Name: comprehensive workflow of mass spectrometry-based shotgun proteomics of tissue samples
Uploaded: 2021-11-13T13:00:00
Description: Watch this Scientific Journal Video about Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples at JoVE.com

We acknowledge MHRD-UAY Project (UCHHATAR AVISHKAR YOJANA), project #34_IITB to SS and MASSFIITB Facility at IIT Bombay supported by the Department of Biotechnology (BT/PR13114/INF/22/206/2015) to carry out all MS-related experiments.

This study was reviewed and approved by institutional review boards and the ethics committee of the Indian Institute of Technology Bombay (IITB-IEC/2016/026). The patients/participants provided their written consent to participate in this study.
1. Tissue lysate preparation
NOTE: Perform all the following steps on the ice to keep the proteases inactive. Make sure the scalpels and any tubes used are sterile to avoid any cross-contamination.
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Tissue proteomics of biological samples enables us to explore new potential biomarkers associated with different stages of disease progression. It also explains the mechanism of signaling and pathways associated with disease progression. The described protocol for tissue quantitative proteomics analysis provides reproducible good coverage data. Most of the steps have been adapted from the manufacturer&#39;s instructions. In order to obtain high-quality data, the following steps are most crucial. Hence, extra care should ...

Proteomics technologies have the potential to enable the identification and quantification of potential candidate markers that can aid in the detection and prognostication of the disease1. Recent advancements in the field of mass spectrometry have&#160;accelerated clinical research at the protein level. Researchers are trying to address the challenge of complicated pathobiology of several diseases using mass spectrometry-based proteomics, which now offers increased sensitivity for protein identification and quantification2. Accurate quantitative measurement of proteins is crucial to comprehend the dynamic and spatial cooperation among proteins in healthy and diseased individuals3; however, such analysis on a proteome-wide scale is not easy.
One major limitation of proteomic profiling of clinical specimens is the complexity of biological samples. Many different types of samples have been investigated to study the disease proteome, such as cell lines, plasma, and tissues4,5. Cell lines are widely used as models in in vitro experiments to mimic different stages of disease progression. However, one major limitation with cell lines is that they easily acquire genotypic and phenotypic changes during the process of cell culture6. Body fluids such as plasma could be an attractive source for biomarker discovery; however, due to the highly abundant proteins and dynamic range of protein concentration, plasma proteomics is a bit more challenging7. Here, peptides originated from the most abundant proteins can suppress those derived from the low abundant proteins even if the mass/charge ratio is the same6. Although there have been advancements in the depletion and fractionation technologies in the last few years, getting good coverage still remains a major limitation of plasma proteomics8,9. The use of tissues for proteomic investigation of disease biology is preferred as tissue samples are most proximal to the disease sites&#160;and offer high physiological and pathological information to provide better insights into the disease biology10,11.
In this manuscript, we have provided a simplified protocol for the quantitative proteomics of tissue samples. We have used a buffer containing 8 M urea for the tissue lysate preparation as this buffer is compatible with mass spectrometry-based investigations. However, it is mandatory to clean the peptides to remove salts before injecting them into the mass spectrometer. One important point to remember is to reduce the urea concentration to less than 1 M before adding trypsin for protein digestion as trypsin exhibits low activity at 8 M urea concentration. We have explained two approaches of quantitative global proteomics: label-based quantification using iTRAQ (isobaric tags for relative and absolute quantification) and label-free quantification (LFQ). The iTRAQ-based quantitative proteomics is mainly used for comparing multiple samples varying in their biological condition (e.g., normal versus disease or treated samples). The approach utilizes isobaric reagents to label the N-terminal primary amines of peptides12. The iTRAQ reagents contain one N-methyl piperazine reporter group, a balancer group, and one N-hydroxy succinimide ester group that reacts with N-terminal primary amines of peptides13. Digested peptides from each condition are labeled with a particular iTRAQ reagent. Following the labeling, the reaction is stopped and labeled peptides from different conditions are pooled into a single tube. This combined sample mixture is analyzed by mass spectrometer for identification and quantification. After the MS/MS analysis, reporter ion fragments with low molecular masses are generated and the ion intensities of these reporter ions are used for the quantification of the proteins.
Another approach, label-free quantification is used to determine the relative number of proteins in complex samples without labeling peptides with stable isotopes.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Reagents</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Acetonitrile (MS grade)</td>
			<td>Fisher Scientific</td>
			<td>A/0620/21</td>
			<td></td>
		</tr>
		<tr>
			<td>Bovine Serum Albumin</td>
			<td>HiMedia</td>
			<td>TC194-25G</td>
			<td></td>
		</tr>
		<tr>
			<td>Calcium chloride</td>
			<td>Fischer Scienific</td>
			<td>BP510-500</td>
			<td></td>
		</tr>
		<tr>
			<td>Formic acid (MS grade)</td>
			<td>Fisher Scientific</td>
			<td>147930250</td>
			<td></td>
		</tr>
		<tr>
			<td>Iodoacetamide</td>
			<td>Sigma</td>
			<td>1149-25G</td>
			<td></td>
		</tr>
		<tr>
			<td>Isopropanol (MS grade)</td>
			<td>Fisher Scientific</td>
			<td>Q13827</td>
			<td></td>
		</tr>
		<tr>
			<td>Magnesium Chloride</td>
			<td>Fischer Scienific</td>
			<td>BP214-500</td>
			<td></td>
		</tr>
		<tr>
			<td>Methanol (MS grade)</td>
			<td>Fisher Scientific</td>
			<td>A456-4</td>
			<td></td>
		</tr>
		<tr>
			<td>MS grade water</td>
			<td>Pierce</td>
			<td>51140</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate Buffer Saline</td>
			<td>HiMedia</td>
			<td>TL1006-500ML</td>
			<td></td>
		</tr>
		<tr>
			<td>Protease inhibitor cocktail</td>
			<td>Roche Diagnostics</td>
			<td>11873580001</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium Chloride</td>
			<td>Merck</td>
			<td>DF6D661300</td>
			<td></td>
		</tr>
		<tr>
			<td>TCEP</td>
			<td>Sigma</td>
			<td>646547</td>
			<td></td>
		</tr>
		<tr>
			<td>Tris Base</td>
			<td>Merck</td>
			<td>648310</td>
			<td></td>
		</tr>
		<tr>
			<td>Trypsin (MS grade)</td>
			<td>Pierce</td>
			<td>90058</td>
			<td></td>
		</tr>
		<tr>
			<td>Bradford Reagent</td>
			<td>Bio-Rad</td>
			<td>5000205</td>
			<td></td>
		</tr>
		<tr>
			<td>Urea</td>
			<td>Merck</td>
			<td>MB1D691237</td>
			<td></td>
		</tr>
		<tr>
			<td>Supplies</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Hypersil Gold C18 column</td>
			<td>Thermo</td>
			<td>25002-102130</td>
			<td></td>
		</tr>
		<tr>
			<td>Micropipettes</td>
			<td>Gilson</td>
			<td>F167380</td>
			<td></td>
		</tr>
		<tr>
			<td>Stage tips</td>
			<td>MilliPore</td>
			<td>ZTC18M008</td>
			<td></td>
		</tr>
		<tr>
			<td>Zirconia/Silica beads</td>
			<td>BioSpec products</td>
			<td>11079110z</td>
			<td></td>
		</tr>
		<tr>
			<td>Equipment</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Bead beater (Homogeniser)</td>
			<td>Bertin Minilys</td>
			<td>P000673-MLYS0-A</td>
			<td></td>
		</tr>
		<tr>
			<td>Microplate reader (spectrophotometer)</td>
			<td>Thermo</td>
			<td>MultiSkan Go</td>
			<td></td>
		</tr>
		<tr>
			<td>pH meter</td>
			<td>Eutech</td>
			<td>CyberScan pH 510</td>
			<td></td>
		</tr>
		<tr>
			<td>Probe Sonicator</td>
			<td>Sonics Materials, Inc</td>
			<td>VCX 130</td>
			<td></td>
		</tr>
		<tr>
			<td>Shaking Drybath</td>
			<td>Thermo</td>
			<td>88880028</td>
			<td></td>
		</tr>
		<tr>
			<td>Orbitrap Fusion mass spectrometer</td>
			<td>Thermo</td>
			<td>FSN 10452</td>
			<td></td>
		</tr>
		<tr>
			<td>Nano LC</td>
			<td>Thermo</td>
			<td>EASY-nLC1200</td>
			<td></td>
		</tr>
		<tr>
			<td>Vacuum concentrator</td>
			<td>Thermo</td>
			<td>Savant ISS 110</td>
			<td></td>
		</tr>
		<tr>
			<td>Software</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Proteome Discoverer</td>
			<td>Thrermo</td>
			<td>Proteome Discoverer 2.2.0.388</td>
			<td></td>
		</tr>
	</tbody>
</table>

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 datasets. However, despite the considerable technical advancements, sample preparation from biospecimens such as patient blood, CSF, and tissue still poses considerable challenges. For identifying biomarkers, tissue proteomics often provides an attractive sample source to translate the research findings from the bench to the clinic. It can reveal potential candidate biomarkers for early diagnosis of cancer and neurodegenerative diseases such as Alzheimer&#39;s disease, Parkinson&#39;s disease, etc. Tissue proteomics also yields a wealth of systemic information based on the abundance of proteins and helps to address interesting biological questions.
Quantitative proteomics analysis can be grouped into two broad categories: a label-based and a label-free approach. In the label-based approach, proteins or peptides are labeled using stable isotopes such as SILAC (stable isotope labeling with amino acids in cell culture) or by chemical tags such as ICAT (isotope-coded affinity tags), TMT (tandem mass tag) or iTRAQ (isobaric tag for relative and absolute quantitation). Label-based approaches have the advantage of more accurate quantitation of proteins and using isobaric labels, multiple samples can be analyzed in a single experiment. The label-free approach provides a cost-effective alternative to label-based approaches. Hundreds of patient samples belonging to a particular cohort can be analyzed and compared with other cohorts based on clinical features. Here, we have described an optimized quantitative proteomics workflow for tissue samples using label-free and label-based proteome profiling methods, which is crucial for applications in life sciences, especially biomarker discovery-based projects.

We have used two different approaches for discovery proteomics: label-free and label-based proteomics approaches. The protein profile of tissue samples on SDS-PAGE showed the intact proteins and could be considered for proteomic analysis (Figure 2A). The quality control check of the instrument was monitored via system suitability software and it showed the day-wise variation in the instrument performance (Figure 2B). We observed 91% sequence coverage of...

Watch this Scientific Journal Video about Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples at JoVE.com

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

The described protocol provides an optimized quantitative proteomics analysis of tissue samples using two approaches: label-based and label free quantitation. Label-based approaches have the advantage of more accurate quantitation of proteins, while a label-free approach is more cost-effective and used to analyze hundreds of samples of a cohort.

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

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