The major vault protein (MVP) mediates diverse cellular responses, including cancer cell resistance to chemotherapy and protection against inflammatory responses to Pseudomonas aeruginosa Here, we report the use of photoactive probes to identify MVP as a target of the N-(3-oxo-dodecanoyl) homoserine lactone (C12), a quorum sensing signal of certain proteobacteria including P. aeruginosa. A treatment of normal and cancer cells with C12 or other N-acyl homoserine lactones (AHLs) results in rapid translocation of MVP into lipid raft (LR) membrane fractions. Like AHLs, inflammatory stimuli also induce LR-localization of MVP, but the C12 stimulation reprograms (functionalizes) bioactivity of the plasma membrane by recruiting death receptors, their apoptotic adaptors, and caspase-8 into LR. These functionalized membranes control AHL-induced signaling processes, in that MVP adjusts the protein kinase p38 pathway to attenuate programmed cell death. Since MVP is the structural core of large particles termed vaults, our findings suggest a mechanism in which MVP vaults act as sentinels that fine-tune inflammation-activated processes such as apoptotic signaling mediated by immunosurveillance cytokines including tumor necrosis factor-related apoptosis inducing ligand (TRAIL).

Access to web-based platforms has enabled scientists to perform research remotely. A critical aspect of mass spectrometry data analysis is the inspection, analysis, and visualization of the raw data to validate data quality and confirm statistical observations. We developed the GNPS Dashboard, a web-based data visualization tool, to facilitate synchronous collaborative inspection, visualization, and analysis of private and public mass spectrometry data remotely.

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography-mass spectrometry (GC-MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC-MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.