Abstract

Isolation of islets of Langerhans (islets) has been performed by means of collagenase digestion of the pancreatic tissue combined with density gradient separation of islets from unwanted exocrine tissues. An enormous number of islets are necessary for clinical islet transplantation. The density gradient used for isolation of a large number of islets should satisfy several requirements in addition to those for the conventional density gradients, such as high viscosity for creating fine interfaces with a large area, easy sterilization, and low cost. This study is concerned with the development of a new density gradient made of low-molecular-weight gelatin. We isolated islets from the hamster pancreatic tissue using the gelatin density gradients. The yield and purity of islet and its insulin release function were compared with those of islets isolated using Ficoll and Ficoll-Conray density gradients that have been conventionally used. The new gelatin density gradient can separate islets from the unwanted exocrine tissue as effectively as the Ficoll density gradient and more effectively than the Ficoll-Conray density gradients. The islets collected using the gelatin gradient retain ability of insulin release increase in response to glucose stimulation, similar to those isolated by the Ficoll-Conray gradient and more than those collected by the Ficoll gradient. In addition, the gelatin effectively inhibited enzyme activities, that is, collagenase and proteolytic enzymes released from the exocrine tissue, and thus it can inhibit overdigestion of islets during their density gradient isolation. The gelatin gradient satisfies most of the additional requirements for islet isolation from the pancreatic tissue of large animals mentioned above. Although several factors, such as molecular weight of gelatin, osmolality of the gradient, and centrifugal conditions, still remain to be optimized, our results suggest that the gelatin gradient has potentiality to isolate islets from the pancreatic tissue of a large animal.

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