Perspective: The complex relationship between charge, mobility, and gas-phase protein structure.

Ion mobility spectrometry coupled to mass spectrometry (IMS/MS) is a widely used tool for biomolecular separations and structural elucidation. The application of IMS/MS has resulted in exciting developments in structural proteomics and genomics. This perspective gives a brief background of the field, addresses some of the important issues in making structural measurements, and introduces complementary techniques.

Investigating direct current potentials that affect native protein conformation during trapped ion mobility spectrometry-mass spectrometry.

Trapped ion mobility spectrometry-time-of-flight mass spectrometry (TIMS-TOFMS) has emerged as a tool to study protein conformational states. In TIMS, gas-phase ions are guided across the IM stages by applying direct current (DC) potentials (D1-6), which, however, might induce changes in protein structures through collisional activation. To define conditions for native protein analysis, we evaluated the influence of these DC potentials using the metalloenzyme bovine carbonic anhydrase (BCA) as primary test compound. The variation of DC potentials did not change BCA-ion charge and heme content but affected (relative) charge-state intensities and adduct retention. Constructed extracted-ion mobilograms and corresponding collisional cross-section (CCS) profiles gave useful insights in (alterations of) protein conformational state. For BCA, the D3 and D6 potential (which are applied between the deflection transfer and funnel 1 [F1] and the accumulation exit and the start of the ramp, respectively) had most profound effects, showing multimodal CCS distributions at higher potentials indicating gradual unfolding. The other DC potentials only marginally altered the CCS profiles of BCA. To allow for more general conclusions, five additional proteins of diverse molecular weight and conformational stability were analyzed, and for the main protein charge states, CCS profiles were constructed. Principal component analysis (PCA) of the obtained data showed that D1 and D3 exhibit the highest degree of correlation with the ratio of folded and unfolded protein (F/U) as extracted from the mobilograms obtained per set D potential. The correlation of D6 with F/U and protein charge were similar, and D2, D4, and D5 showed an inverse correlation with F/U but were correlated with protein charge. Although DC boundary values for induced conformational changes appeared protein dependent, a set of DC values could be determined, which assured native analysis of most proteins.

From the grapevine to the glass: A wine metabolomics tale by FT-ICR-MS.

Wine is one of the most consumed beverages around the world. Its unique characteristics arise from numerous processes, from the selection of grapevine varieties and grapes, the effect of the terroir and geographical origin, through the biochemical process of fermentation by microorganisms, until its aging. All molecules found in wine define its chemical fingerprint and can be used to tell the story of its origin, production, authenticity and quality. Wine's chemical composition can be characterized using an untargeted metabolomics approach based on extreme resolution mass spectrometry. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is currently the most powerful analytical technique to analyse such complex sample, providing the most comprehensive analysis of the chemical fingerprint of wine.

Drivers of the In-Mouth Interaction between Lupin Protein Isolate and Selected Aroma Compounds: A Proton Transfer Reaction-Mass Spectrometry and Dynamic Time Intensity Analysis.

Plant proteins often carry off-notes, necessitating customized aroma addition. In vitro studies revealed protein-aroma binding, limiting release during consumption. This study employs in vivo nose space proton transfer reaction-time-of-flight-mass spectrometry and dynamic sensory evaluation (time intensity) to explore in-mouth interactions. In a lupin protein-based aqueous system, a sensory evaluation of a trained "green" attribute was conducted simultaneously with aroma release of hexanal, nonanal, and 2-nonanone during consumption. Results demonstrated that enlarging aldehyde chains and relocating the keto group reduced maximum perceived intensity (Imax_R) by 71.92 and 72.25%. Protein addition decreased Imax_R by 30.91, 36.84, and 72.41%, indicating protein-aroma interactions. Sensory findings revealed a perceived intensity that was lower upon protein addition. Aroma lingering correlated with aroma compounds' volatility and hydrophobicity, with nonanal exhibiting the longest persistence. In vitro mucin addition increased aroma binding four to 12-fold. Combining PTR-ToF-MS and time intensity elucidated crucial food behavior, i.e., protein-aroma interactions, that are pivotal for food design.

Enrichment methods of N-linked glycopeptides from human serum or plasma: A mini-review.

Human diseases often correlate with changes in protein glycosylation, which can be observed in serum or plasma samples. N-glycosylation, the most common form, can provide potential biomarkers for disease prognosis and diagnosis. However, glycoproteins constitute a relatively small proportion of the total proteins in human serum and plasma compared to the non-glycosylated protein albumin, which constitutes the majority. The detection of microheterogeneity and low glycan abundance presents a challenge. Mass spectrometry facilitates glycoproteomics research, yet it faces challenges due to interference from abundant plasma proteins. Therefore, methods have emerged to enrich N-glycans and N-linked glycopeptides using glycan affinity, chemical properties, stationary phase chemical coupling, bioorthogonal techniques, and other alternatives. This review focuses on N-glycans and N-glycopeptides enrichment in human serum or plasma, emphasizing methods and applications. Although not exhaustive, it aims to elucidate principles and showcase the utility and limitations of glycoproteome characterization.

Simultaneous determination of inflammatory factors SAA and LTF based on stable element labeling and inductively coupled plasma mass spectrometry to aid in the diagnosis of infection.

OBJECTIVE: The clinical value of Serum amyloid A (SAA) and Lactoferrin (LTF) has received significant attention, but their detection methods are inadequate, which limits their application. This study aims to develop a dual detection method based on stable element labeling strategies and inductively coupled plasma mass spectrometry (ICP-MS) for SAA/LTF and to assess whether it can be widely used in clinical practice. METHODS: A duplex immunoassay system based on sandwich method was constructed. After optimization, methodological evaluation was performed with the guidelines of Clinical Laboratory Standards Institute (CLSI). Finally, 131 plasma samples were collected to analyze whether the new method is suitable for clinical detection. RESULTS: The LoB, LLoQ, ULoQ, and linear range of the assay were 1.09 ng/mL, 3 ng/mL, 1500 ng/mL, 3-1500 ng/mL for SAA and 0.85 ng/mL, 2 ng/mL, 1200 ng/mL, 2-1200 ng/mL for LTF respectively. The recovery rates were 95.01% to 106.26%, the intra-batch precision of low, intermediate, and high-level samples was <8%, and the inter-batch of them was <11%, the deviation of interference test results was less than±10%. The Area Under the Curve (AUC) was 0.9809 for SAA, 0.8599 for LTF, and 0.9986 for combination. CONCLUSION: The quantitative duplex immunoassay for SAA/LTF has high accuracy, good precision, and high specificity, which meets the clinical testing requirements and can be widely used in clinical practice.

Screening for Forensically Relevant Drugs Using Data-Independent High-Resolution Mass Spectrometry.

Forensic and clinical laboratories are expected to provide a rapid screening of samples for a wide range of analytes; however, the ever-changing landscape of illicit substances makes analysis complicated. There is a great need for untargeted methods that can aid these laboratories in broad-scope drug screening. Liquid chromatography hyphenated with high-resolution mass spectrometry (LC-HRMS) has become a popular technique for untargeted screening and presumptive identification of drugs of abuse due to its superior sensitivity and detection capabilities in complex matrices. An untargeted extraction and data acquisition method was evaluated for the broad screening of high-priority drugs of abuse in whole blood. A total of 35 forensically relevant target analytes were identified and extracted at biologically relevant low and high (10× low) concentrations from whole blood using supported liquid extraction. Data-independent acquisition was accomplished using ultraperformance liquid chromatography and a quadrupole time-of-flight mass spectrometry. Results were acceptable for screening assays, with limits of detection at or below the recommended low-concentration cutoffs for most analytes. Analyte ionization varied from 30.1 to 267.6% (average: 110.5%) at low concentrations and from 8.6 to 383.5% (average: 93.6%) at high concentrations. Extraction recovery ranged from 8.5 to 330.5% (average: 105.3%) at low concentrations and from 9.4 to 127.5% (average: 82.7%) at high concentrations. This variability was also captured as precision, ranging from 4.7 to 135.2% (average: 36.5%) at low concentrations and from 0.9 to 59.0% (average: 21.7%) at high concentrations. The method described in this work is efficient and effective for qualitative forensic toxicology screening, as demonstrated by analysis of 166 authentic suspected impaired driver and postmortem specimens. That said, it is critical that laboratories establishing untargeted LC-HRMS screening assays be aware of the strengths and limitations across diverse drug categories and chemical structures.

Exposing the molecular heterogeneity of glycosylated biotherapeutics.

The heterogeneity inherent in today's biotherapeutics, especially as a result of heavy glycosylation, can affect a molecule's safety and efficacy. Characterizing this heterogeneity is crucial for drug development and quality assessment, but existing methods are limited in their ability to analyze intact glycoproteins or other heterogeneous biotherapeutics. Here, we present an approach to the molecular assessment of biotherapeutics that uses proton-transfer charge-reduction with gas-phase fractionation to analyze intact heterogeneous and/or glycosylated proteins by mass spectrometry. The method provides a detailed landscape of the intact molecular weights present in biotherapeutic protein preparations in a single experiment. For glycoproteins in particular, the method may offer insights into glycan composition when coupled with a suitable bioinformatic strategy. We tested the approach on various biotherapeutic molecules, including Fc-fusion, VHH-fusion, and peptide-bound MHC class II complexes to demonstrate efficacy in measuring the proteoform-level diversity of biotherapeutics. Notably, we inferred the glycoform distribution for hundreds of molecular weights for the eight-times glycosylated fusion drug IL22-Fc, enabling correlations between glycoform sub-populations and the drug's pharmacological properties. Our method is broadly applicable and provides a powerful tool to assess the molecular heterogeneity of emerging biotherapeutics.

Identification of heavily glycated proteoforms by hydrophilic-interaction liquid chromatography and native size-exclusion chromatography - High-resolution mass spectrometry.

BACKGROUND: The non-enzymatic glycation of proteins and their advanced glycation end products (AGEs) are associated with protein transformations such as in the development of diseases and biopharmaceutical storage. The characterization of heavily glycated proteins at the intact level is of high interest as it allows to describe co-occurring protein modifications. However, the high heterogeneity of glycated protein makes this process challenging, and novel methods are required to accomplish this. RESULTS: In this study, we investigated two novel LC-HRMS methods to study glycated reference proteins at the intact protein level: low-flow hydrophilic-interaction liquid chromatography (HILIC) and native size-exclusion chromatography (SEC). Model proteins were exposed to conditions that favored extensive glycation and the formation of AGEs. After glycation, complicated MS spectra were observed, along with a sharply reduced signal response, possibly due to protein denaturation and the formation of aggregates. When using HILIC-MS, the glycated forms of the proteins could be resolved based on the number of reducing monosaccharides. Moreover, some positional glycated isomers were separated. The SEC-MS method under non-denaturing conditions provided insights into glycated aggregates but offered only a limited separation of glycated species based on molar mass. Overall, more than 25 different types of species were observed in both methods, differing in molar mass by 14-162 Da. 19 of these species have not been previously reported. SIGNIFICANCE: The proposed strategies show great potential to characterize highly glycated intact proteins from native and denaturing perspectives and provide new opportunities for fast clinical diagnoses and investigating glycation-related diseases.

Particle Size Measurement and Detection of Bound Proteins of Non-Porous/Mesoporous Silica Microspheres by Single-Particle Inductively Coupled Plasma Mass Spectrometry.

Single-particle inductively coupled plasma mass spectrometry (spICP-MS) has been used for particle size measurement of diverse types of individual nanoparticles and micrometer-sized carbon-based particles such as microplastics. However, its applicability to the measurement of micrometer-sized non-carbon-based particles such as silica (SiO2) particles is unclear. In this study, the applicability of spICP-MS to particle size measurement of non-porous/mesoporous SiO2 microspheres with a nominal diameter of 5.0 µm or smaller was investigated. Particle sizes of these microspheres were measured using both spICP-MS based on a conventional calibration approach using an ion standard solution and scanning electron microscopy as a reference technique, and the results were compared. The particle size distributions obtained using both techniques were in agreement within analytical uncertainty. The applicability of this technique to the detection of metal-containing protein-binding mesoporous SiO2 microspheres was also investigated. Bound iron (Fe)-containing proteins (i.e., lactoferrin and transferrin) of mesoporous SiO2 microspheres were detected using Fe as a presence marker for the proteins. Thus, spICP-MS is applicable to the particle size measurement of large-sized and non-porous/mesoporous SiO2 microspheres. It has considerable potential for element-based detection and qualification of bound proteins of mesoporous SiO2 microspheres in a variety of applications.

Mass Spectrometry for Biomedical and Food Analysis.

Biomedical and food analysis has always been an important topic that closely relates to health [...].

Trace the origin of yak meat in Xizang based on stable isotope combined with multivariate statistics.

In this study, the feasibility of tracing the origin of yak meat in Xizang Autonomous Region based on stable isotope combined with multivariable statistics was researched. The δ13C, δ15N, δ2H and δ18O in yak meat were determined by stable isotope ratio mass spectrometry, and the data were analyzed by analysis of variance, fisher discriminant analysis (FDA), back propagation (BP) neural network and orthogonal partial least squares discrimination analysis (OPLS-DA). The results showed that the δ13C, δ15N, δ2H and δ18O had significant differences among different origins (P < 0.05). The overall original correct discrimination rate of fisher discriminant analysis was 89.7 %, and the correct discrimination rate of cross validation was 88.2 %. The correct classification rate of BP neural network based on training set was 93.38 %, and the correct classification rate of BP neural network based on test set was 89.83 %. The OPLS-DA model interpretation rate parameter R2Y was 0.67, the model prediction rate parameter Q2 was 0.409, which could distinguish yak meat from seven different producing areas in Xizang Autonomous Region. The results showed that the origin of yak meat in Xizang Autonomous Region can be traced based on stable isotope combined with multivariate statistics.

A millimeter water-in-oil droplet as an alternative back exchange prevention strategy for hydrogen/deuterium exchange mass spectrometry of peptides/proteins.

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) is a versatile bioanalytical technique for protein analysis. Since the reliability of HDX-MS analysis considerably depends on the retention of deuterium labels in the post-labeling workflow, deuterium/hydrogen (D/H) back exchange prevention strategies, including decreasing the pH, temperature, and exposure time to protic sources of the deuterated samples, are widely adopted in the conventional HDX-MS protocol. Herein, an alternative and effective back exchange prevention strategy based on the encapsulation of a millimeter droplet of a labeled peptide solution in a water-immiscible organic solvent (cyclohexane) is proposed. Cyclohexane was used to prevent the undesirable uptake of water by the droplet from the atmospheric vapor through the air-water interface. Using the pepsin digest of deuterated myoglobin, our results show that back exchange kinetics of deuterated peptides is retarded in a millimeter droplet as compared to that in the bulk solution. Performing pepsin digestion directly in a water-in-oil droplet at room temperature (18-21 °C) was found to preserve more deuterium labels than that in the bulk digestion with an ice-water bath. Based on the present findings, it is proposed that keeping deuterated peptides in the form of water-in-oil droplets during the post-labelling workflow will facilitate the preservation of deuterium labels on the peptide backbone and thereby enhance the reliability of the H/D exchange data.

Utilising Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to track the oxidation of lignin by an alkaliphilic laccase.

Lignin is a complex heteroaromatic polymer which is one of the most abundant and diverse biopolymers on the planet. It comprises approximately one third of all woody plant matter, making it an attractive candidate as an alternative, renewable feedstock to petrochemicals to produce fine chemicals. However, the inherent complexity of lignin makes it difficult to analyse and characterise using common analytical techniques, proving a hindrance to the utilisation of lignin as a green chemical feedstock. Herein we outline the tracking of lignin degradation by an alkaliphilic laccase in a semi-quantitative manner using a combined chemical analysis approach using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to characterise shifts in chemical diversity and relative abundance of ions, and NMR to highlight changes in the structure of lignin. Specifically, an alkaliphilic laccase was used to degrade an industrially relevant lignin, with compounds such as syringaresinol being almost wholly removed (95%) after 24 hours of treatment. Structural analyses reinforced these findings, indicating a >50% loss of NMR signal relating to ß-ß linkages, of which syringaresinol is representative. Ultimately, this work underlines a combined analytical approach that can be used to gain a broader semi-quantitative understanding of the enzymatic activity of laccases within a complex, non-model mixture.

PS2MS: A Deep Learning-Based Prediction System for Identifying New Psychoactive Substances Using Mass Spectrometry.

The rapid proliferation of new psychoactive substances (NPS) poses significant challenges to conventional mass-spectrometry-based identification methods due to the absence of reference spectra for these emerging substances. This paper introduces PS2MS, an AI-powered predictive system designed specifically to address the limitations of identifying the emergence of unidentified novel illicit drugs. PS2MS builds a synthetic NPS database by enumerating feasible derivatives of known substances and uses deep learning to generate mass spectra and chemical fingerprints. When the mass spectrum of an analyte does not match any known reference, PS2MS simultaneously examines the chemical fingerprint and mass spectrum against the putative NPS database using integrated metrics to deduce possible identities. Experimental results affirm the effectiveness of PS2MS in identifying cathinone derivatives within real evidence specimens, signifying its potential for practical use in identifying emerging drugs of abuse for researchers and forensic experts.

Epitope Mapping of Japanese Encephalitis Virus Neutralizing Antibodies by Native Mass Spectrometry and Hydrogen/Deuterium Exchange.

Japanese encephalitis virus (JEV) remains a global public health concern due to its epidemiological distribution and the existence of multiple strains. Neutralizing antibodies against this infection have shown efficacy in in vivo studies. Thus, elucidation of the epitopes of neutralizing antibodies can aid in the design and development of effective vaccines against different strains of JEV. Here, we describe a combination of native mass spectrometry (native-MS) and hydrogen/deuterium exchange mass spectrometry (HDX-MS) to complete screening of eight mouse monoclonal antibodies (MAbs) against JEV E-DIII to identify epitope regions. Native-MS was used as a first pass to identify the antibodies that formed a complex with the target antigen, and it revealed that seven of the eight monoclonal antibodies underwent binding. Native mass spectra of a MAb (JEV-27) known to be non-binding showed broad native-MS peaks and poor signal, suggesting the protein is a mixture or that there are impurities in the sample. We followed native-MS with HDX-MS to locate the binding sites for several of the complex-forming antibodies. This combination of two mass spectrometry-based approaches should be generally applicable and particularly suitable for screening of antigen-antibody and other protein-protein interactions when other traditional approaches give unclear results or are difficult, unavailable, or need to be validated.

Qualitative and Quantitative Analytical Techniques of Nucleic Acid Modification Based on Mass Spectrometry for Biomarker Discovery.

Nucleic acid modifications play important roles in biological activities and disease occurrences, and have been considered as cancer biomarkers. Due to the relatively low amount of nucleic acid modifications in biological samples, it is necessary to develop sensitive and reliable qualitative and quantitative methods to reveal the content of any modifications. In this review, the key processes affecting the qualitative and quantitative analyses are discussed, such as sample digestion, nucleoside extraction, chemical labeling, chromatographic separation, mass spectrometry detection, and data processing. The improvement of the detection sensitivity and specificity of analytical methods based on mass spectrometry makes it possible to study low-abundance modifications and their biological functions. Some typical nucleic acid modifications and their potential as biomarkers are displayed, and efforts to improve diagnostic accuracy are discussed. Future perspectives are raised for this research field.

Data-Independent Acquisition Peptidomics.

In recent years, data-independent acquisition (DIA) has emerged as a powerful analysis method in biological mass spectrometry (MS). Compared to the previously predominant data-dependent acquisition (DDA), it offers a way to achieve greater reproducibility, sensitivity, and dynamic range in MS measurements. To make DIA accessible to non-expert users, a multifunctional, automated high-throughput pipeline DIAproteomics was implemented in the computational workflow framework "Nextflow" ( https://nextflow.io ). This allows high-throughput processing of proteomics and peptidomics DIA datasets on diverse computing infrastructures. This chapter provides a short summary and usage protocol guide for the most important modes of operation of this pipeline regarding the analysis of peptidomics datasets using the command line. In brief, DIAproteomics is a wrapper around the OpenSwathWorkflow and relies on either existing or ad-hoc generated spectral libraries from matching DDA runs. The OpenSwathWorkflow extracts chromatograms from the DIA runs and performs chromatographic peak-picking. Further downstream of the pipeline, these peaks are scored, aligned, and statistically evaluated for qualitative and quantitative differences across conditions depending on the user's interest. DIAproteomics is open-source and available under a permissive license. We encourage the scientific community to use or modify the pipeline to meet their specific requirements.

Quantitative Peptidomics Using Reductive Methylation of Amines.

A number of different approaches have been used for quantitative peptidomics. In this protocol, we describe the method in which peptides are reacted with formaldehyde and sodium cyanoborohydride, which converts primary and secondary amines into tertiary amines. By using different combinations of regular reagents, deuterated reagents (2H), and reagents containing deuterium and 13C, it is possible to produce five isotopically distinct forms of the methylated peptides, which can be quantified by mass spectrometry. Peptides with free N-termini that are primary amines incorporate two methyl groups using this procedure, which differ by 2 Da for each of the five isotopic combinations. Peptides that contain unmodified lysine residues incorporate additional pairs of methyl groups, leading to larger mass differences between isotopic forms. The reagents are commercially available, relatively inexpensive, and chemically stable.