Sensitive Detection of Pharmaceutical Drugs and Metabolites in Serum Using Data-Independent Acquisition Mass Spectrometry and Open-Access Data Acquisition Tools

Potential biomarkers analysis and protein internal mechanisms by cold plasma treatment: Is proteomics effective to elucidate protein-protein interaction network and biochemical pathway?

New market trends of meat flavor, tenderness, and color quality indicators have prompted the research on meat preservation as a crucial topic to received attention. Present research about the effects of irradiation, cold plasma technology on meat is incomplete. There are strongly recommended that proteomics techniques be jointly to enhance the coverage of internal meat molecules for meat research. By identifying meat proteins, detecting biological functions, and quantifying the protein segments of specific meat biomarkers, which can be provided for the information of diagnostic components in preservative technologies. The current review provides scientific findings on various control strategies: (i) combine the data-independent acquisition to provide a reference for the meat molecular mechanism and rapid identification; (ii) design molecular networks biological functions assessment model; (iii) molecular investigations of cold plasma techniques and underlying mechanisms; (iv) explore the X-rays and γ-rays treatment in meat preservation and myoglobin change mechanism more comprehensively.

A Novel Approach of SWATH-Based Metabolomics Analysis Using the Human Metabolome Database Spectral Library

Metabolomics is a potential approach to paving new avenues for clinical diagnosis, molecular medicine, and therapeutic drug monitoring and development. The conventional metabolomics analysis pipeline depends on the data-independent acquisition (DIA) technique. Although powerful, it still suffers from stochastic, non-reproducible ion selection across samples. Despite the presence of different metabolomics workbenches, metabolite identification remains a tedious and time-consuming task. Consequently, sequential windowed acquisition of all theoretical MS (SWATH) acquisition has attracted much attention to overcome this limitation. This article aims to develop a novel SWATH platform for data analysis with a generation of an accurate mass spectral library for metabolite identification using SWATH acquisition. The workflow was validated using inclusion/exclusion compound lists. The false-positive identification was 3.4% from the non-endogenous drugs with 96.6% specificity. The workflow has proven to overcome background noise despite the complexity of the SWATH sample. From the Human Metabolome Database (HMDB), 1282 compounds were tested in various biological samples to demonstrate the feasibility of the workflow. The current study identified 377 compounds in positive and 303 in negative modes with 392 unique non-redundant metabolites. Finally, a free software tool, SASA, was developed to analyze SWATH-acquired samples using the proposed pipeline.