-specific method for introducing unique chemistry into proteins, though often at reduced yields compared to wild-type proteins. A powerful platform for ncAA incorporation supports both the expression and evaluation of chemically diverse proteins for a broad range of applications. In yeast, ncAAs have been used to study dynamic cellular processes such as protein-protein interactions and also allow for exploration of eukaryotic-specific biology such as epigenetics. Furthermore, yeast display is an advantageous technology for engineering and screening the properties of proteins in high throughput. The protocols presented in this chapter describe detailed methods for the yeast-based genetic encoding of ncAAs in proteins intracellularly or on the yeast surface. In addition, methods are presented for modifying proteins on the yeast surface using bioorthogonal chemical reactions and evaluating reaction efficiency. Finally, protocols are included for the preparation of libraries that involve genetic code expansion. Libraries of proteins that contain ncAAs or libraries of the cellular machinery required to encode ncAAs can be constructed and screened in high throughput for many biological and chemical applications. Efficient incorporation of ncAAs facilitates elucidation of fundamental eukaryotic biology and advances tools for enzyme and genome engineering to evolve host cells that are better able to accommodate alternative genetic codes.

Highly sensitive detection of multiple proteins from single cells by MoS2-FET biosensors

Single-cell analysis of proteins is critical to gain precise information regarding the mechanisms that dictate the heterogeneity in cellular phenotypes and their differential response to internal and external stimuli. However, tools that allow sensitive and easy measurement of proteins in individual cells are still limited. The emerging semiconductor-based bioelectronics may provide a new approach to overcome the challenges in this field, however its utility in single-cell protein analysis has not been explored. In this study, we investigated multiple protein detection in single cells by MoS₂ field effect transistors (MoS₂-FETs) modified with specific biological probes. First, β-actin antibody was connected to the surface of MoS₂-FETs by covalent bonds, and the fabricated device was tested using β-actin solution with concentrations from 10^-9 to 10^-3 μg/μL. Next, we examined the application of MoS₂-FET for protein analysis in complex biological samples, and the device showed electrical signal response to human embryonic kidney cell line HEK293T in a dose-dependent manner. Furthermore, we applied this method to analyze individual liver cancer MHCC-97L cells, targeting four cellular proteins, including β-actin, epidermal growth factor receptor, sirtuin-2, and glyceraldehyde-3-phosphate dehydrogenase. The devices modified with corresponding probes could identify the target proteins and showed cell number-dependent responses. As a proof of principle, we demonstrated sensitive and multiplexed detection of proteins in single cells using MoS₂-FETs. The biosensor and this detection method are cost-efficient and user-friendly with broad application prospects in biological studies and clinical diagnosis.

Guidelines for the use of flow cytometry and cell sorting in immunological studies (third edition)

The third edition of Flow Cytometry Guidelines provides the key aspects to consider when performing flow cytometry experiments and includes comprehensive sections describing phenotypes and functional assays of all major human and murine immune cell subsets. Notably, the Guidelines contain helpful tables highlighting phenotypes and key differences between human and murine cells. Another useful feature of this edition is the flow cytometry analysis of clinical samples with examples of flow cytometry applications in the context of autoimmune diseases, cancers as well as acute and chronic infectious diseases. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid. All sections are written and peer-reviewed by leading flow cytometry experts and immunologists, making this edition an essential and state-of-the-art handbook for basic and clinical researchers.

Evaluation of immature platelet fraction as a marker of dengue fever progression

OBJECTIVES

Progression of dengue is often associated with thrombocytopenia resulting from viral-induced bone marrow suppression and immune-mediated peripheral platelet consumption. Immature platelet fraction (IPF), which can be measured using a haematology analyser, is a precursor indicating platelet formation in the bone marrow. This study evaluated the trend of IPF as an early recovery indicator of platelets in dengue patients with thrombocytopenia, and its relationship with severe dengue in conjunction with reticulocyte count.

METHODS

Hospitalized patients with dengue were enrolled and followed-up daily until discharge. Blood investigations included daily full blood counts and IPF measured using a haematology analyser.

RESULTS

In total, 287 patients with confirmed dengue were enrolled in this study, 25 of whom had severe dengue. All patients had a decreasing trend in platelet count in the first week of illness, concomitant with an increasing trend in the percentage of immature platelets to total platelets (IPF%) for more than 3 days prior to platelet recovery. IPF% was significantly increased in patients with severe dengue compared with patients with non-severe dengue on days 3-5 after the onset of fever. Reticulocyte count increased significantly in patients with severe dengue on day 5.

CONCLUSIONS

IPF can be utilized as an early recovery indicator of platelets in patients with dengue and thrombocytopenia.

Resolution of Spike Overlapping by Biogeography-Based Optimization

There are many cases in which the separation of different sources from single channel recordings is important, for example, in fluorescence spectral overlap compensation, electrical impedance signaling, intramuscular electromyogram decomposition or in the case of spike sorting of neuron potentials from microelectrode arrays (MEA). Focusing on the latter, the problem can be faced by identifying spikes emerging from the background and clustering into different groups, indicating the activity of different neurons. Problems are found when more spikes are superimposed in overlapped waveforms. We discuss the application of Biogeography-Based Optimization (BBO) to resolve this specific problem. Our algorithm is compared with three spike-sorting methods (SpyKING Circus, Common Basis Pursuit and Klusta), showing statistically better performance (in terms of F1 score, True Positive Rate—TPR and Positive Predictive Value—PPV) in resolving overlaps in realistic, simulated data. Specifically, BBO showed median F1, TPR and PPV of 100%, 100% and about 75%, respectively, considering a simulated noise with the same spectral density as the experimental one and a similar power with highly statistically significant improvements of at least two performance indexes over each of the other three tested algorithms.

AutoSpill is a principled framework that simplifies the analysis of multichromatic flow cytometry data

Compensating in flow cytometry is an unavoidable challenge in the data analysis of fluorescence-based flow cytometry. Even the advent of spectral cytometry cannot circumvent the spillover problem, with spectral unmixing an intrinsic part of such systems. The calculation of spillover coefficients from single-color controls has remained essentially unchanged since its inception, and is increasingly limited in its ability to deal with high-parameter flow cytometry. Here, we present AutoSpill, an alternative method for calculating spillover coefficients. The approach combines automated gating of cells, calculation of an initial spillover matrix based on robust linear regression, and iterative refinement to reduce error. Moreover, autofluorescence can be compensated out, by processing it as an endogenous dye in an unstained control. AutoSpill uses single-color controls and is compatible with common flow cytometry software. AutoSpill allows simpler and more robust workflows, while reducing the magnitude of compensation errors in high-parameter flow cytometry.

Identification and Assessment of Plasmodium berghei Merozoites and Cell Cycle by Flow Cytometry

BACKGROUND

The asexual blood stages of the Plasmodium berghei life cycle including merozoites are attractive targets for transmission blocking vaccines and drugs. Improved understanding of P. berghei life cycle stage growth and development would provide new opportunities to evaluate antimalarial vaccines and drugs.

METHODS

Blood stage samples from C57BL/6 albino mice infected with P. berghei sporozoites were singly stained with a high binding affinity deoxyribonucleic acid dye, YOYO-1, and measured by flow cytometry (FCM). Duplicate slides were made from samples and stained with diluted Giemsa's and YOYO-1, respectively. Correlated results were compared by FCM, light microscopy, and fluorescent microscopy.

RESULTS

Complete life cycle stage determination and analysis by FCM is reported to include merozoites, ring forms, trophozoites, immature, and mature schizonts. FCM demonstrated a clear separation between each stage using their unique fluorescence distribution. When compared to light microscopy, a strong correlation (r 2 = 0.925 to 0.974) was observed in determining the ring forms, trophozoites, and schizonts phases, but only a moderate correlation (r 2 = 0.684 to 0.778) was observed for merozoites. The identification and measurement of merozoites suggest that FCM is a useful technique to monitor the entire life stage of the parasite. Initial stage-specific data demonstrated that mefloquine has a mode of action on mature parasite forms, and artesunic acid was rapidly effective against merozoites and other immature and mature parasite forms with higher killing.

CONCLUSION

Blood stage parasites in each individual life stage, including merozoites, are reliably identified and quantified quickly by FCM, making this technique an ideal alternative to microscopy. This integrated whole life stage model, particularly with confirmed determination of merozoite population, could widely be used for drug and vaccine research in malaria therapy and prophylaxis.

Knockout of RSN1, TVP18 or CSC1-2 causes perturbation of Golgi cisternae in Pichia pastoris

The structural organization of the Golgi stacks in mammalian cells is intrinsically linked to function, including glycosylation, but the role of morphology is less clear in lower eukaryotes. Here we investigated the link between the structural organization of the Golgi and secretory pathway function using Pichia pastoris as a model system. To unstack the Golgi cisternae, we disrupted 18 genes encoding proteins in the secretory pathway without loss of viability. Using biosensors, confocal microscopy and transmission electron microscopy we identified three strains with irreversible perturbations in the stacking of the Golgi cisternae, all of which had disruption in genes that encode proteins with annotated function as or homology to calcium/calcium permeable ion channels. Despite this, no variation in the secretory pathway for ER size, whole cell glycomics or recombinant protein glycans was observed. Our investigations showed the robust nature of the secretory pathway in P. pastoris and suggest that Ca²⁺ concentration, homeostasis or signalling may play a significant role for Golgi stacking in this organism and should be investigated in other organisms.

Evaluating spectral cytometry for immune profiling in viral disease

In conventional fluorescence cytometry, each fluorophore present in a panel is measured in a target detector, through the use of wide band-pass optical filters. In contrast, spectral cytometry uses a large number of detectors with narrow band-pass filters to measure a fluorophore's signal across the spectrum, creating a more detailed fluorescent signature for each fluorophore. The spectral approach shows promise in adding flexibility to panel design and improving the measurement of fluorescent signal. However, few comparisons between conventional and spectral systems have been reported to date. We therefore sought to compare a modern conventional cytometry system with a modern spectral system, and to assess the quality of resulting datasets from the point of view of a flow cytometry user. Signal intensity, spread, and resolution were compared between the systems. Subsequently, the different methods of separating fluorophore signals were compared, where compensation mathematically separates multiple overlapping fluorophores and unmixing relies on creating a detailed fluorescent signature across the spectrum to separate the fluorophores. Within the spectral data set, signal spread and resolution were comparable between compensation and unmixing. However, for some highly overlapping fluorophores, unmixing resolved the two fluorescence signals where compensation did not. Finally, data from mid- to large-size panels were acquired and were found to have comparable resolution for many fluorophores on both instruments, but reduced levels of spreading error on our spectral system improved signal resolution for a number of fluorophores, compared with our conventional system. Furthermore, autofluorescence extraction on the spectral system allowed for greater population resolution in highly autofluorescent samples. Overall, the implementation of a spectral cytometry approach resulted in data that are comparable to that generated on conventional systems, with a number of potential advantages afforded by the larger number of detectors, and the integration of the spectral unmixing approach. © 2020 International Society for Advancement of Cytometry.

Recent Advances in Computer-Assisted Algorithms for Cell Subtype Identification of Cytometry Data

The progress in the field of high-dimensional cytometry has greatly increased the number of markers that can be simultaneously analyzed producing datasets with large numbers of parameters. Traditional biaxial manual gating might not be optimal for such datasets. To overcome this, a large number of automated tools have been developed to aid with cellular clustering of multi-dimensional datasets. Here were review two large categories of such tools; unsupervised and supervised clustering tools. After a thorough review of the popularity and use of each of the available unsupervised clustering tools, we focus on the top six tools to discuss their advantages and limitations. Furthermore, we employ a publicly available dataset to directly compare the usability, speed, and relative effectiveness of the available unsupervised and supervised tools. Finally, we discuss the current challenges for existing methods and future direction for the new generation of cell type identification approaches.

Quality Control of Immunophenotyping

Applications of immunophenotyping using flow cytometry offer precise and accurate means for providing information used to both diagnose and monitor disease; they serve as a standard platform for many research endeavors that study discrete populations of biological entities. The proper use of this highly sophisticated technology requires daily and ongoing monitoring of both the instrument and the methodology. Best practices for this begin with quality control (QC) procedures designed to set up and monitor the instrument performance, the reagents, and the results to ensure that they are working properly both on the day of use and over time. If the results of those QC procedures are outside of acceptable then recording the corrective action taken must also be included in the quality control records. Quality assurance (QA) is a way to know that the three phases of testing, namely, preanalytic, analytic, and postanalytic procedures, are being followed. This chapter describes the procedures used to assess quality control as it pertains to flow cytometry and immunophenotyping in all three phases of testing.

Inherent Immune Cell Variation Within Colonic Segments Presents Challenges for Clinical Trial Design

BACKGROUND AND AIMS

Intestinal biopsy sampling during IBD trials represents a valuable adjunct strategy for understanding drug responses at the tissue level. Given the length and distinctive embryonic origins of the proximal and distal colon, we investigated whether inherent regional differences of immune cell composition could introduce confounders when sampling different disease stages, or pre/post drug administration. Here, we capitalise on novel mass cytometry technology to perform deep immunophenotyping of distinct healthy colonic segments, using the limited numbers of biopsies that can be harvested from patients.

METHODS

Biopsies [2.8 mm] were collected from the caecum, transverse colon, descending colon, and rectum of normal volunteers. Intestinal leukocytes were isolated, stained with a panel of 37 antibodies, and mass cytometry data acquired.

RESULTS

Site-specific patterns of leukocyte localisation were observed. The proximal colon featured increased CD8+ T cells [particularly resident memory], monocytes, and CD19+ B cells. Conversely, the distal colon and rectum tissues exhibited enrichment for CD4+ T cells and antibody-secreting cells. The transverse colon displayed increased abundance of both γδ T cells and NK cells. Subsets of leukocyte lineages also displayed gradients of expression along the colon length.

CONCLUSIONS

Our results show an inherent regional immune cell variation within colonic segments, indicating that regional mucosal signatures must be considered when assessing disease stages or the prospective effects of trial drugs on leukocyte subsets. Precise protocols for intestinal sampling must be implemented to allow for the proper interpretation of potential differences observed within leukocyte lineages present in the colonic lamina propria.

Triploidy in zebrafish larvae: Effects on gene expression, cell size and cell number, growth, development and swimming performance

There is renewed interest in the regulation and consequences of cell size adaptations in studies on understanding the ecophysiology of ectotherms. Here we test if induction of triploidy, which increases cell size in zebrafish (Danio rerio), makes for a good model system to study consequences of cell size. Ideally, diploid and triploid zebrafish should differ in cell size, but should otherwise be comparable in order to be suitable as a model. We induced triploidy by cold shock and compared diploid and triploid zebrafish larvae under standard rearing conditions for differences in genome size, cell size and cell number, development, growth and swimming performance and expression of housekeeping genes and hsp70.1. Triploid zebrafish have larger but fewer cells, and the increase in cell size matched the increase in genome size (+ 50%). Under standard conditions, patterns in gene expression, ontogenetic development and larval growth were near identical between triploids and diploids. However, under demanding conditions (i.e. the maximum swimming velocity during an escape response), triploid larvae performed poorer than their diploid counterparts, especially after repeated stimuli to induce swimming. This result is consistent with the idea that larger cells have less capacity to generate energy, which becomes manifest during repeated physical exertion resulting in increased fatigue. Triploidy induction in zebrafish appears a valid method to increase specifically cell size and this provides a model system to test for consequences of cell size adaptation for the energy budget and swimming performance of this ectothermic vertebrate.

A robust flow cytometry-based biomass monitoring tool enables rapid at-line characterization of S. cerevisiae physiology during continuous bioprocessing of spent sulfite liquor

Assessment of viable biomass is challenging in bioprocesses involving complex media with distinct biomass and media particle populations. Biomass monitoring in these circumstances usually requires elaborate offline methods or sophisticated inline sensors. Reliable monitoring tools in an at-line capacity represent a promising alternative but are still scarce to date. In this study, a flow cytometry-based method for biomass monitoring in spent sulfite liquor medium as feedstock for second generation bioethanol production with yeast was developed. The method is capable of (i) yeast cell quantification against medium background, (ii) determination of yeast viability, and (iii) assessment of yeast physiology though morphological analysis of the budding division process. Thus, enhanced insight into physiology and morphology is provided which is not accessible through common online and offline biomass monitoring methods. To demonstrate the capabilities of this method, firstly, a continuous ethanol fermentation process of Saccharomyces cerevisiae with filtered and unfiltered spent sulfite liquor media was analyzed. Subsequently, at-line process monitoring of viability in a retentostat cultivation was conducted. The obtained information was used for a simple control based on addition of essential nutrients in relation to viability. Thereby, inter-dependencies between nutrient supply, physiology, and specific ethanol productivity that are essential for process design could be illuminated.

Standardization of a compensation matrix for the use in an ISHAGE-based single-platform for CD34+ stem cell quantitation on the FACSVia™ flow cytometer

INTRODUCTION

Becton Dickinson (BD) FACSVia™ is a recently developed flow cytometer with which worldwide clinical experience is limited. Recently, our center started using the single-platform BD Stem Cell Kit (BD SCE) for the quantitation of viable CD34+ (7-aminoactinomycin D-7-AAD-negative cells) on a BD FACSVia™. Currently, there are no formal recommendations for the fluorescence compensation of 7-AAD in this scenario.

METHODS

A 3-color fluorescence compensation matrix ("Optimized BD CS&T") was standardized based on the fluorescence of 7-AAD in samples of 27 individuals. The "Optimized BD CS&T" was compared with manual compensation (predicated method) and BD CS&T beads.

RESULTS

The analysis of the viable CD34+ cells/mm³ showed a very strong correlation between the manual compensation versus "Optimized BD CS&T" (r = 1.00) and manual versus BD CS&T (r = .99). The analysis of CD34+ viability (%) showed a very strong correlation for manual versus "Optimized BD CS&T" (r = .99). However, for manual versus BD CS&T, the correlation was inferior (r = .86). For viable CD34+ cells/mm³ , Bland-Altman plots showed a better concordance between manual and "Optimized BD CS&T" than between manual and BD CS&T. For CD34+ viability (%), the concordance was very good between manual and "Optimized BD CS&T", while there was a poor concordance between manual and BD CS&T.

CONCLUSION

"Optimized BD CS&T" matrix proved to be more precise than the conventional BD CS&T beads. The "Optimized BD CS&T" matrix can be used along with BD SCE kit on BD FACSVia™ flow cytometers.

Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion.

Immunophenotyping of Human Regulatory T Cells

Regulatory T cells, also known as Tregs, play a pivotal role in maintaining homeostasis of the immune system and self-tolerance. Tregs express CD3, CD4, CD25, and FOXP3 but lack CD127. CD4 and CD3 identify helper T lymphocytes, of which Tregs are a subset. CD25 is IL-2Rα, an essential activation marker that is expressed in high levels on Tregs. FOXP3 is the canonical transcription factor, important in the development, maintenance, and identification of Tregs. CD127 is IL-7 receptor, expressed inversely with suppression, and is therefore downregulated on Tregs. Flow cytometry is a powerful tool that is capable of simultaneously measuring Tregs along with several markers associated with subpopulations of Tregs, activation, maturation, proliferation, and surrogates of functional suppression. This chapter describes a multicolor flow cytometry-based approach to measure human Tregs, including details for surface staining, fixation/permeabilization, intracellular/intranuclear staining, acquisition of samples on a flow cytometer, plus analysis and interpretation of resulting FCS files.

The filamentous fungus Penicillium chrysogenum analysed via flow cytometry-a fast and statistically sound insight into morphology and viability

Filamentous fungi serve as production host for a number of highly relevant biotechnological products, like penicillin. In submerged culture, morphology can be exceptionally diverse and is influenced by several process parameters, like aeration, agitation, medium composition or growth rate. Fungal growth leads to several morphological classes encompassing homogeneously dispersed hyphae and various forms of hyphal agglomerates and/or clump structures. Eventually, the so-called pellet structure can be formed, which represents a hyphal agglomerate with a dense core. Pellet structures can hinder oxygen and substrate transport, resulting in different states of viability, which in turn affects productivity and process control. Over the years, several publications have dealt with methods to either gain morphological insight into pellet structure or determine biomass viability. Within this contribution, we present a way to combine both in a flow cytometry–based method employing fluorescent staining. Thereby, we can assess filamentous biomass in a statistically sound way according to (i) morphology and (ii) viability of each detected morphological form. We are confident that this method can shed light on the complex relationship between fungal morphology, viability and productivity—in both process development and routine manufacturing processes.

Unlabeled Competitor Antibody to Reduce Nonlinear Signal Spillover in Mass Cytometry

Mass cytometry (MCM; CyTOF) utilizes isotopically purified metal-tagged antibodies for single-cell analysis and can analyze more than 40 parameters simultaneously with minimum signal spillover to other mass channels as compared to fluorescent flow cytometry. In spite of this improvement, various factors such as metal oxidation, abundance sensitivity related spillover, and metal impurities can cause measurable amounts of spillover in MCM that can potentially lead to misinterpretation of data. Linear spillover can be corrected by applying compensation; however, we demonstrate that at high signal intensities, MCM channel spillovers are frequently nonlinear. This report describes a simple method to correct for nonlinear signal spillover (due to abundance sensitivity, isotopic contamination, or oxide formation) that can occur at high signal intensity through the use of unlabeled competitor antibodies to the specific metal-tagged antibodies causing spillover. This method significantly decreased high signal intensity and nonlinear spillover to other mass channels while maintaining saturating antibody concentrations, thereby facilitating accurate staining and compensation. In contrast, the common method of using under-titrated antibodies to overcome spillover lead to staining intensity that varied with cell numbers and antigen abundance. We demonstrate that this technique reduces total signal without significantly altering immunophenotypic or functional measurement of relative antigen levels and could be used to enable improved linear compensation of signal spillovers from high abundance antigens. STATEMENT OF SIGNIFICANCE: Mass cytometry is becoming a well-established technology for comprehensive analysis of complex biological samples, due to its ability to enable measurement of more than 40 simultaneous parameters. Due to the use of isotopically pure metal-tagged antibodies, measurement channel spillover in mass cytometry is drastically lower than in fluorescent cytometry but can still occur due to metal oxidation, isotopic impurities, or abundance sensitivity when mass signals have high intensity. We show in this report that high abundance antigens with high signal intensity exhibit non-linear mass channel spillovers that cannot be easily compensated. We also demonstrate a simple method for the use of unlabeled competitor antibody to decrease antigen signal intensity while maintaining antigen abundance to allow for more accurate linear compensation. This method performs more consistently than the commonly used approach of using under-titrated antibodies. We believe that this report has immediate practical utility for researchers using mass cytometry and can be broadly utilized to enable compensation of mass cytometry data when needed. We thus feel that this article merits publication as a Brief Report in Cytometry Part A. © 2019 International Society for Advancement of Cytometry.

High-Dimensional Immunophenotyping with Fluorescence-Based Cytometry: A Practical Guidebook

Recent technological advances have greatly diversified the platforms that are available for high-dimensional single-cell immunophenotyping, including mass cytometry, single-cell RNA sequencing, and fluorescent-based flow cytometry. The latter is currently the most commonly used approach, and modern instrumentation allows for the measurement of up to 30 parameters, revealing deep insights into the complexity of the immune system.Here, we provide a practical guidebook for the successful design and execution of complex fluorescence-based immunophenotyping panels. We address common misconceptions and caveats, and also discuss challenges that are associated with the quality control and analysis of these data sets.

DeepScreen: An Accurate, Rapid, and Anti-Interference Screening Approach for Nanoformulated Medication by Deep Learning

Accuracy of current efficacy judgment methods for nanoformulated drug remains unstable due to the interference of nanocarriers. Herein, DeepScreen, a drug screening system utilizing convolutional neural network based on flow cytomerty single-cell images, is introduced. Compared to existing experimental approaches, the high-throughput system has superior precision, rapidity, and anti-interference, and is cost-cutting with high accuracy. First, it can resist most disturbances from manual factors of complicated evaluation progress. In addition, class activation maps generated from DeepScreen indicate that it may identify and locate the tiny variation from cell apoptosis and slight changes of cellular period caused by drug or even nanoformulated drug action at very early stages. More importantly, the excellent performance of assessment on two types of nanoformulations and fluorescent drug proves the fine generality and anti-interference of this novel system. All these privileged performances make DeepScreen a very smart and promising system for drug detection.

Compensation of Signal Spillover in Suspension and Imaging Mass Cytometry

The advent of mass cytometry increased the number of parameters measured at the single-cell level while decreasing the extent of crosstalk between channels relative to dye-based flow cytometry. Although reduced, spillover still exists in mass cytometry data, and minimizing its effect requires considerable expert knowledge and substantial experimental effort. Here, we describe a novel bead-based compensation workflow and R-based software that estimates and corrects for interference between channels. We performed an in-depth characterization of the spillover properties in mass cytometry, including limitations defined by the linear range of the mass cytometer and the reproducibility of the spillover over time and across machines. We demonstrated the utility of our method in suspension and imaging mass cytometry. To conclude, our approach greatly simplifies the development of new antibody panels, increases flexibility for antibody-metal pairing, opens the way to using less pure isotopes, and improves overall data quality, thereby reducing the risk of reporting cell phenotype artifacts.

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Signal spillover can impact quality of mass cytometry data

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Spillover can be corrected by compensation throughout the linear range of the CyTOF

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Compensation enables signal correction and data structure preservation

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CATALYST is a new R package and a web tool to estimate and correct for spillover

xCell: digitally portraying the tissue cellular heterogeneity landscape

Tissues are complex milieus consisting of numerous cell types. Several recent methods have attempted to enumerate cell subsets from transcriptomes. However, the available methods have used limited sources for training and give only a partial portrayal of the full cellular landscape. Here we present xCell, a novel gene signature-based method, and use it to infer 64 immune and stromal cell types. We harmonized 1822 pure human cell type transcriptomes from various sources and employed a curve fitting approach for linear comparison of cell types and introduced a novel spillover compensation technique for separating them. Using extensive in silico analyses and comparison to cytometry immunophenotyping, we show that xCell outperforms other methods. xCell is available at http://xCell.ucsf.edu/.

High-Dimensional Fluorescence Cytometry

The immune system consists of a complex network of cells, all expressing a wide range of surface and/or intracellular proteins. Using flow cytometry, these cells can be analyzed by labeling with fluorophore-conjugated antibodies. The recent expansion of fluorescence flow cytometry technology, in conjunction with the ever-expanding understanding of the complexity of the immune system, has led to the generation of larger high-dimensional fluorescence flow cytometry panels. However, as panel size and complexity increases, so too does the difficulty involved in constructing high-quality panels, in addition to the challenges of analyzing such high-dimensional datasets. As such, this unit seeks to review the key principles involved in building high-dimensional panels, as well as to guide users through the process of building and analyzing quality panels. Here, cytometer configuration, fluorophore brightness, spreading error, antigen density, choosing the best conjugates, titration, optimization, and data analysis will all be addressed. © 2017 by John Wiley & Sons, Inc.

What is a "unimodal" cell population? Using statistical tests as criteria for unimodality in automated gating and quality control

Many automated gating algorithms for flow cytometry data are based on the concept of unimodal cell populations. However, in this article, we show that criteria previously used to make decisions on unimodality cannot adequately distinguish unimodal from bimodal densities. We show that dip and bandwidth tests for unimodality, taken from the statistics literature, can do this with consistent and low error rates. These tests also have the possibility to adjust the significance level to handle the trade-off between failing to detect a second mode and seeing a second mode when there is none. The differences between the dip and bandwidth tests are elucidated using real data from the FlowCAP I challenge, also guidelines for flow cytometry data preprocessing are given. © 2017 International Society for Advancement of Cytometry.

How to Make Distinct Dynamical Systems Appear Spectrally Identical

We show that a laser pulse can always be found that induces a desired optical response from an arbitrary dynamical system. As illustrations, driving fields are computed to induce the same optical response from a variety of distinct systems (open and closed, quantum and classical). As a result, the observed induced dipolar spectra without detailed information on the driving field are not sufficient to characterize atomic and molecular systems. The formulation may also be applied to design materials with specified optical characteristics. These findings reveal unexplored flexibilities of nonlinear optics.

Standardization, Calibration, and Control in Flow Cytometry

Because flow cytometers are designed to measure particle characteristics, particles are the most common materials used to calibrate, control, and standardize the instruments. Definitions and cautions are provided for common terms to alert the reader to critical distinctions in meaning. This unit presents extensive background on particle types and cautions and describes practical aspects of methods to standardize and calibrate instruments. Procedures are provided to characterize performance in terms of optical alignment, fluorescence and light scatter resolution, and sensitivity. Finally, suggestions follow for analyzing particles used for calibration. © 2017 by John Wiley & Sons, Inc.

An Orthogonal Permease-Inducer-Repressor Feedback Loop Shows Bistability

Feedback loops in biological networks, among others, enable differentiation and cell cycle progression, and increase robustness in signal transduction. In natural networks, feedback loops are often complex and intertwined, making it challenging to identify which loops are mainly responsible for an observed behavior. However, minimal synthetic replicas could allow for such identification. Here, we engineered a synthetic permease-inducer-repressor system in Saccharomyces cerevisiae to analyze if a transport-mediated positive feedback loop could be a core mechanism for the switch-like behavior in the regulation of metabolic gene networks such as the S. cerevisiae GAL system or the Escherichia coli lac operon. We characterized the synthetic circuit using deterministic and stochastic mathematical models. Similar to its natural counterparts, our synthetic system shows bistable and hysteretic behavior, and the inducer concentration range for bistability as well as the switching rates between the two stable states depend on the repressor concentration. Our results indicate that a generic permease-inducer-repressor circuit with a single feedback loop is sufficient to explain the experimentally observed bistable behavior of the natural systems. We anticipate that the approach of reimplementing natural systems with orthogonal parts to identify crucial network components is applicable to other natural systems such as signaling pathways.

Immunophenotype Discovery, Hierarchical Organization, and Template-Based Classification of Flow Cytometry Samples

We describe algorithms for discovering immunophenotypes from large collections of flow cytometry samples and using them to organize the samples into a hierarchy based on phenotypic similarity. The hierarchical organization is helpful for effective and robust cytometry data mining, including the creation of collections of cell populations’ characteristic of different classes of samples, robust classification, and anomaly detection. We summarize a set of samples belonging to a biological class or category with a statistically derived template for the class. Whereas individual samples are represented in terms of their cell populations (clusters), a template consists of generic meta-populations (a group of homogeneous cell populations obtained from the samples in a class) that describe key phenotypes shared among all those samples. We organize an FC data collection in a hierarchical data structure that supports the identification of immunophenotypes relevant to clinical diagnosis. A robust template-based classification scheme is also developed, but our primary focus is in the discovery of phenotypic signatures and inter-sample relationships in an FC data collection. This collective analysis approach is more efficient and robust since templates describe phenotypic signatures common to cell populations in several samples while ignoring noise and small sample-specific variations. We have applied the template-based scheme to analyze several datasets, including one representing a healthy immune system and one of acute myeloid leukemia (AML) samples. The last task is challenging due to the phenotypic heterogeneity of the several subtypes of AML. However, we identified thirteen immunophenotypes corresponding to subtypes of AML and were able to distinguish acute promyelocytic leukemia (APL) samples with the markers provided. Clinically, this is helpful since APL has a different treatment regimen from other subtypes of AML. Core algorithms used in our data analysis are available in the flowMatch package at www.bioconductor.org. It has been downloaded nearly 6,000 times since 2014.

Photonic reagents for concentration measurement of flu-orescent proteins with overlapping spectra

By exploiting photonic reagents (i.e., coherent control by shaped laser pulses), we employ Optimal Dynamic Discrimination (ODD) as a novel means for quantitatively characterizing mixtures of fluorescent proteins with a large spectral overlap. To illustrate ODD, we simultaneously measured concentrations of in vitro mixtures of Enhanced Blue Fluorescent Protein (EBFP) and Enhanced Cyan Fluorescent Protein (ECFP). Building on this foundational study, the ultimate goal is to exploit the capabilities of ODD for parallel monitoring of genetic and protein circuits by suppressing the spectral cross-talk among multiple fluorescent reporters.

Nucleotide Excision Repair and Transcription-coupled DNA Repair Abrogate the Impact of DNA Damage on Transcription

DNA adducts derived from carcinogenic polycyclic aromatic hydrocarbons like benzo[a]pyrene (B[a]P) and benzo[c]phenanthrene (B[c]Ph) impede replication and transcription, resulting in aberrant cell division and gene expression. Global nucleotide excision repair (NER) and transcription-coupled DNA repair (TCR) are among the DNA repair pathways that evolved to maintain genome integrity by removing DNA damage. The interplay between global NER and TCR in repairing the polycyclic aromatic hydrocarbon-derived DNA adducts (+)-trans-anti-B[a]P-N(6)-dA, which is subject to NER and blocks transcription in vitro, and (+)-trans-anti-B[c]Ph-N(6)-dA, which is a poor substrate for NER but also blocks transcription in vitro, was tested. The results show that both adducts inhibit transcription in human cells that lack both NER and TCR. The (+)-trans-anti-B[a]P-N(6)-dA lesion exhibited no detectable effect on transcription in cells proficient in NER but lacking TCR, indicating that NER can remove the lesion in the absence of TCR, which is consistent with in vitro data. In primary human cells lacking NER, (+)-trans-anti-B[a]P-N(6)-dA exhibited a deleterious effect on transcription that was less severe than in cells lacking both pathways, suggesting that TCR can repair the adduct but not as effectively as global NER. In contrast, (+)-trans-anti-B[c]Ph-N(6)-dA dramatically reduces transcript production in cells proficient in global NER but lacking TCR, indicating that TCR is necessary for the removal of this adduct, which is consistent with in vitro data showing that it is a poor substrate for NER. Hence, both global NER and TCR enhance the recovery of gene expression following DNA damage, and TCR plays an important role in removing DNA damage that is refractory to NER.

A structural and genotypic scaffold underlying temporal integration

The accumulation and storage of information over time, temporal integration, is key to numerous behaviors. Many oculomotor tasks depend on integration of eye-velocity signals to eye-position commands, a transformation achieved by a hindbrain cell group termed the velocity-to-position neural integrator (VPNI). Although the VPNI's coding properties have been well characterized, its mechanism of function remains poorly understood because few links exist between neuronal activity, structure, and genotypic identity. To fill this gap, we used calcium imaging and single-cell electroporation during oculomotor behaviors to map VPNI neural activity in zebrafish onto a hindbrain scaffold consisting of alternating excitatory and inhibitory parasagittal stripes. Three distinct classes of VPNI cells were identified. One glutamatergic class was medially located along a stripe associated with the alx transcription factor; these cells had ipsilateral projections terminating near abducens motoneurons and collateralized extensively within the ipsilateral VPNI in a manner consistent with integration through recurrent excitation. A second glutamatergic class was more laterally located along a stripe associated with transcription factor dbx1b; these glutamatergic cells had contralateral projections collateralizing near abducens motoneurons, consistent with a role in disconjugate eye movements. A third class, immunohistochemically suggested to be GABAergic, was located primarily in the dbx1b stripe and also had contralateral projections terminating near abducens motoneurons; these cells collateralized extensively in the dendritic field of contralateral VPNI neurons, consistent with a role in coordinating activity between functionally opposing populations. This mapping between VPNI activity, structure, and genotype may provide a blueprint for understanding the mechanisms governing temporal integration.

Polystyrene microspheres enable 10-color compensation for immunophenotyping of primary human leukocytes

Compensation is a critical process for the unbiased analysis of flow cytometry data. Numerous compensation strategies exist, including the use of bead‐based products. The purpose of this study was to determine whether beads, specifically polystyrene microspheres (PSMS) compare to the use of primary leukocytes for single color based compensation when conducting polychromatic flow cytometry. To do so, we stained individual tubes of both PSMS and leukocytes with panel specific antibodies conjugated to fluorochromes corresponding to fluorescent channels FL1‐FL10. We compared the matrix generated by PSMS to that generated using peripheral blood mononuclear cells (PBMC). Ideal for compensation is a sample with both a discrete negative population and a bright positive population. We demonstrate that PSMS display autofluorescence properties similar to PBMC. When comparing PSMS to PBMC for compensation PSMS yielded more evenly distributed and discrete negative and positive populations to use for compensation. We analyzed three donors' PBMC stained with our 10‐color T cell subpopulation panel using compensation generated by PSMS vs.PBMC and detected no significant differences in the population distribution. Panel specific antibodies bound to PSMS represent an invaluable valid tool to generate suitable compensation matrices especially when sample material is limited and/or the sample requires analysis of dynamically modulated or rare events. © 2015 The Authors. Cytometry Part A Published by Wiley Periodicals, Inc.