Bubis Julia A, Arrey Tabiwang N, Damoc Eugen, Delanghe Bernard, Slovakova Jana, Sommer Theresa M, Kagawa Harunobu, Pichler Peter, Rivron Nicolas, Mechtler Karl, Matzinger Manuel
Research Institute of Molecular Pathology (IMP), Vienna BioCenter, Vienna, Austria.
Thermo Fisher Scientific, Bremen, Germany.
Nat Methods. 2025 Mar;22(3):510-519. doi: 10.1038/s41592-024-02559-1. Epub 2025 Jan 16.
Despite significant advancements in sample preparation, instrumentation and data analysis, single-cell proteomics is currently limited by proteomic depth and quantitative performance. Here we demonstrate highly improved depth of proteome coverage as well as accuracy and precision for quantification of ultra-low input amounts. Using a tailored library, we identify up to 7,400 protein groups from as little as 250 pg of HeLa cell peptides at a throughput of 50 samples per day. Using a two-proteome mix, we check for optimal parameters of quantification and show that fold change differences of 2 can still be successfully determined at single-cell-level inputs. Eventually, we apply our workflow to A549 cells, yielding a proteome coverage ranging from 1,801 to a maximum of >5,300 protein groups from a single cell depending on cell size and search strategy used, which allows for the study of dependencies between cell size and cell cycle phase. Additionally, our workflow enables us to distinguish between in vitro analogs of two human blastocyst lineages: naive human pluripotent stem cells (epiblast) and trophectoderm-like cells. Our data harmoniously align with transcriptomic data, indicating that single-cell proteomics possesses the capability to identify biologically relevant differences within the blastocyst.
尽管在样品制备、仪器分析和数据分析方面取得了显著进展,但单细胞蛋白质组学目前仍受蛋白质组深度和定量性能的限制。在此,我们展示了蛋白质组覆盖深度的显著提高,以及对超低输入量进行定量的准确性和精密度。使用定制文库,我们每天可处理50个样品,从低至250 pg的HeLa细胞肽中鉴定出多达7400个蛋白质组。使用双蛋白质组混合物,我们检查了定量的最佳参数,并表明在单细胞水平输入时,仍可成功确定2倍的倍数变化差异。最终,我们将工作流程应用于A549细胞,根据细胞大小和使用的搜索策略,从单个细胞中获得的蛋白质组覆盖范围为1801至最多>5300个蛋白质组,这有助于研究细胞大小与细胞周期阶段之间的依赖性。此外,我们的工作流程使我们能够区分两种人类囊胚谱系的体外类似物:原始人类多能干细胞(外胚层)和滋养外胚层样细胞。我们的数据与转录组数据和谐一致,表明单细胞蛋白质组学具有识别囊胚内生物学相关差异的能力。