Peterková Lenka, Tesařová Michaela, Sukupová Adéla, Michalus Iva, Cejnar Pavel, Fík Zdeněk, Šantrůček Jiří, Kašička Václav, Hynek Radovan
Department of Otorhinolaryngology and Head and Neck Surgery, First Faculty of Medicine Charles University and Motol University Hospital, Prague, Czech Republic.
Institute of Anatomy, First Faculty of Medicine, Charles University, Prague, Czech Republic.
J Sep Sci. 2025 Sep;48(9):e70277. doi: 10.1002/jssc.70277.
Common pathological changes in bone tissues like osteomas or exostoses remain not fully understood at the molecular level due to the difficulties in analyzing bone tissues in which they occur. Therefore, new rapid and powerful techniques are needed that could become routine tools for such analysis. The primary aim of this study was to evaluate whether direct in-bone tryptic protein digestion followed by LC separation and trap ion mobility MS detection and identification of released peptides is able to identify sufficient numbers of proteins in above mentioned bone tissues. The second aim was to verify whether the mathematical analysis of the obtained MS data would have a potential to distinguish pathological and control healthy bone tissues. It turned out that this approach made possible to identify altogether 4810 proteins in samples of control healthy skull bone tissues, 6284 proteins in pathological skull bone tissues, and 3000 proteins in mandibular bone tissues. Mathematical analysis of obtained MS data enabled to discriminate control healthy and pathological skull bone tissues samples with accuracy of 87%. Thus, the reported approach seems to have a high potential for routine and effective characterization of bone tissues, in which pathological changes like exostoses or osteomas may occur. Data are available via ProteomeXchange with identifier PXD065656.
由于分析发生骨瘤或外生骨疣等骨组织存在困难,这些骨组织中的常见病理变化在分子水平上仍未得到充分理解。因此,需要新的快速且强大的技术,使其能够成为此类分析的常规工具。本研究的主要目的是评估在骨内直接进行胰蛋白酶蛋白消化,随后进行液相色谱分离和阱式离子淌度质谱检测及鉴定释放的肽段,是否能够鉴定出上述骨组织中足够数量的蛋白质。第二个目的是验证对获得的质谱数据进行数学分析是否有潜力区分病理和对照健康骨组织。结果表明,这种方法能够在对照健康颅骨骨组织样本中总共鉴定出4810种蛋白质,在病理颅骨骨组织中鉴定出6284种蛋白质,在下颌骨组织中鉴定出3000种蛋白质。对获得的质谱数据进行数学分析能够以87%的准确率区分对照健康和病理颅骨骨组织样本。因此,所报道的方法似乎具有对可能发生外生骨疣或骨瘤等病理变化的骨组织进行常规和有效表征的巨大潜力。数据可通过ProteomeXchange获取,标识符为PXD065656。