DNA damage in response to an Ironman triathlon

The major aims of this study were to investigate the effect of an Ironman triathlon on DNA migration in the single cell gel electrophoresis assay, apoptosis and necrosis in the cytokinesis-block micronucleus cytome assay with lymphocytes and on changes of total antioxidant capacity in plasma. Blood samples were taken 2 days (d) before, within 20 min, 1 d, 5 d and 19 d post-race. The level of strand breaks decreased (p<0.05) immediately after the race, then increased (p<0.01) 1 d post-race and declined (p<0.01) until 19 d post-race. Apoptotic and necrotic cells decreased (p<0.01) and the total antioxidant status increased (p<0.01) immediately after the race. The results indicate that ultra-endurance exercise does not cause prolonged DNA damage in well-trained male athletes.

Label-free isolation of a prostate cancer cell among blood cells and the single-cell measurement of drug accumulation using an integrated microfluidic chip

Circulating tumor cells (CTCs) are found in the blood of patients with cancer. Although these cells are rare, they can provide useful information for chemotherapy. However, isolation of these rare cells from blood is technically challenging because they are small in numbers. An integrated microfluidic chip, dubbed as CTC chip, was designed and fabricated for conducting tumor cell isolation. As CTCs usually show multidrug resistance (MDR), the effect of MDR inhibitors on chemotherapeutic drug accumulation in the isolated single tumor cell is measured. As a model of CTC isolation, human prostate tumor cells were mixed with mouse blood cells and the labelfree isolation of the tumor cells was conducted based on cell size difference. The major advantages of the CTC chip are the ability for fast cell isolation, followed by multiple rounds of single-cell measurements, suggesting a potential assay for detecting the drug responses based on the liquid biopsy of cancer patients.

Evaluation of the alkaline comet assay and urinary 3-methyladenine excretion for monitoring DNA damage in melanoma patients treated with dacarbazine and tamoxifen

Purpose: To develop, using dacarbazine as a model, reliable techniques for measuring DNA damage and repair as pharmacodynamic endpoints for patients receiving chemotherapy. Methods: A group of 39 patients with malignant melanoma were treated with dacarbazine 1 g/m2 i.v. every 21 days. Tamoxifen 20 mg daily was commenced 24 h after the first infusion and continued until 3 weeks after the last cycle of chemotherapy. DNA strand breaks formed during dacarbazine-induced DNA damage and repair were measured in individual cells by the alkaline comet assay. DNA methyl adducts were quantified by measuring urinary 3-methyladenine (3-MeA) excretion using immunoaffinity ELISA. Venous blood was taken on cycles 1 and 2 for separation of peripheral blood lymphocytes (PBLs) for measurement of DNA strand breaks. Results: Wide interpatient variation in PBL DNA strand breaks occurred following chemotherapy, with a peak at 4 h (median 26.6 h, interquartile range 14.75- 40.5 h) and incomplete repair by 24 h. Similarly, there was a range of 3-MeA excretion with peak levels 4-10 h after chemotherapy (median 33 nmol/h, interquartile range 20.448.65 nmol/h). Peak 3-MeA excretion was positively correlated with DNA strand breaks at 4 h (Spearman's correlation coefficient, r = 0.39, P = 0.036) and 24 h (r = 0.46, P = 0.01). Drug-induced emesis correlated with PBL DNA strand breaks (Mann Whitney U-test, P = 0.03) but not with peak 3-MeA excretion. Conclusions: DNA damage and repair following cytotoxic chemotherapy can be measured in vivo by the alkaline comet assay and by urinary 3-MeA excretion in patients receiving chemotherapy.

Single-cell force spectroscopy, an emerging tool to quantify cell adhesion to biomaterials

Cell adhesion receptors play a central role in sensing and integrating signals provided by the cellular environment. Thus, understanding adhesive interactions at the cell-biomaterial interface is essential to improve the design of implants that should emulate certain characteristics of the cell's natural environment. Numerous cell adhesion assays have been developed; among these, atomic force microscopy-based single-cell force spectroscopy (AFM-SCFS) provides a versatile tool to quantify cell adhesion at physiological conditions. Here we discuss how AFM-SCFS can be used to quantify the adhesion of living cells to biomaterials and give examples of using AFM-SCFS in tissue engineering and regenerative medicine. We anticipate that in the near future, AFM-SCFS will be established in the biomaterial field as an important technique to quantify cell-biomaterial interactions and thereby will contribute to the optimization of implants, scaffolds, and medical devices.

Whole-brain imaging with single-cell resolution using chemical cocktails and computational analysis

Systems-level identification and analysis of cellular circuits in the brain will require the development of whole-brain imaging with single-cell resolution. To this end, we performed comprehensive chemical screening to develop a whole-brain clearing and imaging method, termed CUBIC (clear, unobstructed brain imaging cocktails and computational analysis). CUBIC is a simple and efficient method involving the immersion of brain samples in chemical mixtures containing aminoalcohols, which enables rapid whole-brain imaging with single-photon excitation microscopy. CUBIC is applicable to multicolor imaging of fluorescent proteins or immunostained samples in adult brains and is scalable from a primate brain to subcellular structures. We also developed a whole-brain cell-nuclear counterstaining protocol and a computational image analysis pipeline that, together with CUBIC reagents, enable the visualization and quantification of neural activities induced by environmental stimulation. CUBIC enables time-course expression profiling of whole adult brains with single-cell resolution.

Whole-Body Imaging with Single-Cell Resolution by Tissue Decolorization

The development of whole-body imaging at single-cell resolution enables system-level approaches to studying cellular circuits in organisms. Previous clearing methods focused on homogenizing mismatched refractive indices of individual tissues, enabling reductions in opacity but falling short of achieving transparency. Here, we show that an aminoalcohol decolorizes blood by efficiently eluting the heme chromophore from hemoglobin. Direct transcardial perfusion of an aminoalcohol-containing cocktail that we previously termed CUBIC coupled with a 10 day to 2 week clearing protocol decolorized and rendered nearly transparent almost all organs of adult mice as well as the entire body of infant and adult mice. This CUBIC-perfusion protocol enables rapid whole-body and whole-organ imaging at single-cell resolution by using light-sheet fluorescent microscopy. The CUBIC protocol is also applicable to 3D pathology, anatomy, and immunohistochemistry of various organs. These results suggest that whole-body imaging of colorless tissues at high resolution will contribute to organism-level systems biology.

Drug accumulation into single drug-sensitive and drug-resistant prostate cancer cells conducted on the single cell bioanalyzer

Multidrug resistance (MDR) occurs in prostate cancer, and this happens when the cancer cells resist chemotherapeutic drugs by pumping them out of the cells. MDR inhibitors such as cyclosporin A (CsA) can stop the pumping and enhance the drugs accumulated in the cells. The cellular drug accumulation is monitored using a microfluidic chip mounted on a single cell bioanalyzer. This equipment has been developed to measure accumulation of drugs such as doxorubicin (DOX) and fluorescently labeled paclitaxel (PTX) in single prostate cancer cells. The inhibition of drug efflux on the same prostate cell was examined in drug-sensitive and drug-resistant cells. Accumulation of these drug molecules was not found in the MDR cells, PC-3 RX-DT2R cells. Enhanced drug accumulation was observed only after treating the MDR cell in the presence of 5 μM of CsA as the MDR inhibitor. We envision this monitoring of the accumulation of fluorescent molecules (drug or fluorescent molecules), if conducted on single patient cancer cells, can provide information for clinical monitoring of patients undergoing chemotherapy in the future.

Single-cell-precision microplasma-induced cancer cell apoptosis

The issue of single-cell control has recently attracted enormous interest. However, in spite of the presently achievable intracellular-level physiological probing through bio-photonics, nano-probe-based, and some other techniques, the issue of inducing selective, single-cell-precision apoptosis, without affecting neighbouring cells remains essentially open. Here we resolve this issue and report on the effective single-cell-precision cancer cell treatment using the reactive chemistry of the localized corona-type plasma discharge around a needle-like electrode with the spot size ∼1 µm. When the electrode is positioned with the micrometer precision against a selected cell, a focused and highly-localized micro-plasma discharge induces apoptosis in the selected individual HepG2 and HeLa cancer cells only, without affecting any surrounding cells, even in small cell clusters. This is confirmed by the real-time monitoring of the morphological and structural changes at the cellular and cell nucleus levels after the plasma exposure.

Protein complementation assay as a display system for screening protein libraries in the intracellular environment

A wide range of screening strategies have been employed to isolate antibodies and other proteins with specific attributes, including binding affinity, specificity, stability and improved expression. However, there remains no high-throughput system to screen for target-binding proteins in a mammalian, intracellular environment. Such a system would allow binding reagents to be isolated against intracellular clinical targets such as cell signalling proteins associated with tumour formation (p53, ras, cyclin E), proteins associated with neurodegenerative disorders (huntingtin, betaamyloid precursor protein), and various proteins crucial to viral replication (e.g. HIV-1 proteins such as Tat, Rev and Vif-1), which are difficult to screen by phage, ribosome or cell-surface display. This study used the β-lactamase protein complementation assay (PCA) as the display and selection component of a system for screening a protein library in the cytoplasm of HEK 293T cells. The colicin E7 (ColE7) and Immunity protein 7 (Imm7) *Escherichia coli* proteins were used as model interaction partners for developing the system. These proteins drove effective β-lactamase complementation, resulting in a signal-to-noise ratio (9:1 – 13:1) comparable to that of other β-lactamase PCAs described in the literature. The model Imm7-ColE7 interaction was then used to validate protocols for library screening. Single positive cells that harboured the Imm7 and ColE7 binding partners were identified and isolated using flow cytometric cell sorting in combination with the fluorescent β-lactamase substrate, CCF2/AM. A single-cell PCR was then used to amplify the Imm7 coding sequence directly from each sorted cell. With the screening system validated, it was then used to screen a protein library based the Imm7 scaffold against a proof-of-principle target. The wild-type Imm7 sequence, as well as mutants with wild-type residues in the ColE7- binding loop were enriched from the library after a single round of selection, which is consistent with other eukaryotic screening systems such as yeast and mammalian cell-surface display. In summary, this thesis describes a new technology for screening protein libraries in a mammalian, intracellular environment. This system has the potential to complement existing screening technologies by allowing access to intracellular proteins and expanding the range of targets available to the pharmaceutical industry.

Choosing an appropriate modelling framework for analysing multispecies co-culture cell biology experiments

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insuffcient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

Developing a three-dimensional in-vitro cell culture model for studying breast and prostate cancer using starPEG-heparin hydrogels

Introduction Hydrogels prepared from poly(ethylene glycol) (PEG) and maleimide-functionalized heparin provide a potential matrix for use in developing three dimensional (3D) models. We have previously demonstrated that these hydrogels support the cultivation of human umbilical vein endothelial cells (HUVECs) (1). We extend this body of work to study the ability to create an extracellular matrix (ECM)-like model to study breast and prostate cancer cell growth in 3D. Also, we investigate the ability to produce a tri-culture mimicking tumour angiogenesis with cancer spheroids, HUVECs and mesenchymal stem cells (MSC). Materials and Methods The breast cancer cell lines, MCF-7 and MDA-MB-231, and prostate cancer cell lines, LNCaP and PC3, were seeded into starPEG-heparin hydrogels and grown for 14 Days to analyse the effects of varying hydrogel stiffness on spheroid development. Resulting hydrogel constructs were analyzed via Alamar Blue assays, light microscopy, and immunofluorescence staining for cytokeratin 8/18, Ki67 and E-Cadherin. Cancer cell lines were then pre-grown in hydrogels for 5-7 days and then re-seeded into starPEG-heparin hydrogels functionalised with RGD, SDF-1, bFGF and VEGF as spheroids with HUVECs and MSC and grown for 14 days as a tri-culture in Endothelial Cell Growth Medium (ECGM; Promocell). Cell lines were also seeded as a single cell suspension into the functionalised tri-culture system. Cultures were fixed in 4% paraformaldehyde and analysed via immunostaining for Von Willebrand Factor and CD31, as well as the above mentioned markers, and observed using confocal microscopy. Results Cultures prepared in MMP-cleavable starPEG-heparin hydrogels display spheroid formation in contrast to adherent growth on tissue culture plastic. Small differences were visualised in cancer spheroid growth between different gel stiffness across the range of cell lines. Cancer cell lines were able to be co-cultivated with HUVECs and MSC. HUVEC tube formation and cancer line spheroid formation occured after 3-4 days. Interaction was visualised between tumours and HUVECs via confocal microscopy. Slightly increased interaction was seen between cancer tumours and micro-vascular tubes when seeded as single cells compared with the pre-formed spheroid approach. Further studies intend to utilise cytokine gradients to further optimise the ECM environment of in situ tumour angiogenesis. Discussion and Conclusions Our results confirm the suitability of hydrogels constructed from starPEG-heparin for HUVECs and MSC co-cultivation with cancer cell lines to study cell-cell and cell-matrix interactions in a 3D environment. This represents a step forward in the development of 3D culture models to study the pathomechanisms of breast and prostate cancer. References 1. Tsurkan MV, Chwalek K, Prokoph S, Zieris A, Levental KR, Freudenberg U, Werner C. Advanced Materials. 25, 2606-10, 2013. Disclosures The authors declare no conflicts of interest

Estimating cell diffusivity and cell proliferation rate by interpreting IncuCyte ZOOM™ assay data using the Fisher-Kolmogorov model

Background: Standard methods for quantifying IncuCyte ZOOM™ assays involve measurements that quantify how rapidly the initially-vacant area becomes re-colonised with cells as a function of time. Unfortunately, these measurements give no insight into the details of the cellular-level mechanisms acting to close the initially-vacant area. We provide an alternative method enabling us to quantify the role of cell motility and cell proliferation separately. To achieve this we calibrate standard data available from IncuCyte ZOOM™ images to the solution of the Fisher-Kolmogorov model. Results: The Fisher-Kolmogorov model is a reaction-diffusion equation that has been used to describe collective cell spreading driven by cell migration, characterised by a cell diffusivity, D, and carrying capacity limited proliferation with proliferation rate, λ, and carrying capacity density, K. By analysing temporal changes in cell density in several subregions located well-behind the initial position of the leading edge we estimate λ and K. Given these estimates, we then apply automatic leading edge detection algorithms to the images produced by the IncuCyte ZOOM™ assay and match this data with a numerical solution of the Fisher-Kolmogorov equation to provide an estimate of D. We demonstrate this method by applying it to interpret a suite of IncuCyte ZOOM™ assays using PC-3 prostate cancer cells and obtain estimates of D, λ and K. Comparing estimates of D, λ and K for a control assay with estimates of D, λ and K for assays where epidermal growth factor (EGF) is applied in varying concentrations confirms that EGF enhances the rate of scratch closure and that this stimulation is driven by an increase in D and λ, whereas K is relatively unaffected by EGF. Conclusions: Our approach for estimating D, λ and K from an IncuCyte ZOOM™ assay provides more detail about cellular-level behaviour than standard methods for analysing these assays. In particular, our approach can be used to quantify the balance of cell migration and cell proliferation and, as we demonstrate, allow us to quantify how the addition of growth factors affects these processes individually.

Modelling cell separation during plant organ abscission

A simple mathematical model is presented to describe the cell separation process that plants undertake in order to deliberately shed organs. The focus here is on modelling the production of the enzyme polygalacturonase, which breaks down pectin that provides natural cell-to-cell adhesion in the localised abscission zone. A coupled system of three ordinary differential equations is given for a single cell, and then extended to hold for a layer of cells in the abscission zone. Simple observations are made based on the results of this preliminary model and, furthermore, a number of opportunities for applied mathematicians to make contributions in this subject area are discussed.

Improved image quality for x-ray CT imaging of gel dosimeters

Purpose: This study provides a simple method for improving precision of x-ray computed tomography (CT) scans of irradiated polymer gel dosimetry. The noise affecting CT scans of irradiated gels has been an impediment to the use of clinical CT scanners for gel dosimetry studies. Method: In this study, it is shown that multiple scans of a single PAGAT gel dosimeter can be used to extrapolate a ‘zero-scan’ image which displays a similar level of precision to an image obtained by averaging multiple CT images, without the compromised dose measurement resulting from the exposure of the gel to radiation from the CT scanner. Results: When extrapolating the zero-scan image, it is shown that exponential and simple linear fits to the relationship between Hounsfield unit and scan number, for each pixel in the image, provides an accurate indication of gel density. Conclusions: It is expected that this work will be utilised in the analysis of three-dimensional gel volumes irradiated using complex radiotherapy treatments.

Inferring diffusion in single live cells at the single-molecule level

The movement of molecules inside living cells is a fundamental feature of biological processes. The ability to both observe and analyse the details of molecular diffusion in vivo at the single-molecule and single-cell level can add significant insight into understanding molecular architectures of diffus- ing molecules and the nanoscale environment in which the molecules diffuse. The tool of choice for monitoring dynamic molecular localization in live cells is fluorescence microscopy, especially so combining total internal reflection fluorescence with the use of fluorescent protein (FP) reporters in offering exceptional imaging contrast for dynamic processes in the cell mem- brane under relatively physiological conditions compared with competing single-molecule techniques. There exist several different complex modes of diffusion, and discriminating these from each other is challenging at the mol- ecular level owing to underlying stochastic behaviour. Analysis is traditionally performed using mean square displacements of tracked particles; however, this generally requires more data points than is typical for single FP tracks owing to photophysical instability. Presented here is a novel approach allowing robust Bayesian ranking of diffusion processes to dis-criminate multiple complex modes probabilistically. It is a computational approach that biologists can use to understand single-molecule features in live cells.