Advancing the high throughput identification of liver fibrosis protein signatures using multiplexed ion mobility spectrometry

Evaluation of a Reference-Free Collision Cross Section Calibration Strategy for Proteomics Using SLIM-Based High-Resolution Ion Mobility Spectrometry-Mass Spectrometry

Ion mobility spectrometry (IMS) is a gas-phase analytical technique that separates ions with different sizes and shapes and is compatible with mass spectrometry (MS) to provide an additional separation dimension. The rapid nature of the IMS separation combined with the high sensitivity of MS-based detection and the ability to derive structural information on analytes in the form of the property collision cross section (CCS) makes IMS particularly well-suited for characterizing complex samples in -omics applications. In such applications, the quality of CCS from IMS measurements is critical to confident annotation of the detected components in the complex -omics samples. However, most IMS instrumentation in mainstream use requires calibration to calculate CCS from measured arrival times, with the most notable exception being drift tube IMS measurements using multifield methods. The strategy for calibrating CCS values, particularly selection of appropriate calibrants, has important implications for CCS accuracy, reproducibility, and transferability between laboratories. The conventional approach to CCS calibration involves explicitly defining calibrants ahead of data acquisition and crucially relies upon availability of reference CCS values. In this work, we present a novel reference-free approach to CCS calibration which leverages trends among putatively identified features and computational CCS prediction to conduct calibrations post-data acquisition and without relying on explicitly defined calibrants. We demonstrated the utility of this reference-free CCS calibration strategy for proteomics application using high-resolution structures for lossless ion manipulations (SLIM)-based IMS-MS. We first validated the accuracy of CCS values using a set of synthetic peptides and then demonstrated using a complex peptide sample from cell lysate.

Serum dithiothreitol-oxidizing capacity (DOC) is a promising biomarker for excluding significant liver fibrosis: a proof-of-concept study

BACKGROUND

APRI and FIB-4 scores are used to exclude clinically significant fibrosis (defined as stage ≥ F2) in patients with chronic viral hepatitis. However, the cut-offs for these scores (generated by Youden indices) vary between different patient cohorts. This study aimed to evaluate whether serum dithiothreitol-oxidizing capacity (DOC), i.e., a surrogate test of quiescin sulfhydryl oxidase-1, which is a matrix remodeling enzyme, could be used to non-invasively identify significant fibrosis in patients with various chronic liver diseases (CLDs).

METHODS

Diagnostic performance of DOC was compared with APRI and FIB-4 for identifying significant fibrosis. ROC curve analyses were undertaken in: a) two chronic hepatitis B (CHB) cohorts, independently established from hospitals in Wenzhou (n = 208) and Hefei (n = 120); b) a MASLD cohort from Wenzhou hospital (n = 122); and c) a cohort with multiple CLD etiologies (except CHB and MASLD; n = 102), which was identified from patients in both hospitals. Cut-offs were calculated using the Youden index. All CLD patients (n = 552) were then stratified by age for ROC curve analyses and cut-off calculations.

RESULTS

Stratified by CLD etiology or age, ROC curve analyses consistently showed that the DOC test was superior to APRI and FIB-4 for discriminating between clinically significant fibrosis and no fibrosis, when APRI and FIB-4 showed poor/modest diagnostic performance (P < 0.05, P < 0.01 and P < 0.001 in 3, 1 and 3 cohort comparisons, respectively). Conversely, the DOC test was equivalent to APRI and FIB-4 when all tests showed moderate/adequate diagnostic performances (P > 0.05 in 11 cohort comparisons). DOC had a significant advantage over APRI or FIB-4 scores for establishing a uniform cut-off independently of age and CLD etiology (coefficients of variation of DOC, APRI and FIB-4 cut-offs were 1.7%, 22.9% and 47.6% in cohorts stratified by CLD etiology, 2.0%, 26.7% and 29.5% in cohorts stratified by age, respectively). The uniform cut-off was 2.13, yielded from all patients examined. Surprisingly, the uniform cut-off was the same as the DOC upper limit of normal with a specificity of 99%, estimated from 275 healthy control individuals. Hence, the uniform cut-off should possess a high negative predictive value for excluding significant fibrosis in primary care settings. A high DOC cut-off with 97.5% specificity could be used for detecting significant fibrosis (≥ F2) with an acceptable positive predictive value (87.1%).

CONCLUSIONS

This proof-of-concept study suggests that the DOC test may efficiently rule out and rule in significant liver fibrosis, thereby reducing the numbers of unnecessary liver biopsies. Moreover, the DOC test may be helpful for clinicians to exclude significant liver fibrosis in the general population.

Longitudinal analysis of host protein serum signatures of treatment and recovery in pulmonary tuberculosis

BACKGROUND

A better understanding of treatment progression and recovery in pulmonary tuberculosis (TB) infectious disease is crucial. This study analyzed longitudinal serum samples from pulmonary TB patients undergoing interventional treatment to identify surrogate markers for TB-related outcomes.

METHODS

Serum that was collected at baseline and 8, 17, 26, and 52 weeks from 30 TB patients experiencing durable cure were evaluated and compared using a sensitive LC-MS/MS proteomic platform for the detection and quantification of differential host protein signatures relative to timepoint. The global proteome signature was analyzed for statistical differences across the time course and between disease severity and treatment groups.

RESULTS

A total of 676 proteins showed differential expression in the serum over these timepoints relative to baseline. Comparisons to understand serum protein dynamics at 8 weeks, treatment endpoints at 17 and 26 weeks, and post-treatment at 52 weeks were performed. The largest protein abundance changes were observed at 8 weeks as the initial effects of antibiotic treatment strongly impacted inflammatory and immune modulated responses. However, the largest number of proteome changes was observed at the end of treatment time points 17 and 26 weeks respectively. Post-treatment 52-week results showed an abatement of differential proteome signatures from end of treatment, though interestingly those proteins uniquely significant at post-treatment were almost exclusively downregulated. Patients were additionally stratified based upon disease severity and compared across all timepoints, identifying 461 discriminating proteome signatures. These proteome signatures collapsed into discrete expression profiles with distinct pathways across immune activation and signaling, hemostasis, and metabolism annotations. Insulin-like growth factor (IGF) and Integrin signaling maintained a severity signature through 52 weeks, implying an intrinsic disease severity signature well into the post-treatment timeframe.

CONCLUSION

Previous proteome studies have primarily focused on the 8-week timepoint in relation to culture conversion status. While this study confirms previous observations, it also highlights some differences. The inclusion of additional end of treatment and post-treatment time points offers a more comprehensive assessment of treatment progression within the serum proteome. Examining the expression dynamics at these later time periods will help in the investigation of relapse patients and has provided indicative markers of response and recovery.

Towards IMn with Electrostatic Drift Fields: Resetting the Potential of Trapped Ions Between Dimensions of Ion Mobility

Increasing the dimensionality of ion mobility (IM) presents an enticing opportunity to increase the information content and selectivity of many analyses. However, for implementations of IM that use constant electrostatic gradients to separate ions in a buffer gas, technical challenges have limited the adoption of the technique and number of dimensions within individual experiments. Here, we introduce a strategy to "reset" the potentials of ions between IM dimensions. To achieve this, mobility-selected ions are trapped between dimensions of IM, using a combination of RF and electrostatic fields, while the subsequent dimension of IM is devoid of any drift field. By applying an incremental voltage ramp, the potential of the trapping region is elevated, simultaneously establishing the drift field in the subsequent dimension of IM. The trapped ions are then released and separated. We measured similar arrival-time distributions of protein ions using this strategy and a method without potential resetting, suggesting that potential resetting can be performed without additional losses or activation of ions. The findings of those experiments were corroborated by ion trajectory simulations, which exhibited a very small changes in ion position and no significant changes in effective temperatures during potential resetting. Finally, we demonstrate that IM information can be preserved during potential resetting by selecting subpopulations of 9+ cytochrome c ions, resetting their potential, subjecting them to a second-dimension IM separation, and observing the retention of conformers within each subpopulation. We anticipate that this strategy will be useful for advancing flexible, multidimensional experiments on electrostatic IM instruments.

Integrated Transcriptomic and Proteomic Analysis Identifies Plasma Biomarkers of Hepatocellular Failure in Alcohol-Associated Hepatitis

Alcohol-associated hepatitis (AH) is a form of liver failure with high short-term mortality. Recent studies have shown that defective function of hepatocyte nuclear factor 4 alpha (HNF4a) and systemic inflammation are major disease drivers of AH. Plasma biomarkers of hepatocyte function could be useful for diagnostic and prognostic purposes. Herein, an integrative analysis of hepatic RNA sequencing and liquid chromatography-tandem mass spectrometry was performed to identify plasma protein signatures for patients with mild and severe AH. Alcohol-related liver disease cirrhosis, nonalcoholic fatty liver disease, and healthy subjects were used as comparator groups. Levels of identified proteins primarily involved in hepatocellular function were decreased in patients with AH, which included hepatokines, clotting factors, complement cascade components, and hepatocyte growth activators. A protein signature of AH disease severity was identified, including thrombin, hepatocyte growth factor α, clusterin, human serum factor H-related protein, and kallistatin, which exhibited large abundance shifts between severe and nonsevere AH. The combination of thrombin and hepatocyte growth factor α discriminated between severe and nonsevere AH with high sensitivity and specificity. These findings were correlated with the liver expression of genes encoding secreted proteins in a similar cohort, finding a highly consistent plasma protein signature reflecting HNF4A and HNF1A functions. This unbiased proteomic-transcriptome analysis identified plasma protein signatures and pathways associated with disease severity, reflecting HNF4A/1A activity useful for diagnostic assessment in AH.

Noninvasive proteomic biomarkers for alcohol-related liver disease

Alcohol-related liver disease (ALD) is a major cause of liver-related death worldwide, yet understanding of the three key pathological features of the disease-fibrosis, inflammation and steatosis-remains incomplete. Here, we present a paired liver-plasma proteomics approach to infer molecular pathophysiology and to explore the diagnostic and prognostic capability of plasma proteomics in 596 individuals (137 controls and 459 individuals with ALD), 360 of whom had biopsy-based histological assessment. We analyzed all plasma samples and 79 liver biopsies using a mass spectrometry (MS)-based proteomics workflow with short gradient times and an enhanced, data-independent acquisition scheme in only 3 weeks of measurement time. In plasma and liver biopsy tissues, metabolic functions were downregulated whereas fibrosis-associated signaling and immune responses were upregulated. Machine learning models identified proteomics biomarker panels that detected significant fibrosis (receiver operating characteristic-area under the curve (ROC-AUC), 0.92, accuracy, 0.82) and mild inflammation (ROC-AUC, 0.87, accuracy, 0.79) more accurately than existing clinical assays (DeLong's test, P < 0.05). These biomarker panels were found to be accurate in prediction of future liver-related events and all-cause mortality, with a Harrell's C-index of 0.90 and 0.79, respectively. An independent validation cohort reproduced the diagnostic model performance, laying the foundation for routine MS-based liver disease testing.

A Preprocessing Tool for Enhanced Ion Mobility-Mass Spectrometry-Based Omics Workflows

The ability to improve the data quality of ion mobility-mass spectrometry (IM-MS) measurements is of great importance for enabling modular and efficient computational workflows and gaining better qualitative and quantitative insights from complex biological and environmental samples. We developed the PNNL PreProcessor, a standalone and user-friendly software housing various algorithmic implementations to generate new MS-files with enhanced signal quality and in the same instrument format. Different experimental approaches are supported for IM-MS based on Drift-Tube (DT) and Structures for Lossless Ion Manipulations (SLIM), including liquid chromatography (LC) and infusion analyses. The algorithms extend the dynamic range of the detection system, while reducing file sizes for faster and memory-efficient downstream processing. Specifically, multidimensional smoothing improves peak shapes of poorly defined low-abundance signals, and saturation repair reconstructs the intensity profile of high-abundance peaks from various analyte types. Other functionalities are data compression and interpolation, IM demultiplexing, noise filtering by low intensity threshold and spike removal, and exporting of acquisition metadata. Several advantages of the tool are illustrated, including an increase of 19.4% in lipid annotations and a two-times faster processing of LC-DT IM-MS data-independent acquisition spectra from a complex lipid extract of a standard human plasma sample. The software is freely available at https://omics.pnl.gov/software/pnnl-preprocessor.

Optimization of a liquid chromatography-ion mobility-high resolution mass spectrometry platform for untargeted lipidomics and application to HepaRG cell extracts

Analytical methods to evaluate the lipidome of biological samples need to provide high data quality to ensure comprehensive profiling and reliable structural elucidation. In this perspective, liquid chromatography-high resolution mass spectrometry (LC-HRMS) is the state-of-the-art technique for lipidomic analysis of biological samples. There are thousands of lipids in most biological samples, and therefore separation methods before introduction to the mass spectrometer is key for relative quantitation and identification. Chromatographic methods differ across laboratories, without any consensus on the best methodologies. Therefore, we designed an experiment to determine the optimal LC methodology, and assessed the value of ion mobility for an additional dimension of separation. To apply an untargeted method for hypothesis generation focused on lipidomics, LC-HRMS parameters were optimized based on the measurement of 50 panel lipids covering key human metabolic pathways. Reversed-phase liquid chromatography columns were compared based on a quality scoring system considering the signal-to-noise ratio, peak shape, and retention factor. Furthermore, drift tube ion mobility spectrometry (DTIMS) was implemented to increase peak capacity and confidence during annotation by providing collision cross section (CCS) values for the analytes under investigation. However, hyphenating DTIMS to LC-HRMS may result in a reduced sensitivity due to impaired duty cycles. To increase the signal intensity, a Box-Behnken design (BBD) was used to optimize four key factors, i.e. drift entrance voltage, drift exit voltage, rear funnel entrance, and rear funnel exit voltages. Application of a maximized desirability function provided voltages for the above-mentioned parameters resulting in higher signal intensity compared to each combination of parameters used during the BBD. In addition, the influence of single pulse and Hadamard 4-bit multiplexed modes on signal intensity was explored and different trap filling and release times of ions were evaluated. The optimized LC-DTIM-HRMS platform was applied to extracts from HepaRG cells and resulted in 3912 high-quality features (<30% median relative standard deviation; n = 6, t = 24 h). From these features, 436 lipid species could be annotated (i.e., matching based on accurate mass <5 ppm, isotopic pattern, in-silico MS/MS fragmentation, and in-silico CCS database matching <3%). The application of LC-DTIM-HRMS for untargeted analysis workflows is growing and the platform optimization, as described here, can be used to guide the method development and CCS database comparison for high confidence lipid annotation.

Nutritional markers and proteome in patients undergoing treatment for pulmonary tuberculosis differ by geographic region

Introduction

Contemporary phase 2 TB disease treatment clinical trials have found that microbiologic treatment responses differ between African versus non-African regions, the reasons for which remain unclear. Understanding host and disease phenotypes that may vary by region is important for optimizing curative treatments.

Methods

We characterized clinical features and the serum proteome of phase 2 TB clinical trial participants undergoing treatment for smear positive, culture-confirmed TB, comparing host serum protein expression in clinical trial participants enrolled in African and Non-African regions. Serum samples were collected from 289 participants enrolled in the Centers for Disease Control and Prevention TBTC Study 29 (NCT00694629) at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment).

Results

After a peptide level proteome analysis utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS) and subsequent statistical analysis, a total of 183 core proteins demonstrated significant differences at both baseline and at week 8 timepoints between participants enrolled from African and non-African regions. The majority of the differentially expressed proteins were upregulated in participants from the African region, and included acute phase proteins, mediators of inflammation, as well as coagulation and complement pathways. Downregulated proteins in the African population were primarily linked to nutritional status and lipid metabolism pathways.

Conclusions

We have identified differentially expressed nutrition and lipid pathway proteins by geographic region in TB patients undergoing treatment for pulmonary tuberculosis, which appear to be associated with differential treatment responses. Future TB clinical trials should collect expanded measures of nutritional status and further evaluate the relationship between nutrition and microbiologic treatment response.

Glycoproteomic Analysis of Human Urinary Exosomes

Exosomes represent a class of secreted biological vesicles, which have recently gained attention due to their function as intertissue and interorganism transporters of genetic materials, small molecules, lipids, and proteins. Although the protein constituents of these exosomes are often glycosylated, a large-scale characterization of the glycoproteome has not yet been completed. This study identified 3144 unique glycosylation events belonging to 378 glycoproteins and 604 unique protein sites of glycosylation. With these data, we investigated the level of glycan microheterogeneity within the urinary exosomes, finding on average 5.9 glycans per site. The glycan family abundance on individual proteins showed subtle differences, providing an additional level of molecular characterization compared to the unmodified proteome. Finally, we show protein site-specific changes in regard to the common urinary glycoprotein, uromodulin. While uromodulin is an individual case, these same site-specific analyses provide a way forward for developing diagnostic glycoprotein biomarkers with urine as a noninvasive biological fluid. This study represents an important first step in understanding the functional urinary glycoproteome.

Proteomic assessment of serum biomarkers of longevity in older men

The biological bases of longevity are not well understood, and there are limited biomarkers for the prediction of long life. We used a high-throughput, discovery-based proteomics approach to identify serum peptides and proteins that were associated with the attainment of longevity in a longitudinal study of community-dwelling men age ≥65 years. Baseline serum in 1196 men were analyzed using liquid chromatography-ion mobility-mass spectrometry, and lifespan was determined during ~12 years of follow-up. Men who achieved longevity (≥90% expected survival) were compared to those who died earlier. Rigorous statistical methods that controlled for false positivity were utilized to identify 25 proteins that were associated with longevity. All these proteins were in lower abundance in long-lived men and included a variety involved in inflammation or complement activation. Lower levels of longevity-associated proteins were also associated with better health status, but as time to death shortened, levels of these proteins increased. Pathway analyses implicated a number of compounds as important upstream regulators of the proteins and implicated shared networks that underlie the observed associations with longevity. Overall, these results suggest that complex pathways, prominently including inflammation, are linked to the likelihood of attaining longevity. This work may serve to identify novel biomarkers for longevity and to understand the biology underlying lifespan.

Longitudinal proteomics analysis in the immediate microenvironment of islet allografts during progression of rejection

The applicability and benefits of pancreatic islet transplantation are limited due to various issues including the need to avoid immune-mediated rejection. Here, we used our experimental platform of allogeneic islet transplant in the anterior chamber of the eye (ACE-platform) to longitudinally monitor the progress of rejection in mice and obtain aqueous humor samples representative of the microenvironment of the graft for accurately-timed proteomic analyses. LC-MS/MS-based proteomics performed on such mass-limited samples (~5 μL) identified a total of 1296 proteins. Various analyses revealed distinct protein patterns associated with the mounting of the inflammatory and immune responses and their evolution with the progression of the rejection. Pathway analyses indicated predominant changes in cytotoxic functions, cell movement, and innate and adaptive immune responses. Network prediction analyses revealed transition from humoral to cellular immune response and exacerbation of pro-inflammatory signaling. One of the proteins identified by this localized proteomics as a candidate biomarker of islet rejection, Cystatin 3, was further validated by ELISA in the aqueous humor. This study provides (1) experimental evidence demonstrating the feasibility of longitudinal localized proteomics using small aqueous humor samples and (2) proof-of-concept for the discovery of biomarkers of impending immune attack from the immediate local microenvironment of ACE-transplanted islets. SIGNIFICANCE: The combination of the ACE-platform and longitudinal localized proteomics offers a powerful approach to biomarker discovery during the various stages of immune reactions mounted against transplanted tissues including pancreatic islets. It also supports proteomics-assisted drug discovery and development efforts aimed at preventing rejection through efficacy assessment of new agents by noninvasive and longitudinal graft monitoring.

Fundamentals of Ion Mobility-Mass Spectrometry for the Analysis of Biomolecules

Ion mobility-mass spectrometry (IM-MS) combines complementary size- and mass-selective separations into a single analytical platform. This chapter provides context for both the instrumental arrangements and key application areas that are commonly encountered in bioanalytical settings. New advances in these high-throughput strategies are described with description of complementary informatics tools to effectively utilize these data-intensive measurements. Rapid separations such as these are especially important in systems, synthetic, and chemical biology in which many small molecules are transient and correspond to various biological classes for integrated omics measurements. This chapter highlights the fundamentals of IM-MS and its applications toward biomolecular separations and discusses methods currently being used in the fields of proteomics, lipidomics, and metabolomics.

Organic acid shift reagents for the discrimination of carbohydrate isobars by ion mobility-mass spectrometry

Traveling wave and drift tube ion mobility were utilized to separate isomeric disaccharides. Organic acid shift reagents were necessary to increase the resolution of these separations for mixture analysis.

Ion Mobility Spectrometry and the Omics: Distinguishing Isomers, Molecular Classes and Contaminant Ions in Complex Samples

Ion mobility spectrometry (IMS) is a widely used analytical technique providing rapid gas phase separations. IMS alone is useful, but its coupling with mass spectrometry (IMS-MS) and various front-end separation techniques has greatly increased the molecular information achievable from different omic analyses. IMS-MS analyses are specifically gaining attention for improving metabolomic, lipidomic, glycomic, proteomic and exposomic analyses by increasing measurement sensitivity (e.g. S/N ratio), reducing the detection limit, and amplifying peak capacity. Numerous studies including national security-related analyses, disease screenings and environmental evaluations are illustrating that IMS-MS is able to extract information not possible with MS alone. Furthermore, IMS-MS has shown great utility in salvaging molecular information for low abundance molecules of interest when high concentration contaminant ions are present in the sample by reducing detector suppression. This review highlights how IMS-MS is currently being used in omic analyses to distinguish structurally similar molecules, isomers, molecular classes and contaminant ions.

Ion mobility spectrometry: the diagnostic tool of third millennium medicine

Ion mobility spectrometry (IMS) is a fast, low cost, portable, and sensitive technique that separates ions in a drift tube under the influence of an electric field according to their size and shape. IMS represents a non-invasive and reliable instrumental alternative for the diagnosis of different diseases through the analysis of volatile metabolites in biological samples. IMS has applications in medicine in the study of volatile compounds for the non-invasive diagnose of bronchial carcinoma, chronic obstructive pulmonary disease, and other diseases analysing breath, urine, blood, faeces, and other biological samples. This technique has been used to study complex mixtures such as proteomes, metabolomes, complete organisms like bacteria and viruses, monitor anaesthetic agents, determine drugs, pharmaceuticals, and volatile compounds in human body fluids, and others. Pharmaceutical applications include analysis of over-the-counter-drugs, quality assessment, and cleaning verification. Medical practice needs non-invasive, robust, secure, fast, real-time, and low-cost methods with high sensitivity and compact size instruments to diagnose different diseases and IMS is the diagnostic tool that meets all these requirements of the Medicine of the future.

Improved Sensitivity and Separations for Phosphopeptides using Online Liquid Chromotography Coupled with Structures for Lossless Ion Manipulations Ion Mobility-Mass Spectrometry

Phosphoproteomics greatly augments proteomics and holds tremendous potential for insights into the modulation of biological systems for various disease states. However, numerous challenges hinder conventional methods in terms of measurement sensitivity, throughput, quantification, and capabilities for confident phosphopeptide and phosphosite identification. In this work, we report the first example of integrating structures for lossless ion manipulations ion mobility-mass spectrometry (SLIM IM-MS) with online reversed-phase liquid chromatography (LC) to evaluate its potential for addressing the aforementioned challenges. A mixture of 51 heavy-labeled phosphopeptides was analyzed with a SLIM IM module having integrated ion accumulation and long-path separation regions. The SLIM IM-MS provided limits of detection as low as 50-100 pM (50-100 amol/μL) for several phosphopeptides, with the potential for significant further improvements. In addition, conventionally problematic phosphopeptide isomers could be resolved following an 18 m SLIM IM separation. The 2-D LC-IM peak capacity was estimated as ∼9000 for a 90 min LC separation coupled to an 18 m SLIM IM separation, considerably higher than LC alone and providing a basis for both improved identification and quantification, with additional gains projected with the future use of longer path SLIM IM separations. Thus, LC-SLIM IM-MS offers great potential for improving the sensitivity, separation, and throughput of phosphoproteomics analyses.

Physiological and proteomic analyses of Fe(III)-reducing co-cultures of Desulfotomaculum reducens MI-1 and Geobacter sulfurreducens PCA

We established Fe(III)-reducing co-cultures of two species of metal-reducing bacteria, the Gram-positive Desulfotomaculum reducens MI-1 and the Gram-negative Geobacter sulfurreducens PCA. Co-cultures were given pyruvate, a substrate that D. reducens can ferment and use as electron donor for Fe(III) reduction. G. sulfurreducens relied upon products of pyruvate oxidation by D. reducens (acetate, hydrogen) for use as electron donor in the co-culture. Co-cultures reduced Fe(III) to Fe(II) robustly, and Fe(II) was consistently detected earlier in co-cultures than pure cultures. Notably, faster cell growth, and correspondingly faster pyruvate oxidation, was observed by D. reducens in co-cultures. Global comparative proteomic analysis was performed to observe differential protein abundance during co-culture vs. pure culture growth. Proteins previously associated with Fe(III) reduction in G. sulfurreducens, namely c-type cytochromes and type IV pili proteins, were significantly increased in abundance in co-cultures relative to pure cultures. D. reducens ribosomal proteins were significantly increased in co-cultures, likely a reflection of faster growth rates observed for D. reducens cells while in co-culture. Furthermore, we developed multiple reaction monitoring (MRM) assays to quantitate specific biomarker peptides. The assays were validated in pure and co-cultures, and protein abundance ratios from targeted MRM and global proteomic analysis correlate significantly.

Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis

Rationale:

The monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment.

Objective:

We utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy.

Methods:

Serum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoaffinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points.

Results:

A total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were significantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status.

Conclusion:

A comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care.

Evaluating lipid mediator structural complexity using ion mobility spectrometry combined with mass spectrometry

AIM

Lipid mediators (LMs) are broadly defined as a class of bioactive lipophilic molecules that regulate cell-to-cell communication events with many having a strong correlation with various human diseases and conditions. LMs are usually analyzed with  LC-MS, but their numerous isomers greatly complicate the measurements with essentially identical fragmentation spectra and LC separations are not always sufficient for distinguishing the features. Results/methodology: In this work, we characterized LMs using ion mobility spectrometry (IMS) coupled with MS (IMS-MS). The collision cross-sections and m/z values from the IMS and MS analyses displayed distinct trend lines. Specifically, the structural trend lines for sodiated LMs originating from docosahexaenoic acid had the smallest collision cross-section values in relation to m/z, while those from linoleic acid had the largest. LC-IMS-MS analyses were also performed on LMs in flu infected mouse tissue samples. These multidimensional studies were able to assess known LMs while also detecting new species.

CONCLUSION

Adding IMS separations to conventional LC-MS analyses show great utility for enabling better identification and characterization of LMs in complex biological samples.

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.

Coupling Front-End Separations, Ion Mobility Spectrometry, and Mass Spectrometry For Enhanced Multidimensional Biological and Environmental Analyses

Ion mobility spectrometry (IMS) is a widely used analytical technique for rapid molecular separations in the gas phase. Though IMS alone is useful, its coupling with mass spectrometry (MS) and front-end separations is extremely beneficial for increasing measurement sensitivity, peak capacity of complex mixtures, and the scope of molecular information available from biological and environmental sample analyses. In fact, multiple disease screening and environmental evaluations have illustrated that the IMS-based multidimensional separations extract information that cannot be acquired with each technique individually. This review highlights three-dimensional separations using IMS-MS in conjunction with a range of front-end techniques, such as gas chromatography, supercritical fluid chromatography, liquid chromatography, solid-phase extractions, capillary electrophoresis, field asymmetric ion mobility spectrometry, and microfluidic devices. The origination, current state, various applications, and future capabilities of these multidimensional approaches are described in detail to provide insight into their uses and benefits.

Specifically Formed Corona on Silica Nanoparticles Enhances Transforming Growth Factor β1 Activity in Triggering Lung Fibrosis

A corona is a layer of macromolecules formed on a nanoparticle surface in vivo. It can substantially change the biological identity of nanomaterials and possibly trigger adverse responses from the body tissues. Dissecting the role of the corona in the development of a particular disease may provide profound insights for understanding toxicity of nanomaterials in general. In our present study, we explored the capability of different silica nanoparticles (SiNPs) to induce silicosis in the mouse lung and analyzed the composition of coronas formed on these particles. We found that SiNPs of certain size and surface chemistry could specifically recruit transforming growth factor β1 (TGF-β1) into their corona, which subsequently induces the development of lung fibrosis. Once embedded into the corona on SiNPs, TGF-β1 was remarkably more stable than in its free form, and its fibrosis-triggering activity was significantly prolonged. Our study meaningfully demonstrates that a specific corona component on a certain nanoparticle could initiate a particular pathogenic process in a clinically relevant disease model. Our findings may shed light on the understanding of molecular mechanisms of human health risks correlated with exposure to small-scale substances.

The fungal cultivar of leaf-cutter ants produces specific enzymes in response to different plant substrates

Herbivores use symbiotic microbes to help derive energy and nutrients from plant material. Leaf-cutter ants are a paradigmatic example, cultivating their mutualistic fungus Leucoagaricus gongylophorus on plant biomass that workers forage from a diverse collection of plant species. Here, we investigate the metabolic flexibility of the ants' fungal cultivar for utilizing different plant biomass. Using feeding experiments and a novel approach in metaproteomics, we examine the enzymatic response of L. gongylophorus to leaves, flowers, oats or a mixture of all three. Across all treatments, our analysis identified and quantified 1766 different fungal proteins, including 161 putative biomass-degrading enzymes. We found significant differences in the protein profiles in the fungus gardens of subcolonies fed different plant substrates. When provided with leaves or flowers, which contain the majority of their energy as recalcitrant plant polymers, the fungus gardens produced more proteins predicted to break down cellulose: endoglucanase, exoglucanase and β-glucosidase. Further, the complete metaproteomes for the leaves and flowers treatments were very similar, while the mixed substrate treatment closely resembled the treatment with oats alone. This indicates that when provided a mixture of plant substrates, fungus gardens preferentially break down the simpler, more digestible substrates. This flexible, substrate-specific enzymatic response of the fungal cultivar allows leaf-cutter ants to derive energy from a wide range of substrates, which likely contributes to their ability to be dominant generalist herbivores.

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.

Ion Mobility Separations of Isomers based upon Long Path Length Structures for Lossless Ion Manipulations Combined with Mass Spectrometry

Mass spectrometry (MS)-based multi-omic measurements, including proteomics, metabolomics, lipidomics, and glycomics, are increasingly transforming our ability to characterize and understand biological systems. Multi-omic analyses and the desire for comprehensive measurement coverage presently have limitations due to the chemical diversity and range of abundances of biomolecules in complex samples. Advances addressing these challenges increasingly are based upon the ability to quickly separate, react and otherwise manipulate sample components for analysis by MS. Here we report on a new approach using Structures for Lossless Ion Manipulations (SLIM) to enable long serpentine path ion mobility spectrometry (IMS) separations followed by MS analyses. This approach provides previously unachieved resolution for biomolecular species, in conjunction with more effective ion utilization, and a basis for greatly improved characterization of very small sample sizes.

Targeting the untargeted in molecular phenomics with structurally-selective ion mobility-mass spectrometry

Systems-wide molecular phenomics is rapidly expanding through technological advances in instrumentation and bioinformatics. Strategies such as structural mass spectrometry, which utilizes size and shape measurements with molecular weight, serve to characterize the sum of molecular expression in biological contexts, where broad-scale measurements are made that are interpreted through big data statistical techniques to reveal underlying patterns corresponding to phenotype. The data density, data dimensionality, data projection, and data interrogation are all critical aspects of these approaches to turn data into salient information. Untargeted molecular phenomics is already having a dramatic impact in discovery science from drug discovery to synthetic biology. It is evident that these emerging techniques will integrate closely in broad efforts aimed at precision medicine.

Quantitative proteomics and phosphoproteomics on serial tumor biopsies from a sorafenib-treated HCC patient

Compensatory signaling pathways in tumors confer resistance to targeted therapy, but the pathways and their mechanisms of activation remain largely unknown. We describe a procedure for quantitative proteomics and phosphoproteomics on snap-frozen biopsies of hepatocellular carcinoma (HCC) and matched nontumor liver tissue. We applied this procedure to monitor signaling pathways in serial biopsies taken from an HCC patient before and during treatment with the multikinase inhibitor sorafenib. At diagnosis, the patient had an advanced HCC. At the time of the second biopsy, abdominal imaging revealed progressive disease despite sorafenib treatment. Sorafenib was confirmed to inhibit MAPK signaling in the tumor, as measured by reduced ribosomal protein S6 kinase phosphorylation. Hierarchical clustering and enrichment analysis revealed pathways broadly implicated in tumor progression and resistance, such as epithelial-to-mesenchymal transition and cell adhesion pathways. Thus, we describe a protocol for quantitative analysis of oncogenic pathways in HCC biopsies and obtained first insights into the effect of sorafenib in vivo. This protocol will allow elucidation of mechanisms of resistance and enable precision medicine.

Chemometrics for ion mobility spectrometry data: recent advances and future prospects

This is the first comprehensive review on chemometric techniques used in ion mobility spectrometry data analysis.

High-throughput platforms for metabolomics

Mass spectrometry has become a choice method for broad-spectrum metabolite analysis in both fundamental and applied research. This can range from comprehensive analysis achieved through time-consuming chromatography to the rapid analysis of a few target metabolites without chromatography. In this review article, we highlight current high-throughput MS-based platforms and their potential application in metabolomics. Although current MS platforms can reach throughputs up to 0.5 seconds per sample, the metabolite coverage of these platforms are low compared to low-throughput, separation-based MS methods. High-throughput comes at a cost, as it's a trade-off between sample throughput and metabolite coverage. As we will discuss, promising emerging technologies, including microfluidics and miniaturization of separation techniques, have the potential to achieve both rapid and more comprehensive metabolite analysis.

Systems-Wide High-Dimensional Data Acquisition and Informatics Using Structural Mass Spectrometry Strategies

BACKGROUND

Untargeted multiomics data sets are obtained for samples in systems, synthetic, and chemical biology by integrating chromatographic separations with ion mobility-mass spectrometry (IM-MS) analysis. The data sets are interrogated using bioinformatics strategies to organize the data for identification prioritization.

CONTENT

The use of big data approaches for data mining of massive data sets in systems-wide analyses is presented. Untargeted biological data across multiomics dimensions are obtained using a variety of chromatography strategies with structural MS. Separation timescales for different techniques and the resulting data deluge when combined with IM-MS are presented. Data mining self-organizing map strategies are used to rapidly filter the data, highlighting those features describing uniqueness to the query. Examples are provided in longitudinal analyses in synthetic biology and human liver exposure to acetaminophen, and in chemical biology for natural product discovery from bacterial biomes.

CONCLUSIONS

Matching the separation timescales of different forms of chromatography with IM-MS provides sufficient multiomics selectivity to perform untargeted systems-wide analyses. New data mining strategies provide a means for rapidly interrogating these data sets for feature prioritization and discovery in a range of applications in systems, synthetic, and chemical biology.

Enhancing bottom-up and top-down proteomic measurements with ion mobility separations

Proteomic measurements with greater throughput, sensitivity, and structural information are essential for improving both in-depth characterization of complex mixtures and targeted studies. While LC separation coupled with MS (LC-MS) measurements have provided information on thousands of proteins in different sample types, the introduction of a separation stage that provides further component resolution and rapid structural information has many benefits in proteomic analyses. Technical advances in ion transmission and data acquisition have made ion mobility separations an opportune technology to be easily and effectively incorporated into LC-MS proteomic measurements for enhancing their information content. Herein, we report on applications illustrating increased sensitivity, throughput, and structural information by utilizing IMS-MS and LC-IMS-MS measurements for both bottom-up and top-down proteomics measurements.

Gas-Phase Hydrogen-Deuterium Exchange Labeling of Select Peptide Ion Conformer Types: a Per-Residue Kinetics Analysis

The per-residue, gas-phase hydrogen deuterium exchange (HDX) kinetics for individual amino acid residues on selected ion conformer types of the model peptide KKDDDDDIIKIIK have been examined using ion mobility spectrometry (IMS) and HDX-tandem mass spectrometry (MS/MS) techniques. The [M + 4H](4+) ions exhibit two major conformer types with collision cross sections of 418 Å(2) and 446 Å(2); the [M + 3H](3+) ions also yield two different conformer types having collision cross sections of 340 Å(2) and 367 Å(2). Kinetics plots of HDX for individual amino acid residues reveal fast- and slow-exchanging hydrogens. The contributions of each amino acid residue to the overall conformer type rate constant have been estimated. For this peptide, N- and C-terminal K residues exhibit the greatest contributions for all ion conformer types. Interior D and I residues show decreased contributions. Several charge state trends are observed. On average, the D residues of the [M + 3H](3+) ions show faster HDX rate contributions compared with [M + 4H](4+) ions. In contrast the interior I8 and I9 residues show increased accessibility to exchange for the more elongated [M + 4H](4+) ion conformer type. The contribution of each residue to the overall uptake rate showed a good correlation with a residue hydrogen accessibility score model calculated using a distance from charge site and initial incorporation site for nominal structures obtained from molecular dynamic simulations (MDS).

Muscle Segment Homeobox Genes Direct Embryonic Diapause by Limiting Inflammation in the Uterus

Embryonic diapause is a reproductive strategy widespread in the animal kingdom. This phenomenon is defined by a temporary arrest in blastocyst growth and metabolic activity within a quiescent uterus without implantation until the environmental and maternal milieu become favorable for pregnancy to progress. We found that uterine Msx expression persists during diapause across species; their inactivation in the mouse uterus results in termination of diapause with the development of implantation-like responses ("pseudoimplantation") that ultimately succumbed to resorption. To understand the cause of this failure, we compared proteome profiles between floxed and Msx-deleted uteri. In deleted uteri, several functional networks, including transcription/translation, ubiquitin-proteasome, inflammation, and endoplasmic reticulum stress, were dysregulated. Computational modeling predicted intersection of these pathways on an enhanced inflammatory signature. Further studies showed that this signature was reflected in increased phosphorylated IκB levels and nuclear NFκB in deleted uteri. This was associated with enhanced proteasome activity and endoplasmic reticulum stress. Interestingly, treatment with anti-inflammatory glucocorticoid (dexamethasone) reduced the inflammatory signature with improvement of the diapause phenotype. These findings highlight an unexpected role of uterine Msx in limiting aberrant inflammatory responses to maintain embryonic diapause.

Proteomics analysis of bodily fluids in pancreatic cancer

Proteomics study of pancreatic cancer using bodily fluids emphasizes biomarker discovery and clinical application, presenting unique prospect and challenges. Depending on the physiological nature of the bodily fluid and its proximity to pancreatic cancer, the proteomes of bodily fluids, such as pancreatic juice, pancreatic cyst fluid, blood, bile, and urine, can be substantially different in terms of protein constitution and the dynamic range of protein concentration. Thus, a comprehensive discovery and specific detection of cancer-associated proteins within these varied fluids is a complex task, requiring rigorous experiment design and a concerted approach. While major challenges still remain, fluid proteomics studies in pancreatic cancer to date have provided a wealth of information in revealing proteome alterations associated with pancreatic cancer in various bodily fluids.

Turnover rates of hepatic collagen and circulating collagen-associated proteins in humans with chronic liver disease

Accumulation and degradation of scar tissue in fibrotic liver disease occur slowly, typically over many years. Direct measurement of fibrogenesis, the rate of scar tissue deposition, may provide valuable therapeutic and prognostic information. We describe here results from a pilot study utilizing in vivo metabolic labeling to measure the turnover rate of hepatic collagen and collagen-associated proteins in plasma for the first time in human subjects. Eight subjects with chronic liver disease were labeled with daily oral doses of ²H₂O for up to 8 weeks prior to diagnostic liver biopsy and plasma collection. Tandem mass spectrometry was used to measure the abundance and fractional synthesis rate (FSR) of proteins in liver and blood. Relative protein abundance and FSR data in liver revealed marked differences among subjects. FSRs of hepatic type I and III collagen ranged from 0.2–0.6% per day (half-lives of 4 months to a year) and correlated significantly with worsening histologic fibrosis. Analysis of plasma protein turnover revealed two collagen-associated proteins, lumican and transforming growth factor beta-induced-protein (TGFBI), exhibiting FSRs that correlated significantly with FSRs of hepatic collagen. In summary, this is the first direct measurement of liver collagen turnover in vivo in humans and suggests a high rate of collagen remodeling in advanced fibrosis. In addition, the FSRs of collagen-associated proteins in plasma are measurable and may provide a novel strategy for monitoring hepatic fibrogenesis rates.

Development of a New Ion Mobility (Quadrupole) Time-of-Flight Mass Spectrometer

A new ion mobility spectrometer (IMS) platform was developed to improve upon the sensitivity and reproducibility of our previous platforms, and further enhance IMS-MS utility for broad 'pan-omics' measurements. The new platform incorporated an improved electrospray ionization source and interface for enhanced sensitivity, and providing the basis for further benefits based upon implementation of multiplexed IMS. The ion optics included electrodynamic ion funnels at both the entrance and exit of the IMS, an ion funnel trap for ion injection, and a design in which nearly all ion optics (e.g. drift rings, ion funnels) were fabricated using printed circuit board technology. The IMS resolving power achieved was ~73 for singly-charged ions, very close to the predicted diffusion-limited resolving power (~75). The platform's performance evaluation (e.g. for proteomics measurements) include LC-IMS-TOF MS datasets for 30 technical replicates for a trypsin digested human serum, and included platform performance in each dimension (LC, IMS and MS) separately.

Ion mobility-mass spectrometry strategies for untargeted systems, synthetic, and chemical biology

Contemporary strategies that concentrate on only one or a handful of molecular targets limits the utility of the information gained for diagnostic and predictive purposes. Recent advances in the sensitivity, speed, and precision of measurements obtained from ion mobility coupled to mass spectrometry (IM-MS) have accelerated the utility of IM-MS in untargeted, discovery-driven studies in biology. Perhaps most evident is the impact that such wide-scale discovery capabilities have yielded in the areas of systems, synthetic, and chemical biology, where the need for comprehensive, hypothesis-driving studies from multidimensional and unbiased data is required.

DeMix workflow for efficient identification of cofragmented peptides in high resolution data-dependent tandem mass spectrometry

Based on conventional data-dependent acquisition strategy of shotgun proteomics, we present a new workflow DeMix, which significantly increases the efficiency of peptide identification for in-depth shotgun analysis of complex proteomes. Capitalizing on the high resolution and mass accuracy of Orbitrap-based tandem mass spectrometry, we developed a simple deconvolution method of "cloning" chimeric tandem spectra for cofragmented peptides. Additional to a database search, a simple rescoring scheme utilizes mass accuracy and converts the unwanted cofragmenting events into a surprising advantage of multiplexing. With the combination of cloning and rescoring, we obtained on average nine peptide-spectrum matches per second on a Q-Exactive workbench, whereas the actual MS/MS acquisition rate was close to seven spectra per second. This efficiency boost to 1.24 identified peptides per MS/MS spectrum enabled analysis of over 5000 human proteins in single-dimensional LC-MS/MS shotgun experiments with an only two-hour gradient. These findings suggest a change in the dominant "one MS/MS spectrum - one peptide" paradigm for data acquisition and analysis in shotgun data-dependent proteomics. DeMix also demonstrated higher robustness than conventional approaches in terms of lower variation among the results of consecutive LC-MS/MS runs.