Tea Illa, Tcherkez Guillaume
Research School of Biology, Australian National University, Canberra, ACT, Australia; Cancer Metabolism and Genetics Group, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia; EBSI Team, CEISAM, University of Nantes-CNRS UMR 6230, Nantes, France.
Research School of Biology, Australian National University, Canberra, ACT, Australia.
Methods Enzymol. 2017;596:113-147. doi: 10.1016/bs.mie.2017.07.020. Epub 2017 Sep 1.
The natural isotope abundance in bulk organic matter or tissues is not a sufficient base to investigate physiological properties, biosynthetic mechanisms, and nutrition sources of biological systems. In fact, isotope effects in metabolism lead to a heterogeneous distribution of H, O, C, and N isotopes in metabolites. Therefore, compound-specific isotopic analysis (CSIA) is crucial to biological and medical applications of stable isotopes. Here, we review methods to implement CSIA for N and C from plant, animal, and human samples and discuss technical solutions that have been used for the conversion to CO and N for IRMS analysis, derivatization and isotope effect measurements. It appears that despite the flexibility of instruments used for CSIA, there is no universal method simply because the chemical nature of metabolites of interest varies considerably. Also, CSIA methods are often limited by isotope effects in sample preparation or the addition of atoms from the derivatizing reagents, and this implies that corrections must be made to calculate a proper δ-value. Therefore, CSIA has an enormous potential for biomedical applications, but its utilization requires precautions for its successful application.
大量有机物质或组织中的天然同位素丰度不足以作为研究生物系统的生理特性、生物合成机制和营养来源的基础。事实上,新陈代谢中的同位素效应会导致代谢物中氢、氧、碳和氮同位素的不均匀分布。因此,化合物特异性同位素分析(CSIA)对于稳定同位素在生物学和医学中的应用至关重要。在此,我们综述了对植物、动物和人类样本中的氮和碳进行CSIA的方法,并讨论了用于转化为CO和N以进行IRMS分析、衍生化和同位素效应测量的技术解决方案。尽管用于CSIA的仪器具有灵活性,但似乎并没有通用的方法,这仅仅是因为目标代谢物的化学性质差异很大。此外,CSIA方法常常受到样品制备过程中的同位素效应或衍生化试剂中原子添加的限制,这意味着必须进行校正以计算出合适的δ值。因此,CSIA在生物医学应用中具有巨大潜力,但其成功应用需要采取预防措施。