A transcriptomic analysis of the stress induced by capture–release health assessment studies in wild dolphins (Tursiops truncatus)

The health of wild bottlenose dolphins (Tursiops truncatus) is typically evaluated by the study of animals that are captured and released back into the wild after examination. The impact of such studies on gene expression in peripheral blood cells was investigated using microarray and quantitative polymerase chain reaction methods. Significantly increased expression was observed in two major classes of genes: (i) energy metabolism, and (ii) responsiveness to stress and trauma, the latter effect suggesting the initiation of an acute-phase response. The value of data obtained in capture/release studies may need to be weighed against the potential physiological impacts of such studies

Health status, infection and disease in California sea lions (Zalophus californianus) studied using a canine microarray platform and machine-learning approaches

Conservation biologists face many challenges in assessing health, immune status and infectious diseases in protected species. These challenges include unpredictable sample populations, diverse genetic and environmental backgrounds of the animals, as well as the practical, legal and ethical issues involved in experimentation. The use of whole genome scale transcriptomics with animal samples obtained in a minimally invasive manner is an approach that shows promise for health assessment. In this study we assessed the utility of a microarray to identify changes in gene expression predictive of health status by interrogating blood samples from California sea lions (Zalophus californianus) in rehabilitation. A custom microarray was developed from the commercially available dog microarray (Canis familiaris) by selecting probes that demonstrated reliable cross-hybridization with RNA in sea lion blood. This custom microarray was used for the analysis of RNA from 73 sea lion blood samples, from animals with a broad spectrum of health changes. Both traditional classifying techniques and newer artificial neural network approaches correctly classified sea lions with respect to health status, primarily distinguishing between leptospirosis infection and domoic acid exposure. Real time PCR validation for a small set of genes, followed by sequencing, showed good correlation with array results and high identity (96-98%) between the dog and sea lion sequences. This approach to health status classification shows promise for disease identification in a clinical setting, and assessment of health status of wildlife

Quantitative methods to characterize morphological properties of cell lines

Descriptive terms are often used to characterize cells in culture, but the use of nonquantitative and poorly defined terms can lead to ambiguities when comparing data from different laboratories. Although recently there has been a good deal of interest in unambiguous identification of cell lines via their genetic markers, it is also critical to have definitive, quantitative metrics to describe cell phenotypic characteristics. Quantitative metrics of cell phenotype will aid the comparison of data from experiments performed at different times and in different laboratories where influences such as the age of the population and differences in culture conditions or protocols can potentially affect cellular metabolic state and gene expression in the absence of changes in the genetic profile. Here, we present examples of robust methodologies for quantitatively assessing characteristics of cell morphology and cell-cell interactions, and of growth rates of cells within the population. We performed these analyses with endothelial cell lines derived from dolphin, bovine and human, and with a mouse fibroblast cell line. These metrics quantify some characteristics of these cells lines that clearly distinguish them from one another, and provide quantitative information on phenotypic changes in one of the cell lines over large number of passages

From chemical documentation to chemoinformatics: fifty years of chemical information science

This paper summarises the historical development of the discipline that is now called ‘chemoinformatics’. It shows how this has evolved, principally as a result of technological developments in chemistry and biology during the past decade, from long-established techniques for the modelling and searching of chemical molecules. A total of 30 papers, the earliest dating back to 1957, are briefly summarised to highlight some of the key publications and to show the development of the discipline