This work was supported by the Natural Sciences and Engineering Research Council of Canada, NSERC RGPIN 05145-17.

<ol>
	<li>Kovalchuk, S. I., Ziganshin, R., Shelukhina, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Simple+in-house+ultra-high+performance+capillary+column+manufacturing+with+the+FlashPack+approach.">Simple in-house ultra-high performance capillary column manufacturing with the FlashPack approach.</a> Journal of Visualized Experiments. (178), e62522 (2021).</li><li>Sirois, I., Isabelle, M., Duquette, J. D., Saab, F., Caron, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immunopeptidomics:+Isolation+of+mouse+and+human+MHC+Class+I-+and+II-associated+peptides+for+mass+spectrometry+analysis.">Immunopeptidomics: Isolation of mouse and human MHC Class I- and II-associated peptides for mass spectrometry analysis.</a> Journal of Visualized Experiments. (176), e63052 (2021).</li><li>Han, Y., Thomas, C. T., Wennersten, S. A., Lau, E., Lam, M. P. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Shotgun+proteomics+sample+processing+automated+by+an+open-source+lab+robot.">Shotgun proteomics sample processing automated by an open-source lab robot.</a> Journal of Visualized Experiments. (176), e63092 (2021).</li><li>Nickerson, J. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Organic+solvent-based+protein+precipitation+for+robust+proteome+purification+ahead+of+mass+spectrometry.">Organic solvent-based protein precipitation for robust proteome purification ahead of mass spectrometry.</a> Journal of Visualized Experiments. (180), e63503 (2022).</li><li>Li, D., Liang, J., Zhang, Y., Zhang, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+integrated+workflow+of+identification+and+quantification+on+FDR+control-based+untargeted+metabolome.">An integrated workflow of identification and quantification on FDR control-based untargeted metabolome.</a> Journal of Visualized Experiments. , e63625 (2022).</li><li>Petelski, A. A., Nikolai Slavov, N., Specht, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+proteomics+preparation+for+mass+spectrometry+analysis+using+freeze-heat+lysis+and+an+isobaric+carrier.">Single-cell proteomics preparation for mass spectrometry analysis using freeze-heat lysis and an isobaric carrier.</a> Journal of Visualized Experiments. , e63802 (2022).</li></ol>

The author has nothing to disclose.

With its remarkable gains in sensitivity, speed, and versatility, modern mass spectrometry (MS) supplies researchers with greater opportunities for proteome characterization. With improved technologies, researchers are demanding a greater level of stringency in their results. Therefore, of equal importance to the proteomics workflow are innovative sample preparation strategies devised to isolate, separate, and process complex proteomic mixtures ahead of MS. The chemical diversity of proteomic systems precludes a &#8216;one-size-fits-all&#8217; approach to sample preparation. However, as seen through this methods collection, multiple protocols are available to maximize the quality and confidence of MS data. This collection aims to provide researchers with easy-to-implement tools and tricks designed to enhance the expected outcome of proteomic and metabolomic workflows.

Capillary HPLC and UPLC columns are near ubiquitous to comprehensive proteomics workflows. While self-packed capillary columns are a low-cost alternative to commercial columns, those who have attempted to pack their own columns may be familiar with inconsistent packing rates and variable column quality. Kovalchuk and colleagues at the Russian Academy of Science demonstrate their FlashPack approach to ensure the efficient and consistent packing of the UPLC capillary columns1. A combination of precisely controlled variables reduces cupola formation at the capillary entrance and allows rapid column filling using a low-pressure packing bomb.

Immunopeptidomics is an emerging sub-discipline of proteomics, with clinical implications in oncology and immune therapies. Reliable MS analysis requires isolation of MHC class I/II, or human leukocyte antigen (HLA) peptide ligands. To improve the reproducibility of this isolation protocol, Sirois and colleagues at the University of Montreal demonstrate a small-scale bead-based affinity capture workflow, together with anticipated MS results of the recovered immunopeptidome2.

To further improve the stringency of the proteomics data and facilitate high-throughput processing of large numbers of samples, researchers are increasingly turning to robotic platforms to automate the sample processing steps. A low-cost robotic platform is available, though this requires the user to program the desired manipulation steps, which can be a barrier to using this device. Han et al. at the University of Colorado Anschutz Medical Campus have devised a simple open-source coding package and demonstrate the basic steps involved in protein digestion on the Opentrons OT-2 robotic platform3.

Surfactants such as SDS are commonly employed to facilitate cellular extraction and proteome solubilization ahead of MS. However, SDS removal may be incomplete, or otherwise risk sample loss. Nickerson and colleagues at Dalhousie University demonstrate a disposable cartridge to automate the process of protein precipitation4. A combination of salt and organic solvent is critical to maximize protein recovery and can be performed in minimal time at high yields.

Metabolomics is following the footsteps of proteome analysis, with a growing database of reference MS spectra being used to identify unknown metabolites in targeted and untargeted workflows. Similar to the proteomics analysis, spectral identifications are prone to false positive matches, and therefore a statistical reporting of false discovery rate (FDR) is essential to filter low confidence results. Li and colleagues at Jinan University partnered with Chi-Biotech Co. to produce a web-based workflow based on their XY-Meta program and generate a target decoy database of metabolites5. They demonstrate the steps to generate the target database and filter the metabolomic results based on a desired FDR.

Finally, a protocol for single-cell proteome isolation is demonstrated by Petelski and colleagues at Northeastern University6. The Single-Cell ProtEomics (SCoPE2) protocol allows researchers to quantify hundreds to thousands of proteins in a single experiment, using an isobaric carrier to reduce sample loss. The key to the protocol is a rapid thermal cycling step to lyse the cells, as well as efficient tryptic digestion using a larger-than-typical amount of enzyme and isobaric labeling with TMT tags.

Despite decades of experience in proteomics, this maturing field has simply evolved to tackle more challenging problems. The capacity to process a larger number of samples, or smaller quantities of material, with greater consistency and confidence in the data output continues to drive technological innovations. The exchange of ideas related to chemical manipulations, instrumental, and informatics approaches is essential to the growth of this field. One researcher&#8217;s &#8216;problem&#8217; may already have been solved by a simple &#8216;tip or trick&#8217; to overcome the challenge. It is therefore a positive sign that so many unique strategies for proteome analysis are available. For those challenges that remain, it is likely that someone is already working on a possible solution.

tips and tricks for proteome sample preparation

ARTICLES DISCUSSED:
Kovalchuk, S. I., Ziganshin, R., Shelukhina, I. Simple in-house ultra-high performance capillary column manufacturing with the FlashPack approach. Journal of Visualized Experiments. (178), e62522 (2021).
Sirois, I., Isabelle, M., Duquette, J. D., Saab, F., Caron, E. Immunopeptidomics: Isolation of mouse and human MHC Class I- and II-associated peptides for mass spectrometry analysis. Journal of Visualized Experiments. (176), e63052 (2021).
Han, Y., Thomas, C. T., Wennersten, S. A., Lau, E., Lam, M. P. Y. Shotgun proteomics sample processing automated by an open-source lab robot. Journal of Visualized Experiments. (176), e63092 (2021).
Nickerson, J. L. et al. Organic solvent-based protein precipitation for robust proteome purification ahead of mass spectrometry. Journal of Visualized Experiments. (180), e63503 (2022).
Li, D., Liang, J., Zhang, Y., Zhang, G. An integrated workflow of identification and quantification on FDR control-based untargeted metabolome. Journal of Visualized Experiments. doi: 10.3791/63625-v (2022).
Petelski, A. A., Nikolai Slavov, N., Specht, N. Single-cell proteomics preparation for mass spectrometry analysis using freeze-heat lysis and an isobaric carrier. Journal of Visualized Experiments. doi: 10.3791/63802 (2022).

Read this Scientific Article Protocol about Tips And Tricks for Proteome Sample Preparation at JoVE.com