Deep Profiling of Cellular Heterogeneity by Emerging Single‐Cell Proteomic Technologies

The ability to comprehensively profile cellular heterogeneity in functional proteome is crucial in advancing the understanding of cell behavior, organism development, and disease mechanisms. Conventional bulk measurement by averaging the biological responses across a population often loses the information of cellular variations. Single‐cell proteomic technologies are becoming increasingly important to understand and discern cellular heterogeneity. The well‐established methods for single‐cell protein analysis based on flow cytometry and fluorescence microscopy are limited by the low multiplexing ability owing to the spectra overlap of fluorophores for labeling antibodies. Recent advances in mass spectrometry (MS), microchip, and reiterative staining‐based techniques for single‐cell proteomics have enabled the evaluation of cellular heterogeneity with high throughput, increased multiplexity, and improved sensitivity. In this review, the principles, developments, advantages, and limitations of these advanced technologies in analysis of single‐cell proteins, along with their biological applications to study cellular heterogeneity, are described. At last, the remaining challenges, possible strategies, and future opportunities that will facilitate the improvement and broad applications of single‐cell proteomic technologies in cell biology and medical research are discussed.     

Challenges and rewards of interaction proteomics

The recent explosion of high throughput experimental technologies for characterizing protein interactions has generated large amounts of data describing interactions between thousands of proteins and producing genome scale views of protein assemblies. The systems level views afforded by these data hold great promise of leading to new knowledge but also involve many challenges. Deriving meaningful biological conclusions from these views crucially depends on our understanding of the approximation and biases that enter into deriving and interpreting the data. The challenges and rewards of interaction proteomics are reviewed here using as an example the latest comprehensive high throughput analyses of protein interactions in yeast.     

Advances in multiplexed MRM-based protein biomarker quantitation toward clinical utility

Accurate and rapid protein quantitation is essential for screening biomarkers for disease stratification and monitoring, and to validate the hundreds of putative markers in human biofluids, including blood plasma. An analytical method that utilizes stable isotope-labeled standard (SIS) peptides and selected/multiple reaction monitoring-mass spectrometry (SRM/MRM-MS) has emerged as a promising technique for determining protein concentrations. This targeted approach has analytical merit, but its true potential (in terms of sensitivity and multiplexing) has yet to be realized. Described herein is a method that extends the multiplexing ability of the MRM method to enable the quantitation 142 high-to-moderate abundance proteins (from 31 mg/mL to 44 ng/mL) in undepleted and non-enriched human plasma in a single run. The proteins have been reported to be associated to a wide variety of non-communicable diseases (NCDs), from cardiovascular disease (CVD) to diabetes. The concentrations of these proteins in human plasma are inferred from interference-free peptides functioning as molecular surrogates (2 peptides per protein, on average). A revised data analysis strategy, involving the linear regression equation of normal control plasma, has been instituted to enable the facile application to patient samples, as demonstrated in separate nutrigenomics and CVD studies. The exceptional robustness of the LC/MS platform and the quantitative method, as well as its high throughput, makes the assay suitable for application to patient samples for the verification of a condensed or complete protein panel. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.     

Detection and quantification of protein biomarkers from fewer than 10 cells

The use of antibody microarrays continues to grow rapidly due to the recent advances in proteomics and automation and the opportunity this combination creates for high throughput multiplexed analysis of protein biomarkers. However, a primary limitation of this technology is the lack of PCR-like amplification methods for proteins. Therefore, to realize the full potential of array-based protein biomarker screening it is necessary to construct assays that can detect and quantify protein biomarkers with very high sensitivity, in the femtomolar range, and from limited sample quantities. We describe here the construction of ultramicroarrays, combining the advantages of microarraying including multiplexing capabilities, higher throughput, and cost savings with the ability to screen very small sample volumes. Antibody ultramicroarrays for the detection of interleukin-6 and prostate-specific antigen (PSA), a widely used biomarker for prostate cancer screening, were constructed. These ultramicroarrays were found to have a high specificity and sensitivity with detection levels using purified proteins in the attomole range. Using these ultramicroarrays, we were able to detect PSA secreted from 100 LNCaP cells in 3 h and from just four LNCaP cells in 24 h. Cellular PSA could also be detected from the lysate of an average of just six cells. This strategy should enable proteomic analysis of materials that are available in very limited quantities such as those collected by laser capture microdissection, neonatal biopsy microspecimens, and forensic samples.     

Overcoming the dynamic range problem in mass spectrometry-based shotgun proteomics

Protein profiling using mass spectrometry technology has emerged as a powerful method for analyzing large-scale protein-expression patterns in cells and tissues. However, a number of challenges are present in proteomics research, one of the greatest being the high degree of protein complexity and huge dynamic range of proteins expressed in the complex biological mixtures, which exceeds six orders of magnitude in cells and ten orders of magnitude in body fluids. Since many important signaling proteins have low expression levels, methods to detect the low-abundance proteins in a complex sample are required. This review will focus on the fundamental fractionation and mass spectrometry techniques currently used for large-scale shotgun proteomics research.     

Overcoming the dynamic range problem in mass spectrometry-based shotgun proteomics

Protein profiling using mass spectrometry technology has emerged as a powerful method for analyzing large-scale protein-expression patterns in cells and tissues. However, a number of challenges are present in proteomics research, one of the greatest being the high degree of protein complexity and huge dynamic range of proteins expressed in the complex biological mixtures, which exceeds six orders of magnitude in cells and ten orders of magnitude in body fluids. Since many important signaling proteins have low expression levels, methods to detect the low-abundance proteins in a complex sample are required. This review will focus on the fundamental fractionation and mass spectrometry techniques currently used for large-scale shotgun proteomics research.     

Mass spectrometry is only one piece of the puzzle in clinical proteomics.

Biomarker discovery in clinical proteomics is being performed on relatively large patient cohorts by utilizing the high throughput of laser desorption/ionization mass spectrometry (MALDI- and SELDI-TOF-MS). Dealing directly with patient samples as opposed to working in cell or animal systems requires a host of considerations both before and after mass spectrometric analysis to obtain robust biomarker candidates. The challenges associated with the heterogeneity of typical samples are amplified by the ability to detect hundreds to thousands of proteins simultaneously. Adherence to protocols and consistency, however, can ensure optimal results. A study starts necessarily with a relevant clinical question and proceeds to a planning phase where sample availability, statistical test selection, logistics and bias reduction are key points. The physical analysis requires consistency and standardized protocols that are helped significantly through automation. Data analysis is broken into two stages, screening and final testing, which can detect either single candidates or a pattern of proteins. Biomarker identification can be performed at this point and will help significantly in the last stage, interpretation. Replication should be performed in an independent sample set in a separate study. The candidate biomarkers from an initial study give a wealth of information that can help to pinpoint patient subpopulations for a more exhaustive proteomic study using complementary platforms with limited capacity but extremely high information content. A clinical proteomics pilot project can also lead to better selection of model systems by providing a direct link with patient samples.     

Massively Parallel Reporter Assays in Cultured Mammalian Cells

The genetic reporter assay is a well-established and powerful tool for dissecting the relationship between DNA sequences and their gene regulatory activities. The potential throughput of this assay has, however, been limited by the need to individually clone and assay the activity of each sequence on interest using protein fluorescence or enzymatic activity as a proxy for regulatory activity. Advances in high-throughput DNA synthesis and sequencing technologies have recently made it possible to overcome these limitations by multiplexing the construction and interrogation of large libraries of reporter constructs. This protocol describes implementation of a Massively Parallel Reporter Assay (MPRA) that allows direct comparison of hundreds of thousands of putative regulatory sequences in a single cell culture dish.     

Next-generation high-density self-assembling functional protein arrays

We developed a high-density self-assembling protein microarray, based on the nucleic acid programmable protein array (NAPPA) concept, to display thousands of proteins that are produced and captured in situ from immobilized cDNA templates. We arrayed up to 1,000 unique human cDNAs and obtained high yields of protein expression and capture with minimal variation and good reproducibility. This method will enable various experimental approaches to study protein function in high throughput.     

Characterization of large intact protein ions by mass spectrometry: What directions should we follow?

Theoretically, the gas-phase interrogation of whole proteoforms via mass spectrometry, known as top-down proteomics, bypasses the protein inference problem that afflicts peptide-centric proteomic approaches. Despite this obvious advantage, the application of top-down proteomics remains rare, mainly due to limited throughput and difficulty of analyzing proteins >30 kDa. Here we will discuss some of the problems encountered during the characterization of large proteoforms, and guided by a combination of theoretical background and experimental evidence we will describe some innovative data acquisition strategies and novel mass spectrometry technologies that can at least partially overcome such limitations.     

Population Studies of Intact Vitamin D Binding Protein by Affinity Capture ESI-TOF-MS

Blood plasma proteins with molecular weights greater than approximately 30 kDa are refractory to comprehensive, high-throughput qualitative characterization of microheterogeneity across human populations. Analytical techniques for obtaining high mass resolution for targeted, intact protein characterization and, separately, high sample throughput exist, but efficient means of coupling these assay characteristics remain rather limited. This article discusses the impetus for analyzing intact proteins in a targeted manner across populations and describes the methodology required to couple mass spectrometric immunoassay with electrospray ionization mass spectrometry for the purpose of qualitatively characterizing a prototypical large plasma protein, vitamin D binding protein, across populations.     

Protein chips for high-throughput doping screening in athletes

Sport and doping are a contradiction in terms, however, doping abuse in sports has been a serious problem for many years. The systematic screening of every athlete for all prohibited drugs should be an indispensable feature of the Olympic Games. The gas chromatography mass spectrometry method is reserved as a reference method, but is limited by its low throughput. The advent of protein chip technology may enable the screening of all athletes for any illegal use of drugs.     

Determination of binding specificities in highly multiplexed bead-based assays for antibody proteomics

One of the major challenges of antibody-based proteomics is the quality assurance of the generated antibodies to ensure specificity to the target protein. Here we describe a single tube multiplex approach to simultaneously analyze the binding of antibodies to a large number of different antigens. This bead-based assay utilizes the full multiplexing capacity theoretically offered by the Luminex suspension array technology. A protocol for an increased coupling throughput for the immobilization of antigens was developed and used to set up complex and stabile 100-plex bead mixtures. The possibility of using a two-dimensional multiplexing, in terms of high numbers of both analytes and samples or as in this case antigens and antibodies, enables the specificity of 96 antibodies versus 100 different antigens to be determined in 2 h. This high throughput analysis will potentially have great impact on the possibility for the utilization of different antibody proteomics approaches where the quality assessment of antibodies is of the utmost importance.     

In vivo protein complex topologies: sights through a cross-linking lens

Proteins are a remarkable class of molecules that exhibit wide diversity of shapes or topological features that underpin protein interactions and give rise to biological function. In addition to quantitation of abundance levels of proteins in biological systems under a variety of conditions, the field of proteome research has as a primary mission the assignment of function for proteins and if possible, illumination of factors that enable function. For many years, chemical cross-linking methods have been used to provide structural data on single purified proteins and purified protein complexes. However, these methods also offer the alluring possibility to extend capabilities to complex biological samples such as cell lysates or intact living cells where proteins may exhibit native topological features that do not exist in purified form. Recent efforts are beginning to provide glimpses of protein complexes and topologies in cells that suggest continued development will yield novel capabilities to view functional topological features of many proteins and complexes as they exist in cells, tissues, or other complex samples. This review will describe rationale, challenges, and a few success stories along the path of development of cross-linking technologies for measurement of in vivo protein interaction topologies.     

Avidity-based extracellular interaction screening (AVEXIS) for the scalable detection of low-affinity extracellular receptor-ligand interactions

Extracellular protein:protein interactions between secreted or membrane-tethered proteins are critical for both initiating intercellular communication and ensuring cohesion within multicellular organisms. Proteins predicted to form extracellular interactions are encoded by approximately a quarter of human genes, but despite their importance and abundance, the majority of these proteins have no documented binding partner. Primarily, this is due to their biochemical intractability: membrane-embedded proteins are difficult to solubilise in their native conformation and contain structurally-important posttranslational modifications. Also, the interaction affinities between receptor proteins are often characterised by extremely low interaction strengths (half-lives < 1 second) precluding their detection with many commonly-used high throughput methods. Here, we describe an assay, AVEXIS (AVidity-based EXtracellular Interaction Screen) that overcomes these technical challenges enabling the detection of very weak protein interactions (t(1/2) ≤ 0.1 sec) with a low false positive rate. The assay is usually implemented in a high throughput format to enable the systematic screening of many thousands of interactions in a convenient microtitre plate format (Fig. 1). It relies on the production of soluble recombinant protein libraries that contain the ectodomain fragments of cell surface receptors or secreted proteins within which to screen for interactions; therefore, this approach is suitable for type I, type II, GPI-linked cell surface receptors and secreted proteins but not for multipass membrane proteins such as ion channels or transporters. The recombinant protein libraries are produced using a convenient and high-level mammalian expression system, to ensure that important posttranslational modifications such as glycosylation and disulphide bonds are added. Expressed recombinant proteins are secreted into the medium and produced in two forms: a biotinylated bait which can be captured on a streptavidin-coated solid phase suitable for screening, and a pentamerised enzyme-tagged (β-lactamase) prey. The bait and prey proteins are presented to each other in a binary fashion to detect direct interactions between them, similar to a conventional ELISA (Fig. 1). The pentamerisation of the proteins in the prey is achieved through a peptide sequence from the cartilage oligomeric matrix protein (COMP) and increases the local concentration of the ectodomains thereby providing significant avidity gains to enable even very transient interactions to be detected. By normalising the activities of both the bait and prey to predetermined levels prior to screening, we have shown that interactions having monomeric half-lives of 0.1 sec can be detected with low false positive rates.     

Ramanome technology platform for label-free screening and sorting of microbial cell factories at single-cell resolution

Phenotypic profiling of natural, engineered or synthetic cells has increasingly become a bottleneck in the mining and engineering of cell factories. Single-cell phenotyping technologies are highly promising for tackling this hurdle, yet ideally they should allow non-invasive live-cell probing, be label-free, provide landscape-like phenotyping capability, distinguish complex functions, operate with high speed, sufficient throughput and low cost, and finally, couple with cell sorting so as to enable downstream omics analysis. This review focuses on recent progress in Ramanome Technology Platform (RTP), which consists of Raman spectroscopy based phenotyping, sorting and sequencing of single cells, and discuss the key challenges and emerging trends. In addition, we propose ramanome, a collection of single-cell Raman spectra (SCRS) acquired from individual cells within a cellular population or consortium, as a new type of biological phenome datatype at the single-cell resolution. By establishing the phenome-genome links in a label-free, single-cell manner, RTP should find wide applications in functional screening and strain development of live microbial, plant and animal cell factories.     

Trends in mass spectrometry instrumentation for proteomics

Mass spectrometry has become a primary tool for proteomics because of its capabilities for rapid and sensitive protein identification and quantitation. It is now possible to identify thousands of proteins from microgram sample quantities in a single day and to quantify relative protein abundances. However, the need for increased capabilities for proteome measurements is immense and is now driving both new strategies and instrument advances. These developments include those based on integration with multi-dimensional liquid separations and high accuracy mass measurements and promise more than order of magnitude improvements in sensitivity, dynamic range and throughput for proteomic analyses in the near future.     

Proteomics for Protein Expression Profiling in Neuroscience

As the technology of proteomics moves from a theoretical approach to a practical reality, neuroscientists will have to determine the most appropriate applications for this technology. Neuroscientists will have to surmount difficulties particular to their research, such as limited sample amounts, heterogeneous cellular compositions in samples, and the fact that many proteins of interest are rare, hydrophobic proteins. This review examines protein isolation and protein fractionation and separation using two-dimensional electrophoresis (2-DE) and mass spectrometry proteomic methods. Methods for quantifying relative protein expression between samples (e.g., 2-DIGE, and ICAT) are also described. The coverage of the proteome, ability to detect membrane proteins, resource requirements, and quantitative reliability of different approaches is also discussed. Although there are many challenges in proteomic neuroscience, this field promises many rewards in the future.     

Protein identification using top-down

In the last two years, because of advances in protein separation and mass spectrometry, top-down mass spectrometry moved from analyzing single proteins to analyzing complex samples and identifying hundreds and even thousands of proteins. However, computational tools for database search of top-down spectra against protein databases are still in their infancy. We describe MS-Align+, a fast algorithm for top-down protein identification based on spectral alignment that enables searches for unexpected post-translational modifications. We also propose a method for evaluating statistical significance of top-down protein identifications and further benchmark various software tools on two top-down data sets from Saccharomyces cerevisiae and Salmonella typhimurium. We demonstrate that MS-Align+ significantly increases the number of identified spectra as compared with MASCOT and OMSSA on both data sets. Although MS-Align+ and ProSightPC have similar performance on the Salmonella typhimurium data set, MS-Align+ outperforms ProSightPC on the (more complex) Saccharomyces cerevisiae data set.