Development of Mass Spectrometry-Based Shotgun Method for Proteome Analysis of 500 to 5000 Cancer Cells

SpinTip: A Simple, Robust, and Versatile Preanalytical Method for Microscale Suspension Cell Proteomics

Sample loss and contamination are critical preanalytical pitfalls in microscale proteomic applications of nonadhering cells. Common assays and workflows are not easily adoptable to microscale sample sizes of suspension cells due to inadvertent sample loss. This impedes preanalytical experimental manipulation of limited suspension cell samples for microscale proteomics applications, such as encountered for primary human materials. Here, we describe and test a simple manual batch technique for single-step 100-fold concentration of scarce numbers of diluted suspension cells (down to 5000 cells) by volume reduction, facilitating microscale experiments with suspension cells. Pipette tips with heat-sealed orifices (SpinTips) are manufactured within 1 min and serve as versatile microcentrifugation vessels from which supernatant can be aspirated with minimal cell loss. A residual volume of approximately 3 μL can be achieved without visualization of the cell pellet. The results show that SpinTips enable the concentration, medium exchange, washing, and culture of highly limited amounts of suspension cells for functional manipulation and microscale proteomics and are readily incorporated into standard workflows. The application is illustrated by profiling ex vivo responses of primary acute myeloid leukemia (AML) cells from one AML patient to daunorubicin (DNR) to a depth of 3462 quantified proteins with excellent repeatability.

The Intriguing Landscape of Single-Cell Protein Analysis

Profiling protein expression at single-cell resolution is essential for fundamental biological research (such as cell differentiation and tumor microenvironmental examination) and clinical precision medicine where only a limited number of primary cells are permitted. With the recent advances in engineering, chemistry, and biology, single-cell protein analysis methods are developed rapidly, which enable high-throughput and multiplexed protein measurements in thousands of individual cells. In combination with single cell RNA sequencing and mass spectrometry, single-cell multi-omics analysis can simultaneously measure multiple modalities including mRNAs, proteins, and metabolites in single cells, and obtain a more comprehensive exploration of cellular signaling processes, such as DNA modifications, chromatin accessibility, protein abundance, and gene perturbation. Here, the recent progress and applications of single-cell protein analysis technologies in the last decade are summarized. Current limitations, challenges, and possible future directions in this field are also discussed.

The rise of single‐cell proteomics

Mass spectrometry‐based proteomics comprehensively defines proteome expression patterns in thousands of cells majorly contributing to our current understanding of many biological processes. More recently, single‐cell transcriptome and genome studies, however, have demonstrated overwhelming heterogeneity of tissues and cellular subpopulations. These studies have indicated different cellular functionality and identity, which are mainly driven by proteins and their posttranscriptional modifications. The rapidly emerging field of single‐cell proteomics aims at complementing transcriptome and genome data by generating comparative protein expression profiles from individual cells. Recent developments demonstrated tremendous improvements in sample preparation workflows and MS instrumentation, quantifying over 1000 proteins from a single cell. Efficient and reproducible sample processing in conjunction with sensitive MS acquisition strategies will allow to further increase the proteome coverage of tissues with single‐cell resolution. The required throughput and data reliability of such studies are still subject to further developments. Therefore, we herein discuss recent progress on specialized workflows and instrumentation next to advancements outside the field, which we expect to contribute to the development of comprehensive single‐cell proteomics.

MicroPOTS Analysis of Barrett's Esophageal Cell Line Models Identifies Proteomic Changes after Physiologic and Radiation Stress

Moving from macroscale preparative systems in proteomics to micro- and nanotechnologies offers researchers the ability to deeply profile smaller numbers of cells that are more likely to be encountered in clinical settings. Herein a recently developed microscale proteomic method, microdroplet processing in one pot for trace samples (microPOTS), was employed to identify proteomic changes in ∼200 Barrett’s esophageal cells following physiologic and radiation stress exposure. From this small population of cells, microPOTS confidently identified >1500 protein groups, and achieved a high reproducibility with a Pearson’s correlation coefficient value of R > 0.9 and over 50% protein overlap from replicates. A Barrett’s cell line model treated with either lithocholic acid (LCA) or X-ray had 21 (e.g., ASNS, RALY, FAM120A, UBE2M, IDH1, ESD) and 32 (e.g., GLUL, CALU, SH3BGRL3, S100A9, FKBP3, AGR2) overexpressed proteins, respectively, compared to the untreated set. These results demonstrate the ability of microPOTS to routinely identify and quantify differentially expressed proteins from limited numbers of cells.

FACS-Based Proteomics Enables Profiling of Proteins in Rare Cell Populations

Understanding disease pathology often does not require an overall proteomic analysis of clinical samples but rather the analysis of different, often rare, subpopulations of cells in a heterogeneous mixture of cell types. For the isolation of pre-specified cellular subtypes, fluorescence activated cell sorting (FACS) is commonly used for its ability to isolate the required cell populations with high purity, even of scarce cell types. The proteomic analysis of a limited number of FACS-sorted cells, however, is very challenging as both sample preparation inefficiencies and limits in terms of instrument sensitivity are present. In this study, we used CD14+CD15+ immune cells sorted out of peripheral blood mononuclear cells isolated from whole blood to improve and evaluate FACS-based proteomics. To optimize both the protein extraction protocol and the mass spectrometry (MS) data acquisition method, PBMCs as well as commercialized HeLa digest were used. To reflect the limited number of sorted cells in some clinical samples, different numbers of sorted cells (1000, 5000, 10,000, or 50,000) were used. This allowed comparing protein profiles across samples with limited protein material and provided further insights in the benefits and limitations of using a very limited numbers of cells.

Simple Method to Quantify Protein Abundances from 1000 Cells

The rise of single-cell transcriptomics has created an urgent need for similar approaches that use a minimal number of cells to quantify expression levels of proteins. We integrated and optimized multiple recent developments to establish a proteomics workflow to quantify proteins from as few as 1000 mammalian stem cells. The method uses chemical peptide labeling, does not require specific equipment other than cell lysis tools, and quantifies >2500 proteins with high reproducibility. We validated the method by comparing mouse embryonic stem cells and in vitro differentiated motor neurons. We identify differentially expressed proteins with small fold changes and a dynamic range in abundance similar to that of standard methods. Protein abundance measurements obtained with our protocol compared well to corresponding transcript abundance and to measurements using standard inputs. The protocol is also applicable to other systems, such as fluorescence-activated cell sorting (FACS)-purified cells from the tunicate Ciona. Therefore, we offer a straightforward and accurate method to acquire proteomics data from minimal input samples.

Improved Nanoflow RPLC-CZE-MS/MS System with High Peak Capacity and Sensitivity for Nanogram Bottom-up Proteomics

Novel mass spectrometry (MS)-based proteomic tools with extremely high sensitivity and high peak capacity are required for comprehensive characterization of protein molecules in mass-limited samples. We reported a nanoRPLC-CZE-MS/MS system for deep bottom-up proteomics of low micrograms of human cell samples in previous work. In this work, we improved the sensitivity of the nanoRPLC-CZE-MS/MS system drastically via employing bovine serum albumin (BSA)-treated sample vials, improving the nanoRPLC fraction collection procedure, and using a short capillary for fast CZE separation. The improved nanoRPLC-CZE produced a peak capacity of 8500 for peptide separation. The improved system identified 6500 proteins from a MCF7 proteome digest starting with only 500 ng of peptides using a Q-Exactive HF mass spectrometer. The system produced a comparable number of protein identifications (IDs) to our previous system and the two-dimensional (2D) nanoRPLC-MS/MS system developed by Mann's group with 10-fold and 4-fold less sample consumption, respectively. We coupled the single-spot solid phase sample preparation (SP3) method to the improved nanoRPLC-CZE-MS/MS for bottom-up proteomics of 5000 HEK293T cells, resulting in 3689 protein IDs with the consumption of a peptide amount that corresponded to only roughly 1000 cells.

Benchtop-compatible sample processing workflow for proteome profiling of < 100 mammalian cells

Extending proteomics to smaller samples can enable the mapping of protein expression across tissues with high spatial resolution and can reveal sub-group heterogeneity. However, despite the continually improving sensitivity of LC-MS instrumentation, in-depth profiling of samples containing low-nanogram amounts of protein has remained challenging due to analyte losses incurred during preparation and analysis. To address this, we recently developed nanodroplet processing in one pot for trace samples (nanoPOTS), a robotic/microfluidic platform that generates ready-to-analyze peptides from cellular material in ~200 nL droplets with greatly reduced sample losses. In combination with ultrasensitive LC-MS, nanoPOTS has enabled >3000 proteins to be confidently identified from as few as 10 cultured human cells and ~700 proteins from single cells. However, the nanoPOTS platform requires a highly skilled operator and a costly in-house-built robotic nanopipetting instrument. In this work, we sought to evaluate the extent to which the benefits of nanodroplet processing could be preserved when upscaling reagent dispensing volumes by a factor of 10 to those addressable by commercial micropipette. We characterized the resulting platform, termed microdroplet processing in one pot for trace samples (μPOTS), for the analysis of as few as ~25 cultured HeLa cells (4 ng total protein) or 50 μm square mouse liver tissue thin sections and found that ~1800 and ~1200 unique proteins were respectively identified with high reproducibility. The reduced equipment requirements should facilitate broad dissemination of nanoproteomics workflows by obviating the need for a capital-intensive custom liquid handling system.

New mass spectrometry technologies contributing towards comprehensive and high throughput omics analyses of single cells

Mass-spectrometry based omics technologies - namely proteomics, metabolomics and lipidomics - have enabled the molecular level systems biology investigation of organisms in unprecedented detail. There has been increasing interest for gaining a thorough, functional understanding of the biological consequences associated with cellular heterogeneity in a wide variety of research areas such as developmental biology, precision medicine, cancer research and microbiome science. Recent advances in mass spectrometry (MS) instrumentation and sample handling strategies are quickly making comprehensive omics analyses of single cells feasible, but key breakthroughs are still required to push through remaining bottlenecks. In this review, we discuss the challenges faced by single cell MS-based omics analyses and highlight recent technological advances that collectively can contribute to comprehensive and high throughput omics analyses in single cells. We provide a vision of the potential of integrating pioneering technologies such as Structures for Lossless Ion Manipulations (SLIM) for improved sensitivity and resolution, novel peptide identification tactics and standards free metabolomics approaches for future applications in single cell analysis.

Integrated Proteome Analysis Device for Fast Single-Cell Protein Profiling

In our previous work, we have demonstrated an integrated proteome analysis device (iPAD-100) to analyze proteomes from 100 cells. (1) In this work, for the first time, a novel integrated device for single-cell analysis (iPAD-1) was developed to profile proteins in a single cell within 1 h. In the iPAD-1, a selected single cell was directly sucked into a 22 μm i.d. capillary. Then the cell lysis and protein digestion were simultaneously accomplished in the capillary in a 2 nL volume, which could prevent protein loss and excessive dilution. Digestion was accelerated by using elevated temperature with ultrasonication. The whole time of cell treatment was 30 min. After that, single-cell digest peptides were transferred into an LC column directly through a true zero dead volume union, to minimize protein transfer loss. A homemade 22 μm i.d. nano-LC packing column with 3 μm i.d. ESI tip was used in the device to achieve ultrasensitive detection. A 30 min elution program was applied to analysis of the single-cell proteome. Therefore, the total time needed for a single-cell analysis was only 1 h. In an analysis of 10 single HeLa cells, a maximum of 328 proteins were identified in one cell by using an Orbitrap Fusion Tribrid MS instrument, and the detection limit was estimated at around 1.7-170 zmol. Such a sensitivity of the iPAD-1 was ∼120-fold higher than that of our previously developed iPAD-100 system. (1) Prominent cellular heterogeneity in protein expressive profiling was observed. Furthermore, we roughly estimated the phases of the cell cycle of tested HeLa cells by the amount of core histone proteins.

Nanoproteomics comes of age

INTRODUCTION

Nanoproteomics, which is defined as quantitative proteome profiling of small populations of cells (<5000 cells), can reveal critical information related to rare cell populations, hard-to-obtain clinical specimens, and the cellular heterogeneity of pathological tissues. Areas covered: We present a brief review of the recent technological advances in nanoproteomics. These advances include new technologies or approaches covering major areas of proteomics workflow ranging from sample isolation, sample processing, high-resolution separations, to MS instrumentation. Expert commentary: We comment on the current state of nanoproteomics and discuss perspectives on both future technological directions and potential enabling applications.

Nanowell-mediated two-dimensional liquid chromatography enables deep proteome profiling of <1000 mammalian cells

Multidimensional peptide separations can greatly increase the depth of coverage in proteome profiling. However, a major challenge for multidimensional separations is the requirement of large biological samples, often containing milligram amounts of protein. We have developed nanowell-mediated two-dimensional (2D) reversed-phase nanoflow liquid chromatography (LC) separations for in-depth proteome profiling of low-nanogram samples. Peptides are first separated using high-pH LC and the effluent is concatenated into 4 or 12 nanowells. The contents of each nanowell are reconstituted in LC buffer and collected for subsequent separation and analysis by low-pH nanoLC-MS/MS. The nanowell platform minimizes peptide losses to surfaces in offline 2D LC fractionation, enabling >5800 proteins to be confidently identified from just 50 ng of HeLa digest. Furthermore, in combination with a recently developed nanowell-based sample preparation workflow, we demonstrated deep proteome profiling of >6000 protein groups from small populations of cells, including ∼650 HeLa cells and 10 single human pancreatic islet thin sections (∼1000 cells) from a pre-symptomatic type 1 diabetic donor.

Proteomic Analysis of Single Mammalian Cells Enabled by Microfluidic Nanodroplet Sample Preparation and Ultrasensitive NanoLC-MS

We report on the quantitative proteomic analysis of single mammalian cells. Fluorescence-activated cell sorting was employed to deposit cells into a newly developed nanodroplet sample processing chip, after which samples were analyzed by ultrasensitive nanoLC-MS. An average of circa 670 protein groups were confidently identified from single HeLa cells, which is a far greater level of proteome coverage for single cells than has been previously reported. We demonstrate that the single-cell proteomics platform can be used to differentiate cell types from enzyme-dissociated human lung primary cells and identify specific protein markers for epithelial and mesenchymal cells.

Subnanogram proteomics: impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-μm-i.d. columns increase signal intensity by >3-fold relative to those using 75-μm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos MS significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap), leading to a ~3-fold increase in peptide identifications and 1.7-fold increase in identified protein groups for 2 ng tryptic digests of the bacterium S. oneidensis. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~ 95% for 0.5 ng samples and by ~42% for 2 ng samples. Using the best combination of the above variables, we were able to identify >3,000 proteins from 10 ng tryptic digests from both HeLa and THP-1 mammalian cell lines. We also identified >950 proteins from subnanogram archaeal/bacterial cocultures. The present ultrasensitive LC-MS platform achieves a level of proteome coverage not previously realized for ultra-small sample loadings, and is expected to facilitate the analysis of subnanogram samples, including single mammalian cells.

Nanoliter-Scale Oil-Air-Droplet Chip-Based Single Cell Proteomic Analysis

Single cell proteomic analysis provides crucial information on cellular heterogeneity in biological systems. Herein, we describe a nanoliter-scale oil-air-droplet (OAD) chip for achieving multistep complex sample pretreatment and injection for single cell proteomic analysis in the shotgun mode. By using miniaturized stationary droplet microreaction and manipulation techniques, our system allows all sample pretreatment and injection procedures to be performed in a nanoliter-scale droplet with minimum sample loss and a high sample injection efficiency (>99%), thus substantially increasing the analytical sensitivity for single cell samples. We applied the present system in the proteomic analysis of 100 ± 10, 50 ± 5, 10, and 1 HeLa cell(s), and protein IDs of 1360, 612, 192, and 51 were identified, respectively. The OAD chip-based system was further applied in single mouse oocyte analysis, with 355 protein IDs identified at the single oocyte level, which demonstrated its special advantages of high enrichment of sequence coverage, hydrophobic proteins, and enzymatic digestion efficiency over the traditional in-tube system.

Nanodroplet processing platform for deep and quantitative proteome profiling of 10-100 mammalian cells

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues.

There is a great need of developing highly sensitive mass spectrometry-based proteomics analysis for small cell populations. Here, the authors establish a robotically controlled chip-based nanodroplet processing platform and demonstrate its ability to profile the proteome from 10–100 mammalian cells.

Advances in microscale separations towards nanoproteomics applications

Microscale separation (e.g., liquid chromatography or capillary electrophoresis) coupled with mass spectrometry (MS) has become the primary tool for advanced proteomics, an indispensable technology for gaining understanding of complex biological processes. In recent decades significant advances have been achieved in MS-based proteomics. However, the current proteomics platforms still face an analytical challenge in overall sensitivity towards nanoproteomics applications for starting materials of less than 1μg total proteins (e.g., cellular heterogeneity in tissue pathologies). Herein, we review recent advances in microscale separation techniques and integrated sample processing strategies that improve the overall sensitivity and proteome coverage of the proteomics workflow, and their contributions towards nanoproteomics applications.

Optimization and Modeling of Quadrupole Orbitrap Parameters for Sensitive Analysis toward Single-Cell Proteomics

Single-cell proteomics represents a field of extremely sensitive proteomic analysis, owing to the minute amount of yet complex proteins in a single cell. Without amplification potential as of nucleic acids, single-cell mass spectrometry (MS) analysis demands special instrumentation running with optimized parameters to maximize the sensitivity and throughput for comprehensive proteomic discovery. To facilitate such analysis, we here investigated two factors critical to peptide sequencing and protein detection in shotgun proteomics, i.e. precursor ion isolation window (IW) and maximum precursor ion injection time (ITmax), on an ultrahigh-field quadrupole Orbitrap (Q-Exactive HF). Counterintuitive to the frequently used proteomic parameters for bulk samples (>100 ng), our experimental data and subsequent modeling suggested a universally optimal IW of 4.0 Th for sample quantity ranging from 100 ng to 1 ng, and a sample-quantity dependent ITmax of more than 250 ms for 1-ng samples. Compared with the benchmark condition of IW = 2.0 Th and ITmax = 50 ms, our optimization generated up to 300% increase to the detected protein groups for 1-ng samples. The additionally identified proteins allowed deeper penetration of proteome for better revealing crucial cellular functions such as signaling and cell adhesion. We hope this effort can prompt single-cell and trace proteomic analysis and enable a rational selection of MS parameters.

Microproteomics with microfluidic-based cell sorting: Application to 1000 and 100 immune cells

Ultimately, cell biology seeks to define molecular mechanisms underlying cellular functions. However, heterogeneity within cell populations must be considered for optimal assay design and data interpretation. Although single-cell analyses are desirable for addressing this issue, practical considerations, including assay sensitivity, limit their broad application. Therefore, omics studies on small numbers of cells in defined subpopulations represent a viable alternative for elucidating cell functions at the molecular level. MS-based proteomics allows in-depth proteome exploration, although analyses of small numbers of cells have not been pursued due to loss during the multistep procedure involved. Thus, optimization of the proteomics workflow to facilitate the analysis of rare cells would be useful. Here, we report a microproteomics workflow for limited numbers of immune cells using non-damaging, microfluidic chip-based cell sorting and MS-based proteomics. Samples of 1000 or 100 THP-1 cells were sorted, and after enzymatic digestion, peptide mixtures were subjected to nano-LC-MS analysis. We achieved reasonable proteome coverage from as few as 100-sorted cells, and the data obtained from 1000-sorted cells were as comprehensive as those obtained using 1 μg of whole cell lysate. With further refinement, our approach could be useful for studying cell subpopulations or limited samples, such as clinical specimens.

Comparative Evaluation of Small Molecular Additives and Their Effects on Peptide/Protein Identification

Detergents and salts are widely used in lysis buffers to enhance protein extraction from biological samples, facilitating in-depth proteomic analysis. However, these detergents and salt additives must be efficiently removed from the digested samples prior to LC-MS/MS analysis to obtain high-quality mass spectra. Although filter-aided sample preparation (FASP), acetone precipitation (AP), followed by in-solution digestion, and strong cation exchange-based centrifugal proteomic reactors (CPRs) are commonly used for proteomic sample processing, little is known about their efficiencies at removing detergents and salt additives. In this study, we (i) developed an integrative workflow for the quantification of small molecular additives in proteomic samples, developing a multiple reaction monitoring (MRM)-based LC-MS approach for the quantification of six additives (i.e., Tris, urea, CHAPS, SDS, SDC, and Triton X-100) and (ii) systematically evaluated the relationships between the level of additive remaining in samples following sample processing and the number of peptides/proteins identified by mass spectrometry. Although FASP outperformed the other two methods, the results were complementary in terms of peptide/protein identification, as well as the GRAVY index and amino acid distributions. This is the first systematic and quantitative study of the effect of detergents and salt additives on protein identification. This MRM-based approach can be used for an unbiased evaluation of the performance of new sample preparation methods. Data are available via ProteomeXchange under identifier PXD005405.

Palmitic acid is a toll-like receptor 4 ligand that induces human dendritic cell secretion of IL-1β

Palmitic acid (PA) and other saturated fatty acids are known to stimulate pro-inflammatory responses in human immune cells via Toll-like receptor 4 (TLR4). However, the molecular mechanism responsible for fatty acid stimulation of TLR4 remains unknown. Here, we demonstrate that PA functions as a ligand for TLR4 on human monocyte derived dendritic cells (MoDCs). Hydrophobicity protein modeling indicated PA can associate with the hydrophobic binding pocket of TLR4 adaptor protein MD-2. Isothermal titration calorimetry quantified heat absorption that occurred during PA titration into TLR4/MD2, indicating that PA binds to TLR4/MD2. Treatment of human MoDCs with PA resulted in endocytosis of TLR4, further supporting the function of PA as a TLR4 agonist. In addition, PA stimulated DC maturation and activation based on the upregulation of DC costimulatory factors CD86 and CD83. Further experiments showed that PA induced TLR4 dependent secretion of the pro-inflammatory cytokine IL-1β. Lastly, our experimental data show that PA stimulation of NF-κB canonical pathway activation is regulated by TLR4 signaling and that reactive oxygen species may be important in upregulating this pro-inflammatory response. Our experiments demonstrate for the first time that PA activation of TLR4 occurs in response to direct molecular interactions between PA and MD-2. In summary, our findings suggest a likely molecular mechanism for PA induction of pro-inflammatory immune responses in human dendritic cells expressing TLR4.

Tapered-Tip Capillary Electrophoresis Nano-Electrospray Ionization Mass Spectrometry for Ultrasensitive Proteomics: the Mouse Cortex

Ultrasensitive characterization of the proteome raises the potential to understand how differential gene expression orchestrates cell heterogeneity in the brain. Here, we report a microanalytical capillary electrophoresis nano-flow electrospray ionization (CE-nanoESI) interface for mass spectrometry to enable the measurement of limited amounts of proteins in the mouse cortex. Our design integrates a custom-built CE system to a tapered-tip metal emitter in a co-axial sheath-flow configuration. This interface can be constructed in <15 min using readily available components, facilitating broad adaptation. Tapered-tip CE-nanoESI generates stable electrospray by reproducibly anchoring the Taylor cone, minimizes sample dilution in the ion source, and ensures efficient ion generation by sustaining the cone-jet spraying regime. Parallel reaction monitoring provided a 260-zmol lower limit of detection for angiotensin II (156,000 copies). CE was able to resolve a complex mixture of peptides in ~330,000 theoretical plates and identify ~15 amol (~1 pg) of BSA or cytochrome c. Over 30 min of separation, 1 ng protein digest from the mouse cortex yielded 217 nonredundant proteins encompassing a ~3-log-order concentration range using a quadrupole time-of-flight mass spectrometer. Identified proteins included many products from genes that are traditionally used to mark oligodendrocytes, astrocytes, and microglia. Finally, key proteins involved in neurodegenerative disorders were detected (e.g., parkinsonism and spastic paraplegia). CE-nanoESI-HRMS delivers sufficient sensitivity to detect proteins in limited amounts of tissues and cell populations to help understand how gene expression differences maintain cell heterogeneity in the brain. Graphical Abstract ᅟ.

Pathology-Driven Comprehensive Proteomic Profiling of the Prostate Cancer Tumor Microenvironment

Prostate cancer is the second most common cancer in men worldwide. Gleason grading is an important predictor of prostate cancer outcomes and is influential in determining patient treatment options. Clinical decisions based on a Gleason score of 7 are difficult as the prognosis for individuals diagnosed with Gleason 4+3 cancer is much worse than for those diagnosed with Gleason 3+4 cancer. Laser capture microdissection (LCM) is a highly precise method to isolate specific cell populations or discrete microregions from tissues. This report undertook a detailed molecular characterization of the tumor microenvironment in prostate cancer to define the proteome in the epithelial and stromal regions from tumor foci of Gleason grades 3 and 4. Tissue regions of interest were isolated from several Gleason 3+3 and Gleason 4+4 tumors using telepathology to leverage specialized pathology expertise to support LCM. Over 2,000 proteins were identified following liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of all regions of interest. Statistical analysis revealed significant differences in protein expression (>100 proteins) between Gleason 3 and Gleason 4 regions-in both stromal and epithelial compartments. A subset of these proteins has had prior strong association with prostate cancer, thereby providing evidence for the authenticity of the approach. Finally, validation of these proteins by immunohistochemistry has been obtained using an independent cohort of prostate cancer tumor specimens.Implications: This unbiased strategy provides a strong foundation for the development of biomarker protein panels with significant diagnostic and prognostic potential. Mol Cancer Res; 15(3); 281-93. ©2017 AACR.

Quantitative Proteomic Analysis of Mass Limited Tissue Samples for Spatially Resolved Tissue Profiling

Traditionally, proteomic studies have been carried out on whole tissues or organs enabling the profiling of thousands of proteins within a single LC-MS analysis. A disadvantage of this approach is that proteomes generated from whole tissues are an "average" that represents a blend of cell types and distinct anatomical regions which can obscure important biological phenomena. Laser capture microdissection (LCM) is an elegant method that allows tissue features of interest, as small as a single cell, to be identified and isolated for downstream analysis. Herein we describe an approach that utilizes an immobilized enzyme reactor (IMER) coupled directly to nanoLC-MS/MS for highly sensitive, automated, quantitative proteomic analysis of the microscopic tissue specimens generated by LCM.

Development of a stretch-induced neurotrauma model for medium-throughput screening in vitro: identification of rifampicin as a neuroprotectant

BACKGROUND AND PURPOSE

We hypothesized that an in vitro, stretch-based model of neural injury may be useful to identify compounds that decrease the cellular damage in neurotrauma.

EXPERIMENTAL APPROACH

We screened three neural cell lines (B35, RN33B and SH-SY5Y) subjected to two differentiation methods and selected all-trans-retinoic acid-differentiated B35 rat neuroblastoma cells subjected to rapid stretch injury, coupled with a subthreshold concentration of H₂ O₂ , for the screen. The model induced marked alterations in gene expression and proteomic signature of the cells and culminated in delayed cell death (LDH release) and mitochondrial dysfunction [reduced 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) conversion]. Follow-up studies utilized human stem cell-derived neurons subjected to rapid stretch injury.

KEY RESULTS

From screening of a composite library of 3500 drugs, five drugs (when applied in a post-treatment regimen relative to stretch injury) improved both LDH and MTT responses. The effects of rifampicin were investigated in further detail. Rifampicin reduced cell necrosis and apoptosis and improved cellular bioenergetics. In a second model (stretch injury in human stem cell-derived neurons), rifampicin pretreatment attenuated LDH release, protected against the loss of neurite length and maintained neuron-specific class III β-tubulin immunoreactivity.

CONCLUSIONS AND IMPLICATIONS

We conclude that the current model is suitable for medium-throughput screening to identify compounds with neuroprotective potential. Rifampicin, when applied either in pre- or post-treatment, improves the viability of neurons subjected to stretch injury and protects against neurite loss. Rifampicin may be a candidate for repurposing for the therapy of traumatic brain injury.

LINKED ARTICLES

This article is part of a themed section on Inventing New Therapies Without Reinventing the Wheel: The Power of Drug Repurposing. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v175.2/issuetoc.

Single Cell Proteomics Using Frog (Xenopus laevis) Blastomeres Isolated from Early Stage Embryos, Which Form a Geometric Progression in Protein Content

Single cell analysis is required to understand cellular heterogeneity in biological systems. We propose that single cells (blastomeres) isolated from early stage invertebrate, amphibian, or fish embryos are ideal model systems for the development of technologies for single cell analysis. For these embryos, although cell cleavage is not exactly symmetric, the content per blastomere decreases roughly by half with each cell division, creating a geometric progression in cellular content. This progression forms a ladder of single-cell targets for the development of successively higher sensitivity instruments. In this manuscript, we performed bottom-up proteomics on single blastomeres isolated by microdissection from 2-, 4-, 8-, 16-, 32-, and 50-cell Xenopus laevis (African clawed frog) embryos. Over 1 400 protein groups were identified in single-run reversed-phase liquid chromatography-electrospray ionization-tandem mass spectrometry from single balstomeres isolated from a 16-cell embryo. When the mass of yolk-free proteins in single blastomeres decreased from ∼0.8 μg (16-cell embryo) to ∼0.2 μg (50-cell embryo), the number of protein group identifications declined from 1 466 to 644. Around 800 protein groups were quantified across four blastomeres isolated from a 16-cell embryo. By comparing the protein expression among different blastomeres, we observed that the blastomere-to-blastomere heterogeneity in 8-, 16-, 32-, and 50-cell embryos increases with development stage, presumably due to cellular differentiation. These results suggest that comprehensive quantitative proteomics on single blastomeres isolated from these early stage embryos can provide valuable insights into cellular differentiation and organ development.

Simple and Integrated Spintip-Based Technology Applied for Deep Proteome Profiling

Great efforts have been taken for developing high-sensitive mass spectrometry (MS)-based proteomic technologies, among which sample preparation is one of the major focus. Here, a simple and integrated spintip-based proteomics technology (SISPROT) consisting of strong cation exchange beads and C18 disk in one pipet tip was developed. Both proteomics sample preparation steps, including protein preconcentration, reduction, alkylation, and digestion, and reversed phase (RP)-based desalting and high-pH RP-based peptide fractionation can be achieved in a fully integrated manner for the first time. This easy-to-use technology achieved high sensitivity with negligible sample loss. Proteomic analysis of 2000 HEK 293 cells readily identified 1270 proteins within 1.4 h of MS time, while 7826 proteins were identified when 100000 cells were processed and analyzed within only 22 h of MS time. More importantly, the SISPROT can be easily multiplexed on a standard centrifuge with good reproducibility (Pearson correlation coefficient > 0.98) for both single-shot analysis and deep proteome profiling with five-step high-pH RP fractionation. The SISPROT was exemplified by the triplicate analysis of 100000 stem cells from human exfoliated deciduous teeth (SHED). This led to the identification of 9078 proteins containing 3771 annotated membrane proteins, which was the largest proteome data set for dental stem cells reported to date. We expect that the SISPROT will be well suited for deep proteome profiling for fewer than 100000 cells and applied for translational studies where multiplexed technology with good label-free quantification precision is required.

Single-Cell Mass Spectrometry for Discovery Proteomics: Quantifying Translational Cell Heterogeneity in the 16-Cell Frog (Xenopus) Embryo

We advance mass spectrometry from a cell population‐averaging tool to one capable of quantifying the expression of diverse proteins in single embryonic cells. Our instrument combines capillary electrophoresis (CE), electrospray ionization, and a tribrid ultrahigh‐resolution mass spectrometer (HRMS) to enable untargeted (discovery) proteomics with ca. 25 amol lower limit of detection. CE‐μESI‐HRMS enabled the identification of 500–800 nonredundant protein groups by measuring 20 ng, or <0.2% of the total protein content in single blastomeres that were isolated from the 16‐cell frog (Xenopus laevis) embryo, amounting to a total of 1709 protein groups identified between n=3 biological replicates. By quantifying ≈150 nonredundant protein groups between all blastomeres and replicate measurements, we found significant translational cell heterogeneity along multiple axes of the embryo at this very early stage of development when the transcriptional program of the embryo has yet to begin.

Applying multiple proteases to direct digestion of hundred-scale cell samples for proteome analysis

RATIONALE

Analyzing the proteome on the scale of only several hundred cells with mass spectrometry has great significance for applications with limited sample amounts. We applied multiple proteases to the direct digestion of cells and compared the identified proteins both qualitatively and quantitatively.

METHODS

Three hundred cells were directly digested by trypsin, chymotrypsin, or the combination of trypsin and chymotrypsin. The peptides were identified using a LTQ-Orbitrap XL, and data were analyzed using MaxQuant software.

RESULTS

Different proteases produced different identified protein numbers. Trypsin proved to be the best choice for generating the largest protein number, while other proteases complemented the identification results of trypsin by increasing protein sequence coverage. Concerning the quantitative perspective, using trypsin would produce the biggest number of proteins quantifiable by intensity-based absolute quantification (iBAQ).

CONCLUSIONS

When hundred-scale cell samples are analyzed, an optimum choice of proteases should be made to realize different analytical objectives.

Ultrasensitive Proteome Profiling for 100 Living Cells by Direct Cell Injection, Online Digestion and Nano-LC-MS/MS Analysis

Single-cell proteome analysis has always been an exciting goal because it provides crucial information about cellular heterogeneity and dynamic change. Here we presented an integrated proteome analysis device (iPAD) for 100 living cells (iPAD-100) that might be suitable for single-cell analysis. Once cells were cultured, the iPAD-100 could be applied to inject 100 living cells, to transform the living cells into peptides, and to produce protein identification results with total automation. Due to the major obstacle for detection limit of mass spectrometry, we applied the iPAD-100 to analyze the proteome of 100 cells. In total, 813 proteins were identified in a DLD-cell proteome by three duplicate runs. Gene Ontology analysis revealed that proteins from different cellular compartments were well-represented, including membrane proteins. The iPAD-100 greatly simplified the sampling process, reduced sample loss, and prevented contamination. As a result, proteins whose copy numbers were lower than 1000 were identified from 100-cell samples with the iPAD-100, showing that a detection limit of 200 zmol was achieved. With increased sensitivity of mass spectrometry, the iPAD-100 may be able to reveal bountiful proteome information from a single cell in the near future.

Bottom-up proteomic analysis of single HCT 116 colon carcinoma multicellular spheroids

RATIONALE

Proteomic analysis of single multicellular spheroids has not been previously reported. As three-dimensional cell cultures are an increasingly popular model system for biological research, there is interest in obtaining proteomic profiles of these samples. We investigated the proteome of single HCT 116 multicellular spheroids using protocols optimized for small sample sizes.

METHODS

Six biological replicates were analyzed via microscopy for size. Total protein content was assessed via the bicinchoninic acid assay (BCA assay). Five separate biological replicate spheroids were analyzed via mass spectrometry in technical duplicate. An ultra-performance liquid chromatography (UPLC) system coupled with an LTQ Orbitrap Velos was used for peptide separation, analysis, and identification.

RESULTS

The average diameter of six replicate HCT 116 spheroids was 940 ± 30 µm and the average total protein amount was determined to be 39 ± 4 µg. At least 1300 protein groups were identified in each single LC/MS/MS run with 10% of the material from each single spheroid loaded. Database search results showed variation between spheroid protein group identifications. Pearson correlations show that the disparity in identifications is due to random variations in spectra and protocol.

CONCLUSIONS

We detected more than 1350 protein groups in each replicate HCT 116 spheroid. While some variation was detected between replicates, differences in the number of protein groups identified were determined to be the result of random variations in mass spectra acquisition.

Surfactant-aided precipitation/on-pellet-digestion (SOD) procedure provides robust and rapid sample preparation for reproducible, accurate and sensitive LC/MS quantification of therapeutic protein in plasma and tissues

For targeted protein quantification by liquid chromatography mass spectrometry (LC/MS), an optimal approach for efficient, robust and hi-throughput sample preparation is critical, but often remains elusive. Here we describe a straightforward surfactant-aided-precipitation/on-pellet-digestion (SOD) strategy that provides effective sample cleanup and enables high and constant peptide yields in various matrices, allowing reproducible, accurate and sensitive protein quantification. This strategy was developed using quantification of monocolnocal antibody in tissues and plasma as the model system. Surfactant treatment before precipitation substantially increased peptide recovery and reproducibility from plasma/tissue, likely because surfactant permits extensive denaturation/reduction/alkylation of proteins and inactivation of endogenous protease inhibitors, and facilitates removal of matrix components. The subsequent precipitation procedure effectively eliminates the surfactant and nonprotein matrix components, and the thorough denaturation by both surfactant and precipitation enabled very rapid on-pellet-digestion (45 min at 37 °C) with high peptide recovery. The performance of SOD was systematically compared against in-solution-digestion, in-gel-digestion and filter-aided-sample-preparation (FASP) in plasma/tissues, and then examined in a full pharmacokinetic study in rats. SOD achieved the best peptide recovery (∼21.0-700% higher than the other three methods across various matrices), reproducibility (3.75-10.9%) and sensitivity (28-30 ng/g across plasma and tissue matrices), and its performance was independent of matrix types. Finally, in validation and pharmacokinetic studies in rats, SOD outperformed other methods and provided highly accurate and precise quantification in all plasma samples without using stable isotope labeled (SIL)-protein internal standard (I.S.). In summary, the SOD method has proven to be highly robust, efficient and rapid, making it readily adaptable to large-scale clinical and pharmaceutical quantification of biomarkers or biotherapeutics.

An Integrated Platform for Isolation, Processing, and Mass Spectrometry-based Proteomic Profiling of Rare Cells in Whole Blood

Isolation and molecular characterization of rare cells (e.g. circulating tumor and stem cells) within biological fluids and tissues has significant potential in clinical diagnostics and personalized medicine. The present work describes an integrated platform of sample procurement, preparation, and analysis for deep proteomic profiling of rare cells in blood. Microfluidic magnetophoretic isolation of target cells spiked into 1 ml of blood at the level of 1000-2000 cells/ml, followed by focused acoustics-assisted sample preparation has been coupled with one-dimensional PLOT-LC-MS methodology. The resulting zeptomole detection sensitivity enabled identification of ∼4000 proteins with injection of the equivalent of only 100-200 cells per analysis. The characterization of rare cells in limited volumes of physiological fluids is shown by the isolation and quantitative proteomic profiling of first MCF-7 cells spiked into whole blood as a model system and then two CD133+ endothelial progenitor and hematopoietic cells in whole blood from volunteers.

Proteomic challenges: sample preparation techniques for microgram-quantity protein analysis from biological samples

Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed.

Pathway analysis and transcriptomics improve protein identification by shotgun proteomics from samples comprising small number of cells--a benchmarking study

BACKGROUND

Proteomics research is enabled with the high-throughput technologies, but our ability to identify expressed proteome is limited in small samples. The coverage and consistency of proteome expression are critical problems in proteomics. Here, we propose pathway analysis and combination of microproteomics and transcriptomics analyses to improve mass-spectrometry protein identification from small size samples.

RESULTS

Multiple proteomics runs using MCF-7 cell line detected 4,957 expressed proteins. About 80% of expressed proteins were present in MCF-7 transcripts data; highly expressed transcripts are more likely to have expressed proteins. Approximately 1,000 proteins were detected in each run of the small sample proteomics. These proteins were mapped to gene symbols and compared with gene sets representing canonical pathways, more than 4,000 genes were extracted from the enriched gene sets. The identified canonical pathways were largely overlapping between individual runs. Of identified pathways 182 were shared between three individual small sample runs.

CONCLUSIONS

Current technologies enable us to directly detect 10% of expressed proteomes from small sample comprising as few as 50 cells. We used knowledge-based approaches to elucidate the missing proteome that can be verified by targeted proteomics. This knowledge-based approach includes pathway analysis and combination of gene expression and protein expression data for target prioritization. Genes present in both the enriched gene sets (canonical pathways collection) and in small sample proteomics data correspond to approximately 50% of expressed proteomes in larger sample proteomics data. In addition, 90% of targets from canonical pathways were estimated to be expressed. The comparison of proteomics and transcriptomics data, suggests that highly expressed transcripts have high probability of protein expression. However, approximately 10% of expressed proteins could not be matched with the expressed transcripts.

Ultrasensitive proteome analysis using paramagnetic bead technology

In order to obtain a systems-level understanding of a complex biological system, detailed proteome information is essential. Despite great progress in proteomics technologies, thorough interrogation of the proteome from quantity-limited biological samples is hampered by inefficiencies during processing. To address these challenges, here we introduce a novel protocol using paramagnetic beads, termed Single-Pot Solid-Phase-enhanced Sample Preparation (SP3). SP3 provides a rapid and unbiased means of proteomic sample preparation in a single tube that facilitates ultrasensitive analysis by outperforming existing protocols in terms of efficiency, scalability, speed, throughput, and flexibility. To illustrate these benefits, characterization of 1,000 HeLa cells and single Drosophila embryos is used to establish that SP3 provides an enhanced platform for profiling proteomes derived from sub-microgram amounts of material. These data present a first view of developmental stage-specific proteome dynamics in Drosophila at a single-embryo resolution, permitting characterization of inter-individual expression variation. Together, the findings of this work position SP3 as a superior protocol that facilitates exciting new directions in multiple areas of proteomics ranging from developmental biology to clinical applications.

Microbore liquid chromatography ultraviolet detection for quantification of total peptide amount and its application for assessing sample quality in shotgun proteome analysis of hundreds of cells

Mass spectrometric profiling of the proteome of a small number of cells requires not only a sensitive instrument for protein/peptide separation and detection, but also a robust sample preparation protocol to process a very small amount of proteins (<1μg) present in few cells. We have developed and evaluated the performance of a microbore liquid chromatography (LC) UV detection system for quantifying the total amount of peptides in a shotgun proteome analysis workflow that is tailored for the analysis of hundreds of cancer cells. Upon the sample injection into a 1-mm-diameter reversed phase column, a step-gradient was used to first remove salts and other impurities and then elute the peptides quickly without much separation. The UV absorbance of eluted peptides at 214nm was used for peptide quantification with the aid of a calibration curve of a tryptic digest of a mixture of four standard proteins. Two linear calibration regions could be obtained in the peptide amount ranging from 0.03μg to 0.3μg and from 0.6μg to 5μg. The limit of quantification (LOQ) was determined to be 30ng (or 39ng in the linear calibration range). However, the presence of background proteins, mainly keratins, introduced during the sample preparation process was found to be the limiting factor in quantifying a lower amount of peptides from a cell lysate digest. With background absorbance from the digest of contaminant proteins in a solution, the LOQ was found to be 200ng. This nondestructive microbore LC-UV method should be useful in assessing sample quality during the development and applications of an efficient sample preparation method for proteome analysis of a small number of cells. As an example, this method was used for quantifying the peptides generated from breast cancer MCF-7 cell extracts with a limited number of cells: 250, 500 and 1000 cells. Using capillary LC quadrupole time-of-flight mass spectrometry, 81-126, 122-154 and 256-282 proteins could be identified from 250, 500, and 1000 cells, respectively, in duplicate experiments. This method was also applied for the analysis of biological triplicate samples of MCF-7 cells. The average numbers of peptides and proteins detected from the experimental triplicate analyses of biological triplicate samples were 400±71 (9 datasets) and 124±14, respectively, from 250 cells, and 531±44 and 162±16, respectively, from 500 cells.