Determination of individual cell Michaelis-Menten constants

Automated identification and tracking of cells in Cytometry of Reaction Rate Constant (CRRC)

Cytometry of Reaction Rate Constant (CRRC) is a method for studying cell-population heterogeneity using time-lapse fluorescence microscopy, which allows one to follow reaction kinetics in individual cells. The current and only CRRC workflow utilizes a single fluorescence image to manually identify cell contours which are then used to determine fluorescence intensity of individual cells in the entire time-stack of images. This workflow is only reliable if cells maintain their positions during the time-lapse measurements. If the cells move, the original cell contours become unsuitable for evaluating intracellular fluorescence and the CRRC experiment will be inaccurate. The requirement of invariant cell positions during a prolonged imaging is impossible to satisfy for motile cells. Here we report a CRRC workflow developed to be applicable to motile cells. The new workflow combines fluorescence microscopy with transmitted-light microscopy and utilizes a new automated tool for cell identification and tracking. A transmitted-light image is taken right before every fluorescence image to determine cell contours, and cell contours are tracked through the time-stack of transmitted-light images to account for cell movement. Each unique contour is used to determine fluorescence intensity of cells in the associated fluorescence image. Next, time dependencies of the intracellular fluorescence intensities are used to determine each cell's rate constant and construct a kinetic histogram "number of cells vs rate constant." The new workflow's robustness to cell movement was confirmed experimentally by conducting a CRRC study of cross-membrane transport in motile cells. The new workflow makes CRRC applicable to a wide range of cell types and eliminates the influence of cell motility on the accuracy of results. Additionally, the workflow could potentially monitor kinetics of varying biological processes at the single-cell level for sizable cell populations. Although our workflow was designed ad hoc for CRRC, this cell-segmentation/cell-tracking strategy also represents an entry-level, user-friendly option for a variety of biological assays (i.e., migration, proliferation assays, etc.). Importantly, no prior knowledge of informatics (i.e., training a model for deep learning) is required.

Analytical Challenges in Development of Chemoresistance Predictors for Precision Oncology

Chemoresistance, i.e., tumor insensitivity to chemotherapy, shortens life expectancy of cancer patients. Despite the availability of new treatment options, initial systemic regimens for solid tumors are dominated by a set of standard chemotherapy drugs, and alternative therapies are used only when a patient has demonstrated chemoresistance clinically. Chemoresistance predictors use laboratory parameters measured on tissue samples to predict the patient's response to chemotherapy and help to avoid application of chemotherapy to chemoresistant patients. Despite thousands of publications on putative chemoresistance predictors, there are only about a dozen predictors that are sufficiently accurate for precision oncology. One of the major reasons for inaccuracy of predictors is inaccuracy of analytical methods utilized to measure their laboratory parameters: an inaccurate method leads to an inaccurate predictor. The goal of this study was to identify analytical challenges in chemoresistance-predictor development and suggest ways to overcome them. Here we describe principles of chemoresistance predictor development via correlating a clinical parameter, which manifests disease state, with a laboratory parameter. We further classify predictors based on the nature of laboratory parameters and analyze advantages and limitations of different predictors using the reliability of analytical methods utilized for measuring laboratory parameters as a criterion. Our eventual focus is on predictors with known mechanisms of reactions involved in drug resistance (drug extrusion, drug degradation, and DNA damage repair) and using rate constants of these reactions to establish accurate and robust laboratory parameters. Many aspects and conclusions of our analysis are applicable to all types of disease biomarkers built upon the correlation of clinical and laboratory parameters.

Discrimination of leukemic Jurkat cells from normal lymphocytes via novo label-free cytometry based on fluctuation of image gray values

We introduce a simple, label-free cytometry technique, based on the spatio-temporal fluctuation analysis of pixel gray levels of a cell image utilizing the Gray Level Information Entropy (GLIE) function. In this study, the difference in GLIE random fluctuations and its biophysical etiology in a comparison cell model of leukemic Jurkat cells and human healthy donor lymphocytes was explored. A combination of common bright field microscopy and a unique imaging dish wherein cells are individually held untethered in a picoliter volume matrix of optical chambers was used. Random GLIE fluctuations were found to be greater in malignant Jurkat cells than in benign lymphocytes, while these fluctuations correlate with intracellular vesicle Mean Square Displacement (MSD) values and are inhibited by myosin-2 and adenosine triphosphate (ATP) inhibitors. These results suggest that the incoherent active forces acting on the cytoskeleton which cause mechanical dissipative fluctuation of the cytoskeletal and related intracellular content are the biophysical cellular mechanism behind the GLIE random fluctuation results. Analysis of the results in Jurkat cells and normal lymphocytes suggests the possible potential of this simple and automated label-free cytometry to identify malignancy, particularly in a diagnostic setup of multiple cell examination.

Cytometry of Reaction Rate Constant: Measuring Reaction Rate Constant in Individual Cells To Facilitate Robust and Accurate Analysis of Cell-Population Heterogeneity

Robust and accurate analysis of cell-population heterogeneity is challenging but required in many areas of biology and medicine. In particular, it is pivotal to the development of reliable cancer biomarkers. Here, we prove that cytometry of reaction rate constant (CRRC) can facilitate such analysis when the kinetic mechanism of a reaction associated with the heterogeneity is known. In CRRC, the cells are loaded with a reaction substrate, and its conversion into a product is followed by time-lapse fluorescence microscopy at the single-cell level. A reaction rate constant is determined for every cell, and a kinetic histogram "number of cells versus the rate constant" is used to determine quantitative parameters of reaction-based cell-population heterogeneity. Such parameters include, for example, the number and sizes of subpopulations. In this work, we applied CRRC to a reaction of substrate extrusion from cells by ATP-binding cassette (ABC) transporters. This reaction is viewed as a potential basis for predictive biomarkers of chemoresistance in cancer. CRRC proved to be robust (insensitive to variations in experimental settings) and accurate for finding quantitative parameters of cell-population heterogeneity. In contrast, a typical nonkinetic analysis, performed on the same data sets, proved to be both nonrobust and inaccurate. Our results suggest that CRRC can potentially facilitate the development of reliable cancer biomarkers on the basis of quantitative parameters of cell-population heterogeneity. A plausible implementation scenario of CRRC-based development, validation, and clinical use of a predictor of ovarian cancer chemoresistance to its frontline therapy is presented.

Photobleaching of fluorescein as a probe for oxidative stress in single cells

BACKGROUND

ROS are involved in the regulation of many physiological and pathological processes. Apoptosis and necrosis are processes that are induced by changes in concentrations of Reactive Oxygen Species (ROS). This study aims to detect and quantify the cellular response to changing ROS concentrations in the scope of apoptosis and necrosis.

METHODS

Photobleaching of the fluorescent substrate fluorescein is used as a probe to detect the response of individual Jurkat-T-lymphocytes and Prostate-Cancer-3(PC-3) cells to oxidative stress, induced by hydrogen peroxide (H₂O₂). A kinetic model is proposed to describe changes in intracellular dye quantities due to photobleaching, dye hydrolysis, influx and leakage, yielding a single time-dependent decaying exponent+constant.

RESULTS

Fluorescein photobleaching is controlled and used to detect intracellular ROS. An increase in the decay time of fluorescence of intracellular fluorescein (slow photobleaching) was measured from cells incubated with H₂O₂ at 50 μM. At higher H₂O₂ concentrations a decrease in the decay time was measured (fast photobleaching), in contrast to in vitro results with fluorescein and H₂O₂ in phosphate buffer saline (PBS), where the addition of H₂O₂ decreases the decay time, regardless of the irradiation dose used.

CONCLUSIONS

The anomalous, ROS-concentration dependent reduction of the photobleaching rate in cells, as opposed to solutions, might indicate on the regulation of the activity of intracellular oxidative-stress protective mechanisms, as seen earlier with other methods.

SIGNIFICANCE

Assessing photobleaching via the time decay of the fluorescence intensity of an ROS-sensitive fluorophore may be adapted to monitor oxidative stress or ROS-related processes in cells.

Correlation between multi-drug resistance-associated membrane transport in clonal cancer cells and the cell cycle phase

Multidrug resistance driven by ABC membrane transporters is one of the major reasons for treatment failure in human malignancy. Some limited evidence has previously been reported on the cell cycle dependence of ABC transporter expression. However, it has never been demonstrated that the functional activity of these transporters correlates with the cell cycle position. Here, we studied the rate of intrinsic ABC transport in different phases of the cell cycle in cultured MCF-7 breast cancer cells. The rate was characterized in terms of the efflux kinetics from cells loaded with an ABC transporter substrate. As averaging the kinetics over a cell population could lead to errors, we studied kinetics of ABC transport at the single-cell level. We found that the rate of ABC transport in MCF-7 cells could be described by Michaelis-Menten kinetics with two classical parameters, V(max) and K(M). Each of these parameters showed similar unimodal distributions with different positions of maxima for cell subpopulations in the 2c and 4c states. Compared to the 2c cells, the 4c cells exhibited greater V(max) values, indicating a higher activity of transport. They also exhibited a greater V(max)/K(M) ratio, indicating a higher efficiency of transport. Our findings suggest that cell cycle-related modulation of MDR may need to be taken into account when designing chemotherapy regimens which include cytostatic agents.

A cluster pattern algorithm for the analysis of multiparametric cell assays

The issue of multiparametric analysis of complex single cell assays of both static and flow cytometry (SC and FC, respectively) has become common in recent years. In such assays, the analysis of changes, applying common statistical parameters and tests, often fails to detect significant differences between the investigated samples. The cluster pattern similarity (CPS) measure between two sets of gated clusters is based on computing the difference between their density distribution functions' set points. The CPS was applied for the discrimination between two observations in a four-dimensional parameter space. The similarity coefficient (r) ranges between 0 (perfect similarity) to 1 (dissimilar). Three CPS validation tests were carried out: on the same stock samples of fluorescent beads, yielding very low r's (0, 0.066); and on two cell models: mitogenic stimulation of peripheral blood mononuclear cells (PBMC), and apoptosis induction in Jurkat T cell line by H2O2. In both latter cases, r indicated similarity (r < 0.23) within the same group, and dissimilarity (r > 0.48) otherwise. This classification and algorithm approach offers a measure of similarity between samples. It relies on the multidimensional pattern of the sample parameters. The algorithm compensates for environmental drifts in this apparatus and assay; it also may be applied to more than four dimensions.

Breast cancer detection by Michaelis-Menten constants via linear programming

The Michaelis-Menten constants (K(m) and V(max)) operated by linear programming, were employed for detection of breast cancer. The rate of enzymatic hydrolysis of fluorescein diacetate (FDA) in living peripheral blood mononuclear cells (PBMC), derived from healthy subjects and breast cancer (BC) patients, was assessed by measuring the fluorescence intensity (FI) in individual cells under incubation with either the mitogen phytohemagglutinin (PHA) or with tumor tissue, as compared to control. The suggested model diagnoses three conditions: (1) the subject is diseased, (2) the diagnosis is uncertain, and (3) the subject is not diseased. Out of 50 subjects tested, 44 were diagnosed correctly, in 5 cases the diagnosis was not certain, and 1 subject was diagnosed incorrectly.

Tagging and tracking individual networks within a complex mitochondrial web with photoactivatable GFP

Assembly of mitochondria into networks supports fuel metabolism and calcium transport and is involved in the cellular response to apoptotic stimuli. A mitochondrial network is defined as a continuous matrix lumen whose boundaries limit molecular diffusion. Observation of individual networks has proven challenging in live cells that possess dense populations of mitochondria. Investigation into the electrical and morphological properties of mitochondrial networks has therefore not yielded consistent conclusions. In this study we used matrix-targeted, photoactivatable green fluorescent protein to tag single mitochondrial networks. This approach, coupled with real-time monitoring of mitochondrial membrane potential, permitted the examination of matrix lumen continuity and fusion and fission events over time. We found that adjacent and intertwined mitochondrial structures often represent a collection of distinct networks. We additionally found that all areas of a single network are invariably equipotential, suggesting that a heterogeneous pattern of membrane potential within a cell's mitochondria represents differences between discrete networks. Interestingly, fission events frequently occurred without any gross morphological changes and particularly without fragmentation. These events, which are invisible under standard confocal microscopy, redefine the mitochondrial network boundaries and result in electrically disconnected daughter units.

Application of a static fluorescence-based cytometer (the CellScan) in basic cytometric studies, clinical pharmacology, oncology and clinical immunology

The CellScan apparatus is a laser scanning cytometer enabling repetitive fluorescence intensity (FI) and polarization (FP) measurements in living cells, as a means of monitoring lymphocyte activation. The CellScan may serve as a tool for diagnosis of rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) as well as other autoimmune diseases by monitoring FP changes in peripheral blood lymphocytes (PBLs) following exposure to autoantigenic stimuli. Changes in FI and FP in atherosclerotic patients' PBLs following exposure to various stimuli have established the role of the immune system in atherosclerotic disease. The CellScan has been evaluated as a diagnostic tool for drug-allergy, based on FP reduction in PBLs following incubation with allergenic drugs. FI and FP changes in cancer cells have been found to be well correlated with the cytotoxic effect of anti-neoplastic drugs. In conclusion, the CellScan has a variety of applications in cell biology, immunology, cancer research and clinical pharmacology.

A novel mathematical model identifies potential factors regulating bone apposition

The development of pharmaceutical treatments for bone disease can be enhanced by mathematical models that predict their effects on matrix apposition during cancellous bone remodelling. Therefore, a mathematical model was constructed to simulate the rate of focal bone formation from the number of osteoid-forming osteoblasts at one microsite and their rate of activity. The number of mature osteoid-forming cells was simulated from a relationship describing the proliferation of preosteoblasts. Osteoblast activity was described by Michaelis-Menten enzyme kinetic equations adapted to describe cellular activity. The model incorporates the negative feedback effects on the rates of bone apposition due to the reduction in size of mature osteoblasts with continuing differentiation and the reduction in number of osteoid-forming cells with apoptosis and osteocyte formation. In addition, the rate of mineralisation is limited according to osteoid substrate availability. Results of sensitivity analysis revealed the amount of bone formed at one microsite to be more sensitive to changes in factors that controlled cell growth during proliferation and the number of mature osteoid-forming osteoblasts than to those that determined cellular activity. Matrix and osteocyte signalling were shown to have potentially important roles in controlling rates of osteoid apposition in normal, healthy bone. This simple model supports the critical role of controlled mitotic growth in normal bone apposition. It can also help to explain how the homeostatic processes of bone resorption and apposition during remodelling can be disrupted by growth factors that affect the mitotic fraction and division time of proliferative preosteoblast cells.

Sensitivity analysis of a novel mathematical model identifies factors determining bone resorption rates

The development of pharmaceutical treatments for bone disease can be enhanced by computational models that predict their effects on resorption and rates of remodeling. Therefore, a simple mathematical model was formulated to simulate erosion depth and duration of resorption, using Michaelis-Menten (M-M) equations to describe changing rates of cellular activity during the two phases of bone resorption. The model was based on histomorphometric data and cellular interactions that occur in the bone microenvironment cited from the literature. Availability of bone substrate for osteoclastic activity during Phase I was assumed to be limited by the ratio of RANKL (ligand for receptor activator for nuclear factor kappaB) to osteoprotegerin (OPG) ('effective RANKL'). The required presence of marrow stromal cell produced macrophage-colony stimulating factor (M-CSF) for osteoclast action was represented as a factor equal to 1 for healthy bone. Growth factors released from the matrix during Phase I were assumed to cause two negative feedback effects: (1) the inhibitory effect of transforming growth factor-beta1 (TGFbeta1)-induced production of OPG by marrow osteoblast stromal cells, reducing effective RANKL; (2) the apoptosis of osteoclast nuclei assumed to occur at high concentrations of TGFbeta. This signaled the end of Phase I. During Phase II, cellular activity to remove the collagen fibrils left behind by osteoclasts was also simulated by Michaelis-Menten kinetic equations. Results of sensitivity analysis revealed variation in resorption depth and duration to fluctuate within 6% and 7% of the baseline value for changes in most input parameters. However, resorption depth was reduced and the duration of resorption lengthened by both a decrease in matrix TGFbeta and an increase the apoptotic threshold. Furthermore, the duration of resorption, but not erosion depth, was sensitive to changes in the maximum rate of cellular activity during removal of collagen fibrils. This mathematical model, which simulates the changing rates of cellular activity, has identified factors that reduce the duration and depth of resorption. It also suggests new targets for modeling therapeutic intervention to slow the rate of bone remodeling.

Single-cell microbiology: tools, technologies, and applications

The field of microbiology has traditionally been concerned with and focused on studies at the population level. Information on how cells respond to their environment, interact with each other, or undergo complex processes such as cellular differentiation or gene expression has been obtained mostly by inference from population-level data. Individual microorganisms, even those in supposedly "clonal" populations, may differ widely from each other in terms of their genetic composition, physiology, biochemistry, or behavior. This genetic and phenotypic heterogeneity has important practical consequences for a number of human interests, including antibiotic or biocide resistance, the productivity and stability of industrial fermentations, the efficacy of food preservatives, and the potential of pathogens to cause disease. New appreciation of the importance of cellular heterogeneity, coupled with recent advances in technology, has driven the development of new tools and techniques for the study of individual microbial cells. Because observations made at the single-cell level are not subject to the "averaging" effects characteristic of bulk-phase, population-level methods, they offer the unique capacity to observe discrete microbiological phenomena unavailable using traditional approaches. As a result, scientists have been able to characterize microorganisms, their activities, and their interactions at unprecedented levels of detail.

Monitoring of Intracellular Enzyme Kinetic Characteristics of Peripheral Mononuclear Cells in Breast Cancer Patients

A new methodology for the detection of functional response of peripheral blood mononuclear cells against breast cancer (BC) antigens was developed. The method is based on cellular enzymatic activity measurements, using a fluorogenic substrate. We used this method to estimate the kinetic activity of lymphocytes derived from cancer patients and healthy donors. The aim of the study was to determine a possible correlation between the basic characteristics (K(m) and V(max)) of biochemical enzymatic reactions in live peripheral white mononuclear cells and common clinical-pathological characteristics in BC patients. Our method shows that the enzymatic activity, upon interaction with mitogen or tumor antigens, of the peripheral blood cells in BC patients is different from the enzymatic reactions in healthy individuals. This holds true in the early stages, and the difference persists throughout all of the stages of the disease. This difference is manifested, primarily, by an increase in the K(m) values after cell incubation with tumor tissue. It was also demonstrated that higher K(m) values of tumor tissue-activated peripheral blood mononuclear cells are associated with a better prognostic status of the BC patients (lymph node-negative tumors, hormone receptor preservation, and the absence of Her-2/neu protein overexpression). Thus, the present methodology may serve as an additional criterion for prognosis and monitoring, both in BC patients, and in individuals associated with high cancer risk.

A novel approach for on line monitoring of apoptotic cell shrinkage in individual live lymphocytes

The apoptotic process occurs asynchronically in most cell populations and its duration is variable. Therefore, the ability to continuously monitor the death process occurring in individual blood cells before, during and following apoptosis induction is crucial in the evaluation of the efficiency of pro- or anti-apoptotic drugs. We applied a kinetic approach by performing real time measurements of individual living cells. This approach is based on an easy and unique method for monitoring intracellular staining reaction, which accompanied early apoptotic cell shrinkage. The intracellular enzymatic reaction rates were determined by taking repeated, sequential measurements of fluorescence intensity of the same individual cells. These rates were found to correlate with the respective radii of the cells under different conditions, and to decrease following apoptosis induction. The ability to remeasure the same cell before and after apoptosis induction enabled the detection of specific individual lymphocytes, which were more susceptible or resistant to pro-apoptotic stimulus.

Comparison of reagents for shape analysis of fixed cells by automated fluorescence microscopy

BACKGROUND

Cell size and shape have been implicated as potentiators of intracellular signaling events and as indicators of abnormal cell behavior. Automated microscopy and image analysis can provide quantitative information about the size and shape of cultured cells, but it requires that the edge of a cell be clearly identified. Generating adequate contrast at the edge of thin well-spread cells can be challenging.

METHODS

We compared six (five chemically reactive and one lipophilic) fluorescent molecules--5-chloromethyl fluorescein diacetate (CMFDA, CellTracker green), fluorescein-5-maleimide, fluorescein-5-isothiocyanate (FITC), 5-iodoacetamidofluorescein, 5(6)-carboxy fluorescein-N-hydroxysuccinimidyl ester, and N-fluorescein-1,2-dihexadecanoyl-sn-glycerol-3-phosphoethanolamine--for their effectiveness as stains for automated morphology analysis of fixed cells.

RESULTS

Formaldehyde-fixed rat aortic smooth muscle cells stained with fluorescein-5-maleimide or FITC exhibited an average intensity that was at least twofold greater than cells stained with CMFDA even when subjected to a 25-fold shorter exposure time. Cell area determined with the higher intensity stains was less sensitive to threshold settings during automated cell morphology analysis.

CONCLUSION

A procedure that includes the use of fluorescein-5-maleimide or FITC for staining fixed cell provides sensitivity sufficient to permit rapid, automated, morphologic analysis of well-spread fixed cells.

Fluorescence polarization: a novel indicator of cardiomyocyte contraction

The changes measured in intracellular fluorescein fluorescence polarization (IFFP) are used as a new tool for tracing cytoplasmic effects during contractile cycles of cardiac myocytes (1-2-day-old rat hearts), in addition to the established Ca(2+) monitoring and/or videometric methods of tracking cell-shortening. This novel method was found to be non-intrusive to the contraction cycles. The decay of the transient IFFP signal (from 0.220+/-0.01 to 0.170+/-0.013) seems to be closely related to the extended phase of contractile activation. This fact was further supported when Ca(2+) exchanger inhibitor was introduced and significantly decreased (90%) the rate of beats of contraction and IFFP, but not the Ca(2+) beat rate changes. This result suggests that the IFFP indicator is probably associated with the physiological activation, rather than with Ca(2+) alterations. The IFFP measure monitors the average of effective changes in the micro-viscosity of the cytoplasm protein matrix, associated with cellular activation.