Proteins analysis from an average cell population often overlooks the cellular heterogeneity of expressed effector molecules, and knowledge about the regulations of key biological processes may remain obscure. Therefore, the necessity of single-cell proteomics (SCP) technologies arises. Without microfluidic chip, expensive ultrasonic equipment, or reformed liquid chromatogram (LC) system, we established an Ultra-sensitive and Easy-to-use multiplexed Single-Cell Proteomic workflow (UE-SCP). Specifically, the flexible sorting system ensured outstanding cell activity, high accuracy, remarkable efficiency, and robustness during single-cell isolation. Multiplex isobaric labeling realized the high-throughput analysis in trapped ion mobility spectrometry coupled with quadrupole time-of-flight mass spectrometry (timsTOF MS). Using this pipeline, we achieved single-cell protein quantities to a depth of over 2,000 protein groups in two human cell lines, Hela and HEK-293T. A small batch experiment can identify and quantify more than 3200 protein groups in 32 single cells, while a large batch experiment can identify and quantify about 4000 protein groups in 96 single cells. All the 128 single cells from different cell lines could been unsupervised clustered based on their proteomes. After the integration of data quality control, data cleaning, and data analysis, we are confident that our UE-SCP platform will be easy-to-marketing popularization and will promote biological applications of single-cell proteomics.
In recent years, single-cell or low-input multi-omics techniques have brought a revolution in the study of pre-implantation embryo development. However, single-cell or low-input proteome research in this field is relatively underdeveloped, due to the limited source of mammalian embryo samples, the objective reality of high abundance zona pellucida proteins, and the lack of hypersensitive proteome technology. Here, a comprehensive solution of ultrasensitive proteome technology was developed for single-cell or low-input mouse embryos. Both deep coverage route and high-throughput route could significantly reduce the starting material and enhance the proteomic depth without any customized instrument. Using the deep coverage route, an average of 2,665 or 4,585 protein groups can be identified from 1 or 20 mouse zygotes respectively. Using the high-throughput route, 300 single mouse zygotes can be analysis in 8 days with an average of 2,371 proteins identified. With its popularization, we believe researchers can choose deep coverage or high-throughput technology routes according to their own conditions.
Conventional proteomic approaches neglect tissue heterogeneity and spatial localization information. Laser capture microdissection (LCM) can isolate specific cell populations or histological areas from heterogeneous tissue specimens while preserving spatial localization information. Formalin-fixed paraffin-embedded (FFPE) is currently a standardized method for long-term stable preservation of clinical tissue specimens. However, spatially resolved proteomics (SRP) studies of FFPE tissues by combined LCM and mass spectrometry (MS)-based proteomics face challenges, such as formalin-induced protein crosslinking limits protein extraction and digestion, protein loss during sample preparation, and the detectability of MS for trace tissues. Therefore, it is necessary to specifically develop SRP sample preparation methods and MS methods suitable for trace FFPE tissues. Here, we provide an SRP method suitable for trace FFPE tissues produced by LCM, termed LCM-Magnetic Trace Analysis (LCM-MTA), which can significantly increase the sensitivity, recovery, and integrality of SRP. The starting material has been reduced to about 15 cells, which resolution is comparable to existing spatially resolved transcriptome (SRT). We also apply our LCM-MTA into SRP studies on clinical colorectal cancer (CRC) tissues and accurately distinguish the functional differences of different cell types. In conclusion, LCM-MTA is a convenient, universal, and scalable method for SRP of trace FFPE tissues, which can be widely used in clinical and non-clinical research fields.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.