scholarly journals Water droplet-in-oil digestion method for single-cell proteomics

2021 ◽  
Author(s):  
Takeshi Masuda ◽  
Yuma Inamori ◽  
Arisu Furukawa ◽  
Kazuki Momosaki ◽  
Chih-Hsiang Chang ◽  
...  

Recent advances in single-cell proteomics highlight the promise of sensitive analyses in limited cell populations. However, technical challenges remain for sample recovery, throughput, and versatility. Here, we first report a water droplet-in-oil digestion (WinO) method based on carboxyl-coated beads and phase transfer surfactants for proteomic analysis using limited sample amounts. This method was developed to minimize the contact area between the sample solution and the container to reduce the loss of proteins and peptides by adsorption. This method increased protein and peptide recovery 10-fold as well as the number of quantified transmembrane proteins compared to an in-solution digestion (ISD) method. The proteome profiles obtained from 100 cells using the WinO method highly correlated with those from 10000 cells using the ISD method. We successfully applied the WinO method to single-cell proteomics and quantified 462 proteins. Using the WinO method, samples can be easily prepared in a multi-well plate, making it a widely applicable and suitable method for single-cell proteomics.

2021 ◽  
Vol 7 (10) ◽  
pp. eabc5464
Author(s):  
Kiya W. Govek ◽  
Emma C. Troisi ◽  
Zhen Miao ◽  
Rachael G. Aubin ◽  
Steven Woodhouse ◽  
...  

Highly multiplexed immunohistochemistry (mIHC) enables the staining and quantification of dozens of antigens in a tissue section with single-cell resolution. However, annotating cell populations that differ little in the profiled antigens or for which the antibody panel does not include specific markers is challenging. To overcome this obstacle, we have developed an approach for enriching mIHC images with single-cell RNA sequencing data, building upon recent experimental procedures for augmenting single-cell transcriptomes with concurrent antigen measurements. Spatially-resolved Transcriptomics via Epitope Anchoring (STvEA) performs transcriptome-guided annotation of highly multiplexed cytometry datasets. It increases the level of detail in histological analyses by enabling the systematic annotation of nuanced cell populations, spatial patterns of transcription, and interactions between cell types. We demonstrate the utility of STvEA by uncovering the architecture of poorly characterized cell types in the murine spleen using published cytometry and mIHC data of this organ.


Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3126
Author(s):  
Dominik Saul ◽  
Robyn Laura Kosinsky

The human aging process is associated with molecular changes and cellular degeneration, resulting in a significant increase in cancer incidence with age. Despite their potential correlation, the relationship between cancer- and ageing-related transcriptional changes is largely unknown. In this study, we aimed to analyze aging-associated transcriptional patterns in publicly available bulk mRNA-seq and single-cell RNA-seq (scRNA-seq) datasets for chronic myelogenous leukemia (CML), colorectal cancer (CRC), hepatocellular carcinoma (HCC), lung cancer (LC), and pancreatic ductal adenocarcinoma (PDAC). Indeed, we detected that various aging/senescence-induced genes (ASIGs) were upregulated in malignant diseases compared to healthy control samples. To elucidate the importance of ASIGs during cell development, pseudotime analyses were performed, which revealed a late enrichment of distinct cancer-specific ASIG signatures. Notably, we were able to demonstrate that all cancer entities analyzed in this study comprised cell populations expressing ASIGs. While only minor correlations were detected between ASIGs and transcriptome-wide changes in PDAC, a high proportion of ASIGs was induced in CML, CRC, HCC, and LC samples. These unique cellular subpopulations could serve as a basis for future studies on the role of aging and senescence in human malignancies.


Cancers ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 5658
Author(s):  
Donát Alpár ◽  
Bálint Egyed ◽  
Csaba Bödör ◽  
Gábor T. Kovács

Single-cell sequencing (SCS) provides high-resolution insight into the genomic, epigenomic, and transcriptomic landscape of oncohematological malignancies including pediatric leukemia, the most common type of childhood cancer. Besides broadening our biological understanding of cellular heterogeneity, sub-clonal architecture, and regulatory network of tumor cell populations, SCS can offer clinically relevant, detailed characterization of distinct compartments affected by leukemia and identify therapeutically exploitable vulnerabilities. In this review, we provide an overview of SCS studies focused on the high-resolution genomic and transcriptomic scrutiny of pediatric leukemia. Our aim is to investigate and summarize how different layers of single-cell omics approaches can expectedly support clinical decision making in the future. Although the clinical management of pediatric leukemia underwent a spectacular improvement during the past decades, resistant disease is a major cause of therapy failure. Currently, only a small proportion of childhood leukemia patients benefit from genomics-driven therapy, as 15–20% of them meet the indication criteria of on-label targeted agents, and their overall response rate falls in a relatively wide range (40–85%). The in-depth scrutiny of various cell populations influencing the development, progression, and treatment resistance of different disease subtypes can potentially uncover a wider range of driver mechanisms for innovative therapeutic interventions.


2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
D Bongiovanni ◽  
M Klug ◽  
O Lazareva ◽  
K Kirmes ◽  
M Biasi ◽  
...  

Abstract Background Reticulated platelets (RPs) are young, hyper-reactive thrombocytes that contain more RNA compared with mature platelets (MPs). The measurement of RPs level in peripheral blood with point-of-care systems is fast, reproducible, and inexpensive. Elevated RPs in peripheral blood predict adverse events in patients with acute and chronic coronary syndrome through unknown mechanisms. Preliminary transcriptome analyses reported an enrichment of pro-thrombotic transcripts. However, proteomic analyses are not available, and the biological features of RPs are largely unknown. Purpose We aimed to perform the largest proteomic characterization of RPs using mass cytometry with single-cell resolution in patients with chronic coronary syndrome (CCS) undergoing dual antiplatelet therapy (DAPT). Methods Thrombocytes from peripheral blood of CCS patients were isolated, prepared for mass cytometry (CyTOF) and stained with a custom-made CyTOF-panel of 20 antibodies targeting important transmembrane proteins (anti-CD9, anti-CD29, anti-CD31, anti-CD36-, anti-CD40, anti-CD41, anti-CD42a, anti-CD42b-, anti-CD47, anti-CD61, anti-CD62P-, anti-CD63, anti-CD69, anti-CD107a, anti-CD154, anti-GPVI, antiGPIIb/GPIIIa complex, anti-Par1, anti-PEAR-1 and the negative control anti-CD3 coupled with different metal isotopes). Two samples were prepared from each donor: one baseline sample (non-stimulated platelets) and one sample stimulated with 10 μM thrombin receptor-activating peptide (TRAP). According to previous experiences and common practice, we detected RPs and MPs based on their RNA content. We analyzed the results with a custom bioinformatic pipeline. Results 13 patients with CCS on DAPT were included in this study. Mass cytometry highlighted an expression heterogeneity of relevant transmembrane proteins in thrombocytes of CCS patients (Figure 1A-B colored according to expression level: from blue-low to red-high). CyTOF detected an upregulation of important transmembrane receptors in RPs compared to MPs in quiescent platelets: GPVI (p<0.0001), PAR-1 (p<0.0001), GPIX (p<0.0001), and GPIbα (p<0.0001, Figure 1C). After TRAP-stimulation, RPs expressed higher levels of the activation markers P-Selectin (p=0.0016) and LAMP-3 (CD63, p<0.0001) compared to MPs confirming RPs hyperactivity (Figure 1D). Conclusion We here describe the first biological proteomic characterization with single-cell resolution of RPs biology in CCS patients. The upregulation of the activation markers P-Selectin and LAMP-3 as well as of specific transmembrane proteins as the collagen receptor GPVI and the thrombin receptor PAR-1 in patients treated with DAPT (schematic overview in Figure 2) provides the first solid biomolecular explanation of RPs hyper-reactivity and involvement in cardiovascular disease. Moreover, these results offer unexplored therapeutic targets to tailor antiplatelet therapy based on platelet protein expression in patients with elevated RPs FUNDunding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): German Center for Cardiovascular Research (DZHK) Figure 1. Platelet expression Figure 2. Schematic overview


2021 ◽  
Author(s):  
Yakir A Reshef ◽  
Laurie Rumker ◽  
Joyce B Kang ◽  
Aparna Nathan ◽  
Megan B Murray ◽  
...  

As single-cell datasets grow in sample size, there is a critical need to characterize cell states that vary across samples and associate with sample attributes like clinical phenotypes. Current statistical approaches typically map cells to cell-type clusters and examine sample differences through that lens alone. Here we present covarying neighborhood analysis (CNA), an unbiased method to identify cell populations of interest with greater flexibility and granularity. CNA characterizes dominant axes of variation across samples by identifying groups of very small regions in transcriptional space, termed neighborhoods, that covary in abundance across samples, suggesting shared function or regulation. CNA can then rigorously test for associations between any sample-level attribute and the abundances of these covarying neighborhood groups. We show in simulation that CNA enables more powerful and accurate identification of disease-associated cell states than a cluster-based approach. When applied to published datasets, CNA captures a Notch activation signature in rheumatoid arthritis, redefines monocyte populations expanded in sepsis, and identifies a previously undiscovered T-cell population associated with progression to active tuberculosis.


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