Chiva Cristina, Olivella Roger, Staes An, Mendes Maia Teresa, Panse Christian, Stejskal Karel, Douché Thibaut, Lombard Bérangère, Schuhmann Andrea, Loew Damarys, Mechtler Karl, Matondo Mariette, Rettel Mandy, Helm Dominic, Impens Francis, Devos Simon, Shevchenko Anna, Nanni Paolo, Sabidó Eduard
Centre for Genomic Regulation, The Barcelona Institute of Science and Technology (BIST), Dr. Aiguader 88, Barcelona 08003, Spain.
Univeristat Pompeu Fabra, Dr. Aiguader 88, Barcelona 08003, Spain.
J Proteome Res. 2025 Feb 7;24(2):397-409. doi: 10.1021/acs.jproteome.4c00359. Epub 2025 Jan 1.
Quality control procedures play a pivotal role in ensuring the reliability and consistency of data generated in mass spectrometry-based proteomics laboratories. However, the lack of standardized quality control practices across laboratories poses challenges for data comparability and reproducibility. In response, we conducted a harmonization study within proteomics laboratories of the Core for Life alliance with the aim of establishing a common quality control framework, which facilitates comprehensive quality assessment and identification of potential sources of performance drift. Through collaborative efforts, we developed a consensus quality control standard for longitudinal assessment and adopted common processing software. We generated a 4-year longitudinal data set from multiple instruments and laboratories, which enabled us to assess intra- and interlaboratory variability, to identify causes of performance drift, and to establish community reference values for several quality control parameters. Our study enhances data comparability and reliability and fosters a culture of collaboration and continuous improvement within the proteomics community to ensure the integrity of proteomics data.
质量控制程序在确保基于质谱的蛋白质组学实验室所产生数据的可靠性和一致性方面发挥着关键作用。然而,各实验室缺乏标准化的质量控制实践给数据的可比性和可重复性带来了挑战。作为回应,我们在生命联盟核心的蛋白质组学实验室内部开展了一项协调研究,旨在建立一个通用的质量控制框架,以促进全面的质量评估并识别性能漂移的潜在来源。通过共同努力,我们制定了用于纵向评估的共识质量控制标准,并采用了通用的处理软件。我们从多个仪器和实验室生成了一个为期4年的纵向数据集,这使我们能够评估实验室内和实验室间的变异性,识别性能漂移的原因,并为几个质量控制参数建立社区参考值。我们的研究提高了数据的可比性和可靠性,并在蛋白质组学领域培育了合作与持续改进的文化,以确保蛋白质组学数据的完整性。