Composed mainly of β-cells, human islet cells secrete hormones that help regulate blood sugar. In type 1 diabetes (T1D), the immune system attacks β-cells, causing cell dysfunction and death. While researchers have determined several risk factors to developing T1D, including a genetic predisposition and environmental triggers, the exact pathogenic mechanisms remain unknown. Zhang et al. posit that investigating proteomic changes in islets could provide insights to better understand causes of T1D.1
In this investigation, donor organs were obtained from three non-diabetic cadavers from the cGMP/GTP Cell Processing Facility of the Diabetes Research Institute, at the University of Miami. The researchers dissected pancreas samples and captured cells using laser capture microdissection (LCM). To validate the proteomic analysis, they also used enzymatic isolation and culture (EIC). For EIC, they cultured cells for 12 hours prior to mass spectrometry. For LCM they sectioned frozen tissue blocks, dehydrated the slides and stained them with Toluidine Blue O to discriminate islets and acinar tissue. Next, they performed LCM to isolate nine sections of islets and six sections of acinar tissue. They sonicated the samples and digested them with trypsin prior to proteomic analysis.
The team applied liquid chromatography (LC) using an UltiMate 3000 ultra-high-performance LC system (Thermo Scientific) to separate proteins. Then they chose a mass spectrometry–based label-free proteomics approach with nanoLC–mass spectrometry using a Q Exactive HF mass spectrometer (Thermo Scientific).
Applying MaxQuant, the team searched the UniProt database for protein identifications. After removing reverse hits and potential contaminants, they arrived at a total of 1,104 unique proteins for the LCM islets with 80% overlap in the samples and 71% overlap among the three donors, representing good reproducibility in the proteome coverage. The Human Protein Atlas (HPA) indicated that 922 proteins of the total 1,104 proteins previously showed expression in islets.
Zhang and colleagues classified the HPA protein abundance into four levels: high, medium, low and not detectable. The HPA indicated that 169 proteins detected at high abundance, 347 at medium abundance and 170 at low abundance. Comparing this with the Beta Cell Gene Atlas (BCGA) they found 1,065 out of 1,104 proteins in LCM isolates annotated in the pancreatic islet transcriptome. Within the BCGA, researchers found 997 proteins that derived from pancreatic islet transcripts had enriched expression, 12 had moderate expression, 16 had low expression and 32 had no expression.
In LCM acinar tissues, they identified 706 proteins in six samples from the same three cadaveric donors (80% on average) and among cadaveric donors (70%). Comparing cell types, 623 proteins (88.9 ± 1.5%) overlapped with those identified in LCM acinar tissue. Using LCM, Zhang et al. successfully analyzed the proteome of LCM pancreatic islets and LCM acinar tissue from frozen sections of human pancreas. Comparisons of LCM with EIC proteomic analysis revealed 984 proteins with EIC and a 90% overlap with LCM islets.
Using LCM to analyze proteins is a reliable alternative to EIC. Since LCM essentially acts as a “snapshot” preserving samples in time, it helps reveal the pathophysiological mechanisms underlying islet and β-cell dysfunction in T1D.
1. Zhang, L., et al. (2016) “Proteomic profiling of human islets collected from frozen pancreata using laser capture microdissection,” Journal of Proteomics, 150 (pp. 149–159), doi: 10.1016/j.jprot.2016.09.002.