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Dysregulated glycerophospholipid (GP) metabolism in the brain is associated with the progression of neurodegenerative diseases including Alzheimer's disease (AD). Routine liquid chromatography-mass spectrometry (LC-MS)-based large-scale lipidomic methods often fail to elucidate subtle yet important structural features such as sn-position, hindering the precise interrogation of GP molecules. Leveraging high-resolution demultiplexing (HRdm) ion mobility spectrometry (IMS), we develop a four-dimensional (4D) lipidomic strategy to resolve GP sn-position isomers. We further construct a comprehensive experimental 4D GP database of 498 GPs identified from the mouse brain and an in-depth extended 4D library of 2500 GPs predicted by machine learning, enabling automated profiling of GPs with detailed acyl chain sn-position assignment. Analyzing three mouse brain regions (hippocampus, cerebellum, and cortex), we successfully identify a total of 592 GPs including 130 pairs of sn-position isomers. Further temporal GPs analysis in the three functional brain regions illustrates their metabolic alterations in AD progression., (© 2024. The Author(s).)

Fragile X syndrome (FXS), the leading cause of inherited intellectual disability and autism, is caused by the transcriptional silencing of the FMR1 gene, which encodes the fragile X messenger ribonucleoprotein (FMRP). FMRP interacts with numerous brain mRNAs that are involved in synaptic plasticity and implicated in autism spectrum disorders. Our published studies indicate that single-source, soy-based diets are associated with increased seizures and autism. Thus, there is an acute need for an unbiased protein marker identification in FXS in response to soy consumption. Herein, we present a spatial proteomics approach integrating mass spectrometry imaging with label-free proteomics in the FXS mouse model to map the spatial distribution and quantify levels of proteins in the hippocampus and hypothalamus brain regions. In total, 1250 unique peptides were spatially resolved, demonstrating the diverse array of peptidomes present in the tissue slices and the broad coverage of the strategy. A group of proteins that are known to be involved in glycolysis, synaptic transmission, and coexpression network analysis suggest a significant association between soy proteins and metabolic and synaptic processes in the Fmr1 KO brain. Ultimately, this spatial proteomics work represents a crucial step toward identifying potential candidate protein markers and novel therapeutic targets for FXS.

Amino acids (AAs) in the d-form are involved in multiple pivotal neurological processes, although their l-enantiomers are most commonly found. Mass spectrometry-based analysis of low-abundance d-AAs has been hindered by challenging enantiomeric separation from l-AAs, low sensitivity for detection, and lack of suitable internal standards for accurate quantification. To address these critical gaps, N,N -dimethyl-l-leucine (l-DiLeu) tags are first validated as novel chiral derivatization reagents for chromatographic separation of 20 pairs of d/l-AAs, allowing the construction of a 4-plex isobaric labeling strategy for enantiomer-resolved quantification through single step tagging. Additionally, the creative design of N,N -dimethyl-d-leucine (d-DiLeu) reagents offers an alternative approach to generate analytically equivalent internal references of d-AAs using d-DiLeu-labeled l-AAs. By labeling cost-effective l-AA standards using paired d- and l-DiLeu, this approach not only enables absolute quantitation of both d-AAs and l-AAs from complex biological matrices with enhanced precision but also significantly boosts the combined signal intensities from all isobaric channels, greatly improving the detection and quantitation of low-abundance AAs, particularly d-AAs. We term this quantitative strategy CHRISTMAS, which stands for ch iral pai r i sobaric labeling st rategy for m ultiplexed a b s olute quantitation. Leveraging the ion mobility collision cross section (CCS) alignment, interferences from coeluting isomers/isobars are effectively filtered out to provide improved quantitative accuracy. From wild-type and Alzheimer's disease (AD) mouse brains, we successfully quantified 20 l-AAs and 5 d-AAs. The significant presence and differential trends of certain d-AAs compared to those of their l-counterparts provide valuable insights into the involvement of d-AAs in aging, AD progression, and neurodegeneration.

The ubiquity of mass spectrometry-based bottom-up proteomic analyses as a component of biological investigation mandates the validation of methodologies that increase acquisition efficiency, improve sample coverage, and enhance profiling depth. Chromatographic separation is often ignored as an area of potential improvement, with most analyses relying on traditional reversed-phase liquid chromatography (RPLC); this consistent reliance on a single chromatographic paradigm fundamentally limits our view of the observable proteome. Herein, we build upon early reports and validate porous graphitic carbon chromatography (PGC) as a facile means to substantially enhance proteomic coverage without changes to sample preparation, instrument configuration, or acquisition methods. Analysis of offline fractionated cell line digests using both separations revealed an increase in peptide and protein identifications by 43% and 24%, respectively. Increased identifications provided more comprehensive coverage of cellular components and biological processes independent of protein abundance, highlighting the substantial quantity of proteomic information that may go undetected in standard analyses. We further utilize these data to reveal that label-free quantitative analyses using RPLC separations alone may not be reflective of actual protein constituency. Together, these data highlight the value and comprehension offered through PGC-MS proteomic analyses. RAW proteomic data have been uploaded to the MassIVE repository with the primary accession code MSV000091495.

Growing evidence supports the confident association between distinct amyloid beta (Aβ) isoforms and Alzheimer's Disease (AD) pathogenesis. As such, critical investigations seeking to uncover the translational factors contributing to Aβ toxicity represent a venture of significant value. Herein, we comprehensively assess full-length Aβ42 stereochemistry, with a specific focus on models that consider naturally-occurring isomerization of Asp and Ser residues. We customize various forms of d-isomerized Aβ as natural mimics, ranging from fragments containing a single d residue to full length Aβ42 that includes multiple isomerized residues, systematically evaluating their cytotoxicity against a neuronal cell line. Combining multidimensional ion mobility-mass spectrometry experimental data with replica exchange molecular dynamics simulations, we confirm that co-d-epimerization at Asp and Ser residues within Aβ42 in both N-terminal and core regions effectively reduces its cytotoxicity. We provide evidence that this rescuing effect is associated with the differential and domain-specific compaction and remodeling of Aβ42 secondary structure., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Mass spectrometry-based discovery glycoproteomics is highly dependent on the use of chromatography paradigms amenable to analyte retention and separation. When compared against established stationary phases such as reversed-phase and hydrophilic interaction liquid chromatography, reports utilizing porous graphitic carbon have detailed its numerous advantages. Recent efforts have highlighted the utility in porous graphitic carbon in high-throughput glycoproteomics, principally through enhanced profiling depth and liquid-phase resolution at higher column temperatures. However, increasing column temperature has been shown to impart disparaging effects in glycopeptide identification. Herein we further elucidate this trend, describing qualitative and semiquantitative effects of increased column temperature on glycopeptide identification rates, signal intensity, resolution, and spectral count linear response. Through analysis of enriched bovine and human glycopeptides, species with high mannose and sialylated glycans were shown to most significantly benefit and suffer from high column temperatures, respectively. These results provide insight as to how porous graphitic carbon separations may be appropriately leveraged for glycopeptide identification while raising concerns over quantitative and semiquantitative label-free comparisons as the temperature changes. RAW MS glycoproteomic data are available via ProteomeXchange with identifier PXD034354.

Citrullination is a key post-translational modification (PTM) that affects protein structures and functions. Although it has been linked to various biological processes and disease pathogenesis, the underlying mechanism remains poorly understood due to a lack of effective tools to enrich, detect, and localize this PTM. Herein, we report the design and development of a biotin thiol tag that enables derivatization, enrichment, and confident identification of citrullination via mass spectrometry. We perform global mapping of the citrullination proteome of mouse tissues. In total, we identify 691 citrullination sites from 432 proteins which represents the largest data set to date. We discover novel distribution and functions of this PTM. This study depicts a landscape of protein citrullination and lays the foundation for further deciphering their physiological and pathological roles.

Lactylation was initially discovered on human histones. Given its nascence, its occurrence on nonhistone proteins and downstream functional consequences remain elusive. Here we report a cyclic immonium ion of lactyllysine formed during tandem mass spectrometry that enables confident protein lactylation assignment. We validated the sensitivity and specificity of this ion for lactylation through affinity-enriched lactylproteome analysis and large-scale informatic assessment of nonlactylated spectral libraries. With this diagnostic ion-based strategy, we confidently determined new lactylation, unveiling a wide landscape beyond histones from not only the enriched lactylproteome but also existing unenriched human proteome resources. Specifically, by mining the public human Meltome Atlas, we found that lactylation is common on glycolytic enzymes and conserved on ALDOA. We also discovered prevalent lactylation on DHRS7 in the draft of the human tissue proteome. We partially demonstrated the functional importance of lactylation: site-specific engineering of lactylation into ALDOA caused enzyme inhibition, suggesting a lactylation-dependent feedback loop in glycolysis., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Continual developments in instrumental and analytical techniques have aided in establishing rigorous connections between protein glycosylation and human illness. These illnesses, such as various forms of cancer, are often associated with poor prognoses, prompting the need for more comprehensive characterization of the glycoproteome. While innovative instrumental and computational strategies have largely benefited glycoproteomic analyses, less attention is given to benefits gained through alternative, optimized chromatographic techniques. Porous graphitic carbon (PGC) chromatography has gained considerable interest in glycomics research due to its mobile phase flexibility, increased retention of polar analytes, and improved structural elucidation at higher temperatures. PGC has yet to be systematically compared against or in tandem with standard reversed phase liquid chromatography (RPLC) in high-throughput bottom-up glycoproteomic experiments, leaving the potential benefits unexplored. Performing comparative analysis of single and biphasic separation regimes at a range of column temperatures illustrates complementary advantages for each method. PGC separation is shown to selectively retain shorter, more hydrophilic glycopeptide species, imparting higher average charge, and exhibiting greater microheterogeneity coverage for identified glycosites. Additionally, we demonstrate that liquid-phase separation of glycopeptide isomers may be achieved through both single and biphasic PGC separations, providing a means towards facile, multidimensional glycopeptide characterization. Beyond this, we demonstrate how utilization of multiple separation regimes and column temperatures can aid in profiling the glycoproteome in tumorigenic and aggressive prostate cancer cells. RAW MS proteomic and glycoproteomic datasets have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD024196 (10.6019/PXD024196) and PXD024195, respectively., (© 2022. Springer-Verlag GmbH Germany, part of Springer Nature.)

Innovations in medical technology and dedicated focus from the scientific community have inspired numerous treatment strategies for benign and invasive cancers. While these improvements often lend themselves to more positive prognoses and greater patient longevity, means for early detection and severity stratification have failed to keep pace. Detection and validation of cancer-specific biomarkers hinges on the ability to identify subtype-specific phenotypic and proteomic alterations and the systematic screening of diverse patient groups. For this reason, clinical and scientific research settings rely on high throughput and high sensitivity mass spectrometry methods to discover and quantify unique molecular perturbations in cancer patients. Discussed within is an overview of quantitative proteomics strategies and a summary of recent applications that enable revealing potential biomarkers and treatment targets in prostate, ovarian, breast, and pancreatic cancer in a high throughput manner., Competing Interests: CONFLICTS OF INTEREST There are no conflicts of interest to declare.

The extracellular matrix (ECM) is unique to each tissue and capable of guiding cell differentiation, migration, morphology, and function. The ECM proteome of different developmental stages has not been systematically studied in the human pancreas. In this study, we apply mass spectrometry-based quantitative proteomics strategies using N,N-dimethyl leucine isobaric tags to delineate proteome-wide and ECM-specific alterations in four age groups: fetal (18-20 weeks gestation), juvenile (5-16 years old), young adults (21-29 years old) and older adults (50-61 years old). We identify 3,523 proteins including 185 ECM proteins and quantify 117 of them. We detect previously unknown proteome and matrisome features during pancreas development and maturation. We also visualize specific ECM proteins of interest using immunofluorescent staining and investigate changes in ECM localization within islet or acinar compartments. This comprehensive proteomics analysis contributes to an improved understanding of the critical roles that ECM plays throughout human pancreas development and maturation.

Growing implications of glycosylation in physiological occurrences and human disease have prompted intensive focus on revealing glycomic perturbations through absolute and relative quantification. Empowered by seminal methodologies and increasing capacity for detection, identification, and characterization, the past decade has provided a significant increase in the number of suitable strategies for glycan and glycopeptide quantification. Mass-spectrometry-based strategies for glycomic quantitation have grown to include metabolic incorporation of stable isotopes, deposition of mass difference and mass defect isotopic labels, and isobaric chemical labeling, providing researchers with ample tools for accurate and robust quantitation. Beyond this, workflows have been designed to harness instrument capability for label-free quantification, and numerous software packages have been developed to facilitate reliable spectrum scoring. In this review, we present and highlight the most recent advances in chemical labeling and associated techniques for glycan and glycopeptide quantification., Competing Interests: Conflict of interest Authors declare no competing interests., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

A variety of peptidic and proteinaceous contaminants (e.g., proteins, toxins, pathogens) present in the environment may pose risk to human health and wildlife. Peroxymonosulfate is a strong oxidant ( E H 0 = 1.82 V for HSO 5 - , the predominant species at environmental pH values) that may hold promise for the deactivation of proteinaceous contaminants. Relatively little quantitative information exists on the rates of peroxymonosulfate reactions with free amino acids. Here, we studied the oxidation of 19 of the 20 standard proteinogenic amino acids (all except cysteine) by peroxymonosulfate without explicit activation. Reaction half-lives at pH 7 ranged from milliseconds to hours. Amino acids possessing sulfur-containing, heteroaromatic, or substituted aromatic side chains were the most susceptible to oxidation by peroxymonosulfate, with rates of transformation decreasing in the order methionine > tryptophan > tyrosine > histidine. The rate of tryptophan oxidation did not decrease in the presence of an aquatic natural organic matter. Singlet oxygen resulting from peroxymonosulfate self-decomposition, while detected by electron paramagnetic resonance spectroscopy, was unlikely to be the principal reactive species. Our results demonstrate that peroxymonosulfate is capable of oxidizing 19 amino acids without explicit activation and that solvent-exposed methionine and tryptophan residues are likely initial targets of oxidation in peptides and proteins.

The microbial secretome, known as a pool of biomass (i.e., plant-based materials) degrading enzymes, can be utilized to discover industrial enzyme candidates for biofuel production. Proteomics approaches have been applied to discover novel enzyme candidates through comparing protein expression profiles with enzyme activity of the whole secretome under different growth conditions. However, the activity measurement of each enzyme candidate is needed for confident "active" enzyme assignments, which remains to be elucidated. To address this challenge, we have developed an Activity-Correlated Quantitative Proteomics Platform (ACPP) that systematically correlates protein-level enzymatic activity patterns and protein elution profiles using a label-free quantitative proteomics approach. The ACPP optimized a high performance anion exchange separation for efficiently fractionating complex protein samples while preserving enzymatic activities. The detected enzymatic activity patterns in sequential fractions using microplate-based assays were cross-correlated with protein elution profiles using a customized pattern-matching algorithm with a correlation R-score. The ACPP has been successfully applied to the identification of two types of "active" biomass-degrading enzymes (i.e., starch hydrolysis enzymes and cellulose hydrolysis enzymes) from Aspergillus niger secretome in a multiplexed fashion. By determining protein elution profiles of 156 proteins in A. niger secretome, we confidently identified the 1,4-α-glucosidase as the major "active" starch hydrolysis enzyme (R = 0.96) and the endoglucanase as the major "active" cellulose hydrolysis enzyme (R = 0.97). The results demonstrated that the ACPP facilitated the discovery of bioactive enzymes from complex protein samples in a high-throughput, multiplexing, and untargeted fashion. Graphical Abstract ᅟ.