Single-cell Mass Spectrometry Research Articles

Longitudinal dynamic single-cell mass cytometry analysis of peripheral blood mononuclear cells in COVID-19 patients within 6 months after viral RNA clearance

This study investigates the longitudinal dynamic changes in immune cells in COVID-19 patients over an extended period after recovery, as well as the interplay between immune cells and antibodies. Leveraging single-cell mass spectrometry, we selected six COVID-19 patients and four healthy controls, dissecting the evolving landscape within six months post-viral RNA clearance, alongside the levels of anti-spike protein antibodies. The T cell immunophenotype ascertained via single-cell mass spectrometry underwent validation through flow cytometry in 37 samples. Our findings illuminate that CD8 + T cells, gamma-delta (gd) T cells, and NK cells witnessed an increase, in contrast to the reduction observed in monocytes, B cells, and double-negative T (DNT) cells over time. The proportion of monocytes remained significantly elevated in COVID-19 patients compared to controls even after six-month. Subpopulation-wise, an upsurge manifested within various T effector memory subsets, CD45RA + T effector memory, gdT, and NK cells, whereas declines marked the populations of DNT, naive and memory B cells, and classical as well as non-classical monocytes. Noteworthy associations surfaced between DNT, gdT, CD4 + T, NK cells, and the anti-S antibody titer. This study reveals the changes in peripheral blood mononuclear cells of COVID-19 patients within 6 months after viral RNA clearance and sheds light on the interactions between immune cells and antibodies. The findings from this research contribute to a better understanding of immune transformations during the recovery from COVID-19 and offer guidance for protective measures against reinfection in the context of viral variants.

Single-cell proteomics reveals decreased abundance of proteostasis and meiosis proteins in advanced maternal age oocytes.

Advanced maternal age is associated with a decline in oocyte quality, which often leads to reproductive failure in humans. However, the mechanisms behind this age-related decline remain unclear. To gain insights into this phenomenon, we applied plexDIA, a multiplexed, single-cell mass spectrometry method, to analyze the proteome of oocytes from both young women and women of advanced maternal age. Our findings primarily revealed distinct proteomic profiles between immature fully grown germinal vesicle and mature metaphase II oocytes. Importantly, we further show that a woman's age is associated with changes in her oocyte proteome. Specifically, when compared to oocytes obtained from young women, advanced maternal age oocytes exhibited lower levels of the proteasome and TRiC complex, as well as other key regulators of proteostasis and meiosis. This suggests that aging adversely affects the proteostasis and meiosis networks in human oocytes. The proteins identified in this study hold potential as targets for improving oocyte quality and may guide future studies into the molecular processes underlying oocyte aging.

Unraveling the Immune Profile in Emphysema Using Single-Cell and Imaging Mass Spectrometry.

Unraveling the Immune Profile in Emphysema Using Single-Cell and Imaging Mass Spectrometry.

Development of a highly efficient solubilization method for mass spectrometric analysis of phospholipids in living single cells.

Phospholipids are vital constituents of the cell membrane and aid in signal transduction. Phospholipid profiles vary distinctively with the cell type. Notably, specific phospholipid molecules are present in significantly higher or lower concentrations in cancer cells versus normal cells. In this study, live single-cell mass spectrometry (MS) was developed for analyzing phospholipids at the single-cell level. This method facilitates rapid molecular analysis of cells under microscopic observation. For nanoelectrospray ionization, phospholipids were extracted from single cells isolated in a glass capillary through a high-efficiency process. Cell-derived phosphatidylcholines were detected with high sensitivity when trehalose C14 was added as a solubilizing reagent. Trehalose C14 can solubilize cells at low concentrations owing to its low critical micelle concentration, and exerts minimal matrix effects (such as suppressing ionization and causing peak overlap) in the MS analysis of cellular molecules. Analyses of phospholipids in Raji and HEV0070 cells using the developed method revealed specific peaks of phosphatidylcholine and sphingomyelin in the respective cells. The developed technique not only affords phospholipid profiles at the single-cell level, but also holds promise for identifying biomarkers associated with various diseases, particularly cancer.

Abstract 5255: A B7-H3-CAR-modified Vδ1 T cells showed potentanti-solid tumor potential

Abstract Background: CAR-αβT cells have made limited advancement in treating solid tumors. Vδ1 T cells, a subtype of γδT cells, are rare in human peripheral blood, but they are the main tissue-resident immune cells found in epithelial and mucosal tissues. This suggests that Vδ1 T cells might be a potential modality for treating solid tumors. To explore this possibility, we hypothesized that Vδ1 T cells modified with B7-H3 CAR (B7-H3-CAR-Vδ1 T) could have great potential of anti-solid tumor activity, making them a promising candidate for further development as a universal cellular therapy product. Methods: A proprietary manufacturing procedure to produce Vδ1 T cells from the leukopak of healthy donors has been established under GMP compliance. The immune checkpoint molecule B7-H3 was selected as the target. The allogeneic B7-H3-CAR-Vδ1 T cells carrying IL-2 (UTAA06), which displayed the most prolonged anti-tumor activity, were chosen for comprehensive functional validation. Single-cell sequencing and mass spectrometry flow cytometry were utilized to characterize the biology of UTAA06. In vivo effectiveness of UTAA06 was confirmed in animal models. Results: A clinical-grade manufacturing process for Vδ1 T cells is developed. This process results in a purity of over 95% of Vδ1 T cells, with an expansion of more than 20,000-fold, and a CAR lentiviral transduction efficiency of over 50%.žSingle-cell sequencing and mass cytometry analysis both demonstrated that the Vδ1 T cells produced by our approach exhibited high expression levels of natural cytotoxic receptors (including NKG2D, DNAM1, and NKp series receptors), chemokine receptors (such as CXCR3 and CXCR6), anti-tumor related molecules (such as CD27 and CD137), and low expression levels of inhibitory molecules (such as PD1 and LAG3).ž UTAA06 cells did not produce IL17A, which is a signal protein with pro-tumor activity. Meanwhile, UTAA06 demonstrated significant and specific inhibitory effects on the growth of various solid tumor cell lines.žUTAA06 cells were found to significantly suppress tumor cell growth in solid tumor mouse models. The complete remission (CR) for each tumor model was 83.3% of neuroblastoma (SK-N-AS, N=6), 66.7% of pancreatic cancer (SW1990, N=6), 100% of lung cancer (A549, N=6), and 70% of colorectal cancer (HCT-15, N=10) respectively. In addition, a potent capacity of UTAA06 to penetrate tumor tissues with a favorable safety profile in mice was observed. Conclusion: UTAA06 exhibited extraordinary anticancer properties both in vitro and in vivo against solid tumors. Additionally, the outstanding manufacturing process of UTAA06 will facilitate the clinical application of this product. Citation Format: Licui Jiang, Changsong Qi, Fengtao You, Shufen Xiang, Ping Zhang, Min Wang, Hai Wu, Kunmin Yan, Jiequn Huang, Huimin Meng, Nan Yang, Shirley Zhang, Lin Shen, Lin Yang. A B7-H3-CAR-modified Vδ1 T cells showed potentanti-solid tumor potential [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5255.

EIF2Ss, a Novel c-Myc-Correlated Gene Family, is Associated with Poor Prognosis and Immune Infiltration in Pancreatic Adenocarcinoma.

Pancreatic adenocarcinoma (PAAD) is a highly malignant tumor in urgent need of novel diagnostics, prognostic markers, and treatments. Eukaryotic translation initiation factor 2 subunits (EIF2Ss), comprising Eukaryotic translation initiation factor 2 subunit alpha (EIF2S1), Eukaryotic translation initiation factor 2 subunit beta (EIF2S2), and Eukaryotic translation initiation factor 2 subunit gamma (EIF2S3), is a family of eukaryotic initiation factors that participate in early protein synthesis and are crucial for tumor initiation and progression. However, the role of EIF2Ss in PAAD has yet to be reported. The aim of this study was therefore to analyze EIF2Ss in relation to the diagnosis, prognosis, and treatment of PAAD. The cancer genome atlas (TCGA) database was used to investigate gene expression and patient survival. Gene alterations, immune cell infiltration, and immune checkpoints in PAAD were also evaluated. Univariate and multivariate analysis, nomograms, calibration curves, and Decision Curve Analysis (DCA) diagrams were used to develop and evaluate a prediction model for patient outcome. Single-cell RNA-seq (scRNA) analysis, functional enrichment, co-IP assay, mass spectrometry, and western blot were used to study the relationship between EIF2Ss and c-myc in PAAD. EIF2Ss are over-expressed in PAAD tissue and are associated with poor prognosis. The frequency of EIF2S1, EIF2S2, and EIF2S3 gene alteration in PAAD was 0.2%, 0.4%, and 0.2%, respectively. High EIF2Ss expression was associated with Th2 cell infiltration, whereas low expression was associated with pDC infiltration. Moreover, EIF2Ss expression was positively correlated with the expression of the NT5E, ULBP1, PVR, CD44, IL10RB, and CD276 checkpoints. A prediction model developed using EIF2Ss and important clinicopathologic features showed good predictive value for the overall survival of PAAD patients. ScRNA-Seq data showed that EIF2Ss was associated with enrichment for endothelial cells, fibroblasts, malignant cells, and ductal cells. EIF2Ss expression was also correlated with adipogenesis, interferon-alpha response, epithelial-mesenchymal transition, myc targets, G2M checkpoint, oxidative phosphorylation, and hypoxia. Functional enrichment analysis of EIF2Ss showed a close correlation with the myc pathway, and interactions between EIF2Ss and c-myc were confirmed by co-IP assay and mass spectrometry. Importantly, knockdown of c-myc decreased the expression of EIF2S1, EIF2S2, and EIF2S3 in PAAD cells. EIF2Ss were found to have significant clinical implications for the prognosis and treatment of PAAD. Inhibition of c-myc caused the downregulation of EIF2S1, EIF2S2, and EIF2S3 expression.

Microfluidic Impedance Cytometry Enabled One-Step Sample Preparation for Efficient Single-Cell Mass Spectrometry.

Single-cell mass spectrometry (MS) is significant in biochemical analysis and holds great potential in biomedical applications. Efficient sample preparation like sorting (i.e., separating target cells from the mixed population) and desalting (i.e., moving the cells off non-volatile salt solution) is urgently required in single-cell MS. However, traditional sample preparation methods suffer from complicated operation with various apparatus, or insufficient performance. Herein, a one-step sample preparation strategy by leveraging label-free impedance flow cytometry (IFC) based microfluidics is proposed. Specifically, the IFC framework to characterize and sort single-cells is adopted. Simultaneously with sorting, the target cell is transferred from the local high-salinity buffer to the MS-compatible solution. In this way, one-step sorting and desalting are achieved and the collected cells can be directly fed for MS analysis. A high sorting efficiency (>99%), cancer cell purity (≈87%), and desalting efficiency (>99%), and the whole workflow of impedance-based separation and MS analysis of normal cells (MCF-10A) and cancer cells (MDA-MB-468) are verified. As a standalone sample preparation module, the microfluidic chip is compatible with a variety of MS analysis methods, and envisioned to provide a new paradigm in efficient MS sample preparation, and further in multi-modal (i.e., electrical and metabolic) characterization of single-cells.

Screening Metabolic Biomarkers in KRAS Mutated Mouse Acinar and Human Pancreatic Cancer Cells via Single-Cell Mass Spectrometry.

Pancreatic cancer is a highly aggressive and rapidly progressing disease, often diagnosed in advanced stages due to the absence of early noticeable symptoms. The KRAS mutation is a hallmark of pancreatic cancer, yet the underlying mechanisms driving pancreatic carcinogenesis remain elusive. Cancer cells display significant metabolic heterogeneity, which is relevant to the pathogenesis of cancer. Population measurements may obscure information about the metabolic heterogeneity among cancer cells. Therefore, it is crucial to analyze metabolites at the single-cell level to gain a more comprehensive understanding of metabolic heterogeneity. In this study, we employed a 3D-printed ionization source for metabolite analysis in both mice and human pancreatic cancer cells at the single-cell level. Using advanced machine learning algorithms and mass spectral feature selection, we successfully identified 23 distinct metabolites that are statistically significantly different in KRAS mutant human pancreatic cancer cells and mouse acinar cells bearing the oncogenic KRAS mutation. These metabolites encompass a variety of chemical classes, including organic nitrogen compounds, organic acids and derivatives, organoheterocyclic compounds, benzenoids, and lipids. These findings shed light on the metabolic remodeling associated with KRAS-driven pancreatic cancer initiation and indicate that the identified metabolites hold promise as potential diagnostic markers for early detection in pancreatic cancer patients.

Osteomacs promote maintenance of murine hematopoiesis through megakaryocyte-induced upregulation of Embigin and CD166

Maintenance of hematopoietic stem cell (HSC) function in the niche is an orchestrated event. Osteomacs (OM) are key cellular components of the niche. Previously, we documented that osteoblasts, OM, and megakaryocytes interact to promote hematopoiesis. Here, we further characterize OM and identify megakaryocyte-induced mediators that augment the role of OM in the niche. Single-cell mRNA-seq, mass spectrometry, and CyTOF examination of megakaryocyte-stimulated OM suggested that upregulation of CD166 and Embigin on OM augment their hematopoiesis maintenance function. CD166 knockout OM or shRNA-Embigin knockdown OM confirmed that the loss of these molecules significantly reduced the ability of OM to augment the osteoblast-mediated hematopoietic-enhancing activity. Recombinant CD166 and Embigin partially substituted for OM function, characterizing both proteins as critical mediators of OM hematopoietic function. Our data identify Embigin and CD166 as OM-regulated critical components of HSC function in the niche and potential participants in various invitro manipulations of stem cells.

High-throughput single-cell mass spectrometry enables metabolic network analysis by resolving phospholipid C[double bond, length as m-dash]C isomers.

Single-cell mass spectrometry (MS) is an essential technology for sensitive and multiplexed analysis of metabolites and lipids for cell phenotyping and pathway studies. However, the structural elucidation of lipids from single cells remains a challenge, especially in the high-throughput scenario. Technically, there is a contradiction between the inadequate sample amount (i.e. a single cell, 0.5-20 pL) for replicate or multiple analysis, on the one hand, and the high metabolite coverage and multidimensional structure analysis that needs to be performed for each single cell, on the other hand. Here, we have developed a high-throughput single-cell MS platform that can perform both lipid profiling and lipid carbon-carbon double bond (C[double bond, length as m-dash]C) location isomer resolution analysis, aided by C[double bond, length as m-dash]C activation in unsaturated lipids by the Paternò-Büchi (PB) reaction and tandem MS, termed single-cell structural lipidomics analysis. The method can achieve a single-cell analysis throughput of 51 cells per minute. A total of 145 lipids were structurally characterized at the subclass level, of which the relative abundance of 17 isomeric lipids differing in the location of C[double bond, length as m-dash]C from 5 lipid precursors was determined. While cell-to-cell variations in MS1-based lipid profiling can be large, an advantage of quantifying lipid C[double bond, length as m-dash]C location isomers is the significantly improved quantitation accuracy. For example, the relative standard deviations (RSDs) of the relative amounts of PC 34:1 C[double bond, length as m-dash]C position isomers in MDA-MB-468 cells are half smaller than those measured for PC 34:1 as a whole by MS1 abundance profiling. Taken together, the developed method can be effectively used for in-depth structural lipid metabolism network analysis by high-throughput analysis of 142 MDA-MB-468 human breast cancer cells.

Ferroptosis Inducers Upregulate PD-L1 in Recurrent Triple-Negative Breast Cancer.

(1) Background: Triple-negative breast cancer (TNBC) is a distinct subgroup of breast cancer presenting a high level of recurrence, and neo-adjuvant chemotherapy is beneficial in its therapy management. Anti-PD-L1 immunotherapy improves the effect of neo-adjuvant therapy in TNBC. (2) Methods: Immune-modulation and ferroptosis-related R-packages were developed for integrative omics analyses under ferroptosis-inducer treatments: TNBC cells stimulated with ferroptosis inducers (GSE173905, GSE154425), single cell data (GSE191246) and mass spectrometry on breast cancer stem cells. Clinical association analyses were carried out with breast tumors (TCGA and METABRIC cohorts). Protein-level validation was investigated through protein atlas proteome experiments. (3) Results: Erastin/RSL3 ferroptosis inducers upregulate CD274 in TNBC cells (MDA-MB-231 and HCC38). In breast cancer, CD274 expression is associated with overall survival. Breast tumors presenting high expression of CD274 upregulated some ferroptosis drivers associated with prognosis: IDO1, IFNG and TNFAIP3. At the protein level, the induction of Cd274 and Tnfaip3 was confirmed in breast cancer stem cells under salinomycin treatment. In a 4T1 tumor treated with cyclophosphamide, the single cell expression of Cd274 was found to increase both in myeloid- and lymphoid-infiltrated cells, independently of its receptor Pdcd1. The CD274 ferroptosis-driver score computed on a breast tumor transcriptome stratified patients on their prognosis: low score was observed in the basal subgroup, with a higher level of recurrent risk scores (oncotypeDx, ggi and gene70 scores). In the METABRIC cohort, CD274, IDO1, IFNG and TNFAIP3 were found to be overexpressed in the TNBC subgroup. The CD274 ferroptosis-driver score was found to be associated with overall survival, independently of TNM classification and age diagnosis. The tumor expression of CD274, TNFAIP3, IFNG and IDO1, in a biopsy of breast ductal carcinoma, was confirmed at the protein level (4) Conclusions: Ferroptosis inducers upregulate PD-L1 in TNBC cells, known to be an effective target of immunotherapy in high-risk early TNBC patients who received neo-adjuvant therapy. Basal and TNBC tumors highly expressed CD274 and ferroptosis drivers: IFNG, TNFAIP3 and IDO1. The CD274 ferroptosis-driver score is associated with prognosis and to the risk of recurrence in breast cancer. A potential synergy of ferroptosis inducers with anti-PD-L1 immunotherapy is suggested for recurrent TNBC.

SINGLE-CELL AND SPATIAL OMICS FOR MAPPING CELLULAR SENESCENCE IN HEALTH, AGING AND DISEASE

Abstract NIH SenNet consortium aims to dissect the heterogeneity of senescent cells (SnCs) and map their impact on the microenvironment at a single cell resolution and in the spatial tissue context, which requires the implementation of an array of omics technologies to comprehensively identify, characterize, and spatially profile SnCs across tissues in humans and mice. These technologies are broadly categorized into two groups –single cell omics and spatial mapping. To achieve single cell resolution and overcome the scarcity of SnCs, high-throughput single-cell and single-nucleus transcriptomic techniques have become a mainstay tool for surveying tens of thousands of cells to identify transcriptional signatures in rare cell populations, enabling discovery of potential new SnC biomarkers. Novel single cell mass spectrometry methods are developed for unbiased discovery of proteomic signatures of SnCs. A hallmark of SnCs is the senescence-associated secretory phenotype (SASP), which requires the use of proteomics, secretomics, metabolomics and lipidomics, especially SASP-associated extracellular vesicles, for comprehensive characterization of SAPS. High resolution molecular and cellular imaging of gene expression (e.g., MERFISH) or protein markers (e.g., CODEX) is critical for the study of SnCs in the large-scale tissue context. NGS-based spatial omics sequencing is poised to bridge the gap to realize both genome scale and cellular resolution in mapping SnCs in tissue. Novel technologies such as Seq-Scope and Pixel-Seq developed within SenNet further enabled subcellular resolution. SenNet investigators also developed spatially resolved epigenome and multi-omics sequencing techniques to link transcriptional or proteomic phenotype of SnCs to epigenetic mechanism. Further integration with high-resolution imaging makes spatial omics the crucial linchpin in connecting mechanistic underpinnings and molecular signatures with morphological features and spatial distribution. All these are critical for the construction of a map of SnCs and associated niches in the native tissue environment implicated in human health, aging, and disease, which is one of the main goals of the SenNet consortium.

Quantification of Nitric Oxide in Single Cells Using the Single-Probe Mass Spectrometry Technique.

Nitric oxide (NO) is a small molecule that plays important roles in biological systems and human diseases. The abundance of intracellular NO is tightly related to numerous biological processes. Due to cell heterogeneity, the intracellular NO amounts significantly vary from cell to cell, and therefore, any meaningful studies need to be conducted at the single-cell level. However, measuring NO in single cells is very challenging, primarily due to the extremely small size of single cells and reactive nature of NO. In the current studies, the quantitative reaction between NO and amlodipine, a compound containing the Hantzsch ester group, was performed in live cells. The product dehydro amlodipine was then detected by the Single-probe single-cell mass spectrometry technique to quantify NO in single cells. The experimental results indicated heterogeneous distributions of intracellular NO amounts in single cells with the existence of subpopulations.

Recent developments in ionization techniques for single-cell mass spectrometry.

The variation among individual cells plays a significant role in many biological functions. Single-cell analysis is advantageous for gaining insight into intricate biochemical mechanisms rarely accessible when studying tissues as a whole. However, measurement on a unicellular scale is still challenging due to unicellular complex composition, minute substance quantities, and considerable differences in compound concentrations. Mass spectrometry has recently gained extensive attention in unicellular analytical fields due to its exceptional sensitivity, throughput, and compound identification abilities. At present, single-cell mass spectrometry primarily concentrates on the enhancement of ionization methods. The principal ionization approaches encompass nanoelectrospray ionization (nano-ESI), laser desorption ionization (LDI), secondary ion mass spectrometry (SIMS), and inductively coupled plasma (ICP). This article summarizes the most recent advancements in ionization techniques and explores their potential directions within the field of single-cell mass spectrometry.

Single-cell proteomics: quantifying post-transcriptional regulation during development with mass-spectrometry.

Many developmental processes are regulated post-transcriptionally. Such post-transcriptional regulatory mechanisms can now be analyzed by robust single-cell mass spectrometry methods that allow accurate quantification of proteins and their modification in single cells. These methods can enable quantitative exploration of protein synthesis and degradation mechanisms that contribute to developmental cell fate specification. Furthermore, they may support functional analysis of protein conformations and activities in single cells, and thus link protein functions to developmental processes. This Spotlight provides an accessible introduction to single-cell mass spectrometry methods and suggests initial biological questions that are ripe for investigation.

Quantifying Cell Heterogeneity and Subpopulations Using Single Cell Metabolomics.

Mass spectrometry (MS) has become an indispensable tool for metabolomics studies. However, due to the lack of applicable experimental platforms, suitable algorithm, software, and quantitative analyses of cell heterogeneity and subpopulations, investigating global metabolomics profiling at the single cell level remains challenging. We combined the Single-probe single cell MS (SCMS) experimental technique with a bioinformatics software package, SinCHet-MS (Single Cell Heterogeneity for Mass Spectrometry), to characterize changes of tumor heterogeneity, quantify cell subpopulations, and prioritize the metabolite biomarkers of each subpopulation. As proof of principle studies, two melanoma cancer cell lines, the primary (WM115; with a lower drug resistance) and the metastatic (WM266-4; with a higher drug resistance), were used as models. Our results indicate that after the treatment of the anticancer drug vemurafenib, a new subpopulation emerged in WM115 cells, while the proportion of the existing subpopulations was changed in the WM266-4 cells. In addition, metabolites for each subpopulation can be prioritized. Combining the SCMS experimental technique with a bioinformatics tool, our label-free approach can be applied to quantitatively study cell heterogeneity, prioritize markers for further investigation, and improve the understanding of cell metabolism in human diseases and response to therapy.

Single-cell mass spectrometry studies of drug metabolism heterogeneity and primary resistance to gefitinib in non-small cell lung cancer cells

Patients with epidermal growth factor receptor (EGFR) wild-type non-small cell lung cancer (NSCLC) often show primary resistance to gefitinib therapy. It is thus necessary to study the metabolism of gefitinib in NSCLC cells to comprehensively reveal the reasons for the primary resistance of tumors. Herein, we develop a platform for studying drug metabolism heterogeneity based on single-cell mass spectrometry (sDMH-scMS) by integrating living-cell electrolaunching ionization MS (ILCEI-MS) and high-performance liquid chromatography-MS (HPLC-MS) analysis, and the primary resistance of NSCLC cells to gefitinib was studied using this platform. The ILCEI-MS analysis showed that approximately 11.9% of NSCLC single cells contained the gefitinib metabolite M11; HPLC-MS detection diluted the intensity of M11 in subpopulations and concealed the heterogeneity of drug metabolism in tumor single cells. The intensity of gefitinib in EGFR wild-type A549 cells was markedly lower than in mutant PC9 cells, and the intensity of gefitinib metabolites was significantly higher than in PC9 cells, suggesting that the primary resistance of NSCLC cells is related to gefitinib metabolism. Moreover, the combination of gefitinib and the drug-metabolizing enzyme inhibitor α-naphthoflavone was shown to overcome the primary resistance of the NSCLC cells. Overall, the results of this study are expected to be applicable for clinical drug resistance diagnosis and treatment at the single-cell level.

Efficient Sample Preparation System for Multi-Omics Analysis via Single Cell Mass Spectrometry.

Mass spectrometry (MS) has become a powerful tool for metabolome, lipidome, and proteome analyses. The efficient analysis of multi-omics in single cells, however, is still challenging in the manipulation of single cells and lack of in-fly cellular digestion and extraction approaches. Here, we present a streamlined strategy for highly efficient and automatic single-cell multi-omics analysis by MS. We developed a 10-pL-level microwell chip for housing individual single cells, whose proteins were found to be digested in 5 min, which is 144 times shorter than traditional bulk digestion. Besides, an automated picoliter extraction system was developed for sampling of metabolites, phospholipids, and proteins in tandem from the same single cell. Also, 2 min MS2 spectra were obtained from 700 pL solution of a single cell sample. In addition, 1391 proteins, phospholipids, and metabolites were detected from one single cell within 10 min. We further analyzed cells digested from cancer tissue samples, achieving up to 40% increase in cell classification accuracy using multi-omics analysis in comparison with single-omics analysis. This automated single-cell MS strategy is highly efficient in analyzing multi-omics information for investigation of cell heterogeneity and phenotyping for biomedical applications.

Proteomics mining of cancer hallmarks on a single-cell resolution.

Dysregulated proteome is an essential contributor in carcinogenesis. Protein fluctuations fuel the progression of malignant transformation, such as uncontrolled proliferation, metastasis, and chemo/radiotherapy resistance, which severely impair therapeutic effectiveness and cause disease recurrence and eventually mortality among cancer patients. Cellular heterogeneity is widely observed in cancer and numerous cell subtypes have been characterized that greatly influence cancer progression. Population-averaged research may not fully reveal the heterogeneity, leading to inaccurate conclusions. Thus, deep mining of the multiplex proteome at the single-cell resolution will provide new insights into cancer biology, to develop prognostic biomarkers and treatments. Considering the recent advances in single-cell proteomics, herein we review several novel technologies with particular focus on single-cell mass spectrometry analysis, and summarize their advantages and practical applications in the diagnosis and treatment for cancer. Technological development in single-cell proteomics will bring a paradigm shift in cancer detection, intervention, and therapy.

Chemical Decrosslinking-Based Peptide Characterization of Formaldehyde-Fixed Rat Pancreas Using Fluorescence-Guided Single-Cell Mass Spectrometry.

Approaches for the characterization of proteins/peptides in single cells of formaldehyde-fixed (FF) tissues via mass spectrometry (MS) are still under development. The lack of a general method for selectively eliminating formaldehyde-induced crosslinking is a major challenge. A workflow is shown for the high-throughput peptide profiling of single cells isolated from FF tissues, here the rodent pancreas, which possesses multiple peptide hormones from the islets of Langerhans. The heat treatment is enhanced by a collagen-selective multistep thermal process assisting efficient isolation of islets from the FF pancreas and, subsequently, their dissociation into single islet cells. Hydroxylamine-based chemical decrosslinking helped restore intact peptide signals from individual isolated cells. Subsequently, an acetone/glycerol-assisted cell dispersion was optimized for spatially resolved cell deposition onto glass slides, while a glycerol solution maintained the hydrated state of the cells. This sample preparation procedure allowed peptide profiling in FF single cells by fluorescence-guided matrix-assisted laser desorption ionization MS. Here, 2594 single islet cells were analyzed and 28 peptides were detected, including insulin C-peptides and glucagon. T-distributed stochastic neighbor embedding (t-SNE) data visualization demonstrated that cells cluster based on cell-specific pancreatic peptide hormones. This workflow expands the sample availability for single-cell MS characterization to a wide range of formaldehyde-treated tissue specimens stored in biobanks.