Ultrahigh-Resolution Mass Spectrometry-Based Platform for Plasma Metabolomics Applied to Type 2 Diabetes Research
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https://figshare.com/articles/dataset/Ultrahigh-Resolution_Mass_Spectrometry-Based_Platform_for_Plasma_Metabolomics_Applied_to_Type_2_Diabetes_Research/13100021
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资源简介:
Metabolomicsthe endpoint
of the omics cascadeis
increasingly recognized as a preferred method for understanding the
ultimate responses of biological systems to stress. Flow injection
electrospray (FIE) mass spectrometry (MS) has advantages for untargeted
metabolic fingerprinting due to its simplicity and capability for
high-throughput screening but requires a high-resolution mass spectrometer
to resolve metabolite features. In this study, we developed and validated
a high-throughput and highly reproducible metabolomics platform integrating
FIE with ultrahigh-resolution Fourier transform ion cyclotron resonance
(FTICR) MS for analysis of both polar and nonpolar metabolite features
from plasma samples. FIE-FTICR MS enables high-throughput detection
of hundreds of metabolite features in a single mass spectrum without
a front-end separation step. Using plasma samples from genetically
identical obese mice with or without type 2 diabetes (T2D), we validated
the intra and intersample reproducibility of our method and its robustness
for simultaneously detecting alterations in both polar and nonpolar
metabolite features. Only 5 min is needed to acquire an ultra-high
resolution mass spectrum in either a positive or negative ionization
mode. Approximately 1000 metabolic features were reproducibly detected
and annotated in each mouse plasma group. For significantly altered
and highly abundant metabolite features, targeted tandem MS (MS/MS)
analyses can be applied to confirm their identity. With this integrated
platform, we successfully detected over 300 statistically significant
metabolic features in T2D mouse plasma as compared to controls and
identified new T2D biomarker candidates. This FIE-FTICR MS-based method
is of high throughput and highly reproducible with great promise for
metabolomics studies toward a better understanding and diagnosis of
human diseases.
创建时间:
2020-10-15



