Evaluation of a prototype Orbitrap Astral Zoom mass spectrometer for quantitative proteomics - Beyond identification lists.

Mass spectrometry instrumentation continues to evolve rapidly yet quantifying these advances beyond conventional peptide and protein detections remain challenging. Here, we evaluate a modified Orbitrap Astral Zoom mass spectrometer (MS) prototype and compare its performance to the standard Orbitrap Astral MS. Across a range of acquisition methods and sample inputs, the prototype instrument outperformed the standard Orbitrap Astral MS in precursor and protein identifications, ion beam utilization, and quantitative precision.

Proteomic Plasticity in the Coral Gamete Bundles after Parent Thermal Bleaching.

Coral reefs are vital to marine biodiversity and human livelihoods, but they face significant threats from climate change. Increased ocean temperatures drive massive "bleaching" events, during which corals lose their symbiotic algae and the important metabolic resources those algae provide. Proteomics is a crucial tool for understanding coral function and tolerance to thermal stress, as proteins drive physiological processes and accurately represent cell functional phenotypes.

Hybrid Quadrupole Mass Filter-Radial Ejection Linear Ion Trap and Intelligent Data Acquisition Enable Highly Multiplex Targeted Proteomics.

Targeted mass spectrometry (MS) methods are powerful tools for the selective and sensitive analysis of peptides identified in global discovery experiments. Selected reaction monitoring (SRM) is the most widely accepted clinical MS method due to its reliability and performance. However, SRM and parallel reaction monitoring (PRM) are limited in throughput and are typically used for assays with around 100 targets or fewer.

A Framework for Quality Control in Quantitative Proteomics.

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow, from planning to analysis. We share vignettes applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years.

Development of highly multiplex targeted proteomics assays in biofluids using the Stellar mass spectrometer.

The development of targeted assays that monitor biomedically relevant proteins is an important step in bridging discovery experiments to large scale clinical studies. Targeted assays are currently unable to scale to hundreds or thousands of targets. We demonstrate the generation of large-scale assays using a novel hybrid nominal mass instrument.

Hybrid Quadrupole Mass Filter - Radial Ejection Linear Ion Trap and Intelligent Data Acquisition Enable Highly Multiplex Targeted Proteomics.

Targeted mass spectrometry (MS) methods are powerful tools for selective and sensitive analysis of peptides identified by global discovery experiments. Selected reaction monitoring (SRM) is currently the most widely accepted MS method in the clinic, due to its reliability and analytical performance. However, due to limited throughput and the difficulty in setting up and analyzing large scale assays, SRM and parallel reaction monitoring (PRM) are typically used only for very refined assays of on the order of 100 targets or less.

Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data-Independent Acquisition.

We evaluate the quantitative performance of the newly released Asymmetric Track Lossless (Astral) analyzer. Using data-independent acquisition, the Thermo Scientific Orbitrap Astral mass spectrometer quantifies 5 times more peptides per unit time than state-of-the-art Thermo Scientific Orbitrap mass spectrometers, which have long been the gold standard for high-resolution quantitative proteomics. Our results demonstrate that the Orbitrap Astral mass spectrometer can produce high-quality quantitative measurements across a wide dynamic range.

Targeted proteomics data interpretation with DeepMRM.

Targeted proteomics is widely utilized in clinical proteomics; however, researchers often devote substantial time to manual data interpretation, which hinders the transferability, reproducibility, and scalability of this approach. We introduce DeepMRM, a software package based on deep learning algorithms for object detection developed to minimize manual intervention in targeted proteomics data analysis. DeepMRM was evaluated on internal and public datasets, demonstrating superior accuracy compared with the community standard tool Skyline.

Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data Independent Acquisition.

We evaluate the quantitative performance of the newly released Asymmetric Track Lossless (Astral) analyzer. Using data independent acquisition, the Thermo Scientific™ Orbitrap™ Astral™ mass spectrometer quantifies 5 times more peptides per unit time than state-of-the-art Thermo Scientific™ Orbitrap™ mass spectrometers, which have long been the gold standard for high resolution quantitative proteomics. Our results demonstrate that the Orbitrap Astral mass spectrometer can produce high quality quantitative measurements across a wide dynamic range.

MSstats Version 4.0: Statistical Analyses of Quantitative Mass Spectrometry-Based Proteomic Experiments with Chromatography-Based Quantification at Scale.

The R-Bioconductor family of packages is widely used for statistical analyses of quantitative bottom-up mass spectrometry-based proteomic experiments to detect differentially abundant proteins. It is applicable to a variety of experimental designs and data acquisition strategies and is compatible with many data processing tools used to identify and quantify spectral features. In the face of ever-increasing complexities of experiments and data processing strategies, the core package of the family, with the same name , has undergone a series of substantial updates.

Utilizing Skyline to analyze lipidomics data containing liquid chromatography, ion mobility spectrometry and mass spectrometry dimensions.

Lipidomics studies suffer from analytical and annotation challenges because of the great structural similarity of many of the lipid species. To improve lipid characterization and annotation capabilities beyond those afforded by traditional mass spectrometry (MS)-based methods, multidimensional separation methods such as those integrating liquid chromatography, ion mobility spectrometry, collision-induced dissociation and MS (LC-IMS-CID-MS) may be used. Although LC-IMS-CID-MS and other multidimensional methods offer valuable hydrophobicity, structural and mass information, the files are also complex and difficult to assess.

Cullin-independent recognition of HHARI substrates by a dynamic RBR catalytic domain.

RING-between-RING (RBR) E3 ligases mediate ubiquitin transfer through an obligate E3-ubiquitin thioester intermediate prior to substrate ubiquitination. Although RBRs share a conserved catalytic module, substrate recruitment mechanisms remain enigmatic, and the relevant domains have yet to be identified for any member of the class. Here we characterize the interaction between the auto-inhibited RBR, HHARI (AriH1), and its target protein, 4EHP, using a combination of XL-MS, HDX-MS, NMR, and biochemical studies.

Skyline Batch: An Intuitive User Interface for Batch Processing with Skyline.

Skyline Batch is a newly developed Windows forms application that enables the easy and consistent reprocessing of data with Skyline. Skyline has made previous advances in this direction; however, none enable seamless automated reprocessing of local and remote files. Skyline keeps a log of all of the steps that were taken in the document; however, reproducing these steps takes time and allows room for human error.

Development and Application of Multidimensional Lipid Libraries to Investigate Lipidomic Dysregulation Related to Smoke Inhalation Injury Severity.

The implication of lipid dysregulation in diseases, toxic exposure outcomes, and inflammation has brought great interest to lipidomic studies. However, lipids have proven to be analytically challenging due to their highly isomeric nature and vast concentration ranges in biological matrices. Therefore, multidimensional techniques such as those integrating liquid chromatography, ion mobility spectrometry, collision-induced dissociation, and mass spectrometry (LC-IMS-CID-MS) have been implemented to separate lipid isomers as well as provide structural information and increased identification confidence.

Audit logs to enforce document integrity in Skyline and Panorama.

Summary: Skyline is a Windows application for targeted mass spectrometry method creation and quantitative data analysis. Like most graphical user interface (GUI) tools, it has a complex user interface with many ways for users to edit their files which makes the task of logging user actions challenging and is the reason why audit logging of every change is not common in GUI tools. We present an object comparison-based approach to audit logging for Skyline that is extensible to other GUI tools.

Selection of Features with Consistent Profiles Improves Relative Protein Quantification in Mass Spectrometry Experiments.

In bottom-up mass spectrometry-based proteomics, relative protein quantification is often achieved with data-dependent acquisition (DDA), data-independent acquisition (DIA), or selected reaction monitoring (SRM). These workflows quantify proteins by summarizing the abundances of all the spectral features of the protein ( precursor ions, transitions or fragments) in a single value per protein per run. When abundances of some features are inconsistent with the overall protein profile (for technological reasons such as interferences, or for biological reasons such as post-translational modifications), the protein-level summaries and the downstream conclusions are undermined.

Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics.

Vendor-independent software tools for quantification of small molecules and metabolites are lacking, especially for targeted analysis workflows. Skyline is a freely available, open-source software tool for targeted quantitative mass spectrometry method development and data processing with a 10 year history supporting six major instrument vendors. Designed initially for proteomics analysis, we describe the expansion of Skyline to data for small molecule analysis, including selected reaction monitoring, high-resolution mass spectrometry, and calibrated quantification.

Standardization of PGC-LC-MS-based glycomics for sample specific glycotyping.

Porous graphitized carbon (PGC) based chromatography achieves high-resolution separation of glycan structures released from glycoproteins. This approach is especially valuable when resolving structurally similar isomers and for discovery of novel and/or sample-specific glycan structures. However, the implementation of PGC-based separations in glycomics studies has been limited because system-independent retention values have not been established to normalize technical variation.

Improving Precursor Selectivity in Data-Independent Acquisition Using Overlapping Windows.

A major goal of proteomics research is the accurate and sensitive identification and quantification of a broad range of proteins within a sample. Data-independent acquisition (DIA) approaches that acquire MS/MS spectra independently of precursor information have been developed to overcome the reproducibility challenges of data-dependent acquisition and the limited breadth of targeted proteomics strategies. Typical DIA implementations use wide MS/MS isolation windows to acquire comprehensive fragment ion data.

Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry.

Data independent acquisition (DIA) mass spectrometry is a powerful technique that is improving the reproducibility and throughput of proteomics studies. Here, we introduce an experimental workflow that uses this technique to construct chromatogram libraries that capture fragment ion chromatographic peak shape and retention time for every detectable peptide in a proteomics experiment. These coordinates calibrate protein databases or spectrum libraries to a specific mass spectrometer and chromatography setup, facilitating DIA-only pipelines and the reuse of global resource libraries.

Using Skyline to Analyze Data-Containing Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry Dimensions.

Recent advances in ion mobility spectrometry (IMS) have illustrated its power in determining the structural characteristics of a molecule, especially when coupled with other separations dimensions such as liquid chromatography (LC) and mass spectrometry (MS). However, these three separation techniques together greatly complicate data analyses, making better informatics tools essential for assessing the resulting data. In this manuscript, Skyline was adapted to analyze LC-IMS-CID-MS data from numerous instrument vendor datasets and determine the effect of adding the IMS dimension into the normal LC-MS molecular pipeline.

A Library of Phosphoproteomic and Chromatin Signatures for Characterizing Cellular Responses to Drug Perturbations.

Although the value of proteomics has been demonstrated, cost and scale are typically prohibitive, and gene expression profiling remains dominant for characterizing cellular responses to perturbations. However, high-throughput sentinel assays provide an opportunity for proteomics to contribute at a meaningful scale. We present a systematic library resource (90 drugs × 6 cell lines) of proteomic signatures that measure changes in the reduced-representation phosphoproteome (P100) and changes in epigenetic marks on histones (GCP).

Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses.

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is the main method for high-throughput identification and quantification of peptides and inferred proteins. Within this field, data-independent acquisition (DIA) combined with peptide-centric scoring, as exemplified by the technique SWATH-MS, has emerged as a scalable method to achieve deep and consistent proteome coverage across large-scale data sets. We demonstrate that statistical concepts developed for discovery proteomics based on spectrum-centric scoring can be adapted to large-scale DIA experiments that have been analyzed with peptide-centric scoring strategies, and we provide guidance on their application.