We would like to acknowledge the Fall 2021 NSF I-Corps Program (Northeastern University site) award that has funded this publication.

<ol><li>Symmons, O., Raj, A. <a target="_blank" href="https://pubmed.ncbi.nlm.nih.gov/27259209/">What's luck got to do with it: single cells, multiple fates, and biological nondeterminism.</a> Molecular Cell. 62 (5), 788-802 (2016).</li>
<li>Paul, I., White, C., Turcinovic, I., Emili, A. <a target="_blank" href="https://pubmed.ncbi.nlm.nih.gov/33351222/">Imaging the future: the emerging era of single-cell spatial proteomics.</a> The FEBS Journal. 288 (24), 6990-7001 (2020).</li>
<li>Levy, E., Slavov, N. <a target="_blank" href="https://pubmed.ncbi.nlm.nih.gov/30072488/">Single cell protein analysis for systems biology.</a> Essays in Biochemistry. 62 (4), 595-605 (2018).</li>
<li>Nagasawa, S., Kashima, Y., Suzuki, A., Suzuki, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Single-cell+and+spatial+analyses+of+cancer+cells%3A+toward+elucidating+the+molecular+mechanisms+of+clonal+evolution+and+drug+resistance+acquisition%5BTitle%5D)+AND+%22Inflammation+and+Regeneration%22%5BJournal%5D)">Single-cell and spatial analyses of cancer cells: toward elucidating the molecular mechanisms of clonal evolution and drug resistance acquisition.</a> Inflammation and Regeneration. 41 (1), 22(2021).</li>
<li>Shaffer, S. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Rare+cell+variability+and+drug-induced+reprogramming+as+a+mode+of+cancer+drug+resistance%5BTitle%5D)+AND+%22Nature%22%5BJournal%5D)">Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance.</a> Nature. 555 (7695), 274(2018).</li>
<li>Pan, D., Jia, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Application+of+single-cell+multi-omics+in+dissecting+cancer+cell+plasticity+and+tumor+heterogeneity%5BTitle%5D)+AND+%22Frontiers+in+Molecular+Biosciences%22%5BJournal%5D)">Application of single-cell multi-omics in dissecting cancer cell plasticity and tumor heterogeneity.</a> Frontiers in Molecular Biosciences. 8, 757024(2021).</li>
<li>Segerstolpe, Å, et al. <a target="_blank" href="https://pubmed.ncbi.nlm.nih.gov/27667667/">Single-cell transcriptome profiling of human pancreatic islets in health and type 2 diabetes.</a> Cell Metabolism. 24 (4), 593-607 (2016).</li>
<li>Tritschler, S., Theis, F. J., Lickert, H., Böttcher, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Systematic+single-cell+analysis+provides+new+insights+into+heterogeneity+and+plasticity+of+the+pancreas%5BTitle%5D)+AND+%22Molecular+Metabolism%22%5BJournal%5D)">Systematic single-cell analysis provides new insights into heterogeneity and plasticity of the pancreas.</a> Molecular Metabolism. 6 (9), 974-990 (2017).</li>
<li>Hanna, S. J., Tatovic, D., Thayer, T. C., Dayan, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Insights+from+single+cell+rna+sequencing+into+the+immunology+of+type+1+diabetes-+cell+phenotypes+and+antigen+specificity%5BTitle%5D)+AND+%22Frontiers+in+Immunology%22%5BJournal%5D)">Insights from single cell rna sequencing into the immunology of type 1 diabetes- cell phenotypes and antigen specificity.</a> Frontiers in Immunology. 12, 751701(2021).</li>
<li>Baron, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+single-cell+transcriptomic+map+of+the+human+and+mouse+pancreas+reveals+inter-+and+intra-cell+population+structure%5BTitle%5D)+AND+%22Cell+Systems%22%5BJournal%5D)">A single-cell transcriptomic map of the human and mouse pancreas reveals inter- and intra-cell population structure.</a> Cell Systems. 3 (4), 346-360 (2016).</li>
<li>Franks, A., Airoldi, E., Slavov, N. <a target="_blank" href="https://pubmed.ncbi.nlm.nih.gov/28481885/">Post-transcriptional regulation across human tissues.</a> PLoS Computational Biology. 13 (5), 1005535(2017).</li>
<li>Slavov, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Unpicking+the+proteome+in+single+cells%5BTitle%5D)+AND+%22Science%22%5BJournal%5D)">Unpicking the proteome in single cells.</a> Science. 367 (6477), 512-513 (2020).</li>
<li>Specht, H., Slavov, N. <a target="_blank" href="https://pubmed.ncbi.nlm.nih.gov/29945450/">Transformative opportunities for single-cell proteomics.</a> Journal of Proteome Research. 17 (8), 2565-2571 (2018).</li>
<li>Slavov, N. <a target="_blank" href="https://pubmed.ncbi.nlm.nih.gov/34986167/">Learning from natural variation across the proteomes of single cells.</a> PLoS Biology. , (2021).</li>
<li>Slavov, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Driving+single+cell+proteomics+forward+with+innovation%5BTitle%5D)+AND+%22Journal+of+Proteome+Research%22%5BJournal%5D)">Driving single cell proteomics forward with innovation.</a> Journal of Proteome Research. 20 (11), 4915-4918 (2021).</li>
<li>Specht, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Single-cell+proteomic+and+transcriptomic+analysis+of+macrophage+heterogeneity+using+SCoPE2%5BTitle%5D)+AND+%22Genome+Biology%22%5BJournal%5D)">Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2.</a> Genome Biology. 22 (1), 50(2021).</li>
<li>Petelski, A. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Multiplexed+single-cell+proteomics+using+SCoPE2%5BTitle%5D)+AND+%22Nature+Protocols%22%5BJournal%5D)">Multiplexed single-cell proteomics using SCoPE2.</a> Nature Protocols. 16 (12), 5398-5425 (2021).</li>
<li>Slavov, N. <a target="_blank" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8683604/">Scaling up single-cell proteomics.</a> Molecular and Cellular Proteomics: MCP. 21 (1), 100179(2022).</li>
<li>Cong, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Ultrasensitive+single-cell+proteomics+workflow+identifies%3E+1000+protein+groups+per+mammalian+cell%5BTitle%5D)+AND+%22Chemical+Science%22%5BJournal%5D)">Ultrasensitive single-cell proteomics workflow identifies> 1000 protein groups per mammalian cell.</a> Chemical Science. 12 (3), 1001-1006 (2021).</li>
<li>Lombard-Banek, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((In+vivo+subcellular+mass+spectrometry+enables+proteo-metabolomic+single-cell+systems+biology+in+a+chordate+embryo+developing+to+a+normally+behaving+tadpole+%28X.+laevis%29%5BTitle%5D)+AND+%22Angewandte+Chemie%22%5BJournal%5D)">In vivo subcellular mass spectrometry enables proteo-metabolomic single-cell systems biology in a chordate embryo developing to a normally behaving tadpole (X. laevis).</a> Angewandte Chemie. 60 (23), 12852-12858 (2021).</li>
<li>Specht, H., Slavov, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Optimizing+accuracy+and+depth+of+protein+quantification+in+experiments+using+isobaric+carriers%5BTitle%5D)+AND+%22Journal+of+Proteome+Research%22%5BJournal%5D)">Optimizing accuracy and depth of protein quantification in experiments using isobaric carriers.</a> Journal of Proteome Research. 20 (1), 880-887 (2020).</li>
<li>Budnik, B., Levy, E., Harmange, G., Slavov, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((SCoPE-MS%3A+mass+spectrometry+of+single+mammalian+cells+quantifies+proteome+heterogeneity+during+cell+differentiation%5BTitle%5D)+AND+%22Genome+Biology%22%5BJournal%5D)">SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation.</a> Genome Biology. 19 (1), 161(2018).</li>
<li>Specht, H., Harmange, G., Perlman, D. H., Emmott, E. <a target="_blank" href="https://www.biorxiv.org/content/10.1101/399774v1">Automated sample preparation for high-throughput single-cell proteomics.</a> BioRxiv. , at https://www.biorxiv.org/content/10.1101/399774v1.abstract (2018).</li>
<li>Singh, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Towards+resolving+proteomes+in+single+cells%5BTitle%5D)+AND+%22Nature+Methods%22%5BJournal%5D)">Towards resolving proteomes in single cells.</a> Nature Methods. 18 (8), 856(2021).</li>
<li>Huffman, R. G., Chen, A., Specht, H., Slavov, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((DO-MS%3A+Data-driven+optimization+of+mass+spectrometry+methods%5BTitle%5D)+AND+%22Journal+of+Proteome+Research%22%5BJournal%5D)">DO-MS: Data-driven optimization of mass spectrometry methods.</a> Journal of Proteome Research. 18 (6), 2493-2500 (2019).</li>
<li>Chen, A. T., Franks, A., Slavov, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((DART-ID+increases+single-cell+proteome+coverage%5BTitle%5D)+AND+%22PLoS+Computational+Biology%22%5BJournal%5D)">DART-ID increases single-cell proteome coverage.</a> PLoS Computational Biology. 15 (7), 1007082(2019).</li>
<li>Cheung, T. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Defining+the+carrier+proteome+limit+for+single-cell+proteomics%5BTitle%5D)+AND+%22Nature+Methods%22%5BJournal%5D)">Defining the carrier proteome limit for single-cell proteomics.</a> Nature Methods. 18 (1), 76-83 (2021).</li>
<li>Leduc, A., Huffman, R. G., Slavov, N. <a target="_blank" href="https://www.biorxiv.org/content/10.1101/2021.04.24.441211v4.article-info">Droplet sample preparation for single-cell proteomics applied to the cell cycle.</a> bioRxiv. , https://www.biorxiv.org/content/10.1101/2021.04.24.441211v1.abstract (2021).</li>
<li>Vanderaa, C., Gatto, L. <a target="_blank" href="https://www.tandfonline.com/doi/full/10.1080/14789450.2021.1988571">Utilizing Scp for the analysis and replication of single-cell proteomics data.</a> bioRxiv. , (2021).</li>
</ol>

The authors have no conflicts of interest.

One of the keys to successful preparation and analysis of single cells by SCoPE2 is the preparation of the carrier and reference channels. The suggested carrier size is 100 to 200 cells; however, the number of cells needed for a particular single-cell experiment can be determined based on principles as discussed elsewhere21. For the suggested size, at least ~11,275 cells are needed per 384-well plate, allowing for a 200-cell carrier and 5-cell reference in each set. It can be advantageous to isolate more cells if the desired cell populations are not a limiting factor, to simply have extra material in case of mistakes (as was done in this protocol, isolating 22,000 cells instead of 11,275 cells). The amount of carrier and reference needed for the number of desired plates should be prepared in a single batch to minimize any batch-to-batch variation that can cause peptide identification or quantification to differ between batches.
Before isolating single-cells into wells of a 384-well plate, it is important to consider the design of the plate layout. Within each 384-well plate, it is recommended to implement both positive and negative controls. Negative controls are wells in which no cells are added but undergo the same reagent additions and procedures as the single-cell wells. Positive controls are wells in which cell lysate diluted to 2-5 cells/&#181;L is added instead of single cells. This is particularly important to implement when single-cell isolation methods are not well-validated. Each 384-well plate should ideally have a randomized distribution of single cells and controls (e.g., not have negative or positive controls in just one row). Each plate should have an equal distribution of all cell populations of interest, rather than isolating one cell type in one plate and a second cell type in a second plate. This will avoid tying batch effects with cell types of interest. In addition, if more than one 384-well plate is needed for analysis, it is advisable to isolate cells in a single session, rather than spreading the isolation step over several days, if possible.
Lysis of both single cells and carrier/reference takes place in water through a freeze-heat cycle23. It is anticipated that most proteases have been denatured during this step. Trypsin is then added immediately following the denaturation step at a high concentration, many orders of magnitude greater in concentration than even the most abundant cellular proteases. By mass action, most products of protease activity will be due to trypsin.
Reduction/alkylation of cysteine residues is not performed in this protocol before trypsin digestion. Cysteine-containing peptides represent roughly 10% of tryptic peptides from the human proteome. We observe fewer cysteine-containing peptides using an approach without reduction/alkylation. These steps use reagents that are incompatible with labeling by TMT (NHS-ester chemistry) immediately following digestion.
In this TMT labeling strategy, the carrier and references are labeled with 126 and 127N, respectively, while single-cell and control wells are labeled with 128C through 135N. The two labels after the reference, 127C and 128N, are not used due to isotopic cross contamination arising from the carrier and reference channels, which are clearly much more abundant in peptide material than the single cells. In total, there are 12 TMT channels per set that can be used for labeling single cells or control wells with TMTpro-16plex, or 14 TMT channels per set with TMTpro-18plex.
The critical steps in the protocol to perform single-cell proteomics measurements using this protocol include preparation of the carrier, single-cell isolation, lysis, digestion, barcode labeling, and proper mass spectrometry parameters. These steps have been outlined in this document and have been extensively detailed elsewhere17,21,25. Each step has a corresponding plot or set of plots in DO-MS that allow easy quality control. For example, in the case of successful creation of the carrier, plots depicting the number of peptides identified, the labeling efficiency, and the percentage of miscleavage rate allow verification of its successful preparation. Representative DO-MS reports are included in this publication and can be seen at http://scope2.slavovlab.net/ for the original data16. These DO-MS reports allow for assessing optimization of the method in directions not yet investigated by the authors, such as longer LC gradients, different digestion enzymes, or alternative chemical barcodes.
Currently, the serial analysis of peptides by data-dependent acquisition algorithms limits the number of peptides that can be analyzed in an LC run of a reasonable length. This is in part due to the longer fill times required for the successful acquisition of enough ions for reliable single-cell quantification21. An inherent limitation to using the carrier is the lack of direct assessment of digestion and labeling efficiency of the single cells. Currently, one solution to this limitation is performing quality control on a larger sample processed alongside the single cells.
We proposed a number of opportunities for improving single-cell proteomics, such as building mass spectrometers with multiple analyzers. The current method allows the quantification of thousands of proteins from single mammalian cells at a speed of approximately 100 cells per day with commercially available reagents and equipment. SCoPE2, the second generation of the SCoPE-MS approach, significantly improved upon its predecessor with respect to the number of cells analyzable per unit time, the number of proteins analyzable per unit time, the time needed for sample preparation, the accessibility of reagents and equipment, and the overall cost of preparation and analysis per single cell. Membrane-bound proteins are accessible using the freeze-heat lysis and protease digestion, as shown in comparison to urea lysis23. The method identifies many proteins from the top third of the proteome with respect to abundance16. If the modified proteoform is in the top third of the proteome, and the modified peptide is amenable to mass spectrometry analysis (ionizes well, has a mass difference from unmodified peptide), it will more likely be amenable to this protocol. This method may be fruitfully applied in biological systems where there is meaningful heterogeneity amongst cells, such as in differentiation, senescence, or immunological responses (i.e., phagocytosis).

Single-cell analysis is widely used to study the level of heterogeneity within biological systems that would otherwise be indiscernible by&#160;bulk measurements1,2,3. Such cellular diversity can have functional consequences that can further the understanding of integral biological processes, from cancer cell therapeutic resistance4,5,6 to cell-to-cell heterogeneity in diabetes7,8,9,10. Many investigations have focused on measuring nucleic acids in single cells, by measuring genetic or transcriptomic levels and have enabled the classification of cell types and states. Such progress in the nucleic acid space, however, cannot fill the knowledge gap of post-transcriptional regulation11, driving the need for similarly high-throughput protein measurements in single cells12,13,14,15.
We have developed SCoPE216,17 to address the demand for rigorous and robust single-cell proteomics of mammalian systems. It is a multiplexed method, allowing for increased throughput by labeling and analyzing many cells in parallel18, in contrast to label-free mthods that analyze one cell at at time19,20. The sample preparation methodology, mass spectrometry approach, and subsequent data analysis steps allow for accurate quantification of hundreds to thousands of proteins per single cell. This method makes mass spectrometry analysis of single cells possible through the isobaric carrier21, a small bulk sample of cells (usually 25-200) that is biologically similar to the single-cell population of interest. This carrier material is multiplexed in a set with a reference channel of the same material and single cells through the use of tandem mass tags (TMT labels). The carrier channel reduces sample loss to surface areas and provides the ion backbone fragments for successful peptide identification. The reference channel, which is prepared in bulk and subsequently diluted down to 5-10 cell equivalents for each single-cell set, helps control technical variability in the analysis. Specifically, the reference allows for the normalization of variability caused by LC-MS/MS-related effects, such as ion sampling and ionization efficiencies. Usually, the reference and the carrier channels are made from the same cell population.
This sample preparation protocol is a second-generation method building upon SCoPE-MS22 by multiple synergistic improvements. The improvements include a cell lysis method that avoids sample clean-up, which is a common step of MS proteomics preparations. It uses mPOP (minimal ProteOmic sample Preparation)23, which is a freeze-heat lysis method. This method enabled lysis of single cells in smaller volumes and in multiwell plates rather than in vials, facilitating a higher throughput rate and automation by thermal cyclers. Altogether, this method has lowered the cost per single cell and increased quantitative accuracy as compared to SCoPE-MS16,24.
This protocol describes how to prepare single cells for proteomic analysis, including how to prepare the carrier and reference channels using TMTpro 18-plex isobaric labels. Mammalian cells that are in single-cell suspension and that can be isolated into 384-well plates are likely amenable to this protocol. Also included are representative results of successful single-cell sets, displaying several quality control plots generated by a R Shiny app, DO-MS25. Other published software tools26,27 and experimental guidelines17,21 have improved the adoption of this protocol. We hope this visual guide will further help researchers perform single-cell proteomics experiments.

<table><tbody><tr><td>384-well plate, standard PCR plate</td><td>Thermo Fisher Scientific</td><td>AB1384</td><td>Polypropylene plates should be used, if need to substitute. If substituted, levels of potential polymer contamination from other plates should be assessed prior to SCoPE2 preparation.</td></tr><tr><td>Acetonitrile (for preparation of buffers), Optima LC-MS/MS grade</td><td>Fisher Scientific</td><td>A955-1</td><td>This acetonitrile is used for any buffers, namely the 50% acetonitrile that is used to pass through wells after passing through the carrier and reference when combining SCoPE2 sets.&lt;br/&gt; Caution: Acetonitrile is a flammable liquid. It can irritate skin, eyes, respiratory tract, and central nervous system. Be sure to wear personal protective equipment. Handle under a chemical fume hood.</td></tr><tr><td>Acetonitrile (for preparation of TMT ), anhydrous, 99.8%</td><td>Sigma Aldrich</td><td>271004-100ML</td><td>This acetonitrile is used to resuspend TMT labels at the manufacturer concentration.&lt;br/&gt; Caution: Acetonitrile is a flammable liquid. It can irritate skin, eyes, respiratory tract, and central nervous system. Be sure to wear personal protective equipment. Handle under a chemical fume hood.</td></tr><tr><td>Adhesive PCR plate foils</td><td>Thermo Fisher Scientific</td><td>AB0626</td><td></td></tr><tr><td>Autosampler vial screw thread caps</td><td>Thermo Fisher Scientific</td><td>C5000-51B</td><td></td></tr><tr><td>Autosampler vial spinner (i.e. myFuge 5)</td><td>MTC Bio</td><td>C2595</td><td>This model does not have any speed control. It is simply used to colelct liquid at the bottom of autosampler vials.</td></tr><tr><td>Benzonase nuclease</td><td>Sigma Aldrich</td><td>E1014-25KU</td><td></td></tr><tr><td>Clear glass screw thread vials, 9 mm</td><td>Thermo Fisher Scientific</td><td>60180-509</td><td></td></tr><tr><td>Formic Acid, Pierce, LC-MS/MS grade</td><td>Thermo Fisher Scientific</td><td>85178</td><td>Caution: Formic acid is a flammable liquid. It can cause serious eye damage or skin burns. Be sure to wear personal protective equipment. Handle in a well-ventilated area.</td></tr><tr><td>Glass autosampler inserts, 9 mm</td><td>Thermo Fisher Scientific</td><td>C4010-630</td><td></td></tr><tr><td>Hydroxylamine (HA), 50% wt/vol</td><td>Sigma Aldrich</td><td>467804-50ML</td><td>Caution: Hydroxylamine can cause skin irritation. Be sure to wear personal protective equipment.</td></tr><tr><td>Mantis microfluidic chips, low-volume 3PFE chips</td><td>Formulatrix</td><td>MCLVPR2</td><td>These chips are meant to be used with the Mantis microfluidics liquid handler to dispense organic solutions. These can be used to dispense TMT labels.</td></tr><tr><td>Mantis microfluidic chips, low-volume silicone chips</td><td>Formulatrix</td><td>MCLVS12</td><td>These chips are meant to be used with the Mantis microfluidics liquid handler to dispense aqueous solutions. These cannot be used to dispense TMT labels.</td></tr><tr><td>Mantis microfluidic liquid handler</td><td>Formulatrix</td><td></td><td>Liquid handler can be substituted. However, it is important to check if the system is compatible with 100% acetonitrile (as in the case of TMT labels), and that the system does not introduce polymer contamination or other type of contamination into the samples.</td></tr><tr><td>Mantis PCR plate adapter with wide conical pins for automated plate handling</td><td>Formulatrix</td><td>232400</td><td></td></tr><tr><td>MassPREP peptide mixture</td><td>Waters</td><td>186002337</td><td>Mixture of nine nontryptic peptides</td></tr><tr><td>PCR tube spinner (i.e., 16-place microcentrifuge for 0.2 mL tubes)</td><td>USA Scientific</td><td>2621-0016</td><td>This model does not have any speed control. It is simply used to collect liquid at the bottom of tubes.</td></tr><tr><td>PCR tubes: TempAssure 0.2 mL PCR 8-tube strips</td><td>USA Scientific</td><td>1402-3900</td><td>If substituted, levels of potential polymer contamination from other plates should be assessed prior to SCoPE2 preparation.</td></tr><tr><td>Phosphate-buffered saline (PBS), 10x, pH 7.4, RNase-free</td><td>Thermo Fisher Scientific</td><td>AM9625</td><td></td></tr><tr><td>Plate spinner (i.e., PlateFuge microcentrifuge)</td><td>Benchmark Scientific</td><td>Model C2000</td><td>This model does not have any speed control. It is simply used to collect liquid at the bottom of wells.</td></tr><tr><td>Thermal Cycler (i.e., C1000 Touch with 384-well module)</td><td>Biorad</td><td>1851138</td><td></td></tr><tr><td>TMTpro 16plex Label Reagent Set, 1 x 5 mg</td><td>Thermo Fisher Scientific</td><td>A44520</td><td></td></tr><tr><td>Triethylammonium bicarbonate (TEAB), 1 M, pH 8.5</td><td>Sigma Aldrich</td><td>T7408100ML</td><td></td></tr><tr><td>Trypsin Gold Mass Spectrometry Grade</td><td>Promega</td><td>V5280</td><td>This is trypsin is of very high purity. Other trypsin reagents can vary in their levels of purity. Level of purity is important for achieving positive SCoPE2 results.&lt;br/&gt; &lt;br/&gt; Caution: Trypsin can cause skin, respiratory, and eye irritation. Be sure to wear personal protective equipment. Handle under a chemical fume hood.</td></tr><tr><td>Vortex (Analog vortex mixer)</td><td>VWR</td><td>Model 58816-121</td><td></td></tr><tr><td>Water bath sonicator (i.e., 2.8 L ultrasonic cleaner with digital timer)</td><td>VWR</td><td>97043964</td><td></td></tr><tr><td>Water, Optima LC-MS/MS grade</td><td>Fisher Scientific</td><td>W6-1</td><td>All solutions that need to be diluted or made are recommended to be made with mass-spectrometry grade water. Any dilutions and/or master mixes should be made fresh. Contamination resulting from lower-grade water can negatively affect peptide detection and single-cell data quality .</td></tr></tbody></table>

single-cell proteomics preparation for mass spectrometry analysis using freeze-heat lysis and an isobaric carrier

Single-cell proteomics analysis requires sensitive, quantitatively accurate, widely accessible, and robust methods. To meet these requirements, the Single-Cell ProtEomics (SCoPE2) protocol was developed as a second-generation method for quantifying hundreds to thousands of proteins from limited samples, down to the level of a single cell. Experiments using this method have achieved quantifying over 3,000 proteins across 1,500 single mammalian cells (500-1,000 proteins per cell) in 10 days of mass spectrometer instrument time. SCoPE2 leverages a freeze-heat cycle for cell lysis, obviating the need for clean-up of single cells and consequently reducing sample losses, while expediting sample preparation and simplifying its automation. Additionally, the method uses an isobaric carrier, which aids protein identification and reduces sample losses.
This video protocol provides detailed guidance to enable the adoption of automated single-cell protein analysis using only equipment and reagents that are widely accessible. We demonstrate critical steps in the procedure of preparing single cells for proteomic analysis, from harvesting up to injection to liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Additionally, viewers are guided through the principles of experimental design with the isobaric carrier, quality control for both isobaric carrier and single-cell preparations, and representative results with a discussion of limitations of the approach.

Positive results from the protocol entail verifying that a number of critical steps in the protocol have been successfully performed; these include the preparation of the carrier, single-cell isolation, lysis, digestion, barcode labeling, and MS parameter optimization. DO-MS plots allow the easy assessment of the completion of each critical step in the protocol. A successfully prepared carrier, which usually corresponds to 25 and 200 cells in quantity (per set),&#160;is well-digested and well-labeled. Plots from DO-MS allow quantifying the intensity of the sample (to estimate the quantity), the digestion efficiency (ideally &#60;25% miscleavages), and the labeling efficiency (must be &#62;99%). Most critically, carrier samples that are not completely labeled may permit the cross reaction with the barcodes intended for single cells and add a spurious signal to the quantification of single-cell peptides.
Negative control wells include all experimental reagents but lack a cell. This allows not only background noise to be assessed but also cell isolation efficiency to be determined by providing a representative signal of an empty well. The DO-MS report offers plots to assess the measured signal of the control well alongside the single-cell wells to determine the success of cell isolation and background noise. Additionally, the quality of quantitation can be assessed by using the SCoPE2 pipeline (available on GitHub: github.com/SlavovLab/SCoPE2) or the SCP Bioconductor package29.
Digestion and labeling efficiency of the single cells may not be directly assayed as with the carrier, but DO-MS again provides plots that allow the estimation of the digestion and labeling efficiency. By including a control of 100-200 cells alongside the preparation of the single cells (i.e., receiving all the same reagent additions), the digestion and labeling efficiencies can be assessed for that control, and assumed to be shared by the single cells prepared alongside. Poor digestion will be indicated by a high ratio of the intensity of miscleaved peptides to their completely cleaved counterparts (Figure 1).
Another factor to consider in the sets is the fraction of missing data and the median reporter ion intensity in each TMT channel (Figure 2). When single cells are successfully prepared, the amount of missing data per cell and positive control is much lower than in negative control samples. Likewise, the median intensity of precursors is much higher in single cells and positive controls than for negative controls. The optimization of MS parameters has been discussed extensively elsewhere21, and optimal parameters can be determined using such tools as DO-MS or SCP Companion25,27.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63802/63802fig01.jpg" /> 
Figure 1: Carrier preparation quality control. DO-MS plots depicting (A) labeling efficiency of a successfully prepared carrier at sites of labeling with TMT: the primary amine on the side chain of lysine and the peptide N-terminus, and (B) the digestion efficiency at amino acid residues of tryptic cleavage. Abbreviation: TMT = tandem mass tag. <a href="https://www.jove.com/files/ftp_upload/63802/63802fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/63802/63802fig02.jpg" /> 
Figure 2: Single-cell preparation quality control. DO-MS plots depicting (A) the fraction of missing data in single cells (C5-10), controls (C13,16), carrier (C1), and reference (C2), and (B) the intensity of single cells and controls. Tags 127C, 128N, 131C, 132N, 133N, and 133C, which correspond to C3, C4, C11, C12, and C15, are unused in this particular set. The positive control consists of cellular material processed to peptides in bulk, then diluted to a level of 2-5 cells/&#956;L prior to labeling. The negative control consists of a well subjected to all preparatory steps used for single cells, just without the addition of a single cell. Abbreviation: TMT = tandem mass tag. <a href="https://www.jove.com/files/ftp_upload/63802/63802fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Single-Cell Proteomics Preparation for Mass Spectrometry Analysis Using Freeze-Heat Lysis and an Isobaric Carrier at JoVE.com

Single-Cell Proteomics Preparation for Mass Spectrometry Analysis Using Freeze-Heat Lysis and an Isobaric Carrier

In this protocol, we describe how to prepare mammalian cells for single-cell proteomics analysis via mass spectrometry using commercially available reagents and equipment, with options for both manual and automatic pipetting.

Single-cell proteomics analysis requires sensitive, quantitatively accurate, widely accessible, and robust methods. To meet these requirements, the ...

single-cell-proteomics-preparation-for-mass-spectrometry-analysis

Research

JoVE Journal

Biology

3.8K Views.  Northeastern University. In this protocol, we describe how to prepare mammalian cells for single-cell proteomics analysis via mass spectrometry using commercially available reagents and equipment, with options for both manual and automatic pipetting.

Video: Single-Cell Proteomics Preparation for Mass Spectrometry Analysis Using Freeze-Heat Lysis and an Isobaric Carrier

An Aquatic Microbial Metaproteomics Workflow: From Cells to Tryptic Peptides Suitable for Tandem Mass Spectrometry-based Analysis

Meta-omic technologies such as metagenomics, metatranscriptomics and metaproteomics can aid in the understanding of microbial community structure and metabolism. Although powerful, metagenomics alone can only elucidate functional potential. On the other hand, metaproteomics enables the description of the expressed in situ metabolism and function of a community. Here we describe a protocol for cell lysis, protein and DNA isolation, as well as peptide digestion and extraction from marine microbial cells collected on a cartridge filter unit (such as the Sterivex filter unit) and preserved in an RNA stabilization solution (like RNAlater). In mass spectrometry-based proteomics studies, the identification of peptides and proteins is performed by comparing peptide tandem mass spectra to a database of translated nucleotide sequences. Including the metagenome of a sample in the search database increases the number of peptides and proteins that can be identified from the mass spectra. Hence, in this protocol DNA is isolated from the same filter, which can be used subsequently for metagenomic analysis.

This protocol is for the extraction and concentration of protein and DNA from microbial biomass collected from seawater, followed by the generation of tryptic peptides suitable for tandem mass spectrometry-based proteomic analysis.

Meta-omic technologies such as metagenomics, metatranscriptomics and metaproteomics can aid in the understanding of microbial community structure and ...

Environment

A Simple Fractionated Extraction Method for the Comprehensive Analysis of Metabolites, Lipids, and Proteins from a Single Sample

Understanding of complex biological systems requires the measurement, analysis and integration of multiple compound classes of the living cell, usually determined by transcriptomic, proteomic, metabolomics and lipidomic measurements. In this protocol, we introduce a simple method for the reproducible extraction of metabolites, lipids and proteins from biological tissues using a single aliquot per sample. The extraction method is based on a methyl tert-butyl ether: methanol: water system for liquid: liquid partitioning of hydrophobic and polar metabolites into two immiscible phases along with the precipitation of proteins and other macromolecules as a solid pellet. This method, therefore, provides three different fractions of specific molecular composition, which are fully compatible with common high throughput 'omics' technologies such as liquid chromatography (LC) or gas chromatography (GC) coupled to mass spectrometers. Even though the method was initially developed for the analysis of different plant tissue samples, it has proved to be fully compatible for the extraction and analysis of biological samples from systems as diverse as algae, insects, and mammalian tissues and cell cultures.

A protocol for comprehensive extraction of lipids, metabolites and proteins from biological tissues using one sample is presented.

Understanding of complex biological systems requires the measurement, analysis and integration of multiple compound classes of the living cell, usually ...

Biochemistry

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) coupled to tandem mass spectrometry (LC-MS/MS) and isobaric labeling multiplexing capacity. Here, we introduce a deep-proteomics profiling protocol that combines 10-plex tandem mass tag (TMT) labeling with an extensive LC/LC-MS/MS platform, and post-MS computational interference correction to accurately quantitate whole proteomes. This protocol includes the following main steps: protein extraction and digestion, TMT labeling, 2-dimensional (2D) LC, high-resolution mass spectrometry, and computational data processing. Quality control steps are included for troubleshooting and evaluating experimental variation. More than 10,000 proteins in mammalian samples can be confidently quantitated with this protocol. This protocol can also be applied to the quantitation of post translational modifications with minor changes. This multiplexed, robust method provides a powerful tool for proteomic analysis in a variety of complex samples, including cell culture, animal tissues, and human clinical specimens.

We present a protocol to accurately quantitate proteins with isobaric labelling, extensive fractionation, bioinformatics tools, and quality control steps in combination with liquid chromatography interfaced to a high-resolution mass spectrometer.

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) ...

Carrier-assisted One-pot Sample Preparation for Targeted Proteomics Analysis of Small Numbers of Human Cells

Protein analysis of small numbers of human cells is primarily achieved by targeted proteomics with antibody-based immunoassays, which have inherent limitations (e.g., low multiplex and unavailability of antibodies for new proteins). Mass spectrometry (MS)-based targeted proteomics has emerged as an alternative because it is antibody-free, high multiplex, and has high specificity and quantitation accuracy. Recent advances in MS instrumentation make MS-based targeted proteomics possible for multiplexed quantification of highly abundant proteins in single cells. However, there is a technical challenge for effective processing of single cells with minimal sample loss for MS analysis. To address this issue, we have recently developed a convenient protein carrier-assisted one-pot sample preparation coupled with liquid chromatography (LC) - selected reaction monitoring (SRM) termed cLC-SRM for targeted proteomics analysis of small numbers of human cells. This method capitalizes on using the combined excessive exogenous protein as a carrier and low-volume one-pot processing to greatly reduce surface adsorption losses as well as high-specificity LC-SRM to effectively address the increased dynamic concentration range due to the addition of exogeneous carrier protein. Its utility has been demonstrated by accurate quantification of most moderately abundant proteins in small numbers of cells (e.g., 10-100 cells) and highly abundant proteins in single cells. The easy-to-implement features and no need for specific devices make this method readily accessible to most proteomics laboratories. Herein we have provided a detailed protocol for cLC-SRM analysis of small numbers of human cells including cell sorting, cell lysis and digestion, LC-SRM analysis, and data analysis. Further improvements in detection sensitivity and sample throughput are needed towards targeted single-cell proteomics analysis. We anticipate that cLC-SRM will be broadly applied to biomedical research and systems biology with the potential of facilitating precision medicine.

A protein carrier-assisted one-pot sample preparation coupled with liquid chromatography (LC) - selected reaction monitoring (SRM) termed cLC-SRM is a convenient method for multiplexed targeted proteomics analysis of small numbers of cells, including single cells. It capitalizes on using excessive exogenous protein as a carrier and high-specificity LC-SRM for targeted quantification.

Protein analysis of small numbers of human cells is primarily achieved by targeted proteomics with antibody-based immunoassays, which have inherent ...

Digital Microfluidics for Automated Proteomic Processing

Clinical proteomics has emerged as an important new discipline, promising the discovery of biomarkers that will be useful for early diagnosis and prognosis of disease. While clinical proteomic methods vary widely, a common characteristic is the need for (i) extraction of proteins from extremely heterogeneous fluids (i.e. serum, whole blood, etc.) and (ii) extensive biochemical processing prior to analysis. Here, we report a new digital microfluidics (DMF) based method integrating several processing steps used in clinical proteomics. This includes protein extraction, resolubilization, reduction, alkylation and enzymatic digestion. Digital microfluidics is a microscale fluid-handling technique in which nanoliter-microliter sized droplets are manipulated on an open surface. Droplets are positioned on top of an array of electrodes that are coated by a dielectric layer - when an electrical potential is applied to the droplet, charges accumulate on either side of the dielectric. The charges serve as electrostatic handles that can be used to control droplet position, and by biasing a sequence of electrodes in series, droplets can be made to dispense, move, merge, mix, and split on the surface. Therefore, DMF is a natural fit for carrying rapid, sequential, multistep, miniaturized automated biochemical assays. This represents a significant advance over conventional methods (relying on manual pipetting or robots), and has the potential to be a useful new tool in clinical proteomics.
Mais J. Jebrail, Vivienne N. Luk, and Steve C. C. Shih contributed equally to this work.
Sergio L. S. Freire's current address is at the University of the Sciences in Philadelphia located at 600 South 43rd Street, Philadelphia, PA 19104.

Digital Microfluidics is a technique characterized by the manipulation of discrete droplets (~nL - mL) on an array of electrodes by the application of electrical fields. It is well-suited for carrying out rapid, sequential, miniaturized automated biochemical assays. Here, we report a platform capable of automating several proteomic processing steps.

Clinical proteomics has emerged as an important new discipline, promising the discovery of biomarkers that will be useful for early diagnosis and ...

Cell-Lineage Guided Mass Spectrometry Proteomics in the Developing (Frog) Embryo

Characterization of molecular events as cells give rise to tissues and organs raises a potential to better understand normal development and design efficient remedies for diseases. Technologies enabling accurate identification and quantification of diverse types and large numbers of proteins would provide still missing information on molecular mechanisms orchestrating tissue and organism development in space and time. Here, we present a mass spectrometry-based protocol that enables the measurement of thousands of proteins in identified cell lineages in Xenopus laevis (frog) embryos. The approach builds on reproducible cell-fate maps and established methods to identify, fluorescently label, track, and sample cells and their progeny (clones) from this model of vertebrate development. After collecting cellular contents using microsampling or isolating cells by dissection or fluorescence-activated cell sorting, proteins are extracted and processed for bottom-up proteomic analysis. Liquid chromatography and capillary electrophoresis are used to provide scalable separation for protein detection and quantification with high-resolution mass spectrometry (HRMS). Representative examples are provided for the proteomic characterization of neural-tissue fated cells. Cell-lineage-guided HRMS proteomics is adaptable to different tissues and organisms. It is sufficiently sensitive, specific, and quantitative to peer into the spatio-temporal dynamics of the proteome during vertebrate development.

Cell-Lineage Guided Mass Spectrometry Proteomics in the Developing Frog Embryo

Here we describe a mass spectrometry-based proteomic characterization of cell lineages with known tissue fates in the vertebrate Xenopus laevis embryo.

Characterization of molecular events as cells give rise to tissues and organs raises a potential to better understand normal development and design ...

Chemistry

"Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome

Over the past decade, mass spectrometry-based proteomics has enabled an in-depth characterization of biological systems across a broad array of applications. The cell surface proteome ("surfaceome") in human disease is of significant interest, as plasma membrane proteins are the primary target of most clinically approved therapeutics, as well as a key feature by which to diagnostically distinguish diseased cells from healthy tissues. However, focused characterization of membrane and surface proteins of the cell has remained challenging, primarily due to the complexity of cellular lysates, which mask proteins of interest by other high-abundance proteins. To overcome this technical barrier and accurately define the cell surface proteome of various cell types using mass spectrometry proteomics, it is necessary to enrich the cell lysate for cell surface proteins prior to analysis on the mass spectrometer. This paper presents a detailed workflow for labeling cell surface proteins from cancer cells, enriching these proteins out of the cell lysate, and subsequent sample preparation for mass spectrometry analysis.

Here, we describe a proteomics workflow for characterization of the cell surface proteome of various cell types. This workflow includes cell surface protein enrichment, subsequent sample preparation, analysis using an LC-MS/MS platform, and data processing with specialized software.

Over the past decade, mass spectrometry-based proteomics has enabled an in-depth characterization of biological systems across a broad array of ...

Profiling of Methyltransferases and Other S-adenosyl-L-homocysteine-binding Proteins by Capture Compound Mass Spectrometry (CCMS)

There is a variety of approaches to reduce the complexity of the proteome on the basis of functional small molecule-protein interactions such as affinity chromatography 1 or Activity Based Protein Profiling 2. Trifunctional Capture Compounds (CCs, Figure 1A) 3 are the basis for a generic approach, in which the initial equilibrium-driven interaction between a small molecule probe (the selectivity function, here S-adenosyl-L-homocysteine, SAH, Figure 1A) and target proteins is irreversibly fixed upon photo-crosslinking between an independent photo-activable reactivity function (here a phenylazide) of the CC and the surface of the target proteins. The sorting function (here biotin) serves to isolate the CC - protein conjugates from complex biological mixtures with the help of a solid phase (here streptavidin magnetic beads). Two configurations of the experiments are possible: "off-bead" 4 or the presently described "on-bead" configuration (Figure 1B). The selectivity function may be virtually any small molecule of interest (substrates, inhibitors, drug molecules).
S-Adenosyl-L-methionine (SAM, Figure 1A) is probably, second to ATP, the most widely used cofactor in nature 5, 6. It is used as the major methyl group donor in all living organisms with the chemical reaction being catalyzed by SAM-dependent methyltransferases (MTases), which methylate DNA 7, RNA 8, proteins 9, or small molecules 10. Given the crucial role of methylation reactions in diverse physiological scenarios (gene regulation, epigenetics, metabolism), the profiling of MTases can be expected to become of similar importance in functional proteomics as the profiling of kinases. Analytical tools for their profiling, however, have not been available. We recently introduced a CC with SAH as selectivity group to fill this technological gap (Figure 1A).
SAH, the product of SAM after methyl transfer, is a known general MTase product inhibitor 11. For this reason and because the natural cofactor SAM is used by further enzymes transferring other parts of the cofactor or initiating radical reactions as well as because of its chemical instability 12, SAH is an ideal selectivity function for a CC to target MTases. Here, we report the utility of the SAH-CC and CCMS by profiling MTases and other SAH-binding proteins from the strain DH5&alpha; of Escherichia coli (E. coli), one of the best-characterized prokaryotes, which has served as the preferred model organism in countless biochemical, biological, and biotechnological studies. Photo-activated crosslinking enhances yield and sensitivity of the experiment, and the specificity can be readily tested for in competition experiments using an excess of free SAH.

Profiling of Methyltransferases and Other S-adenosyl-L-homocysteine-binding Proteins by Capture Compound Mass Spectrometry CCMS

Capture Compounds are trifunctional small molecules to reduce the complexity of the proteome by functional reversible small molecule-protein interaction followed by photo-crosslinking and purification. Here we use a Capture Compound with S-adenosyl-L-homocysteine-binding as selectivity function to isolate methyltransferases from an Escherichia coli whole cell lysate and identify them by MS.

There is a variety of approaches to reduce the complexity of the proteome on the basis of functional small molecule-protein interactions such as affinity ...

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

Mass spectrometry (MS)-based proteomics enables comprehensive proteome analysis across a wide range of biological samples, including cells, tissues, and body fluids. Formalin-fixed, paraffin-embedded (FFPE) tissue sections, commonly used for long-term archiving, have emerged as valuable resources for proteomic studies. Beyond their storage benefits, researchers can isolate regions of interest (ROIs) from normal tissue regions through collaborative efforts with pathologists. Despite this potential, a streamlined approach for proteomic experiments encompassing ROI isolation, proteomic sample preparation, and MS analysis remains lacking. In this protocol, an integrated workflow that combines macrodissection of ROIs, suspension trapping-based sample preparation, and high-throughput MS analysis is presented. Through this approach, the ROIs of patients' FFPE tissues, consisting of benign serous cystic neoplasms (SCN) and precancerous intraductal papillary mucinous neoplasms (IPMN) diagnosed by pathologists, were macrodissected, collected, and analyzed, resulting in high proteome coverage. Furthermore, molecular differences between the two distinct pancreatic cystic neoplasms were successfully identified, thus demonstrating the applicability of this approach for advancing proteomic research with FFPE tissues.

Here, we establish a mass spectrometry-based proteomic method using isolated regions of interest in formalin-fixed, paraffin-embedded tissue sections. This protocol is used to analyze proteome from specific tissue areas in archived formalin-fixed, paraffin-embedded tissue sections.

Mass spectrometry (MS)-based proteomics enables comprehensive proteome analysis across a wide range of biological samples, including cells, tissues, and ...

High-throughput and Deep-proteome Profiling by 16-plex Tandem Mass Tag Labeling Coupled with Two-dimensional Chromatography and Mass Spectrometry

Isobaric tandem mass tag (TMT) labeling is widely used in proteomics because of its high multiplexing capacity and deep proteome coverage. Recently, an expanded 16-plex TMT method has been introduced, which further increases the throughput of proteomic studies. In this manuscript, we present an optimized protocol for 16-plex TMT-based deep-proteome profiling, including protein sample preparation, enzymatic digestion, TMT labeling reaction, two-dimensional reverse-phase liquid chromatography (LC/LC) fractionation, tandem mass spectrometry (MS/MS), and computational data processing. The crucial quality control steps and improvements in the process specific for the 16-plex TMT analysis are highlighted. This multiplexed process offers a powerful tool for profiling a variety of complex samples such as cells, tissues, and clinical specimens. More than 10,000 proteins and posttranslational modifications such as phosphorylation, methylation, acetylation, and ubiquitination in highly complex biological samples from up to 16 different samples can be quantified in a single experiment, providing a potent tool for basic and clinical research.

Presented here is an optimized high-throughput protocol developed with 16-plex tandem mass tag reagents, enabling quantitative proteome profiling of biological samples. Extensive basic pH fractionation and high-resolution LC-MS/MS mitigate ratio compression and provide deep proteome coverage.

Isobaric tandem mass tag (TMT) labeling is widely used in proteomics because of its high multiplexing capacity and deep proteome coverage. Recently, an ...