Quantificação de apoptose e necrose mediante corantes fluorescentes e análise de imagens, no cultivo de células de inseto: o caso da Drosophila melanogaster S2

• Autor(a) principal: Silva, Bruna Gabriela
• Data de Publicação: 2007
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFSCAR
• Texto Completo: https://repositorio.ufscar.br/handle/ufscar/3981
• topic: Engenharia química; Células - morte; Yo-Pro-1; Células de inseto; Processamento de imagens; Cell death; Image analysis; YO-PRO-1; Insect cell; S2; ENGENHARIAS::ENGENHARIA QUIMICA

In animal cell cultures there are two kinds of cell death: apoptosis (programmed cell death) and necrosis (cell death due to external sources). The inovative method of cell death identification that have attracted interest is the use of fluorescence microscopy and fluorescent dye (to bind DNA and RNA). Image analysis techniques has become a useful tool in cell death quantification, once they are non destructive for the culture and have easy application with using adjusted softwares. Based in these new technological trends, the present work considers the development of a methodology for quantification of apoptotic and necrotic cell death in cultures of insect cells Drosophila melanogaster (S2). This methodology involved the development of a experimental procedure using new dyes (YO-PRO-1 and Propidium Iodide), that have presented advantages over the others because they are non destructive to the culture an are able to clearly discriminate between apoptotic and necrotic cell death. The use of this dyes was compared with the method of exclusion of Trypan blue and fluorescent dyes Acridine Orange and Ethidium Bromide. Besides being less toxic to cells S2, YO-PRO-1 and Propidium Iodide showed more sensitivity in the identification of death and in the calculation of cell viability. It also envolved the development of an algorithm based on image analysis techniques for quantification of the two kinds of cell death, less subjective than the manual methods currently used. The algorithm showed to be efficient, fast an of easy application with a error around 2% when compared to manual methodology. The calculated cell concentration by the algorithm was very close to experimental.