Journal of the American Society for Mass Spectrometry最新文献

{"title":"Improving Top-Down Sequence Coverage with Targeted Fragment Matching.","authors":"Matthew T Robey, Kenneth R Durbin","doi":"10.1021/jasms.4c00161","DOIUrl":"https://doi.org/10.1021/jasms.4c00161","url":null,"abstract":"<p><p>Top-down mass spectrometry (TDMS) of intact proteins and antibodies enables direct determination of truncations, sequence variants, post-translational modifications, and disulfides without the need for any proteolytic cleavage. While mass deconvolution of top-down tandem mass spectra is typically used to identify fragment masses for matching to candidate proteoforms, larger molecules such as monoclonal antibodies can produce many fragment ions, making spectral interpretation challenging. Here, we explore an alternative approach for proteoform spectral matching that is better suited for larger protein analysis. This workflow uses direct matching of theoretical proteoform isotopic distributions to TDMS spectra, avoiding drawbacks of mass deconvolution such as poor sensitivity and problems differentiating overlapping distributions. Using a data set that analyzed an intact NIST monoclonal antibody across different fragmentation modes, we show that this isotope fitting strategy increased the sequence coverage of both light and heavy chain sequences >3-fold. We further found that isotope fitting is particularly amenable to identifying large fragments, including those near the hinge region that have been traditionally difficult to analyze by top-down methods. These advances in proteoform spectral matching can greatly increase the power of top-down analyses for intact biotherapeutics and other large molecules.</p>","PeriodicalId":672,"journal":{"name":"Journal of the American Society for Mass Spectrometry","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142492612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Charging of DNA Complexes in Positive-Mode Native Electrospray Ionization Mass Spectrometry.","authors":"Mia L Abramsson, Louise J Persson, Frank Sobott, Erik G Marklund, Michael Landreh","doi":"10.1021/jasms.4c00335","DOIUrl":"https://doi.org/10.1021/jasms.4c00335","url":null,"abstract":"<p><p>Native mass spectrometry (nMS) provides insights into the structures and dynamics of biomacromolecules in their native-like states by preserving noncovalent interactions through \"soft\" electrospray ionization (ESI). For native proteins, the number of charges that are acquired scales with the surface area and mass. Here, we explore the effect of highly negatively charged DNA on the ESI charge of protein complexes and find a reduction of the mass-to-charge ratio as well as a greater variation. The charge state distributions of pure DNA assemblies show a lower mass-to-charge ratio than proteins due to their greater density in the gas phase, whereas the charge of protein-DNA complexes can additionally be influenced by the distribution of the ESI charges, ion pairing events, and collapse of the DNA components. Our findings suggest that structural features of protein-DNA complexes can result in lower charge states than expected for proteins.</p>","PeriodicalId":672,"journal":{"name":"Journal of the American Society for Mass Spectrometry","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142455369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-Guided Design of MALDI Matrices: Exploring the Electron Transfer Chemical Space for Mass Spectrometric Analysis of Low-Molecular-Weight Compounds.","authors":"Carlos A Padilla, Luis M Díaz-Sánchez, Cristian Blanco-Tirado, Aldo F Combariza, Marianny Y Combariza","doi":"10.1021/jasms.4c00186","DOIUrl":"https://doi.org/10.1021/jasms.4c00186","url":null,"abstract":"<p><p>The development of matrices for Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry (MALDI MS) has traditionally relied on experimental efforts. Here, we propose a Goal-Directed artificial intelligence generative model, fueled by computational chemistry calculated data, to construct a chemical space optimized for Electron Transfer (ET) processes in MALDI analysis. We utilized a group of 30 reported ET matrices, subjected to structural enumeration and molecular properties prediction using semiempirical and <i>ab initio</i> calculations, to establish a comprehensive database comprising diverse structural and property data. Subsequently, employing a protocol of structural enumeration with 68 canonical SMILES of Bemis-Murcko (BM) fragments, we expanded the structural complexity of the initial library. This process generated 82753 compounds organized into 10 scaffold levels, with a p50 index from the Cyclic System Retrieval (CSR) curve of scaffolds of 50%. From the resulting enumerated library, a diverse subset of structures was selected by using the Jarvis-Patrick clustering method. These structures, along with their associated properties measured from quantum mechanics and experimental data, were used to train a Machine Learning (ML) model to predict ionization energy (<i>E</i>_<i>i</i>) values. Subsequently, a Scoring Neural Network (SNN), coupled with our Goal-Directed generative model using a Recurrent Neural Network (RNN) with Deep Learning (DL) architectures, was trained. The generative model was guided using a prior network within a Reinforcement/Transfer Learning environment. The final AI-generative model learned that structures with high unsaturation, H/C ratios under 1, and molecular weights between 100 and 300 u are favorable for ET MALDI matrices, as well as those with few aromatic rings and zero aliphatic rings. Other molecular features were also favored. The resulting AI-generated library exhibits <i>E</i>_<i>i</i> values over 8.0 eV, akin to those of reported \"good\" ET MALDI matrices, indicating successful design with high synthesis accessibility scores. In conclusion, our generative model provided valuable insights into the molecular features ideal for ET MALDI compounds while generating a wide range of structurally diverse molecules within a similar molecular property space. The next critical step in this process is to synthesize a selection of these generated compounds for the experimental validation and further characterization.</p>","PeriodicalId":672,"journal":{"name":"Journal of the American Society for Mass Spectrometry","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142455367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Met4DX: A Unified and Versatile Data Processing Tool for Multidimensional Untargeted Metabolomics Data.","authors":"Yandong Yin, Mingdu Luo, Zheng-Jiang Zhu","doi":"10.1021/jasms.4c00290","DOIUrl":"https://doi.org/10.1021/jasms.4c00290","url":null,"abstract":"<p><p>Liquid chromatography-mass spectrometry (LC-MS) is a powerful tool in untargeted metabolomics, enabling the high-sensitivity and high-specificity characterization of metabolites. The integration of ion mobility (IM) with LC-MS, known as LC-IM-MS, enhances the analytical depth, facilitating more comprehensive metabolite profiling. However, the complexity of data generated by these technologies presents significant challenges in data processing. Addressing these challenges, we developed Met4DX, a unified and versatile software tool for processing both 3D and 4D untargeted metabolomics data. Met4DX incorporates a new MS1-oriented peak detection approach coupled with our bottom-up assembly algorithm, enabling highly sensitive and comprehensive peak detection in untargeted metabolomics data. Additionally, Met4DX employs a uniform quantification strategy to enhance the precision of peak integration across different samples. The software provides a user-friendly interface that simplifies data processing with default parameter sets, consolidating peak detection, alignment, quantification, and other procedures into a single streamlined workflow. Together, Met4DX offers a comprehensive solution for multidimensional metabolomics data processing, transforming raw data from diverse MS instruments into a final feature table containing quantification and identification results. We postulate Met4DX facilitates metabolite discovery in biological samples by deciphering the complex untargeted metabolomics data. Met4DX is freely available on the Internet (https://met4dx.zhulab.cn/).</p>","PeriodicalId":672,"journal":{"name":"Journal of the American Society for Mass Spectrometry","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142455371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of Peptide Identification System for ToF-SIMS Spectra Using Supervised Machine Learning.","authors":"Satoka Aoyagi, Miya Fujita, Hidemi Itoh, Hiroto Itoh, Takaharu Nagatomi, Masayuki Okamoto, Tomikazu Ueno","doi":"10.1021/jasms.4c00310","DOIUrl":"https://doi.org/10.1021/jasms.4c00310","url":null,"abstract":"<p><p>Time-of-flight secondary ion mass spectrometry (ToF-SIMS) data interpretation for organic materials is complicated because of various fragment ions produced from each molecule and the overlapping of certain mass peaks from different molecules. Fragmentation mechanisms in SIMS are complex because different sputtering and ionization processes can simultaneously occur. Therefore, a prediction system that can identify materials in a sample is required. A novel prediction system for peptides based on ToF-SIMS and amino-acid-based teaching information (labels) for supervised machine learning was developed. To develop the prediction system for general organic materials, the annotation of materials is crucial to creating effective labels for supervised learning. Peptides are composed of 20 amino acid residues, which can be used as labels. We previously developed a peptide prediction system using Random Forest, a supervised machine-learning method. However, only the amino acids contained in the target peptide were predicted, and the amino acid sequence was unable to be assumed. In this study, the amino acid sequence of the test peptide was determined by adding the information on two adjacent amino acids to the labels. Once the prediction system learned the target peptide spectra, the peptides in the newly obtained ToF-SIMS spectra could be identified. The new prediction system also provides useful information for the identification of unknown peptides. The prediction results indicate that two adjacent permutations of amino acids are effective pieces of teaching information for expressing the amino acid sequence of a peptide.</p>","PeriodicalId":672,"journal":{"name":"Journal of the American Society for Mass Spectrometry","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142455370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ToF-SIMS Investigation of Environmental Effects on Analyte Migration in Matrix Coatings for Mass Spectrometry Imaging Using a Newly Developed Vapor Deposition System.","authors":"Thorsten Adolphs, Michael Bäumer, Florian Bosse, Bart Jan Ravoo, Richard E Peterson, Heinrich F Arlinghaus, Bonnie J Tyler","doi":"10.1021/jasms.4c00340","DOIUrl":"https://doi.org/10.1021/jasms.4c00340","url":null,"abstract":"<p><p>High resolution mass spectrometry images are of increasing importance in biological applications, such as the study of tissues and single cells. Two promising techniques for this are matrix-enhanced secondary ion mass spectrometry (ME-SIMS) and matrix-assisted laser desorption/ionization (MALDI). For both techniques, the sample of interest must be coated with a matrix prior to analysis, and analytes must migrate into the matrix. The mechanisms involved in this migration and the factors that influence the migration are poorly understood, which lead to difficulties with reproducibility. In this work, a sublimation matrix coater with an effusion cell and sample cooling was developed and built in-house for controlled physical vapor deposition. In this system, sample transfer between the coater and mass spectrometer is possible without breaking vacuum, which facilitates the study of environmental influences on analyte migration. The influence of exposure to ambient air on the migration of two analytes (a lipid and a peptide), which were coated with the matrix α-cyano-4-hydroxycinnamic acid (CHCA), was studied using 3D-SIMS imaging. Although the distribution of analyte in the matrix changed very little after 21 h of storage in vacuum, significant redistribution of the analyte was observed after exposure to ambient air. The magnitude of the effect was greater for the lipid than for the peptide. Further work is needed to determine the role of humidity in the redistribution process and the impact of analyte redistribution on MALDI measurements.</p>","PeriodicalId":672,"journal":{"name":"Journal of the American Society for Mass Spectrometry","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142399037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GingisREX: A Complementary Enzyme for the Detection of Bacterial Proteins.","authors":"Thomas Powell, Philip Widdowson, Andreas Nägeli, Martin Ebner, Andrew Creese","doi":"10.1021/jasms.4c00347","DOIUrl":"https://doi.org/10.1021/jasms.4c00347","url":null,"abstract":"<p><p>Reliable enzymatic digestion underscores successful mass-spectrometry-based proteomics experiments. In this study, we compare the use of the arginine-specific protease, GingisREX, against a more traditional approach in the identification of <i>Escherichia coli</i> proteins. An increased number of protein identifications were noted when GingisREX was used compared to a trypsin/lys-C mixture. This improvement was attributed to the generation of fewer peptides per protein, resulting in a simpler peptide mixture. Furthermore, GingisREX exhibited increased digestion efficiency, fewer missed cleavages, and improved MS/MS data quality for higher molecular weight peptides. The data here establish GingisREX to be a protease complementary to trypsin for enhanced detection of bacterial proteins. With further optimization, GingisREX could prove to be an effective alternative to trypsin for identifying host cell proteins in biotherapeutics.</p>","PeriodicalId":672,"journal":{"name":"Journal of the American Society for Mass Spectrometry","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142399036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Characterizing Theta-Emitter Generation for Use in Microdroplet Reactions.","authors":"Jacob B Hatvany, Emma-Le P Olsen, Elyssia S Gallagher","doi":"10.1021/jasms.4c00262","DOIUrl":"https://doi.org/10.1021/jasms.4c00262","url":null,"abstract":"<p><p>Theta emitters are useful for generating microdroplets for rapid-mixing reactions. Theta emitters are glass tips containing an internal septum that separates two channels. When used for mixing, the solutions from each channel are sprayed with mixing occurring during electrospray ionization (ESI) with reaction times on the order of microseconds to milliseconds. Theta emitters of increasing size cause the formation of ESI droplets of increasing size, which require longer times for desolvation and increase droplet lifetimes. Droplets with longer lifetimes provide more time for mixing and allow for increased reaction times prior to desolvation. Because theta emitters are typically produced in-house, there is a need to consistently pull tips with a variety of sizes. Herein, we characterize the effect of pull parameters on the generation of distinct-sized theta emitters using a P-1000 tip puller. Of the examined parameters, the velocity value had the largest impact on the channel diameter. This work also compares the effect of pulling parameters between single-channel and theta capillaries to examine how the internal septum in theta capillaries affects tip pulling. We demonstrate the utility of using theta emitters with different sizes for establishing distinct reaction times. Finally, we offer suggestions on producing theta emitters of various sizes while maintaining high repeatability. Through this work, we provide resources to establish a versatile and inexpensive rapid-mixing system for probing biologically relevant systems and performing rapid derivatizations.</p>","PeriodicalId":672,"journal":{"name":"Journal of the American Society for Mass Spectrometry","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142455368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hierarchical Biclustering of Mouse Pancreas Mass Spectrometry Imaging Data Using Recursive Rank-2 Non-negative Matrix Factorization.","authors":"Melanie Nijs, Etienne Waelkens, Bart De Moor","doi":"10.1021/jasms.4c00268","DOIUrl":"https://doi.org/10.1021/jasms.4c00268","url":null,"abstract":"<p><p>One of the main challenges in mass spectrometry imaging data analysis remains the analysis of <i>m</i>/<i>z</i>-spectra displaying a low signal-to-noise ratio caused by their low abundance, sample preparation, matrix effects, fragmentation, and other artifacts. Additionally, we observe that molecules with a high abundance suppress those with lower intensities and misdirect classical tools for MSI data analysis, such as principal component analysis. As a result, the observed significance of a molecule may not always be directly related to its abundance. In this work, we present a recursive rank-2 non-negative matrix factorization (rr2-NMF) algorithm that automatically returns spectral and spatial visualization of colocalized molecules, both highly and lowly abundant. Using this hierarchical decomposition, our method finds spatial and spectral correlations on different levels of abundances. The quality of the analysis is evaluated on MALDI-TOF data of healthy mouse pancreatic tissue for the annotation of molecules of interest in the lower abundances. The results show interesting findings regarding the functioning and colocalization of certain molecules.</p>","PeriodicalId":672,"journal":{"name":"Journal of the American Society for Mass Spectrometry","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142387185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introducing FISCAS, a Tool for the Effective Generation of Single Cell MALDI-MSI Data.","authors":"Jan Schwenzfeier, Sarah Weischer, Sebastian Bessler, Jens Soltwisch","doi":"10.1021/jasms.4c00279","DOIUrl":"https://doi.org/10.1021/jasms.4c00279","url":null,"abstract":"<p><p>We introduce Fluorescence Integrated Single-Cell Analysis Script (FISCAS), which combines fluorescence microscopy with MALDI-MSI to streamline single-cell analysis. FISCAS enables automated selection of tight measurement regions, thereby reducing the acquisition of off-target pixels, and makes use of established algorithms for cell segmentation and coregistration to rapidly compile single-cell spectra. MALDI-compatible staining of membranes, nuclei, and lipid droplets allows the collection of fluorescence data prior to the MALDI-MSI measurement on a timsTOF fleX MALDI-2. Usefulness of the software is demonstrated by the example of THP-1 cells during stimulated differentiation into macrophages at different time points. In this proof-of-principle study, FISCAS was used to automatically generate single-cell mass spectra along with a wide range of morphometric parameters for a total number of roughly 1300 cells collected at 24, 48, and 72 h after the onset of stimulation. Data analysis of the combined morphometric and single-cell mass spectrometry data shows significant molecular heterogeneity within the cell population at each time point, indicating an independent differentiation of each individual cell rather than a synchronized mechanism. Here, the grouping of cells based on their molecular phenotype revealed an overall clearer distinction of the different phases of differentiation into macrophages and delivered an increased number of lipid signals as possible markers compared with traditional bulk analysis. Utilizing the linkage between mass spectrometric data and fluorescence microscopy confirmed the expected positive correlation between lipid droplet staining and the overall signal for triacylglyceride (TG), demonstrating the usefulness of this multimodal approach.</p>","PeriodicalId":672,"journal":{"name":"Journal of the American Society for Mass Spectrometry","volume":null,"pages":null},"PeriodicalIF":3.1,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142387186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}