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 tumor 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, 1804-3349, 1778-3049 and 1074-2487 protein groups are quantified in single A549 cells (n = 37), HeLa cells (n = 44) and U2OS cells (n = 27), respectively. Benefiting from the flexible cell picking-up ability, we study tumor cell migration at the single cell proteome level, demonstrating the potential in practical biological research from single-cell insight.

Nowadays, 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 for the first time. This platform was applied to analyze single mouse oocytes at different meiotic maturation stages, reaching an average quantification depth of 19948 genes and 2663 protein groups in single mouse oocytes. This reliable quantitative two-omics dataset of single cells provided an important resource for understanding the relationship between the transcriptome and the proteome in cells. Based on the correlation analysis of RNAs and proteins in the same single cell, we demonstrated the expressive heterogeneity of transcriptome and proteome during the cellular biological process. Specially, we analyzed the meiosis regulatory network during oocyte maturation with an unprecedented depth at the single-cell level, and identified 30 transcript-protein pairs as specific oocyte maturational signatures, providing crucial insights into the regulatory features of transcription and translation during oocyte meiotic maturation.