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基于基质辅助激光解吸电离飞行时间质谱(MALDI-TOF-MS)的新冠病毒筛查中鼻拭子运输培养基内源性肽段的鉴定

Identification of Endogenous Peptides in Nasal Swab Transport Media used in MALDI-TOF-MS Based COVID-19 Screening.

作者信息

Tsai Helen, Phinney Brett S, Grigorean Gabriela, Salemi Michelle R, Rashidi Hooman H, Pepper John, Tran Nam K

机构信息

Proteomics Core, University of California, Davis, 451 E. Health Sciences Dr., Davis, California 95616, United States.

Department of Pathology and Laboratory Medicine, University of California, Davis, 4400 V St., Sacramento, California 95817, United States.

出版信息

ACS Omega. 2022 May 9;7(20):17462-17471. doi: 10.1021/acsomega.2c01864. eCollection 2022 May 24.

Abstract

Mass spectrometry (MS) based diagnostic detection of 2019 novel coronavirus infectious disease (COVID-19) has been postulated to be a useful alternative to classical PCR based diagnostics. These MS based approaches have the potential to be both rapid and sensitive and can be done on-site without requiring a dedicated laboratory or depending on constrained supply chains (i.e., reagents and consumables). Matrix-assisted laser desorption ionization (MALDI)-time-of-flight (TOF) MS has a long and established history of microorganism detection and systemic disease assessment. Previously, we have shown that automated machine learning (ML) enhanced MALDI-TOF-MS screening of nasal swabs can be both sensitive and specific for COVID-19 detection. The underlying molecules responsible for this detection are generally unknown nor are they required for this automated ML platform to detect COVID-19. However, the identification of these molecules is important for understanding both the mechanism of detection and potentially the biology of the underlying infection. Here, we used nanoscale liquid chromatography tandem MS to identify endogenous peptides found in nasal swab saline transport media to identify peptides in the same the mass over charge (/) values observed by the MALDI-TOF-MS method. With our peptidomics workflow, we demonstrate that we can identify endogenous peptides and endogenous protease cut sites. Further, we show that SARS-CoV-2 viral peptides were not readily detected and are highly unlikely to be responsible for the accuracy of MALDI based SARS-CoV-2 diagnostics. Further analysis with more samples will be needed to validate our findings, but the methodology proves to be promising.

摘要

基于质谱(MS)的2019新型冠状病毒感染疾病(COVID-19)诊断检测被认为是传统基于聚合酶链反应(PCR)诊断方法的一种有用替代方法。这些基于MS的方法有可能既快速又灵敏,并且可以在现场进行,无需专门的实验室或依赖受限的供应链(即试剂和耗材)。基质辅助激光解吸电离(MALDI)-飞行时间(TOF)质谱在微生物检测和全身性疾病评估方面有着悠久且成熟的历史。此前,我们已经表明,自动化机器学习(ML)增强的MALDI-TOF-MS鼻拭子筛查对COVID-19检测既灵敏又特异。负责这种检测的潜在分子通常未知,并且这种自动化ML平台检测COVID-19也不需要它们。然而,识别这些分子对于理解检测机制以及潜在的基础感染生物学都很重要。在这里,我们使用纳米级液相色谱串联质谱来识别鼻拭子盐水转运介质中发现的内源性肽,以识别与MALDI-TOF-MS方法观察到的相同质荷比(/)值的肽。通过我们的肽组学工作流程,我们证明可以识别内源性肽和内源性蛋白酶切割位点。此外,我们表明严重急性呼吸综合征冠状病毒2(SARS-CoV-2)病毒肽不容易被检测到,并且极不可能是基于MALDI的SARS-CoV-2诊断准确性的原因。需要用更多样本进行进一步分析来验证我们的发现,但该方法证明是有前景的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c18/9134385/3231d46f411a/ao2c01864_0001.jpg

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