Dataset Information

A quantitative proteomic workflow for characterization of frozen clinical biopsies: laser capture microdissection coupled with label-free mass spectrometry.

ABSTRACT: This paper describes a simple, highly efficient and robust proteomic workflow for routine liquid-chromatography tandem mass spectrometry analysis of Laser Microdissection Pressure Catapulting (LMPC) isolates. Highly efficient protein recovery was achieved by optimization of a "one-pot" protein extraction and digestion allowing for reproducible proteomic analysis on as few as 500 LMPC isolated cells. The method was combined with label-free spectral count quantitation to characterize proteomic differences from 3000-10,000 LMPC isolated cells. Significance analysis of spectral count data was accomplished using the edgeR tag-count R package combined with hierarchical cluster analysis. To illustrate the capability of this robust workflow, two examples are presented: 1) analysis of keratinocytes from human punch biopsies of normal skin and a chronic diabetic wound and 2) comparison of glomeruli from needle biopsies of patients with kidney disease. Differentially expressed proteins were validated by use of immunohistochemistry. These examples illustrate that tissue proteomics carried out on limited clinical material can obtain informative proteomic signatures for disease pathogenesis and demonstrate the suitability of this approach for biomarker discovery.

SUBMITTER: Shapiro JP

PROVIDER: S-EPMC3835202 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A quantitative proteomic workflow for characterization of frozen clinical biopsies: laser capture microdissection coupled with label-free mass spectrometry.

Shapiro John P JP Biswas Sabyasachi S Merchant Anand S AS Satoskar Anjali A Taslim Cenny C Lin Shili S Rovin Brad H BH Sen Chandan K CK Roy Sashwati S Freitas Michael A MA

Journal of proteomics 20120925

This paper describes a simple, highly efficient and robust proteomic workflow for routine liquid-chromatography tandem mass spectrometry analysis of Laser Microdissection Pressure Catapulting (LMPC) isolates. Highly efficient protein recovery was achieved by optimization of a "one-pot" protein extraction and digestion allowing for reproducible proteomic analysis on as few as 500 LMPC isolated cells. The method was combined with label-free spectral count quantitation to characterize proteomic dif ...[more]

PMID: 23022584

Similar Datasets

Project description:The etiology of Type 1 Diabetes (T1D) remains elusive. Enzymatically isolated and cultured (EIC) islets cannot fully reflect the natural protein composition and disease process of in vivo islets, because of the stress from isolation procedures. In order to study islet protein composition in conditions close to the natural environment, we performed proteomic analysis of EIC islets, and laser capture microdissected (LCM) human islets and acinar tissue from fresh-frozen pancreas sections of three cadaveric donors. 1104 and 706 proteins were identified from 6 islets equivalents (IEQ) of LCM islets and acinar tissue, respectively. The proteomic profiles of LCM islets were reproducible within and among cadaveric donors. The endocrine hormones were only detected in LCM islets, whereas catalytic enzymes were significantly enriched in acinar tissue. Furthermore, high overlap (984 proteins) and similar function distribution were found between LCM and EIC islets proteomes, except that EIC islets had more acinar contaminants and stress-related signal transducer activity proteins. The comparison among LCM islets, LCM acinar tissue and EIC islets proteomes indicates that LCM combined with proteomic methods enables accurate and unbiased profiling of islet proteome from frozen pancreata. This paves the way for proteomic studies on human islets during the progression of T1D.The etiological agent triggering autoimmunity against beta cells in Type 1 diabetes (T1D) remains obscure. The in vitro models available (enzymatically isolated and cultured islets, EIC islets) do not accurately reflect what happens in vivo due to lack of the natural environment where islets exist and the preparation-induced changes in cell physiology. The importance of this study is that we investigated the feasibility of laser capture microdissection (LCM) for the isolation of intact islets from frozen cadaveric pancreatic tissue sections. We compared the protein profile of LCM islets (9 replicates from 3 cadaveric donors) with that of both LCM acinar tissues (6 replicates from the same 3 cadaveric donor as LCM islets) and EIC islets (at least 4 replicates for each sample with the same islets equivalents) by using proteomics techniques with advanced instrumentation, nanoLC-Q Exactive HF Orbitrap mass spectrometry (nano LC-MS/MS). The results demonstrate that the LCM method is reliable in isolating islets with an intact environment. LCM-based islet proteomics is a feasible approach to obtain good proteome coverage for assessing the pathology of T1D using cadaveric pancreatic samples, even from very small sample amounts. Future applications of this LCM-based proteomic method may help us understand the pathogenesis of T1D and identify potential biomarkers for T1D diagnosis at an early stage.

Project description:Background:Haematoxylin and eosin (H&E)-which respectively stain nuclei blue and other cellular and stromal material pink-are routinely used for clinical diagnosis based on the identification of morphological features. A richer characterization can be achieved by laser capture microdissection coupled to mass spectrometry (LCM-MS), giving an unbiased assay of the proteins that make up the tissue. However, the process of fixing and H&E staining of tissues provides challenges with standard sample preparation methods for mass spectrometry, resulting in low protein yield. Here we describe a microproteomics technique to analyse H&E-stained, formalin-fixed paraffin-embedded (FFPE) tissues. Methods:Herein, we utilize heat extraction, physical disruption, and in column digestion for the analysis of H&E stained FFPE tissues. Micro-dissected morphologically normal human lung alveoli (0.082 mm3) and human lung blood vessels (0.094 mm3) from FFPE-fixed H&E-stained sections from Idiopathic Pulmonary Fibrosis (IPF) specimens (n?=?3 IPF specimens) were then subject to a qualitative and then quantitative proteomics approach using BayesENproteomics. In addition, we tested the sensitivity of this method by processing and analysing a range of micro-dissected human lung blood vessel tissue volumes. Results:This approach yields 1252 uniquely expressed proteins (at a protein identification threshold of 3 unique peptides) with 892 differentially expressed proteins between these regions. In accord with prior knowledge, our methodology approach confirms that human lung blood vessels are enriched with smoothelin, CNN1, ITGA7, MYH11, TAGLN, and PTGIS; whereas morphologically normal human lung alveoli are enriched with cytokeratin-7, -8, -18, -19, 14, and -17. In addition, we identify a total of 137 extracellular matrix (ECM) proteins and immunohistologically validate that laminin subunit beta-1 localizes to morphologically normal human lung alveoli and tenascin localizes to human lung blood vessels. Lastly, we show that this micro-proteomics technique can be applied to tissue volumes as low as 0.0125 mm3. Conclusion:Herein we show that our multistep sample preparation methodology of LCM-MS can identify distinct, characteristic proteomic compositions of anatomical features within complex fixed and stained tissues.

Project description:Different cell types and multiple cellular connections characterize the human brain. Gene expression analysis using a specific population of cells is more accurate than conducting analysis of the whole tissue homogenate, particularly in the context of neurodegenerative diseases, where a specific subset of cells is affected by the different pathology. Due to the difficulty of obtaining homogenous cell populations, gene expression in specific cell-types (neurons, astrocytes, etc.) has been understudied. To leverage the use of archive resources of frozen human brains in studies of neurodegenerative diseases, we developed and calibrated a method to quantify cell-type specific-neuronal, astrocytes-expression profiles of genes implicated in neurodegenerative diseases, including Parkinson's and Alzheimer's diseases. Archive human frozen brain tissues were used to prepare slides for rapid immunostaining using cell-specific antibodies. The immunoreactive-cells were isolated by Laser Capture Microdissection (LCM). The enrichment for a particular cell-type of interest was validated in post-analysis stage by the expression of cell-specific markers. We optimized the technique to preserve the RNA integrity, so that the RNA was suitable for downstream expression analyses. Following RNA extraction, the expression levels were determined digitally using nCounter Single Cell Gene Expression assay (NanoString Technologies®). The results demonstrated that using our optimized technique we successfully isolated single neurons and astrocytes from human frozen brain tissues and obtained RNA of a good quality that was suitable for mRNA expression analysis. We present here new advancements compared to previous reported methods, which improve the method's feasibility and its applicability for a variety of downstream molecular analyses. Our new developed method can be implemented in genetic and functional genomic research of neurodegenerative diseases and has the potential to significantly advance the field.

Dataset Information

A quantitative proteomic workflow for characterization of frozen clinical biopsies: laser capture microdissection coupled with label-free mass spectrometry.

Publications

A quantitative proteomic workflow for characterization of frozen clinical biopsies: laser capture microdissection coupled with label-free mass spectrometry.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets