To begin, pack three layers of C18 resin in a 200-microliter pipette tip to construct a STop And Go Extraction or STAGE tip for each peptide sample.
Stop the enzymatic digestion of the previously incubated peptide samples by adding 1 by 10 volumes of stopping solution. Centrifuge the samples at 13,200 rpm for 10 minutes and transfer the supernatant to a new 2-milliliter tube.
Next, wash the STAGE tips with 100 microliters of 100 percent acetonitrile and centrifuge the STAGE tips at 1000 g for 2 minutes or until all the liquid pass through the C18 resin.
Repeat the STAGE tip washes with 50 microliters of Buffer B followed by 200 microliters of Buffer A with the same centrifugation conditions.
Load the samples into the STAGE tips to centrifuge at 1000 g for 3 to 5 minutes. Then, wash the STAGE tips with 200 microliters of Buffer A by centrifugation at 1000 g for 3 to 5 minutes.
Next, add 50 microliters of Buffer B into each STAGE tip, and using a syringe, elute the samples containing Buffer B into a 0.2-milliliter PCR tube.
Once the samples are eluted, dry the peptides using a vacuum centrifuge for 45 minutes. Run the samples on high-resolution mass spectrometry with the conditions described in the text manuscript.
To process the data for proteomic profiling, upload the raw data files obtained from mass spectrometry into the MaxQuant software. Refer to the text manuscript for all parameters of the software and its adjustments.
In global parameters, import the FASTA file of Homo sapiens for sequence identification downloaded from the Uniprot database recording the Organism ID, number of proteins, and file download date.
Set the number of computer cores for processing and select Start. Upon completion of MaxQuant, a 'Combined' folder, along with other files needed for uploading to data repositories, is generated.
To analyze the data, upload the 'proteingroups.txt' into Perseus and select all label-free quantification or LFQ intensity files to the 'Main' window. Filter the rows by removing contaminants, reverse peptides, and peptides only identified by site and transform the data by log2(x).
To observe the number of proteins detected in each replicate, construct a numeric Venn diagram and set categorial annotations for each sample by providing the same name for all replicates of one biological sample.
Filter the rows based on valid value with the protein identified in more than 50 percent of the replicates and within at least one group. To replace missing values for LFQ, perform imputation from the normal distribution.
Add annotation information downloaded from the Perseus website to the protein rows by adding txt.gz FASTA files in 'bin', 'conf', and 'annotation' folders. Bring in specific terms like protein names, gene names, and gene ontology.
The matrix is now complete and can be visualized in tools such as principal component analysis plots, heat maps, and category enrichment. Perform statistical testing to determine significant changes in protein abundance between the tested conditions.