July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
Using statistical models to identify key variables critical for generation of retinal organoids from iPSC
Author Affiliations & Notes
  • Valeria Chichagova
    Newcells Biotech, Newcastle upon Tyne, United Kingdom
    Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
  • Dean Hallam
    Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
  • Mike Nicholds
    Newcells Biotech, Newcastle upon Tyne, United Kingdom
  • Robert Thomas
    Centre for Biological Engineering, Loughborough University, Loughborough, United Kingdom
  • Majlinda Lako
    Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
  • Lyle Armstrong
    Newcells Biotech, Newcastle upon Tyne, United Kingdom
    Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
  • Footnotes
    Commercial Relationships   Valeria Chichagova, None; Dean Hallam, None; Mike Nicholds, None; Robert Thomas, None; Majlinda Lako, None; Lyle Armstrong, None
  • Footnotes
    Support  CRACKIT23 challenge phase 1 (NC/CO16206/1), European Research Council (#614620), RP Fighting Blindness Innovation grant (GR584).
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 565. doi:
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      Valeria Chichagova, Dean Hallam, Mike Nicholds, Robert Thomas, Majlinda Lako, Lyle Armstrong; Using statistical models to identify key variables critical for generation of retinal organoids from iPSC. Invest. Ophthalmol. Vis. Sci. 2018;59(9):565.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : To evaluate the effects of key culture medium components on efficiency of generation of retinal organoids from induced pluripotent stem cells (iPSC) using statistical models.

Methods : iPSC from an unaffected subject were differentiated using a 96 well format. Design of Experiment (DoE) methodology was applied to evaluate the effects of key variables on the expression of genes marking various retinal cell phenotypes (RECOVERIN, CRX, RPE65, MITF, MATH5, PROX1, VSX2, AP2-α) emerging during differentiation. An initial full factorial design was applied to screen the effects of initial cell seeding density, 1-Thioglycerol, BMP4, Knock-out serum (KSR) and Lipids. A subsequent duplicated ½ fraction factorial design with centre points was applied to evaluate influential factors BMP4 and cell density at improved ranges identified from the initial design and in conjunction with CHIR99021 and SU5402. DoE responses were CT for the target gene normalised to GAPDH.

Results : A 2-level factorial experimental design was conducted at day 35 of differentiation to determine the key variables in early stage commitment. In our system cell number played the biggest single effect on the measured outcomes with a predicted optimal range between 6,000-8,000 cells per well. BMP4 supplementation also had a significant effect, initially higher concentration was better for retinal pigment epithelium (RPE) and retinal ganglion cells (RGC), however increasing the concentration further appeared detrimental, thus indicating 2-2.25 nM range to be the most optimal. 15% KSR proved to be most beneficial concentration, promoting CRX and RECOVERIN expression. The process control highlighted that only AP2-α was elevated at higher seeding density, while MATH5 increased at lower densities. A major advantage of this system was the ability to assess compounding effects, with lower cell numbers and higher concentrations of BMP4 increasing the gene expression of photoreceptors, RGC and RPE but had the converse effect on horizontal cells. These insights highlight the optimal growth conditions will be a compromise between the requirements of the many cell types present in the retinal organoids.

Conclusions : Our data show that starting cell number, BMP4, KSR and lipids are the main players in formation of neural retina; and CHIR99021, SU5402 and cell number in RPE generation.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

 

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