Capacitance cytometry: Measuring biological cells one by one

Measuring the DNA content of eukaryotic cells is a fundamental task in biology and medicine. We have observed a linear relationship between the DNA content of eukaryotic cells and the change in capacitance that is evoked by the passage of individual cells across a 1-kHz electric field. This relationship is species-independent; consequently, we have developed a microfluidic technique—“capacitance cytometry”—that can be used to quantify the DNA content of single eukaryotic cells and to analyze the cell-cycle kinetics of populations of cells. Comparisons with standard flow cytometry demonstrate the sensitivity of this new technique.

Analysis of RNA-protein interactions by flow cytometry

Flow cytometry, in combination with advances in bead coding technologies, is maturing as a powerful high-throughput approach for analyzing molecular interactions. Applications of this technology include antibody assays and single nucleotide polymorphism mapping. This review describes the recent development of a microbead flow cytometric approach to analyze RNA-protein interactions and discusses emerging bead coding strategies that together will allow genome-wide identification of RNA-protein complexes. The microbead flow cytometric approach is flexible and provides new opportunities for functional genomic studies and small-molecule screening.

Determination of Coniothyrium minitans conidial and germling lectin avidity by flow cytometry and digital microscopy

The avidity of conidia and 48-h-old germlings of Coniothyrium minitans for FITC-conjugated lectins was characterised by flow cytometry and digital microscopy. Six isolates of C. minitans representing three morphological types were compared. Binding of Con A, SBA and WGA by conidial populations varied markedly in extent and pattern between isolates, however, with increasing culture age, conidia from all isolates demonstrated a significant reduction in lectin avidity. Germling isolates bound significantly different amounts of lectins and lectin binding differed significantly with locality. Spore walls of all germlings from all isolates bound more ConA compared with hyphal apices and mature hyphal walls. In contrast, hyphal apices of the majority of germling isolates, readily bound SBA and mature hyphal walls of germling isolates bound more WGA than other regions of the germlings. Such differential lectin binding by conidia and germlings may influence their specific surface interactions and adherence characteristics.

Single-cell ELISA and flow cytometry as methods for highlighting potential neuronal and astrocytic toxicant specificity

The timeline imposed by recent worldwide chemical legislation is not amenable to conventional in vivo toxicity testing, requiring the development of rapid, economical in vitro screening strategies which have acceptable predictive capacities. When acquiring regulatory neurotoxicity data, distinction on whether a toxic agent affects neurons and/or astrocytes is essential. This study evaluated neurofilament (NF) and glial fibrillary acidic protein (GFAP) directed single-cell (S-C) ELISA and flow cytometry as methods for distinguishing cell-specific cytoskeletal responses, using the established human NT2 neuronal/astrocytic (NT2.N/A) co-culture model and a range of neurotoxic (acrylamide, atropine, caffeine, chloroquine, nicotine) and non-neurotoxic (chloramphenicol, rifampicin, verapamil) test chemicals. NF and GFAP directed flow cytometry was able to identify several of the test chemicals as being specifically neurotoxic (chloroquine, nicotine) or astrocytoxic (atropine, chloramphenicol) via quantification of cell death in the NT2.N/A model at cytotoxic concentrations using the resazurin cytotoxicity assay. Those neurotoxicants with low associated cytotoxicity are the most significant in terms of potential hazard to the human nervous system. The NF and GFAP directed S-C ELISA data predominantly demonstrated the known neurotoxicants only to affect the neuronal and/or astrocytic cytoskeleton in the NT2.N/A cell model at concentrations below those affecting cell viability. This report concluded that NF and GFAP directed S-C ELISA and flow cytometric methods may prove to be valuable additions to an in vitro screening strategy for differentiating cytotoxicity from specific neuronal and/or astrocytic toxicity. Further work using the NT2.N/A model and a broader array of toxicants is appropriate in order to confirm the applicability of these methods.

Characterization of Acanthamoeba-microsphere association by multiparameter flow cytometry and confocal microscopy

Background: Acanthamoebae, in common with other protozoa, readily endocytose particulate material, which in turn may lead to the spread of infectious disease. Methods: Evaluation and quantification of plain and carboxylate FITC-microsphere association with acanthamoebal trophzoites was undertaken using a combination of flow cytometry and confocal microscopy. Trophozoites from strains and species of Acanthamoeba were exposed to plain and carboxylate FITC-microspheres. Microsphere size and aspects such as trophozoite starvation, maturity, and exposure to metabolic inhibitors were assessed. Results: All species and strains of Acanthamoeba readily endocytosed plain and carboxylate microspheres. Starving trophozoites significantly increased binding and potential ingestion of microspheres, whereas trophozoites of increasing maturity lost such abilities. Trophozoites showed a significant preference for 2.0- and 3.0-μm-diameter microspheres when compared with other sizes, which in turn could occupy much of the cytoplasm. The physiological inhibitors sodium azide, 2,4-clinitrophenol, and cytochalasin B reduced microsphere association with trophozoites; however, some microspheres still bound and associated with trophozoites after inhibitor exposure, a manifestation of both active and inactive agent involvement in microsphere endocytosis. Conclusions: Even though the origins of microsphere binding by acanthamoebal trophozoite remains shrouded, the combination of flow cytometry and confocal microscopy supported synergistic quantification and qualification of trophozoite-microsphere endocytosis. © 2006 International Society for Analytical Cytology.

A mathematical resolution to log transformations and the binning effect in applied processing of data in flow cytometry

This dissertation develops a new mathematical approach that overcomes the effect of a data processing phenomenon known as “histogram binning” inherent to flow cytometry data. A real-time procedure is introduced to prove the effectiveness and fast implementation of such an approach on real-world data. The histogram binning effect is a dilemma posed by two seemingly antagonistic developments: (1) flow cytometry data in its histogram form is extended in its dynamic range to improve its analysis and interpretation, and (2) the inevitable dynamic range extension introduces an unwelcome side effect, the binning effect, which skews the statistics of the data, undermining as a consequence the accuracy of the analysis and the eventual interpretation of the data. ^ Researchers in the field contended with such a dilemma for many years, resorting either to hardware approaches that are rather costly with inherent calibration and noise effects; or have developed software techniques based on filtering the binning effect but without successfully preserving the statistical content of the original data. ^ The mathematical approach introduced in this dissertation is so appealing that a patent application has been filed. The contribution of this dissertation is an incremental scientific innovation based on a mathematical framework that will allow researchers in the field of flow cytometry to improve the interpretation of data knowing that its statistical meaning has been faithfully preserved for its optimized analysis. Furthermore, with the same mathematical foundation, proof of the origin of such an inherent artifact is provided. ^ These results are unique in that new mathematical derivations are established to define and solve the critical problem of the binning effect faced at the experimental assessment level, providing a data platform that preserves its statistical content. ^ In addition, a novel method for accumulating the log-transformed data was developed. This new method uses the properties of the transformation of statistical distributions to accumulate the output histogram in a non-integer and multi-channel fashion. Although the mathematics of this new mapping technique seem intricate, the concise nature of the derivations allow for an implementation procedure that lends itself to a real-time implementation using lookup tables, a task that is also introduced in this dissertation. ^

Multidimensional classification and diagnosis of leukemia in flow cytometry

This research is to establish new optimization methods for pattern recognition and classification of different white blood cells in actual patient data to enhance the process of diagnosis. Beckman-Coulter Corporation supplied flow cytometry data of numerous patients that are used as training sets to exploit the different physiological characteristics of the different samples provided. The methods of Support Vector Machines (SVM) and Artificial Neural Networks (ANN) were used as promising pattern classification techniques to identify different white blood cell samples and provide information to medical doctors in the form of diagnostic references for the specific disease states, leukemia. The obtained results prove that when a neural network classifier is well configured and trained with cross-validation, it can perform better than support vector classifiers alone for this type of data. Furthermore, a new unsupervised learning algorithm---Density based Adaptive Window Clustering algorithm (DAWC) was designed to process large volumes of data for finding location of high data cluster in real-time. It reduces the computational load to ∼O(N) number of computations, and thus making the algorithm more attractive and faster than current hierarchical algorithms.

Spatial variability in Florida Bay particulate organic matter composition: combining flow cytometry with stable isotope analyses

Long-term management plans for restoration of natural flow conditions through the Everglades increase the importance of understanding potential nutrient impacts of increased freshwater delivery on Florida Bay biogeochemistry. Planktonic communities respond quickly to changes in water quality, thus spatial variability in community composition and relationships to nutrient parameters must be understood in order to evaluate future downstream impacts of modifications to Everglades hydrology. Here we present initial results combining flow cytometry analyses of phytoplankton and bacterial populations (0.1–50 μm size fraction) with measurements of δ13C and δ15N composition and dissolved inorganic nutrient concentrations to explore proxies for planktonic species assemblage compositions and nutrient cycling. Particulate organic material in the 0.1–50 μm size fraction was collected from five stations in Northeastern and Western Florida Bay to characterize spatial variability in species assemblage and stable isotopic composition. A dense bloom of the picocyanobacterium, Synechococcus elongatus, was observed at Western Florida Bay sites. Smaller Synechococcus sp. were present at Northeast sites in much lower abundance. Bacteria and detrital particles were also more abundant at Western Florida Bay stations than in the northeast region. The highest abundance of detritus occurred at Trout Creek, which receives freshwater discharge from the Everglades through Taylor Slough. In terms of nutrient availability and stable isotopic values, the S. elongatus population in the Western bay corresponded to low DIN (0.5 μM NH 4 + ; 0.2 μM NO 3 − ) concentrations and depleted δ15N signatures ranging from +0.3 to +0.8‰, suggesting that the bloom supported high productivity levels through N2-fixation. δ15N values from the Northeast bay were more enriched (+2.0 to +3.0‰), characteristic of N-recycling. δ13C values were similar for all marine Florida Bay stations, ranging from −17.6 to −14.4‰, however were more depleted at the mangrove ecotone station (−25.5 to −22.3‰). The difference in the isotopic values reflects differences in carbon sources. These findings imply that variations in resource availability and nutrient sources exert significant control over planktonic community composition, which is reflected by stable isotopic signatures.