Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell.

The shotgun proteomic analysis is currently the most promising single-cell protein sequencing technology, however its identification level of ~1000 proteins per cell is still insufficient for practical applications. Here, we develop a pick-up single-cell proteomic analysis (PiSPA) workflow to achieve a deep identification capable of quantifying up to 3000 protein groups in a mammalian cell using the label-free quantitative method. The PiSPA workflow is specially established for single-cell samples mainly based on a nanoliter-scale microfluidic liquid handling robot, capable of achieving single-cell capture, pretreatment and injection under the pick-up operation strategy. Using this customized workflow with remarkable improvement in protein identification, 2449-3500, 2278-3257 and 1621-2904 protein groups are quantified in single A549 cells (n = 37), HeLa cells (n = 44) and U2OS cells (n = 27) under the DIA (MBR) mode, respectively. Benefiting from the flexible cell picking-up ability, we study HeLa cell migration at the single cell proteome level, demonstrating the potential in practical biological research from single-cell insight.

Simultaneous deep transcriptome and proteome profiling in a single mouse oocyte.

Although single-cell multi-omics technologies are undergoing rapid development, simultaneous transcriptome and proteome analysis of a single-cell individual still faces great challenges. Here, we developed a single-cell simultaneous transcriptome and proteome (scSTAP) analysis platform based on microfluidics, high-throughput sequencing, and mass spectrometry technology to achieve deep and joint quantitative analysis of transcriptome and proteome at the single-cell level, providing an important resource for understanding the relationship between transcription and translation in cells. This platform was applied to analyze single mouse oocytes at different meiotic maturation stages, reaching an average quantification depth of 19,948 genes and 2,663 protein groups in single mouse oocytes. In particular, we analyzed the correlation of individual RNA and protein pairs, as well as the meiosis regulatory network with unprecedented depth, and identified 30 transcript-protein pairs as specific oocyte maturational signatures, which could be productive for exploring transcriptional and translational regulatory features during oocyte meiosis.