Easy and Accessible Workflow for Label-Free Single-Cell Proteomics

Single-cell proteomics differentiates Arabidopsis root cell types

Single-cell proteomics (SCP) is an emerging approach to resolve cellular heterogeneity within complex tissues of multi-cellular organisms. Here, we demonstrate the feasibility of SCP on plant samples using the model plant Arabidopsis thaliana. Specifically, we focused on examining isolated single cells from the cortex and endodermis, which are two adjacent root cell types derived from a common stem cell lineage. From 756 root cells, we identified 3763 proteins and 1118 proteins/cell. Ultimately, we focus on 3217 proteins quantified following stringent filtering. Of these, we identified 596 proteins whose expression is enriched in either the cortex or endodermis and are able to differentiate these closely related plant cell types. Collectivity, this study demonstrates that SCP can resolve neighboring cell types with distinct functions, thereby facilitating the identification of biomarkers and candidate proteins to enable functional genomics.

Parallel sample processing for mass spectrometry-based single cell proteomics

BACKGROUND

Single cell mass spectrometry (scMS) has shown great promise for label free proteomics analysis recently. To present single cell samples for proteomics analysis by MS is not a trivial task. Existing methods rely on robotic liquid handlers to scale up sample preparation throughput. The cost associated with specialized equipment hinders the broad adoption of these workflows, and the sequential sample processing nature limits the ultimate throughput.

RESULTS

In this work, we report a parallel sample processing workflow that can simultaneously process 10 single cells without the need of robotic liquid handlers for scMS. This method utilized 3D printed microfluidic devices to form reagent arrays on a glass slide, and a magnetic beads-based streamlined sample processing workflow to present peptides for LC-MS detection. We optimized key operational parameters of the method and demonstrated the quantification consistency among 10 parallel processed samples. Finally, the utility of the method in differentiating cell lines and studying the proteome change induced by drug treatment were demonstrated.

SIGNIFICANCE

The present method allows parallel sample processing for single cells without the need of expensive liquid handlers, which has great potential to further improve throughput and decrease the barrier for single cell proteomics.

Thermal inkjet makes label-free single-cell proteomics accessible and easy

In this study, we adapted an HP D100 Single Cell Dispenser - a novel low-cost thermal inkjet (TIJ) platform with impedance-based single cell detection - for dispensing of individual cells and one-pot sample preparation. We repeatedly achieved label-free identification of up to 1,300 proteins from a single cell in a single run using an Orbitrap Fusion Lumos Mass Spectrometer coupled to either an Acquity UPLC M-class system or a Vanquish Neo UHPLC system. The developed sample processing workflow is highly reproducible, robust, and applicable to standardized 384- and 1536-well microplates, as well as glass LC vials. We demonstrate the applicability of the method for proteomics of single cells from multiple cell lines, mixed cell suspensions, and glioblastoma tumor spheroids. As additional proof of robustness, we monitored the results of genetic manipulations and the expression of engineered proteins in individual cells. Our cost-effective and robust single-cell proteomics workflow can be transferred to other labs interested in studying cells at the individual cell level.

Massively parallel sample preparation for multiplexed single-cell proteomics using nPOP

Single-cell proteomics by mass spectrometry (MS) allows the quantification of proteins with high specificity and sensitivity. To increase its throughput, we developed nano-proteomic sample preparation (nPOP), a method for parallel preparation of thousands of single cells in nanoliter-volume droplets deposited on glass slides. Here, we describe its protocol with emphasis on its flexibility to prepare samples for different multiplexed MS methods. An implementation using the plexDIA MS multiplexing method, which uses non-isobaric mass tags to barcode peptides from different samples for data-independent acquisition, demonstrates accurate quantification of ~3,000-3,700 proteins per human cell. A separate implementation with isobaric mass tags and prioritized data acquisition demonstrates analysis of 1,827 single cells at a rate of >1,000 single cells per day at a depth of 800-1,200 proteins per human cell. The protocol is implemented by using a cell-dispensing and liquid-handling robot-the CellenONE instrument-and uses readily available consumables, which should facilitate broad adoption. nPOP can be applied to all samples that can be processed to a single-cell suspension. It takes 1 or 2 d to prepare >3,000 single cells. We provide metrics and software (the QuantQC R package) for quality control and data exploration. QuantQC supports the robust scaling of nPOP to higher plex reagents for achieving reliable and scalable single-cell proteomics.

Limiting the impact of protein leakage in single-cell proteomics

Limiting artifacts during sample preparation can significantly increase data quality in single-cell proteomics experiments. Towards this goal, we characterize the impact of protein leakage by analyzing thousands of primary single cells that were prepared either fresh immediately after dissociation or cryopreserved and prepared at a later date. We directly identify permeabilized cells and use the data to define a signature for protein leakage. We use this signature to build a classifier for identifying damaged cells that performs accurately across cell types and species.

Multicolumn Nanoflow Liquid Chromatography with Accelerated Offline Gradient Generation for Robust and Sensitive Single-Cell Proteome Profiling

Peptide separations that combine high sensitivity, robustness, peak capacity, and throughput are essential for extending bottom-up proteomics to smaller samples including single cells. To this end, we have developed a multicolumn nanoLC system with offline gradient generation. One binary pump generates gradients in an accelerated fashion to support multiple analytical columns, and a single trap column interfaces with all analytical columns to reduce required maintenance and simplify troubleshooting. A high degree of parallelization is possible, as one sample undergoes separation while the next sample plus its corresponding mobile phase gradient are transferred into the storage loop and a third sample is loaded into a sample loop. Selective offline elution from the trap column into the sample loop prevents salts and hydrophobic species from entering the analytical column, thus greatly enhancing column lifetime and system robustness. With this design, samples can be analyzed as fast as every 20 min at a flow rate of just 40 nL/min with close to 100% MS utilization time and continuously for as long as several months without column replacement. We utilized the system to analyze the proteomes of single cells from a multiple myeloma cell line upon treatment with the immunomodulatory imide drug lenalidomide.

Development of an efficient, effective, and economical technology for proteome analysis

We present an efficient, effective, and economical approach, named E3technology, for proteomics sample preparation. By immobilizing silica microparticles into the polytetrafluoroethylene matrix, we develop a robust membrane medium, which could serve as a reliable platform to generate proteomics-friendly samples in a rapid and low-cost fashion. We benchmark its performance using different formats and demonstrate them with a variety of sample types of varied complexity, quantity, and volume. Our data suggest that E3technology provides proteome-wide identification and quantitation performance equivalent or superior to many existing methods. We further propose an enhanced single-vessel approach, named E4technology, which performs on-filter in-cell digestion with minimal sample loss and high sensitivity, enabling low-input and low-cell proteomics. Lastly, we utilized the above technologies to investigate RNA-binding proteins and profile the intact bacterial cell proteome.

Solid-Phase Microextraction-Aided Capillary Zone Electrophoresis-Mass Spectrometry: Toward Bottom-Up Proteomics of Single Human Cells

Capillary zone electrophoresis-mass spectrometry (CZE-MS) has been recognized as a valuable technique for the proteomics of mass-limited biological samples (i.e., single cells). However, its broad adoption for single cell proteomics (SCP) of human cells has been impeded by the low sample loading capacity of CZE, only allowing us to use less than 5% of the available peptide material for each measurement. Here we present a reversed-phase-based solid-phase microextraction (RP-SPME)-CZE-MS platform to solve the issue, paving the way for SCP of human cells using CZE-MS. The RP-SPME-CZE system was constructed in one fused silica capillary with zero dead volume for connection via in situ synthesis of a frit, followed by packing C8 beads into the capillary to form a roughly 2 mm long SPME section. Peptides captured by SPME were eluted with a buffer containing 30% (v/v) acetonitrile and 50 mM ammonium acetate (pH 6.5), followed by dynamic pH junction-based CZE-MS. The SPME-CZE-MS enabled the injection of nearly 40% of the available peptide sample for each measurement. The system identified 257 ± 24 proteins and 523 ± 69 peptides (N = 2) using a Q-Exactive HF mass spectrometer when only 0.25 ng of a commercial HeLa cell digest was available in the sample vial and 0.1 ng of the sample was injected. The amount of available peptide is equivalent to the protein mass of one HeLa cell. The data indicate that SPME-CZE-MS is ready for SCP of human cells.

AM-DMF-SCP: Integrated Single-Cell Proteomics Analysis on an Active Matrix Digital Microfluidic Chip

Single-cell proteomics offers unparalleled insights into cellular diversity and molecular mechanisms, enabling a deeper understanding of complex biological processes at the individual cell level. Here, we develop an integrated sample processing on an active-matrix digital microfluidic chip for single-cell proteomics (AM-DMF-SCP). Employing the AM-DMF-SCP approach and data-independent acquisition (DIA), we identify an average of 2258 protein groups in single HeLa cells within 15 min of the liquid chromatography gradient. We performed comparative analyses of three tumor cell lines: HeLa, A549, and HepG2, and machine learning was utilized to identify the unique features of these cell lines. Applying the AM-DMF-SCP to characterize the proteomes of a third-generation EGFR inhibitor, ASK120067-resistant cells (67R) and their parental NCI-H1975 cells, we observed a potential correlation between elevated VIM expression and 67R resistance, which is consistent with the findings from bulk sample analyses. These results suggest that AM-DMF-SCP is an automated, robust, and sensitive platform for single-cell proteomics and demonstrate the potential for providing valuable insights into cellular mechanisms.

What's new in single-cell proteomics

In recent years, single-cell proteomics (SCP) has advanced significantly, enabling the analysis of thousands of proteins within single mammalian cells. This progress is driven by advances in experimental design, with maturing label-free and multiplexed methods, optimized sample preparation, and innovations in separation techniques, including ultra-low-flow nanoLC. These factors collectively contribute to improved sensitivity, throughput, and reproducibility. Cutting-edge mass spectrometry platforms and data acquisition approaches continue to play a critical role in enhancing data quality. Furthermore, the exploration of spatial proteomics with single-cell resolution offers significant promise for understanding cellular interactions, giving rise to various phenotypes. SCP has far-reaching applications in cancer research, biomarker discovery, and developmental biology. Here, we provide a critical review of recent advances in the field of SCP.

Open-tubular trap columns: towards simple and robust liquid chromatography separations for single-cell proteomics

Nanoflow liquid chromatography-mass spectrometry is key to enabling in-depth proteome profiling of trace samples, including single cells, but these separations can lack robustness due to the use of narrow-bore columns that are susceptible to clogging. In the case of single-cell proteomics, offline cleanup steps are generally omitted to avoid losses to additional surfaces, and online solid-phase extraction/trap columns frequently provide the only opportunity to remove salts and insoluble debris before the sample is introduced to the analytical column. Trap columns are traditionally short, packed columns used to load and concentrate analytes at flow rates greater than those employed in analytical columns, and since these first encounter the uncleaned sample mixture, trap columns are also susceptible to clogging. We hypothesized that clogging could be avoided by using large-bore porous layer open tubular trap columns (PLOTrap). The low back pressure ensured that the PLOTraps could also serve as the sample loop, thus allowing sample cleanup and injection with a single 6-port valve. We found that PLOTraps could effectively remove debris to avoid column clogging. We also evaluated multiple stationary phases and PLOTrap diameters to optimize performance in terms of peak widths and sample loading capacities. Optimized PLOTraps were compared to conventional packed trap columns operated in forward and backflush modes, and were found to have similar chromatographic performance of backflushed traps while providing improved debris removal for robust analysis of trace samples.

One-Tip enables comprehensive proteome coverage in minimal cells and single zygotes

Mass spectrometry (MS)-based proteomics workflows typically involve complex, multi-step processes, presenting challenges with sample losses, reproducibility, requiring substantial time and financial investments, and specialized skills. Here we introduce One-Tip, a proteomics methodology that seamlessly integrates efficient, one-pot sample preparation with precise, narrow-window data-independent acquisition (nDIA) analysis. One-Tip substantially simplifies sample processing, enabling the reproducible identification of >9000 proteins from ~1000 HeLa cells. The versatility of One-Tip is highlighted by nDIA identification of ~6000 proteins in single cells from early mouse embryos. Additionally, the study incorporates the Uno Single Cell Dispenser™, demonstrating the capability of One-Tip in single-cell proteomics with >3000 proteins identified per HeLa cell. We also extend One-Tip workflow to analysis of extracellular vesicles (EVs) extracted from blood plasma, demonstrating its high sensitivity by identifying >3000 proteins from 16 ng EV preparation. One-Tip expands capabilities of proteomics, offering greater depth and throughput across a range of sample types.

Single-Cell Proteomics Analysis with Tecan Uno and SCREEN Workflow

With advances in sample preparation, small-volume liquid dispensing technologies, high-resolution MS/MS instrumentation, and data acquisition methodologies, it has become increasingly possible to confidently investigate the heterogeneous proteome found within individual cells. In this chapter, we present an automated high-throughput sample preparation workflow based on the Tecan Uno instrument for quantitative single-cell mass spectrometry-based proteomics. Cells are analyzed by the Single-Cell Proteome Analysis platform (SCREEN), which was introduced earlier and provides deeper proteome coverage across single cells.

Efficient and Sensitive Sample Preparation, Separations, and Data Acquisition for Label-Free Single-Cell Proteomics

We describe a sensitive and efficient workflow for label-free single-cell proteomics that spans sample preparation, liquid chromatography separations, and mass spectrometry data acquisition. The Tecan Uno Single Cell Dispenser provides rapid cell isolation and nanoliter-volume reagent dispensing within 384-well PCR plates. A newly developed sample processing workflow achieves cell lysis, protein denaturation, and digestion in 1 h with a single reagent dispensing step. Low-flow liquid chromatography coupled with wide-window data-dependent acquisition results in the quantification of nearly 3000 proteins per cell using an Orbitrap Exploris 480 mass spectrometer. This approach greatly broadens accessibility to sensitive single-cell proteome profiling for nonspecialist laboratories.

Analyzing Posttranslational Modifications in Single Cells

With the rapid expansion of capabilities in the analysis of proteins in single cells, we can now identify multiple classes of protein posttranslational modifications on some of these proteins. Each new technology that has increased the number of proteins measured per cell has likewise increased our ability to identify and quantify modified peptides. In this chapter, I will discuss our current capabilities, concerns, and challenges specific to this emerging field of study and the inevitable demand for services, providing a general review of concepts that should be considered.

A Multiplexed Single-Cell Proteomic Workflow Applicable to Drug Treatment Studies

It is now well accepted that individual cells within a population will respond to treatment of the same drug in a heterogenous manner. Recent advances have allowed, for the first time, the quantitative analysis of the proteomes of single human cells by mass spectrometry. A major focus of many groups, including our own, has been to use this emerging technology to rapidly identify subpopulations of cells with unique drug response and adaptation methods. While the technology in single-cell proteomics today is progressing at a truly staggering rate, we will detail our current methods for applying highly multiplexed single-cell proteomics to drug treatment studies.

Simple Tool for Rapidly Assessing the Quality of Multiplexed Single Cell Proteomics Data

Recent advances in the sensitivity and speed of mass spectrometers coupled with improved sample preparation methods have enabled the field of single cell proteomics to proliferate. While heavy development is occurring in the label free space, dramatic improvements in throughput are provided by multiplexing with tandem mass tags. Hundreds or thousands of single cells can be analyzed with this method, yielding large data sets which may contain poor data arising from loss of material during cell sorting or poor digestion, labeling, and lysis. To date, no tools have been described that can assess data quality prior to data processing. We present herein a lightweight python script and accompanying graphic user interface that can rapidly quantify reporter ion peaks within each MS/MS spectrum in a file. With simple summary reports, we can identify single cell samples that fail to pass a set quality threshold, thus reducing analysis time waste. In addition, this tool, Diagnostic Ion Data Analysis Reduction (DIDAR), will create reduced MGF files containing only spectra possessing a user-specified number of single cell reporter ions. By reducing the number of spectra that have excessive zero values, we can speed up sample processing with little loss in data completeness as these spectra are removed in later stages in data processing workflows. DIDAR and the DIDAR GUI are compatible with all modern operating systems and are available at: https://github.com/orsburn/DIDARSCPQC. All files described in this study are available at www.massive.ucsd.edu as accession MSV000088887.

An Automated Nanowell-Array Workflow for Quantitative Multiplexed Single-Cell Proteomics Sample Preparation at High Sensitivity

Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lags. Here, we introduce the proteoCHIP, a universal option for single-cell proteomics sample preparation including multiplexed labeling up to 16-plex with high sensitivity and throughput. The automated processing using a commercial system combining single-cell isolation and picoliter dispensing, the cellenONE, reduces final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error-prone manual sample handling and overcoming evaporation. The specialized proteoCHIP design allows direct injection of single cells via a standard autosampler resulting in around 1500 protein groups per TMT10-plex with reduced or eliminated need for a carrier proteome. We evaluated the effect of wider precursor isolation windows at single-cell input levels and found that using 2 Da isolation windows increased overall sensitivity without significantly impacting interference. Using the dedicated mass spectrometry acquisition strategies detailed here, we identified on average close to 2000 proteins per TMT10-plex across 170 multiplexed single cells that readily distinguished human cell types. Overall, our workflow combines highly efficient sample preparation, chromatographic and ion mobility-based filtering, rapid wide-window data-dependent acquisition analysis, and intelligent data analysis for optimal multiplexed single-cell proteomics. This versatile and automated proteoCHIP-based sample preparation approach is sufficiently sensitive to drive biological applications of single-cell proteomics and can be readily adopted by proteomics laboratories.