Abstract
The a priori identification of induced pluripotent stem cells remains a challenge. Being able to quickly identify the most embryonic stem cell-similar induced pluripotent stem cells when validating results could help to reduce costs and save time. In this context, tools based on non-classic logic can be useful in creating aid-systems based on visual criteria. True colonies when viewed at 100x magnification have been found to have the following 3 characteristics: a high degree of border delineation, a more uniform texture, and the absence of a cracked texture. These visual criteria were used for fuzzy logic modeling. We investigated the possibility of predicting the presence of alkaline phosphatase activity, typical of true induced pluripotent stem cell colonies, after 25 individuals, with varying degrees of experience in working with murine iPS cells, categorized the images of 136 colonies based on visual criteria. Intriguingly, the performance evaluation by area under the ROC curve (16 individuals with satisfactory performance), Spearman correlation (all statistically significant), and Cohen's Kappa agreement analysis (all statistically significant) demonstrates that the discriminatory capacity of different evaluators are similar, even those who have never cultivated cells. Thus, we report on a new system to facilitate visual identification of murine- induced pluripotent stem cell colonies that can be useful for staff training and opens the possibility of exploring visual characteristics of induced pluripotent stem cell colonies with their functional peculiarities. The fuzzy model has been integrated as a web-based tool named “2see-iPS” which is freely accessed at http://genetica.incor.usp.br/2seeips/.
Highlights
Identifying emerging induced pluripotent stem cell colonies based solely on morphological criteria is possible [1]; it is difficult to classify a priori which ones are true, that is, those that will have characteristics similar to the characteristics of embryonic stem (ES) cells after being collected and reprogrammed
Images were grouped according to alkaline phosphatase activity into 2 groups, positive (60.3%) and negative (39.7%) colonies, which hereafter will be called true and false induced pluripotent stem (iPS) colonies
We present the results of the generation of a system to aid the identification of true induced pluripotent cell colonies using fuzzy logic
Summary
Identifying emerging induced pluripotent stem (iPS) cell colonies based solely on morphological criteria is possible [1]; it is difficult to classify a priori which ones are true, that is, those that will have characteristics similar to the characteristics of embryonic stem (ES) cells after being collected and reprogrammed. The initial identification of potential colonies is performed using reporter gene systems with fluorescent probes or antibiotic resistance for ES pluripotency genes, such as Fbox15 [4], UTF1 [5,6], Nanog [7,8], and Oct3/4 [2] These systems facilitate the rapid identification of true colonies before collection without killing them, unlike assays necessary for verification of expression of alkaline phosphatase (based on regular substrates) or other intracellular molecular markers. To date there is only one method, recently described, capable of detecting alkaline phosphatase positive cells using a fluorogenic substrate without destroying cells [10] This is a promising approach, still involves increasing processing time and costs using reagents which possible negative effects are not fully studied. These still may pose a problem when it is necessary to collect several colonies and, subsequently, to validate them as pluripotent, especially when it is not suitable to introduce exogenous elements into genomes, such as human cells that will be used in the future in clinical practice
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