Flow cytometry and laser scanning cytometry, a comparison of techniques

The effects of incubation media on the assessment of the shape of human erythrocytes by flow cytometry: a contribution to mathematical data interpretation to enable wider application of the method

Flow cytometry (FC) analysis of erythrocyte shape and related biomechanical properties, such as osmotic fragility, have not moved from a research tool to regular clinical testing. The main reason is existing evidence that various pre-analytical factors influence the mathematical interpretation of the data obtained. With an aim to contribute to the standardization and broaden the use of FC for human erythrocyte shape assessment, freshly prepared peripheral blood erythrocytes isolated from healthy donors were incubated in iso and hypo-osmotic solutions (pure saline, saline with potassium and calcium, and phosphate buffered saline) and examined by FC using values of forward scatter (FSC) and side scatter (SSC). Kurtosis, skewness, Pearson's second skewness coefficient of dissymmetry (PCD), and spherical index, calculated from FSC distributions, were used for the erythrocyte shape evaluation. In all isotonic media FSC distribution and FSC-based morphology parameters showed huge inter-individual and inter-medium variation. With decreasing osmolality, in all media and samples, the size of the erythrocytes increased, and swelling index and kurtosis decreased. However, changes in skewness and PCD were influenced by the medium used and the sample tested. Compared to FSC, SSC signal in isotonic and its change in hypotonic media showed lower inter-individual variation and was not influenced by the type of medium. We propose a spherical index and kurtosis as FSC-based indicators of erythrocyte shape. As more resistant to the influence of the preanalytical treatment, SSC data appeared to be unfairly neglected for the assessment of erythrocyte shape, in comparison to the usually employed FSC data.

Pollen analysis using multispectral imaging flow cytometry and deep learning

Pollen identification and quantification are crucial but challenging tasks in addressing a variety of evolutionary and ecological questions (pollination, paleobotany), but also for other fields of research (e.g. allergology, honey analysis or forensics). Researchers are exploring alternative methods to automate these tasks but, for several reasons, manual microscopy is still the gold standard. In this study, we present a new method for pollen analysis using multispectral imaging flow cytometry in combination with deep learning. We demonstrate that our method allows fast measurement while delivering high accuracy pollen identification. A dataset of 426 876 images depicting pollen from 35 plant species was used to train a convolutional neural network classifier. We found the best-performing classifier to yield a species-averaged accuracy of 96%. Even species that are difficult to differentiate using microscopy could be clearly separated. Our approach also allows a detailed determination of morphological pollen traits, such as size, symmetry or structure. Our phylogenetic analyses suggest phylogenetic conservatism in some of these traits. Given a comprehensive pollen reference database, we provide a powerful tool to be used in any pollen study with a need for rapid and accurate species identification, pollen grain quantification and trait extraction of recent pollen.

Influence of different methods and anticoagulants on platelet parameter measurement

Platelets are the smallest and perhaps the most versatile components of human blood. Besides their role in coagulation and the maintenance of vascular integrity, they are involved in many physiological processes, ranging from immune response and leukocyte recruitment to the production of antimicrobial peptides and immune-suppressive factors like TGF-β. These versatile abilities make platelets interesting for researchers from different disciplines. However, beside profound investigation into platelets’ physiological role, there is a need for correct, standardized and thus reproducible quantification of platelet parameters. Mean platelet volume (MPV) is a widespread prognostic marker for several conditions, such as, acute coronary syndrome, chronic kidney disease and liver cirrhosis. Platelet activation is regarded as a marker for inflammatory processes, for example in autoimmune diseases such as type-1 diabetes, systemic lupus erythematosus and rheumatoid arthritis. The monitoring of platelet function is relevant for patients receiving antiplatelet medication. Platelet parameter measurement is affected by the choice of in vitro anticoagulant, the measurement technology and the time delay after sampling. This review focuses on the pre-analytical variability that arises as a result of the use of different in vitro anticoagulants and analyzer technologies when determining platelet parameters, since, even approximately 180 years after the discovery of platelets, there is still no standardized procedure.

The Effects of Different Fluorescent Indicators in Observing the Changes of the Mitochondrial Membrane Potential during Oxidative Stress-Induced Mitochondrial Injury of Cardiac H9c2 Cells

We evaluated the ability of different fluorescent indicators by various analytical instruments, including a laser scanning confocal microscope (LSCM), fluorescence plate reader, and flow cytometer (FCM), to measure the mitochondrial membrane potential (ΔΨm) of cardiac H9c2 cells during oxidative stress-induced mitochondrial injury. The mitochondrial oxygen consumption rate and a transmission electron microscope were used to detect changes in mitochondrial functions and morphology, respectively. Cardiac H9c2 cells were exposed to H₂O₂ (500, 750, 1000, and 1250 μM) to induce mitochondrial oxidative stress injury, and fluorescent indicators including tetramethyl rhodamine ethyl ester (TMRE), 5,5',6,6'-tetrachloro-1,1',3,3'-tetraethylbenzimidazolocarbocyanine iodide (JC-1), and rhodamine 123 (R123) were used to detect changes in ΔΨm using an LSCM, fluorescence plate reader, and FCM. The decrease in ΔΨm caused by H₂O₂ was determined by endpoint and dynamic analyses after staining with JC-1 or TMRE. With the R123 probe, the LSCM could only detect the change in ΔΨm caused by 1000 μM H₂O₂. Moreover, R123 was less effective than JC-1 and TMRE for measurement of ΔΨm by the LSCM. Our data indicated that an LSCM is the most suitable instrument to detect dynamic changes in ΔΨm, whereas all three instruments can detect ΔΨm at the endpoint.

Prognostic significance of S-phase fractions in peritumoral invading zone analyzed by laser scanning cytometry in patients with high-grade glioma: A preliminary study

The predominant characteristic of malignant glioma is the presence of invading tumor cells in the peritumoral zone. Distinguishing between tumor cells and normal cells in a peritumoral lesion is challenging. Therefore, the aim of the present study was to investigate the cell-cycle phase measurements of fixed paraffin-embedded specimens from the peritumoral invading zone of high-grade gliomas using laser scanning cytometry. A total of 12 high-grade gliomas (2 anaplastic astrocytomas and 10 glioblastomas) were studied. The tumor core and peritumoral invading zone of each tumor specimen were investigated. Tissue sections (50 µm) from the paraffin blocks were deparaffinized, rehydrated and enzymatically disintegrated, and the cells in suspension were stained with propidium iodide and placed on microscope slides. A slight trend for an increased S-phase fraction in the peritumoral invading zone compared with the tumor core was observed (P=0.24). Additionally, there was a trend for a decrease in the overall survival time of patients with increasing peritumoral invading zone S-phase fraction (P=0.12). These data suggest that laser scanning cytometry is a powerful and clinically relevant tool for the objective analysis of the cell cycle in malignant gliomas.

Recent developments in proteomic methods and disease biomarkers

Proteomic methodologies for identification and analysis of biomarkers have gained more attention during recent years and have evolved rapidly. Identification and detection of disease biomarkers are important to foresee outbreaks of certain diseases thereby avoiding surgery and other invasive and expensive medical treatments for patients. Thus, more research into discovering new biomarkers and new methods for faster and more accurate detection is needed. It is often difficult to detect and measure biomarkers because of their low concentrations and the complexity of their respective matrices. Therefore it is hard to find and validate methods for accurate screening methods suitable for clinical use. The most recent developments during the last three years and also some historical considerations of proteomic methodologies for identification and validation of disease biomarkers are presented in this review.

Engineering and exploitation of a fluorescent HIV-1 gp120 for live cell CD4 binding assays

The HIV-1 envelope glycoprotein, gp120, binds the host cell receptor, CD4, in the initial step of HIV viral entry and infection. This process is an appealing target for the development of inhibitory drugs and neutralizing antibodies. To study gp120 binding and intracellular trafficking, we engineered a fluorescent fusion of the humanized gp120 JRFL HIV-1 variant and GFP. Gp120-sfGFP is glycosylated with human sugars, robustly expressed, and secreted from cultured human cells. Protein dynamics, quality control, and trafficking can be visualized in live cells. The fusion protein can be readily modified with different gp120 variants or fluorescent proteins. Finally, secreted gp120-sfGFP enables a sensitive and easy binding assay that can quantitatively screen potential inhibitors of gp120-CD4 binding on live cells via fluorescence imaging or laser scanning cytometry. This adaptable research tool should aid in studies of gp120 cell biology and the development of novel anti-HIV drugs.

High-resolution cytometry for high-content cell cycle analysis

One of the major limitations of flow cytometry (FCM) is the absence of an intracellular view. Automated microscopy and image analysis, together with technological developments, led to new approaches in cytometry that bypass the above limitation, introducing high resolution, high content, and large statistical sampling. However, few attempts have been made, until now, to translate the wide repertoire of FCM assays into high-content image screening. This unit describes the implementation of an acquisition and analysis protocol for evaluation of the cell cycle by automated microscopy. The approach grants the possibility to perform simultaneous analysis of a high number of different parameters. A large part of this unit is devoted to the description of hardware features that can optimize the recorded information together with the acquisition and analysis procedures employed to produce good-quality data.

Temporally and spatially restricted gene expression profiling

Identifying gene function in specific cells is critical for understanding the processes that make cells unique. Several different methods are available to isolate actively transcribed RNA or actively translated RNA in specific cells at a chosen time point. Cell-specific mRNA isolation can be accomplished by the expression of transgenes in cells of interest, either directly from a specific promoter or using a modular system such as Gal4/UAS or Cre/lox. All of the methods described in this review, namely thiol-labeling of RNA (TU-tagging or RABT), TRAP (translating ribosome affinity purification) and INTACT (isolation of nuclei tagged in specific cell types), allow next generation sequencing, permitting the identification of enriched gene transcripts within the specific cell-type. We describe here the general concept of each method, include examples, evaluate possible problems related to each technique, and suggest the types of questions for which each method is best suited.

Role of flow cytometry in myelodysplastic syndromes: diagnosis, classification, prognosis and response assessment

Myelodysplastic syndromes (MDS) are a heterogeneous group of myeloid neoplasms. With the emergence of therapeutic options, attempts to standardize diagnostic, prognostic and response criteria to guide treatment decisions are increasingly important. This has been achieved in part by the revised 2008 World Health Organization classification and consensus guidelines outlining refined definitions and standards. Conventional criteria have limitations in terms of sensitivity and specificity. Multiparameter flow cytometry (FC) can be used real-time, and is a highly reproducible and objective way of assessing the pattern of expression of multiple antigens on a single hematopoietic cell and defined subpopulations. By comparing antigen expression within maturing myelomonocytic populations with that identified on the equivalent normal cells, abnormalities identified may provide a diagnostic indication of stem cell dysmaturation. There are now increasingly robust data demonstrating the capacity of FC to discriminate MDS from non-clonal cytopenias and dysplasia, as well as further refine disease classification and prognostication, which will be reviewed here.

A computational platform for robotized fluorescence microscopy (I): high-content image-based cell-cycle analysis

Hardware automation and software development have allowed a dramatic increase of throughput in both acquisition and analysis of images by associating an optimized statistical significance with fluorescence microscopy. Despite the numerous common points between fluorescence microscopy and flow cytometry (FCM), the enormous amount of applications developed for the latter have found relatively low space among the modern high-resolution imaging techniques. With the aim to fulfill this gap, we developed a novel computational platform named A.M.I.CO. (Automated Microscopy for Image-Cytometry) for the quantitative analysis of images from widefield and confocal robotized microscopes. Thanks to the setting up of both staining protocols and analysis procedures, we were able to recapitulate many FCM assays. In particular, we focused on the measurement of DNA content and the reconstruction of cell-cycle profiles with optimal parameters. Standard automated microscopes were employed at the highest optical resolution (200 nm), and white-light sources made it possible to perform an efficient multiparameter analysis. DNA- and protein-content measurements were complemented with image-derived information on their intracellular spatial distribution. Notably, the developed tools create a direct link between image-analysis and acquisition. It is therefore possible to isolate target populations according to a definite quantitative profile, and to relocate physically them for diffraction-limited data acquisition. Thanks to its flexibility and analysis-driven acquisition, A.M.I.CO. can integrate flow, image-stream and laser-scanning cytometry analysis, providing high-resolution intracellular analysis with a previously unreached statistical relevance.

Rise of the micromachines: microfluidics and the future of cytometry

The past decade has brought many innovations to the field of flow and image-based cytometry. These advancements can be seen in the current miniaturization trends and simplification of analytical components found in the conventional flow cytometers. On the other hand, the maturation of multispectral imaging cytometry in flow imaging and the slide-based laser scanning cytometers offers great hopes for improved data quality and throughput while proving new vistas for the multiparameter, real-time analysis of cells and tissues. Importantly, however, cytometry remains a viable and very dynamic field of modern engineering. Technological milestones and innovations made over the last couple of years are bringing the next generation of cytometers out of centralized core facilities while making it much more affordable and user friendly. In this context, the development of microfluidic, lab-on-a-chip (LOC) technologies is one of the most innovative and cost-effective approaches toward the advancement of cytometry. LOC devices promise new functionalities that can overcome current limitations while at the same time promise greatly reduced costs, increased sensitivity, and ultra high throughputs. We can expect that the current pace in the development of novel microfabricated cytometric systems will open up groundbreaking vistas for the field of cytometry, lead to the renaissance of cytometric techniques and most importantly greatly support the wider availability of these enabling bioanalytical technologies.