14.1 Introduction: Flow Cytometry (figure 1) measure the specific characteristic of a large number of individual cells rapidly. Before flow cytometric analysis, cells in suspension are fluorescently labeled, mostly with fluorescently conjugated monoclonal antibody (mAb). In a flow cytometer, the suspended cells pass through a flow chamber at a rate of 1,000 to 10,000 cells per minute through a focused beam of laser. After fluorescent activation of the fluorophore at an excitation wave length, a detector processes the emitted fluorescence and light scattering properties of each cell. Scientists at Naval Research Laboratory developed a flow cytometry technique for detecting the presence of viruses in cells and study their growth. It targets the viral RNA. The technique referred to as locked nucleic acid (LNA) flow cytometry-fluorescence in situ hybridization (flow-FISH) involves binding of an LNA probe to viral RNA. The researchers demonstrated that the combination of LNA probes with flow-FISH can be used to quantify viral RNA in infected cells. This will also allow researchers to monitor changes in viral RNA accompanying antiviral drug treatment. A number of improved flow FISH methods have been developed. These include partial automation procedure and multicolor flow FISH which is the current fastest and most sensitive method available. A step by step procedure of flow FISH as described by Baerlocher et al based on their study to measure the average length of telomere is as follows: Each flow-FISH experiment begins with acquisition of premixed calibration (MESF) beads. Several thousand events are collected, and the main fluorescence and coefficient of variation (CV) of each of the five peaks is recorded and plotted against MESF content provided by the manufacturer to control for the linearity of the instrument. The next step are related to the selection of the optimal values for the detectors, amplifiers, fluorescence compensation setting and threshold values for analysis of flow FISH samples. Once an appropriate instrument setting has been selected, these can be saved and recalled for future study, although minor day-to-day adjustments are needed between experiments and between samples. The instrument settings are further adjusted to provide a good separation of the events of interest over the entire range in the selected channels. Various compensation settings are selected for the analysis of cells simultaneously labeled with fluorescein, phycoerythrin (PE), LDS751, and cy-5. Except for the compensation setting of fluorescence 2 channel (FI2, PE), fluorescence detected in the FI1 (green fluorescence) channel, the setting for green fluorescence detection is typically not readjusted after the acquisition of the MESF bead data because the range of fluorescence in test cells is typically known. Following hybridization of nucleated human blood cells mixed with bovine thymocytes, three population of cells can typically be distinguished based on two parameters: forward light scatter which provide a measure of cell size, LDS 751fluorescence which provide measure of DNA content or accebility. The three populations are bovine thymocytes (R1) which are dimly labeled with LDS 751, human lymphocyte (R2) which has intermediate forward scatter and LDS 751, and granulocyte (R3) which are mostly brightly stained with LDS 751.
Figure 1: A flow cytometry technique
Lymphocytes are further separated from granulocytes by combining the gates with the gates set in dot plots of side scatter versus forward light scatter. Cells within the lymphocyte gate (R2 + R4) are further subdivided on the basis of antibody labeling with Cy5 or Allophycocyanin and PE . The PE signal is derived either from directly labeled CD20 antibody, or indirectly from biotinylated CD57 antibodies followed by Streptavidin-PE. After the identification of these various gates the following populations can be distinguished: bovine control cells (R1 + R4), lymphocytes (R2 + R4), granulocytes (R3 + R5), PE-positive lymphocytes (R2 + R4 + R6), PE-negative, CD45RA-positive lymphocytes (R2 + R4 + R7) and PE-negative, CD45RA-negative lymphocytes (R2 + R4 + R8). Each of these populations of cells is analyzed for their autofluorescence by analysing green fluorescence in tubes that were processed as for flow FISH in the absence of a PNA probe and blue peaks and for the fluorescence obtained with the telomere PNA probe and red peaks in. At least 10,000 events of human cells are typically acquired for each analysis. Figure 2 is a typical image of a flow cytometry analysis.
Figure 2: Example of flow FISH data analysis based on nucleated blood cells from a normal human donor: For each nucleated blood sample two samples are analyzed: one in which the cells were hybridized to the peptide nucleic acid (PNA) probe (c) and one that was treated identically but without the PNA probe (b). The latter is required to measure the level of autofluorescence in cells of interest and to enable telomere length to be calculated from specific PNA hybridization (g). Cells are counterstained with non-saturating concentrations of the DNA dye LDS751 and various antibodies (CD45RA–Cy5 and CD20– phycoerythrin (PE) in this case) before the acquisition of listmode data. The first step in the subsequent analysis is to identify cells using forward light and side scatter in a bivariate dot plot (d). Within gates R4 and R5 three cell populations can be observed in a bivariate plot of forward light scatter signal versus LDS751 fluorescence (a). The mild formaldehyde fixation of the bovine thymocytes limits their staining by LDS751, which is useful to distinguish these small cells from human lymphocytes with largely overlapping forward and side light scatter properties. Granulocytes are labeled more brightly by LDS751, and can be distinguished from lymphocytes. The green fluorescence of cells gated as in (a) hybridized in the presence or absence of fluorescein-labeled PNA is shown relative to LDS751 fluorescence in the contour plots shown in (c) and (b), respectively. By combining the gates shown in (a) and (d), fluorescence histograms (g) of the indicated cell populations are obtained, which are used for subsequent calculations of telomere length. Antibodies specific for CD45RA and CD20 cells are used (e) to perform telomere length analysis of specific populations within the lymphocyte gate (R2 + R4). Note that the fluorescence histogram of granulocytes is more symmetrical than that of lymphocytes, and that cells with relatively long telomeres are readily identified among CD20+ B lymphocytes. (Source: Baelocher et al, 2006)
Most the drug targets used for the treatment of human diseases are found in the human genome sequences; however in infectious diseases, the drug targets are represented by the genome of both the host and pathogen. Therefore a systematic functional genomics approach is needed to elucidate the changes that take place in the transcriptomes and proteomes of both the host and pathogen. Proteomic has been used in studying bacterial and fungal pathogens but the technique is still in development. Flow Cytometry (DNA microarrays) is an ideal technique for studying changes in the transcriptome of both host and oncoviruses. High density DNA arrays are generated by spotting DNA fragments which are derived by PCR or synthetic oligonucleotide onto a solid surface such as glass. Oligonucleotide can also be generated on glass wafers using photolithography. Deposition of thousands of probes on solid support surface allows the simultaneous monitoring of the expression levels of the corresponding mRNAs which is isolated from various sources. DNA arrays are essential in analyzing host-pathogen interaction. LNA-flow FISH can be used for fast and easy way to screen for compounds with antiviral activity and could be utilized for monitoring infections in blood for vaccine therapy and development. This chapter will therefore review some of the data on DNA arrays with emphasis on Merkel cell polyomavirus.
Polymaviruses (PyV) are naked, circular, ds-DNA viruses that infect birds and mammals and a fish-associated polyomavirus has been described. The genome of most polymaviruses is about 5000bp which encodes regulatory and structural proteins. The major regulatory proteins are the large tumor antigen (LT-ag) and the small tumor antigen (ST-ag) that share conserved functional domain made of binding motifs for the tumor suppressor pRB and p53 as well as for protein phosphatase 2A respectively. About two structural proteins (VP1 and VP2) form the capsid. The regulatory proteins are expressed early during infection and play a part in viral replication and transcription. The structural proteins are expressed later in the infectious cycle. Most of the polymaviruses encodes additional regulatory and structural proteins such as ALTO, VP3, VP4, and agnoprotein. Eleven novel human PyV have been described: KIPyV, WUPyV, Merkel cell PyV (MCPyV), HPyV6, HPyV7, Trichodysplasia spinulosa-associated PyV (TSPyV), HPyV9, HPyV10 (and isolates of MW and MX), STLPyV, PHyV12, and NJPyV-2013. MCPyV is associated with cancer in its natural host. About 80% of Merkel cell carcinoma (MCC) tumors are positive for MCPyV genome which is integrated and encodes a truncated form of LT-ag. Specific inhibitors against HPyV such as MCPyV are still lacking while the development of vaccines and vaccination are still in the preliminary stages. Therefore just like with other oncoviruses, identification of a unique technique that will aid in the acceleration of the development of anti-oncoviral drugs will be of immense help in the management of viral-associated cancers. Microarray techniques have been used in a number of studies which helped in our understanding of the pathogenesis of some viruses. In RSV infection, for example, microarray was used to identify genes involved in the pathways of neuroactive ligand-receptor interaction, p53 signaling, ubiquitin mediated proteolysis, Jak-STAT signaling, cytokine-cytokine receptor interaction, hematopoitic cell lineage, cell cycle, and apoptosis. Respiratory disease biomarkers like APG2, SCNN1G, EPB41LAB, CSF1, PTEN, TUBB1, and ESR2 were detected with microarray. Flow cytometry in conjunction with cell culture have been used to analyze ganciclovir and foscarnet susceptibility for human cytomegalovirus clinical isolates.
There are two approaches of identifying drugs molecules: 1.Targeting key viral function, and 2. Use of other broad spectrum of drugs that were originally designed for the treatment of another infection. Although there are no data on drug development utilizing the technique, lot of research have been undertaken using this technique to either identify new drug targets or analyzing existing drug. In a study, Jiang et al used FAC to identify a novel anticancer drug which targets the Wnt/B-catenin pathway. Sharma et al studied the effect of artesunate on polyomavirus BKV. Using flow cytometry to analysis cell cycle, they found that artesunate decreased the release of infectious progeny in concentration-dependent manner. They therefore concluded that artesunate inhibits BKV replication in RPTECS.
Measurement of binding of biotherapeutic or its cellular target, receptor occupancy is now becoming an important tool in the development of biologically-based therapeutic agents. RO assay by flow cytometry describes the quantitative and/ or qualitative assessment of the binding of a therapeutic agent to its cell surface target. Taking into consideration that most oncoviral agents utilize receptor, this can be an ideal technique for drug development in oncoviral infection. Such assay can be simple as measuring the number of cell surface receptors bind by anti-receptor therapeutic agents or can be designed to address more complicated issues such as internalization, fusion, shedding, or assembly events. Data generated from RO assays can also be used to model pharmacodynamic (PD) markers during drug development as well as during pre-clinical and clinical trials. Drug development PD biomarkers are mostly used as surrogate markers to monitor changes in the biological effects of drugs. Data collected from assessment of these markers can be used in conjunction with pharmacokinetic (PK) data to aid in the efficient and effective design of clinical trials. Flow cytometry is unique technique which can be used for oncoviral drug development. However, some few challenges will be encountered when using this technique. These include how to maintain the stability of the target-bound therapeutic agent and the stability of the target receptor. Also reagent selection will be an issue as reagent needs to be evaluated for their potential to compete with the therapeutic agent and bind with comparable affinity.
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