Stepped collisional energy MS(All) : an analytical approach for optimal MS/MS acquisition of complex mixture with diverse physicochemical properties

Plasma-Droplet Fusion-Mass Spectrometry Reveals Sub-Millisecond Protein Unfolding Dynamics Induced by Reactive Oxygen Species

Investigating the connection between reactive oxygen species (ROS) and oxidative protein unfolding is critical to reveal the mechanisms underlying disease involving elevated ROS and protein misfolding. This could inform the development of therapeutics targeting cells based on their redox status. In this study, we developed a plasma-droplet fusion-mass spectrometry platform to rapidly assess protein resilience to ROS. This home-built system fuses ROS generated from the microplasma source with protein microdroplets from a tunable nanospray source. At the droplet-plasma intersection, ROS interact with proteins before entering the mass spectrometer for mass identification and structural characterization. Benefiting from the small-sized microdroplet with adjustable traveling velocity, the platform enables the first sub-millisecond kinetic study of ROS-induced protein unfolding, with a rate constant of approximately 1.81 ms-1. Capturing ROS-induced protein unfolding intermediates and the resultant ligand release dynamics can be extended to many more protein systems. We foresee broad applications for establishing previously undetected protein unfolding events when biologically impactful ROS are enriched in time and space with functional proteins and complexes.

Functional Metabolomics and Chemoproteomics Approaches Reveal Novel Metabolic Targets for Anticancer Therapy

Cancer cells exhibit different metabolic patterns compared to their normal counterparts. Although the reprogrammed metabolism has been indicated as strong biomarkers of cancer initiation and progression, increasing evidences suggest that metabolic alteration tuned by oncogenic drivers contributes to the occurrence and development of cancers rather than just being a hallmark of cancer. With this notion, targeting cancer metabolism holds promise as a novel anticancer strategy and is embracing its renaissance during the past two decades. Herein we have summarized the most recent developments in omics technology, including both metabolomics and proteomics, and how the combined use of these analytical tools significantly impacts this field by comprehensively and systematically recording the metabolic changes in cancer and hence reveals potential therapeutic targets that function by modulating the disrupted metabolic pathways.

Selectivity enhancement using sequential mass isolation window acquisition with hybrid quadrupole time-of-flight mass spectrometry for pesticide residues

The introduction of sequential mass isolation window acquisition mode in high-resolution quadrupole time-of-flight analysers undoubtedly represents an important improvement in the MS/MS spectra obtained when working in non-target analysis. However, the advantages and limitations of this approach have not been sufficiently defined and evaluated. The present work seeks to fill this gap by considering its application in non-target multiresidue pesticide analysis. This work focuses on the called SWATH^® method, which combines both MS and MS/MS acquisition, dividing the entire mass range into smaller segments for the MS/MS mode. The effect of the number of mass isolation windows, the total cycle-time lapsed, the sensitivity obtained, the MS/MS spectra quality, the ion ratio stability as well as the identification and quantification capabilities has been evaluated. The use of ten mass isolation windows for data acquisition was selected as a compromise between the required points per chromatographic peak and the reduction in interferences achieved. An identification study was carried out on 141 pesticides in 20 vegetable matrices to check the false positives and false identifications found automatically, in accordance with the criteria set out in Document No. SANTE/11945/2015. Furthermore, special attention was given to certain issues that can make correct identification difficult, such as low fragment abundance due using of a generic collision energy, the matrix influence on the collision cell, the effect of the concentration level as well as deconvolution failure and mass window width. Finally, to verify the efficiency of the optimum parameters proposed, two proficiency samples were analysed, obtaining good results. This proved the benefits in terms of identification and quantification purposes.

Stepwise targeted matching strategy from in vitro to in vivo based on ultra-high performance liquid chromatography tandem mass spectrometry technology to quickly identify and screen pharmacodynamic constituents

The study of in vivo pharmacodynamic constituents (PCs) of traditional Chinese medicine (TCM) is important for providing new clues for TCM applications in clinical therapies in modern medicine. However, detecting and identifying PCs from complex biological samples remain a challenge. In this study, a practical and novel stepwise targeted matching and longitudinal analysis strategy from in vitro to in vivo was developed. This strategy combined with ultra-high performance liquid chromatography tandem mass spectrometry was applied to quickly discover PCs in TCM. This approach was developed based on a core perception that all drugs taken orally might be transformed progressively and orderly from the intestinal tract, liver, and blood to the target organ. Based on this core perception, stepwise targeted matching was orderly and efficiently accomplished by multiple screening processes that were based on a stepwise enriched in-house library. Ginseng (Panax ginseng) was set as the example of herbal medicine for validating the reliability and availability of this approach. By applying this novel strategy to the stepwise screening of metabolites, we successfully identified 113 metabolites, among which 59 compounds were defined as prototypes. Based on the in vivo metabolites, network pharmacology analysis was applied to screen the PCs of ginseng and clarified the action mechanism of ginseng for the treatment of Alzheimer's disease (AD). A total of 27 herbal constituents and 64 related targets shared commonly by compounds and AD were integrated via target network pharmacology analysis. These results demonstrated that this original approach will greatly improve high-throughput screening of metabolites and PCs on AD. It also can explicate the mechanism of action of TCM. Furthermore, this strategy is practicable to identify metabolites and screen PCs in other herbal medicines.