Boosting Detection of Low-Abundance Proteins in Thermal Proteome Profiling Experiments by Addition of an Isobaric Trigger Channel to TMT Multiplexes

Single-cell multi-omics in the study of digestive system cancers

Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.

Assessment of the proteome profile of decellularized human amniotic membrane and its biocompatibility with umbilical cord-derived mesenchymal stem cells

Extracellular matrix-based bio-scaffolds are useful for tissue engineering as they retain the unique structural, mechanical, and physiological microenvironment of the tissue thus facilitating cellular attachment and matrix activities. However, considering its potential, a comprehensive understanding of the protein profile remains elusive. Herein, we evaluate the impact of decellularization on the human amniotic membrane (hAM) based on its proteome profile, physicochemical features, as well as the attachment, viability, and proliferation of umbilical cord-derived mesenchymal stem cells (hUC-MSC). Proteome profiles of decellularized hAM (D-hAM) were compared with hAM, and gene ontology (GO) enrichment analysis was performed. Proteomic data revealed that D-hAM retained a total of 249 proteins, predominantly comprised of extracellular matrix proteins including collagens (collagen I, collagen IV, collagen VI, collagen VII, and collagen XII), proteoglycans (biglycan, decorin, lumican, mimecan, and versican), glycoproteins (dermatopontin, fibrinogen, fibrillin, laminin, and vitronectin), and growth factors including transforming growth factor beta (TGF-β) and fibroblast growth factor (FGF) while eliminated most of the intracellular proteins. Scanning electron microscopy was used to analyze the epithelial and basal surfaces of D-hAM. The D-hAM displayed variability in fibril morphology and porosity as compared with hAM, showing loosely packed collagen fibers and prominent large pore areas on the basal side of D-hAM. Both sides of D-hAM supported the growth and proliferation of hUC-MSC. Comparative investigations, however, demonstrated that the basal side of D-hAM displayed higher hUC-MSC proliferation than the epithelial side. These findings highlight the importance of understanding the micro-environmental differences between the two sides of D-hAM while optimizing cell-based therapeutic applications.

Proteomic Profiles of Human Arterioles Isolated From Fresh Adipose Tissue or Following Overnight Storage

Arterioles are key determinants of the total peripheral vascular resistance, which, in turn, is a key determinant of arterial blood pressure. However, the amount of protein available from one isolated human arteriole may be less than 5 μg, making proteomic analysis challenging. In addition, obtaining human arterioles requires manual dissection of unfrozen clinical specimens. This limits its feasibility, especially for powerful multicenter clinical studies in which clinical specimens need to be shipped overnight to a research laboratory for arteriole isolation. We performed a study to address low-input, test overnight tissue storage and develop a reference human arteriolar proteomic profile. In tandem mass tag proteomics, use of a booster channel consisting of human induced pluripotent stem cell-derived endothelial and vascular smooth muscle cells (1:5 ratio) increased the number of proteins detected in a human arteriole segment with a false discovery rate of <0.01 from 1051 to more than 3000. The correlation coefficient of proteomic profile was similar between replicate arterioles isolated freshly, following cold storage, or before and after the cold storage (1-way analysis of variance; P = .60). We built a human arteriolar proteomic profile consisting of 3832 proteins based on the analysis of 12 arteriole samples from 3 subjects. Of 1945 blood pressure-relevant proteins that we curated, 476 (12.5%) were detected in the arteriolar proteome, which was a significant overrepresentation (χ2 test; P < .05). These findings demonstrate that proteomic analysis is feasible with arterioles isolated from human adipose tissue following cold overnight storage and provide a reference human arteriolar proteome profile highly valuable for studies of arteriole-related traits.

Stability-based approaches in chemoproteomics

Target deconvolution can help understand how compounds exert therapeutic effects and can accelerate drug discovery by helping optimise safety and efficacy, revealing mechanisms of action, anticipate off-target effects and identifying opportunities for therapeutic expansion. Chemoproteomics, a combination of chemical biology with mass spectrometry has transformed target deconvolution. This review discusses modification-free chemoproteomic approaches that leverage the change in protein thermodynamics induced by small molecule ligand binding. Unlike modification-based methods relying on enriching specific protein targets, these approaches offer proteome-wide evaluations, driven by advancements in mass spectrometry sensitivity, increasing proteome coverage and quantitation methods. Advances in methods based on denaturation/precipitation by thermal or chemical denaturation, or by protease degradation are evaluated, emphasising the evolving landscape of chemoproteomics and its potential impact on future drug-development strategies.

Sensitive N-Glycopeptide Profiling of Single and Rare Cells Using an Isobaric Labeling Strategy without Enrichment

Single-cell omics is critical in revealing population heterogeneity, discovering unique features of individual cells, and identifying minority subpopulations of interest. As one of the major post-translational modifications, protein N-glycosylation plays crucial roles in various important biological processes. Elucidation of the variation in N-glycosylation patterns at single-cell resolution may largely facilitate the understanding of their key roles in the tumor microenvironment and immune therapy. However, comprehensive N-glycoproteome profiling for single cells has not been achieved due to the extremely limited sample amount and incompatibility with the available enrichment strategies. Here, we have developed an isobaric labeling-based carrier strategy for highly sensitive intact N-glycopeptide profiling for single cells or a small number of rare cells without enrichment. Isobaric labeling has unique multiplexing properties, by which the "total" signal from all channels triggers MS/MS fragmentation for N-glycopeptide identification, while the reporter ions provide quantitative information. In our strategy, a carrier channel using N-glycopeptides obtained from bulk-cell samples significantly improved the "total" signal of N-glycopeptides and, therefore, promoted the first quantitative analysis of averagely 260 N-glycopeptides from single HeLa cells. We further applied this strategy to study the regional heterogeneity of N-glycosylation of microglia in mouse brain and discovered region-specific N-glycoproteome patterns and cell subtypes. In conclusion, the glycocarrier strategy provides an attractive solution for sensitive and quantitative N-glycopeptide profiling of single/rare cells that cannot be enriched by traditional workflows.

UTP18-mediated p21 mRNA instability drives adenoma-carcinoma progression in colorectal cancer

Colorectal cancer (CRC) often develops slowly from adenoma, but the underlying mechanism remains unclear, hampering the prevention or treatment of colorectal adenoma-carcinoma progression. In this study, we use in-depth quantitative proteomics combined with survival analysis, revealing that the ribosome protein U3 small nucleolar RNA-associated protein 18 homolog (UTP18) is consistently upregulated in the progression of colorectal adenoma to carcinoma and is associated with adenoma recurrence, effective serodiagnosis, and poor prognosis of CRC. Furthermore, deSUMOylation induces the nucleocytoplasmic transport of UTP18, driving cell-cycle progression and tumorigenesis via mediation of the instability of p21 mRNA. In addition, the growth and ribosome biogenesis of adenoma organoids is found to be promoted by overexpression of UTP18. Thus, UTP18 contributes to multiple roles in adenogenesis and malignancy of CRC, suggesting that it could be a potential biomarker and drug target for colorectal adenoma and cancer.

Experimental strategies to improve drug-target identification in mass spectrometry-based thermal stability assays

Mass spectrometry (MS)-based thermal stability assays have recently emerged as one of the most promising solutions for the identification of protein-ligand interactions. Here, we have investigated eight combinations of several recently introduced MS-based advancements, including the Phase-Constrained Spectral Deconvolution Method, Field Asymmetric Ion Mobility Spectrometry, and the implementation of a carrier sample as improved MS-based acquisition approaches for thermal stability assays (iMAATSA). We used intact Jurkat cells treated with a commercially available MEK inhibitor, followed by heat treatment, to prepare a set of unfractionated isobarically-labeled proof-of-concept samples to compare the performance of eight different iMAATSAs. Finally, the best-performing iMAATSA was compared to a conventional approach and evaluated in a fractionation experiment. Improvements of up to 82% and 86% were demonstrated in protein identifications and high-quality melting curves, respectively, over the conventional approach in the proof-of-concept study, while an approximately 12% improvement in melting curve comparisons was achieved in the fractionation experiment.

Challenges in neoantigen-directed therapeutics

A fundamental prerequisite for the efficacy of cancer immunotherapy is the presence of functional, antigen-specific T cells within the tumor. Neoantigen-directed therapy is a promising strategy that aims at targeting the host's immune response against tumor-specific antigens, thereby eradicating cancer cells. Initial forays have been made in clinical environments utilizing vaccines and adoptive cell therapy; however, many challenges lie ahead. We provide an in-depth overview of the current state of the field with an emphasis on in silico neoantigen discovery and the clinical aspects that need to be addressed to unlock the full potential of this therapy.

Thermal proteome profiling: Insights into protein modifications, associations, and functions

Tracking proteins' biophysical characteristics on a proteome-wide scale can provide valuable information on their functions and interactions. Thermal proteome profiling (TPP) is a multiplexed quantitative proteomics approach that measures changes in protein thermal stability-a key biophysical property-across different cellular states. Developed in 2014, as a target-deconvolution assay for drugs and other small molecules, TPP has since evolved to a system-level biochemical omics technique providing insights into context-dependent changes in protein states. In this review, we summarise key advances in the experimental and data analysis pipeline that have aided this transformation and discuss the recent developments and applications of TPP.

Boost-DiLeu: Enhanced Isobaric N,N-Dimethyl Leucine Tagging Strategy for a Comprehensive Quantitative Glycoproteomic Analysis

Intact glycopeptide analysis has been of great interest because it can elucidate glycosylation site information and glycan structural composition at the same time. However, mass spectrometry (MS)-based glycoproteomic analysis is hindered by the low abundance and poor ionization efficiency of glycopeptides. Relatively large amounts of starting materials are needed for the enrichment, which makes the identification and quantification of intact glycopeptides from samples with limited quantity more challenging. To overcome these limitations, we developed an improved isobaric labeling strategy with an additional boosting channel to enhance N,N-dimethyl leucine (DiLeu) tagging-based quantitative glycoproteomic analysis, termed as Boost-DiLeu. With the integration of a one-tube sample processing workflow and high-pH fractionation, 3514 quantifiable N-glycopeptides were identified from 30 μg HeLa cell tryptic digests with reliable quantification performance. Furthermore, this strategy was applied to human cerebrospinal fluid (CSF) samples to differentiate N-glycosylation profiles between Alzheimer's disease (AD) patients and non-AD donors. The results revealed processes and pathways affected by dysregulated N-glycosylation in AD, including platelet degranulation, cell adhesion, and extracellular matrix, which highlighted the involvement of N-glycosylation aberrations in AD pathogenesis. Moreover, weighted gene coexpression network analysis (WGCNA) showed nine modules of glycopeptides, two of which were associated with the AD phenotype. Our results demonstrated the feasibility of using this strategy for in-depth glycoproteomic analysis of size-limited clinical samples. Taken together, we developed and optimized a strategy for the enhanced comprehensive quantitative intact glycopeptide analysis with DiLeu labeling, showing significant promise for identifying novel therapeutic targets or biomarkers in biological systems with a limited sample quantity.

Thermal Proteome Profiling Reveals the O-GlcNAc-Dependent Meltome

Posttranslational modifications alter the biophysical properties of proteins and thereby influence cellular physiology. One emerging manner by which such modifications regulate protein functions is through their ability to perturb protein stability. Despite the increasing interest in this phenomenon, there are few methods that enable global interrogation of the biophysical effects of posttranslational modifications on the proteome. Here, we describe an unbiased proteome-wide approach to explore the influence of protein modifications on the thermodynamic stability of thousands of proteins in parallel. We apply this profiling strategy to study the effects of O-linked N-acetylglucosamine (O-GlcNAc), an abundant modification found on hundreds of proteins in mammals that has been shown in select cases to stabilize proteins. Using this thermal proteomic profiling strategy, we identify a set of 72 proteins displaying O-GlcNAc-dependent thermostability and validate this approach using orthogonal methods targeting specific proteins. These collective observations reveal that the majority of proteins influenced by O-GlcNAc are, surprisingly, destabilized by O-GlcNAc and cluster into distinct macromolecular complexes. These results establish O-GlcNAc as a bidirectional regulator of protein stability and provide a blueprint for exploring the impact of any protein modification on the meltome of, in principle, any organism.

Phosphoproteome Profiling Using an Isobaric Carrier without the Need for Phosphoenrichment

Phosphorylation is a crucial component of cellular signaling cascades. It controls a variety of biological cellular functions, including cell growth and apoptosis. Owing to the low stoichiometry of phosphorylated proteins, the enrichment of phosphopeptides prior to LC-MS/MS is necessary for comprehensive phosphoproteome analysis, and quantitative phosphoproteomic workflows are typically limited by the amount of sample required. To address this issue, we developed an easy-to-establish, widely applicable, and reproducible strategy to increase phosphoproteomic signals from a small amount of sample without a phosphoenrichment step. By exploiting the multiplexing nature of isobaric labeling to generate a merged signal from multiple samples, and using a larger amount of enriched phosphopeptides as a carrier, we were able to increase trace amounts of phosphopeptides in the unpurified sample to an identifiable level and perform quantification using the reporter ion intensity of the isobaric tag. Our results showed that >1400 phosphopeptides were quantified from 250 ng of tryptic peptides prepared from cells. In a proof-of-concept of our strategy, we distinguished three types of lung cancer cell lines based on their quantitative phosphoproteomic data and identified changes in the phosphoproteome induced by drug treatment.

Understanding the effect of carrier proteomes in single cell proteomic studies - key lessons

INTRODUCTION

Mass spectrometry based single cell proteomics (scMS) is experiencing rapid evolution due to the increased sensitivity of mass spectrometers as well as advances in multiplexing and sample preparation. To date, researchers have focused on two general approaches to scMS: label free and isobaric label based multiplexing. While label free analysis provides straightforward sample preparation and a clear path to automation, it currently lacks the throughput necessary to practically analyze thousands of single cells. Multiplexed analysis utilizing isobaric labels requires additional sample manipulation, but increases throughput such that analyzing thousands of cells is currently achievable. A key feature of multiplexed scMS experiments is a 'carrier proteome' - a sample added at 25x-500x the single cell samples that increases the number of proteins that can be identified in an MS analysis.

AREAS COVERED

Here, we review early examples of carrier proteomes in quantitative proteomics before summarizing advantages and challenges of using a carrier proteome in scMS experiments.

EXPERT OPINION

We conclude that the addition of carrier proteomes improves depth of identification for scMS, but high levels of carrier proteomes can have adverse effects on quantitative accuracy and precision.

Scaling Up Single-Cell Proteomics

Single-cell tandem MS has enabled analyzing hundreds of single cells per day and quantifying thousands of proteins across the cells. The broad dissemination of these capabilities can empower the dissection of pathophysiological mechanisms in heterogeneous tissues. Key requirements for achieving this goal include robust protocols performed on widely accessible hardware, robust quality controls, community standards, and automated data analysis pipelines that can pinpoint analytical problems and facilitate their timely resolution. Toward meeting these requirements, this perspective outlines both existing resources and outstanding opportunities, such as parallelization, for catalyzing the wide dissemination of quantitative single-cell proteomics analysis that can be scaled up to tens of thousands of single cells. Indeed, simultaneous parallelization of the analysis of peptides and single cells is a promising approach for multiplicative increase in the speed of performing deep and quantitative single-cell proteomics. The community is ready to begin a virtuous cycle of increased adoption fueling the development of more technology and resources for single-cell proteomics that in turn drive broader adoption, scientific discoveries, and clinical applications.