Automated quantification reveals hyperglycemia inhibits endothelial angiogenic function.
OBJECTIVE
Diabetes Mellitus (DM) has reached epidemic levels globally. A contributing factor to the development of DM is high blood glucose (hyperglycemia). One complication associated with DM is a decreased angiogenesis. The Matrigel tube formation assay (TFA) is the most widely utilized in vitro assay designed to assess angiogenic factors and conditions. In spite of the widespread use of Matrigel TFAs, quantification is labor-intensive and subjective, often limiting experiential design and interpretation of results. This study describes the development and validation of an open source software tool for high throughput, morphometric analysis of TFA images and the validation of an in vitro hyperglycemic model of DM.


RESULTS
Endothelial cells mimic angiogenesis when placed onto a Matrigel coated surface by forming tube-like structures. The goal of this study was to develop an open-source software algorithm requiring minimal user input (Pipeline v1.3) to automatically quantify tubular metrics from TFA images. Using Pipeline, the ability of endothelial cells to form tubes was assessed after culture in normal or high glucose for 1 or 2 weeks. A significant decrease in the total tube length and number of branch points was found when comparing groups treated with high glucose for 2 weeks versus normal glucose or 1 week of high glucose.


CONCLUSIONS
Using Pipeline, it was determined that hyperglycemia inhibits formation of endothelial tubes in vitro. Analysis using Pipeline was more accurate and significantly faster than manual analysis. The Pipeline algorithm was shown to have additional applications, such as detection of retinal vasculature.
Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America; Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America.
Anthony R
AR
Prisco
Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America; Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America.
John D
JD
Bukowy
Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America; Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America.
Brian R
BR
Hoffmann
Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America; Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America.
Jamie R
JR
Karcher
Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America; Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America.
Eric C
EC
Exner
Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America; Department of Physiology, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America.
Andrew S
AS
Greene
D000465:Algorithms; D000818:Animals; D001331:Automation; D003198:Computer Simulation; D042783:Endothelial Cells / Q000473:pathology*; D006943:Hyperglycemia / Q000473:pathology*; D055806:Microvessels / Q000473:pathology; D009206:Myocardium / Q000473:pathology; D018919:Neovascularization, Physiologic; D011642:Publications; D051381:Rats; D012171:Retinal Vessels / Q000473:pathology; D014584:User-Computer Interface