Multi-mode acquisition (MMA): An MS/MS acquisition strategy for maximizing selectivity, specificity and sensitivity of DIA product ion spectra

Acquisition and Analysis of DIA-Based Proteomic Data: A Comprehensive Survey in 2023

Data-independent acquisition (DIA) mass spectrometry (MS) has emerged as a powerful technology for high-throughput, accurate, and reproducible quantitative proteomics. This review provides a comprehensive overview of recent advances in both the experimental and computational methods for DIA proteomics, from data acquisition schemes to analysis strategies and software tools. DIA acquisition schemes are categorized based on the design of precursor isolation windows, highlighting wide-window, overlapping-window, narrow-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation-enhanced DIA methods. For DIA data analysis, major strategies are classified into spectrum reconstruction, sequence-based search, library-based search, de novo sequencing, and sequencing-independent approaches. A wide array of software tools implementing these strategies are reviewed, with details on their overall workflows and scoring approaches at different steps. The generation and optimization of spectral libraries, which are critical resources for DIA analysis, are also discussed. Publicly available benchmark datasets covering global proteomics and phosphoproteomics are summarized to facilitate performance evaluation of various software tools and analysis workflows. Continued advances and synergistic developments of versatile components in DIA workflows are expected to further enhance the power of DIA-based proteomics.

Deep representation features from DreamDIAXMBD improve the analysis of data-independent acquisition proteomics

We developed DreamDIA^XMBD (denoted as DreamDIA), a software suite based on a deep representation model for data-independent acquisition (DIA) data analysis. DreamDIA adopts a data-driven strategy to capture comprehensive information from elution patterns of peptides in DIA data and achieves considerable improvements on both identification and quantification performance compared with other state-of-the-art methods such as OpenSWATH, Skyline and DIA-NN. Specifically, in contrast to existing methods which use only 6 to 10 selected fragment ions from spectral libraries, DreamDIA extracts additional features from hundreds of theoretical elution profiles originated from different ions of each precursor using a deep representation network. To achieve higher coverage of target peptides without sacrificing specificity, the extracted features are further processed by nonlinear discriminative models under the framework of positive-unlabeled learning with decoy peptides as affirmative negative controls. DreamDIA is publicly available at https://github.com/xmuyulab/DreamDIA-XMBD for high coverage and accuracy DIA data analysis.

Molecular characterization of a fungal cyclophilin allergen Rhi o 2 and elucidation of antigenic determinants responsible for IgE-cross-reactivity

Cyclophilins are structurally conserved pan-allergens showing extensive cross-reactivity. So far, no precise information on cross-reactive IgE-epitopes of cyclophilins is available. Here, an 18-kDa IgE-reactive cyclophilin (Rhi o 2) was purified from Rhizopus oryzae, an indoor mold causing allergic sensitization. Based on LC-MS/MS-derived sequences of natural Rhi o 2, the full-length cDNA was cloned, and expressed as recombinant (r) allergen. Purified rRhi o 2 displayed IgE-reactivity and basophil degranulation with sera from all cyclophilin-positive patients. The melting curve of properly folded rRhi o 2 showed partial refolding after heat denaturation. The allergen displayed monomeric functional peptidyl-prolyl cis-trans isomerase (PPIase) activity. In IgE-inhibition assays, rRhi o 2 exhibited extensive cross-reactivity with various other cyclophilins reported as allergens from diverse sources including its homologous human autoantigen. By generating a series of deletion mutants, a conserved 69-residue (Asn⁸¹-Asn¹⁴⁹) fragment at C terminus of Rhi o 2 was identified as crucial for IgE-recognition and cross-reactivity. Grafting of the Asn⁸¹-Asn¹⁴⁹ fragment within the primary structure of yeast cyclophilin CPR1 by replacing its homologous sequence resulted in a hybrid molecule with structural folds similar to Rhi o 2. The IgE-reactivity and allergenic activity of the hybrid cyclophilin were greater than that of CPR1. Therefore, the Asn⁸¹-Asn¹⁴⁹ fragment can be considered as the site of IgE recognition of Rhi o 2. Hence, Rhi o 2 serves as a candidate antigen for the molecular diagnosis of mold allergy, and determination of a major cross-reactive IgE-epitope has clinical potential for the design of next-generation immunotherapeutics against cyclophilin-induced allergies.

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. However, wide isolation windows produce highly chimeric spectra, limiting the achievable sensitivity and accuracy of quantification and identification. Here, we present a DIA strategy in which spectra are collected with overlapping (rather than adjacent or random) windows and then computationally demultiplexed. This approach improves precursor selectivity by nearly a factor of 2, without incurring any loss in mass range, mass resolution, chromatographic resolution, scan speed, or other key acquisition parameters. We demonstrate a 64% improvement in sensitivity and a 17% improvement in peptides detected in a 6-protein bovine mix spiked into a yeast background. To confirm the method's applicability to a realistic biological experiment, we also analyze the regulation of the proteasome in yeast grown in rapamycin and show that DIA experiments with overlapping windows can help elucidate its adaptation toward the degradation of oxidatively damaged proteins. Our integrated computational and experimental DIA strategy is compatible with any DIA-capable instrument. The computational demultiplexing algorithm required to analyze the data has been made available as part of the open-source proteomics software tools Skyline and msconvert (Proteowizard), making it easy to apply as part of standard proteomics workflows. Graphical Abstract.

Application of the broadband collision-induced dissociation (bbCID) mass spectrometry approach for protein glycosylation and phosphorylation analysis

RATIONALE

Analysis of post-translationally modified peptides by mass spectrometry (MS) remains incomplete, in part due to incomplete sampling of all peptides which is inherent to traditional data-dependent acquisition (DDA). An alternative MS approach, data-independent acquisition (DIA), enables comprehensive recording of all detectable precursor and product ions, independent of precursor intensity. The use of broadband collision-induced dissociation (bbCID), a DIA method, was evaluated for the identification of protein glycosylation and phosphorylation.

METHODS

bbCID was applied to identify glycopeptides and phosphopeptides generated from standard proteins using a high-resolution Bruker maXis 3G mass spectrometer. In bbCID, precursor and product ion spectra were obtained by alternating low and high collision energy. Precursor ions were assigned manually based on the detection of diagnostic ions specific to either glycosylation or phosphorylation. The composition of the glycan modification was resolved in the positive ion mode, while the level of phosphorylation was investigated in the negative ion mode.

RESULTS

The results demonstrate for the first time that the use of a bbCID approach is suitable for the identification of glycopeptides and phosphopeptides based on the detection of specific diagnostic and associated precursor ions. The novel use of bbCID in negative ion mode allowed the discrimination of singly and multiply phosphorylated peptides based on the detection of phosphate diagnostic ions. The results also demonstrate the ability of this approach to allow the identification of glycan composition in N- and O-linked glycopeptides, in positive ion mode.

CONCLUSIONS

We contend that bbCID is a valuable addition to the existing toolkit for PTM discovery. Moreover, this technique could be employed to direct targeted proteomics methods, particularly where there is no a priori information on glycosylation or phosphorylation status. This technique is immediately relevant to the characterisation of individual proteins or biological samples of low complexity, as demonstrated for the analysis of the glycosylation status of a therapeutic protein.

Scanning Quadrupole Data-Independent Acquisition, Part A: Qualitative and Quantitative Characterization

A novel data-independent acquisition (DIA) method incorporating a scanning quadrupole in front of a collision cell and orthogonal acceleration time-of-flight mass analyzer is described. The method has been characterized for the qualitative and quantitative label-free proteomic analysis of complex biological samples. The principle of the scanning quadrupole DIA method is discussed, and analytical instrument characteristics, such as the quadrupole transmission width, scan/integration time, and chromatographic separation, have been optimized in relation to sample complexity for a number of different model proteomes of varying complexity and dynamic range including human plasma, cell lines, and bacteria. In addition, the technological merits over existing DIA approaches are described and contrasted. The qualitative and semiquantitative performance of the method is illustrated for the analysis of relatively simple protein digest mixtures and a well-characterized human cell line sample using untargeted and targeted search strategies. Finally, the results from a human cell line were compared against publicly available data that used similar chromatographic conditions but were acquired with DDA technology and alternative mass analyzer systems. Qualitative comparison showed excellent concordance of results with >90% overlap of the detected proteins.

Online Hydrogen-Deuterium Exchange Traveling Wave Ion Mobility Mass Spectrometry (HDX-IM-MS): a Systematic Evaluation

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) is an important tool for measuring and monitoring protein structure. A bottom-up approach to HDX-MS provides peptide level deuterium uptake values and a more refined localization of deuterium incorporation compared with global HDX-MS measurements. The degree of localization provided by HDX-MS is proportional to the number of peptides that can be identified and monitored across an exchange experiment. Ion mobility spectrometry (IMS) has been shown to improve MS-based peptide analysis of biological samples through increased separation capacity. The integration of IMS within HDX-MS workflows has been commercialized but presently its adoption has not been widespread. The potential benefits of IMS, therefore, have not yet been fully explored. We herein describe a comprehensive evaluation of traveling wave ion mobility integrated within an online-HDX-MS system and present the first reported example of UDMS^E acquisition for HDX analysis. Instrument settings required for optimal peptide identifications are described and the effects of detector saturation due to peak compression are discussed. A model system is utilized to confirm the comparability of HDX-IM-MS and HDX-MS uptake values prior to an evaluation of the benefits of IMS at increasing sample complexity. Interestingly, MS and IM-MS acquisitions were found to identify distinct populations of peptides that were unique to the respective methods, a property that can be utilized to increase the spatial resolution of HDX-MS experiments by >60%. Graphical Abstract ᅟ.

DIA is not a new mass spectrometry acquisition method

Contrary to what is being said by several colleagues (and even advertised), data-independent analysis/acquisition (DIA) is not a new mass spectrometry acquisition method. Here we draw a timeline of events showing that DIA has been around since the early 2000s.

Exploring novel paths towards protein signatures of chronic pain

Pain is a major symptom of many medical conditions and the worldwide number one reason for people to seek medical assistance. It affects the quality of life of patients and poses a heavy financial burden on society with high costs of treatment and lost productivity. Furthermore, the treatment of chronic pain presents a big challenge as pain therapeutics often lack efficacy and exhibit minimal safety profiles. The latter can be largely attributed to the fact that current therapies target molecules with key physiological functions throughout the body. In light of these difficulties, the identification of proteins specifically involved in chronic pain states is of paramount importance for designing selective interventions. Several profiling efforts have been employed with the aim to dissect the molecular underpinnings of chronic pain, both on the level of the transcriptome and proteome. However, generated results are often inconsistent and non-overlapping, which is largely due to inherent technical constraints. A potential solution may be offered by emerging strategies capable of performing standardized and reproducible proteome analysis, such as data-independent acquisition-mass spectrometry (DIA-MS). We have recently demonstrated the applicability of DIA-MS to interrogate chronic pain-related proteome alterations in mice. Based on our results, we aim to provide an overview on DIA-MS and its potential to contribute to the comprehensive characterization of molecular signatures underlying pain pathologies.