Percorrer por autor "Uddin, Mohammed J."
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- Optimizing MS Parameters for Data-Independent Acquisition (DIA) to Enhance Untargeted MetabolomicsPublication . Pinto, Frederico G.; Giddey, Alexander D.; Almarri, Rouda S. B.; Alkhnbashi, Omer S.; Garrett, Timothy J.; Uddin, Mohammed J.; Soares, Nelson C.Data-Independent Acquisition (DIA) has emerged as a powerful mass spectrometry (MS) strategy for comprehensive metabolomics. This study presents a novel short gradient (13 min) nanosensitive analytical method for human plasma analysis using DIA LC-MS/MS, focusing on in-depth optimization of MS parameters to maximize data quality and metabolite coverage. Key MS parameters, including scan speed, isolation window width, resolution, automatic gain control, and collision energy, were systematically tuned to balance the sensitivity and specificity while minimizing interferences. The optimized method enabled the detection of 2,907 features with 675 annotated compounds, leveraging recent progress in nano-LC-MS/MS for multiomics applications and showcasing the possibility of combining proteomics and metabolomics within a single chromatographic system. Ultimately, a comparison was performed between the data acquired through the DIA and DDA MS approaches in the context of untargeted metabolomics. This optimized analytical method yields more robust and reproducible results, thereby expanding the potential for meaningful discoveries across diverse biological fields.
- Repurposing proteomic nanoLC-MS platforms for untargeted metabolomics: evaluating DIA and polarity switching performance in human plasmaPublication . Pinto, Frederico G.; Giddey, Alexander D.; Mohamed, Nesrin; Almarri, Rauda S. B.; Murtaza, Munazza; Nassir, Nasna; Alkhnbashi, Omer S.; Uddin, Mohammed J.; Soares, Nelson C.Background: Many of the advanced MS methods applied in proteomics such as nanoflow LC-MS with data-independent acquisition have yet to be verified and/or optimized on metabolomics applications. Research design and methods: This study evaluates the feasibility of repurposing a proteomics-optimized nanoLC-MS platform for untargeted metabolomics. Using NIST SRM 1950 reference human plasma, we compared the performance of polarity switching and separate polarity modes under DIA conditions, focusing on metabolite coverage, annotation, and response linearity. Results: We observed, in the separate polarity and switching polarity runs 669 and 353 features in (+) mode and 558 and 446 features in (-) mode, respectively. A total of 233 metabolites were annotated using the (±) separate polarities and 179 using the (±) switching polarity based on MassBank of North America (MoNA) public MS library and filtered with the Human Metabolome Database (HMDB). Both switching and separate polarity methods performed well regarding response linearities which were investigated by spiking some amino acid compounds into plasma matrix. Conclusions: The polarity switching DIA approach for metabolomics reduced sample consumption and analysis time, but led to fewer detected features and annotations compared to separate polarity runs. These findings support the use of unified nanoLC-MS platforms for integrated multi-omics analysis.