Biomolecular signatures of diabetic wound healing by structural mass spectrometry

HILIC-IM-MS for Simultaneous Lipid and Metabolite Profiling of Bacteria

Although MALDI-ToF platforms for microbial identifications have found great success in clinical microbiology, the sole use of protein fingerprints for the discrimination of closely related species, strain-level identifications, and detection of antimicrobial resistance remains a challenge for the technology. Several alternative mass spectrometry-based methods have been proposed to address the shortcomings of the protein-centric approach, including MALDI-ToF methods for fatty acid/lipid profiling and LC-MS profiling of metabolites. However, the molecular diversity of microbial pathogens suggests that no single "ome" will be sufficient for the accurate and sensitive identification of strain- and susceptibility-level profiling of bacteria. Here, we describe the development of an alternative approach to microorganism profiling that relies upon both metabolites and lipids rather than a single class of biomolecule. Single-phase extractions based on butanol, acetonitrile, and water (the BAW method) were evaluated for the recovery of lipids and metabolites from Gram-positive and -negative microorganisms. We found that BAW extraction solutions containing 45% butanol provided optimal recovery of both molecular classes in a single extraction. The single-phase extraction method was coupled to hydrophilic interaction liquid chromatography (HILIC) and ion mobility-mass spectrometry (IM-MS) to resolve similar-mass metabolites and lipids in three dimensions and provide multiple points of evidence for feature annotation in the absence of tandem mass spectrometry. We demonstrate that the combined use of metabolites and lipids can be used to differentiate microorganisms to the species- and strain-level for four of the ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Acinetobacter baumannii, and Pseudomonas aeruginosa) using data from a single ionization mode. These results present promising, early stage evidence for the use of multiomic signatures for the identification of microorganisms by liquid chromatography, ion mobility, and mass spectrometry that, upon further development, may improve upon the level of identification provided by current methods.

Advances in non-invasive biosensing measures to monitor wound healing progression

Impaired wound healing is a significant financial and medical burden. The synthesis and deposition of extracellular matrix (ECM) in a new wound is a dynamic process that is constantly changing and adapting to the biochemical and biomechanical signaling from the extracellular microenvironments of the wound. This drives either a regenerative or fibrotic and scar-forming healing outcome. Disruptions in ECM deposition, structure, and composition lead to impaired healing in diseased states, such as in diabetes. Valid measures of the principal determinants of successful ECM deposition and wound healing include lack of bacterial contamination, good tissue perfusion, and reduced mechanical injury and strain. These measures are used by wound-care providers to intervene upon the healing wound to steer healing toward a more functional phenotype with improved structural integrity and healing outcomes and to prevent adverse wound developments. In this review, we discuss bioengineering advances in 1) non-invasive detection of biologic and physiologic factors of the healing wound, 2) visualizing and modeling the ECM, and 3) computational tools that efficiently evaluate the complex data acquired from the wounds based on basic science, preclinical, translational and clinical studies, that would allow us to prognosticate healing outcomes and intervene effectively. We focus on bioelectronics and biologic interfaces of the sensors and actuators for real time biosensing and actuation of the tissues. We also discuss high-resolution, advanced imaging techniques, which go beyond traditional confocal and fluorescence microscopy to visualize microscopic details of the composition of the wound matrix, linearity of collagen, and live tracking of components within the wound microenvironment. Computational modeling of the wound matrix, including partial differential equation datasets as well as machine learning models that can serve as powerful tools for physicians to guide their decision-making process are discussed.

Lipidomics and RNA sequencing reveal a novel subpopulation of nanovesicle within extracellular matrix biomaterials

Biomaterials composed of extracellular matrix (ECM) provide both mechanical support and a reservoir of constructive signaling molecules that promote functional tissue repair. Recently, matrix-bound nanovesicles (MBVs) have been reported as an integral component of ECM bioscaffolds. Although liquid-phase extracellular vesicles (EVs) have been the subject of intense investigation, their similarity to MBV is limited to size and shape. Liquid chromatography-mass spectrometry (LC-MS)-based lipidomics and redox lipidomics were used to conduct a detailed comparison of liquid-phase EV and MBV phospholipids. Combined with comprehensive RNA sequencing and bioinformatic analysis of the intravesicular cargo, we show that MBVs are a distinct and unique subpopulation of EV and a distinguishing feature of ECM-based biomaterials. The results begin to identify the differential biologic activities mediated by EV that are secreted by tissue-resident cells and deposited within the ECM.

Utilizing Untargeted Ion Mobility-Mass Spectrometry To Profile Changes in the Gut Metabolome Following Biliary Diversion Surgery

Obesity and obesity-related disorders are a global epidemic affecting over 10% of the world's population. Treatment of these diseases has become increasingly challenging and expensive. The most effective and durable treatment for Class III obesity (body mass index ≥35 kg/m²) is bariatric surgery, namely, Roux-en-Y gastric bypass (RYGB) and vertical sleeve gastrectomy. These procedures are associated with increased circulating bile acids, molecules that not only facilitate intestinal fat absorption but are also potent hormones regulating numerous metabolic pathways. We recently reported on a novel surgical procedure in mice, termed distal gallbladder bile diversion to the ileum (GB-IL_dist), that emulates the altered bile flow after RYGB without other manipulations of gastrointestinal anatomy. GB-IL_dist improves oral glucose tolerance in mice made obese with high-fat diet. This is accompanied by fat malabsorption and weight loss, which complicates studying the role of elevated circulating bile acids in metabolic control. A less aggressive surgery in which the gallbladder bile is diverted to the proximal ileum, termed GB-IL_prox, also improves glucose control but is not accompanied by fat malabsorption. To better understand the differential effects achieved by these bile diversion procedures, an untargeted ultraperformance liquid chromatography-ion mobility-mass spectrometry (UPLC-IM-MS) method was optimized for fecal samples derived from mice that have undergone bile diversion surgery. Utilizing the UPLC-IM-MS method, we were able to identify dysregulation of bile acids, short-chain fatty acids, and cholesterol derivatives that contribute to the differential metabolism resulting from these surgeries.

Different pro-angiogenic potential of γ-irradiated PBMC-derived secretome and its subfractions

Secretomes from various cell sources exert strong regenerative activities on numerous organs, including the skin. Although secretomes consist of many diverse components, a growing body of evidence suggests that small extracellular vesicles (EVs) account for their regenerative capacity. We previously demonstrated that the secretome of γ-irradiated peripheral blood mononuclear cells (PBMCs) exhibits wound healing capacity. Therefore, we sought to dissect the molecular composition of EVs present in the secretome and compared wound healing-related activities of these EVs to other subfractions of the secretome and the fully supplemented secretome (MNC^aposec). Compared to EVs derived from non-irradiated PBMCs, γ-irradiation significantly increased the size and number and changed the composition of released EVs. Detailed characterization of the molecular components of EVs, i.e. miRNA, proteins, and lipids, derived from irradiated PBMCs revealed a strong association with regenerative processes. Reporter gene assays and aortic ring sprouting assays revealed diminished activity of the subfractions compared to MNC^aposec. In addition, we showed that MNC^aposec accelerated wound closure in a diabetic mouse model. Taken together, our results suggest that secretome-based wound healing represents a promising new therapeutic avenue, and strongly recommend using the complete secretome instead of purified subfractions, such as EVs, to exploit its full regenerative capacity.

Untargeted Molecular Discovery in Primary Metabolism: Collision Cross Section as a Molecular Descriptor in Ion Mobility-Mass Spectrometry

In this work, we established a collision cross section (CCS) library of primary metabolites based on analytical standards in the Mass Spectrometry Metabolite Library of Standards (MSMLS) using a commercially available ion mobility-mass spectrometer (IM-MS). From the 554 unique compounds in the MSMLS plate library, we obtained a total of 1246 CCS measurements over a wide range of biochemical classes and adduct types. Resulting data analysis demonstrated that the curated CCS library provides broad molecular coverage of metabolic pathways and highlights intrinsic mass-mobility relationships for specific metabolite superclasses. The separation and characterization of isomeric metabolites were assessed, and all molecular species contained within the plate library, including isomers, were critically evaluated to determine the analytical separation efficiency in both the mass ( m/ z) and mobility (CCS/ΔCCS) dimension required for untargeted metabolomic analyses. To further demonstrate the analytical utility of CCS as an additional molecular descriptor, a well-characterized biological sample of human plasma serum (NIST SRM 1950) was examined by LC-IM-MS and used to provide a detailed isomeric analysis of carbohydrate constituents by ion mobility.

Gated Trapped Ion Mobility Spectrometry Coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

Analysis of molecules by ion mobility spectrometry coupled with mass spectrometry (IMS-MS) provides chemical information on the three dimensional structure and mass of the molecules. The coupling of ion mobility to trapping mass spectrometers has historically been challenging due to the large differences in analysis time between the two devices. In this paper we present a modification of the trapped ion mobility (TIMS) analysis scheme termed "Gated TIMS" that allows efficient coupling to a Fourier Transform Ion Cyclotron Resonance (FT-ICR) analyzer. Analyses of standard compounds and the influence of source conditions on the TIMS distributions produced by ion mobility spectra of labile ubiquitin protein ions are presented. Ion mobility resolving powers up to 100 are observed. Measured collisional cross sections of ubiquitin ions are in excellent qualitative and quantitative agreement to previous measurements. Gated TIMS FT-ICR produces results comparable to those acquired using TIMS/time-of-flight MS instrument platforms as well as numerous drift tube IMS-MS studies published in the literature.

Untargeted metabolic profiling identifies interactions between Huntington's disease and neuronal manganese status

Manganese (Mn) is an essential micronutrient for development and function of the nervous system. Deficiencies in Mn transport have been implicated in the pathogenesis of Huntington's disease (HD), an autosomal dominant neurodegenerative disorder characterized by loss of medium spiny neurons of the striatum. Brain Mn levels are highest in striatum and other basal ganglia structures, the most sensitive brain regions to Mn neurotoxicity. Mouse models of HD exhibit decreased striatal Mn accumulation and HD striatal neuron models are resistant to Mn cytotoxicity. We hypothesized that the observed modulation of Mn cellular transport is associated with compensatory metabolic responses to HD pathology. Here we use an untargeted metabolomics approach by performing ultraperformance liquid chromatography-ion mobility-mass spectrometry (UPLC-IM-MS) on control and HD immortalized mouse striatal neurons to identify metabolic disruptions under three Mn exposure conditions, low (vehicle), moderate (non-cytotoxic) and high (cytotoxic). Our analysis revealed lower metabolite levels of pantothenic acid, and glutathione (GSH) in HD striatal cells relative to control cells. HD striatal cells also exhibited lower abundance and impaired induction of isobutyryl carnitine in response to increasing Mn exposure. In addition, we observed induction of metabolites in the pentose shunt pathway in HD striatal cells after high Mn exposure. These findings provide metabolic evidence of an interaction between the HD genotype and biologically relevant levels of Mn in a striatal cell model with known HD by Mn exposure interactions. The metabolic phenotypes detected support existing hypotheses that changes in energetic processes underlie the pathobiology of both HD and Mn neurotoxicity.

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.

Structural mass spectrometry of tissue extracts to distinguish cancerous and non-cancerous breast diseases

Aberrant metabolism in breast cancer tumors has been widely studied by both targeted and untargeted analyses to characterize the affected metabolic pathways. In this work, we utilize ultra-performance liquid chromatography (UPLC) in tandem with ion mobility-mass spectrometry (IM-MS), which provides chromatographic, structural, and mass information, to characterize the aberrant metabolism associated with breast diseases such as cancer. In a double-blind analysis of matched control (n = 3) and disease tissues (n = 3), samples were homogenized, polar metabolites were extracted, and the extracts were characterized by UPLC-IM-MS/MS. Principle component analysis revealed a strong separation between disease tissues, with one diseased tissue clustering with the control tissues along PC1 and two others separated along PC2. Using post-ion mobility MS/MS spectra acquired by data-independent acquisition, the features giving rise to the observed grouping were determined to be biomolecules associated with aggressive breast cancer tumors, including glutathione, oxidized glutathione, thymosins β4 and β10, and choline-containing species. Pathology reports revealed the outlier of the disease tissues to be a benign fibroadenoma, whereas the other disease tissues represented highly metabolic benign and aggressive tumors. This IM-MS-based workflow bridges the transition from untargeted metabolomic profiling to tentative identifications of key descriptive molecular features using data acquired in one analysis, with additional experiments performed only for validation. The ability to resolve cancerous and non-cancerous tissues at the biomolecular level demonstrates UPLC-IM-MS/MS as a robust and sensitive platform for metabolomic profiling of tissues.

Fundamentals of trapped ion mobility spectrometry

Trapped ion mobility spectrometry (TIMS) is a relatively new gas-phase separation method that has been coupled to quadrupole orthogonal acceleration time-of-flight mass spectrometry. The TIMS analyzer is a segmented rf ion guide wherein ions are mobility-analyzed using an electric field that holds ions stationary against a moving gas, unlike conventional drift tube ion mobility spectrometry where the gas is stationary. Ions are initially trapped, and subsequently eluted from the TIMS analyzer over time according to their mobility (K). Though TIMS has achieved a high level of performance (R > 250) in a small device (<5 cm) using modest operating potentials (<300 V), a proper theory has yet to be produced. Here, we develop a quantitative theory for TIMS via mathematical derivation and simulations. A one-dimensional analytical model, used to predict the transit time and theoretical resolving power, is described. Theoretical trends are in agreement with experimental measurements performed as a function of K, pressure, and the axial electric field scan rate. The linear dependence of the transit time with 1/K provides a fundamental basis for determination of reduced mobility or collision cross section values by calibration. The quantitative description of TIMS provides an operational understanding of the analyzer, outlines the current performance capabilities, and provides insight into future avenues for improvement.

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.