Homeostatic IL-13 in healthy skin directs dendritic cell differentiation to promote TH2 and inhibit TH17 cell polarization.

The signals driving the adaptation of type 2 dendritic cells (DC2s) to diverse peripheral environments remain mostly undefined. We show that differentiation of CD11blo migratory DC2s-a DC2 population unique to the dermis-required IL-13 signaling dependent on the transcription factors STAT6 and KLF4, whereas DC2s in lung and small intestine were STAT6-independent. Similarly, human DC2s in skin expressed an IL-4 and IL-13 gene signature that was not found in blood, spleen and lung DCs. In mice, IL-13 was secreted homeostatically by dermal innate lymphoid cells and was independent of microbiota, TSLP or IL-33. In the absence of IL-13 signaling, dermal DC2s were stable in number but remained CD11bhi and showed defective activation in response to allergens, with diminished ability to support the development of IL-4+GATA3+ helper T cells (TH), whereas antifungal IL-17+RORγt+ TH cells were increased. Therefore, homeostatic IL-13 fosters a noninflammatory skin environment that supports allergic sensitization.

Kinetic analysis of intracellular Hoechst 33342--DNA interactions by flow cytometry: misinterpretation of side population status?

We outline a simple approach involving instrument setup and calibration for the analysis of Hoechst dye 33342-loading in human cell lines for exploring heterogeneity in dye efflux efficiency and the status of side population (SP) A549 lung cancer cells. Dual excitation 488 nm/multiline UV (351-364 nm) flow cytometry was used to confirm ABCG2-specific inhibition of dye efflux using Fumitremorgin C. Transporter gene expression, assayed by qRT-PCR, confirmed higher expression of ABCG2 versus ABCB1, reiterated in a cloned subline. Coexpression of aldehyde dehydrogenase genes ranked as aldehyde dehydrogenase class 1A1 (ALDH1A1) > ALDH3A1 > ALDH3, relative expression of all genes was again reiterated in a cloned subline. Permeabilized cells were used to create red:violet (660:405 nm Em wavelengths) ratiometric references for mapping temporal changes in Hoechst 33342-DNA fluorescence in live cells. A live cell "kinetic SP gate" tracked progressive dye loading of the whole population and coapplication of the far red (>695 nm wavelength) fluorescing dye DRAQ7 enabled viable cell gating. Kinetic gating revealed a continuum for dye accumulation suggesting that SP enumeration is critically dependent upon the nonlinear relationship of the spectral shift with progressive dye-DNA binding and thus requires accurate definition. To this end, permeabilized cell reference samples permit reproducible instrument setup, guide gate boundaries for SP and compromised cells, and offer a simple means of comparing SP enumeration across laboratory sites/platforms. Our approach reports the dynamic range for the spectral shift, revealing noninformative staining conditions and explaining a source of variability for SP enumeration. We suggest that live cell kinetic sorting of all cells with the same dye:DNA load but with differences in efflux capacity can be used to explore drug resistance capability without prejudice. The SP phenotype should be regarded as a kinetic parameter and not a fixed characteristic--critical for functional assay design and the interpretation of heterogeneity.

Interoperability of time series cytometric data: a cross platform approach for modeling tumor heterogeneity.

The cell cycle, with its highly conserved features, is a fundamental driver for the temporal control of cell proliferation-while abnormal control and modulation of the cell cycle are characteristic of tumor cells. The principal aim in cancer biology is to seek an understanding of the origin and nature of innate and acquired heterogeneity at the cellular level, driven principally by temporal and functional asynchrony. A major bottleneck when mathematically modeling these biological systems is the lack of interlinked structured experimental data. This often results in the in silico models failing to translate the specific hypothesis into parameterized terms that enable robust validation and hence would produce suitable prediction tools rather than just simulation tools. The focus has been on linking data originating from different cytometric platforms and cell-based event analysis to inform and constrain the input parameters of a compartmental cell cycle model, hence partly measuring and deconvolving cell cycle heterogeneity within a tumor population. Our work has addressed the concept that the interoperability of cytometric data, derived from different cytometry platforms, can complement as well as enhance cellular parameters space, thus providing a more broader and in-depth view of the cellular systems. The initial aim was to enable the cell cycle model to deliver an improved integrated simulation of the well-defined and constrained biological system. From a modeling perspective, such a cross platform approach has provided a paradigm shift from conventional cross-validation approaches, and from a bioinformatics perspective, novel computational methodology has been introduced for integrating and mapping continuous data with cross-sectional data. This establishes the foundation for developing predictive models and in silico tracking and prediction of tumor progression

Flow-based cytometric analysis of cell cycle via simulated cell populations.

We present a new approach to the handling and interrogating of large flow cytometry data where cell status and function can be described, at the population level, by global descriptors such as distribution mean or co-efficient of variation experimental data. Here we link the "real" data to initialise a computer simulation of the cell cycle that mimics the evolution of individual cells within a larger population and simulates the associated changes in fluorescence intensity of functional reporters. The model is based on stochastic formulations of cell cycle progression and cell division and uses evolutionary algorithms, allied to further experimental data sets, to optimise the system variables. At the population level, the in-silico cells provide the same statistical distributions of fluorescence as their real counterparts; in addition the model maintains information at the single cell level. The cell model is demonstrated in the analysis of cell cycle perturbation in human osteosarcoma tumour cells, using the topoisomerase II inhibitor, ICRF-193. The simulation gives a continuous temporal description of the pharmacodynamics between discrete experimental analysis points with a 24 hour interval; providing quantitative assessment of inter-mitotic time variation, drug interaction time constants and sub-population fractions within normal and polyploid cell cycles. Repeated simulations indicate a model accuracy of +/-5%. The development of a simulated cell model, initialized and calibrated by reference to experimental data, provides an analysis tool in which biological knowledge can be obtained directly via interrogation of the in-silico cell population. It is envisaged that this approach to the study of cell biology by simulating a virtual cell population pertinent to the data available can be applied to "generic" cell-based outputs including experimental data from imaging platforms.

Long-term time series analysis of quantum dot encoded cells by deconvolution of the autofluorescence signal.

The monitoring of cells labeled with quantum dot endosome-targeted markers in a highly proliferative population provides a quantitative approach to determine the redistribution of quantum dot signal as cells divide over generations. We demonstrate that the use of time-series flow cytometry in conjunction with a stochastic numerical simulation to provide a means to describe the proliferative features and quantum dot inheritance over multiple generations of a human tumor population. However, the core challenge for long-term tracking where the original quantum dot fluorescence signal over time becomes redistributed across a greater cell number requires accountability of background fluorescence in the simulation. By including an autofluorescence component, we are able to continue even when this signal predominates (i.e., >80% of the total signal) and obtain valid readouts of the proliferative system. We determine the robustness of the technique by tracking a human osteosarcoma cell population over 8 days and discuss the accuracy and certainty of the model parameters obtained. This systems biology approach provides insight into both cell heterogeneity and division dynamics within the population and furthermore informs on the lineage history of its members.

Single cell tracking reveals that Msh2 is a key component of an early-acting DNA damage-activated G2 checkpoint.

Dysfunction of cell-cycle checkpoints in DNA mismatch repair (MMR)-deficient cells in response to DNA damage has implications for anticancer therapy and genetic instability. We have studied the cell-cycle effects of MMR deficiency (Msh2(-/-)) in primary mouse embryonic fibroblasts (MEFs) exposed to cisplatin (10 microM x 1 h) using time-lapse microscopy. Kinetic responses of MEFs from different embryos and passage ages varied, but we report a consistent drug-induced inhibition of mitotic entry (approx. 50%). There was a loss of an early-acting (<5 h) delay in G2 to M transition in Msh2(-/-) cells, although a later-acting G2 arrest was apparently normal. This suggests that Msh2 primarily acts to delay mitotic entry of cells already in G2, that is, DNA damage incurred during G2 does not influence the cell once committed to mitotic traverse. Irrespective of Msh2 status, cisplatin treatment and the incurred DNA damage did not effect mitotic traverse or show any evidence for early (within 24 h) cell death. The results indicate that Msh2(-/-) status can result in the premature commitment to mitosis of a cell subpopulation, determined by the fraction residing in G2 at the time of damage induction. The findings suggest a new route to MMR-driven genetic instability that does not rely primarily on the integrity of the late-acting checkpoint.

Microtubule stress modifies intra-nuclear location of Msh2 in mouse embryonic fibroblasts.

The maintenance of genomic stability in mitotic and meiotic cycles through mismatch repair (MMR) demands the coordination of MMR functions with multiple processes including cell cycle traverse, linked changes in microtubule dynamics, protein translocation at chromatin sites and checkpoint activation. We have studied changes in the intracellular location of the MMR protein Msh2 in response to mitosis, microtubule disruption by colcemid and DNA damage induction by cis-platin in mouse embryonic fibroblasts (MEFs). Image analysis indicated that MEFs have a normally high nuclear retention of Msh2 during interphase with a precipitous dispersal of protein from chromatin sites into the cytoplasm at mitosis. Dispersal was also observed in cisplatin- and colcemid-treated interphase MEFs without any change in the overall Msh2 levels throughout the cell cycle. There was no evidence of co-localization of the punctate cytoplasmic Msh2 foci with any microtubule structures and knockout of Msh2 altered neither the extent of microtubule disruption nor the functional activation of the spindle assembly checkpoint by colcemid. Critically, extra-nuclear relocation of protein did not alter the ability to mount an Msh2-dependent G2 checkpoint delay in response to cisplatin-induced DNA damage. Depletion of the nuclear pool of Msh2 protein in cells undergoing dispersal was found to involve a rapid relocation of protein from AT-rich chromatin sites as defined by coassociation studies exploiting a newly-characterized base-pair preference of the fluorescent DNA binding probe DRAQ5. The study reveals the unexpected mobility of MMR protein pools during the MEF cell cycle and in response to different stress-inducing agents. The results link for the first time microtubule-integrity with intra-nuclear Msh2 protein dynamics. The high nuclear retention of Msh2 in interphase MEFs is in contrast to human tumor cells while the observations on protein dispersal suggest that only low levels of nuclear-located Msh2 are needed for G2 checkpoint activation by DNA damage.

Time-lapse microscopy approaches to track cell cycle and lineage progression at the single-cell level.

Time-lapse microscopy can be described as the repeated collection of an image (in n-dimensions; x, y, z, λ) or field of view from a microscope at discrete time intervals. The duration of the time interval defines the temporal resolution, which in turn characterizes the type of event detected. This unit describes the implementation of time-lapse microscopy to link initial cell cycle position during acute exposures to anti-cancer agents with anti-proliferative consequences for individual cells. The approach incorporates fundamental concepts arising from the ability to capture simple video sequences of cells from which it is possible to extract kinetic descriptors that reflect the interplay of mitosis and cell death in the growth of an unsynchronized tumor population. Utilizing a multi-well format enables the user to screen different drug derivatives, multiple dose ranges, or cell cultures with unique genetic backgrounds. The objective of this unit is to present the basic methodology for capturing time-lapse sequences and touch upon subsequent mining of the data for deriving event curves and possible cell lineage maps.

BH3 helix-derived biophotonic nanoswitches regulate cytochrome c release in permeabilised cells.

Dynamic physical interactions between proteins underpin all key cellular processes and are a highly attractive area for the development of research tools and medicines. Protein-protein interactions frequently involve α-helical structures, but peptides matching the sequences of these structures usually do not fold correctly in isolation. Therefore, much research has focused on the creation of small peptides that adopt stable α-helical structures even in the absence of their intended protein targets. We show that short peptides alkylated with azobenzene crosslinkers can be used to photo-stimulate mitochondrial membrane depolarization and cytochrome c release in permeabilised cells, the initial events of the intrinsic apoptosis pathway.

Automated cell identification and tracking using nanoparticle moving-light-displays.

An automated technique for the identification, tracking and analysis of biological cells is presented. It is based on the use of nanoparticles, enclosed within intra-cellular vesicles, to produce clusters of discrete, point-like fluorescent, light sources within the cells. Computational analysis of these light ensembles in successive time frames of a movie sequence, using k-means clustering and particle tracking algorithms, provides robust and automated discrimination of live cells and their motion and a quantitative measure of their proliferation. This approach is a cytometric version of the moving light display technique which is widely used for analyzing the biological motion of humans and animals. We use the endocytosis of CdTe/ZnS, core-shell quantum dots to produce the light displays within an A549, epithelial, lung cancer cell line, using time-lapse imaging with frame acquisition every 5 minutes over a 40 hour time period. The nanoparticle moving light displays provide simultaneous collection of cell motility data, resolution of mitotic traversal dynamics and identification of familial relationships allowing construction of multi-parameter lineage trees.

A transfer function approach to measuring cell inheritance.

BACKGROUND: The inheritance of cellular material between parent and daughter cells during mitosis is highly influential in defining the properties of the cell and therefore the population lineage. This is of particular relevance when studying cell population evolution to assess the impact of a disease or the perturbation due to a drug treatment. The usual technique to investigate inheritance is to use time-lapse microscopy with an appropriate biological marker, however, this is time consuming and the number of inheritance events captured are too low to be statistically meaningful. RESULTS: Here we demonstrate the use of a high throughput fluorescence measurement technique e.g. flow cytometry, to measure the fluorescence from quantum dot markers which can be used to target particular cellular sites. By relating, the fluorescence intensity measured between two time intervals to a transfer function we are able to deconvolve the inheritance of cellular material during mitosis. To demonstrate our methodology we use CdTe/ZnS quantum dots to measure the ratio of endosomes inherited by the two daughter cells during mitosis in the U2-OS, human osteoscarcoma cell line. The ratio determined is in excellent agreement with results obtained previously using a more complex and computational intensive bespoke stochastic model. CONCLUSIONS: The use of a transfer function approach allows us to utilise high throughput measurement of large cell populations to derive statistically relevant measurements of the inheritance of cellular material. This approach can be used to measure the inheritance of organelles, proteins etc. and also particles introduced to cells for drug delivery.

Statistical analysis of nanoparticle dosing in a dynamic cellular system.

The delivery of nanoparticles into cells is important in therapeutic applications and in nanotoxicology. Nanoparticles are generally targeted to receptors on the surfaces of cells and internalized into endosomes by endocytosis, but the kinetics of the process and the way in which cell division redistributes the particles remain unclear. Here we show that the chance of success or failure of nanoparticle uptake and inheritance is random. Statistical analysis of nanoparticle-loaded endosomes indicates that particle capture is described by an over-dispersed Poisson probability distribution that is consistent with heterogeneous adsorption and internalization. Partitioning of nanoparticles in cell division is random and asymmetric, following a binomial distribution with mean probability of 0.52-0.72. These results show that cellular targeting of nanoparticles is inherently imprecise due to the randomness of nature at the molecular scale, and the statistical framework offers a way to predict nanoparticle dosage for therapy and for the study of nanotoxins.

Single cell nanoparticle tracking to model cell cycle dynamics and compartmental inheritance.

Single cell encoding with quantum dots as live cell optical tracers for deriving proliferation parameters has been developed using modelling to investigate cell cycle and proliferative outputs of human osteosarcoma cells undergoing mitotic bypass and endocycle routing. A computer-based simulation of the evolving cell population provides information on the dilution and segregation of nanoparticle dose cell by cell division and allows quantitative assessment of patterns of division, at both single cell and including whole population level cell cycle routing, with no a-priori knowledge of the population proliferation potential. The output therefore provides a unique mitotic distribution function that represents a convolution of cell cycle kinetics (cell division) and the partitioning coefficient for the labelled cell compartment (daughter-daughter inheritance or lineage asymmetry). The current study has shown that the cellular quantum dot fluorescence reduced over time as the particles were diluted by the process of cell division and had the properties of a non-random highly asymmetric event. Asymmetric nanoparticle segregation in the endosomal compartment has major implications on cell-fate determining signaling pathways and could lead to an understanding of the origins of unique proliferation and drug-resistance characteristics within a tumour cell lineage.

Time-lapse microscopy approaches to track cell cycle progression at the single-cell level.

Time-lapse microscopy can be described as the repeated collection of a field of view from a microscope at discrete time intervals. The duration of the time interval defines the temporal resolution, which in turn characterizes the type of event detected. This unit describes the implementation of time-lapse microscopy to link initial cell cycle position during acute exposures to anti-cancer agents with anti-proliferative consequences for individual cells. The approach incorporates fundamental concepts arising from the ability to capture simple video sequences of cells from which it is possible to extract kinetic descriptors that reflect the interplay of mitosis and cell death in the growth of an unsynchronized tumor population. Utilizing a multi-well format enables the user to test different drug derivatives, multiple dose ranges, or cell cultures with unique genetic backgrounds. The objective of this unit is to present a generic methodology for capturing time-lapse sequences and subsequently mining the data for comprehensive event analysis.