histone-modification-screening-using-liquid-chromatography-trapped

Histone Modification Screening using Liquid Chromatography, Trapped Ion Mobility Spectrometry, and Time-Of-Flight Mass Spectrometry

Histone proteins are highly abundant and conserved among eukaryotes and play a large role in gene regulation as a result of structures known as ...

tracing-de-novo-lipids-using-stable-isotope-labeling-lc-tims-tof-msms

Tracing <em>de novo</em> Lipids using Stable Isotope Labeling LC-TIMS-TOF MS/MS

Lipids are highly diverse, and small changes in lipid structures and composition can have profound effects on critical biological functions. Stable ...

Fentanyl Analog Screening using LC-TIMS-TOF MS/MS

The use of fentanyl and the emergence of fentanyl analogs over recent decades has become an increasing concern to the community at large. Fentanyl and its ...

Bruker Daltonics Inc.

Transition metal-containing proteins and enzymes are critical for the maintenance of cellular function and metal-based (metallo)drugs are commonly used for the treatment of many diseases, such as cancer. Detection and characterisation of metallodrug targets is crucial for improving drug-design and therapeutic efficacy. Due to the unique isotopic ratios of many metal species, and the complexity of proteomic samples, standard MS data analysis of these species is unsuitable for accurate assignment. Herein a new method for differentiating metal-containing species within complex LCMS data is presented based upon the Smart Numerical Annotation Procedure (SNAP). SNAP-LC accounts for the change in isotopic envelopes for analytes containing non-standard species, such as metals, and will accurately identify, record, and display the particular spectra within extended LCMS runs that contain target species, and produce accurate lists of matched peaks, greatly assisting the identification and assignment of modified species and tailored to the metals of interest. Analysis of metallated species obtained from tryptic digests of common blood proteins after reactions with three candidate metallodrugs is presented as proof-of-concept examples and demonstrates the effectiveness of SNAP-LC for the fast and accurate elucidation of metallodrug targets.

Automatic assignment of metal-containing peptides in proteomic LC-MS and MS/MS data sets.

Parallel reaction monitoring (PRM) has emerged as a popular approach for targeted protein quantification. With high ion utilization efficiency and first-in-class acquisition speed, the timsTOF Pro provides a powerful platform for PRM analysis. However, sporadic chromatographic drift in peptide retention time represents a fundamental limitation for the reproducible multiplexing of targets across PRM acquisitions. Here, we present PRM-LIVE, an extensible, Python-based acquisition engine for the timsTOF Pro, which dynamically adjusts detection windows for reproducible target scheduling. In this initial implementation, we used iRT peptides as retention time standards and demonstrated reproducible detection and quantification of 1857 tryptic peptides from the cell lysate in a 60 min PRM-LIVE acquisition. As an application in functional proteomics, we use PRM-LIVE in an activity-based protein profiling platform to assess binding selectivity of small-molecule inhibitors against 220 endogenous human kinases.

PRM-LIVE with Trapped Ion Mobility Spectrometry and Its Application in Selectivity Profiling of Kinase Inhibitors.

Current mass spectrometry methods enable high-throughput proteomics of large sample amounts, but proteomics of low sample amounts remains limited in depth and throughput. To increase the throughput of sensitive proteomics, we developed an experimental and computational framework, called plexDIA, for simultaneously multiplexing the analysis of peptides and samples. Multiplexed analysis with plexDIA increases throughput multiplicatively with the number of labels without reducing proteome coverage or quantitative accuracy. By using three-plex non-isobaric mass tags, plexDIA enables quantification of threefold more protein ratios among nanogram-level samples. Using 1-hour active gradients, plexDIA quantified ~8,000 proteins in each sample of labeled three-plex sets and increased data completeness, reducing missing data more than twofold across samples. Applied to single human cells, plexDIA quantified ~1,000 proteins per cell and achieved 98% data completeness within a plexDIA set while using ~5 minutes of active chromatography per cell. These results establish a general framework for increasing the throughput of sensitive and quantitative protein analysis.

Matthew Willetts

Bruker Daltonics Inc.

Histone Modification Screening using Liquid Chromatography, Trapped Ion Mobility Spectrometry, and Time-Of-Flight Mass Spectrometry

Tracing de novo Lipids using Stable Isotope Labeling LC-TIMS-TOF MS/MS

Fentanyl Analog Screening using LC-TIMS-TOF MS/MS