NEW YORK(GenomeWeb) – Researchers at Rotterdam's Erasmus University Medical Center have demonstrated the compatibility of acid guanidinium thiocyanate, phenol, and chloroform extraction (AGPC) with mass spec-based proteomics.
Commonly used to extract DNA and RNA from tissue for analysis, AGPC has been less commonly used for protein work given various technical difficulties. In a paper published last week in the Journal of Proteome Research, the Erasmus team presented a workflow using AGPC for protein extraction in shotgun proteomics.
According to Arzu Umar, an Erasmus researcher and senior author on the paper, the method could offer improved multi-omic analyses and significantly add to the store of clinical samples available for proteomic research.
AGPC is a liquid-liquid extraction method that generates a water phase containing RNA and an organic phase containing DNA and protein. In theory, the procedure allows for capture of DNA, RNA, and protein from a single, identical piece of tissue. However, in practice, sample prep difficulties have limited the approach's usefulness for mass spec-based proteomics.
Specifically, the protein pellets generated by precipitation of the protein in the organic fraction are typically too large to be re-dissolved. Additionally, detergents like SDS that are used to dissolve these protein pellets must be removed prior to digestion and mass spec analysis.
To get around these issues, the Erasmus team used only a portion of the organic fraction generated by the AGPC extraction, leaving them with a smaller protein pellet that could be more easily dissolved. Additionally, they used filter-aided sample preparation (FASP) to clean up the sample for mass spec analysis.
"Usually people prepare whole tissue biopsies which can be several hundred milligrams of tissue and then you have a very large organic fraction," Umar told GenomeWeb. "But what we have shown is you don't need to use this whole organic fraction, but only a smaller fraction. And then you end up with relatively smaller amounts of protein but still between 50 and 200 micrograms, which is an enormous amount for current day proteomics pipelines."
In the JPR study, the researchers applied this approach to 11 snap-frozen breast tumor tissues, running the proteins extracted via the AGPC method on a nanoLC system attached to a Thermo Fisher Scientific Q Exactive using tandem mass tag isobaric labels for quantitation.
To determine whether the technique resulted in protein fractions representative of the tumor samples, they compared RNA and protein levels of the clinical breast cancer markers HER2, ER, and PR, which, Umar noted, previous research has demonstrated are correlated at the transcript and protein level.
"We know that not all proteins correspond with their RNA," she said. "But we know from previous experiments that these three proteins should correlate well, and in our case they did. So we basically did this as a proof of principle."
Additionally, the researchers tried successfully to divide the samples into ER-positive and ER-negative groups based on their protein data.
Development of an AGPC extraction approach compatible with shotgun proteomics is significant in that it allows for multi-omic analyses to be easily performed on the exact same tissue, as opposed to different sections of a single tumor.
"Cancer tissue is very heterogeneous," Umar said. "So if you are using different portions of tumor tissue, they could give you completely different molecular profiles. So it would be best to extract your DNA, RNA, and protein from exactly the same starting material, but so far it hasn't been done all that often."
She cited the example of the National Cancer Institute's Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium, which have partnered on a project in which CPTAC researchers are performing proteomic analysis of tumors previously characterized genomically by the TCGA project.
While the tumors are matched, different portions of the tumors are being used for each part of the analysis, raising the issue of tumor heterogeneity, Umar said, noting that this issue is common to the majority of multi-omic studies done to date.
Beyond potentially helping with questions of tumor heterogeneity, use of proteins captured during AGPC extraction also opens up a potentially large set of new clinical samples for proteomics research. Indeed, this was the Erasmus group's initial motivation for researching the method, Umar said.
She and her colleagues were in the middle of developing a biomarker signature to identify triple-negative breast cancer patients who should receive adjuvant chemotherapy when they realized that they would not have enough clinical samples to validate their signature.
"Biomarker discovery isn't very meaningful if you can't validate it," Umar said. And so, the researchers turned to organic fractions left over from clinical samples that had been prepared for genomic analysis using AGPC extraction.
Their success using these fractions suggests that other proteomics researchers could do likewise – a potentially significant finding given the difficulty researchers often have obtaining high quality clinical samples for their work.
"In most cases, people don't have the availability of many fresh frozen samples for protein analysis," Umar said. "So what we provide here is a nice alternative, because these organic fractions are usually left over [after genomic studies]."
She added that she has begun telling her collaborators on the genomics side to store these organic fractions and that she hopes the practice will become more widespread in the genomics community.
"If people are not aware, then they don't really store them," she said. "But we tell our collaborators to please store them, and when you ask, they do. It's really not much effort to keep [the organic fractions], because the only thing they need to do is not throw them away. So it's not much effort and a huge gain."
In an email to GenomeWeb, Mehdi Mesri, a program manager for the CPTAC project noted that while AGPC extractions "are not typically saved for future mass spectrometric analysis" due to the perceived challenges in using these fractions, "in a scenario where the source specimen is no longer available and once wished to analyze... proteins on the remaining tissue sample, AGPC extraction is an interesting approach."
He added that of particular interest was the Erasmus team's finding that the protein data corresponded as expected with the transcript data, indicating that AGPC is as effective for protein extraction as standard proteomic sample prep methods.