Systematic random sampling of the comet assay

The comet assay is a technique used to quantify DNA damage and repair at a cellular level. In the assay, cells are embedded in agarose and the cellular content is stripped away leaving only the DNA trapped in an agarose cavity which can then be electrophoresed. The damaged DNA can enter the agarose and migrate while the undamaged DNA cannot and is retained. DNA damage is measured as the proportion of the migratory ‘tail’ DNA compared to the total DNA in the cell. The fundamental basis of these arbitrary values is obtained in the comet acquisition phase using fluorescence microscopy with a stoichiometric stain in tandem with image analysis software. Current methods deployed in such an acquisition are expected to be both objectively and randomly obtained. In this paper we examine the ‘randomness’ of the acquisition phase and suggest an alternative method that offers both objective and unbiased comet selection. In order to achieve this, we have adopted a survey sampling approach widely used in stereology, which offers a method of systematic random sampling (SRS). This is desirable as it offers an impartial and reproducible method of comet analysis that can be used both manually or automated. By making use of an unbiased sampling frame and using microscope verniers, we are able to increase the precision of estimates of DNA damage. Results obtained from a multiple-user pooled variation experiment showed that the SRS technique attained a lower variability than that of the traditional approach. The analysis of a single user with repetition experiment showed greater individual variances while not being detrimental to overall averages. This would suggest that the SRS method offers a better reflection of DNA damage for a given slide and also offers better user reproducibility.

Modelling the comet assay

The single-cell gel electrophoresis technique or comet assay is widely regarded as a quick and reliable method of analysing DNA damage in individual cells. It has a proven track record from the fields of biomonitoring to nutritional studies. The assay operates by subjecting cells that are fixed in agarose to high salt and detergent lysis, thus removing all the cellular content except the DNA. By relaxing the DNA in an alkaline buffer, strands containing breaks are released from supercoiling. Upon electrophoresis, these strands are pulled out into the agarose, forming a tail which, when stained with a fluorescent dye, can be analysed by fluorescence microscopy. The intensity of this tail reflects the amount of DNA damage sustained. Despite being such an established and widely used assay, there are still many aspects of the comet assay which are not fully understood. The present review looks at how the comet assay is being used, and highlights some of its limitations. The protocol itself varies among laboratories, so results from similar studies may vary. Given such discrepancies, it would be attractive to break the assay into components to generate a mathematical model to investigate specific parameters.

Comet sensitivity in assessing DNA damage and repair in different cell cycle stages

The comet assay is a sensitive tool for estimation of DNA damage and repair at the cellular level, requiring only a very small number of cells. In comparing the levels of damage or repair in different cell samples, it is possible that small experimental effects could be confounded by different cell cycle states in the samples examined, if sensitivity to DNA damage, and repair capacity, varies with the cell cycle. We assessed this by arresting HeLa cells in various cell cycle stages and then exposing them to ionizing radiation. Unirradiated cells demonstrated significant differences in strand break levels measured by the comet assay (predominantly single-strand breaks) at different cell cycle stages, increasing from G1 into S and falling again in G2. Over and above this variation in endogenous strand break levels, a significant difference in susceptibility to breaks induced by 3.5 Gy ionizing radiation was also evident in different cell cycle phases. Levels of induced DNA damage fluctuate throughout the cycle, with cells in G1 showing slightly lower levels of damage than an asynchronous population. Damage increases as cells progress through S phase before falling again towards the end of S phase and reaching lowest levels in M phase. The results from repair experiments (where cells were allowed to repair for 10 min after exposure to ionizing radiation) also showed differences throughout the cell cycle with G1-phase cells apparently being the most efficient at repair and M-phase cells the least efficient. We suggest, therefore, that in experiments where small differences in DNA damage and repair are to be investigated with the comet assay, it may be desirable to arrest cells in a specific stage of the cell cycle or to allow for differential cycle distribution.

Championing the interface between mental health and child protection: evaluation of a service initiative to improve joint working in Northern Ireland

The importance of establishing effective interagency working between adult mental health services and child care services in order to safeguard children has been repeatedly identified by research, policy, inquiries and inspection reports. This article reports on the evaluation of an initiative in one Health and Social Care Trust in Northern Ireland that aimed to facilitate joint working and so improve service provision and protection for children and families. The Champions Initiative involved identifying a champion in each multi-disciplinary community mental health team and in each family and child care team who would have responsibility for providing information, promoting joint working and identifying any obstacles to better co-operation. The evaluation of this initiative assessed levels of experience, training, confidence, understanding and awareness in the Champions and their team members at baseline. The Champions and their Team Leaders were then followed-up after six months to obtain their qualitative views of the impact of the initiative. The results include comparisons between mental health and child care staff, and crucially, views about whether the initiative has had any impact on working together. This study also generated recommendations for further service development in this complex and important area of practice.

Identification of candidate small-molecule therapeutics to cancer by gene-signature perturbation in connectivity mapping.

Connectivity mapping is a recently developed technique for discovering the underlying connections between different biological states based on gene-expression similarities. The sscMap method has been shown to provide enhanced sensitivity in mapping meaningful connections leading to testable biological hypotheses and in identifying drug candidates with particular pharmacological and/or toxicological properties. Challenges remain, however, as to how to prioritise the large number of discovered connections in an unbiased manner such that the success rate of any following-up investigation can be maximised. We introduce a new concept, gene-signature perturbation, which aims to test whether an identified connection is stable enough against systematic minor changes (perturbation) to the gene-signature. We applied the perturbation method to three independent datasets obtained from the GEO database: acute myeloid leukemia (AML), cervical cancer, and breast cancer treated with letrozole. We demonstrate that the perturbation approach helps to identify meaningful biological connections which suggest the most relevant candidate drugs. In the case of AML, we found that the prevalent compounds were retinoic acids and PPAR activators. For cervical cancer, our results suggested that potential drugs are likely to involve the EGFR pathway; and with the breast cancer dataset, we identified candidates that are involved in prostaglandin inhibition. Thus the gene-signature perturbation approach added real values to the whole connectivity mapping process, allowing for increased specificity in the identification of possible therapeutic candidates.

TMAX – a Database System Integrating Tissue Biomarker & Genomic Data

Background: Popular approaches in human tissue-based biomarker discovery include tissue microarrays (TMAs) and DNA Microarrays (DMAs) for protein and gene expression profiling respectively. The data generated by these analytic platforms, together with associated image, clinical and pathological data currently reside on widely different information platforms, making searching and cross-platform analysis difficult. Consequently, there is a strong need to develop a single coherent database capable of correlating all available data types.

Method: This study presents TMAX, a database system to facilitate biomarker discovery tasks. TMAX organises a variety of biomarker discovery-related data into the database. Both TMA and DMA experimental data are integrated in TMAX and connected through common DNA/protein biomarkers. Patient clinical data (including tissue pathological data), computer assisted tissue image and associated analytic data are also included in TMAX to enable the truly high throughput processing of ultra-large digital slides for both TMAs and whole slide tissue digital slides. A comprehensive web front-end was built with embedded XML parser software and predefined SQL queries to enable rapid data exchange in the form of standard XML files.

Results & Conclusion: TMAX represents one of the first attempts to integrate TMA data with public gene expression experiment data. Experiments suggest that TMAX is robust in managing large quantities of data from different sources (clinical, TMA, DMA and image analysis). Its web front-end is user friendly, easy to use, and most importantly allows the rapid and easy data exchange of biomarker discovery related data. In conclusion, TMAX is a robust biomarker discovery data repository and research tool, which opens up the opportunities for biomarker discovery and further integromics research.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. © 2013 McArt et al.