Brockbals Lana, Ueland Maiken, Fu Shanlin, Padula Matthew P
Centre for Forensic Science, School of Mathematical and Physical Sciences, Faculty of Science, University of Technology Sydney, PO Box 123, Broadway, 2007 NSW, Australia; Department of Forensic Pharmacology and Toxicology, Institute of Forensic Medicine, University of Zurich, Winterthurerstrasse 190/52, 8057 Zurich, Switzerland.
Centre for Forensic Science, School of Mathematical and Physical Sciences, Faculty of Science, University of Technology Sydney, PO Box 123, Broadway, 2007 NSW, Australia; Hyphenated Mass Spectrometry Laboratory, Faculty of Science, University of Technology Sydney, PO Box 123, Broadway, 2007 NSW, Australia.
Talanta. 2025 May 1;286:127442. doi: 10.1016/j.talanta.2024.127442. Epub 2024 Dec 24.
The importance of sample preparation selection if often overlooked particularly for untargeted multi-omics approaches that gained popularity in recent years. To minimize issues with sample heterogeneity and additional freeze-thaw cycles during sample splitting, multiple -omics datasets (e.g. metabolomics, lipidomics and proteomics) should ideally be generated from the same set of samples. For sample extraction, commonly biphasic organic solvent systems are used that require extensive multi-step protocols. Individual studies have recently also started to investigate monophasic (all-in-one) extraction procedures. The aim of the current study was to develop and systematically compare ten different mono- and biphasic extraction solvent mixtures for their potential to aid in the most comprehensive metabolomics, lipidomics and proteomics datasets. As the focus was on human postmortem tissue samples (muscle and liver tissue), four tissue homogenization parameters were also evaluated. Untargeted liquid chromatography mass spectrometry-based metabolomics, lipidomic and proteomics methods were utilized along with 1D sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and bicinchoninic acid (BCA) assay results. Optimal homogenization was found to be achieved by bead-homogenizing 20 mg of muscle or liver tissue with 200 μL (1:10 ratio) Water:Methanol (1:2) using 3 × 30 s pulses. The supernatant of the homogenate was further extracted. Comprehensive ranking, taking nine different processing parameters into account, showed that the monophasic extraction solvents, overall, showed better scores compared to the biphasic solvent systems, despite their recommendation for one or all of the -omics extractions. The optimal extraction solvent was found to be Methanol:Acetone (9:1), resulting in the most comprehensive metabolomics, lipidomics and proteomics datasets, showing the potential to be automated, hence, allowing for high-throughput analysis of samples and opening the door for comprehensive multi-omics results from routine clinical cases in the future.
样本制备方法选择的重要性常常被忽视，尤其是对于近年来颇受青睐的非靶向多组学方法。为了尽量减少样本异质性以及样本分割过程中额外的冻融循环问题，理想情况下，多个组学数据集（如代谢组学、脂质组学和蛋白质组学）应从同一组样本中生成。对于样本提取，通常使用双相有机溶剂系统，这需要复杂的多步操作流程。最近，个别研究也开始探索单相（一体化）提取方法。本研究的目的是开发并系统比较十种不同的单相和双相提取溶剂混合物，评估它们在助力生成最全面的代谢组学、脂质组学和蛋白质组学数据集方面的潜力。由于研究重点是人类死后组织样本（肌肉和肝脏组织），还评估了四个组织匀浆参数。采用了基于非靶向液相色谱质谱的代谢组学、脂质组学和蛋白质组学方法，以及一维十二烷基硫酸钠聚丙烯酰胺凝胶电泳（SDS-PAGE）和二喹啉甲酸（BCA）测定结果。结果发现，通过用200μL（1:10比例）水:甲醇（1:2）对20mg肌肉或肝脏组织进行珠磨匀浆，采用3×30s脉冲，可以实现最佳匀浆效果。匀浆液的上清液进一步提取。综合考虑九个不同的处理参数进行全面排名后发现，尽管推荐将双相溶剂系统用于一种或所有组学提取，但总体而言，单相提取溶剂的得分优于双相溶剂系统。发现最佳提取溶剂是甲醇:丙酮（9:1），它能生成最全面的代谢组学、脂质组学和蛋白质组学数据集，显示出自动化的潜力，从而能够对样本进行高通量分析，并为未来常规临床病例的全面多组学结果打开大门。
