The importance of connexin hemichannels during chondroprogenitor cell differentiation in hydrogel versus microtissue culture models

Appropriate selection of scaffold architecture is a key challenge in cartilage tissue engineering. Gap junction-mediated intercellular contacts play important roles in precartilage condensation of mesenchymal cells. However, scaffold architecture could potentially restrict cell-cell communication and differentiation. This is particularly important when choosing the appropriate culture platform as well as scaffold-based strategy for clinical translation, that is, hydrogel or microtissues, for investigating differentiation of chondroprogenitor cells in cartilage tissue engineering. We, therefore, studied the influence of gap junction-mediated cell-cell communication on chondrogenesis of bone marrow-derived mesenchymal stromal cells (BM-MSCs) and articular chondrocytes. Expanded human chondrocytes and BM-MSCs were either (re-) differentiated in micromass cell pellets or encapsulated as isolated cells in alginate hydrogels. Samples were treated with and without the gap junction inhibitor 18-α glycyrrhetinic acid (18αGCA). DNA and glycosaminoglycan (GAG) content and gene expression levels (collagen I/II/X, aggrecan, and connexin 43) were quantified at various time points. Protein localization was determined using immunofluorescence, and adenosine-5'-triphosphate (ATP) was measured in conditioned media. While GAG/DNA was higher in alginate compared with pellets for chondrocytes, there were no differences in chondrogenic gene expression between culture models. Gap junction blocking reduced collagen II and extracellular ATP in all chondrocyte cultures and in BM-MSC hydrogels. However, differentiation capacity was not abolished completely by 18αGCA. Connexin 43 levels were high throughout chondrocyte cultures and peaked only later during BM-MSC differentiation, consistent with the delayed response of BM-MSCs to 18αGCA. Alginate hydrogels and microtissues are equally suited culture platforms for the chondrogenic (re-)differentiation of expanded human articular chondrocytes and BM-MSCs. Therefore, reducing direct cell-cell contacts does not affect in vitro chondrogenesis. However, blocking gap junctions compromises cell differentiation, pointing to a prominent role for hemichannel function in this process. Therefore, scaffold design strategies that promote an increasing distance between single chondroprogenitor cells do not restrict their differentiation potential in tissue-engineered constructs.

Intellectual property and emerging technologies: The new biology

This unique and comprehensive collection investigates the challenges posed to intellectual property by recent paradigm shifts in biology. It explores the legal ramifications of emerging technologies, such as genomics, synthetic biology, stem cell research, nanotechnology, and biodiscovery. Extensive contributions examine recent controversial court decisions in patent law – such as Bilski v. Kappos, and the litigation over Myriad’s patents in respect of BRCA1 and BRCA2 – while other papers explore sui generis fields, such as access to genetic resources, plant breeders' rights, and traditional knowledge. The collection considers the potential and the risks of the new biology for global challenges – such as access to health-care, the protection of the environment and biodiversity, climate change, and food security. It also considers Big Science projects – such as biobanks, the 1000 Genomes Project, and the Doomsday Vault. The inter-disciplinary research brings together the work of scholars from Australia, Canada, Europe, the UK and the US and involves not only legal analysis of case law and policy developments, but also historical, comparative, sociological, and ethical methodologies. Intellectual Property and Emerging Technologies will appeal to policy-makers, legal practitioners, business managers, inventors, scientists and researchers.

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.

Single molecule microscopy in 3D cell cultures and tissues

From the onset of the first microscopic visualization of single fluorescent molecules in living cells at the beginning of this century, to the present, almost routine application of single molecule microscopy, the method has well-proven its ability to contribute unmatched detailed insight into the heterogeneous and dynamic molecular world life is composed of. Except for investigations on bacteria and yeast, almost the entire story of success is based on studies on adherent mammalian 2D cell cultures. However, despite this continuous progress, the technique was not able to keep pace with the move of the cell biology community to adapt 3D cell culture models for basic research, regenerative medicine, or drug development and screening. In this review, we will summarize the progress, which only recently allowed for the application of single molecule microscopy to 3D cell systems and give an overview of the technical advances that led to it. While initially posing a challenge, we finally conclude that relevant 3D cell models will become an integral part of the on-going success of single molecule microscopy.

Stochastic dynamics of interacting haematopoietic stem cell niche lineages

Since we still know very little about stem cells in their natural environment, it is useful to explore their dynamics through modelling and simulation, as well as experimentally. Most models of stem cell systems are based on deterministic differential equations that ignore the natural heterogeneity of stem cell populations. This is not appropriate at the level of individual cells and niches, when randomness is more likely to affect dynamics. In this paper, we introduce a fast stochastic method for simulating a metapopulation of stem cell niche lineages, that is, many sub-populations that together form a heterogeneous metapopulation, over time. By selecting the common limiting timestep, our method ensures that the entire metapopulation is simulated synchronously. This is important, as it allows us to introduce interactions between separate niche lineages, which would otherwise be impossible. We expand our method to enable the coupling of many lineages into niche groups, where differentiated cells are pooled within each niche group. Using this method, we explore the dynamics of the haematopoietic system from a demand control system perspective. We find that coupling together niche lineages allows the organism to regulate blood cell numbers as closely as possible to the homeostatic optimum. Furthermore, coupled lineages respond better than uncoupled ones to random perturbations, here the loss of some myeloid cells. This could imply that it is advantageous for an organism to connect together its niche lineages into groups. Our results suggest that a potential fruitful empirical direction will be to understand how stem cell descendants communicate with the niche and how cancer may arise as a result of a failure of such communication.

Analysis of focal adhesion turnover: A quantitative live-cell imaging example

Recent advances in optical and fluorescent protein technology have rapidly raised expectations in cell biology, allowing quantitative insights into dynamic intracellular processes like never before. However, quantitative live-cell imaging comes with many challenges including how best to translate dynamic microscopy data into numerical outputs that can be used to make meaningful comparisons rather than relying on representative data sets. Here, we use analysis of focal adhesion turnover dynamics as a straightforward specific example on how to image, measure, and analyze intracellular protein dynamics, but we believe this outlines a thought process and can provide guidance on how to understand dynamic microcopy data of other intracellular structures.

Genetics of rheumatoid arthritis contributes to biology and drug discovery

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

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.

Circulating tumor cell detection in high-risk non-metastatic prostate cancer

Purpose The detection of circulating tumor cells (CTCs) provides important prognostic information in men with metastatic prostate cancer. We aim to determine the rate of detection of CTCs in patients with high-risk non-metastatic prostate cancer using the CellSearch® method. Method Samples of peripheral blood (7.5 mL) were drawn from 36 men with newly diagnosed high-risk non-metastatic prostate cancer, prior to any initiation of therapy and analyzed for CTCs using the CellSearch® method. Results The median age was 70 years, median PSA was 14.1, and the median Gleason score was 9. The median 5-year risk of progression of disease using a validated nomogram was 39 %. Five out of 36 patients (14 %, 95 % CI 5–30 %) had CTCs detected in their circulation. Four patients had only 1 CTC per 7.5 mL of blood detected. One patient had 3 CTCs per 7.5 mL of blood detected, which included a circulating tumor microemboli. Both on univariate analysis and multivariate analysis, there were no correlations found between CTC positivity and the classic prognostic factors including PSA, Gleason score, T-stage and age. Conclusion This study demonstrates that patients with high-risk, non-metastatic prostate cancer present infrequently with small number of CTCs in peripheral blood. This finding is consistent with the limited literature available in this setting. Other CTC isolation and detection technologies with improved sensitivity and specificity may enable detection of CTCs with mesenchymal phenotypes, although none as yet have been validated for clinical use. Newer assays are emerging for detection of new putative biomarkers for prostate cancer. Correlation of disease control outcomes with CTC detection will be important.

The cross-talk of LDL-cholesterol with cell migration: Insights from the Niemann Pick Type C1 mutation

Cholesterol is considered indispensible for the recruitment and functioning of integrins in focal adhesions for cell migration. However, the physiological cholesterol pools that control integrin trafficking and focal adhesion assembly remain unclear. Using Niemann Pick Type C1 (NPC) mutant cells, which accumulate Low Density lipoprotein (LDL)-derived cholesterol in late endosomes (LE), several recent studies indicate that LDL-cholesterol has multiple roles in regulating focal adhesion dynamics. Firstly, targeting of endocytosed LDL-cholesterol from LE to focal adhesions controls their formation at the leading edge of migrating cells. Other newly emerging literature suggests that this may be coupled to vesicular transport of integrins, Src kinase and metalloproteases from the LE compartment to focal adhesions. Secondly, our recent work identified LDL-cholesterol as a key factor that determines the distribution and ability of several Soluble NSF Attachment Protein (SNAP) Receptor (SNARE) proteins, key players in vesicle transport, to control integrin trafficking to the cell surface and extracellular matrix (ECM) secretion. Collectively, dietary, genetic and pathological changes in cholesterol metabolism may link with efficiency and speed of integrin and ECM cell surface delivery in metastatic cancer cells. This commentary will summarize how direct and indirect pathways enable LDL-cholesterol to modulate cell motility.

Epithelial-mesenchymal axis in head and neck cancer cell lines

Objectives: Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous tumour type which necessitates multiple invitro models to attain an appreciation of its multiple subtypes. The phenomenon of epithelial-mesenchymal transition (EMT) isimportant to the development of a metastatic cancer cell phenotype being relevant to the ability of cancer cells to intravasate intovasculature and to invade tissues. The role of EMT in human papilloma virus (HPV) positive HNSCC is not well understood. Thispaper aims to characterize seven HNSCC cell lines (FaDu, SCC-25, SCC-15, CAL27, RPMI2650) including two new HPV-16positive HNSCC cell lines (UD-SCC2, 93-VU-147T) for their epithelial and mesenchymal properties. Materials and methods: A panel of HNSCC cell lines from multiple head and neck anatomical sites were profiled for basalexpression of epithelial and mesenchymal characteristics at mRNA, protein and functional levels (proliferative, migratory andinvasive properties). Furthermore, 3D spheroid forming capabilities were investigated. Results: We found that the HPV-16 positive cell line, in particular UD-SCC2 demonstrated a more invasive and mesenchymalphenotype at the molecular and functional levels suggesting HPV infection may mediate some of these cellular properties.Moreover, HPV-negative cell lines were not strictly epithelial presenting with a dynamic range of expression. Conclusions: This study presents the molecular and phenotypic diversity of HNSCC cell lines. It highlights the need formore studies in this field and a scoring system where HNSCC cell lines are ranked according to their respective epithelial andmesenchymal nature. This data will be useful to anyone modelling HNSCC behaviour, providing a molecular context which willenable them to decipher cell phenotypes and to develop therapies which block EMT progression.

Adipocytes promote prostate cancer stem cell self-renewal through amplification of the cholecystokinin autocrine loop

Obesity has long been linked with prostate cancer progression, although the underlying mechanism is still largely unknown. Here, we report that adipocytes promote the enrichment of prostate cancer stem cells (CSCs) through a vicious cycle of autocrine amplification. In the presence of adipocytes, prostate cancer cells actively secrete the peptide hormone cholecystokinin (CCK), which not only stimulates prostate CSC self-renewal, but also induces cathepsin B (CTSB) production of the adipocytes. In return, CTSB facilitates further CCK secretion by the cancer cells. More importantly, inactivation of CCK receptor not only suppresses CTSB secretion by the adipocytes, but also synergizes the inhibitory effect of CTSB inhibitor on adipocyte-promoted prostate CSC self-renewal. In summary, we have uncovered a novel mechanism underlying the mutual interplay between adipocytes and prostate CSCs, which may help explaining the role of adipocytes in prostate cancer progression and provide opportunities for effective intervention.

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 the movement of interacting cell populations: A moment dynamics approach

Mathematical models describing the movement of multiple interacting subpopulations are relevant to many biological and ecological processes. Standard mean-field partial differential equation descriptions of these processes suffer from the limitation that they implicitly neglect to incorporate the impact of spatial correlations and clustering. To overcome this, we derive a moment dynamics description of a discrete stochastic process which describes the spreading of distinct interacting subpopulations. In particular, we motivate our model by mimicking the geometry of two typical cell biology experiments. Comparing the performance of the moment dynamics model with a traditional mean-field model confirms that the moment dynamics approach always outperforms the traditional mean-field approach. To provide more general insight we summarise the performance of the moment dynamics model and the traditional mean-field model over a wide range of parameter regimes. These results help distinguish between those situations where spatial correlation effects are sufficiently strong, such that a moment dynamics model is required, from other situations where spatial correlation effects are sufficiently weak, such that a traditional mean-field model is adequate.