Flow Cytometry and Real-Time Quantitative PCR as Tools for Assessing Plasmid Persistence

The maintenance of a plasmid in the absence of selection for plasmid-borne genes is not guaranteed. However, plasmid persistence can evolve under selective conditions. Studying the molecular mechanisms behind the evolution of plasmid persistence is key to understanding how plasmids are maintained under nonselective conditions. Given the current crisis of rapid antibiotic resistance spread by multidrug resistance plasmids, this insight is of high medical relevance. The conventional method for monitoring plasmid persistence (i.e., the fraction of plasmid-containing cells in a population over time) is based on cultivation and involves differentiating colonies of plasmid-containing and plasmid-free cells on agar plates. However, this technique is time-consuming and does not easily lend itself to high-throughput applications. Here, we present flow cytometry (FCM) and real-time quantitative PCR (qPCR) as alternative tools for monitoring plasmid persistence. For this, we measured the persistence of a model plasmid, pB10::gfp, in three Pseudomonas hosts and in known mixtures of plasmid-containing and -free cells. We also compared three performance criteria: dynamic range, resolution, and variance. Although not without exceptions, both techniques generated estimates of overall plasmid loss rates that were rather similar to those generated by the conventional plate count (PC) method. They also were able to resolve differences in loss rates between artificial plasmid persistence assays. Finally, we briefly discuss the advantages and disadvantages for each technique and conclude that, overall, both FCM and real-time qPCR are suitable alternatives to cultivation-based methods for routine measurement of plasmid persistence, thereby opening avenues for high-throughput analyses.     

Flow Cytometry Bioinformatics

Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing, and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results. Computational methods exist to assist in the preprocessing of flow cytometry data, identifying cell populations within it, matching those cell populations across samples, and performing diagnosis and discovery using the results of previous steps. For preprocessing, this includes compensating for spectral overlap, transforming data onto scales conducive to visualization and analysis, assessing data for quality, and normalizing data across samples and experiments. For population identification, tools are available to aid traditional manual identification of populations in two-dimensional scatter plots (gating), to use dimensionality reduction to aid gating, and to find populations automatically in higher dimensional space in a variety of ways. It is also possible to characterize data in more comprehensive ways, such as the density-guided binary space partitioning technique known as probability binning, or by combinatorial gating. Finally, diagnosis using flow cytometry data can be aided by supervised learning techniques, and discovery of new cell types of biological importance by high-throughput statistical methods, as part of pipelines incorporating all of the aforementioned methods. Open standards, data, and software are also key parts of flow cytometry bioinformatics. Data standards include the widely adopted Flow Cytometry Standard (FCS) defining how data from cytometers should be stored, but also several new standards under development by the International Society for Advancement of Cytometry (ISAC) to aid in storing more detailed information about experimental design and analytical steps. Open data is slowly growing with the opening of the CytoBank database in 2010 and FlowRepository in 2012, both of which allow users to freely distribute their data, and the latter of which has been recommended as the preferred repository for MIFlowCyt-compliant data by ISAC. Open software is most widely available in the form of a suite of Bioconductor packages, but is also available for web execution on the GenePattern platform.

This is a “Topic Page” article for PLOS Computational Biology.

     

Stochastic Measurement Models for Quantifying Lymphocyte Responses Using Flow Cytometry

Adaptive immune responses are complex dynamic processes whereby B and T cells undergo division and differentiation triggered by pathogenic stimuli. Deregulation of the response can lead to severe consequences for the host organism ranging from immune deficiencies to autoimmunity. Tracking cell division and differentiation by flow cytometry using fluorescent probes is a major method for measuring progression of lymphocyte responses, both in vitro and in vivo. In turn, mathematical modeling of cell numbers derived from such measurements has led to significant biological discoveries, and plays an increasingly important role in lymphocyte research. Fitting an appropriate parameterized model to such data is the goal of these studies but significant challenges are presented by the variability in measurements. This variation results from the sum of experimental noise and intrinsic probabilistic differences in cells and is difficult to characterize analytically. Current model fitting methods adopt different simplifying assumptions to describe the distribution of such measurements and these assumptions have not been tested directly. To help inform the choice and application of appropriate methods of model fitting to such data we studied the errors associated with flow cytometry measurements from a wide variety of experiments. We found that the mean and variance of the noise were related by a power law with an exponent between 1.3 and 1.8 for different datasets. This violated the assumptions inherent to commonly used least squares, linear variance scaling and log-transformation based methods. As a result of these findings we propose a new measurement model that we justify both theoretically, from the maximum entropy standpoint, and empirically using collected data. Our evaluation suggests that the new model can be reliably used for model fitting across a variety of conditions. Our work provides a foundation for modeling measurements in flow cytometry experiments thus facilitating progress in quantitative studies of lymphocyte responses.     

Detection of Bacteriophage-Infected Cells of Lactococcus lactis by Using Flow Cytometry

Bacteriophage infection in dairy fermentation constitutes a serious problem worldwide. We have studied bacteriophage infection in Lactococcus lactis by using the flow cytometer. The first effect of the infection of the bacterium is a change from cells in chains toward single cells. We interpret this change as a consequence of a cease in cell growth, while the ongoing cell divisions leave the cells as single cells. Late in the infection cycle, cells with low-density cell walls appear, and these cells can be detected on cytograms of light scatter versus, for instance, fluorescence of stained DNA. We describe a new method for detection of phage infection in Lactococcus lactis dairy cultures. The method is based on flow cytometric detection of cells with low-density cell walls. The method allows fast and early detection of phage-infected bacteria, independently of which phage has infected the culture. The method can be performed in real time and therefore increases the chance of successful intervention in the fermentation process.     

Detection of DNA in Ancient Skeletal Remains Using DNA Flow Cytometry

Cortical bone samples were removed from individual burials from Tomb Dk31 in the Dakhleh Oasis, Egypt. The tissue was disaggregated, stained with the DNA specific fluorescent dye DAPI and analyzed using the flow cytom-eter. DNA flow cytometry measures the cellular DNA content and this is correlated with modal chromosome content. When DNA is present in skeletal remains further investigations such as extracting, amplifying and sequencing may then be carried out. The method offers a relatively rapid and inexpensive means of pinpointing samples of skeletal DNA that can be further analyzed.     

Detection of DNA in Ancient Skeletal Remains Using DNA Flow Cytometry

Cortical bone samples were removed from individual burials from Tomb Dk31 in the Dakhleh Oasis, Egypt. The tissue was disaggregated, stained with the DNA specific fluorescent dye DAPI and analyzed using the flow cytom-eter. DNA flow cytometry measures the cellular DNA content and this is correlated with modal chromosome content. When DNA is present in skeletal remains further investigations such as extracting, amplifying and sequencing may then be carried out. The method offers a relatively rapid and inexpensive means of pinpointing samples of skeletal DNA that can be further analyzed.     

Use of Flow Cytometry To Follow the Physiological States of Microorganisms in Cider Fermentation Processes

The flow cytometry (FC) technique used with certain fluorescent dyes (ChemChrome V6 [CV6], DRAQ5, and PI) has proven useful to label and to detect different physiological states of yeast and malolactic bacterium starters conducting cider fermentation over time (by performing sequential inoculation of microorganisms). First, the technique was tested with pure cultures of both types of microorganisms grown in synthetic media under different induced stress conditions. Metabolically active cells detected by FC and by the standard plate-counting method for both types of microorganisms in fresh overnight pure cultures gave good correlations between the two techniques in samples taken at this stage. Otherwise, combining the results obtained by FC and plating during alcoholic and malolactic fermentation over time in the cider-making process, different subpopulations were detected, showing significant differences between the methods. A small number of studies have applied the FC technique to analyze fermentation processes and mixed cultures over time. The results were used to postulate equations explaining the different physiological states in cell populations taken from fresh, pure overnight cultures under nonstress conditions or cells subjected to stress conditions over time, either under a pure-culture fermentation process (in this work, corresponding to alcoholic fermentation) or under mixed-fermentation conditions (for the malolactic-fermentation phase), that could be useful to improve the control of the processes.     

流式细胞术

流式细胞术是一种综合应用光学、机械学、流体力学、电子计算机、细胞生物学、分子免疫学等学科技术,对高速流动的细胞或亚细胞进行快速定量测定和分析的方法。它一秒钟能分析几千个细胞,并同时测定细胞的多个参数,广泛应用于生物医学的许多领域,如测定细胞的特征(形态、膜电位等)和细胞内pH,细胞DNA、蛋白质含量、表面受体、Ca2+等。对生物工程学来说,了解细胞的这些参数尤为重要,因为它们能比用传统技术测得的数据更好地描述细胞群体。从流式细胞仪对细胞多种参数的测定及原理,到它在生物工程学中的应用等方面进行了介绍,并讨论了流式细胞术的局限性和面临的挑战。     

Single-cell Analysis of Bacillus subtilis Biofilms Using Fluorescence Microscopy and Flow Cytometry

Biofilm formation is a general attribute to almost all bacteria ^1-6. When bacteria form biofilms, cells are encased in extracellular matrix that is mostly constituted by proteins and exopolysaccharides, among other factors ^7-10. The microbial community encased within the biofilm often shows the differentiation of distinct subpopulation of specialized cells ^11-17. These subpopulations coexist and often show spatial and temporal organization within the biofilm ^18-21.Biofilm formation in the model organism Bacillus subtilis requires the differentiation of distinct subpopulations of specialized cells. Among them, the subpopulation of matrix producers, responsible to produce and secrete the extracellular matrix of the biofilm is essential for biofilm formation ^11,19. Hence, differentiation of matrix producers is a hallmark of biofilm formation in B. subtilis.We have used fluorescent reporters to visualize and quantify the subpopulation of matrix producers in biofilms of B. subtilis^15,19,22-24. Concretely, we have observed that the subpopulation of matrix producers differentiates in response to the presence of self-produced extracellular signal surfactin ²⁵. Interestingly, surfactin is produced by a subpopulation of specialized cells different from the subpopulation of matrix producers ¹⁵.We have detailed in this report the technical approach necessary to visualize and quantify the subpopulation of matrix producers and surfactin producers within the biofilms of B.subtilis. To do this, fluorescent reporters of genes required for matrix production and surfactin production are inserted into the chromosome of B. subtilis. Reporters are expressed only in a subpopulation of specialized cells. Then, the subpopulations can be monitored using fluorescence microscopy and flow cytometry (See Fig 1).The fact that different subpopulations of specialized cells coexist within multicellular communities of bacteria gives us a different perspective about the regulation of gene expression in prokaryotes. This protocol addresses this phenomenon experimentally and it can be easily adapted to any other working model, to elucidate the molecular mechanisms underlying phenotypic heterogeneity within a microbial community.     

Flow Cytometry of Mitotic Cells

We have developed a procedure using flow cytometric measurement of a mitosis-specific antigen that may be used to count mitotic cells and sort them from nonmitotic cells. The procedure may also be used in conjunction with measurement of cellular DNA content and of bromodeoxyuridine incorporation into cellular DNA to assign cells to the G1/G0, S, G2, or M phase of the cell cycle.     

A Novel Quantitative Kinase Assay Using Bacterial Surface Display and Flow Cytometry

The inhibition of tyrosine kinases is a successful approach for the treatment of cancers and the discovery of kinase inhibitor drugs is the focus of numerous academic and pharmaceutical laboratories. With this goal in mind, several strategies have been developed to measure kinase activity and to screen novel tyrosine kinase inhibitors. Nevertheless, a general non-radioactive and inexpensive approach, easy to implement and adapt to a range of applications, is still missing. Herein, using Bcr-Abl tyrosine kinase, an oncogenic target and a model protein for cancer studies, we describe a novel cost-effective high-throughput screening kinase assay. In this approach, named the BacKin assay, substrates displayed on a Bacterial cell surface are incubated with Kinase and their phosphorylation is examined and quantified by flow cytometry. This approach has several advantages over existing approaches, as using bacteria (i.e. Escherichia coli) to display peptide substrates provides a self renewing solid support that does not require laborious chemical strategies. Here we show that the BacKin approach can be used for kinetic and mechanistic studies, as well as a platform to characterize and identify small-molecule or peptide-based kinase inhibitors with potential applications in drug development.     

Real-Time Monitoring of Protein Conformational Changes Using a Nano-Mechanical Sensor

Proteins can switch between different conformations in response to stimuli, such as pH or temperature variations, or to the binding of ligands. Such plasticity and its kinetics can have a crucial functional role, and their characterization has taken center stage in protein research. As an example, Topoisomerases are particularly interesting enzymes capable of managing tangled and supercoiled double-stranded DNA, thus facilitating many physiological processes. In this work, we describe the use of a cantilever-based nanomotion sensor to characterize the dynamics of human topoisomerase II (Topo II) enzymes and their response to different kinds of ligands, such as ATP, which enhance the conformational dynamics. The sensitivity and time resolution of this sensor allow determining quantitatively the correlation between the ATP concentration and the rate of Topo II conformational changes. Furthermore, we show how to rationalize the experimental results in a comprehensive model that takes into account both the physics of the cantilever and the dynamics of the ATPase cycle of the enzyme, shedding light on the kinetics of the process. Finally, we study the effect of aclarubicin, an anticancer drug, demonstrating that it affects directly the Topo II molecule inhibiting its conformational changes. These results pave the way to a new way of studying the intrinsic dynamics of proteins and of protein complexes allowing new applications ranging from fundamental proteomics to drug discovery and development and possibly to clinical practice.     

Selection of Aptamers for Mature White Adipocytes by Cell SELEX Using Flow Cytometry

Background

Adipose tissue, mainly composed of adipocytes, plays an important role in metabolism by regulating energy homeostasis. Obesity is primarily caused by an abundance of adipose tissue. Therefore, specific targeting of adipose tissue is critical during the treatment of obesity, and plays a major role in overcoming it. However, the knowledge of cell-surface markers specific to adipocytes is limited.

Methods and Results

We applied the CELL SELEX (Systematic Evolution of Ligands by EXponential enrichment) method using flow cytometry to isolate molecular probes for specific recognition of adipocytes. The aptamer library, a mixture of FITC-tagged single-stranded random DNAs, is used as a source for acquiring molecular probes. With the increasing number of selection cycles, there was a steady increase in the fluorescence intensity toward mature adipocytes. Through 12 rounds of SELEX, enriched aptamers showing specific recognition toward mature 3T3-L1 adipocyte cells were isolated. Among these, two aptamers (MA-33 and 91) were able to selectively bind to mature adipocytes with an equilibrium dissociation constant (Kd) in the nanomolar range. These aptamers did not bind to preadipocytes or other cell lines (such as HeLa, HEK-293, or C2C12 cells). Additionally, it was confirmed that MA-33 and 91 can distinguish between mature primary white and primary brown adipocytes.

Conclusions

These selected aptamers have the potential to be applied as markers for detecting mature white adipocytes and monitoring adipogenesis, and could emerge as an important tool in the treatment of obesity.     

Determination of the Total Microbial Abundance in Black Sea Bottom Sediments Using Flow Cytometry

Microbiology - The known approaches to sample preparation have been improved to achieve a more complete detection of microorganisms of the Black Sea bottom sediments using flow cytometry of SYBR...     

利用流式细胞仪测定荚蒾属植物的基因组大小

荚蒾属 (Viburnum) 植物在园林中广泛用作观赏灌木,并且其具有优良园艺性状的杂交种在世界范围内越来越受欢迎。本研究利用流式细胞仪测定了14种荚蒾属植物的基因组大小。二倍体中基因组大小变化范围是255pg（陕西荚蒾）到426pg（琼花）。同时,琼花的核型也较不对称,这可能反应了它的育种历史。四倍体物种珊瑚树的基因组大小（762pg）是其他二倍体物种的两倍还多,这揭示了该属的多倍化在进化中可能并不遥远。该研究为荚蒾属细胞遗传学和分类学的深入研究奠定了基础,并为该属杂交育种提供有用的信息。     

Temporal Tracking of Cell Cycle Progression Using Flow Cytometry without the Need for Synchronization

This protocol describes a method to permit the tracking of cells through the cell cycle without requiring the cells to be synchronized. Achieving cell synchronization can be difficult for many cell systems. Standard practice is to block cell cycle progression at a specific stage and then release the accumulated cells producing a wave of cells progressing through the cycle in unison. However, some cell types find this block toxic resulting in abnormal cell cycling, or even mass death. Bromodeoxyuridine (BrdU) uptake can be used to track the cell cycle stage of individual cells. Cells incorporate this synthetic thymidine analog, while synthesizing new DNA during S phase. By providing BrdU for a brief period it is possible to mark a pool of cells that were in S phase while the BrdU was present. These cells can then be tracked through the remainder of the cell cycle and into the next round of replication, permitting the duration of the cell cycle phases to be determined without the need to induce a potentially toxic cell cycle block. It is also possible to determine and correlate the expression of both internal and external proteins during subsequent stages of the cell cycle. These can be used to further refine the assignment of cell cycle stage or assess effects on other cellular functions such as checkpoint activation or cell death.     

Identification of Phytoplankton from Flow Cytometry Data by Using Radial Basis Function Neural Networks

We describe here the application of a type of artificial neural network, the Gaussian radial basis function (RBF) network, in the identification of a large number of phytoplankton strains from their 11-dimensional flow cytometric characteristics measured by the European Optical Plankton Analyser instrument. The effect of network parameters on optimization is examined. Optimized RBF networks recognized 34 species of marine and freshwater phytoplankton with 91.5% success overall. The relative importance of each measured parameter in discriminating these data and the behavior of RBF networks in response to data from “novel” species (species not present in the training data) were analyzed.     

A Bead-Based Method for Multiplexed Identification and Quantitation of DNA Sequences Using Flow Cytometry

A new multiplexed, bead-based method which utilizes nucleic acid hybridizations on the surface of microscopic polystyrene spheres to identify specific sequences in heterogeneous mixtures of DNA sequences is described. The method consists of three elements: beads (5.6-μm diameter) with oligomer capture probes attached to the surface, three fluorophores for multiplexed detection, and flow cytometry instrumentation. Two fluorophores are impregnated within each bead in varying amounts to create different bead types, each associated with a unique probe. The third fluorophore is a reporter. Following capture of fluorescent cDNA sequences from environmental samples, the beads are analyzed by flow cytometric techniques which yield a signal intensity for each capture probe proportional to the amount of target sequences in the analyte. In this study, a direct hybrid capture assay was developed and evaluated with regard to sequence discrimination and quantitation of abundances. The target sequences (628 to 728 bp in length) were obtained from the 16S/23S intergenic spacer region of microorganisms collected from polluted groundwater at the nuclear waste site in Hanford, Wash. A fluorescence standard consisting of beads with a known number of fluorescent DNA molecules on the surface was developed, and the resolution, sensitivity, and lower detection limit for measuring abundances were determined. The results were compared with those of a DNA microarray using the same sequences. The bead method exhibited far superior sequence discrimination and possesses features which facilitate accurate quantitation.