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Effectiveness of mass spectrometry and genomic analysis in the surveillance of nontuberculous Mycobacterium in Taiwan.

Nontuberculous mycobacteria (NTM) are diverse, and species-level identification remains challenging in routine diagnostics. We analyzed NTM isolates collected at three regional centers of the National Taiwan University Hospital (NTUH) from 2019 to 2024 to assess geographic variation and identification performance after implementation of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Among 3,188 cases meeting the microbiological criteria for probable pulmonary NTM disease, the species distribution differed by region: Mycobacterium avium complex predominated in central Taiwan (Yunlin, 47.3%), whereas M. abscessus complex (Taipei, 26.5%) and M. kansasii (Hsinchu, 12.4%) were more common in northern Taiwan. In 2019, 14.5% of isolates were reported to be unidentified by MALDI-TOF MS; with workflow optimization and database updates, this percentage decreased but plateaued at 4.5-4.8%. Whole-genome sequencing (WGS) of 61 randomly selected persistently unidentified isolates revealed eight average nucleotide identity (ANI)-defined clusters; 55 isolates (90.2%) could not be assigned to known species using current reference databases. Two clusters detected only in Hsinchu were phylogenetically closest to M. kyorinense, with ANI values below the species demarcation threshold. Overall, we observed marked regional heterogeneity of NTM in Taiwan and a persistent identification gap that remained after MALDI-TOF MS optimization and follow-up WGS.IMPORTANCEThis study characterized regional differences in the NTM species distribution across Taiwan, and the results highlight the limitations of current identification approaches. MALDI-TOF MS identifies most isolates, but locally circulating lineages represent a persistent gap in global reference libraries. Even with whole-genome sequencing (WGS), 90.2% (55/61) of persistently unresolved isolates could not be assigned to known species in the current reference databases despite the formation of clear ANI- and phylogeny-defined clusters. These findings show that both proteomic and genomic reference resources for clinical NTM remain incomplete. Expanding regionally representative databases and performing WGS for isolates that remain unresolved by MALDI-TOF MS will be necessary to improve species-level resolution for surveillance and clinical interpretation.

Taiwan

The Hunt Lab Guide to De Novo Peptide Sequence Analysis by Tandem Mass Spectrometry.

Donald Hunt has made seminal contributions to the fields of proteomics, immunology, epigenetics, and glycobiology. The foundation of every important work to come out of the Hunt Laboratory is de novo peptide sequencing. For decades, he taught hundreds of students, postdocs, engineers, and scientists to directly interpret mass spectral data. To honor his legacy and ensure that the art of de novo sequencing is not lost, we have adapted his teaching materials into "The Hunt Lab Guide to De Novo Peptide Sequence Analysis by Tandem Mass Spectrometry". In addition to the de novo sequencing tutorials, we present two freely available software tools that facilitate manual interpretation of mass spectra and validation of search results. The first, "Hunt Lab Peptide Fragment Calculator", calculates precursor and fragment mass-to-charge ratios for any peptide. The second program, "Predator Protein Fragment Calculator", was inspired in part by the fragment calculator developed in the Hunt Lab. Its capabilities are enhanced to facilitate interpretation of mass spectral data derived from intact proteins. We hope that the combination of these educational tools will continue to benefit students and researchers by empowering them to interpret data on their own.

Tandem Mass Spectrometry

Column switching liquid chromatography dual mass spectrometry system for simultaneous untargeted metabolomics and targeted exposomics.

Exposome-wide association studies (ExWAS) require the detection of metabolites and exposures with diverse chemical properties across wide concentration ranges, a task that typically demands multiple analytical methods. To address this challenge, we develop an integrated column-switching two-dimensional liquid chromatography-dual mass spectrometry (2DLC-dual-MS) system. This system employs a 2DLC setup to sequentially separate polar and non-polar compounds with log P ranging from -8 to 15. The separated fractions are directed via a three-way valve to a high-resolution MS (HRMS) and a triple quadrupole MS (TQMS), enabling simultaneous untargeted metabolome analysis and targeted quantification of 601 exposures. The method is particularly suited for the concurrent analysis of metabolome and exposome in human blood, where their concentrations typically differ by 2-3 orders of magnitude. In a demonstration application on lung adenocarcinoma ExWAS, the system exhibits good stability over more than 300 consecutive injections for both metabolome and exposome analysis, confirming its robustness for ExWAS applications.

Metabolomics

Comprehensive mass spectrometry screening-derived atlas of HDAC inhibitors reveals histone-specific acetylation changes.

Histone deacetylase inhibitors (HDACis) have emerged as valuable therapeutics for cancer and other diseases; however, their effects on histone post-translational modification remain poorly characterized. Here, we applied quantitative mass spectrometry and high-throughput sequencing to systematically profile site-specific changes in histone modifications in response to a panel of HDACis. This platform enabled mapping of histone modification changes across hundreds of sites, including low-abundance histone marks. Furthermore, an integrative analysis of chromatin immunoprecipitation followed by sequencing (ChIP-seq) and RNA-sequencing (RNA-seq) data identified genome-wide binding sites for the low-abundance histone modification of H2A.Z acetylation in HeLa and MDA-MB-231 breast cancer cells, highlighting the role of H2A.Z acetylation in regulating gene expression across diverse biological pathways, including specific genes involved in tumor suppressor pathways. Our findings provide a functional resource for identifying and quantifying histone modification changes and transcriptional regulation of histone H2A.Z acetylation following pharmacological perturbation.

Histone Deacetylase Inhibitors

Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking.

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

Biological Products

Network pharmacology combined with ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry method to explore the mechanism of Shizhi Fang in treating uric acid nephropathy mice.

OBJECTIVE: To elucidate the potential mechanisms of Shizhi Fang (SZF, ) in the treatment of uric acid nephropathy (UAN). METHODS: SZF-containing serum was prepared from six male rats and analyzed using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Network pharmacology was employed was integrated with UPLC-Q-TOF-MS to predict SZF targets for the treatment of UAN, which were subsequently validated through in vivo experiments. Sixty male Bagg Albino Laboratory-Bred Mouse, substrain c mice were randomly allocated into six groups: Normal, Model, Febuxostat, and three SZF dosage groups. Except for the Normal group, all mice were administered potassium oxonate (250 mg/kg) and adenine (50 mg/kg) via gavage to induce UAN. Four hours post-administration, the Febuxostat group received Febuxostat (6 mg/kg), while the SZF groups received low (0.234 g/kg), medium (0.468 g/kg), or high (0.936 g/kg) doses of SZF. The Normal and Model groups were given an equivalent volume of saline. All treatments were conducted over a period of four weeks. Urine and blood samples were collected for biochemical analysis, and kidney tissues were subjected to histopathological examination and Western blot analysis. RESULTS: Nine prototype compounds and 30 metabolites were identified in SZF serum. Network pharmacology analysis revealed 195 drug targets and 1608 disease targets, with 76 common drug-disease targets, including signal transducer and activator of transcription 3 (STAT3), proto-oncogene tyrosine-protein kinase Src (SRC), matrix metalloproteinase-9 (MMP9), Caspase 3, and toll-like receptor 4 (TLR4) as key targets. Gene Ontology analysis identified 325 biological processes, 48 cellular components, and 72 molecular functions, while Kyoto Encyclopedia of Genes and Genomes analysis identified 113 pathways. Molecular docking demonstrated strong binding affinities between active compounds and their targets. In the animal study, SZF treatment alleviated pathological damage and improved serum and urine biochemical markers compared to the Model group (P < 0.05, P < 0.01, P < 0.001). Western blot analysis showed a significant reduction in phosphorylated-STAT3, phosphorylated-SRC, MMP9, TLR4, and Caspase3 expression in renal tissues of SZF-treated mice (P < 0.001). CONCLUSION: SZF may exert therapeutic effects on UAN through multiple targets and pathways.

Animals

Analytical challenges for mapping non-canonical and non-protein ubiquitin/Ubl modifications by mass spectrometry.

INTRODUCTION: Covalent modification by ubiquitin via Lys isopeptide bonds is fundamental for regulating protein turnover and function. Additionally, ubiquitin esterification occurs on Ser/Thr/Tyr residues in proteins and on non-proteinaceous substrates including ribose, saccharides, lipids, and small molecule drugs. Ubiquitin posttranslational modifications may therefore be much more widespread across cell biological pathways. Recent literature (PubMed) reflects the increased interest in analytical methods for mapping of non-canonical substrates modified by ubiquitin and ubiquitin-like (UBL) proteins. AREAS COVERED: Mass spectrometry (MS)-based methodologies involve advanced proteomic techniques to identify ubiquitin modifications on amino acids other than Lys, such as Ser, Thr, Tyr and Cys as well as protein N-termini. After digestion, standard MS workflows identify canonical ubiquitination by detecting a ubiquitin C-terminal tag attached to the amine side chains of Lys residues of substrate-derived peptides suitable for MS/MS sequencing. For non-canonical modifications on proteins and substrates other than proteins, specialized strategies are required, such as using antibodies to enrich N-terminally modified peptides in combination with using high-resolution MS/MS based on softer fragmentation technologies to detect esterification and possibly other types of substrate modifications. EXPERT OPINION: Enabling such technologies will reveal a previously unrecognized angle of the ubiquitin code's complexity in cells.

Humans

Relative Quantitative Analysis of Site-Specific N-Linked Glycosylation in Hyperglycosylated Interferon-&#x3b2; via Mass Spectrometry.

Glycosylation is a critical determinant of the efficacy, stability, and pharmacological behavior of therapeutic proteins. R27T, an engineered variant of interferon-&#x3b2;1a, contains two N-glycosylation sites (Asn25 and Asn80), increasing its structural complexity and analytical requirements. In this study, we performed comprehensive total and site-specific glycan profiling of R27T using complementary analytical approaches. For total glycan analysis, the released N-glycans were fluorescently labeled with procainamide, providing enhanced sensitivity and broader glycan coverage compared with conventional 2-aminobenzamide labeling. Site-specific glycan profiling was performed by liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based peptide mapping. Protease digestion conditions were optimized to improve recovery of site-specific glycopeptides, with chymotrypsin identified as the most effective enzyme for resolving glycopeptides from individual glycosylation sites. Total glycan distributions reconstructed from peptide-mapping data were compared with fluorescence-based glycan profiling, showing that total and site-specific glycan data can be effectively combined. Minor discrepancies were observed depending on glycan structure, mainly due to differences in ionization efficiency. Distinct glycan distributions were observed between the two N-glycosylation sites of R27T. Molecular modeling further suggested that the additional glycan at Asn25 may enhance structural stability and receptor-binding affinity. These results demonstrate an integrative strategy for accurate glycan characterization in multi-site glycoproteins relevant to biotherapeutic development.

Glycosylation

Proteome-wide structural and interaction analysis using cross-linking mass spectrometry and its applications.

Deciphering the mechanisms of protein-protein interactions (PPIs) and protein structural changes within the native cellular environment is crucial for advancing drug discovery. In vivo chemical cross-linking coupled with mass spectrometry (XL-MS) captures weak, transient, and higher-order interactions that are often dysregulated under altered physiological conditions and remain challenging to detect using conventional methods. Applications of in vivo XL-MS range from targeted mapping of PPIs to large-scale identification of interactome networks within the cells. The integration of quantitative approaches further facilitates comparison across different physiological conditions. The recent incorporation of machine learning (ML) tools into XL-MS workflows is transforming the depth and efficiency of this technology. AI-driven algorithms now enable more accurate identification of cross-linked peptides and the mapping of interaction topologies. Furthermore, the synergistic coupling of in vivo XL-MS data with AI-assisted structural modeling platforms such as AlphaFold allows dynamic and high-throughput prediction of protein networks. This review discusses the broader applications of in vivo XL-MS in complex biological samples, ranging from organelles and cells to whole tissues, and highlights how AI integration is expanding structural biology toward a systems-level understanding of proteome architecture.

Mass Spectrometry

Effects of aerosol aging on composition and light-absorbance of nitrogen-containing organic compounds: Evidences from ultra-high-resolution mass spectrometry analysis.

Nitrogen-containing organic compounds (NOCs) are key components of particulate matter (PM), but their compositional evolution and light-absorbing properties during atmospheric aging remain poorly understood. In this study, ultra-high-performance liquid chromatography coupled with Orbitrap mass spectrometry was used to semi-quantitatively analyze 59 PM1 samples collected in Shanghai. NOCs accounted for 31 % and 64 % of the detected species in negative (ESI-) and positive (ESI+) ionization modes, respectively. Atmospheric aging significantly reduced the molecular diversity of polar organics, with both the number and mass concentration percentages of CHON- compounds showing significant negative correlations with aging degree. Van Krevelen analysis demonstrated a decrease in the number of carboxylic-rich alicyclic molecules and their CHON- contributions during the aging process (from 37.7 % in fresh samples to 21.2 % in aged samples). CHN+ compounds, a major NOCs group in ESI+ mode, also decreased with aging. Correlation analyses involving the Bep/(Bep+Bap) ratio, relative humidity, and mass absorption efficiency at 365 nm revealed a decline in light absorption capacity with aging, suggesting aqueous-phase oxidation as a dominant aging mechanism. CHON- and CHN+ compounds were identified as the principal light-absorbing constituents in PM1. This work provides new insights into the aging-induced transformations of NOCs in urban PM1, and their changing role in light absorption, highlighting the need for further investigation of the aging mechanisms of NOCs.

Aerosols

Structure-resolved virus-host interactomics by cross-linking mass spectrometry.

Viruses depend on host protein networks to replicate, assemble progeny, and spread between cells and organisms. Defining these virus-host protein interactions is challenging because they are highly dependent on infection stage, cell type, species, and because mechanistic interpretation requires information about structural interfaces and conformational states. Cross-linking mass spectrometry (XL-MS) addresses these challenges by adding a spatial and structural dimension to virus-host interactomics in native systems. In this review, we discuss how XL-MS has advanced from targeted analysis of viral protein complexes to structure-resolved mapping of virion architecture and infected-cell virus-host interactomes. We highlight how XL-MS complements AP-MS, cryo-EM/cryo-ET, quantitative proteomics, genetic perturbation, and structure prediction to connect physical proximity with molecular mechanisms. Finally, we discuss current limitations in sensitivity, chemical coverage, temporal resolution, and model interpretation, and outline how future quantitative and integrative XL-MS workflows may enable systems-level structural virology.

Mass Spectrometry

Robust phosphoproteomic profiling of tyrosine phosphorylation sites from human T cells using immobilized metal affinity chromatography and tandem mass spectrometry.

Protein tyrosine phosphorylation cascades are difficult to analyze and are critical for cell signaling in higher eukaryotes. Methodology for profiling tyrosine phosphorylation, considered herein as the assignment of multiple protein tyrosine phosphorylation sites in single analyses, was reported recently (Salomon, A. R.; Ficarro, S. B.; Brill, L. M.; Brinker, A.; Phung, Q. T.; Ericson, C.; Sauer, K.; Brock, A.; Horn, D. M.; Schultz, P. G.; Peters, E. C. Proc. Natl. Acad. Sci. U.S.A. 2003, 100, 443-448). The technology platform included the use of immunoprecipitation, immobilized metal affinity chromatography (IMAC), liquid chromatography, and tandem mass spectrometry. In the present report, we show that when using complex mixtures of peptides from human cells, methylation improved the selectivity of IMAC for phosphopeptides and eliminated the acidic bias that occurred with unmethylated peptides. The IMAC procedure was significantly improved by desalting methylated peptides, followed by gradient elution of the peptides to a larger IMAC column. These improvements resulted in assignment of approximately 3-fold more tyrosine phosphorylation sites, from human cell lysates, than the previous methodology. Nearly 70 tyrosine-phosphorylated peptides from proteins in human T cells were assigned in single analyses. These proteins had unknown functions or were associated with a plethora of fundamental cellular processes. This robust technology platform should be broadly applicable to profiling the dynamics of tyrosine phosphorylation.

Cells, Cultured

Solvent Leveling Explains Supercharging in Electrospray Ionization Mass Spectrometry.

Supplementing standard electrospray ionization (ESI) solvents with specific low-volatility organic compounds (e.g., sulfolane or any positional isomer of nitrobenzyl alcohol) increases biomolecular analyte charge for mass spectrometry in the phenomenon known as supercharging. Controversial mechanisms responsible for increasing charge are considered, and the data is found to correlate highly to solvent leveling; i.e., protonated solvent is the strongest acid in a solution because any stronger acid simply dissociates to protonate more solvent. Hence, the recipe for increasing charge in positive ion mode is to make the protonated solvent into a stronger acid (equivalent to reducing the neutral solvent's basicity). That change is accomplished by adding involatile, weak bases to the solvent. A secondary effect of weak base additives is to suppress the solution-phase ionization of weak acid residues; e.g., reducing opposite charging. Here the abilities of analogous compounds to increase or decrease charging in positive ion mode ESI are predicted from experimentally measured basicities. Consistently, amides, nitriles, and pyrazoles more basic than water reduced the average charge of protein analytes electrosprayed from denaturing solutions, while analogues less basic than water increased the average charge, establishing the veracity of solvent leveling as a supercharging mechanism. In other words, reducing the charge departing on solvent leaves more charge for the protein analyte.

Journal Article

Computational mass spectrometry and genome mining guided discovery of metallophores produced by Microbulbifer.

Iron is an essential component of cellular biology. Thus, iron's low bioavailability is a key evolutionary pressure guiding microbial dynamics in the marine environment. Among marine bacteria, Microbulbifer is a chemically underexplored and functionally versatile bacterial genus, which is commonly associated with sponges, algae, corals, and sediments. Previously, genome analyses have revealed that Microbulbifer spp. can degrade polymers and synthesize natural products. Despite their recognized potential to produce secondary metabolites, siderophores are yet to be identified in Microbulbifer, and their iron acquisition strategies remain largely unknown. Here, we developed a comprehensive mass spectrometry-based query language code to determine siderophore production by Microbulbifer spp. in mono- and mixed cultures. Using this workflow, we discovered a new metallophore, which we named bulbichelin, as well as a suite of previously unreported petrobactins containing an unprecedented longer chain length acylation on the central spermidine moiety. We applied genome mining methods to describe the biosynthesis of these compounds. Using metal infusion mass spectrometry, we show that bulbichelins bind a variety of metals. Notably, neither of these compounds were produced in a co-culture of Microbulbifer with coral-derived pathogen Vibrio coralliilyticus Cn52-H1. Understanding how siderophores shape interspecies interactions between Microbulbifer spp. and other marine organisms will aid in unraveling the chemical and catalytic versatility of this genus and adaptation in nutrient deplete marine environment.

MassQL

Quantitative RNA modification mapping by mass spectrometry with isobaric tags and nucleobase fragment analysis.

RNA modifications regulate RNA stability, translation, stress responses, and disease processes, yet their function remains poorly understood due to technical limitations in sequence analysis. Here, we present an RNA-specific isobaric tandem mass tagging (RMT) platform for omic-scale quantitative mapping of RNA modifications. The platform combines RNA-specific tags adapted from proteomics with an end-to-end workflow spanning sample preparation through data processing. Validation using synthetic oligonucleotides and total tRNA from Pseudomonas aeruginosa yielded reproducible quantification, with coefficients of variation below 5%. Together with nucleobase fragment analysis, we identified and quantified 24 RNA modifications in PA14 tRNAs, including previously undescribed m2A38 and Gm/Cm39, and assigned their corresponding writer enzymes. Further analyses of tRNAs from writer knockout strains and stressed cells revealed dynamic modification patterns, modification interdependencies, and their potential roles in stress adaptation. This method provides a robust, cost-effective platform for quantitative RNA modification mapping, enabling deeper biological insights.

RNA, Transfer

Proteome-Scale Tissue Mapping Using Mass Spectrometry Based on Label-Free and Multiplexed Workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of &#x223c;3500 proteins at a spatial resolution of 50&#xa0;&#x3bc;m and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provides robust protein quantifications in identifying differentially abundant proteins and spatially covariable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial coexpression analysis.

Proteome

Quantitative Profiling of Histone Variants and Posttranslational Modifications by Tandem Mass Spectrometry in Arabidopsis.

Histone dynamics constitute an important layer of gene regulations associated with development and growth in multicellular eukaryotes. They also stand as key determinants of plant responses to environmental changes. Histone dynamics include the exchange of histone variants as well as post-translational modifications of their amino acid residues (such as acetylation and mono/di/trimethylation), commonly referred to as histone marks. Investigating histone dynamics with a focus on combinatorial changes occurring at their residues will greatly help unravel how plants achieve phenotypic plasticity.Mass spectrometry (MS) analysis offers unequaled resolution of the abundance of histone variants and of their marks. Indeed, relative to other techniques such as western blot or genome-wide profiling, this powerful technique allows quantifying the relative abundances of histone forms, as well as revealing coexisting marks on the same histone molecule. Yet, while MS-based histone analysis has proven efficient in several animals and other model organisms, this method stands out as more challenging in plants. One major challenge is the isolation of sufficient amounts of pure, high-quality histones, likely rendered difficult by the presence of the cell wall, for sufficiently deep and resolutive identification of histone species.In this chapter, we describe a straightforward MS-based proteomic method, implemented to characterize histone marks from Arabidopsis thaliana seedling tissues and cell culture suspensions. After acid extraction of histones, in vitro propionylation of free lysine residues, and digestion with trypsin, a treatment at highly basic pH allows obtaining sharp spectral signals of biologically relevant histone peptide forms.The method workflow described here shall be used to measure changes in histone marks between Arabidopsis thaliana genotypes, along developmental time-courses, or upon various stresses and treatments.

Histones

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 &#xb5;m and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

Journal Article