Investigating mouse hepatic lipidome dysregulation following exposure to emerging per- and polyfluoroalkyl substances (PFAS).

Per- and polyfluoroalkyl substances (PFAS) are environmental pollutants that have been associated with adverse health effects including liver damage, decreased vaccine responses, cancer, developmental toxicity, thyroid dysfunction, and elevated cholesterol. The specific molecular mechanisms impacted by PFAS exposure to cause these health effects remain poorly understood, however there is some evidence of lipid dysregulation. Thus, lipidomic studies that go beyond clinical triglyceride and cholesterol tests are greatly needed to investigate these perturbations. Here, we have utilized a platform coupling liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) separations to simultaneously evaluate PFAS bioaccumulation and lipid metabolism disruptions. For the study, liver samples collected from C57BL/6 mice exposed to either of the emerging PFAS hexafluoropropylene oxide dimer acid (HFPO-DA or "GenX") or Nafion byproduct 2 (NBP2) were assessed. Sex-specific differences in PFAS accumulation and liver size were observed for both PFAS, in addition to disturbed hepatic liver lipidomic profiles. Interestingly, GenX resulted in less hepatic bioaccumulation than NBP2 yet gave a higher number of significantly altered lipids when compared to the control group, implying that the accumulation of substances in the liver may not be a reliable measure of the substance's capacity to disrupt the liver's natural metabolic processes. Specifically, phosphatidylglycerols, phosphatidylinositols, and various specific fatty acyls were greatly impacted, indicating alteration of inflammation, oxidative stress, and cellular signaling processes due to emerging PFAS exposure. Overall, these results provide valuable insight into the liver bioaccumulation and molecular mechanisms of GenX- and NBP2-induced hepatotoxicity.

Reverse metabolomics for the discovery of chemical structures from humans.

Determining the structure and phenotypic context of molecules detected in untargeted metabolomics experiments remains challenging. Here we present reverse metabolomics as a discovery strategy, whereby tandem mass spectrometry spectra acquired from newly synthesized compounds are searched for in public metabolomics datasets to uncover phenotypic associations. To demonstrate the concept, we broadly synthesized and explored multiple classes of metabolites in humans, including N-acyl amides, fatty acid esters of hydroxy fatty acids, bile acid esters and conjugated bile acids. Using repository-scale analysis1,2, we discovered that some conjugated bile acids are associated with inflammatory bowel disease (IBD). Validation using four distinct human IBD cohorts showed that cholic acids conjugated to Glu, Ile/Leu, Phe, Thr, Trp or Tyr are increased in Crohn's disease. Several of these compounds and related structures affected pathways associated with IBD, such as interferon-γ production in CD4+ T cells3 and agonism of the pregnane X receptor4. Culture of bacteria belonging to the Bifidobacterium, Clostridium and Enterococcus genera produced these bile amidates. Because searching repositories with tandem mass spectrometry spectra has only recently become possible, this reverse metabolomics approach can now be used as a general strategy to discover other molecules from human and animal ecosystems.

Characterizing Adeno-Associated Virus Capsids with Both Denaturing and Intact Analysis Methods.

Adeno-associated virus (AAV) capsids are among the leading gene delivery platforms used to treat a vast array of human diseases and conditions. AAVs exist in a variety of serotypes due to differences in viral protein (VP) sequences with distinct serotypes targeting specific cells and tissues. As the utility of AAVs in gene therapy increases, ensuring their specific composition is imperative for the correct targeting and gene delivery. From a quality control perspective, current analytical tools are limited in their selectivity for viral protein (VP) subunits due to their sequence similarities, instrumental difficulties in assessing the large molecular weights of intact capsids, and the uncertainty in distinguishing empty and filled capsids. To address these challenges, we combined two distinct analytical workflows that assess the intact capsids and VP subunits separately. First, a selective temporal overview of resonant ion (STORI)-based charge detection-mass spectrometry (CD-MS) was applied for characterization of the intact capsids. Liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) separations were then used for the capsid denaturing measurements. This multimethod combination was applied to three AAV serotypes (AAV2, AAV6, and AAV8) to evaluate their intact empty and filled capsid ratios and then examine the distinct VP sequences and modifications present.

Aggregated Molecular Phenotype Scores: Enhancing Assessment and Visualization of Mass Spectrometry Imaging Data for Tissue-Based Diagnostics.

Mass spectrometry imaging (MSI) has gained increasing popularity for tissue-based diagnostics due to its ability to identify and visualize molecular characteristics unique to different phenotypes within heterogeneous samples. Data from MSI experiments are often assessed and visualized using various supervised and unsupervised statistical approaches. However, these approaches tend to fall short in identifying and concisely visualizing subtle, phenotype-relevant molecular changes. To address these shortcomings, we developed aggregated molecular phenotype (AMP) scores. AMP scores are generated using an ensemble machine learning approach to first select features differentiating phenotypes, weight the features using logistic regression, and combine the weights and feature abundances. AMP scores are then scaled between 0 and 1, with lower values generally corresponding to class 1 phenotypes (typically control) and higher scores relating to class 2 phenotypes. AMP scores, therefore, allow the evaluation of multiple features simultaneously and showcase the degree to which these features correlate with various phenotypes. Due to the ensembled approach, AMP scores are able to overcome limitations associated with individual models, leading to high diagnostic accuracy and interpretability. Here, AMP score performance was evaluated using metabolomic data collected from desorption electrospray ionization MSI. Initial comparisons of cancerous human tissues to their normal or benign counterparts illustrated that AMP scores distinguished phenotypes with high accuracy, sensitivity, and specificity. Furthermore, when combined with spatial coordinates, AMP scores allow visualization of tissue sections in one map with distinguished phenotypic borders, highlighting their diagnostic utility.

Utilizing Aggregated Molecular Phenotype (AMP) Scores to Visualize Simultaneous Molecular Changes in Mass Spectrometry Imaging Data.

Mass spectrometry imaging (MSI) has gained increasing popularity for tissue-based diagnostics due to its ability to identify and visualize molecular characteristics unique to different phenotypes within heterogeneous samples. Data from MSI experiments are often visualized using single ion images and further analyzed using machine learning and multivariate statistics to identify m/z features of interest and create predictive models for phenotypic classification. However, often only a single molecule or m/z feature is visualized per ion image, and mainly categorical classifications are provided from the predictive models. As an alternative approach, we developed an aggregated molecular phenotype (AMP) scoring system. AMP scores are generated using an ensemble machine learning approach to first select features differentiating phenotypes, weight the features using logistic regression, and combine the weights and feature abundances. AMP scores are then scaled between 0 and 1, with lower values generally corresponding to class 1 phenotypes (typically control) and higher scores relating to class 2 phenotypes. AMP scores therefore allow the evaluation of multiple features simultaneously and showcase the degree to which these features correlate with various phenotypes, leading to high diagnostic accuracy and interpretability of predictive models. Here, AMP score performance was evaluated using metabolomic data collected from desorption electrospray ionization (DESI) MSI. Initial comparisons of cancerous human tissues to normal or benign counterparts illustrated that AMP scores distinguished phenotypes with high accuracy, sensitivity, and specificity. Furthermore, when combined with spatial coordinates, AMP scores allow visualization of tissue sections in one map with distinguished phenotypic borders, highlighting their diagnostic utility.

Temporal chemical composition changes in water below a crude oil slick irradiated with natural sunlight.

Photooxidation can alter the environmental fate and effects of spilled oil. To better understand this process, oil slicks were generated on seawater mesocosms and exposed to sunlight for 8 days. The molecular composition of seawater under irradiated and non-irradiated oil slicks was characterized using ion mobility spectrometry-mass spectrometry and polyaromatic hydrocarbons analyses. Biomimetic extraction was performed to quantify neutral and ionized constituents. Results show that seawater underneath irradiated oil showed significantly higher amounts of hydrocarbons with oxygen- and sulfur-containing by-products peaking by day 4-6; however, concentrations of dissolved organic carbon were similar. Biomimetic extraction indicated toxic units in irradiated mesocosms increased, mainly due to ionized components, but remained <1, suggesting limited potential for ecotoxicity. Because the experimental design mimicked important aspects of natural conditions (freshly collected seawater, natural sunlight, and relevant oil thickness and concentrations), this study improves our understanding of the effects of photooxidation during a marine oil spill.

Stability and Dissociation of Adeno-Associated Viral Capsids by Variable Temperature-Charge Detection-Mass Spectrometry.

Adeno-associated viral (AAV) vectors have emerged as gene therapy and vaccine delivery systems. Differential scanning fluorimetry or differential scanning calorimetry is commonly used to measure the thermal stability of AAVs, but these global methods are unable to distinguish the stabilities of different AAV subpopulations in the same sample. To address this challenge, we combined charge detection-mass spectrometry (CD-MS) with a variable temperature (VT) electrospray source that controls the temperature of the solution prior to electrospray. Using VT-CD-MS, we measured the thermal stabilities of empty and filled capsids. We found that filled AAVs ejected their cargo first and formed intermediate empty capsids before completely dissociating. Finally, we observed that pH stress caused a major decrease in thermal stability. This new approach better characterizes the thermal dissociation of AAVs, providing the simultaneous measurement of the stabilities and dissociation pathways of different subpopulations.

Surface Modified Nano-Electrospray Needles Improve Sensitivity for Native Mass Spectrometry.

Native mass spectrometry (MS) and charge detection-mass spectrometry (CD-MS) have become versatile tools for characterizing a wide range of proteins and macromolecular complexes. Both commonly use nanoelectrospray ionization (nESI) from pulled borosilicate needles, but some analytes are known to nonspecifically adsorb to the glass, which may lower sensitivity and limit the quality of the data. To improve the sensitivity of native MS and CD-MS, we modified the surface of nESI needles with inert surface modifiers, including polyethylene-glycol. We found that the surface modification improved the signal intensity for native MS of proteins and for CD-MS of adeno-associated viral capsids. Based on mechanistic comparisons, we hypothesize that the improvement is more likely due to an increased flow rate with coated ESI needles rather than less nonspecific adsorption. In any case, these surface-modified needles provide a simple and inexpensive method for improving the sensitivity of challenging analytes.

High-Resolution Demultiplexing (HRdm) Ion Mobility Spectrometry-Mass Spectrometry for Aspartic and Isoaspartic Acid Determination and Screening.

Isomeric peptide analyses are an analytical challenge of great importance to therapeutic monoclonal antibody and other biotherapeutic product development workflows. Aspartic acid (Asp, D) to isoaspartic acid (isoAsp, isoD) isomerization is a critical quality attribute (CQA) that requires careful control, monitoring, and quantitation during the drug discovery and production processes. While the formation of isoAsp has been implicated in a variety of disease states such as autoimmune diseases and several types of cancer, it is also understood that the formation of isoAsp results in a structural change impacting efficacy, potency, and immunogenic properties, all of which are undesirable. Currently, lengthy ultrahigh-performance liquid chromatography (UPLC) separations are coupled with MS for CQA analyses; however, these measurements often take over an hour and drastically limit analysis throughput. In this manuscript, drift tube ion mobility spectrometry-mass spectrometry (DTIMS-MS) and both a standard and high-resolution demultiplexing approach were utilized to study eight isomeric Asp and isoAsp peptide pairs. While the limited resolving power associated with the standard DTIMS analysis only separated three of the eight pairs, the application of HRdm distinguished seven of the eight and was only unable to separate DL and isoDL. The rapid high-throughput HRdm DTIMS-MS method was also interfaced with both flow injection and an automated solid phase extraction system to present the first application of HRdm for isoAsp and Asp assessment and demonstrate screening capabilities for isomeric peptides in complex samples, resulting in a workflow highly suitable for biopharmaceutical research needs.

Utilizing liquid chromatography, ion mobility spectrometry, and mass spectrometry to assess INLIGHT™ derivatized N-linked glycans in biological samples.

Glycosylation is a ubiquitous co- and post-translational modification involved in the sorting, folding, and trafficking of proteins in biological systems; in humans, >50% of gene products are glycosylated with the cellular machinery of glycosylation compromising ~2% of the genome. Perturbations in glycosylation have been implicated in a variety of diseases including neurodegenerative diseases and certain types of cancer. However, understanding the relationship between a glycan and its biological role is often difficult due to the numerous glycan isomers that exist. To address this challenge, nanoflow liquid chromatography, ion mobility spectrometry, and mass spectrometry (nLC-IMS-MS) were combined with the Individuality Normalization when Labeling with the Isotopic Glycan Hydrazide Tags (INLIGHT™) strategy to study a series of glycan standards and those enzymatically released from the glycoproteins horseradish peroxidase, fetuin, and pooled human plasma. The combination of IMS and the natural (NAT) and stable-isotope label (SIL) in the INLIGHT™ strategy provided additional confidence for each glycan identification due to the mobility aligned NAT- and SIL-labeled glycans and further capabilities for isomer examinations. Additionally, molecular trend lines based on the IMS and MS dimensions were investigated for the INLIGHT™ derivatized glycans, facilitating rapid identification of putative glycans in complex biological samples.

Spatial Distribution of Polycyclic Aromatic Hydrocarbon Contaminants after Hurricane Harvey in a Houston Neighborhood.

BACKGROUND: Hurricane Harvey made landfall along the Texas Gulf Coast as a Category 4 hurricane on August 25, 2017, producing unprecedented precipitation that devastated coastal areas. Catastrophic flooding in the City of Houston inundated industrial and residential properties resulting in the displacement and transfer of soil, sediment, and debris and heightening existing environmental justice (EJ) concerns. OBJECTIVES: The primary aim of this study was to evaluate the presence, distribution, and potential human health implications of polycyclic aromatic hydrocarbons (PAHs) in a residential neighborhood of Houston, Texas following a major hurricane. METHODS: Concentrations of PAHs in 40 soil samples collected from a residential neighborhood in Houston, Texas were measured. Spatial interpolation was applied to determine the distribution of PAHs. Potential human health risks were evaluated by calculating toxicity equivalency quotients (TEQs) and incremental excess lifetime cancer risk (IELCR). RESULTS: Total priority PAH concentrations varied across samples (range: 9.7 × 101 ng/g-1.6 × 104 ng/g; mean: 3.0 × 103 ng/g ± 3.6 × 103 standard deviation). Spatial analysis indicated a variable distribution of PAH constituents and concentrations. The IELCR analysis indicated that nine of the 40 samples were above minimum standards. CONCLUSIONS: Findings from this study highlight the need for fine scale soil testing in residential areas as well as the importance of site-specific risk assessment. COMPETING INTERESTS: The authors declare no competing financial interests.

A Comparative Analysis of Analytical Techniques for Rapid Oil Spill Identification.

The complex chemical composition of crude oils presents many challenges for rapid chemical characterization in the case of a spill. A number of approaches are currently used to "fingerprint" petroleum-derived samples. Gas chromatography coupled with mass spectrometry (GC-MS) is the most common, albeit not very rapid, technique; however, with GC-MS alone, it is difficult to resolve the complex substances in crude oils. The present study examined the potential application of ion mobility spectrometry-mass spectrometry (IMS-MS) coupled with chem-informatic analyses as an alternative high-throughput method for the chemical characterization of crude oils. We analyzed 19 crude oil samples from on- and offshore locations in the Gulf of Mexico region in the United States using both GC-MS (biomarkers, gasoline range hydrocarbons, and n-alkanes) and IMS-MS (untargeted analysis). Hierarchical clustering, principal component analysis, and nearest neighbor-based classification were used to examine sample similarity and geographical groupings. We found that direct-injection IMS-MS performed either equally or better than GC-MS in the classification of the origins of crude oils. In addition, IMS-MS greatly increased the sample analysis throughput (minutes vs hours per sample). Finally, a tabletop science-to-practice exercise, utilizing both the GC-MS and IMS-MS data, was conducted with emergency response experts from regulatory agencies and the oil industry. This activity showed that the stakeholders found the IMS-MS data to be highly informative for rapid chemical fingerprinting of complex substances in general and specifically advantageous for accurate and confident source-grouping of crude oils. Collectively, the present study shows the utility of IMS-MS as a technique for rapid fingerprinting of complex samples and demonstrates its advantages over traditional GC-MS-based analyses when used for decision-making in emergency situations. Environ Toxicol Chem 2021;40:1034-1049. © 2020 SETAC.

Folding and Assembly of Short α, ß, γ-Hybrid Peptides: Minor Variations in Sequence and Drastic Differences in Higher-Level Structures.

Multilevel protein structures typically involve polypeptides of sufficient lengths. Here we report the folding and assembly of seven short tetrapeptides sharing the same types of α-, ß-, and aromatic γ-amino acid residues. These are two sets of hybrid peptides, with three members in one set and four in the other, having complementary hydrogen-bonding sequences that were hypothesized to pair into linear H-bonded duplexes. However, instead of undergoing the anticipated pairing, the initially examined three oligomers, 1 and 2a or 2b, differing only in their central αß hybrid dipeptide sequence, do not associate with each other and exhibit distinctly different folding behavior. Experiments based on NMR and mass spectrometry, along with computational studies and systematic inference, reveal that oligomer 1 folds into an expanded ß-turn containing an unusual hybrid α/ß-amino acid sequence composed of glycine and ß-alanine, two α- and ß-amino acid residues that are conformationally most flexible, and peptides 2a and 2b adopt a noncanonical, extended helical conformation and dimerize into double helices undergoing rapid conformational exchange or helix inversion. The different central dipeptide sequences, αß vs ßα, result in drastically different intramolecular H-bonding patterns that are responsible for the observed folding behavior of 1 and 2. The revealed turn and double helix have few natural or synthetic counterparts, and provide novel and unique folding prototypes based on which chiral α- and ß-amino acids are incorporated. The resultant derivatives 1a, 1b, 2c, and 2d follow the same folding and assembling behavior and demonstrate the generality of this system with the formation of expanded ß-turns and double helices with enhanced folding stabilities, hampered helix inversion, as well as defined and dominant helical sense. This work has demonstrated the unique capability of synthetic foldamers in generating structures with fascinating folding and assembling behavior. The revealed systems offer ample opportunity for further structural optimization and applications.

Evaluating the structural complexity of isomeric bile acids with ion mobility spectrometry.

Bile acids (BAs) play an integral role in digestion through the absorption of nutrients, emulsification of fats and fat-soluble vitamins, and maintenance of cholesterol levels. Metabolic disruption, diabetes, colorectal cancer, and numerous other diseases have been linked with BA disruption, making improved BA analyses essential. To date, most BA measurements are performed using liquid chromatography separations in conjunction with mass spectrometry measurements (LC-MS). However, 10-40 min LC gradients are often used for BA analyses and these may not even be sufficient for distinguishing all the important isomers present in the human body. Ion mobility spectrometry (IMS) is a promising tool for BA evaluations due to its ability to quickly separate isomeric molecules with subtle structural differences. In this study, we utilized drift tube IMS (DTIMS) coupled with MS to characterize 56 different unlabeled BA standards and 16 deuterated versions. In the DTIMS-MS analyses of 12 isomer groups, BAs with smaller m/z values were easily separated in either their deprotonated or sodiated forms (or both). However, as the BAs grew in m/z value, they became more difficult to separate with two isomer groups being inseparable. Metal ions such as copper and zinc were then added to the overlapping BAs, and due to different binding sites, the resulting complexes were separable. Thus, the rapid structural measurements possible with DTIMS-MS show great potential for BAs measurements with and without prior LC separations.

Utilizing ion mobility spectrometry and mass spectrometry for the analysis of polycyclic aromatic hydrocarbons, polychlorinated biphenyls, polybrominated diphenyl ethers and their metabolites.

Polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) are persistent environmental pollutants originating from incomplete combustion of organic materials and synthetic sources. PAHs, PCBs, and PBDEs have all been shown to have a significant effect on human health with correlations to cancer and other diseases. Therefore, measuring the presence of these xenobiotics in the environment and human body is imperative for assessing their health risks. To date, their analyses require both gas chromatography and liquid chromatography separations in conjunction with mass spectrometry measurements for detection of both the parent molecules and their hydroxylated metabolites, making their studies extremely time consuming. In this work, we characterized PAHs, PCBs, PBDEs and their hydroxylated metabolites using ion mobility spectrometry coupled with mass spectrometry (IMS-MS) and in combination with different ionization methods including electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI) and atmospheric pressure photoionization (APPI). The collision cross section and m/z trend lines derived from the IMS-MS analyses displayed distinct trends for each molecule type. Additionally, the rapid isomeric and molecular separations possible with IMS-MS showed great promise for quickly distinguishing the parent and metabolized PAH, PCB, and PDBE molecules in complex environmental and biological samples.

Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS.

In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150-250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMS-CID-TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10-200 nM range, while simultaneously achieving discovery measurements of not initially targeted peptides as markers from the same proteins and, eventually, other proteins. Graphical Abstract ᅟ.

Compression Ratio Ion Mobility Programming (CRIMP) Accumulation and Compression of Billions of Ions for Ion Mobility-Mass Spectrometry Using Traveling Waves in Structures for Lossless Ion Manipulations (SLIM).

We report on the implementation of a traveling wave (TW) based compression ratio ion mobility programming (CRIMP) approach within structures for lossless ion manipulations (SLIM) that enables both greatly enlarged trapped ion charge capacities and also efficient ion population compression for use in ion mobility (IM) separations. Ion accumulation is conducted in a SLIM serpentine ultralong path with extended routing (SUPER) region after which CRIMP compression allows the large ion populations to be "squeezed". The SLIM SUPER IM module has two regions, one operating with conventional traveling waves (i.e., traveling trap; TT region) and the second having an intermittently pausing or "stuttering" TW (i.e., stuttering trap; ST region). When a stationary voltage profile was used in the ST region, ions are blocked at the TT-ST interface and accumulated in the TT region and then can be released by resuming a conventional TW in the ST region. The population can also be compressed using CRIMP by the repetitive merging of ions distributed over multiple TW bins in the TT region into a single TW bin in the ST region. Ion accumulation followed by CRIMP compression provides the basis for the use of larger ion populations for IM separations. We show that over 109 ions can be accumulated with high efficiency in the present device and that the extent of subsequent compression is only limited by the space charge capacity of the trapping region. Approximately 5 × 109 charges introduced from an electrospray ionization source were trapped for a 40 s accumulation period, more than 2 orders of magnitude greater than the previously reported charge capacity of an ion funnel trap. Importantly, we show that extended ion accumulation in conjunction with CRIMP compression and multiple passes through the serpentine path provides the basis for a highly desirable combination of ultrahigh sensitivity and SLIM SUPER high-resolution IM separations.

Identification of Hip BMD Loss and Fracture Risk Markers Through Population-Based Serum Proteomics.

Serum proteomics analysis may lead to the discovery of novel osteoporosis biomarkers. The Osteoporotic Fractures in Men (MrOS) study comprises men ≥65 years old in the US who have had repeated BMD measures and have been followed for incident fracture. High-throughput quantitative proteomic analysis was performed on baseline fasting serum samples from non-Hispanic white men using a multidimensional approach coupling liquid chromatography, ion-mobility separation, and mass spectrometry (LC-IMS-MS). We followed the participants for a mean of 4.6 years for changes in femoral neck bone mineral density (BMD) and for incident hip fracture. Change in BMD was determined from mixed effects regression models taking age and weight into account. Participants were categorized into three groups: BMD maintenance (no decline; estimated change ≥0 g/cm2 , n = 453); expected loss (estimated change 0 to 1 SD below the estimated mean change, -0.034 g/cm2 for femoral neck, n = 1184); and accelerated loss (estimated change ≥1 SD below mean change, n = 237). Differential abundance values of 3946 peptides were summarized by meta-analysis to determine differential abundance of each of 339 corresponding proteins for accelerated BMD loss versus maintenance. Using this meta-analytic standardized fold change at cutoffs of ≥1.1 or ≤0.9 (p < 0.10), 20 proteins were associated with accelerated BMD loss. Associations of those 20 proteins with incident hip fracture were tested using Cox proportional hazards models with age and BMI adjustment in 2473 men. Five proteins were associated with incident hip fracture (HR between 1.29 and 1.41 per SD increase in estimated protein abundance). Some proteins have been previously associated with fracture risk (eg, CD14 and SHBG), whereas others have roles in cellular senescence and aging (B2MG and TIMP1) and complement activation and innate immunity (CO7, CO9, CFAD). These findings may inform development of biomarkers for future research in bone biology and fracture prediction. © 2017 American Society for Bone and Mineral Research.

Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry.

Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches.