Impact of standardization on clinical cell analysis by flow cytometry

The evolution of flow cytometry from a research tool to a pivotal technology for clinical diagnostic purposes has required significant efforts to standardize methods. The great advantage of flow cytometry is that it's applications are highly amenable to standardization. Here, we review the efforts that have been made for flow cytometric applications in four major fields of clinical cell analysis: CD4+ T-cell enumeration, CD34+ hematopoietic stem and progenitor cell enumeration, screening for the HLA-B27 antigen and leukemia/lymphoma immunophenotyping. These standardization efforts have been parallelled by the establishment of external quality assessment (EQA) schemes in many countries worldwide. The goal of these EQA exercises has been primarily educa-tional, but their results will increasingly serve as a basis for laboratory accreditation. This important development requires that the EQA schemes, in particular the quality of the distributed samples and the procedures for evaluating the results, meet the highest standards.     

Multiplexed and microparticle-based analyses: quantitative tools for the large-scale analysis of biological systems.

While the term flow cytometry refers to the measurement of cells, the approach of making sensitive multiparameter optical measurements in a flowing sample stream is a very general analytical approach. The past few years have seen an explosion in the application of flow cytometry technology for molecular analysis and measurements using microparticles as solid supports. While microsphere-based molecular analyses using flow cytometry date back three decades, the need for highly parallel quantitative molecular measurements that has arisen from various genomic and proteomic advances has driven the development in particle encoding technology to enable highly multiplexed assays. Multiplexed particle-based immunoassays are now common place, and new assays to study genes, protein function, and molecular assembly. Numerous efforts are underway to extend the multiplexing capabilities of microparticle-based assays through new approaches to particle encoding and analyte reporting. The impact of these developments will be seen in the basic research and clinical laboratories, as well as in drug development.     

Cryo-electron microscopy for structural biology:current status and future perspectives

Recently, significant technical breakthroughs in both hardware equipment and software algorithms have enabled cryo-electron microscopy(cryo-EM) to become one of the most important techniques in biological structural analysis. The technical aspects of cryo-EM define its unique advantages and the direction of development. As a rapidly emerging field, cryo-EM has benefitted from highly interdisciplinary research efforts. Here we review the current status of cryo-EM in the context of structural biology and discuss the technical challenges. It may eventually merge structural and cell biology at multiple scales.     

Imaging flow cytometry: coping with heterogeneity in biological systems

Imaging flow cytometry (IFC) platforms combine features of flow cytometry and fluorescent microscopy with advances in data-processing algorithms. IFC allows multiparametric fluorescent and morphological analysis of thousands of cellular events and has the unique capability of identifying collected events by their real images. IFC allows the analysis of heterogeneous cell populations, where one of the cellular components has low expression (<0.03%) and can be described by Poisson distribution. With the help of IFC, one can address a critical question of statistical analysis of subcellular distribution of proteins in a cell. Here the authors review advantages of IFC in comparison with more traditional technologies, such as Western blotting and flow cytometry (FC), as well as new high-throughput fluorescent microscopy (HTFM), and discuss further developments of this novel analytical technique.     

Computational and Experimental Validation of B and T-Cell Epitopes of the In Vivo Immune Response to a Novel Malarial Antigen

Vaccine development efforts will be guided by algorithms that predict immunogenic epitopes. Such prediction methods rely on classification-based algorithms that are trained against curated data sets of known B and T cell epitopes. It is unclear whether this empirical approach can be applied prospectively to predict epitopes associated with protective immunity for novel antigens. We present a comprehensive comparison of in silico B and T cell epitope predictions with in vivo validation using an previously uncharacterized malaria antigen, CelTOS. CelTOS has no known conserved structural elements with any known proteins, and thus is not represented in any epitope databases used to train prediction algorithms. This analysis represents a blind assessment of this approach in the context of a novel, immunologically relevant antigen. The limited accuracy of the tested algorithms to predict the in vivo immune responses emphasizes the need to improve their predictive capabilities for use as tools in vaccine design.     

FuGEFlow: data model and markup language for flow cytometry

Background  

Flow cytometry technology is widely used in both health care and research. The rapid expansion of flow cytometry applications has outpaced the development of data storage and analysis tools. Collaborative efforts being taken to eliminate this gap include building common vocabularies and ontologies, designing generic data models, and defining data exchange formats. The Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) standard was recently adopted by the International Society for Advancement of Cytometry. This standard guides researchers on the information that should be included in peer reviewed publications, but it is insufficient for data exchange and integration between computational systems. The Functional Genomics Experiment (FuGE) formalizes common aspects of comprehensive and high throughput experiments across different biological technologies. We have extended FuGE object model to accommodate flow cytometry data and metadata.     

Polychromatic flow cytometry: a rapid method for the reduction and analysis of complex multiparameter data.

BACKGROUND: Recent advances in flow cytometry have resulted in the development of reliable techniques for performing polychromatic (5-17 color) flow cytometry analysis. However, the data reduction and analysis involved in the resolution of hundreds of possible cellular subphenotypes identified, using a single polychromatic flow cytometry staining panel, presents a major obstacle to the successful application of this technology. METHODS: To generate two distinct collections of T cell populations with differentially expressed surface markers, cryopreserved lymph node cells from 5 melanoma patients vaccinated with the modified gp100(209-2M) melanoma peptide were stimulated with cognate peptide and cultured in either IL-21 + low-dose IL-2 or IL-15 + low-dose IL-2. In vitro stimulated (IVS) cells were interrogated using 8-color flow cytometry. Data were analyzed using Winlist Hyperlog and FCOM software, and 32 T cell subsets were resolved for each culture condition. Hierarchical clustering analysis was applied to the relative percentages of each subphenotype for both IVS conditions to determine if unique cell surface marker expression signatures were produced for each IVS culture. RESULTS: Sequential data analysis using Hyperlog and FCOM demonstrated that lymphocytes cultured in IL-21 + IL-2 had a distinctively different set of subphenotype signatures compared to cells grown in IL-15 + IL-2 for all 5 patients. Importantly, subsequent cluster analysis of all 32 subphenotype frequencies in each IVS test condition for all 5 patients reproducibly demonstrated that cellular subphenotypes produced after IL-21 + IL-2 IVS partitioned separately from subphenotypes produced by IL-15 + IL-2 IVS. CONCLUSIONS: The integrated sequential use of Hyperlog and FCOM software with cluster analysis algorithms for the reduction and analysis of polychromatic flow cytometry data produces an effective, rapid technique for the assessment of complex patterns of subphenotype expression between and within multiple test samples. This approach to data analysis may enhance the use of polychromatic flow cytometry for both research and clinical applications.     

Image analysis software for automatic DNA ploidy assessment of archival solid tumours.

BACKGROUND: Image cytometry has proved to provide a good alternative to flow cytometry for DNA ploidy measurement of archival tumors. However, when interactively done this technique is unable to give statistically valuable results within an acceptable time for clinical oncology. METHODS: An image cytometer was developed for fully automatic DNA ploidy quantitation, focusing efforts on speed and accuracy. Software functionalities include systematic acquisition of fields on a microscopic slide, detection, localization and sorting of nuclei, computation of the DNA content together with post-processing tools, for a deeper analysis of the DNA ploidy diagram. RESULTS: DNA ploidy analysis of archival breast carcinoma samples illustrates the accuracy of DNA ploidy measurements and the sensitivity in the detection of DNA ploidy abnormalities as a result of cell sorting. CONCLUSIONS: Fully automatic image cytometry is able to combine qualities of flow cytometry (automatic analysis of a statistically significant collection of cell nuclei) with additional advantages: sorting of unwanted events (debris, stromal and inflammatory cell nuclei) and facilities for an a posteriori control of the quality of cell selection. This method is well suited to DNA ploidy analysis of archival cancer samples.     

质谱流式技术用于单细胞检测

质谱流式技术(mass cytometry)是利用质谱原理对单细胞进行多参数检测的流式技术,能够在单细胞水平实现超过50种标志物的同时测量,显著增强了对细胞生长进程和复杂细胞系统的评估能力。该文简要介绍了质谱流式技术的基本工作原理,并从金属元素标记、质量分析器、高维单细胞数据处理等方面展开论述,阐明设计新型金属元素标签和选择飞行时间质谱的必要性,归纳分析高维单细胞数据的算法并总结各种算法的优点和局限性。     

流式细胞仪的原理、应用及最新进展

流式细胞术是一种采用激光束激发单行流动的细胞,对它的散射光和携带的荧光进行探测,从而完成细胞分析和分选的技术。以流式细胞术为核心技术,流式细胞仪集光学、电子学、生物学、免疫学等多门学科和技术于一体,能够高效分析微小颗粒(如细胞,细菌)的先进科技设备。它对社会产生了深远的影响,成为了科学研究的必要工具。最近几年,流式细胞仪取得了长足进步。为了深入的了解它,本文从流式细胞仪的工作原理和技术指标,在临床医学、生物学、生殖学和制药学中的应用,以及它的世界格局、仪器功能的最新进展三方面,进行了简明、扼要的论述。展望未来:功能专业化、自动化,体积小型化,多色多参数分析能力提高和分析分选速度更快成为流式细胞仪发展的趋势。     

Scanning cytometry with a LEAP: laser-enabled analysis and processing of live cells in situ.

BACKGROUND: Scanning cytometry now has many of the features (and power) of multiparameter flow cytometry while keeping its own advantages as an imaging technology. Modern instruments combine capabilities of scanning cytometry with the ability to manipulate cells. A new technology, called LEAP (laser-enabled analysis and processing), offers a unique combination of capabilities in cell purification and selective macromolecule delivery (optoinjection). METHODS: LEAP-mediated cell purification and optoinjection effects were assessed in model experiments using adherent and suspension cell types and cell mixtures plated and processed at different densities. Optoinjection effects were visualized by delivering fluorescent dextrans into cells. Results were analyzed using the LEAP instrument's own imaging system as well as by fluorescence and confocal microscopy. RESULTS: Live cell samples (adherent and suspension) could be purified to 90-100% purity with 50-90% yield, causing minimal cell damage depending on the cell type and plating density. Nearly one hundred percent of the targeted cells of all cell types examined could be successfully optoinjected with dextrans of 3-70 kDa, causing no visual damage to the cells. Indirect optoinjection effects were observed on untargeted cells within 5-60 microm to targeted areas under conditions used here. CONCLUSIONS: LEAP provides solutions in cell purification and targeted macromolecule delivery for traditional and challenging applications where other methods fall short.     

Flow cytometry: basic principles and applications

Flow cytometry is a sophisticated instrument measuring multiple physical characteristics of a single cell such as size and granularity simultaneously as the cell flows in suspension through a measuring device. Its working depends on the light scattering features of the cells under investigation, which may be derived from dyes or monoclonal antibodies targeting either extracellular molecules located on the surface or intracellular molecules inside the cell. This approach makes flow cytometry a powerful tool for detailed analysis of complex populations in a short period of time. This review covers the general principles and selected applications of flow cytometry such as immunophenotyping of peripheral blood cells, analysis of apoptosis and detection of cytokines. Additionally, this report provides a basic understanding of flow cytometry technology essential for all users as well as the methods used to analyze and interpret the data. Moreover, recent progresses in flow cytometry have been discussed in order to give an opinion about the future importance of this technology.     

发展我国大规模细胞培养生物反应器装备制造业

生物反应器在生物工程装备制造业的产业化方面具有极其重要的意义。在分析了生物反应器产业的产品特点后,对我国生物反应器产业的现状和今后发展作了讨论。对以代谢流分析为核心的生物反应器、带pH测量与补料控制的摇床、动物细胞大规模培养生物反应器研制、生物反应器中试系统设计、大型生物反应器设计与制造技术研究等几个重要开发内容进行深入讨论,最后对细胞过程的系统生物学研究与生物反应器作了展望。     

Flow cytometry in radiation research: past, present and future

Flow cytometry is an invaluable technique in research and clinical laboratories. The technique has been applied extensively to many areas of radiation research at both the experimental and clinical level. In the past few years, there has been a significant increase in the capabilities of modern flow cytometers to undertake multicolor analysis in a user-friendly manner. The developments in cytometric technology are being matched by the rapid development of new reagents, new fluorochromes and new platforms such as bead arrays. These developments are facilitating many new applications in both basic and clinical research that have relevance for many fields of biology, including radiation research. This review provides a historical overview of the application of flow cytometry to radiobiology and an update on how technology and reagents have changed and cites examples of new applications relevant to radiation researchers. In addition, some entirely new flow instrumentation is currently under development that has significant potential for applications in radiation research.     

An EPROM-based programmable contour generator for use in flow cytometry

An erasable programmable read-only memory (EPROM) contour generator has been fabricated to produce contours for use in flow cytometry. Contours are analog waveforms representing the fluorescence or light-scatter intensity distribution along a cell or object. The generator has particular utility in the development and testing of slit-scan instrumentation and analysis algorithms. Contours are generated without the requirement of specimens or full operation of the flow instrumentation. The generator provides control of contour height, width, offset, and rate. The EPROM may be custom programmed to produce contours for specific test applications or for reproducing "real" contour events. The generator is useful in situations where constant repetitive contours of predetermined characteristics are required.     

Mass cytometry as a platform for the discovery of cellular biomarkers to guide effective rheumatic disease therapy

The development of biomarkers for autoimmune diseases has been hampered by a lack of understanding of disease etiopathogenesis and of the mechanisms underlying the induction and maintenance of inflammation, which involves complex activation dynamics of diverse cell types. The heterogeneous nature and suboptimal clinical response to treatment observed in many autoimmune syndromes highlight the need to develop improved strategies to predict patient outcome to therapy and personalize patient care. Mass cytometry, using CyTOF®, is an advanced technology that facilitates multiparametric, phenotypic analysis of immune cells at single-cell resolution. In this review, we outline the capabilities of mass cytometry and illustrate the potential of this technology to enhance the discovery of cellular biomarkers for rheumatoid arthritis, a prototypical autoimmune disease.     

流式细胞仪的原理、应用及最新进展

流式细胞术是一种采用激光束激发单行流动的细胞,对它的散射光和携带的荧光进行探测,从而完成细胞分析和分选的技术。以流式细胞术为核心技术,流式细胞仪集光学、电子学、生物学、免疫学等多门学科和技术于一体,能够高效分析微小颗粒（如细胞,细菌）的先进科技设备。它对社会产生了深远的影响,成为了科学研究的必要工具。最近几年,流式细胞仪取得了长足进步。为了深入的了解它,本文从流式细胞仪的工作原理和技术指标,在临床医学、生物学、生殖学和制药学中的应用,以及它的世界格局、仪器功能的最新进展三方面,进行了简明、扼要的论述。展望未来：功能专业化、自动化,体积小型化,多色多参数分析能力提高和分析分选速度更快成为流式细胞仪发展的趋势。     

Identifying dynamical persistent biomarker structures for rare events using modern integrative machine learning approach

The evolution of omics and computational competency has accelerated discoveries of the underlying biological processes in an unprecedented way. High throughput methodologies, such as flow cytometry, can reveal deeper insights into cell processes, thereby allowing opportunities for scientific discoveries related to health and diseases. However, working with cytometry data often imposes complex computational challenges due to high-dimensionality, large size, and nonlinearity of the data structure. In addition, cytometry data frequently exhibit diverse patterns across biomarkers and suffer from substantial class imbalances which can further complicate the problem. The existing methods of cytometry data analysis either predict cell population or perform feature selection. Through this study, we propose a “wisdom of the crowd” approach to simultaneously predict rare cell populations and perform feature selection by integrating a pool of modern machine learning (ML) algorithms. Given that our approach integrates superior performing ML models across different normalization techniques based on entropy and rank, our method can detect diverse patterns existing across the model features. Furthermore, the method identifies a dynamic biomarker structure that divides the features into persistently selected, unselected, and fluctuating assemblies indicating the role of each biomarker in rare cell prediction, which can subsequently aid in studies of disease progression.     

Uses and future applications of flow cytometry in immunotoxicity testing.

Flow cytometry is an emerging technology that has numerous applications to immunotoxicity testing. The use and development of high-speed single-cell laser-based assays capable of quantitation of fluorescence, light scatter, and electrical impedance measurements can provide important information on xenobiotic-induced toxicity in defined target cell populations. The purpose of this article is to briefly review established and emerging immunotoxicology assays that use flow cytometry. In the coming years it is likely that many new flow cytometry assays will be developed and validated that will improve the sensitivity and perhaps specificity of immunotoxicity testing. Since flow cytometry is readily adaptable to high-throughput screening, it is also likely that this technology will increasingly find its place in the preclinical testing of drugs and chemicals in the pharmaceutical and chemical industries.     

GenePattern flow cytometry suite

Background

Traditional flow cytometry data analysis is largely based on interactive and time consuming analysis of series two dimensional representations of up to 20 dimensional data. Recent technological advances have increased the amount of data generated by the technology and outpaced the development of data analysis approaches. While there are advanced tools available, including many R/BioConductor packages, these are only accessible programmatically and therefore out of reach for most experimentalists. GenePattern is a powerful genomic analysis platform with over 200 tools for analysis of gene expression, proteomics, and other data. A web-based interface provides easy access to these tools and allows the creation of automated analysis pipelines enabling reproducible research.

Results

In order to bring advanced flow cytometry data analysis tools to experimentalists without programmatic skills, we developed the GenePattern Flow Cytometry Suite. It contains 34 open source GenePattern flow cytometry modules covering methods from basic processing of flow cytometry standard (i.e., FCS) files to advanced algorithms for automated identification of cell populations, normalization and quality assessment. Internally, these modules leverage from functionality developed in R/BioConductor. Using the GenePattern web-based interface, they can be connected to build analytical pipelines.

Conclusions

GenePattern Flow Cytometry Suite brings advanced flow cytometry data analysis capabilities to users with minimal computer skills. Functionality previously available only to skilled bioinformaticians is now easily accessible from a web browser.