Single-cell analysis for proteome and related researches

Trends in Analytical Chemistry 120 (2019) 115666

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Single-cell analysis for proteome and related researches Xi Shao, Lingxiao Weng, Mingxia Gao, Xiangmin Zhang* Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai 200438, China

a r t i c l e i n f o

a b s t r a c t

Article history: Available online 17 September 2019

Single-cell proteome analysis is essential to cellular heterogeneity research. Because single cell is too small to analyze, conventional proteome analytical methods are not applicative to single-cell proteome analysis. Therefore, it is urgent to develop single-cell proteome analytical methods. Although it is a great challenge, many advances have been achieved in recent years. In label based methods, around 50 target proteins from single cells can be simultaneously analyzed with high throughput. In MS (non-label) based methods, over 200 proteins from single somatic cells can be identified by ultra-sensitive nanoLC-MS/MS. It has broken through the bottle-neck of protein number of label based methods, and made whole proteome analysis of single somatic cells promising. Herein, we have reviewed recent published methods of single-cell proteome analysis, and given a guidance of method selection for applications. Finally, we have offered our opinions for developing single-cell proteome analytical methods in the future. © 2019 Elsevier B.V. All rights reserved.

Keywords: Single-cell analysis Proteome Cellular heterogeneity Fluorescence analysis nanoLC-MS/MS

1. Introduction Single-cell studies are very important. There are no two cells identical in proteome and other omics. It will result in many differences in biological functionality of individual cells. Single-cell analysis is the only way to understand cellular heterogeneity [1,2]. Besides, single-cell analysis can realize analysis of rare cells [3]. Many scientists have devoted themselves to the research of single-cell analysis. Although analyzing single cell is still a great challenge nowadays, it is inspiring to see that great advances in single-cell analysis have been achieved in recent years [3e7]. A major part of single-cell analysis is about the study of singlecell omics, including single-cell genome [6], transcriptome [4], proteome [3], metabolome [7], epigenome [5] analysis and so on. Before driving into details, it is worthy to note that qualitative and quantitative information of one kind of component in cells is usually not highly correlated with another kind of component [8,9]. For example, Xie et al. demonstrated that the protein and mRNA copy numbers for any given gene in single Escherichia coli cell are uncorrelated [8]. So, to depict full picture of single cells, each branch of single-cell omics should be analyzed respectively. Until now, single-cell genome and transcriptome analysis is mature due to the great technological development of single-cell DNA/RNA sequencing [6,10,11]. However, because peptides,

* Corresponding author. E-mail address: [email protected] (X. Zhang). https://doi.org/10.1016/j.trac.2019.115666 0165-9936/© 2019 Elsevier B.V. All rights reserved.

proteins and metabolites cannot be amplified like genes [12], single-cell proteome and other omics studies are far from maturity in technological investigations. Proteins offer a direct view into the function of cells [13]. It is important and meaningful to learn cellular heterogeneity among cells at proteome level. However, single-cell proteome analysis faces many difficulties. Take somatic cells for instance, size of most somatic cells are 10e20 mm in diameter [14]; amount of proteins are ~0.1 ng [15]; protein species are more than 10000 [14]. Common methods cannot analyze such a small and complicated sample. Many scientists have paid great efforts to developing new methods for single-cell proteome analysis. A serial of work have been conducted in recent years [16e28]. In this review, we summarized and discussed those novel and representative methods of single-cell proteome analysis. Also, applications of those methods were mentioned. Finally, a guidance for method selection was offered for single-cell proteome analysis.

2. A general view of single-cell proteome analytical methods Label based and MS (non-label) based detection are two main approaches in single-cell proteome analysis. In label based singlecell proteome analysis, target proteins are analyzed. By the use of antibodies, target proteins in single cells are bound with fluorescent, metal or other labels. Via fluorescence analysis or MS analysis, the information of target proteins is unraveled by detection of

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labels. The methods can be categorized into: 1. labeling and fluorescence analysis; 2. labeling plus separation and fluorescence analysis; 3. labeling and MS analysis. In MS (non-label) based single-cell proteome analysis, tandem MS is used to detect all peptides or proteins. Labels are not needed in the analysis. Peptides or proteins are identified through m/z and intensity of MS peaks in MS1 and MSn. Furthermore, it can be categorized into: 1. direct MS analysis; 2. separation and MS analysis. In the following, we introduced recent published representative methods according to the category. 3. Label based single-cell proteome analysis In many situations, only a few target proteins rather than whole proteome were needed to analyze in single cells. Because the advantage of high throughput and low detection limit, label based methods became the first choice for target proteins analysis in single cells. Enhancing ability of multiplex proteins analysis in single cells was the main development direction of label based methods [3,22].

fluorescence of cells (~1000 MESF/cell [39], molecules of equivalent soluble fluorochrome). Nowadays, sensitivity of high-end commercial FFC has reached 100 MESF [38]. In the above three mentioned typical methods (immunofluorescence microscopy, gene engineering technology and FFC), identified proteins from each single cell was limited by detection channels of fluorescence. Emission bands of fluorescent dyes were quite wide. Although the detection channel could be increased by adding lasers of different wavelengths, the maximal number of detection channel was below 20 [40,41]. Furthermore, the more detection channels used, the more complicated of data analysis and more errors would occur [42,43]. Consequently, usually only one or several proteins could be simultaneously analyzed by above three methods in most cases [38]. Years ago, when MS was not as powerful as today, Edman degradation was an available method to proteins sequencing [3]. Recently, through fluorescently labeling aimed amino acids and imaging the decrease of fluorescence during rounds of Edman degradation, Marcotte group accomplished highly parallel singlemolecule identification of proteins in zeptomole-scale mixtures (Fig. 2) [44,45]. Low abundant proteins in single cells could be identified in the work.

3.1. Labeling and fluorescence analysis 3.2. Labeling plus separation and fluorescence analysis Fluorescence analysis had an ultra-high sensitivity and resolution. With the development of florescent dyes and super-resolution microscopes, single biomolecule detection in living cells was available nowadays [29]. Such a good sensitivity was enough for single-cell proteome analysis. Therefore, many labeling and fluorescence analysis methods were developed for single-cell proteome analysis. The general process of the method was to bind target proteins in single cells with fluorescent labels first, and then detected target proteins by observing the fluorescence. Antibody fluorescent labels could quickly bind with target proteins in single cells by use of antigen-antibody reaction. In the project of Cell Atlas within Human Protein Atlas, scientists used as many as 13993 antibodies and immunofluorescence microscopy to locate subcellular distribution of 12003 proteins in human cells (Fig. 1) [30]. Besides subcellular localization of proteins, this work also demonstrated that the label-fluorescence based methods could realize analysis of most proteins (from low abundant to high abundant) in single cells. By use of gene engineering technology, fluorescent proteins [31] could be co-expressed with proteins translated from target genes. Fluorescence emitted by the fluorescent protein represented distribution of target proteins in cells, with no need of antibody [32]. This method could reveal whether the target gene expressed or not in single cells. More importantly, it could show the distribution of target proteins and realize dynamic monitoring of proteins in single cells. Hence, it was usually applied to discover related biological functions of target genes and proteins [33e37]. As cell culture was required in gene editing, the method could not directly analyze given samples, which limited its applications [21]. Fluorescence flow cytometry (FFC) was a widely used technique for high-throughput single-cell proteome analysis, which could reach more than 30000 cell/s [38]. Common process of FFC was to firstly label cells with antibody fluorescent labels. Then labeled cells were put in FFC. When labeled cells flowed through the detection window of FFC one by one, laser(s) in the FFC would excite fluorophores of fluorescent antibodies in each cell, and information of fluorescence of each cell was recorded. In addition, fluorescenceactivated cell sorting (FACS) was an expansion of FFC, which could collect target cells from whole cells sample after fluorescence detection. FFC could not realize single molecule detection, because the sensitivity of FFC was controlled by the spontaneous

By adding protein separation between labeling and fluorescence analysis, limitation in detection channel could be eliminated and higher multiplex proteins profiling could be obtained. Electrophoresis has been applied for protein separation. Schaffer and Herr group developed single-cell western blotting (scWestern) [46,47]. In scWestern, single cells were captured in microwells array on a slide. Each cell was lysed in a microwell. After lysis, shortseparation-distance PA gel electrophoresis (PAGE) and protein immobilization in situ were conducted. Primary and fluorescently labeled secondary antibody probes were used to detect proteins in the gel. Detecting threshold of scWestern was ~27000 molecules. Maximal 11 target proteins could be analyzed by chemical stripping and reprobing. The throughput was medium. Thousands of single cells could be analyzed simultaneously due to the use of microwells array. Single-cell differentiation of rat neural stem cells and responses to mitogen stimulation were learned by scWestern. The geometry of microwells was further investigated to improve the performance of single-cell protein PAGE [48]. Because different proteins labeled with the same antibody might be separated by PAGE, the impact of antibody cross-reactivity could be effectively reduced [47]. Comparing with FFC, the specificity and quantification ability of scWestern was better. Similarly, Herr group developed single-cell resolution isoelectric focusing (scIEF) by microfluidic design and photoactivatable materials (benzophenone methacrylamide) for single-cell (glioblastoma cells) proteome analysis [49]. Its detection limit was 42000 molecules. Liu group developed single-cell chemical proteomics (SCCP) to profile low abundant proteins in single cells [50,51]. An activitybased trimodular probe (ABP) was used to label target proteins in single cells. For each analysis, a single cell was injected into the system of capillary electrophoresis-laser induced fluorescence (CE-LIF) for cell lysis, protein separation and detection. Membrane protein GB1 and cysteine cathepsin family protein were analyzed respectively. The detection limit was as low as 500 molecules. Allbritton group used single-cell capillary electrophoresis to evaluate oncogenic kinase activity in single PANC-1 cells [52]. Guan group realized analysis of human transmembrane protein (Her2) in single Hela cells by a capillary electroosmotic driven (EOD)-LIF system [53]. The detection limit reached 165 molecules.

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Fig. 2. Scheme of single-molecule fluorosequencing. A) Workflow of protein and peptide analysis by single-molecule fluorosequencing. B) Scheme of repeated cycles of Edman degradation. Positions of fluorescent dyes within each molecule were revealed by imaging. C) Coverage of human proteins through the use of two label types. Proteins were identified by an amino acid labeling scheme. Each curve plot showed the relationship between the number of Edman cycles and the coverage of the uniquely identifiable proteins. Reprinted with permission from Ref. [44].

Due to the use of capillary electrophoresis, cells could only be treated and analyzed one by one. The analyzing speed was around 10 cells per hour in maximal. The throughput was low. Also, it was a pity that they did not identify multiple target proteins in those reports [50e53].

Protein separation could be conducted not only by electrophoresis or chromatography, but also by different spatial antigenantibody reaction. Heath group developed a method called single-cell barcode chip (SCBC) [54,55]. In SCBC, antibody labels were immobilized on the chip by DNA-encoded antibody library

Fig. 1. Subcellular locations of Cell Atlas. A) Schematic of a cell. Proteomes of secreted proteins and 13 subcellular locations (30 subcellular structures) were defined in the Cell Atlas. B) Fluorescence images of subcellular structure represented in the Cell Atlas by immunofluorescence microscopy. Proteins in aimed subcellular structures were marked in green. Microtubules and nucleus were marked in red and blue, respectively. The size of each image is 64 mm. Reprinted with permission from Ref. [30].

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(DEAL) method to form a spatially encoded antibody barcode. Different antibodies were in different barcode strips. Each cell was restricted in a microchamber on the chip, and each microchamber had a complete barcode. Target intracellular proteins (requiring cell lysis) or secreted proteins were captured on the barcode. Finally, fluorescently labeled secondary antibody probes were used for protein detection on the barcode. One of the highlights of SCBC was that it can analyze secreted proteins of single cells after incubating cells in the microchamber in suitable environment for hours. The throughput of SCBC depended on the number of microchambers on the chip, which could be thousands per experiment. As few as 100e1000 molecules of proteins could be detected by SCBC. Jensena and Fan group further developed the SCBC to realize codetection of 42 immune effector proteins secreted from single cells, and demonstrated that a large degree of intrinsic heterogeneity still existed among the phenotypically similar cell populations [56]. In this version of SCBC, there were spectral encoding (three colors) and spatial encoding (15 bars). So, more multiplexing (42 proteins and 3 controls) single-cell proteins assay could be achieved. Nevertheless, in SCBC, species of antibodies were unchangeable after fabrication of barcode, which restricted its flexibility in application. 3.3. Labeling and MS analysis Compared with florescence analysis, MS had a much larger amount of detection channels, which significantly increased the multiplex of protein analysis. Also, MS had high resolution, thus could completely distinguish various elements. In MS analysis, there was no interference between channels, and no need to calculate compensation. The experimental processes were simplified, and the consumption of samples and reagents were saved [57]. Tanner's group developed mass cytometry for the first time by combination of flow cytometry with MS [57]. Device of the mass cytometry was named as cyTOF. The principle of the mass cytometry was using stable precious metal or rare earth metal-labeled specific antibodies to label target proteins in cells. Labeled cells were injected into inductively coupled plasma mass spectrometry (ICP-MS) one by one with the help of flow cytometry. Cells were burned in the plasma torch of ICP-MS, and metal elements of the antibody labels were ionized and sent into mass spectrometry for detection. Qualitative and quantitative information of metal elements represented the information of target proteins [58]. All metal elements used for labeling were extremely rare in human body. Therefore, the background was very low and the sensitivity was quite high (~350 molecules/cell). The throughput of cyTOF could reach 2000 cells/s, which depended on the speed of ICP-MS [57]. Because there were many detection channels in MS, the number of detected proteins has increased. However, species of metal elements, and the cross-reactivity of antibodies still restricted the number of proteins identified in mass cytometry to below 50. Mass cytometry was a widely used technique in single-cell proteome analysis. Except for secreted proteins, membrane proteins and intracellular proteins could be identified. Many research fields of single-cell analysis such as biomarker screening, immunophenotyping, infectious disease/microbiology, inherited disease, oncology, stem cell and so on were learned by mass cytometry [58e62]. It should be noticed that mass cytometry could not only detect proteins, but also detect mRNAs. Nolan and Gherardini group developed PLAYR (proximity ligation assay for RNA) to simultaneous quantification of more than 40 different mRNAs and proteins by cyTOF [63]. Secondary ion mass spectrometry (SIMS) has been used to image the isotopic composition of samples. Nolan group developed a method that utilized antibodies labeled with isotopically pure

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elemental metal reporters, SIMS and multiplexed ion beam imaging (MIBI) to analyze distribution of ten markers (target proteins) in tissue sections [64]. Over a five-log dynamic range and parts-perbillion sensitivity could be realized. Also, Diederichsen and Rizzoli group developed a method called specific protein isotopic and fluorescence labeling (SPILL) to image proteins in single cells by SIMS [65]. 4. Mass (non-label) based single-cell proteome analysis In single-cell proteome analysis, nearly all non-label based methods utilized MS for final detection. MS had ability to rapidly interrogate virtually all analytes in samples [12,66]. As discussed before, all label based methods had the bottleneck of identified protein number in a single run [22]. Non-label method of MS could significantly increase the identified protein number in each singlecell proteome analysis, and had potential to analyze whole proteome from single cells [3]. Also, it would greatly reduce the complexity and cost of experiments because no labeling reaction was needed before analysis. Moreover, dynamic ranges of MS detection could reach 6e8 orders of magnitude [67,68], which close to the dynamic range of proteins copy number per cell (8 orders of magnitude [9]). In comparison, dynamic ranges of most fluorescence analysis were around 3 orders of magnitude [38,64]. 4.1. Direct MS Direct MS analysis without separation mainly applied to endogenous peptides rather than proteins identification in single cells, because separation was necessary when analyzing proteins in cells by MS, no matter top-down or bottom-up strategy [69]. Sweedler group used optical imaging to locate cells on a slide. Each cell was irradiated by ~30 mm diameter laser of MALDI MS after matrix deposition, then the peptides were analyzed. Cellular subtypes and rare cells among large cellular populations could be discovered by the information of identified peptides [70,71]. The authors also tried to use separation to identify more endogenous peptides or lipids. By use of liquid microjunction extraction after single-cell MALDI-MS analysis, more lipids and peptides were identified by CE-ESI-MS [72]. With the help of solid-phase extraction, extracellular neuropeptides secreted from a single neuron were analyzed by MALDI MS system [73]. By use of a focusing objective and a novel way of matrix deposition, Spengler group developed a 1.4-mm lateral resolution of APMALDI MSI (atmospheric pressure MALDI mass spectrometry imaging). It could be applied to detection of metabolites, lipids, and small peptides in a 1.5-mm2 sampling area [74]. 4.2. Separation and MS analysis In conventional proteome analysis, only nano liquid chromatography-tandem mass spectrometry (nanoLC-MS/MS) and capillary electrophoresis-tandem mass spectrometry (CE-MS/MS) could achieve large scale of protein detection (>1000 proteins) [69]. As mentioned above, label based single-cell proteome analysis had met the bottleneck in identified protein number [22]. The only promising approach to realize large scale of protein identification (at least hundreds of proteins) from single cells was to develop nanoLC-MS/MS or CE-MS/MS based methods. There were mainly two kind of mammalian cells, somatic cells, and germ cells. Usually, diameter of somatic cells was ranged from 10 to 20 mm [14]. Germ cells were much larger than somatic cells, which could be larger than 1000 mm in diameter [75]. Therefore, germ cells were ~100-fold in diameter, ~106-fold in volume, and ~106-fold in protein amount than somatic cells. Therefore,

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proteome of single germ cells was much easier to be analyzed by nanoLC-MS/MS and CE-MS/MS system. Single Xenopus eggs and embryos were lysed and digested by conventional methods and analyzed by commercial nanoLC-MS/MS system. Around 5800 and 4000 proteins were identified from single Xenopus eggs and embryos [75,76], respectively. By use of microdissection, blastomeres were isolated from early stage of Xenopus embryos. There were ~0.8 mg (16-cell embryo) to ~0.2 mg (50-cell embryo) yolk-free proteins in single blastomeres, which was only several tenths of the whole embryo. From the same sample type of single blastomeres in a 16-cell embryo, Dovichi group identified 1466 proteins by nanoLC-MS/MS [77] and Nemes group identified 1070 proteins by CE-MS/MS [78,79] (Fig. 3). Murgia and Mann group used nanoLC-MS/MS to compare the proteome of single muscle fibers of younger subjects with older, and found that glycolysis and glycogen metabolism quickly decreased in aging fast muscle fibers [80].

However, for somatic cells, nothing could be identified if conventional nanoLC-MS/MS and CE-MS/MS were directly applied to single-cell proteome analysis. Most somatic cells contained only ~0.1 ng protein [14]. Additionally, proteins and peptides of single somatic cells would be severely lost and diluted during cell treatment and sample injection by conventional methods and devices. Therefore, in order to realize single somatic cell proteome analysis by nanoLC-MS/MS and CE-MS/MS, two aspects of the system must be improved. One was cell treatment, including single-cell capture, single-cell lysis, digestion, and sample injection. Those processes should be matched with the size of single somatic cells to reduce sample loss and dilution. The other aspect was to substantially improve the sensitivity of nanoLC-MS/MS or CE-MS/MS. Many parts in the system such as chromatographic column, ESI-tip, and MS should be minimized and improved.

Fig. 3. A) Micrographs of the Xenopus laevis embryos, and a workflow illustration for single-cell proteome analysis of individual blastomeres by nanoLC-MS/MS. Reprinted with permission from Ref. [77]. B) Workflow of individual blastomere proteome analysis in 16-cell Xenopus embryos by CE-MS/MS. Reprinted with permission from Ref. [78].

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Although sensitivity of CE-MS/MS has been sharply improved in these years [17,81], there were few reports on large scale identification of proteins from single somatic cells by CE-MS/MS. In these years, nanoLC-MS/MS has gained big boosts in the field of single somatic cell proteome analysis. Scientists firstly tried to analyze little amount of somatic cells. Figeys group developed an integrated rare cell proteomic reactor (RCPR) [82] for analysis of 50000 cells. By use of a strong cationic exchange (SCX) monolithic column and reagents, the cell lysate was digested in the column. The SCX column was directly connected with a nanoLC-MS/MS system. A total of 2281 proteins were identified from 50000 hESCs cells (embryonic stem cells) by RCPR. Similar techniques were utilized by Tian group's simple and integrated spintip-based proteomics technology (SISPROT) [83]. In their work, SCX and RP packing materials were filled in a tip. The cell lysate was digested in the SCX packing bed and purified by the RP packing bed. The eluate was collected in a tube and then injected for nanoLC-MS/MS analysis. Finally, 1270e7826 proteins were identified from 2000 to 100000 Human embryonic kidney (HEK) 293T cells. Besides on-column digestion, enrichment materials were also used to keep high sample concentration and control sample loss. Krijgsveld group developed a method called single-pot solidphase-enhanced sample preparation (SP3) [84]. In SP3, carboxycoated magnetic beads were used to capture proteins and peptides during cells lysis and digestion, in order to reduce sample loss and dilution during sample treatment process. Finally, 2500 proteins were identified from 1000 HeLa cells. In the year of 2018, single-cell proteome analysis of somatic cells based on nanoLC-MS/MS was realized by three groups. A liquid processing method called SODA (sequential operation droplet

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array) technique was developed in 2013 by Fang group [85] and was applied for quantifying gene expression in individual cells [86]. Based on this technique, Kelly group developed a chip called nanoPOTS (nanodroplet processing in one pot for trace samples) for analysis of 10e100 cells [67]. Furthermore, they combined nanoPOTS with fluorescence activated cell sorting (FACS) to realize single-cell analysis (Fig. 4) [87]. In nanoPOTS, cells were randomly collected in each pit on the chip. By FACS, single cells were collected in each pit. Cells in each pit were lysed and digested respectively. The final volume of digests was only 200 nL. The obtained digests were directly inhaled into a bare capillary, and then connected into nanoLC-MS/MS system to inject sample. Besides single-cell treatment, an ultra-long and ultra-narrow bore chromatographic column (50/70 cm  30-mm-i.d.), and Orbitrap Fusion Lumos Tribrid MS were used for ultrasensitive analysis. Finally, approximate 1500e3000 proteins were identified from 10 to 140 HeLa cells, and 211 proteins were identified in single HeLa cells. With match between runs (MBR) algorithm, 669 proteins were identified from a single HeLa cell. The detection limit was around 16 zmol. Fang group developed a nanoliter-scale oil-air-droplet (OAD) device for proteome analysis from 1 to 100 cells (Fig. 5) [88]. It is the first report of using SODA technique to achieve single cell proteomics analysis. Cell lysis, protein reduction, alkylation, and digestion was carried out in a nanoliter droplet (~550 nL). Cell digests were directly injected into a capillary column by nitrogen pressure. In maximal, 51 proteins were identified in a single HeLa cell. Zhang group developed a series of integrated proteome analysis devices (iPAD) for small amount cells and single-cell proteome analysis [68,89e91]. The main principle of iPAD was to conduct online cell lysis and digestion simultaneously in a capillary. Intact

Fig. 4. Overview of an integrated platform for single-cell proteome analysis. A) Scheme of FACS sorting cells and distributing them into nanowells of the nanoPOTS chip. Single cells were lysed and digested into peptides in the nanoPOTS chip, and then analyzed by nanoLC-MS/MS. B) Fluorescence images of precise collection of defined numbers of HeLa cells. C) The m/z to retention time plot of 2825 peptides identified from a single HeLa cell. Reprinted with permission from Ref. [87].

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Fig. 5. Overview of the nanoliter-scale oil-air-droplet chip-based device. A) Structure of the nanoliter scale oil-air-droplet (OAD) chip and the self-aligning monolithic (SAM) device. B) Workflow of single-cell pretreatment and sample injection. Reprinted from Ref. [88] with permission of American Chemical Society.

living cells were sucked into the capillary with necessary reagents at 4 C. When the temperature was risen to 50 C, cells could be simultaneously lysed and digested. And the digestion could be directly loaded into the separation column for analysis. The authors firstly developed iPAD-100, by which 651 proteins were identified from 100 DLD-1 (Duke's type C colorectal adenocarcinoma) cells [90]. After that, by use of a 2 m  20-mm-i.d. five-layer GNPs@C18 open tubular column, iPAD-80 was built and 514 proteins were identified from 80 HepG2 cells [89]. Recently, the authors built iPAD-1 (Fig. 6) and realized identification of 181 proteins (328 proteins, MBR) from a single HeLa cell [68]. In iPAD-1, sample loss and dilution were greatly reduced via the only 2 nL cell treatment volume and zero dead volume sample loading. By utilization of ultra-narrow bore column (20-mm-i.d.) and ESI-tip (3-mm-i.d.), and Orbitrap Fusion Tribrid MS, the detection limit was sharply

declined to 1.7 zmol. Due to the used of ultrasonication in singlecell treatment and short column (3 cm long) in separation, whole analysis time (cell treatment and nanoLC-MS/MS analysis) of single cell was as fast as 1 h. In addition, the iPAD-1 was excellent in single-cell capture. Compared with chip-based random cell capture method [87], any specific cell could be chosen and sucked into the capillary of iPAD-1 with the help of microscope. Even if there was only one cell in the solution, single-cell capture and proteome analysis could still be easily accomplished. 5. Guidance of method selection In our point of view, there are six indexes (strategy, protein number, specificity, detection limit, throughput and commercialization) to evaluate methods of single-cell proteome analysis.

Fig. 6. Layout of the integrated proteome analysis device for fast single-cell protein profiling. Selected single cell and solution was aspirated into the capillary 1 by use of syringe pump. After single-cell lysis and digestion in the capillary 1, the capillary 1 with single-cell digest was connected with the integrated separation column. Then, nanoLC-MS/MS was applied for separation and detection. Reprinted from Ref. [68] with permission of American Chemical Society.

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Table 1 A list of representative methods for single-cell proteome analysis. Methods

Strategy

Proteins number

Specificity

Detection limit (molecules)

Throughput

Commercial

Fluorescence microscope [30] FFC [38] scWestern [46] Mass cytometry [57,58] SCBC [56] iPAD-1 [68] nanoPOTS [87]

Label based for target proteins

<10 <10 ~10 ~50 ~50 ~200 ~200

Medium Medium High Medium Medium High High

1 ~100 ~27000 ~350 100e1000 1000e10000 ~10000

Medium High Medium High Medium Low Low

Yes Yes No Yes No Half Half

Mass (non-label) based for whole proteome

Strategy is about the label based or mass (non-label) based. Label based methods apply to targets proteins analysis; mass (non-label) based methods apply to whole proteome analysis. Identified protein number is one of the most important indexes. Each biofunction in cells concerned a large number of proteins. Detecting only a little proteins cannot show the big picture [69]. Specificity represents the accuracy of protein qualification. For instance, in label based methods, there is cross-reactivity between antigens and antibodies, which may lead to false detection [47]. Also, the higher specificity, the higher accuracy of quantification of the methods. And the ability of quantification is very important to investigate cellular heterogeneity. Throughput of methods is important in practical applications. The higher throughput, the more single cells can be analyzed in experiments; and the more cellular heterogeneity may be found. Commercialization of instruments and reagents are essential for widespread using of methods [21,92]. We selected seven representative methods for single-cell proteome analysis, and listed them in Table 1. When only one or several proteins in single cells need analysis, fluorescence microscope [30] and FFC [38] methods are available. Due to the capability of single molecule detection, nearly all the proteins in single cells can be analyzed by fluorescence microscope as long as there are matched antibodies. One of the biggest advantage of FFC is high throughput. Millions of single cells can be quickly analyzed in one test. It should be noticed that secreted proteins cannot be analyzed by FFC. The scWestern can simultaneously analyze ~10 target proteins in single cells [46]. Because the proteins are separated in PAGE, the impact of cross-reactivity between antigens and antibodies can be eliminated. Thus higher specificity and better quantification are obtained. But commercial instruments of scWestern has not been seen yet. Mass cytometry and SCBC methods can simultaneously detect 50 target proteins in maximal from single cells. By use of commercial instruments of cyTOF, mass cytometry can be conveniently applied to analyze membrane and intracellular proteins [57,58]. However, cyTOF cannot be used to analyze secreted proteins. SCBC is suitable for analyzing secreted proteins [56]. But its application is limited for lack of commercial instruments. Mass (non-label) based method is the only choice for whole proteome analysis from single cells up to now. If cells are germ cells or large size cells, conventional nanoLC-MS/MS [77] and CE-MS/MS [78] can be directly used for analysis. As for most somatic cells (10e20 mm), iPAD-1 [68] and nanoPOTS [87] are available for ~200 proteins identification. Both iPAD-1 and nanoPOTS methods are based on specialized single-cell treatment devices and ultrasensitive nanoLC-MS/MS. It is worth noting that any specific cell can be chosen and analyzed by iPAD-1. Even if there is only one cell, analysis can still be easily accomplished. 6. Conclusion and outlook Nowadays, single-cell proteome analysis is no longer impossible for scientists. More and more information of cellular heterogeneity is unraveled by the developing single-cell proteome analytical

methods. Label based methods can detect a maximal of 50 target proteins simultaneously from single cells. Due to high throughput and low detection limit, the methods can quickly analyze low abundant proteins from a large amount of single cells. Also, commercial instruments such as fluorescence microscopy, FFC and cyTOF facilitate the widespread use of the methods. Mass (nonlabel) based methods can analyze endogenous peptides and whole proteome from single cells. Single somatic cells (10e20 mm) once cannot be analyzed by nanoLC-MS/MS system. The recent developed single-cell treatment devices and ultra-sensitive nanoLC-MS/ MS system such as iPAD-1 [68] can realize identification of around 200 proteins from single somatic cells (10e20 mm). And the protein number is larger by use of MBR algorithm. Like the technology development of single-cell whole genome analysis [10,93,94], the capability of whole proteome analysis for single somatic cells is a milestone event for single-cell proteome analysis. It may significantly promote the development of single-cell analysis. Although there is huge progress in development of novel methods for single-cell proteome analysis, technologies are far from mature. Much more efforts should be paid in this area continuously. We expect that over 1000 proteins can be identified from single somatic cells by nanoLC-MS/MS. CE-MS/MS also has the potential to analyze whole proteome from single somatic cells. Besides, how to realize high-throughput analysis of whole proteome from a mass of single cells is also a great task in the future. We believe that as long as over 1000 proteins identification and high through-put analysis are both realized in one method, single cell proteomic will receive a great development. Acknowledgements This research was supported by National Natural Science Foundation of China (no. 21775027) and National Research Program of China (Projects: 2017YFA0505003, 2016YFA0501402, 2016Y FA0501401 and 2012YQ12004409). References [1] S.J. Altschuler, L.F. Wu, Cellular heterogeneity: do differences make a difference? Cell 141 (2010) 559e563. [2] K. Klep
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