Single-cell proteomics provides information about a cell at its protein level, which can be useful for research on cancer drug resistance and cell differentiation. However, current proteomics methods are not versatile and often result in high sample losses. To overcome this problem, researchers have now developed a new method of sample preparation called “water droplet-in-oil digestion” which minimizes sample loss, maximizes protein identification and provides better sensitivity by compared to conventional methods.
The proteins that make up our cells hold a world of information that, when unlocked, can give us insight into the origins of many essential biological phenomena. This information is gathered using an analytical technique known as “single-cell proteomics”, in which single-cell analysis is performed to observe the characteristics of individual cells at their protein level. Over the years, scientists have used single-cell proteomics in the areas of cancer genomics, cell differentiation, and tissue development. However, current proteomics techniques suffer from low protein sample recovery, low throughput, and lack of versatility.
Fortunately, a team of researchers from Japan and the United States led by Assistant Professor Takeshi Masuda of Kumamoto University in Japan has found a solution to these problems. In a recent study posted online on July 11, 2022 and published in Volume 94, Number 29 of Analytical Chemistry on July 26, 2022, the team introduced a simple but highly efficient method of sample preparation for single-cell proteomics called the “drop-in-oil method” (WinO). The technique uses the immiscibility of water with oil/organic solvent to its advantage to prepare protein samples with minimal loss and increased chance of sample recovery.
“To make single-cell proteomics more efficient, we either need to amplify the protein sample or ensure that no part is lost during sample preparation. As we did not have the means to do the First, it was crucial that we reduce adsorption losses during sample preparation steps like sample transfer,” says Dr. Masuda. “The WinO technique not only reduces sample loss through adsorption, but also offers better throughput compared to conventional methods.”
For the WinO process, the team first prepared an extraction buffer by mixing a microliter of water with phase transfer surfactants (which increase the solubility of hydrophobic proteins) and hydrophobic nanomagnetic beads coated with carboxyl. This mixture was then poured dropwise into 50 microliters of ethyl acetate.
The next step was protein extraction, which was performed by adding cell droplets from the cell sorter to the ethyl acetate-water droplet combo and spinning it in a centrifuge to allow the protein to settle. accumulate in the water droplet. After extraction, the sample was digested using a protein enzyme, Lys-C, and labeled using a “tandem mass tag” reagent. The extracted-digested-labeled sample was then purified and recovered for single-cell analysis and proteomic profiles.
To compare the effectiveness of the WinO method against conventional methods, the team also prepared samples using the standard in-solution digestion (ISD) method and performed proteomic analysis. They found that the WinO method resulted in a 10-fold increase in protein and peptide recovery compared to ISD. This remarkable improvement was attributed to a reduced contact area between the extraction solution and the sample container.
To analyze the sensitivity of the two methods, the team also compared the proteomic profiles obtained. They observed a strong correlation between the proteomic profiles obtained for 100 cells with WinO and that for 10,000 cells with ISD. Additionally, the team successfully quantified 462 proteins using WinO, demonstrating that it provides much higher throughput and extraction efficiency than conventional techniques.
The enhanced protein retrieval and identification capability provided by WinO could allow closer examination of cancer cell protein expression and better understanding of the mechanisms underlying cancer drug resistance. Additionally, WinO can be semi-automated using a liquid handling robot, making it suitable for high-speed, high-capacity sample processing. “Our research could allow scientists to perform proteomics on rare and limited sample quantities as well as provide new insight into protein expression, opening up possibilities for discovering novel biological phenomena,” concludes Dr. Masuda.
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