comprehensive-workflow-mass-spectrometry-based-shotgun-proteomics

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples

Recent advances in mass spectrometry have resulted in deep proteomic&#160;analysis along with the generation of&#160;robust and&#160;reproducible ...

Indian Institute of Technology Bombay

Meningiomas (MGs) are frequent tumors of the CNS originating from the meningeal layers of the spinal cord and the brain. In this study, comparative tissue proteomic analysis of low and high grades of MGs was performed by using iTRAQ-based quantitative proteomics in combination with ESI-quadrupole-TOF and Q-Exactive MS, and results were validated by employing ELISA. Combining the results obtained from two MS platforms, we were able to identify overall 4308 proteins (1% false discover rate), among which 2367 exhibited differential expression (more than and equal to 2 peptide and ≥ 1.5-fold in at least one grade) in MGs. Several differentially expressed proteins were found to be associated with diverse signaling pathways, including integrin, Wnt, Ras, epidermal growth factor receptor, and FGR signaling. Proteins, such as vinculin or histones, which act as the signaling activators to initiate multiple signaling pathways, were found to be upregulated in MGs. Quite a few candidates, such as protein S-100A6, aldehyde dehydrogenase mitochondrial, AHNAK, cytoskeleton-associated protein 4, and caveolin, showed sequential increase in low- and high-grade MGs, whereas differential expressions of collagen alpha-1 (VI), protein S100-A9, 14 kDa phosphohistidine phosphatase, or transgelin-2 were found to be grade specific. Our findings provide new insights regarding the association of various signal transduction pathways in MG pathogenesis and may introduce new opportunities for the early detection and prognosis of MGs.

Multipronged quantitative proteomic analyses indicate modulation of various signal transduction pathways in human meningiomas.

Targeted Proteomics Workshop and International Symposium (IIT Bombay, Mumbai, India): An Accelerator for Global Proteomics.

The discovery of DNA microarrays was a major milestone in genomics; however, it could not adequately predict the structure or dynamics of underlying protein entities, which are the ultimate effector molecules in a cell. Protein microarrays allow simultaneous study of thousands of proteins/peptides, and various advancements in array technologies have made this platform suitable for several diagnostic and functional studies. Antibody arrays enable researchers to quantify the abundance of target proteins in biological fluids and assess PTMs by using the antibodies. Protein microarrays have been used to assess protein-protein interactions, protein-ligand interactions, and autoantibody profiling in various disease conditions. Here, we summarize different microarray platforms with focus on its biological and clinical applications in autoantibody profiling and PTM studies. We also enumerate the potential of tissue microarrays to validate findings from protein arrays as well as other approaches, highlighting their significance in proteomics.

Protein microarray applications: Autoantibody detection and posttranslational modification.

Protein microarrays are platforms for studying protein-protein interactions and identifying disease-related self-antigens/autoantigens, which elicit an immune response in a high-throughput format. Protein arrays have been extensively used over the past two decades for several clinical applications. By using this platform, serum containing autoantibodies against potential self-antigens can be screened on proteome-wide arrays, harboring a large repertoire of full-length human proteins. Identification of such autoantigens can help deducing early diagnostic, as well as, prognostic markers in case of malignancies, autoimmune disorders, and other systemic diseases. Here, we provide an overview of the protein microarray technology along with details of an established method to study autoantibody profiles from patient sera.

Serum Profiling for Identification of Autoantibody Signatures in Diseases Using Protein Microarrays.

Meningiomas are one of the most common tumors of the Central nervous system (CNS). This study aims to identify the autoantibody biomarkers in meningiomas using high-density human proteome arrays (~17,000 full-length recombinant human proteins). Screening of sera from 15 unaffected healthy individuals, 10 individuals with meningioma grade I and 5 with meningioma grade II was performed. This comprehensive proteomics based investigation revealed the dysregulation of 489 and 104 proteins in grades I and II of meningioma, respectively, along with the enrichment of several signalling pathways, which might play a crucial role in the manifestation of the disease. Autoantibody targets like IGHG4, CRYM, EFCAB2, STAT6, HDAC7A and CCNB1 were significantly dysregulated across both the grades. Further, we compared this to the tissue proteome and gene expression profile from GEO database. Previously reported upregulated proteins from meningioma tissue-based proteomics obtained from high-resolution mass spectrometry demonstrated an aggravated autoimmune response, emphasizing the clinical relevance of these targets. Some of these targets like SELENBP1 were tested for their presence in tumor tissue using immunoblotting. In the light of highly invasive diagnostic modalities employed to diagnose CNS tumors like meningioma, these autoantibody markers offer a minimally invasive diagnostic platform which could be pursued further for clinical translation.

Evaluation of autoantibody signatures in meningioma patients using human proteome arrays.

The emergence of omics technologies over the last decade has helped in advancement of research and our understanding of complex diseases like brain cancers. However, barring genomics, no other omics technology has been able to find utility in clinical settings. The recent advancements in mass spectrometry instrumentation have resulted in proteomics technologies becoming more sensitive and reliable. Targeted proteomics, a relatively new branch of mass spectrometry-based proteomics has shown immense potential in addressing the shortcomings of the standard molecular biology-based techniques like Western blotting and Immunohistochemistry. In this study we demonstrate the utility of Multiple reaction monitoring (MRM), a targeted proteomics approach, in quantifying peptides from proteins like Apolipoprotein A1 (APOA1), Apolipoprotein E (APOE), Prostaglandin H2 D-Isomerase (PTGDS), Vitronectin (VTN) and Complement C3 (C3) in cerebrospinal fluid (CSF) collected from Glioma and Meningioma patients. Additionally, we also report transitions for peptides from proteins - Vimentin (VIM), Cystatin-C (CST3) and Clusterin (CLU) in surgically resected Meningioma tissues; Annexin A1 (ANXA1), Superoxide dismutase (SOD2) and VIM in surgically resected Glioma tissues; and Microtubule associated protein-2 (MAP-2), Splicing factor 3B subunit 2 (SF3B2) and VIM in surgically resected Medulloblastoma tissues. To our knowledge, this is the first study reporting the use of MRM to validate proteins from three types of brain malignancies and two different bio-specimens. Future studies involving a large cohort of samples aimed at accurately detecting and quantifying peptides of proteins with roles in brain malignancies could potentially result in a panel of proteins showing ability to classify and grade tumors. Successful application of these techniques could ultimately offer alternative strategies with increased accuracy, sensitivity and lower turnaround time making them translatable to the clinics.

Shuvolina Mukherjee

Department of Biosciences and Bioengineering

Indian Institute of Technology Bombay

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples

Shuvolina Mukherjee

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Biosciences and Bioengineering

Indian Institute of Technology Bombay

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples

Department of Biosciences and Bioengineering