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A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus
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posted on 2020-08-20, 17:37 authored by Ada AdminAda Admin, Robert N. Bone, Olufunmilola Oyebamiji, Sayali Talware, Sharmila Selvaraj, Preethi Krishnan, Farooq Syed, Huanmei Wu, Carmella Evans-MolinaThe Golgi apparatus (GA) is an important site of insulin processing and
granule maturation, but whether GA organelle dysfunction and GA stress are
present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to
develop a transcriptional signature of β-cell GA stress using existing RNA
sequencing and microarray datasets generated using human islets from donors
with diabetes and islets where
type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we
applied a filter set of 1,030 genes accepted as GA associated. In parallel, we generated an RNA-sequencing
dataset from human islets treated with brefeldin A (BFA), a known GA stress
inducer. Overlapping the T1D and T2D
groups with the BFA dataset, we identified 120 and 204 differentially expressed
genes, respectively. In both the T1D and
T2D models, pathway analyses revealed that the top pathways were associated
with GA integrity, organization, and trafficking. Quantitative RT-PCR was used to validate a
common signature of GA stress that included ATF3,
ARF4, CREB3, and COG6. Taken together, these data indicate that GA-associated
genes are dysregulated in diabetes and identify putative markers of β-cell GA
stress.