Hasan Md Mehedi, Razu Mamudul Hasan, Akter Sonia, Mou Salma Akter, Islam Minhazul, Khan Mala
Bangladesh Reference Institute for Chemical Measurements Dhaka Bangladesh
RSC Adv. 2024 Jul 15;14(31):22292-22303. doi: 10.1039/d4ra01130a. eCollection 2024 Jul 12.
As an analytical matrix, saliva has superior characteristics than blood and urine. Saliva collection is, first and foremost, non-invasive, making it convenient, painless, and secure for more susceptible people. Second, it does not need professional training for medical personnel, resulting in cost-effectiveness and suitability for extensive collection in support of research. In this study, we developed a method and used it to quantify 13 salivary-free amino acid (SFAA) profiles to support the early clinical diagnosis of diseases using LC-MS/MS. Using an Intrada Amino Acid column (100 × 3 mm, 3 μm), chromatographic separation was accomplished with a binary gradient elution, and an electrospray ionisation source running in the positive ionisation mode was chosen for data collection using the multiple reaction monitoring (MRM) modes. Amino acids were extracted from saliva using acetonitrile. In the MRM mode, LODs and LOQs for ten amino acids were in the range of 0.06-2.50 μM and 0.19-7.58 μM, respectively, and those values were in the range of 1.00-3.00 μM and 3.00-8.50 μM, respectively, for three amino acids. Matrix-matched six-point calibration curves showed a linear correlation coefficient ( ) of ≥0.998. Recovery experiments validated the method by spiking the control sample at three different concentration levels (5, 50 and 100 μM), and the accuracy level was 85-110%. Except for Thr and Ser, intra- ( = 3) and inter-day ( = 3) precision fell between 0.02 and 7.28. Salivary amino acids can serve as possible biomarkers for various malignancies, with fluctuations in body fluids being crucial for cancer diagnosis; therefore, examining amino acid patterns in saliva can assist in early cancer detection. LC-MS offers improved selectivity and sensitivity for non-derivatised amino acid analysis, surpassing conventional methods and offering proactive quality assurance, making it suitable for complicated sample matrices. These discoveries could be significant in investigating new pathways and cancer treatments and looking for possible AA biomarkers for other malignancies and diseases.
作为一种分析基质，唾液具有比血液和尿液更优越的特性。首先，唾液采集是非侵入性的，这使得它对于更易受影响的人群来说方便、无痛且安全。其次，它不需要医护人员进行专业培训，从而具有成本效益且适合大规模采集以支持研究。在本研究中，我们开发了一种方法并使用它来定量13种唾液游离氨基酸（SFAA）谱，以支持使用液相色谱-串联质谱（LC-MS/MS）进行疾病的早期临床诊断。使用Intrada氨基酸柱（100×3 mm，3μm），通过二元梯度洗脱完成色谱分离，并选择在正离子模式下运行的电喷雾电离源，使用多反应监测（MRM）模式进行数据采集。使用乙腈从唾液中提取氨基酸。在MRM模式下，十种氨基酸的检测限（LOD）和定量限（LOQ）分别在0.06 - 2.50μM和0.19 - 7.58μM范围内，三种氨基酸的值分别在1.00 - 3.00μM和3.00 - 8.50μM范围内。基质匹配的六点校准曲线显示线性相关系数（ ）≥0.998。回收率实验通过在三个不同浓度水平（5、50和100μM）对对照样品加标来验证该方法，准确度水平为85 - 110％。除苏氨酸（Thr）和丝氨酸（Ser）外，日内（ = 3）和日间（ = 3）精密度在0.02至7.28之间。唾液氨基酸可作为各种恶性肿瘤的潜在生物标志物，体液中的波动对癌症诊断至关重要；因此，检测唾液中的氨基酸模式有助于早期癌症检测。LC-MS对未衍生化氨基酸分析具有更高选择性和灵敏度，优于传统方法并提供主动质量保证，使其适用于复杂样品基质。这些发现对于研究新途径和癌症治疗以及寻找其他恶性肿瘤和疾病的可能氨基酸生物标志物可能具有重要意义。
