We introduce vacuum resonance-enhanced multiphoton ionization (REMPI) with high-resolution Orbitrap Fourier transform mass spectrometry (FTMS) for analyzing silylated polar compounds. UV laser radiation at 248 nm sensitively and selectively targets aromatic constituents, while high-resolution mass spectrometry (HRMS) enables high-performance mass spectrometric detection. This workflow enhances the detection confidence of polar constituents by identifying unique isotopologue patterns, including at the isotopic fine structure (IFS) level, in analytical standards and complex bio-oils. A direct and derivatized gas chromatography (GC) procedure on a polar standard component mixture allowed us to explore the general ionization and detection characteristics of REMPI FTMS. HRMS enabled the examination of the complex isotopologue profiles, revealing distinct patterns for the CHOSi-class compounds. Particularly in complex mixtures, this isobaric/isonucleonic complexity exceeded the classical mass resolution capabilities of the employed Orbitrap D30 series and prompted the usage of prolonged transients via an external data acquisition system. This procedure substantially improved mass spectrometric results by recording the unreduced time-domain transient data for up to 2 s. Notably, the ability to distinguish diagnostic isotopic pairs, such as C/Si vs C/Si with a mass split of ∼3.79 mDa and CC/SiSi vs C/Si, with an approximate mass difference of ∼3.32 mDa, demonstrates a significant and expected performance improvement. Finally, we benchmark the GC HRMS methodology to identify silylated oxygenated and nitrogen-containing constituents in ultracomplex bio-oil samples. The presented approach of utilizing the silicon isotope pattern and unique isotopologue mass splits for increasing attribution confidence can be applied beyond bio-oils toward the general GC analyses of polar oxygenates.

Fragmentation is a phenomenon ubiquitously observed during research and development of therapeutic antibodies. The clear identification of the cleavage site is vital for comprehending fragmentation mechanisms and optimizing processes. Capillary electrophoresis-sodium dodecyl sulfate (CE-SDS) is now widely used to detect and quantify fragments, while its peak identification is hindered by immature capillary electrophoresis-sodium dodecyl sulfate coupled with mass spectrometry techniques. In this study, we developed a systematic workflow for fragment characterization, which integrated direct identification, fragment enrichment, and fragmentation confirmation using multiple techniques, such as microscale peptide mapping (PM), PM of N-termini labeled sample, and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) in-gel extraction for molecular weight (MW) and PM measurements. By employing this innovative workflow, we successfully identified the cleavage sites of two therapeutic antibodies. In the first case, through direct liquid chromatography-mass spectrometry (LC-MS) characterization, the cleavages leading to the loss of biological function were identified on the linker of a bispecific antibody. In the second case involving a tetravalent antibody, direct LC-MS analysis failed. However, more sophisticated analysis nailed down the critical cleavage at the LC/HC: G-R site in the CDR3 region of the antibody. Our systematic workflow provides a clear and accessible method for identifying cleavage sites with broad applicability across pharmaceutical laboratories.

While resonance ionization mass spectrometry (RIMS) has demonstrated utility in measuring isotopic compositions of elements in complex matrices without the need for chemical separation to remove isobaric interferences, it has had limited application in measuring elemental compositions. The ability to determine elemental compositions via an in situ method like RIMS would be an exceptional asset in spent nuclear fuel analysis, where they are important in assessing reactor histories and whose chemical separation presents a radiological hazard. However, quantitative elemental analysis by RIMS requires special considerations because each element is ionized by its own set of lasers tuned to element specific resonant ionization wavelengths. We present the first comprehensive study of measuring elemental ratios by RIMS in spent nuclear fuel. All actinides produced by neutron capture are enhanced significantly radially from the center to the edge of a fuel pellet. This edge effect is not readily accessible by conventional bulk measurements.

Isotope labeling of both N and C in selected amino acids in a protein, known as sparse labeling, is an alternative to uniform labeling and is particularly useful for proteins that must be expressed using mammalian cells, including glycoproteins. High levels of enrichment in the selected amino acids enable multidimensional heteronuclear NMR measurements of glycoprotein three-dimensional structure. Mass spectrometry provides a means to quantify the degree of enrichment. Mass spectrometric measurements of tryptic peptides of a selectively labeled glycoprotein expressed in HEK293 cells revealed complicated isotope patterns which consisted of many overlapping isotope patterns from intermediately labeled peptides, which complicates the determination of the label incorporation. Two challenges are uncovered by these measurements. Metabolic scrambling of amino groups can reduce the N content of enriched amino acids or increase the N in nontarget amino acids. Also, undefined, unlabeled medium components may dilute the enrichment level of labeled amino acids. The impact of this unexpected metabolic scrambling was overcome by simulating isotope patterns for all isotope-labeled peptide states and generating linear combinations to fit to the data. This method has been used to determine the percent incorporation of N and C labels and has identified several metabolic scrambling effects that were previously undetected in NMR experiments. Ultrahigh mass resolution is also utilized to obtain isotopic fine structure, from which enrichment levels of N and C can be assigned unequivocally. Finally, tandem mass spectrometry can be used to confirm the location of heavy isotope labels in the peptides.

High spatial resolution is a key parameter in mass spectrometry imaging (MSI), enabling a greater understanding of system biology and cellular processes. Using a novel IR laser with good Gaussian beam quality ( = 4) coupled with spatial filtering and a reflective objective, 20 μm spatial resolution was obtained by IR-MALDESI. The optical train was optimized on burn paper before demonstrating feasibility for imaging of liver tissue. Finally, a mouse brain was analyzed using nested regions of interest at 20 and 140 μm spatial resolution, detecting neurotransmitters and lipids with high spatial resolution on the corpus callosum and surrounding brain tissue.

Post expression from the host cells, biotherapeutics undergo downstream processing steps before final formulation. Mass spectrometry and biophysical characterization methods are valuable for examining conformational and stoichiometric changes at these stages, although typically not used in biomanufacturing, where stability is assessed via bulk property studies. Here we apply hybrid MS methods to understand how solution condition changes impact the structural integrity of a biopharmaceutical across the processing pipeline. As an exemplar product, we use the model IgG1 antibody, mAb4. Flexibility, stability, aggregation propensity, and bulk properties are evaluated in relation to perfusion media, purification stages, and formulation solutions. Comparisons with Herceptin, an extensively studied IgG1 antibody, were conducted in a mass spectrometry-compatible solution. Despite presenting similar charge state distributions (CSD) in native MS, mAb4, and Herceptin show distinct unfolding patterns in activated ion mobility mass spectrometry (aIM-MS) and differential scanning fluorimetry (DSF). Herceptin's greater structural stability and aggregation onset temperature () are attributed to heavier glycosylation and kappa-class light chains, unlike the lambda-class light chains in mAb4. Hydrogen-deuterium exchange mass spectrometry (HDX-MS) revealed that mAb4 undergoes substantial structural changes during purification, marked by high flexibility, low melting temperature (Tm), and prevalent repulsive protein-protein interactions but transitions to a compact and stable structure in high-salt and formulated environments. Notably, in formulation, the third constant domain (CH3) of the heavy chain retains flexibility and is a region of interest for aggregation. Future work could translate features of interest from comprehensive studies like this to targeted approaches that could be utilized early in the development stage to aid in decision-making regarding targeted mutations or to guide the design space of bioprocesses and formulation choices.

Hydrothermal fluid plays a crucial role in the generation and migration of hydrocarbons within sedimentary basins. Herein, we employed bulk analysis and high-resolution mass spectrometry techniques to investigate the transformation dynamics from source rock to hydrocarbons under conditions influenced by magmatic activities in the Kongdian Formation, Huanghua Depression, China. The results revealed that hydrocarbon generation in the Ek shale of the study area was significantly influenced by abnormal heating from hydrothermal fluids. High temperatures associated with these fluids accelerated the conversion of organic matter within source rocks, enhancing hydrocarbon generation rates. Subsequently, the hydrocarbons migrated into fracture networks, where they solidified as low-reflectance solid bitumen, forming trapped fractures of pyrobitumen and authigenic mineral aggregates leached from thermal fluid. High aliphatic fractions were noted in the source rock extracts, while extracts from low-reflectance solid bitumen exhibited higher aromatic fraction. Aliphatic and aromatic compounds in extracts from both the low-reflectance solid bitumen and the source rock exhibited similar maturities and origins. Regarding polar compounds, the compound classes O, O, NO, and NO showed higher abundances in source rock extracts compared to those in low-reflectance solid bitumen, while the S and N classes showed the opposite trend. Thus, fractionation clearly occurs when hydrocarbons expelled from source rocks by thermal fluids solidify into low-reflectance solid bitumen. This unique study provides valuable insights into understanding the fate of hydrocarbons originating from source rocks heated by thermal fluids, and explores the potential for unconventional oil in regions with intense hydrothermal alteration.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) measurement data and machine learning were used in this work to classify six different types of plastics. In order to take into account the characteristics of the measurement data, the local maxima of the measurement data were first examined in a preprocessing step. Several machine learning methods were then implemented to create a model that could successfully classify the plastics. To visualize the data distribution, we applied a dimensionality reduction method, namely, principal component analysis. Finally, to distinguish between the six types of plastics, we conducted an ensemble analysis using four tree-based algorithms: decision tree, random forest, gradient boosting, and LIGHTGBM. This approach can identify the feature importance of plastic samples and allow the inference of the chemical properties of each plastic type. In this way, ToF-SIMS data could be utilized to successfully classify plastics and enhance explainability.

Protein footprinting is a useful method for studying protein higher order structure and conformational changes induced by interactions with various ligands via addition of covalent modifications onto the protein. Compared to other methods that provide single amino acid-level structural resolution, such as cryo-EM, X-ray diffraction, and NMR, mass spectrometry (MS)-based methods can be advantageous as they require lower protein amounts and purity. As with other MS-based proteomic methods, such as post-translational modification analysis, enrichment techniques have proven necessary for both optimal sensitivity and sequence coverage when analyzing highly complex proteomes. Currently used reagents for footprinting via covalent labeling, such as hydroxyl radicals and carbodiimide-based methods, do not yet have a suitable enrichment method, limiting their applicability to whole proteome analysis. Here, we report a method for enrichable covalent labeling built upon the GEE/EDC system commonly used to covalently label aspartic acid and glutamic acid residues. Novel labeling reagents containing alkynyl functionality can be "clicked" to any azido-containing molecule with copper-catalyzed azide-alkyne cycloaddition (CuAAC), allowing for enrichment or further labeling. Multiple azide- and alkyne-containing GEE-like molecules were tested, and the most efficient method was determined to be the EDC-facilitated coupling of glycine propargyl amide (GPA) to proteins. The pipeline we report includes clicking via CuAAC to a commercially available biotin-azide containing a photocleavable linker, followed by enrichment using a streptavidin resin and subsequent cleavage under ultraviolet light. The enrichment process was optimized through the screening of clickable amines, coupling reagents, and enrichment scaffolds and methods with pure model proteins and has also been applied to complex mixtures of proteins isolated from the model plant, , suggesting that our method may ultimately be used to measure protein conformation on a proteomic scale.

Existing analytical techniques are being improved or applied in new ways to profile the tissue microenvironment (TME) to better understand the role of cells in disease research. Fully understanding the complex interactions between cells of many different types and functions is often slowed by the intense data analysis required. Multiplexed Ion Beam Imaging (MIBI) has been developed to simultaneously characterize 50+ cell types and their functions within the TME with a subcellular spatial resolution, but this results in complex data sets that are challenging to qualitatively analyze. Deep Learning (DL) techniques were used to build the MIBIsight workflow, which can process images containing thousands of cells into easily digestible reports and plots to enable researchers to easily summarize data sets in a study and make informed conclusions. Here we present the three types of DL models that have been trained with annotated MIBI images that have been pathologist validated as well as the associated workflow for the evolution of raw mass spectral data into actionable reports and plots.

Protein lactylation is a novel post-translational modification (PTM) involved in many important physiological processes such as macrophage polarization, immune regulation, and tumor cell growth. However, traditional methodologies for studying lactylation have predominantly relied on peptide enrichment from whole-cell lysates, which tend to favor the detection of high-abundance peptides, thus limiting the identification of low-abundance lactylated peptides. To address this limitation, here, we employed subcellular fractionation to separate proteins and map lactylated peptides from each isolated subcellular fraction using a model cell line. In brief, we identified 1,217 lysine lactylation (Kla) sites on 553 proteins across four subcellular fractions. Subsequent pathway enrichment analysis revealed that Kla proteins participate in distinct pathways depending on the subcellular contexts. In addition, this subcellular fractionation method enabled the discovery of 36 previously unreported Kla proteins and 223 novel Kla sites, many of which are present in low abundance. Notably, several proteins contain multiple newly identified Kla sites, exemplified by the transcriptional regulator ATRX. Furthermore, our results indicate the possibility of PTM crosstalk between Kla and other PTMs such as ubiquitination and sumoylation. In conclusion, subcellular fractionation facilitates the identification of Kla proteins that have been previously uncovered and could be overlooked by affinity enrichment of whole-cell lysates.

Collision-induced unfolding (CIU) has provided new levels of understanding of the stabilities and structure(s) for gas phase protein and protein complex ions formed by electrospray ionization (ESI). Variable-temperature (vT-ESI) data provide complementary information about temperature-induced folding/unfolding (TIU) reactions of solution phase ions. Results obtained by using CIU and TIU provide complementary information about stabilities of gas phase versus solution phase ions. Such comparisons may provide the most direct experimental approach to answer a long-standing question from Fred McLafferty: "For how long, under what conditions, and to what extent, can solution structure be retained without solvent?" Answers to this question require greater understanding of the (i) structure(s), stabilities, and dynamics of proteins/protein complexes in solution prior to ESI; (ii) effects of water removal by droplet fission and "freeze-drying" by evaporation of water from the nanodroplet; and (iii) potential reactions and structural changes that may occur as the ions traverse the heated capillary, the final stage in the transition to solvent-free gas phase ions. Here, we employ vT-ESI coupled with ion mobility-mass spectrometry (IM-MS) as a means to provide more detailed answers to the above-mentioned questions. Apo- and metalated-metallothionein-2A (MT), a cysteine-rich metal binding protein, and various proteoforms of transthyretin (TTR), a homotetrameric (56 kDa) retinol and thyroxine transporter protein complex were studied to examine distinct features of CIU and TIU across two different types of protein complexes. The results in this work shed light on the capabilities of CIU, TIU, and average charge state (Z) for probing the rugged energy landscape of native proteins and highlights the effects of water and cofactors (metal ions) on the structure and stabilities of proteins and protein complexes.

The identification and control of high-risk host cell proteins (HCPs) in biotherapeutics development are crucial for ensuring product quality and shelf life. Specifically, HCPs with hydrolase activity can cause the degradation of excipient polysorbates (PS), leading to a decrease in the shelf life of the drug product. In this study, we systematically optimized every step of an activity-based protein profiling (ABPP) workflow to identify trace amounts of active polysorbate-degradative enzymes (PSDEs) in biotherapeutic process intermediates. Evaluation of various parameters during sample preparation pinpointed the optimal pH level and fluorophosphonate (FP)-biotin concentration. Moreover, the combined use of a short liquid chromatography gradient and the fast-scanning parallel accumulation-serial fragmentation (PASEF) methodology increased sample throughput without compromising identification coverage. Tuning the trapped ion mobility spectrometry (TIMS) parameters further enhanced sensitivity. In addition, we evaluated various data acquisition modes, including PASEF combined with data-dependent acquisition (DDA PASEF), data-independent acquisition (diaPASEF), or parallel reaction monitoring (prm-PASEF). By employing the newly optimized ABPP workflow, we successfully identified PSDEs at a concentration as low as 10 ppb in a drug substance sample. Finally, the new workflow enabled us to detect a PSDE that could not be detected with the original workflow during a PS degradation root-cause investigation.

The growing use of branched polymers in various industrial and technological applications has prompted significant interest in understanding their properties, for which accurate structure determination is vital. This work is the first instance where the macromolecular structures of dendrimers, linear polymers, and hyperbranched polymers with analogous 2,2-bis(hydroxymethyl)propionic acid (bis-MPA) backbone groups were synthesized and analyzed via tandem mass spectrometry (MS/MS). When comparing the fragmentation pathways of these polymers, some unique and interesting patterns emerge that provide insight into the primary structures and architectures of each of these materials. As expected, the linear polymer undergoes multiple random backbone cleavages resulting in several fragment ion distributions that vary in size and end group composition. The hyperbranched polymer dissociates preferentially at branching sites; however, differently branched isomers exist for each oligomer size, thus giving rise again to several fragment distributions. In contrast, the dendrimer presents a unique fragmentation pattern comprising key fragment ions of high molecular weight; this unique characteristic stands out as a signature for identifying dendrimer structures. Overall, dendrimers, hyperbranched polymers, and linear polymers display individualized fragmentation behaviors, which are caused by differences in primary structure. As a result, tandem mass spectrometry fragmentation is a particularly useful analytical tool for distinguishing such macromolecular architectures.

The Identity algorithm implemented in the MS Search (NIST) software is widely used for library searches of gas chromatography/mass spectrometry data against electron ionization mass spectral databases. It has been available to researchers since 1993, with the release of MS Search 1.5a. Despite its extensive use, the operational details of the algorithm have remained ambiguous. Attempts to replicate the algorithm have been unsuccessful because, as found in this research, the description in the manual is neither fully complete nor accurate. The main novelty of this work is the development of a unique approach for deconstructing the Identity algorithm. It is purely based on analyzing library search results obtained from several groups of synthetic mass spectra, each tailored to isolate and examine specific components of the algorithm. This approach facilitated a comprehensive understanding of the Identity algorithm and led to the development of a custom implementation that fully replicates the results obtained from the original MS Search software. The custom implementation of the Identity algorithm is now available in the mssearchr R package, enhancing accessibility for researchers.

The analysis of complex mixtures poses a challenge due to the high number of compounds present in a mixture, which often exceed the capabilities of analytical methods and instruments. Even more challenging is understanding the structural details of compounds within a complex sample. Most analytical methods provide just bulk information on complex samples, and individual structural details cannot be observed. High-resolution mass spectrometry, the best method to analyze complex samples, suffers from inherent problems for structural studies in complex systems because collision-induced fragmentation (CID) measurements cannot provide data from individual compounds alone. The combination of different steps of chromatographic separation, here the combination of size exclusion chromatography with argentation chromatography, provides sufficient reduction in complexity to implement a method that allows gaining structural details of individual compounds within a complex mixture. The combination of offline size exclusion chromatography followed by online argentation chromatography effectively creates fractions based on the respective properties of the compounds in the mixture (size and number of π-bonds and heteroatoms) and reduces matrix effects to a great extent. Mass spectrometry with ultrahigh resolution provides basic chemical information for each detected compound and also provides the opportunity to gain structural information from MS/MS experiments. The results indicate effectively separated sample fractions yielded by the chromatographic steps with tremendously decreased total numbers of compounds. Especially, argentation chromatography proved to be a valuable separation tool when it comes to heteroatom-containing constituents. In the end, the fragmentation experiments indicated high-quality data due to the clean ion isolation enabled by prior separation. The structural elucidations provided deep insights into the carbon space of crude oil.

HNTX-XXI, a peptide toxin derived from the venom of the spider , comprises a 64-amino-acid protein architecture that notably incorporates eight cysteine residues positioned at positions 2, 10, 14, 16, 17, 23, 36, and 63. The close spatial proximity of Cys16 and Cys17 poses a challenge in resolving their disulfide bridge configurations using standard methodologies. In this study, we introduce an innovative and highly efficient approach for delineating disulfide pairings in peptides containing adjacent cysteines. Our methodology integrates a two-step proteolytic digestion strategy utilizing trypsin and Glu-specific staphylococcal V8 protease coupled with a subsequent round of Edman degradation. This multifaceted approach enables the precise characterization of the disulfide bonds within the peptide. Specifically, targeted proteolysis by trypsin and V8, followed by reversed-phase HPLC separation of the resulting peptides, facilitated the unambiguous identification of disulfide linkages between Cys10-Cys23 and Cys14-Cys63. For the fragment containing the four remaining cysteines, a single cycle of Edman degradation was employed, strategically breaking the peptide bond between the adjacent cysteines. This pivotal step enabled the isolation and analysis of the resulting fragments. Subsequently, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was utilized, revealing the presence of two additional disulfide bonds: Cys2-Cys17 and Cys16-Cys36. Collectively, these findings allow for the definitive assignment of the four disulfide linkages in HNTX-XXI as Cys2-Cys17, Cys10-Cys23, Cys14-Cys63, and Cys16-Cys36. This rapid and sensitive methodology represents a significant advancement in the structural characterization of peptide toxins with complex disulfide bond patterns, underscoring its potential for broad application in the field of venom peptide research.

The matrix effect limits the accuracy of quantitation of the otherwise popular metabolomics technique liquid chromatography coupled to mass spectrometry (LC-MS). The gold standard to correct for this phenomenon, whereby compounds coeluting with the analyte of interest cause ionization enhancement or suppression, is to quantify an analyte based on the peak area ratio with an isotopologue added to the sample as an internal standard. However, these stable isotopes are expensive and sometimes unavailable. Here, we describe an alternative approach: matrix effect correction and quantifying analytes using a signal ratio with a postcolumn infused standard (PCIS). Using an LC-MS/MS method for eight endocannabinoids and related metabolites in plasma, we provide strategies to select, optimize, and evaluate PCIS candidates. Based on seven characteristics, the structural endocannabinoid analogue arachidonoyl-2'-fluoroethylamide was selected as a PCIS. Three methods to evaluate the PCIS correction vs no correction showed that PCIS correction improved values for the matrix effect, precision, and dilutional linearity of at least six of the analytes to within acceptable ranges. PCIS correction also resulted in parallelization of calibration curves in plasma and neat solution, for six of eight analytes even with higher accuracy than peak area ratio correction with their stable isotope labeled internal standard, i.e., the gold standard. This enables quantification based on neat solutions, which is a significant step toward absolute quantification. We conclude that PCIS has great, but so far underappreciated, potential in accurate LC-MS quantification.

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a rapidly advancing technology for biomedical research. As spatial resolution increases, however, so do acquisition time, file size, and experimental cost, which increases the need to perform precise sampling of targeted tissue regions to optimize the biological information gleaned from an experiment and minimize wasted resources. The ability to define instrument measurement regions based on key tissue features and automatically sample these specific regions of interest (ROIs) addresses this challenge. Herein, we demonstrate a workflow using standard software that allows for direct sampling of microscopy-defined regions by MALDI IMS. Three case studies are included, highlighting different methods for defining features from common sample types─manual annotation of vasculature in human brain tissue, automated segmentation of renal functional tissue units across whole slide images using custom segmentation algorithms, and automated segmentation of dispersed HeLa cells using open-source software. Each case minimizes data acquisition from unnecessary sample regions and dramatically increases throughput while uncovering molecular heterogeneity within targeted ROIs. This workflow provides an approachable method for spatially targeted MALDI IMS driven by microscopy as part of multimodal molecular imaging studies.

Peak annotation plays an important role in mass spectral evaluation of the NIST 2023 tandem mass spectral library. While most fragment ions are formed by neutral losses, there are peaks that represent adduct ions from these fragments. Previously, we have reported two main types of addition reactions in the collision cell, namely addition of HO and N. Here we report a different reaction in the collision cell, with addition of O leading to a small peak that could only be assigned to a peroxyl radical ion. For example, some protonated iodoaromatics lose an iodine atom to form a radical cation [M+H-I], which reacts with O to generate a peroxyl radical ion [M+H-I+O]. Higher concentrations of O result in higher peroxyl radical peaks, which become dominant while the precursor ions are consumed, as examined by five compounds under different concentrations of O. The correlation of the peroxyl radical peak intensities to the concentration of O provides a tool to estimate trace amounts of O within the instrument. In the NIST 2023 tandem mass spectral library, the peaks for [M+H-X+O] are most abundant in numbers and in intensity for X = NO or I, are much less abundant for X = Br, and are rare for X = Cl. Other leaving groups in this library are SOH, SONH, CSNH, COCF, SOCH, and COCH. The O addition reaction is also observed with negative ions in this library. While adducts of HO and N often constitute major peaks, the peaks of the peroxyl radicals under standard conditions are mostly very small and may be mistaken for noise, but their correct annotation improves the quality of the spectra and is important when comparing spectra from different instruments or conditions.