Coupling Microdroplet-Based Sample Preparation, Multiplexed Isobaric Labeling, and Nanoflow Peptide Fractionation for Deep Proteome Profiling of the Tissue Microenvironment.

There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity in a cell-type-specific manner to better understand and predict the function of complex biological systems such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverage due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (microdroplet processing in one pot for trace samples), multiplexed isobaric labeling, and a nanoflow peptide fractionation approach. The integrated workflow allowed us to maximize proteome coverage of laser-isolated tissue samples containing nanogram levels of proteins. We demonstrated that the deep spatial proteomics platform can quantify more than 5000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 µm2) and differentiate unique protein abundance patterns in pancreas. Furthermore, the use of the microPOTS chip eliminated the requirement for advanced microfabrication capabilities and specialized nanoliter liquid handling equipment, making it more accessible to proteomic laboratories.

Interlaboratory Comparison of Antibody-Free LC-MS/MS Measurements of C-peptide and Insulin.

BACKGROUND: The enhanced precision and selectivity of liquid chromatography-tandem mass spectrometry (LC-MS/MS) makes it an attractive alternative to certain clinical immunoassays. Easily transferrable work flows could help facilitate harmonization and ensure high-quality patient care. We aimed to evaluate the interlaboratory comparability of antibody-free multiplexed insulin and C-peptide LC-MS/MS measurements. METHODS: The laboratories that comprise the Targeted Mass Spectrometry Assays for Diabetes and Obesity Research (TaMADOR) consortium verified the performance of a validated peptide-based assay (reproducibility, linearity, and lower limit of the measuring interval [LLMI]). An interlaboratory comparison study was then performed using shared calibrators, de-identified leftover laboratory samples, and reference materials. RESULTS: During verification, the measurements were precise (2.7% to 3.7%CV), linear (4 to 15 ng/mL for C-peptide and 2 to 14 ng/mL for insulin), and sensitive (LLMI of 0.04 to 0.10 ng/mL for C-peptide and 0.03 ng/mL for insulin). Median imprecision across the 3 laboratories was 13.4% (inter-quartile range [IQR] 11.6%) for C-peptide and 22.2% (IQR 20.9%) for insulin using individual measurements, and 10.8% (IQR 8.7%) and 15.3% (IQR 14.9%) for C-peptide and insulin, respectively, when replicate measurements were averaged. Method comparison with the University of Missouri reference method for C-peptide demonstrated a robust linear correlation with a slope of 1.044 and r2 = 0.99. CONCLUSIONS: Our results suggest that combined LC-MS/MS measurements of C-peptide and insulin are robust and adaptable and that standardization with a reference measurement procedure could allow accurate and precise measurements across sites, which could be important to diabetes research and help patient care in the future.

Decrease in multiple complement proteins associated with development of islet autoimmunity and type 1 diabetes.

Type 1 diabetes (T1D) is a chronic condition caused by autoimmune destruction of the insulin-producing pancreatic ß cells. While it is known that gene-environment interactions play a key role in triggering the autoimmune process leading to T1D, the pathogenic mechanism leading to the appearance of islet autoantibodies-biomarkers of autoimmunity-is poorly understood. Here we show that disruption of the complement system precedes the detection of islet autoantibodies and persists through disease onset. Our results suggest that children who exhibit islet autoimmunity and progress to clinical T1D have lower complement protein levels relative to those who do not progress within a similar time frame. Thus, the complement pathway, an understudied mechanistic and therapeutic target in T1D, merits increased attention for use as protein biomarkers of prediction and potentially prevention of T1D.

Multi-scale signaling and tumor evolution in high-grade gliomas.

Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas.