The Future of Flow Cytometry in Biotechnology: The Response to Diversity and Complexity

Flow cytometry is a mature technology: Instruments recognizable as having elements of modern flow cytometers date back at least 30 years. There are many good sources for information about the essential features of flow cytometers, how they operate, and how they have been used. For the purposes of this book, it is necessary to know that flow cytometers have fluidic, optical, electronic, computational, and mechanical features. The main function of the fluidic components is to use hydrodynamic focusing to create a stable particle stream in which particles are aligned in single file within a sheath stream, so that the particles can be analyzed and sorted. The main functions of the optical components are to allow the particles to be illuminated by one or more lasers or other light sources and to allow scattered light as well as multiple fluorescence signals to be resolved and be routed to individual detectors. The electronics coordinate these functions, from the acquisition of the signals (pulse collection, pulse analysis, triggering, time delay, data, gating, detector control) to forming and charging individual droplets, and to making sort decisions. The computational components are directed at postacquisition data display and analysis, analysis of multivariate populations and multiplexing assays, and calibration and analysis of time-dependent cell or reaction phenomena. Mechanical components are now being integrated with flow cytometers to handle plates of samples and to coordinate automation such as the movement of a cloning tray with the collection of the droplets. The reader is directed to a concise description of these processes in Robinson’s article in the Encyclopedia of Biomaterials and Biomedical Engineering. This book was conceived of to provide a perspective on the future of flow cytometry, and particularly its application to biotechnology. It attempts to answer the question I heard repeatedly, especially during my association with the National Institutes of Health–funded National Flow Cytometry Resource at Los Alamos National Laboratory: What is the potential for innovation in flow cytometer design and application? This volume brings together those approaches that identify the unique contributions of flow cytometry to the modern world of biotechnology.

Flow Cytometry and Cell Sorting in Plant Biotechnology

Higher plants comprise approximately 250,000 described species and represent a critical component of the planetary biomass. They contribute functions essential for life, of which the most important is photosynthesis, as it provides the means for conversion of incident solar radiation into biomass accumulation, as well as the oxygen required by aerobic life forms. Fixed carbon in the form of carbohydrate provides the basis of the food chain, and metabolic interconversions within plants provide a variety of essential dietary factors. Plants also provide biomass in the form of structural materials and are the source of many natural products with important biomedical properties. As a consequence, considerable scientific interest is invested in determining the molecular mechanisms underlying plant growth, development, metabolism, and responses to biotic and abiotic stresses. Investment has also been made in developing tools and resources for biological investigations using plants. Notable advances include the development of genetics, of means for transformation using defined DNA sequences, and most recently, of the entire nuclear genome sequences of two plant species (Arabidopsis thaliana and Oryza sativa). On the basis of information of this type and that from other sources, it is evident that higher plants share many features with other eukaryotic organisms. Shared features can be observed at many levels; for example, the overall method of construction of cells, in which a bilamellar plasma membrane separates the cytoplasm from the external milieu and provides primary homeostatic regulation. Eukaryotic cells of different kingdoms share organelles, as well as overall regulatory mechanisms. Shared, or highly similar, protein sequences are observed, and they perform similar functions as enzymes, regulatory molecules, or structural components . Higher land plants have evident differences from other eukaryotes. They contain unique classes of organelles primarily devoted to energy capture from sunlight (plastids and peroxisomes). Of these, chloroplasts contain highly fluorescent pigments devoted to photosynthesis, which, particularly chlorophyll, provide unique and powerful signals that can be employed for flow cytometric analysis. Higher plants are also essentially immobile in the sporophytic stage and hence must be capable of responding to changes in environmental conditions and to biotic attack.

Applications of Flow Cytometry in Animal Reproduction

Animals use many highly specialized cells to carry out their reproductive functions. These cells include not only germ-line cells—spermatozoa/oocytes—but also a variety of supporting cells of the remaining organs of the reproductive system and their precursors, thereby making production of viable offspring possible. Reproductive processes, at least in nonhuman mammals, also require functional mammary glands for adequate nourishment of newborn offspring. Specific analyses or sorting of the specialized cells of the reproductive system can provide a means of monitoring and modifying reproductive processes in animals and man. Male gametes are relatively small, haploid cells suspended in fluid secretions from the testes and accessory reproductive organs. Fully functional, mature spermatozoa are incapable of dividing; thus, these terminal gametes are readily quantified and characterized by flow cytometry. Many thousands to millions of spermatozoa can be readily analyzed and sorted. This situation differs markedly from most other kinds of cells, with which cell division and cell cycle differences can make interpretations of data more difficult. Many of the cells of the reproductive and endocrine systems of mammals have been studied by flow analyses. Female gametes, however, are relatively large, often exceeding 100 min diameter, and therefore are not readily analyzed using flow cytometry. Although the oocytes themselves usually are not useful targets, some of the supporting cumulus cells surrounding developing oocytes can be analyzed and thereby provide useful information about that particular ovarian follicle. The functional status of these specialized cells is an indicator of the health of the follicle and of the likelihood that the associated oocyte can produce viable offspring. Reproductive functions in animals are controlled by various widely distributed cellular components of the endocrine system including the hypothalamus, the pituitary gland, the gonads, and the placenta. Such regulatory cells can be isolated and cultured and have their in vitro function monitored, using flow cytometric analysis of their internal components and surface receptors. The supporting cells of animal reproductive systems make possible the production of viable offspring. The functional status of these supporting cells can be evaluated by flow analyses, including the epithelial cervical cells of the female tract, and most accessory tissues, including the male accessory sex glands.

FACS-Based High-Throughput Functional Screening of Genetic Libraries for Drug Target Discovery

A primary aim of functional genomics in pharmaceutical applications is to identify genes whose function is critical to maintaining a disease state and to determining whether therapeutic modulation of this function results in a beneficial clinical response. However, although many genomic approaches can identify disease-associated genes, lengthy follow-up studies are usually required to determine which genes are functionally important and are causally linked to a given disease. In contrast, retrovirally mediated functional genetic screening approaches enable rapid identification of physiologically relevant targets. Genetic screens are designed to detect functional changes that result in changes in cellular function that correlate with disease amelioration. Retroviruses possess unique properties that allow delivery of complex libraries of potential genetic effectors to a variety of cell types. These effectors can perturb specific interactions required to achieve a complete functional response and establish a direct relationship with a cellular function. Functional screens are employed to select for cells endowed with a desired genetic effector–induced change in phenotype. Identification of a genetic effector that causes an altered cellular phenotype that correlates with clinical benefit can explicate critical signaling components suitable for therapeutic intervention. Flow cytometry represents a uniquely powerful methodology to monitor complex multiparametric changes of individual cells in large populations. In conjunction with recent advances in retroviral expression systems, the sensitivity and speed of flow cytometry enables a highly efficient functional screening of complex libraries in a wide range of cell-based assays. In this chapter, we discuss the process of functional genetic screening and show specific examples of its implementation. We focus particularly on the critical parameters involved in the design and execution of functional genetic screening approaches based on FACS (fluorescence activated cell sorter). Retroviruses provide a powerful method of introducing genes into mammalian cells in an efficient and stable manner. Recent advances in retroviral vector technology and packaging systems have extended their application to allow efficient and stable delivery of highly diverse libraries encoding various types of genetic effectors, including cDNAs, peptides, and ribozymes, into a broad range of cell types.

Multiparameter Analysis: Application to Vaccine Analysis

Fluorescence-based flow cytometry was introduced in the late 1960s and is now used extensively both in basic research and in the clinic. Flow cytometry allows not only for the rapid multiparametric analysis of cells on a cell-by-cell basis but also for the viable separation, or sorting, of highly purified populations of cells. In this chapter, we will discuss only the analysis aspects. The earliest flow cytometry experiments had three parameters: one fluorescence measurement and two scattered light signals. An early “one-color” experiment successfully separated antibody-secreting B cells from mouse splenocytes. This and other early studies quickly demonstrated the usefulness of this technology in immunological studies. However, measurement of only one fluorescence was a limitation. By adding detectors collecting light in specified wavelength ranges, multiple fluorescence measurements could be made simultaneously. By 1984, four-color fluorescence experiments could be routinely performed, at least in the most sophisticated flow cytometry laboratories, but it took another 10 years before most laboratories could perform routine three-color experiments. One reason for this delay is that it took some time to recognize the need for measuring multiple parameters in addressing questions that explored the complexity of the immune system. Another reason was that it was not until the late 1980s that fourcolor benchtop instrumentation became available. The AIDS epidemic also had a major effect on the expansion of flow cytometry into the research community, as early in the epidemic, the enumeration of CD4 was found to serve as a surrogate marker for disease progression. During this period, we were examining a number of functionally-important T cell subsets in HIV-infected adults and children, including naïve and memory, using three-color flow cytometry. These studies demonstrated clearly for the first time the loss of both CD4 and CD8 naïve T cells during HIV disease progression. This loss had not been previously recognized either because appropriate combinations of reagents were not used or because the studies were limited to two colors. Having demonstrated that multiple markers used in combination could lead to clinically relevant findings that were previously missed, we wondered how many other important subsets could be detected by measuring additional parameters.

Flow Cytometry, Beads, and Microchannels

Microfluidic devices generally consume microliter to submicroliter volumes of sample and are thus well suited for use when the required reagents are scarce or expensive. Because microfluidic devices operate in a regime in which small Reynolds numbers govern the delivery of fluid samples, reagent mixing and subsequent reactivity has been a severe limiting factor in their applicability. The inclusion of packed beads in the microfluidic device repertoire has several advantages: molecular assemblies for the assay are created outside the channel on beads and characterized with flow cytometry, uniform populations of beads may be assured through rapid cytometric sorting, beads present a larger surface area for the display of receptors than flat surfaces, rapid mixing in the microcolumn is achieved because the distance that must be covered by diffusion is limited to the (≤1-μm) interstitial space between the closely packed receptorbearing beads, and analytes are captured in a flow-through format and, as such, each bead can act as a local concentrator of analytes. Progress in the combined use of beads and microfluidic devices has been limited by the ability to pack beads at specific sections of microfluidic devices. A subsequent challenge associated with the packed microcolumns of beads is the substantial pressure drop that affects the fluid flow velocity. However, some of these challenges have been overcome in the design of simple model systems that have potential applications in DNA analysis, chromatography, and immunoassays. It is the intent of this chapter to examine the recent emergence of small-volume heterogeneous immunoassays, using beads trapped in microchannels, while excluding other closely related applications such as capillary electrophoresis and flow injection–based approaches. Of necessity, the authors’ interests and availability of information pertinent to the specific discussions presented below impose additional restrictions. To date, there are only a handful of applications that combine packed beads and microfluidic devices, and even fewer that make the overt connection between flow cytometry–based assays and beads. Harrison and coworkers have provided one of the earliest conceptual demonstrations of the capability to incorporate packed beads in microfluidic devices for analytical purposes.

Automation and High- Throughput Flow Cytometry

The flow cytometer is unique among biomedical analysis instruments in its ability to make multiple correlated optical measurements on individual cells or particles at high rates. Moreover, an ever-expanding arsenal of fluorescent probes enables the modern flow cytometer to quantify a large and growing diversity of cell-associated macromolecules and physiological processes. Modern flow cytometers have achieved such a level of sophistication and reliability that unattended operation by automated systems is a practical reality. From its inception, flow cytometry has been in the vanguard of automation in cytological analysis. One of the most powerful automated features is cell sorting, an operation in which highly purified subsets of cells or particles are isolated from heterogeneous source populations on the basis of a targeted, multiparameter phenotype. The method most widely used for sorting today, which is based on electrostatic deflection of charged droplets, was developed over 30 years ago and led to commercial flow cytometers that were capable of sorting cells at rates of hundreds of cells per second. Influenced by the need of the Human Genome Project for efficient isolation of purified chromosomes, a high-speed chromosome flow sorter was developed and patented in 1982 that increased sort rates to tens of thousands of events per second (13). Commercial systems subsequently became available in the 1990s that permitted sorting of cells at such high rates (www.bdbiosciences.com; www.dakocytomation. com). Thus, since the initial development of the technology, the throughput of automated cell sorting has increased by nearly two orders of magnitude. In single cell analysis and sorting, throughput is determined by the rate at which the flow cytometer can process individual cells as they pass single file through the point of detection. Another aspect of flow cytometer throughput concerns the rate at which the flow cytometer can sequentially process multiple discreet collections of cells. This component of throughput will be important, for example, in the screening of collections of test compounds for their effects on bulk populations of cells. This is of particular relevance for modern drug discovery, in which there is a need to test cellular targets against millions of potentially valuable compounds that may bind cellular receptors to effect clinically therapeutic cellular responses.

Analysis of GTP-Binding Protein–Coupled Receptor Assemblies by Flow Cytometry

GTP-binding protein–coupled receptors (GPCRs) represent the largest family of integral membrane signal-transducing molecules in the human genome, with estimates of at least 600 members. As such, they represent the targets of approximately 30%–50% of the prescription drugs on the market. They are involved in virtually every physiological process in the human body, with ligands including light, odorants, amines, peptides, proteins, lipids, and nucleotides. Binding of these ligands on the extracellular surface of the receptor leads to conformational changes within the receptor, resulting in a multitude of cellular responses. GPCRs, as their name implies, function through the actions of heterotrimeric GTP-binding proteins (G proteins). These G proteins then couple to a diverse array of effector molecules at the cell surface and inside the cell. GPCRs contain a common structural motif, with seven transmembrane alpha helices. With the recent description of the three-dimensional crystal structure of rhodopsin in its inactive state, a greater, though still incomplete, understanding of the functions of this receptor family has been achieved. In addition to the activation of G proteins, GPCRs undergo extensive regulation mediated primarily by a variety of kinases, including second messenger kinases and the family of G protein–coupled receptor kinases (GRKs). Following receptor phosphorylation by GRKs, additional proteins named arrestins associate with GPCRs. The traditional role of these molecules has been to serve as desensitizing agents, preventing further association of the receptor with G proteins. However, recent studies have demonstrated that arrestins can serve as adapters in the process of receptor internalization as well as scaffolds in the activation of numerous kinase pathways. Interactions between GPCRs and cellular proteins such as adaptins, rab GTPases, phosphatases, and ion channels have also been described. Thus, it has become apparent that understanding the interactions between GPCRs and their associated proteins is critical for any detailed understanding of receptor function. An overview of the activation and regulation of GPCRs is shown in figure 17.1 to provide a context for the approaches to be described in the remainder of this chapter.

Genetic Analysis Using Microsphere Arrays

The use of DNA microarrays to analyze simultaneously many genetic features from a sample is providing a new perspective on the effect of the genome on normal biological processes and disease states. The translation of this new perspective into new diagnostics and treatments will require development of microarray technology to enable cost-effective, high-throughput analysis of many samples. Microsphere arrays—sets of optically encoded microparticles—measured by flow cytometry are an experimentally flexible alternative to the flat-surface microarrays that are being used in a variety of biomedical analyses. In this chapter, we review the major areas where microsphere arrays are being used for genetic analysis and discuss the key experimental considerations that enable these and future applications. The human genome project and other genome projects have opened great new possibilities for biomedical research. Along with these new possibilities have come new technical challenges involving the conversion of raw DNA sequence data into useful information for basic research, diagnostic, and therapeutic applications. Applications include the discovery of new associations between diseases and specific genes, the evaluation of genetic predisposition to disease, and the prediction of the response of individual patients to drugs. In the areas of public health, addressing issues such as infectious disease, food safety, and bioterrorism can all be enhanced through molecular analysis. Perhaps the most daunting challenge involves the specific analysis of hundreds or thousands of genetic features in hundreds or thousands of individual samples. To address these challenges, a variety of analytical methods and platforms are being developed, ranging from laboratory methods such as mass spectrometry to portable microfluidic devices. Each of these assay platforms has characteristic features that determine sensitivity, throughput, and flexibility. Flow cytometry is among the most versatile of analytical platforms, providing sensitive and quantitative multiparameter fluorescence measurements of cells and microparticles with high analysis rates. These features underlie the development of several current and emerging genetic analysis tools. One of the earliest flow cytometric measurements was a genetic analysis of a sort— the measurement of relative DNA content in individual cells using fluorescent DNA binding dyes.

A Guide to Informatics in Flow Cytometry

Flow cytometry is a result of the computer revolution. Biologists used fluorescent dyes in microscopy and medicine almost a hundred years before the first flow cytometer. Only after electronics became sophisticated enough to control individual cells and computers became fast enough to analyze the data coming out of the instrument, and to make a decision in time to deflect the stream, did cell sorting become viable. Since the 1970s, the capabilities of computers have grown exponentially. According to the famed Moore’s Law, the size of the computer, as tracked by the number of transistors on a chip, doubles every 18 months. This rule has held for three decades so far, and new technologies continue to appear to keep that growth on track. The clock speed of chips is now measured in gigahertz—billions of instructions per second—and hard drives are now available with capacities measured in terabytes. Having computers so powerful, cheap, and ubiquitous changes the nature of scientific exploration. We are in the early steps of a long march of biotechnology breakthroughs spawned from this excess of compute power. From genomics to proteomics to high-throughput flow cytometry, the trend in biological research is toward massproduced, high-volume experiments. Automation is the key to scaling their size and scope and to lowering their cost per test. Each step that was previously done by human hands is being delegated to a computer or a robot for the implementation to be more precise and to scale efficiently. From making sort decisions in milliseconds to creating data archives that may last for centuries, computers control the information involved with cytometry, and software controls the computers. As the technology matures and the size and number of exper iments increase, the emphasis of software development switches from instrument control to analysis and management. The challenge for computers is not in running the cytometer any more. The more modern challenge for informatics is to analyze, aggregate, maintain, access, and exchange the huge volume of flow cytometry data. Clinical and other regulated use of cytometry necessitates more rigorous data administration techniques. These techniques introduce issues of security, integrity, and privacy into the processing of data.