Flow cytometry: past and future

Flow cytometry in acute myeloid leukemia and detection of minimal residual disease

Acute myeloid leukemia (AML) is a common type of acute leukemia (AL), belonging to malignant tumors of the hematopoietic system with the characteristics of rapid disease development, control with extreme difficulties, easy recurrence, poor prognosis, and incidence rate increasing with age. The traditionally diagnostic standard of French American British (FAB), being based on the morphological examination with high human subjectivity, can no longer meet the demand of clinical diagnosis and treatment of AML. Requirements of objective accuracy and low-dose sample, have become the indispensable method for AML diagnosis and monitoring prognosis. Flow cytometry is a modern technology that can quickly and accurately detect the series, antigen distribution, differentiation stage of AML cells, minimal residual lesions after AML therapy, so as to provide the great significance in guiding clinical diagnosis, hierarchical treatment, and prognosis judgement. This article will systematically elaborate on the application of flow cytometry in the diagnosis and classification of AML, and the detection of minimal residual lesions, thereby providing reference significance for dynamic monitoring and prognostic observation of AML with different immune subtypes of FAB.

Discovering microbiota functions via chemical probe incorporation for targeted sequencing

Our microbiota plays crucial roles in immune development and homeostasis and has been implicated in virtually all major diseases of the 21st century. Nevertheless, our understanding of the exact microbial functions that underlie these correlations remains extremely limited, due in large part to the difficulty of profiling cellular activities within non-model organisms and complex communities. Over the past decade, new flow cytometric approaches have been developed to distinguish specific microbial populations based on their interactions with metabolite analogs, modified biomolecules, and reactive compounds. By selecting and separating active microbes via fluorescence-activated cell sorting, PRobe INcorporation for Targeted sequencing (PRINT-seq) has inspired innovative approaches to identify and characterize functional members of our microbiota. Here, we provide a broad overview of this evolving technology and summarize how this method has been recently employed as a diagnostic fingerprint for diverse microbial activities.

Unlocking the Complexity: Exploration of Acute Lymphoblastic Leukemia at the Single Cell Level

Acute lymphoblastic leukemia (ALL) is the most common cancer in children. ALL originates from precursor lymphocytes that acquire multiple genomic changes over time, including chromosomal rearrangements and point mutations. While a large variety of genomic defects was identified and characterized in ALL over the past 30 years, it was only in recent years that the clonal heterogeneity was recognized. Thanks to the latest advancements in single-cell sequencing techniques, which have evolved from the analysis of a few hundred cells to the analysis of thousands of cells simultaneously, the study of tumor heterogeneity now becomes possible. Different modalities can be explored at the single-cell level: DNA, RNA, epigenetic modifications, and intracellular and cell surface proteins. In this review, we describe these techniques and highlight their advantages and limitations in the study of ALL biology. Moreover, multiomics technologies and the incorporation of the spatial dimension can provide insight into intercellular communication. We describe how the different single-cell sequencing technologies help to unravel the molecular complexity of ALL, shedding light on its development, its heterogeneity, its interaction with the leukemia microenvironment and possible relapse mechanisms.

Spectral Algal Fingerprinting and Long Sequencing in Synthetic Algal-Microbial Communities

Synthetic biology has advanced in creating artificial microbial and algal communities, but technical and evolutionary complexities still pose significant challenges. Traditional methods, like microscopy and pigment analysis, are limited in throughput and resolution. In contrast, advancements in full-spectrum cytometry enabled high-throughput, multidimensional analysis of single cells based on size, complexity, and spectral fingerprints, offering more precision and flexibility than conventional flow cytometry. This study uses full-spectrum cytometry to analyze synthetic algal-microbial communities, enabling rapid species identification and enumeration. The workflow involves recording individual spectral signatures from monocultures, using autofluorescence to capture populations of interest, and creating a spectral library for further analysis. This spectral library was used for the analysis of the synthetic phytoplankton communities, revealing differences in spectral signatures. Moreover, the synthetic consortium experiment monitored algal growth, comparing results from different instruments, highlighting the advantages of the spectral virtual filter system for precise population separation and abundance tracking. By capturing the entire emission spectrum of each cell, this method enhances understanding of algal-microbial community dynamics and responses to environmental stressors. The development of standardized spectral libraries would improve the characterization of algal communities, further advancing synthetic biology and phytoplankton ecology research.

Fast and quantitative mitophagy assessment by flow cytometry using the mito-QC reporter

Mitochondrial quality control is finely tuned by mitophagy, the selective degradation of mitochondria through autophagy, and mitochondrial biogenesis. Removal of damaged mitochondria is essential to preserve cellular bioenergetics and prevent detrimental events such as sustained mitoROS production, pro-apoptotic cytochrome c release or mtDNA leakage. The array of tools available to study mitophagy is very limited but in constant development. Almost a decade ago, we developed a method to assess mitophagy flux using MitoTracker Deep Red in combination with lysosomal inhibitors. Now, using the novel tandem-fluorescence reporter mito-QC (mCherry-GFP-FIS1101-152) that allows to differentiate between healthy mitochondria (mCherry+GFP+) and mitolysosomes (mCherry+GFP-), we have developed a robust and quantitative method to assess mitophagy by flow cytometry. This approach has been validated in ARPE-19 cells using PINK1/Parkin-dependent (CCCP) and PINK1/Parkin-independent (DFP) positive controls and complementary techniques. Furthermore, we show that the mito-QC reporter can be multiplexed, especially if using spectral flow cytometry, to simultaneously study other cellular parameters such as viability or ROS production. Using this technique, we evaluated and characterized two prospective mitophagy inducers and further dissected their mechanism of action. Finally, using mito-QC reporter mice, we developed a protocol to measure mitophagy levels in the retina ex vivo. This novel methodology will propel mitophagy research forward and accelerate the discovery of novel mitophagy modulators.

High-throughput fluorescence lifetime imaging flow cytometry

Flow cytometry is a vital tool in biomedical research and laboratory medicine. However, its accuracy is often compromised by undesired fluctuations in fluorescence intensity. While fluorescence lifetime imaging microscopy (FLIM) bypasses this challenge as fluorescence lifetime remains unaffected by such fluctuations, the full integration of FLIM into flow cytometry has yet to be demonstrated due to speed limitations. Here we overcome the speed limitations in FLIM, thereby enabling high-throughput FLIM flow cytometry at a high rate of over 10,000 cells per second. This is made possible by using dual intensity-modulated continuous-wave beam arrays with complementary modulation frequency pairs for fluorophore excitation and acquiring fluorescence lifetime images of rapidly flowing cells. Moreover, our FLIM system distinguishes subpopulations in male rat glioma and captures dynamic changes in the cell nucleus induced by an anti-cancer drug. FLIM flow cytometry significantly enhances cellular analysis capabilities, providing detailed insights into cellular functions, interactions, and environments.

Flow Cytometric Assessment of Malignant Hematologic Disorders

Multiparameter flow cytometry (MPF) is an essential component of the diagnostic workup of hematologic malignancies. Recently developed tools have expanded the utility of MPF in detecting T-cell clonality and myelomonocytic dysplasia. Minimal/measurable residual disease analysis has long been established as critical in the management of B-lymphoblastic leukemia and is emerging as a useful tool in myeloid malignancies. With the continued increased complexity of MPF assays, emerging tools for data collection and analysis will allow users to take full advantage of MPF in the diagnosis of hematologic disease.

Spiramycin-loaded maltodextrin nanoparticles as a promising treatment of toxoplasmosis on murine model

Despite being the initial choice for treating toxoplasmosis, sulfadiazine and pyrimethamine have limited effectiveness in eliminating the infection and were linked to a variety of adverse effects. Therefore, the search for new effective therapeutic strategies against toxoplasmosis is still required. The current work is the first research to assess the efficacy of spiramycin-loaded maltodextrin nanoparticles (SPM-loaded MNPs) as a novel alternative drug therapy against toxoplasmosis in a murine model. Fifty laboratory-bred Swiss albino mice were divided into five groups: normal control group (GI, n = 10), positive control group (GII, n = 10), orally treated with spiramycin (SPM) alone (GIII, n = 10), intranasal treated with SPM-loaded MNPs (GIV, n = 10), and orally treated with SPM-loaded MNPs (GV, n = 10). Cysts of Toxoplasma gondii ME-49 strain were used to infect the mice. Tested drugs were administered 2 months after the infection. Drug efficacy was assessed by counting brain cysts, histopathological examination, and measures of serum CD19 by flow cytometer. The orally treated group with SPM-loaded MNPs (GV) showed a marked reduction of brain cyst count (88.7%), histopathological improvement changes, and an increasing mean level of CD19 (80.2%) with significant differences. SPM-loaded MNPs showed potent therapeutic effects against chronic toxoplasmosis. Further research should be conducted to assess it in the treatment of human toxoplasmosis, especially during pregnancy.

Water-Soluble Fluorescent Polymer Dyes with Tunable Emission Spectra for Flow Cytometry Applications

The application of spectrally unique, bright, and water-soluble fluorescent dyes is indispensable for the analysis of biological systems. Multiparameter flow cytometry is a powerful tool for characterization of mixed cell populations. To discriminate the different cell populations, they are typically stained by a set of fluorescent reagents, e.g., antibody-fluorophore conjugates. The number of parameters which can be studied simultaneously strongly depends on the availability of reagents which can be differentiated by their spectral properties. In this study a series of fluorescent polymer dyes was developed, that can be excited with a single violet laser (405 nm) but distinguished by their unique emission spectra. The polyfluorene-based polymers can be used on their own, or in combination with covalently bound small-molecule dyes to generate energy transfer constructs to red-shift the emission wavelength based on Förster resonance energy transfer (FRET). The polymer dyes were utilized in a biological flow cytometry assay by conjugating several of them to antibodies, demonstrating their effectiveness as reagents. This report represents the first systematic investigation of structure-property relationships for this type of fluorescent dyes.

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.

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.

Flow cytometry: Aspects and application in plant and biological science

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

Flow Cytometry and Its Applications to Molecular Biology and Diagnosis 2.0

Flow cytometry is a single-cell based technology aimed to quantify the scattering of light and the emission of multiple fluorescence signals by individual cells, biological vesicles, or synthetic microscopical particles when examined one by one at high speed using lasers or other suitable illumination sources [...].

Ethanolic Extract from Seed Residues of Sea Buckthorn (Hippophae rhamnoides L.) Ameliorates Oxidative Stress Damage and Prevents Apoptosis in Murine Cell and Aging Animal Models

Hippophae rhamnoides L. has been widely used in research and application for almost two decades. While significant progress was achieved in the examination of its fruits and seeds, the exploration and utilization of its by-products have received relatively less attention. This study aims to address this research gap by investigating the effects and underlying mechanisms of sea buckthorn seed residues both in vitro and in vivo. The primary objective of this study is to assess the potential of the hydroalcoholic extract from sea buckthorn seed residues (HYD-SBSR) to prevent cell apoptosis and mitigate oxidative stress damage. To achieve this, an H2O2-induced B16F10 cell model and a D-galactose-induced mouse model were used. The H2O2-induced oxidative stress model using B16F10 cells was utilized to evaluate the cellular protective and reparative effects of HYD-SBSR. The results demonstrated the cytoprotective effects of HYD-SBSR, as evidenced by reduced apoptosis rates and enhanced resistance to oxidative stress alongside moderate cell repair properties. Furthermore, this study investigated the impact of HYD-SBSR on antioxidant enzymes and peroxides in mice to elucidate its reparative potential in vivo. The findings revealed that HYD-SBSR exhibited remarkable antioxidant performance, particularly at low concentrations, significantly enhancing antioxidant capacity under oxidative stress conditions. To delve into the mechanisms underlying HYD-SBSR, a comprehensive proteomics analysis was conducted to identify differentially expressed proteins (DEPs). Additionally, a Gene Ontology (GO) analysis and an Encyclopedia of Genes and Genomes (KEGG) pathway cluster analysis were performed to elucidate the functional roles of these DEPs. The outcomes highlighted crucial mechanistic pathways associated with HYD-SBSR, including the PPAR signaling pathway, fat digestion and absorption, glycerophospholipid metabolism, and cholesterol metabolism. The research findings indicated that HYD-SBSR, as a health food supplement, exhibits favorable effects by promoting healthy lipid metabolism, contributing to the sustainable and environmentally friendly production of sea buckthorn and paving the way for future investigations and applications in the field of nutraceutical and pharmaceutical research.

Integrated flow cytometric and proteomics analyses reveal the regulatory network underlying sugarcane protoplast responses to fusion

BACKGROUND

Somatic cell fusion is a process that transfers cytoplasmic and nuclear genes to create new germplasm resources. But our limited understanding of the physiological and molecular mechanisms that shape protoplast responses to fusion.

METHOD

We employed flow cytometry, cytology, proteomics, and gene expression analysis to examine the sugarcane (Saccharum spp.) protoplast fusion.

RESULTS

Flow cytometry analysis revealed the fusion rate of protoplasts was 1.95%, the FSC value and SSC of heterozygous cells was 1.17-1.47 times higher than that of protoplasts. The protoplasts viability decreased and the MDA increased after fusion. During fusion, the cell membranes were perforated to different degrees, nuclear activity was weakened, while microtubules depolymerized and formed several short rod like structures in the protoplasts. The most abundant proteins during fusion were mainly involved in RNA processing and modification, cell cycle control, cell division, chromosome partition, nuclear structure, extracellular structures, and nucleotide transport and metabolism. Moreover, the expression of key regeneration genes, such as WUS, GAUT, CESA, PSK, Aux/IAA, Cdc2, Cyclin D3, Cyclin A, and Cyclin B, was significantly altered following fusion.

PURPOSE AND SIGNIFICANCE

Overall, our findings provide a theoretical basis that increases our knowledge of the mechanisms underlying protoplast fusion.

Label-Free Analysis of Urine Samples with In-Flow Digital Holographic Microscopy

Urinary tract infections are among the most frequent infectious diseases and require screening a great amount of urine samples from patients. However, a high percentage of samples result as negative after urine culture plate tests (CPTs), demanding a simple and fast preliminary technique to screen out the negative samples. We propose a digital holographic microscopy (DHM) method to inspect fresh urine samples flowing in a glass capillary for 3 min, recording holograms at 2 frames per second. After digital reconstruction, bacteria, white and red blood cells, epithelial cells and crystals were identified and counted, and the samples were classified as negative or positive according to clinical cutoff values. Taking the CPT as reference, we processed 180 urine samples and compared the results with those of urine flow cytometry (UFC). Using standard evaluation metrics for our screening test, we found a similar performance for DHM and UFC, indicating DHM as a suitable and fast screening technique retaining several advantages. As a benefit of DHM, the technique is label-free and does not require sample preparation. Moreover, the phase and amplitude images of the cells and other particles present in urine are digitally recorded and can serve for further investigation afterwards.

Understanding virus-host interactions in tissues

Although virus-host interactions are usually studied in a single cell type using in vitro assays in immortalized cell lines or isolated cell populations, it is important to remember that what is happening inside one infected cell does not translate to understanding how an infected cell behaves in a tissue, organ or whole organism. Infections occur in complex tissue environments, which contain a host of factors that can alter the course of the infection, including immune cells, non-immune cells and extracellular-matrix components. These factors affect how the host responds to the virus and form the basis of the protective response. To understand virus infection, tools are needed that can profile the tissue environment. This Review highlights methods to study virus-host interactions in the infection microenvironment.

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.

Microsystem Advances through Integration with Artificial Intelligence

Microfluidics is a rapidly growing discipline that involves studying and manipulating fluids at reduced length scale and volume, typically on the scale of micro- or nanoliters. Under the reduced length scale and larger surface-to-volume ratio, advantages of low reagent consumption, faster reaction kinetics, and more compact systems are evident in microfluidics. However, miniaturization of microfluidic chips and systems introduces challenges of stricter tolerances in designing and controlling them for interdisciplinary applications. Recent advances in artificial intelligence (AI) have brought innovation to microfluidics from design, simulation, automation, and optimization to bioanalysis and data analytics. In microfluidics, the Navier-Stokes equations, which are partial differential equations describing viscous fluid motion that in complete form are known to not have a general analytical solution, can be simplified and have fair performance through numerical approximation due to low inertia and laminar flow. Approximation using neural networks trained by rules of physical knowledge introduces a new possibility to predict the physicochemical nature. The combination of microfluidics and automation can produce large amounts of data, where features and patterns that are difficult to discern by a human can be extracted by machine learning. Therefore, integration with AI introduces the potential to revolutionize the microfluidic workflow by enabling the precision control and automation of data analysis. Deployment of smart microfluidics may be tremendously beneficial in various applications in the future, including high-throughput drug discovery, rapid point-of-care-testing (POCT), and personalized medicine. In this review, we summarize key microfluidic advances integrated with AI and discuss the outlook and possibilities of combining AI and microfluidics.

Evaluation of volume-based flow cytometry as a potential primary method for quantification of bacterial reference material

Bacterial reference materials (RMs) play a crucial role in many analytical processes of microbiological detection. Currently, bacteria are typically counted using the traditional plate-based approach, which results in a higher uncertainty of bacterial RMs unfortunately. Therefore, novel methods are urgently required for the value assignment of RMs in the field of microbiology to derive measurement traceability and accuracy. A potential primary method for microbiological quantification based on flow cytometry (FCM) is described in this study using Escherichia coli O157 (E. coli O157) as an example. The proposed method was applied to determine the number of viable E. coli O157 cells in the RMs with a result of (5.48 ± 0.27) × 10⁸ cells mL^-1, which was in good agreement with the result obtained using the plate-based method (E_n = 0.47). Additionally, this method could be entirely described and understood by equations, and provides formal traceability to the SI for counts of viable bacterial cells, while the associated relative expanded uncertainty (4.93%, k = 2) was significantly lower in comparison to the plate-based method. Therefore, the FCM-based method might be a potential primary method for characterizing bacterial RMs. To our knowledge, this is the first description of FCM as a potential primary method for accurate and traceable quantification of viable bacterial cells with a comprehensive uncertainty statement in microbiological metrology.

Analysis of Salmonella lineage-specific traits upon cell sorting

Microbial cell individuality is receiving increasing interest in the scientific community. Individual cells within clonal populations exhibit noticeable phenotypic heterogeneity. The advent of fluorescent protein technology and advances in single-cell analysis has revealed phenotypic cell variant in bacterial populations. This heterogeneity is evident in a wide range of phenotypes, for example, individual cells display variable degrees of gene expression and survival under selective conditions and stresses, and can exhibit differing propensities to host interactions. Last few years, numerous cell sorting approaches have been employed for resolving the properties of bacterial subpopulations. This review provides an overview of applications of cell sorting to analyze Salmonella lineage-specific traits, including bacterial evolution studies, gene expression analysis, response to diverse cellular stresses and characterization of diverse bacterial phenotypic variants.

Gold-nanoparticle-embedded hydrogel droplets with enhanced fluorescence for imaging and quantification of proteins in cells

Conventional cellular protein detection techniques such as immunocytochemistry and flow cytometry require abundant cells, posing multiple challenges, including difficulty and cost for obtaining enough cells and the potential for clogging the instrument when using flow cytometry. Also, it is challenging to conduct cellular protein imaging and quantification simultaneously from a single experiment. We present a novel 3D platform, which integrates highly biocompatible cell-entrapped alginate hydrogel droplet array with gold-nanoparticle (AuNP)-based metal enhanced fluorescence (MEF), to achieve simultaneous imaging and quantification of proteins in intact cells in a sensitive manner. Compared to 2D immunocytochemistry, this 3D system allows for a higher cell loading capacity per unit area; together with the MEF-based signal enhancement from the embedded AuNPs, sensitive protein quantification was realized. Furthermore, compared to flow cytometry, this platform allows for protein imaging from individual cells. Taking the detection of EpCAM protein in ovarian cancer cells as a model, we optimized the AuNP size and concentration for optimal fluorescent signals. The 5 nm AuNPs at 6.54 × 10¹³ particles/mL proved to be the most effective in signal enhancement, providing 2.4-fold higher signals compared to that without AuNPs and 6.4-fold higher signals than that of 2D immunocytochemistry. The number of cells required in our technology is 1-3 orders of magnitude smaller than that of conventional methods. This AuNP-embedded hydrogel platform combines the benefits of immunocytochemistry and flow cytometry, providing increased assay sensitivity while also allowing for qualitative analysis through imaging, suitable for protein determination in a variety of cells.

A report on a modified protocol for flow cytometry-based assessment of blood group erythrocyte antigens potentially suitable for analysis of weak ABO subgroups

BACKGROUND

Flow cytometry (FC) has proven its utility in scrutinizing AB antigen expression in red blood cells (RBCs), cooperating with serological tests for accurate blood group typing. However, technical difficulties may impair the characterization of weak ABO subtypes when background noises appear at non-negligible levels.

STUDY DESIGN AND METHODS

We sought to establish an FC method that could prevent antibody-induced hemagglutination and an increase in cellular autofluorescence, two major issues inherent to RBC-FC analysis of AB expression. We optimized fixatives, multicolor-staining protocols, and sequential gating strategies. Blood samples from weak ABO subtype cases, B_m and A_el , were analyzed with the established protocol.

RESULTS

The optimized mixture of glutaraldehyde and formaldehyde successfully generated fixed RBCs resistant to agglutination while maintaining low autofluorescence. These features allowed co-staining of leukocyte- and erythrocyte-markers, which enabled sequential gating strategies facilitating the precise AB antigen analysis in purely single RBCs with minimum background noises. By the established FC analysis, we could detect in the B_m sample a small RBC population exhibiting weak B antigen expression. The assay also proved it feasible to identify a small population (0.04%) of RBCs weakly expressing the A antigen in the A_el sample confirmed as harboring a rare c.816dupG ABO variant allele.

CONCLUSION

The RBC-FC analysis described here allows the detection of AB antigens weakly expressed in RBCs while achieving minimum background noise levels in negative control samples. Overall, the modified protocol provides a quick and reliable assay valuable in transfusion medicine and is potentially applicable to the characterization of rare weak ABO variants.

Advanced immunophenotyping: A powerful tool for immune profiling, drug screening, and a personalized treatment approach

Various autoimmune diseases are characterized by distinct cell subset distributions and activation profiles of peripheral blood mononuclear cells (PBMCs). PBMCs can therefore serve as an ideal biomarker material, which is easily accessible and allows for screening of multiple cell types. A detailed understanding of the immune landscape is critical for the diagnosis of patients with autoimmune diseases, as well as for a personalized treatment approach. In our study, we investigate the potential of multi-parameter spectral flow cytometry for the identification of patients suffering from autoimmune diseases and its power as an evaluation tool for in vitro drug screening approaches (advanced immunophenotyping). We designed a combination of two 22-color immunophenotyping panels for profiling cell subset distribution and cell activation. Downstream bioinformatics analyses included percentages of individual cell populations and median fluorescent intensity of defined markers which were then visualized as heatmaps and in dimensionality reduction approaches. In vitro testing of epigenetic immunomodulatory drugs revealed an altered activation status upon treatment, which supports the use of spectral flow cytometry as a high-throughput drug screening tool. Advanced immunophenotyping might support the exploration of novel therapeutic drugs and contribute to future personalized treatment approaches in autoimmune diseases and beyond.

Tumor-Associated Macrophages and Related Myelomonocytic Cells in the Tumor Microenvironment of Multiple Myeloma

Multiple myeloma (MM) is the second-most common hematologic malignancy and remains incurable despite potent plasma cell directed therapeutics. The tumor microenvironment (TME) is a key player in the pathogenesis and progression of MM and is an active focus of research with a view to targeting immune dysregulation. Tumor-associated macrophages (TAM), myeloid derived suppressor cells (MDSC), and dendritic cells (DC) are known to drive progression and treatment resistance in many cancers. They have also been shown to promote MM progression and immune suppression in vitro, and there is growing evidence of their impact on clinical outcomes. The heterogeneity and functional characteristics of myelomonocytic cells in MM are being unraveled through high-dimensional immune profiling techniques. We are also beginning to understand how they may affect and be modulated by current and future MM therapeutics. In this review, we provide an overview of the biology and clinical relevance of TAMs, MDSCs, and DCs in the MM TME. We also highlight key areas to be addressed in future research as well as our perspectives on how the myelomonocytic compartment of the TME may influence therapeutic strategies of the future.

Glioma Stem Cells: Novel Data Obtained by Single-Cell Sequencing

Glioma is the most common type of primary CNS tumor, composed of cells that resemble normal glial cells. Recent genetic studies have provided insight into the inter-tumoral heterogeneity of gliomas, resulting in the updated 2021 WHO classification of gliomas. Thorough understanding of inter-tumoral heterogeneity has already improved the prognosis and treatment outcomes of some types of gliomas. Currently, the challenge for researchers is to study the intratumoral cell heterogeneity of newly defined glioma subtypes. Cancer stem cells (CSCs) present in gliomas and many other tumors are an example of intratumoral heterogeneity of great importance. In this review, we discuss the modern concept of glioma stem cells and recent single-cell sequencing-driven progress in the research of intratumoral glioma cell heterogeneity. The particular emphasis was placed on the recently revealed variations of the cell composition of the subtypes of the adult-type diffuse gliomas, including astrocytoma, oligodendroglioma and glioblastoma. The novel data explain the inconsistencies in earlier glioma stem cell research and also provide insight into the development of more effective targeted therapy and the cell-based immunotherapy of gliomas. Separate sections are devoted to the description of single-cell sequencing approach and its role in the development of cell-based immunotherapies for glioma.

Emerging insights and challenges for understanding T cell function through the proteome

T cells rapidly transition from a quiescent state into active proliferation and effector function upon exposure to cognate antigen. These processes are tightly controlled by signal transduction pathways that influence changes in chromatin remodeling, gene transcription, and metabolism, all of which collectively drive specific T cell memory or effector cell development. Dysregulation of any of these events can mediate disease and the past several years has shown unprecedented novel approaches to understand these events, down to the single-cell level. The massive explosion of sequencing approaches to assess the genome and transcriptome at the single cell level has transformed our understanding of T cell activation, developmental potential, and effector function under normal and various disease states. Despite these advances, there remains a significant dearth of information regarding how these events are translated to the protein level. For example, resolution of protein isoforms and/or specific post-translational modifications mediating T cell function remains obscure. The application of proteomics can change that, enabling significant insights into molecular mechanisms that regulate T cell function. However, unlike genomic approaches that have enabled exquisite visualization of T cell dynamics at the mRNA and chromatin level, proteomic approaches, including those at the single-cell level, has significantly lagged. In this review, we describe recent studies that have enabled a better understanding of how protein synthesis and degradation change during T cell activation and acquisition of effector function. We also highlight technical advances and how these could be applied to T cell biology. Finally, we discuss future needs to expand upon our current knowledge of T cell proteomes and disease.

Optimized Protocol for Microalgae DNA Staining with SYTO9/SYBR Green I, Based on Flow Cytometry and RSM Methodology: Experimental Design, Impacts and Validation

Multiple fluorochromes are extensively used to investigate different microalgal aspects, such as viability and physiology. Some of them can be used to stain nucleic acids (DNA). Well-known examples are SYBR Green I and SYTO 9, the latter of which offers several advantages, especially when combined with flow cytometry (FCM)—a powerful method for studying microalgal population heterogeneity and analyzing their cell cycles. However, the effects of these dyes on the microalgae cell physiology have not been fully elucidated yet. A statistical experimental design, using response surface methodology (RSM) with FCM was applied in this study to optimize the DNA staining of a non-conventional microalgae, Chromochloris zofingiensis, with SYBR Green I and SYTO 9, and to optimize the variables affecting staining efficiency, i.e., the dye concentration, incubation time and staining temperature. We found that none of these factors affects the staining efficiency, which was not less than 99.65%. However, for both dyes, the dye concentration was shown to be the most significant factor causing cell damage (p-values: 0.0003; <0.0001) for SYBR Green I and SYTO 9, respectively. The staining temperature was only significant for SYTO 9 (p-value: 0.0082), and no significant effect was observed regarding the incubation time for both dyes. The values of the optimized parameters (0.5 µM, 05 min and 25 °C) for SYTO 9 and (0.5 X, 5 min and 25 °C) for SYBR Green I resulted in the maximum staining efficiency (99.8%; 99.6%), and the minimum damaging effects (12.86%; 13.75%) for SYTO 9 and SYBR Green I, respectively. These results offer new perspectives for improving the use of DNA staining fluorochromes and provides insights into their possible side effects on microalgae.

Involvement of TLR2-TLR4, NLRP3, and IL-17 in pain induced by a novel Sprague-Dawley rat model of experimental autoimmune encephalomyelitis

Up to 92% of patients suffering from multiple sclerosis (MS) experience pain, most without adequate treatment, and many report pain long before motor symptoms associated with MS diagnosis. In the most commonly studied rodent model of MS, experimental autoimmune encephalomyelitis (EAE), motor impairments/disabilities caused by EAE can interfere with pain testing. In this study, we characterize a novel low-dose myelin-oligodendrocyte-glycoprotein (MOG)-induced Sprague-Dawley (SD) model of EAE-related pain in male rats, optimized to minimize motor impairments/disabilities. Adult male SD rats were treated with increasing doses of intradermal myelin-oligodendrocyte-glycoprotein (MOG1-125) (0, 4, 8, and 16 μg) in incomplete Freund's adjuvant (IFA) vehicle to induce mild EAE. Von Frey testing and motor assessments were conducted prior to EAE induction and then weekly thereafter to assess EAE-induced pain and motor impairment. Results from these studies demonstrated that doses of 8 and 16 μg MOG1-125 were sufficient to produce stable mechanical allodynia for up to 1 month in the absence of hindpaw motor impairments/disabilities. In the follow-up studies, these doses of MOG1-125, were administered to create allodynia in the absence of confounded motor impairments. Then, 2 weeks later, rats began daily subcutaneous injections of the Toll-like receptor 2 and 4 (TLR2-TLR4) antagonist (+)-naltrexone [(+)-NTX] or saline for an additional 13 days. We found that (+)-NTX also reverses EAE-induced mechanical allodynia in the MOG-induced SD rat model of EAE, supporting parallels between models, but now allowing a protracted timecourse to be examined completely free of motor confounds. Exploring further mechanisms, we demonstrated that both spinal NOD-like receptor protein 3 (NLRP3) and interleukin-17 (IL-17) are necessary for EAE-induced pain, as intrathecal injections of NLRP3 antagonist MCC950 and IL-17 neutralizing antibody both acutely reversed EAE-induced pain. Finally, we show that spinal glial immunoreactivity induced by EAE is reversed by (+)-NTX, and that spinal demyelination correlates with the severity of motor impairments/disabilities. These findings characterize an optimized MOG-induced SD rat model of EAE for the study of pain with minimal motor impairments/disabilities. Finally, these studies support the role of TLR2-TLR4 antagonists as a potential treatment for MS-related pain and other pain and inflammatory-related disorders.

Revealing the Dynamics of Mitochondrial Microenvironment during Apoptosis under Two-photon Fluorescence Lifetime Microscopy by a Cyclic Iridium (III) Complex

Mitochondria-mediated apoptosis is a major mode of cell death and is inextricably linked to various pathological processes such as tumorigenesis. However, there is still a paucity of non-toxic tools that...