IS-RT-PCR assay detection of MT-MMP in a human breast cancer cell line

The in situ-reverse transcription-polymerase chain reaction (IS-RT-PCR) is a method that allows the direct localisation of gene expression. The method utilises the dual buffer mediated activity of the enzyme rTth DNA polymerase enabling both reverse transcription and DNA amplification. Labelled nucleoside triphosphates allow the site of expression to be labelled, rather than the PCR primers themselves, giving a more accurate localisation of transcript expression and decreased background than standard in situ hybridisation (ISH) assays. The MDA-MB-231 human breast carcinoma (HBC) cell line was assayed via the IS-RT-PCR technique, using primers encoding MT-MMP (membrane-type matrix metalloproteinase) and human β-actin. Our results clearly indicate baseline expression of MT-MMP in the relatively invasive MDA-MB-231 cell line at a signal intensity similar to the housekeeping gene β-actin, and results following induction with Concanavalin A (Con A) are consistent with our previous results obtained via Northern blotting.

Ghrelin O-acyltransferase (GOAT) is expressed in prostate cancer tissues and cell lines and expression is differentially regulated in vitro by ghrelin

Background Ghrelin is a 28 amino acid peptide hormone that is expressed in the stomach and a range of peripheral tissues, where it frequently acts as an autocrine/paracrine growth factor. Ghrelin is modified by a unique acylation required for it to activate its cognate receptor, the growth hormone secretagogue receptor (GHSR), which mediates many of the actions of ghrelin. Recently, the enzyme responsible for adding the fatty acid residue (octanoyl/acyl group) to the third amino acid of ghrelin, GOAT (ghrelin O-acyltransferase), was identified. Methods We used cell culture, quantitative real-time reverse transcription (RT)-PCR and immunohistochemistry to demonstrate the expression of GOAT in prostate cancer cell lines and tissues from patients. Real-time RT-PCR was used to demonstrate the expression of prohormone convertase (PC)1/3, PC2 and furin in prostate cancer cell lines. Prostate-derived cell lines were treated with ghrelin and desacyl ghrelin and the effect on GOAT expression was measured using quantitative RT-PCR. Results We have demonstrated that GOAT mRNA and protein are expressed in the normal prostate and human prostate cancer tissue samples. The RWPE-1 and RWPE-2 normal prostate-derived cell lines and the LNCaP, DU145, and PC3 prostate cancer cell lines express GOAT and at least one other enzyme that is necessary to produce mature, acylated ghrelin from proghrelin (PC1/3, PC2 or furin). Finally, ghrelin, but not desacyl ghrelin (unacylated ghrelin), can directly regulate the expression of GOAT in the RWPE-1 normal prostate derived cell line and the PC3 prostate cancer cell line. Ghrelin treatment (100nM) for 6 hours significantly decreased GOAT mRNA expression two-fold (P < 0.05) in the PC3 prostate cancer cell line, however, ghrelin did not regulate GOAT expression in the DU145 and LNCaP prostate cancer cell lines. Conclusions This study demonstrates that GOAT is expressed in prostate cancer specimens and cell lines. Ghrelin regulates GOAT expression, however, this is likely to be cell-type specific. The expression of GOAT in prostate cancer supports the hypothesis that the ghrelin axis has autocrine/paracrine roles. We propose that the RWPE-1 prostate cell line and the PC3 prostate cancer cell line may be useful for investigating GOAT regulation and function.

Synergism between Wnt3a and heparin enhances osteogenesis via a phosphoinositide 3-kinase/Akt/RUNX2 pathway

A new strategy has emerged to improve healing of bone defects using exogenous glycosaminoglycans by increasing the effectiveness of bone-anabolic growth factors. Wnt ligands play an important role in bone formation. However, their functional interactions with heparan sulfate/heparin have only been investigated in non-osseous tissues. Our study now shows that the osteogenic activity of Wnt3a is cooperatively stimulated through physical interactions with exogenous heparin. N-Sulfation and to a lesser extent O-sulfation of heparin contribute to the physical binding and optimal co-stimulation of Wnt3a. Wnt3a-heparin signaling synergistically increases osteoblast differentiation with minimal effects on cell proliferation. Thus, heparin selectively reduces the effective dose of Wnt3a needed to elicit osteogenic, but not mitogenic responses. Mechanistically, Wnt3a-heparin signaling strongly activates the phosphoinositide 3-kinase/Akt pathway and requires the bone-related transcription factor RUNX2 to stimulate alkaline phosphatase activity, which parallels canonical beta-catenin signaling. Collectively, our findings establish the osteo-inductive potential of a heparin-mediated Wnt3a-phosphoinositide 3-kinase/Akt-RUNX2 signaling network and suggest that heparan sulfate supplementation may selectively reduce the therapeutic doses of peptide factors required to promote bone formation.

Are in vitro estimates of cell diffusivity and cell proliferation rate sensitive to assay geometry?

Cells respond to various biochemical and physical cues during wound–healing and tumour progression. In vitro assays used to study these processes are typically conducted in one particular geometry and it is unclear how the assay geometry affects the capacity of cell populations to spread, or whether the relevant mechanisms, such as cell motility and cell proliferation, are somehow sensitive to the geometry of the assay. In this work we use a circular barrier assay to characterise the spreading of cell populations in two different geometries. Assay 1 describes a tumour–like geometry where a cell population spreads outwards into an open space. Assay 2 describes a wound–like geometry where a cell population spreads inwards to close a void. We use a combination of discrete and continuum mathematical models and automated image processing methods to obtain independent estimates of the effective cell diffusivity, D, and the effective cell proliferation rate, λ. Using our parameterised mathematical model we confirm that our estimates of D and λ accurately predict the time–evolution of the location of the leading edge and the cell density profiles for both assay 1 and assay 2. Our work suggests that the effective cell diffusivity is up to 50% lower for assay 2 compared to assay 1, whereas the effective cell proliferation rate is up to 30% lower for assay 2 compared to assay 1.

Oestrogen and progestin responses in human endometrium

Our understanding of the mechanisms of the actions of oestrogens and progestins have evolved from the simple concept of nuclear receptor-mediated regulation of transcription to a highly sophisticated, finely tuned interplay between various coregulators, other signaling cascades and transcription factors. The net result of these complex regulatory mechanisms is a steroid-, cell-, or tissue-specific action of oestrogens and progestins. their antagonists or selective modulators of their receptors. In this review, we have attempted to shed some light on the regulation of the actions of oestrogens and progestins on the human endometrium. (C) 2003 Elsevier Science Ltd. All rights reserved.

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.

Inventing life: Patent law and synthetic biology

With promises of improved medical treatments, greener energy and even artificial life, the field of synthetic biology has captured the public imagination and attracted significant government and commercial investment. This excitement reached a crescendo on 21 May 2010, when scientists at the J Craig Venter Institute in the United States announced that they had made a “self-replicating synthetic bacterial cell”. This was the first living cell to have an entirely human-made genome, which means that all of the cell’s characteristics were controlled by a DNA sequence designed by scientists. This achievement in biological engineering was made possible by combining molecular biotechnology, gene synthesis technology and information technology.

Allergen capture by IgE and IgG enhanced cell-binding by allergen multimers: How complex is it?

Allergic diseases are the most common chronic disease of the western world, costing $7.8 billion per year in lost productivity and medical care in Australia alone.1 IgE is central to the immunopathogenesis of allergic diseases and important advances are now being made on multiple fronts of IgE research. In particular, two groups independently invested in the generation of IgE reporter mice to address the vexing question of the route of development of the elusive IgE+ B cell.2, 3 Two new anti-IgE mAb targeting membrane IgE and cell-bound IgE have the potential to deplete the cellular source of IgE.4, 5 These could be candidates for alternative anti-IgE treatment options with advantages over current anti-IgE therapy (OmalizumAb), which depletes free serum IgE. Researchers are still intrigued by the modes of interaction of IgE with allergen, and with both its receptors; the high affinity FcεR1 on mast cells and basophils, and the low affinity, C-type lectin, IgE receptor, CD23,6 on B cells and monocytes (Figure 1a and b). A new approach to the study of the complexity of these interactions was recently reported by Reginald et al.7 on page 167 of this issue.

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.

Spectral analysis of pair-correlation bandwidth: Application to cell biology images

Images from cell biology experiments often indicate the presence of cell clustering, which can provide insight into the mechanisms driving the collective cell behaviour. Pair-correlation functions provide quantitative information about the presence, or absence, of clustering in a spatial distribution of cells. This is because the pair-correlation function describes the ratio of the abundance of pairs of cells, separated by a particular distance, relative to a randomly distributed reference population. Pair-correlation functions are often presented as a kernel density estimate where the frequency of pairs of objects are grouped using a particular bandwidth (or bin width), Δ>0. The choice of bandwidth has a dramatic impact: choosing Δ too large produces a pair-correlation function that contains insufficient information, whereas choosing Δ too small produces a pair-correlation signal dominated by fluctuations. Presently, there is little guidance available regarding how to make an objective choice of Δ. We present a new technique to choose Δ by analysing the power spectrum of the discrete Fourier transform of the pair-correlation function. Using synthetic simulation data, we confirm that our approach allows us to objectively choose Δ such that the appropriately binned pair-correlation function captures known features in uniform and clustered synthetic images. We also apply our technique to images from two different cell biology assays. The first assay corresponds to an approximately uniform distribution of cells, while the second assay involves a time series of images of a cell population which forms aggregates over time. The appropriately binned pair-correlation function allows us to make quantitative inferences about the average aggregate size, as well as quantifying how the average aggregate size changes with time.

Migration of breast cancer cells : understanding the roles of volume exclusion and cell-to-cell adhesion

We study MCF-7 breast cancer cell movement in a transwell apparatus. Various experimental conditions lead to a variety of monotone and nonmonotone responses which are difficult to interpret. We anticipate that the experimental results could be caused by cell-to-cell adhesion or volume exclusion. Without any modeling, it is impossible to understand the relative roles played by these two mechanisms. A lattice-based exclusion process random-walk model incorporating agent-to-agent adhesion is applied to the experimental system. Our combined experimental and modeling approach shows that a low value of cell-to-cell adhesion strength provides the best explanation of the experimental data suggesting that volume exclusion plays a more important role than cell-to-cell adhesion. This combined experimental and modeling study gives insight into the cell-level details and design of transwell assays.

Solid freeform fabrication of hydrogel structures and cell encapsulation

We aim to fabricate computer-controlled hydrogel structures containing viable encapsulated cells to overcome the low seeding densities which are inherent to most pre-fabricated scaffold systems.