Sensitive and Accurate Proteome Profiling of Embryogenesis Using Real-Time Search and TMTproC Quantification.

Multiplexed proteomics has become a powerful tool for investigating biological systems. Using balancer-peptide conjugates (e.g.

Autonomous Dissociation-type Selection for Glycoproteomics Using a Real-Time Library Search.

Tandem mass spectrometry (MS/MS) is the gold standard for intact glycopeptide identification, enabling peptide sequence elucidation and site-specific localization of glycan compositions. Beam-type collisional activation is generally sufficient for glycopeptides, while electron-driven dissociation is crucial for site localization in glycopeptides. Modern glycoproteomic methods often employ multiple dissociation techniques within a single LC-MS/MS analysis, but this approach frequently sacrifices sensitivity when analyzing multiple glycopeptide classes simultaneously.

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.

Deep Proteomic Compound Profiling with the Orbitrap Ascend Tribrid Mass Spectrometer Using Tandem Mass Tags and Real-Time Search.

Tandem mass tags (TMT) and tribrid mass spectrometers are a powerful combination for high-throughput proteomics with high quantitative accuracy. Increasingly, this technology is being used to map the effects of drugs on the proteome. However, the depth of proteomic profiling is still limited by sensitivity and speed.

Real-Time Spectral Library Matching for Sample Multiplexed Quantitative Proteomics.

Sample multiplexed quantitative proteomics assays have proved to be a highly versatile means to assay molecular phenotypes. Yet, stochastic precursor selection and precursor coisolation can dramatically reduce the efficiency of data acquisition and quantitative accuracy. To address this, intelligent data acquisition (IDA) strategies have recently been developed to improve instrument efficiency and quantitative accuracy for both discovery and targeted methods.

Dynamic Data-Independent Acquisition Mass Spectrometry with Real-Time Retrospective Alignment.

Data-independent acquisition (DIA) mass spectrometry has grown in popularity in recent years, because of the reproducibility and quantitative rigor of a systematic tandem mass spectrometry (MS/MS) sampling method. However, traditional DIA methods may spend valuable instrument time acquiring MS/MS spectra with no usable information in them, affecting sensitivity and quantitative performance. We developed a DIA strategy that dynamically adjusts the MS/MS windows during the chromatographic separation.

Improved Structural Characterization of Glycerophospholipids and Sphingomyelins with Real-Time Library Searching.

In mass spectrometry-based lipidomics, complex lipid mixtures undergo chromatographic separation, are ionized, and are detected using tandem MS (MS) to simultaneously quantify and structurally characterize eluting species. The reported structural granularity of these identified lipids is strongly reliant on the analytical techniques leveraged in a study. For example, lipid identifications from traditional collisionally activated data-dependent acquisition experiments are often reported at either species level or molecular species level.

Novel Real-Time Library Search Driven Data Acquisition Strategy for Identification and Characterization of Metabolites.

Structural characterization of novel metabolites in drug discovery or metabolomics is one of the most challenging tasks. Multilevel fragmentation (MS) based approaches combined with various dissociation modes are frequently utilized for facilitating structure assignment of unknown compounds. As each of the MS precursors undergoes MS, the instrument cycle time can limit the total number of precursors analyzed in a single LC run for complex samples.

Benchmarking the Orbitrap Tribrid Eclipse for Next Generation Multiplexed Proteomics.

The rise of sample multiplexing in quantitative proteomics for the dissection of complex phenotypic comparisons has been advanced by the development of ever more sensitive and robust instrumentation. Here, we evaluated the utility of the Orbitrap Eclipse Tribrid mass spectrometer (advanced quadrupole filter, optimized FTMS scan overhead) and new instrument control software features (Precursor Fit filtering, TurboTMT and Real-time Peptide Search filtering). Multidimensional comparisons of these novel features increased total peptide identifications by 20% for SPS-MS methods and 14% for HRMS methods.

Unabridged Analysis of Human Histone H3 by Differential Top-Down Mass Spectrometry Reveals Hypermethylated Proteoforms from MMSET/NSD2 Overexpression.

Histones, and their modifications, are critical components of cellular programming and epigenetic inheritance. Recently, cancer genome sequencing has uncovered driver mutations in chromatin modifying enzymes spurring high interest how such mutations change histone modification patterns. Here, we applied Top-Down mass spectrometry for the characterization of combinatorial modifications (i.

Comparison of data acquisition strategies on quadrupole ion trap instrumentation for shotgun proteomics.

The most common data collection in shotgun proteomics is via data-dependent acquisition (DDA), a process driven by an automated instrument control routine that directs MS/MS acquisition from the highest abundant signals to the lowest. An alternative to DDA is data-independent acquisition (DIA), a process in which a specified range in m/z is fragmented without regard to prioritization of a precursor ion or its relative abundance in the mass spectrum, thus potentially offering a more comprehensive analysis of peptides than DDA. In this work, we evaluate both DDA and DIA on three different linear ion trap instruments: an LTQ, an LTQ modified with an electrodynamic ion funnel, and an LTQ Velos.

Novel parallelized quadrupole/linear ion trap/Orbitrap tribrid mass spectrometer improving proteome coverage and peptide identification rates.

Proteome coverage and peptide identification rates have historically advanced in line with improvements to the detection limits and acquisition rate of the mass spectrometer. For a linear ion trap/Orbitrap hybrid, the acquisition rate has been limited primarily by the duration of the ion accumulation and analysis steps. It is shown here that the spectral acquisition rate can be significantly improved through extensive parallelization of the acquisition process using a novel mass spectrometer incorporating quadrupole, Orbitrap, and linear trap analyzers.

Multiplexed MS/MS for improved data-independent acquisition.

In mass spectrometry-based proteomics, data-independent acquisition (DIA) strategies can acquire a single data set useful for both identification and quantification of detectable peptides in a complex mixture. However, DIA data are noisy owing to a typical five- to tenfold reduction in precursor selectivity compared to data obtained with data-dependent acquisition or selected reaction monitoring. We demonstrate a multiplexing strategy, MSX, for DIA analysis that increases precursor selectivity fivefold.

Evaluation of front-end higher energy collision-induced dissociation on a benchtop dual-pressure linear ion trap mass spectrometer for shotgun proteomics.

We report the implementation of front-end higher energy collision-induced dissociation (fHCD) on a benchtop dual-pressure linear ion trap. Software and hardware modifications were employed, described in detail vide-infra, to allow isolated ions to undergo collisions with ambient gas molecules in an intermediate multipole (q00) of the instrument. Results comparing the performance of fHCD and resonance excitation collision-induced dissociation (RE-CID) in terms of injection time, total number of scans, efficiency, mass measurement accuracy (MMA), unique peptide identifications, and spectral quality of labile modified peptides are presented.

A high voltage asymmetric waveform generator for FAIMS.

High field asymmetric waveform ion mobility spectrometry (FAIMS) has been used increasingly in recent years as an additional method of ion separation and selection before mass spectrometry. The FAIMS electrodes are relatively simple to design and fabricate for laboratories wishing to implement their own FAIMS designs. However, construction of the electronics apparatus needed to produce the required high magnitude asymmetric electric field oscillating at a frequency of several hundred kilohertz is not trivial.

Assessing the dynamic range and peak capacity of nanoflow LC-FAIMS-MS on an ion trap mass spectrometer for proteomics.

Proteomics experiments on complex mixtures have benefited greatly from the advent of fast-scanning ion trap mass spectrometers. However, the complexity and dynamic range of mixtures analyzed using shotgun proteomics is still beyond what can be sampled by data-dependent acquisition. Furthermore, the total liquid chromatography-mass spectrometry (LC-MS) peak capacity is not sufficient to resolve the precursors within these mixtures, let alone acquire tandem mass spectra on all of them.

Label-free comparative analysis of proteomics mixtures using chromatographic alignment of high-resolution muLC-MS data.

Label-free relative quantitative proteomics is a powerful tool for the survey of protein level changes between two biological samples. We have developed and applied an algorithm using chromatographic alignment of microLC-MS runs to improve the detection of differences between complex protein mixtures. We demonstrate the performance of our software by finding differences in E.

Semi-supervised learning for peptide identification from shotgun proteomics datasets.

Shotgun proteomics uses liquid chromatography-tandem mass spectrometry to identify proteins in complex biological samples. We describe an algorithm, called Percolator, for improving the rate of confident peptide identifications from a collection of tandem mass spectra. Percolator uses semi-supervised machine learning to discriminate between correct and decoy spectrum identifications, correctly assigning peptides to 17% more spectra from a tryptic Saccharomyces cerevisiae dataset, and up to 77% more spectra from non-tryptic digests, relative to a fully supervised approach.