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Recent development in proteomic sample preparation using nanofluidic devices has made single-cell proteome profiling possible. However, these nanofluidic devices require special expertise and costly nanopipetting instruments. They are also specially designed for single cells, are not well-suited for profiling rare samples consisting of a few hundred mammalian cells, arguably a more common need that remains a great challenge. Herein, we developed an easy-to-use and scalable device for processing low-input samples, which combined the merits of previously reported rare cell proteomic reactor (RCPR) and mixed-mode simple and integrated spintip-based proteomics technology, as an alternative to nanofluidic devices. All steps of proteomics sample preparation, including protein preconcentration, impurity removal, reduction, alkylation, digestion, and desalting, were fully integrated in our workflow, and the device can be directly connected to online nanoLC-MS system after processing the rare samples. Using the developed 3-frit mixed-mode RCPR, we identified on average 946 ± 158, 2 998 ± 106, and 3 934 ± 85 protein groups in data-dependent acquisition (DDA) mode from 10, 100, and 500 fluorescence-activated cell sorting (FACS)-sorted 293T cells, respectively. As an illustrative application of this technology, we performed a label-free proteome comparison of 500 FACS-sorted mouse cochlear hair cells of two different ages. On average, 2 595 ± 230 and 2 042 ± 120 protein groups were quantified in the juvenile and the adult samples in DDA mode, respectively, achieving dynamic ranges of over 6 orders of magnitude for both.

Tyrosine phosphorylation (pTyr) regulates various signaling pathways under normal and cancerous states. Due to their low abundance and transient and dynamic natures, systematic profiling of pTyr sites is challenging. Antibody and engineered binding domain-based approaches have been well applied to pTyr peptide enrichment. However, traditional methods have the disadvantage of a long sample preparation process, which makes them unsuitable for processing limited amount of samples, especially in a high-throughput manner. In this study we developed a 96-well microplate-based approach to integrate all the sample preparation steps starting from cell culture to MS-compatible pTyr peptide enrichment in three consecutive 96-well microplates. By assembling an engineered SH2 domain onto a microplate, nonspecific adsorption of phosphopeptides is greatly reduced, which allows us to remove the Ti-IMAC purification and three C18 desalting steps (after digestion, pTyr enrichment, and Ti-IMAC purification) and, therefore, greatly simplifies the entire pTyr peptide enrichment workflow, especially when processing a large number of samples. Starting with 96-well microplate-cultured, pervanadate-stimulated cells, our approach could enrich 21% more pTyr sites than the traditional serial pTyr enrichment approach and showed good sensitivity and reproducibility in the range of 200 ng to 200 μg peptides. Importantly, we applied this approach to profile tyrosine kinase inhibitor-mediated EGFR signaling pathway and could well differentiate the distinct response of different pTyr sites. Collectively, the integrated 96-well microplate-based approach is valuable for profiling pTyr sites from limited biological samples and in a high-throughput manner.

Capillary- and micro-flow liquid chromatography-tandem mass spectrometry (capLC-MS/MS and μLC-MS/MS) is becoming a valuable alternative to nano-flow LC-MS/MS due to its high robustness and throughput. The systematic comparison of capLC-MS/MS and μLC-MS/MS systems for global proteome profiling has not been reported yet. Here, the capLC-MS/MS (150 μm i.d. column, 1 μL/min) and μLC-MS/MS (1 mm i.d. column, 50 μL/min) systems were both established based on UltiMate 3000 RSLCnano coupled to an Orbitrap Exploris 240 by integrating with different flowmeters. We evaluated both systems in terms of sensitivity, analysis throughput, separation efficiency, and robustness. capLC-MS/MS was about 10 times more sensitive than μLC-MS/MS at different gradient lengths. Compared with capLC-MS/MS, μLC-MS/MS was able to achieve higher analysis throughput and separation efficiency. During the 7 days' long-term performance test, both systems showed good reproducibility of chromatographic full width (RSDlt; 3%), retention time (RSDlt; 0.4%), and protein identification (RSDlt; 3%). These results demonstrate that capLC-MS/MS is more suitable for high-throughput analysis of clinical samples with a limited starting material. When enough samples are available, μLC-MS/MS is preferred. Together, capLC and μLC coupled to Orbitrap Exploris 240 with moderate sensitivity should well meet the needs of large-cohort clinical proteomic analysis.

Protein complexes mediated by various post-translational modifications (PTMs) play important roles in almost every aspect of biological processes. PTM-mediated protein complexes often have weak and transient binding properties, which limit their unbiased profiling especially in complex biological samples. Here, we developed a plug-and-play chemical proteomic approach for high-throughput analyis of PTM-mediated protein complexes. Taking advantage of the glutathione-S-transferase (GST) tag, which is the gold standard for protein purification and has wide access to a variety of proteins of interest (POIs), a glutathione (GSH) group- and photo-cross-linking group-containing trifunctional chemical probe was developed to tag POIs and assembled onto a streptavidin-coated 96-well plate for affinity purification, photo-cross-linking, and proteomics sample preparation in a fully integrated manner. Compared with the previously developed photo-pTyr-scaffold strategy, by assembling the tyrosine phosphorylation (pTyr) binding domain through covalent NHS chemistry, the new plug-and-play strategy using a noncovalent GST-GSH interaction has comparable enrichment efficiency for EGF stimulation-dependent pTyr protein complexes. To further prove its feasibility, we additionally assembled four pTyr-binding domains in the 96-well plate and selectively identified their pTyr-dependent interacting proteins. Importantly, we systematically optimized and applied the plug-and-play approach for exploring protein methylation-mediated protein complexes, which are difficult to be characterized due to their weak binding affinity and the lack of efficient enrichment strategies. We explored a comprehensive protein methylation-mediated interaction network assembled by five protein methylation binding domains including the chromo domain of MPP8, tandem tudor domain of KDM4A, full-length CBX1, PHD domain of RAG2, and tandem tudor domain of TP53BP1 and validated the chromo domain- and tudor domain-mediated interaction with histone H3. Collectively, this plug-and-play approach provides a convenient and generic strategy for exploring PTM-dependent protein complexes for any POIs with the GST tag.

A fully integrated sample preparation technology, termed Intact GlycoSISPROT, was developed for the highly sensitive analysis of site-specific glycopeptides. Through integrating all glycoproteomic sample preparation steps into a single spintip, Intact GlycoSISPROT provided a tool for site-specific glycosylation analysis with low micrograms to even nanograms of protein sample.

Vast majority of cellular activities are carried out by protein complexes that assembled dynamically in response to cellular needs and environmental cues. Large scale efforts had uncovered a large repertoire of functionally uncharacterized protein complexes which necessitate new strategies to delineate their roles in various cellular activities and diseases. Thermal proximity co-aggregation profiling could be readily deployed to simultaneously characterize the dynamics for hundreds to thousands of protein complexesin situacross different cellular conditions. Toward this goal, we had optimized the original method both experimentally and computationally. In this new iteration termed Slim-TPCA, fewer temperatures are used which increase throughputs by over 3X, while coupled with new scoring metrics and statistical evaluation resulted in minimal compromise in coverage and the detection of more relevant protein complexes. Overall, less samples are needed, false positives from batch effects are minimized and statistical evaluation time is reduced by two orders of magnitude. We applied Slim-TPCA to profile state of protein complexes in K562 cells under different duration of glucose deprivation. More protein complexes are found dissociated based on TPCA signature in accordance with expected downregulation of most cellular activities. These complexes include 55S ribosome and various respiratory complexes in mitochondria revealing the utility of TPCA to study protein complexes in organelles. On other hand, protein complexes involved in protein transport and degradation are found increasingly associated revealing their involvement in metabolic reprogramming during glucose deprivation. In summary. Slim-TPCA is an efficient strategy for proteome-wide characterization of protein complexes. The various algorithmic improvement of Slim-TPCA is available as Python package athttps://pypi.org/project/Slim-TPCA/

Background This study aimed to identify new protein markers that can evaluate the metastatic ability of Pancreatic neuroendocrine tumors (PanNETs) and predict prognosis together with Ki-67. Methods Multicentric series analysis was performed to evaluate the effect of metastasis on overall survival (N = 1,109). Single-cell RNA sequencing, proteomics (32 PanNETs and 10 normal pancreas tissues), and immunohistochemical staining (152 PanNETs) were conducted to screen proteins associated with PanNET metastatic capability. Associations between expression of screened proteins and survival were examined using Cox regression. In vitro experiments were performed to verify the function of candidate protein. A survival signature was constructed using recursive partitioning and survival forest analyses. Results The combination of G grade and metastasis predicted long-term survival more accurately though retrospective analysis. Single-cell RNA-seq highlighted the PanNET characteristics of metastasis that do not correspond with G grade and identified high metastatic capability subgroups in PanNET. Five proteins (PIN1, POSTN, SEMA4F, ASPN, and KCDT12), which may be related to the metastatic capability of PanNETs, were identified by proteomics. Random survival forest analysis showed that PIN1 could be a marker of PanNET metastatic ability. PIN1 overexpression promoted metastasis through LAMIN in PanNET cells. Finally, a survival signature with a consistency index of 0.921 and strong calibration was established, with good ability to predict patient survival. Conclusion In summary, we found that PIN1 can precisely evaluate the metastatic potential of PanNETs and, together with the proliferation marker Ki-67, can accurately predict the survival of PanNET patients.

Many secreted proteins, including cytokines, growth factors and hormones, are crucial in processes like intercellular signaling. Dynamic changes in secreted proteins usually reflect the growth and pathological state of the cells. Many drug targets are secretory proteins. The proteins are also important biomarkers. Conditioned cell culture media are important samples for secretory proteomic studies. Biomass spectrometry-based proteomic analysis enables the systematic study of secretory proteins. The main problem in analyzing secretory proteins in conditioned culture media is the low concentration of these proteins and the presence of serum, amino acids, and additives in culture media that may interfere with the protein analysis. Conventional secretory proteome analysis uses serum-free cell culture to reduce sample complexity, and typically involves protein concentration, purification, and desalting using ultrafiltration, dialysis, lyophilization, and trichloroacetic acid (TCA) or acetone precipitation, followed by enzymatic digestion and mass spectrometry analysis. This analytical process does not allow specific enrichment of secreted proteins. Thus, only a few secreted proteins can be identified. In addition, prolonged serum-free incubation of cells also tends to lead to unexpected changes in their activity status. A bioorthogonal-based enrichment approach can effectively avoid this problem. In recent years, unnatural sugars containing bio-orthologous groups, such as azide groups, have been used to metabolically label glycosylated proteins, enabling cellular imaging or selective enrichment of glycoproteins and their use for proteomic analysis. The strategy is a two-step process. First, azide-based sugar analogues are added to the cell culture medium and introduced to glycoproteins via the intracellular glycan biosynthesis pathway. Second, they are specifically covalently labeled with imaging probes or affinity probes via click chemistry. Since secreted proteins are usually glycoproteins, this glycolytic labeling has been used to label and enrich secreted proteins. N-Azidoacetylgalactosamine (GalNAz), N-azidoacetylglucosamine (GlcNAz), and N-azidoacetylmannosamine (ManNAz) are classical azide-based sugar analogues. Their effects on cytoplasmic membrane proteins have been compared. However, only ManNAz has been used for metabolic labeling of secreted proteins. No other glyco-analogues that label secreted proteins have been reported. Here, the bio-orthogonal chemical biology technology achieved highly selective labeling and enriched secreted proteins. In combination with click chemistry, different sugar analogues were evaluated for metabolic labeling of secreted proteins. HeLa cells were metabolically labeled by ManNAz, GalNAz, and GlcNAz (the three most commonly used commercial sugar analogues). These glycolytic markers can selectively label specific types of glycosylation. For example, ManNAz, an analogue of the biosynthetic precursor of sialic acid, N-acetylmannosamine (ManNAc), can label sialylated N- or O-glycoproteins. GalNAz, an analogue of N-acetylgalactosamine (GalNAc), can replace GalNAc as a core residue of mucin-type O-glycans and thus label O-glycoproteins. In addition, the intracellular metabolic intermediate of GalNAz (pyrophosphate) UDP-GalNAz can be interconverted with UDP-GlcNAz catalyzed by UDP-galactose-4-differential isomerase (GALE) and thus can also label N-glycoproteins and O-GlcNAc glycoproteins instead of GlcNAc. The GlcNAz analogue is commonly used to label nuclear and cytoplasmic glycoproteins with β-O-GlcNAc residues, but can also label N-glycoproteins with mucin-type O-glycoproteins by converting GALE to GalNAz, followed by enrichment using a biotin-alkynyl probe. Label-free quantitative proteomic analysis was performed to evaluate their labeling efficiency. ManNAz-based secretory protein labeling identified 282 secretory proteins, 224 plasma membrane proteins, and 846 N-glycosites. Compared with GalNAz and GlcNAz, the enrichment of secreted proteins was increased 130% and 67.2%, respectively, and the enrichment of plasma membrane proteins was increased 273.3% and 148.7%, respectively. This study provides a useful comparative analysis and new strategies for highly selective enrichment and systematic secretome analysis.

Tyrosine phosphorylation (pTyr)-dependent signaling pathways play a vital role in various biological processes, which are spatiotemporally assembled and dynamically regulated on a minute scale by pTyr in living cells. Studying these pTyr-mediated signaling complexes is therefore challenging due to the highly dynamic nature of the protein complexes and the low abundance of pTyr. In this study, we adopted minute-resolution APEX2-based proximity labeling (PL) in living cells and Src SH2 superbinder-based pTyr peptide enrichment for simultaneously profiling these protein complexes and associated pTyr sites from the same affinity-purified sample. Upon different time courses of EGF stimulation of the living cells stably expressing APEX2-FLAG-GRB2, we constructed two-dimensional time-course curves for both interactome and tyrosine phosphoproteome. Well-annotated pTyr signaling complexes in EGFR signaling and located at the endosome were quantified with tightly correlated time-course curves for both interacting proteins and pTyr sites. Importantly, the correlated time-course curves for EGFR and endosomal HGS were well validated by targeted-parallel reaction monitoring (PRM)-MS analysis. Taking advantage of the high sensitivity of the PRM assay, the low-abundant pTyr peptide EGFR pY1110, which cannot be identified in the data-dependent acquisition (DDA) analysis, could be well quantified. Collectively, this two-dimensional proximity proteomic strategy is promising for comprehensively characterizing pTyr-mediated protein complexes with high sensitivity in living cells.

Background Non-invasive detection of blood-based markers is a critical clinical need. Plasma has become the main sample type for clinical proteomics research because it is easy to obtain and contains measurable protein biomarkers that can reveal disease-related physiological and pathological changes. Many efforts have been made to improve the depth of its identification, while there is an increasing need to improve the throughput and reproducibility of plasma proteomics analysis in order to adapt to the clinical large-scale sample analysis. Methods We have developed and optimized a robust plasma analysis workflow that combines an automated sample preparation platform with a micro-flow LC–MS-based detection method. The stability and reproducibility of the workflow were systematically evaluated and the workflow was applied to a proof-of-concept plasma proteome study of 30 colon cancer patients from three age groups. Results This workflow can analyze dozens of samples simultaneously with high reproducibility. Without protein depletion and prefractionation, more than 300 protein groups can be identified in a single analysis with micro-flow LC–MS system on a Orbitrap Exploris 240 mass spectrometer, including quantification of 35 FDA approved disease markers. The quantitative precision of the entire workflow was acceptable with median CV of 9%. The preliminary proteomic analysis of colon cancer plasma from different age groups could be well separated with identification of potential colon cancer-related biomarkers. Conclusions This workflow is suitable for the analysis of large-scale clinical plasma samples with its simple and time-saving operation, and the results demonstrate the feasibility of discovering significantly changed plasma proteins and distinguishing different patient groups.

Identification of the tyrosine phosphorylation (pY)-dependent interactome of immune co-receptors is crucial for understanding signal pathways involved in immunotherapy. However, identifying the motif-specific interactome for each pY commonly found on these multi-phosphorylated membrane proteins remains challenging. Here, we describe a photoaffinity-based chemical proteomic approach to dissect the motif-specific cytoplasmic interactomes of the critical immune co-receptor CD28. Various full-length CD28 cytoplasmic tails (CD28cyto) with defined pY and selectively replaced photo-methionine were synthesized and applied to explore three pY-motif-dependent CD28cyto interactomes. We identified a stand-alone interaction of phospholipase PLCG1 with the Y191 motif with enhanced affinity for the sequence neighboring the transmembrane domain. Importantly, taking advantage of native top-down mass spectrometry with a 193-nm laser, we discovered the direct association of a previously undefined pY218 motif with the kinase PKCθ through its C2 domain. This synthetic CD28cyto-based photoaffinity proteomic approach is generically applicable to the study of other immune co-receptors with multiple pY sites on their linear cytoplasmic tail.

Function or disfunction of proteins depends on the primary structures, and protein sequencing, which provides key information on protein related biological processes and disease, plays important roles in biological, biomedical, clinical research and application. To obtain the precise protein sequences, researchers developed different methods over the past few decades, and these methods include conventional methods and newly methods. The former includes Edman degradation and mass spectrometry (MS), and the latter includes single-molecule detection, nanopore and other lately developed techniques. In the 1960s, the classic Edman degradation was firstly developed for sequencing protein molecules from N-terminus using cyclic chemical reaction. Afterwards, solid-state, and gas-state Edman degradation was further developed that still plays a significant role in the modern technologies. This review discusses the principle and limits of Edman degradation. Moreover, we discussed advantages and shortcomings of MS-based approaches, which are the current standard methods for protein sequencing applications. Single-molecule approaches could bring revolution in proteomics, realizing high sensitivity for the low-abundance protein detection and single-cell proteomics. With the development of the single-molecule nucleic acid sequencing, four kinds of basic groups of DNA/RNA can be effectively detected using label-free or fluorescence labelling strategies. However, it is still a challenge to label and analyze all twenty kinds of amino acid residues. Moreover, sensitive optical detection has been utilized for high throughput protein sequencing using fluorescence labelling. In this approach, selected residues of peptides were labelled, and the C-terminus was anchored onto the glass substrate. N-terminus was degraded through Edman cycles. Finally, the sequence can be analyzed through the wide-field fluorescence signals. This method has potential of large-scale, sensitive, and parallel detection. We have discussed its principle and characteristic features in detail. Nanopore, including biological nanopore and solid-state nanopore, has been emerged as powerful technologies for protein sequencing. Nanopore can provide single-molecule sensing interface and controlled nano-confined space enabling ultimate sensitivity and high spatiotemporal resolution. The mechanism of nanopore-based technologies depends on the interaction of functional group and the nanopore, inducing the current modulations. The information of peptides can be obtained by monitoring the ionic current responses. Arrayed nanopores have potential of high-throughput detection at low-abundance. It is still in early stage of development and some challenges need to be addressed. As “finger-print” signal, Raman spectrum is an ideal candidate for protein sequencing. However, very weak signals can significantly restrict its application, especially at low concentration of target molecule. Surface enhanced Raman spectroscopy (SERS) can enhance the Raman signal to achieve the detection on the scale of a single molecule. Combination of the SERS and nanopore has demonstrated powerful capability of label-free detection of ten kinds of amino acids. Moreover, this method offers a new strategy for protein sequencing. Comparing with the weak Raman signal, fluorescence signals are more accessible, even on the level of single molecule. Several molecular dynamics (MD) simulations have been discussed to show possibility of fluorescence labelled protein sequencing within nanopore. Nevertheless, some drawbacks need to be addressed, especially the high-cost fabrication of nanopore and translocation of proteins through a pore. Specifically, this review also discusses the future challenges as well as summarize recent efforts to break the bottleneck of the current protein sequencing, promoting development of medical treatment, disease diagnosis and related fields.

Proteomic analysis aims at characterizing proteins on a large scale, including their relative abundance, post-translational modifications, protein-protein interactions and so on. Proteomic profiling helps to elucidate the mechanisms of disease occurrence and to discover new diagnostic markers and therapeutic targets. Mass spectrometry (MS)-based proteomic technologies have advanced to allow comprehensive qualitative and quantitative proteome profiling across a myriad proteins in cells and tissues. High-throughput proteomics is the core technique for large-scale protein characterization. With the increased demand for large cohort proteomic analysis in the biomedical research field, high-throughput proteomic analysis has become a critical issue that needs to be urgently addressed. The standard shotgun proteomic workflow comprises four steps, including sample preparation, peptide separation, MS acquisition, and data analysis. Advances in these four steps have contributed to the development of high-throughput proteomics. In this review, we aimed at summarizing the current information on the state-of-the-art development of high-throughput proteomic analysis, mainly including the following topics: (1) High-throughput, automatic proteomic sample preparation methods based on liquid-handling workstations. The automation of the proteomic sample preparation steps is essential for high-throughput proteomic analysis, which will significantly reduce variation of manual operation and sample loss by multistep sample processing. The commercial liquid handling workstations, including King FisherTM Flex, Agilent Bravo, AssayMAP Bravo, and Biomek® NXP, perform the handling steps of 96- or 384-channel microplate formats using a mechanical arm that increases the throughput and robustness of sample preparation. (2) High-throughput proteomic detection methods based on microliter-flow-rate liquid chromatography coupled with mass spectrometry (micro-flow LC-MS/MS). Nanoliter-flow-rate liquid chromatography coupled with mass spectrometry (Nano-flow LC-MS/MS) is widely used in classic proteomic research due to its excellent sensitivity, which often comes at the expense of robustness. Owing to the improved robustness and decreased injection-to-injection overheads, micro-flow LC-MS/MS has become increasingly popular in high-throughput proteomic analysis. (3) Using MS instrumentation with high sensitivity and fast scanning speed to realize in-depth proteomic analysis coupled with short chromatographic gradient separation. In recent years, new MS instrumentation continues to exhibit speed of analysis and sensitivity enables the large-scale profiling of hundreds of samples. In particular, ion mobility-based MS, such as timsTOF Pro and Exploris 480 equipped with a front-end high field asymmetric waveform ion mobility spectrometry (FAIMS), which provides fast, sensitive, and robust proteome profiling, thus shifting proteomics to the high-throughput era. (4) Artificial intelligence-, deep neural network-, and machine learning-based proteome data analysis methods. These approaches have improved comprehensive proteomic analysis efficiency. Specifically, the emergence of new algorithms and the up gradation of search engines accelerate the process of high-throughput data analysis. Additionally, the challenges and future development of high-throughput proteomics are prospected. In conclusion, high-throughput proteomic technologies are expected to gradually "transform" and become powerful tools for large cohort proteomic analysis in the near future.

The human body comprises rich populations of cells, which are arranged into tissues and organs with diverse functionalities. These cells exhibit a broad spectrum of phenotypes and are often organized as a heterogeneous but sophisticatedly regulated ecosystem - tissue microenvironment, inside which every cell interacts with and is reciprocally influenced by its surroundings through its life span. Therefore, it is critical to comprehensively explore the cellular machinery and biological processes in the tissue microenvironment, which is best exemplified by the tumor microenvironment (TME). The past decade has seen increasing advances in the field of spatial proteomics, the main purpose of which is to characterize the abundance and spatial distribution of proteins and their post-translational modifications in the microenvironment of diseased tissues. Herein, we outline the achievements and remaining challenges of mass spectrometry-based tissue spatial proteomics. Exciting technology developments along with important biomedical applications of spatial proteomics are highlighted. In detail, we focus on high-quality resources built by scalpel macrodissection-based region-resolved proteomics, method development of sensitive sample preparation for laser microdissection-based spatial proteomics, and antibody recognition-based multiplexed tissue imaging. In the end, critical issues and potential future directions for spatial proteomics are also discussed.

Two-dimensional digital microfluidic platforms, on which droplets are actuated by electrowetting on dielectrics, have merits such as dynamic reconfigurability and ease for automation. However, concerns for digital microfluidic platforms based on low-cost printed circuit boards, such as the scalability of the electrode array and the reliability of the device operation, should be addressed before high throughput and fully automatic applications can be realized. In this work we report the progress in addressing those issues by using active-matrix circuitry to automatically drive a large electrode array with enhanced device reliability. We describe the design and the fabrication of a robust and scalable active-matrix driven digital microfluidic platform based on printed-circuit board technology. Reliable actuation of aqueous and organic droplets is achieved using a free-standing double-layer hydrophobic membrane. To demonstrate the versatility of the digital microfluidic platform, a pentapeptide is synthesized on the device within 30 minutes. With these improvements, a fully automatic, scalable, robust, reusable, and low-cost digital microfluidic platform capable of parallel manipulation of a large number of droplets can find numerous applications in chemical engineering, bioengineering and biomedical engineering.

Signaling complexes are often organized in a spatiotemporal manner and on a minute timescale. Proximity labeling based on engineered ascorbate peroxidase APEX2 pioneered in situ capture of spatiotemporal membrane protein complexes in living cells, but its application to cytosolic proteins remains limited due to the high labeling background. Here, we develop proximity labeling probes with increased labeling selectivity. These probes, in combination with label-free quantitative proteomics, allow exploring cytosolic protein assemblies such as phosphotyrosine-mediated protein complexes formed in response to minute-scale EGF stimulation. As proof-of-concept, we systematically profile the spatiotemporal interactome of the EGFR signaling component STS1. For STS1 core complexes, our proximity proteomics approach shows comparable performance to affinity purification-mass spectrometry-based temporal interactome profiling, while also capturing additional—especially endosomally-located—protein complexes. In summary, we provide a generic approach for exploring the interactome of mobile cytosolic proteins in living cells at a temporal resolution of minutes., APEX-based proximity labeling allows capturing protein interaction dynamics but its high labeling background limits its utility for cytosolic proteins. Here, the authors develop more selective proximity labeling probes, enabling the APEX-based characterization of time-resolved cytosolic protein interactomes.

Gangliosides are a family of glycosphingolipids which are particularly enriched in the nervous system. They play crucial roles in neuroprotection and neurological diseases. Alzheimer's disease (AD) is a neurodegenerative disease with cognitive, judgment and memory dysfunction. In this study, a mass spectrometry-based data-dependent acquisition method assisted with fragmentation characteristics screening by computer algorithm was developed for qualitative and quantitative analysis of gangliosides at low concentration. The developed method was applied to obtain detailed ganglioside species content in hippocampus of model mice (APPswe/PS1dE9 transgenic mice) with AD at 3- to 8-month-old. Up-regulated acetylated and N-acetylgalactosaminylated ganglioside species, and the down-regulated major gangliosides were observed with the development of AD from early to late stage. We speculated that deterioration of AD may be related to the acetylation/N-acetylgalactosaminylation transformation of complex gangliosides due to the inhibition of GD3 synthase activity. Moreover, the ganglioside species di-O-Ac-GT1a (d36:1), O-Ac-GD1b (d36:1) and O-Ac-GD1b (d36:0) were considered as the time-coursed biomarkers, and O-Ac-GT1a (d36:2) could be a candidate for early diagnosis of AD.

Ganglioside is an important class of lipid species involved in intercellular signaling and various diseases, especially for neurodegenerative diseases. Systematic ganglioside profiling is challenging because of their naturally low abundance and highly diverse species. Herein, a new data-independent acquisition and parallel reaction monitoring (DIA/PRM) method with superior sensitivity was developed. The untargeted DIA acquisition consecutively records all the precursor ion and fragment ions at the same time, while the targeted PRM analysis with versatile higher collisional dissociation generates full MS/MS spectra for structure elucidation and verification. As compared with traditional data-dependent acquisition (DDA), the DIA/PRM method unbiasedly detected the majority of abundant ganglioside species and as low as 50 pg of ganglioside in an untargeted manner. Gangliosides in four kinds of biological samples including the mouse brain, mouse plasma, HeLa cell, and human colon cancer tissue were systematically identified, and low-abundance ganglioside species were further extended on the basis of linear chromatography retention rules of the most frequently detected ganglioside species. A total of 383 ganglioside features were defined with 329 of them derived from 32 ganglioside species. Taking advantage of the high-resolution MS analysis, rare ganglioside species were further elucidated according to their characteristic fragment ions and neutral losses. In total, 18 gangliosides with a ceramide carbon number from 20 to 25 and modified gangliosides, including 18 acetylated, 8 diacetylated, 1 phosphorylated, 36 N-glycolyneuraminic acid (NeuGc)-containing, and 7 di-NeuGc-containing gangliosides, were newly identified. The developed DIA/PRM method therefore generated a rich ganglioside resource for further functional exploration and is a unique alternative for DDA analysis for global ganglioside profiling in various biological systems.

A high-throughput proteomic workflow with good sensitivity and reproducibility is highly demanding for proteomic studies of large clinical cohorts. We present a workflow that seamlessly integrates the zwitter-ionic monolith-based spintip (ZIM-Tip) with the Evosep One liquid chromatography system to address this challenge. Disposable ZIM-Tips were prepared with satisfying permeability based on photo-initiated free radical polymerization. Sample preparation steps, including ion-exchange-based protein concentration, reduction, alkylation, and enzymatic digestion, were processed on the ZIM-Tips in 2 h with about 10% sample loss. The peptides recovered from ZIM-Tips were directly loaded on Evotips for desalting and proteomic data acquisition. In one-hour high performance liquid chromatography-MS/MS run, more than 4000 proteins were consistently identified from 1 µg of cell lysate using timsTOF Pro-mass spectrometer in data-dependent acquisition mode (DDA). At least 20 samples with protein amount of 1 µg could be processed each day. Good intra- and inter-day precision in quantification were demonstrated with median coefficient of variation (CV) values of less than 20% and 30%, respectively. The average Pearson correlation coefficients of each two sets of samples are 0.934 and 0.901, respectively. Collectively, the ZIM-Tip technology offers an useful solution for clinical cohort studies with demand for large sample amounts and low sample input while maintaining in-depth proteome coverage.

The dual-specificity tyrosine phosphorylation-regulated kinase DYRK2 has emerged as a critical regulator of cellular processes. We took a chemical biology approach to gain further insights into its function. We developed C17, a potent small-molecule DYRK2 inhibitor, through multiple rounds of structure-based optimization guided by several co-crystallized structures. C17 displayed an effect on DYRK2 at a single-digit nanomolar IC50 and showed outstanding selectivity for the human kinome containing 467 other human kinases. Using C17 as a chemical probe, we further performed quantitative phosphoproteomic assays and identified several novel DYRK2 targets, including eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1) and stromal interaction molecule 1 (STIM1). DYRK2 phosphorylated 4E-BP1 at multiple sites, and the combined treatment of C17 with AKT and MEK inhibitors showed synergistic 4E-BP1 phosphorylation suppression. The phosphorylation of STIM1 by DYRK2 substantially increased the interaction of STIM1 with the ORAI1 channel, and C17 impeded the store-operated calcium entry process. These studies collectively further expand our understanding of DYRK2 and provide a valuable tool to pinpoint its biological function.

Androgen receptor (AR) signaling plays important roles in breast cancer progression. We show here that Kindlin-2, a focal adhesion protein, is critically involved in the promotion of AR signaling and breast cancer progression. Kindlin-2 physically associates with AR and Src through its two neighboring domains, namely F1 and F0 domains, resulting in formation of a Kindlin-2-AR-Src supramolecular complex and consequently facilitating Src-mediated AR Tyr-534 phosphorylation and signaling. Depletion of Kindlin-2 was sufficient to suppress Src-mediated AR Tyr-534 phosphorylation and signaling, resulting in diminished breast cancer cell proliferation and migration. Re-expression of wild-type Kindlin-2, but not AR-binding-defective or Src-binding-defective mutant forms of Kindlin-2, in Kindlin-2-deficient cells restored AR Tyr-534 phosphorylation, signaling, breast cancer cell proliferation and migration. Furthermore, re-introduction of phosphor-mimic mutant AR-Y534D, but not wild-type AR reversed Kindlin-2 deficiency-induced inhibition of AR signaling and breast cancer progression. Finally, using a genetic knockout strategy, we show that ablation of Kindlin-2 from mammary tumors in mouse significantly reduced AR Tyr-534 phosphorylation, breast tumor progression and metastasis in vivo. Our results suggest a critical role of Kindlin-2 in promoting breast cancer progression and shed light on the molecular mechanism through which it functions in this process.

Proteomic analysis aims at characterizing proteins on a large scale, including their relative abundance, post-translational modifications, protein-protein interactions and so on. Proteomic profiling helps to elucidate the mechanisms of disease occurrence and to discover new diagnostic markers and therapeutic targets. Mass spectrometry (MS)-based proteomic technologies have advanced to allow comprehensive qualitative and quantitative proteome profiling across a myriad proteins in cells and tissues. High-throughput proteomics is the core technique for large-scale protein characterization. With the increased demand for large cohort proteomic analysis in the biomedical research field, high-throughput proteomic analysis has become a critical issue that needs to be urgently addressed. The standard shotgun proteomic workflow comprises four steps, including sample preparation, peptide separation, MS acquisition, and data analysis. Advances in these four steps have contributed to the development of high-throughput proteomics. In this review, we aimed at summarizing the current information on the state-of-the-art development of high-throughput proteomic analysis, mainly including the following topics: (1) High-throughput, automatic proteomic sample preparation methods based on liquid-handling workstations. The automation of the proteomic sample preparation steps is essential for high-throughput proteomic analysis, which will significantly reduce variation of manual operation and sample loss by multistep sample processing. The commercial liquid handling workstations, including King Fisher

In recent years, proteomic techniques have undergone rapid progress in terms of sample pretreatment, separation, and mass spectrometry (MS) detection. The current MS-based proteomic techniques can be used to identify up to 10000 proteins both qualitatively and quantitatively within a few hours. However, the current mainstream proteomic approaches do not fulfill the need to analyze minute amounts of biological samples, especially rare cells and single mammalian cells. Capillary electrophoresis (CE)-based separation offers many advantages, such as narrow peaks, high separation efficiency, and low sample requirement, which make it an ideal separation approach for combination with high-resolution MS. We have reviewed the state-of-the-art development of integrated and online sample preparation methods and nanoscale liquid chromatography-mass spectrometry (nanoLC-MS) for high-sensitivity proteomics, and described the associated challenges. Integrated and online sample preparation methods can minimize sample loss and improve lysis and digestion efficiencies. The simple and integrated spintip-based proteomics technology (SISPROT) developed by our group has shown robust performance for the comprehensive profiling of various types of samples and the sensitive analysis of small numbers of cells, down to a few hundred. A few groups have applied integrated/online sample preparation methods, such as nanodroplet processing in one pot for trace samples (nanoPOTS) and integrated proteome analysis system for one cell (iPAD-1), to achieve the identification of hundreds of proteins from a single HeLa cell. We propose that one of the key technical challenges in this field is that the performance of current nanoLC separation techniques cannot match modern high-resolution MS techniques, with ultrahigh scan rates of over 40 Hz; therefore, the insufficient chromatographic performance results in reduced utilization of MS/MS scan capacity. Wide chromatographic peaks result in insufficient precursors to trigger MS/MS scans and redundant sampling, irrespective of whether dynamic exclusion has been enabled. In view of the above mentioned technical challenges, we have focused on discussing the unique technical advantages and potential opportunities of CE-MS, which mainly include the following. (1) High-performance capillary electrophoresis (HPCE) separation for minute amounts of tryptic peptide samples. Capillary electrochromatography can further improve the column capacity limit of HPCE. (2) CE-MS interfaces for high-sensitivity proteomics. Although sheath liquid interfaces have proven versatile and robust and are currently more commonly used, sheathless interfaces can significantly enhance the signal/noise ratio owing to decreased analyte dilution and background noise. Thus, sheathless interfaces are potentially more suitable for ultrasensitive proteomics. (3) Synergetic utilization of HPCE separation and MS detection at high scan rates. The most promising way to fully utilize the ultrahigh scan rates of modern high-resolution MS is to enhance the quality of peptide separation. Narrower peptide peaks in HPCE separation may greatly reduce redundant sampling and boost sensitivity. Overall, we anticipate that, after further improvement, CE-MS-based proteomics will be more widely applied to proteomic analysis of minute amounts of biological samples, such as single mammalian cells. Furthermore, more sensitive data acquisition modes, such as data-independent acquisition, may be used for global proteomic profiling, and parallel reaction monitoring may be used to target a limited number of important proteins. Matching between runs and machine learning algorithms may improve the accuracy of proteomic analysis of minute amounts of samples.

The epidermal growth factor receptor (EGFR) signal modulates cell proliferation, migration, and survival. Aberrant activation of EGFR constitutes the major cause of various cancers. Receptor ubiquitination and degradation mediated by CBL proteins play negative regulatory roles and control the intensity and duration of the signaling. With the construction of stable cell lines inducibly expressing FLAG-tagged CBL or CBLB, we identified 102 and 82 stable interacting proteins of CBL and CBLB, respectively, through the affinity purification followed by mass spectrometry (AP-MS) approach. Time-resolved profiling at six different time points combined with functional annotations of the temporal interactomes provides insights into the dynamic assembly of signal proteins upon EGFR signaling activation. Comparison between the interactomes of CBL and CBLB indicates their redundant but also complementary functions. Importantly, we validated the stable association of EPS15L1 and ITSN2 and temporal association of TNK2 to both CBL and CBLB through biochemical assays. Collectively, these results offer a useful resource for CBL and CBLB interactomes and highlight their prominent and diverse roles in the EGFR signaling network.

Lung adenocarcinoma is heterogeneous and hierarchically organized, with a subpopulation of stem-like cells (CSCs) that reside at the apex of the hierarchy, in which exosomes act as important mediators by transporting specific molecules among different cell populations. Although there have been numerous studies on tumor exosomes, the constituents and functional properties of CSC-derived exosomes are still poorly characterized. Here we present a detail transcriptome and proteome atlas of the exosomes released by human lung adenocarcinoma stem-like cells (LSLCs). The transcriptome analysis indicates the specific patterns of exosomal constituents, including the fragmentation of transcripts and the low-level presence of circular RNAs, and identifies multiple exosomal-enriched mRNAs and lncRNAs. Integrative analysis of transcriptome and proteome data reveals the diverse functions of exosomal-enriched RNAs and proteins, many of which are associated with tumorigenesis. Importantly, several LSLC markers we identified are highly expressed in LSLC-derived exosomes and associate with poor survival, which may serve as promising liquid biopsy biomarkers for lung adenocarcinoma diagnosis. Our study provides a resource for the future elucidation of the functions of tumor-derived exosomes and their regulatory mechanisms in mediating lung cancer development.

Low-abundance phosphotyrosine (pTyr)-mediated signaling protein complexes play critical roles in cancer signaling. The precise and comprehensive profiling of these pTyr-mediated protein complexes remains challenging because of their dynamic nature and weak binding affinity. Taking advantage of the SH2 domains modified with trifunctional chemical probes and genetic mutations (termed Photo-pTyr-scaffold), we developed a Photo-pTyr-scaffold-based forward-phase protein array that can be used to specifically capture complexes by developing an engineered SH2 domain, photoaffinity cross-linking, and antibody-based measuring weak pTyr-mediated protein complexes from complex biological samples in a 96-well microplate format. This platform demonstrated good precision for quantitation (R2 = 0.99) and high sensitivity by which only 5 μg of whole cell lysates is needed. We successfully applied the technology for profiling the dynamic EGF-stimulation-dependent EGFR signaling protein complexes across four different time courses (i.e., 0, 2, 5, 10, and 30 min) in a high-throughput manner. We further evaluated the modulation of EGFR-GRB2-SHC1 protein complexes by FDA-approved EGFR kinase inhibitor erlotinib, demonstrating the feasibility of this approach for high-throughput drug screening. The Photo-pTyr-scaffold-based forward-phase protein array could be generically applicable for exploring the dynamic pTyr signaling complexes in various biological systems and screening for related drugs in a high-throughput manner.