Multiple Reaction Monitoring Profiling (MRM-Profiling) of Lipids To Distinguish Strain-Level Differences in Microbial Resistance in Escherichia coli

Lipid mediators of inhalation exposure-induced pulmonary toxicity and inflammation

Many inhalation exposures induce pulmonary inflammation contributing to disease progression. Inflammatory processes are actively regulated via mediators including bioactive lipids. Bioactive lipids are potent signaling molecules involved in both pro-inflammatory and resolution processes through receptor interactions. The formation and clearance of lipid signaling mediators are controlled by multiple metabolic enzymes. An imbalance of these lipids can result in exacerbated and sustained inflammatory processes which may result in pulmonary damage and disease. Dysregulation of pulmonary bioactive lipids contribute to inflammation and pulmonary toxicity following exposures. For example, inhalation of cigarette smoke induces activation of pro-inflammatory bioactive lipids such as sphingolipids, and ceramides contributing to chronic obstructive pulmonary disease. Additionally, exposure to silver nanoparticles causes dysregulation of inflammatory resolution lipids. As inflammation is a common consequence resulting from inhaled exposures and a component of numerous diseases it represents a broadly applicable target for therapeutic intervention. With new appreciation for bioactive lipids, technological advances to reliably identify and quantify lipids have occurred. In this review, we will summarize, integrate, and discuss findings from recent studies investigating the impact of inhaled exposures on pro-inflammatory and resolution lipids within the lung and their contribution to disease. Throughout the review current knowledge gaps in our understanding of bioactive lipids and their contribution to pulmonary effects of inhaled exposures will be presented. New methods being employed to detect and quantify disruption of pulmonary lipid levels following inhalation exposures will be highlighted. Lastly, we will describe how lipid dysregulation could potentially be addressed by therapeutic strategies to address inflammation.

Uptake and Metabolic Conversion of Exogenous Phosphatidylcholines Depending on Their Acyl Chain Structure in Arabidopsis thaliana

Fungi and plants are not only capable of synthesizing the entire spectrum of lipids de novo but also possess a well-developed system that allows them to assimilate exogenous lipids. However, the role of structure in the ability of lipids to be absorbed and metabolized has not yet been characterized in detail. In the present work, targeted lipidomics of phosphatidylcholines (PCs) and phosphatidylethanolamines (PEs), in parallel with morphological phenotyping, allowed for the identification of differences in the effects of PC molecular species introduced into the growth medium, in particular, typical bacterial saturated (14:0/14:0, 16:0/16:0), monounsaturated (16:0/18:1), and typical for fungi and plants polyunsaturated (16:0/18:2, 18:2/18:2) species, on Arabidopsis thaliana. For comparison, the influence of an artificially synthesized (1,2-di-(3-(3-hexylcyclopentyl)-propanoate)-sn-glycero-3-phosphatidylcholine, which is close in structure to archaeal lipids, was studied. The phenotype deviations stimulated by exogenous lipids included changes in the length and morphology of both the roots and leaves of seedlings. According to lipidomics data, the main trends in response to exogenous lipid exposure were an increase in the proportion of endogenic 18:1/18:1 PC and 18:1_18:2 PC molecular species and a decrease in the relative content of species with C18:3, such as 18:3/18:3 PC and/or 16:0_18:3 PC, 16:1_18:3 PE. The obtained data indicate that exogenous lipid molecules affect plant morphology not only due to their physical properties, which are manifested during incorporation into the membrane, but also due to the participation of exogenous lipid molecules in the metabolism of plant cells. The results obtained open the way to the use of PCs of different structures as cellular regulators.

Machine-Learning Classification of Bacteria Using Two-Dimensional Tandem Mass Spectrometry

Biothreat detection has continued to gain attention. Samples suspected to fall into any of the CDC's biothreat categories require identification by processes that require specialized expertise and facilities. Recent developments in analytical instrumentation and machine learning algorithms offer rapid and accurate classification of Gram-positive and Gram-negative bacterial species. This is achieved by analyzing the negative ions generated from bacterial cell extracts with a modified linear quadrupole ion-trap mass spectrometer fitted with two-dimensional tandem mass spectrometry capabilities (2D MS/MS). The 2D MS/MS data domain of a bacterial cell extract is recorded within five s using a five-scan average after sample preparation by a simple extraction. Bacteria were classified at the species level by their lipid profiles using the random forest, k-nearest neighbor, and multilayer perceptron machine learning models. 2D MS/MS data can also be treated as image data for use with image recognition algorithms such as convolutional neural networks. The classification accuracy of all models tested was greater than 99%. Adding to previously published work on the 2D MS/MS analysis of bacterial growth and the profiling of sporulating bacteria, this study demonstrates the utility and information-rich nature of 2D MS/MS in the identification of bacterial pathogens at the species level when coupled with machine learning.

Silver Nanoparticle Targets Fabricated Using Chemical Vapor Deposition Method for Differentiation of Bacteria Based on Lipidomic Profiles in Laser Desorption/Ionization Mass Spectrometry

The global threat of numerous infectious diseases creates a great need to develop new diagnostic methods to facilitate the appropriate prescription of antimicrobial therapy. More recently, the possibility of using bacterial lipidome analysis via laser desorption/ionization mass spectrometry (LDI-MS) as useful diagnostic tool for microbial identification and rapid drug susceptibility has received particular attention because lipids are present in large quantities and can be easily extracted similar to ribosomal proteins. Therefore, the main goal of the study was to evaluate the efficacy of two different LDI techniques-matrix-assisted (MALDI) and surface-assisted (SALDI) approaches-in the classification of the closely related Escherichia coli strains under cefotaxime addition. Bacterial lipids profiles obtained by using the MALDI technique with different matrices as well as silver nanoparticle (AgNP) targets fabricated using the chemical vapor deposition method (CVD) of different AgNP sizes were analyzed by the means of different multivariate statistical methods such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), sparse partial least squares discriminant analysis (sPLS-DA), and orthogonal projections to latent structures discriminant analysis (OPLS-DA). The analysis showed that the MALDI classification of strains was hampered by interference from matrix-derived ions. In contrast, the lipid profiles generated by the SALDI technique had lower background noise and more signals associated with the sample, allowing E. coli to be successfully classified into cefotaxime-resistant and cefotaxime-sensitive strains, regardless of the size of the AgNPs. AgNP substrates obtained using the CVD method were used for the first time for distinguishing closely related bacterial strains based on their lipidomic profiles and demonstrate high potential as a future diagnostic tool for the detection of antibiotic susceptibility.

β-Lactamase Sensitive Probe for Rapid Detection of Antibiotic-Resistant Bacteria with Gas Chromatography–Tandem Mass Spectrometry

β-Lactamase (Bla) produced by bacteria to resist β-lactam antibiotics is a serious public health threat. Developing efficient diagnostic protocols for drug-resistant bacteria is of great significance. In this work, based on gas molecules in bacteria, a novel research strategy was proposed to develop a gas molecule-based probe by grafting 2-methyl-3-mercaptofuran (MF) onto cephalosporin intermediates via a nucleophilic substitution reaction. The probe can release the corresponding MF by reacting with Bla. The released MF, as a marker of drug-resistant bacteria, was analyzed by headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry. The Bla concentration as low as 0.2 nM can be easily observed, providing an efficient method for detecting enzyme activity and screening drug-resistant strains in vivo. Importantly, the method is universal, and probes with different properties can be prepared by changing different substrates to further identify different types of bacteria, thereby broadening the research methods and ideas for monitoring physiological processes.

Transient Complexity of E. coli Lipidome Is Explained by Fatty Acyl Synthesis and Cyclopropanation

In the case of many bacteria, such as Escherichia coli, the composition of lipid molecules, termed the lipidome, temporally adapts to different environmental conditions and thus modifies membrane properties to permit growth and survival. Details of the relationship between the environment and lipidome composition are lacking, particularly for growing cultures under either favourable or under stress conditions. Here, we highlight compositional lipidome changes by describing the dynamics of molecular species throughout culture-growth phases. We show a steady cyclopropanation of fatty acyl chains, which acts as a driver for lipid diversity. There is a bias for the cyclopropanation of shorter fatty acyl chains (FA 16:1) over longer ones (FA 18:1), which likely reflects a thermodynamic phenomenon. Additionally, we observe a nearly two-fold increase in saturated fatty acyl chains in response to the presence of ampicillin and chloramphenicol, with consequences for membrane fluidity and elasticity, and ultimately bacterial stress tolerance. Our study provides the detailed quantitative lipidome composition of three E. coli strains across culture-growth phases and at the level of the fatty acyl chains and provides a general reference for phospholipid composition changes in response to perturbations. Thus, lipidome diversity is largely transient and the consequence of lipid synthesis and cyclopropanation.

Suspect screening of exogenous compounds using multiple reaction screening (MRM) profiling in human urine samples

Thousands of chemical compounds produced by industry are dispersed in the human environment widely enough to reach the world population, and the introduction of new chemicals constantly occurs. As new synthetic molecules emerge, rapid analytical workflows for screening possible presence of exogenous compounds in biofluids can be useful as a first pass analysis to detect chemical exposure and guide the development and application of more elaborate LC-MS/MS methods for quantification. In this study, a suspect screening workflow using the multiple reaction monitoring (MRM) profiling method is proposed as a first pass exploratory technique to survey selected exogenous molecules in human urine samples. The workflow was applied to investigate 12 human urine samples using 310 MRMs related to the chemical functionalities of 87 exogenous compounds present in the METLIN database and reported in the literature. A total of 11 MRMs associated with five different compounds were detected in the samples. Product ion scans for the precursor ions of the selected MRMs were acquired as a further identification step for these chemicals. The suspect screening results suggested the presence of five exogenous compounds in the human urine samples analyzed, namely metformin, metoprolol, acetaminophen, paraxanthine and acrylamide. LC-MS/MS was applied as a last step to confirm these results, and the presence of four out of the five targets selected by MRM profiling were corroborated, indicating that this workflow can support the selection of suspect compounds to screen complex samples and guide more time-consuming and specific quantification analyses.

Mechanistic Studies and In Vivo Efficacy of an Oxadiazole-Containing Antibiotic

Methicillin-resistant Staphylococcus aureus (MRSA) infections are still difficult to treat, despite the availability of many FDA-approved antibiotics. Thus, new compound scaffolds are still needed to treat MRSA. The oxadiazole-containing compound, HSGN-94, has been shown to reduce lipoteichoic acid (LTA) in S. aureus, but the mechanism that accounts for LTA biosynthesis inhibition remains uncharacterized. Herein, we report the elucidation of the mechanism by which HSGN-94 inhibits LTA biosynthesis via utilization of global proteomics, activity-based protein profiling, and lipid analysis via multiple reaction monitoring (MRM). Our data suggest that HSGN-94 inhibits LTA biosynthesis via direct binding to PgcA and downregulation of PgsA. We further show that HSGN-94 reduces the MRSA load in skin infection (mouse) and decreases pro-inflammatory cytokines in MRSA-infected wounds. Collectively, HSGN-94 merits further consideration as a potential drug for staphylococcal infections.

Review of non-invasive detection of SARS-CoV-2 and other respiratory pathogens in exhaled breath condensate

In 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged to cause high viral infectivity and severe respiratory illness in humans (COVID-19). Worldwide, limited pandemic mitigation strategies, including lack of diagnostic test availability, resulted in COVID-19 overrunning health systems and spreading throughout the global population. Currently, proximal respiratory tract (PRT) specimens such as nasopharyngeal swabs are used to diagnose COVID-19 because of their relative ease of collection and applicability in large scale screening. However, localization of SARS-CoV-2 in the distal respiratory tract (DRT) is associated with more severe infection and symptoms. Exhaled breath condensate (EBC) is a sample matrix comprising aerosolized droplets originating from alveolar lining fluid that are further diluted in the DRT and then PRT and collected via condensation during tidal breathing. The COVID-19 pandemic has resulted in recent resurgence of interest in EBC collection as an alternative, non-invasive sampling method for the staging and accurate detection of SARS-CoV-2 infections. Herein, we review the potential utility of EBC collection for detection of SARS-CoV-2 and other respiratory infections. While much remains to be discovered in fundamental EBC physiology, pathogen-airway interactions, and optimal sampling protocols, EBC, combined with emerging detection methods, presents a promising non-invasive sample matrix for detection of SARS-CoV-2.

Development of nanoparticles derived from corn as mass producible bionanoparticles with anticancer activity

Recent studies showed that plant-derived nanoparticles (NPs) can be easily produced in high yields and have potential applications as therapeutic agents or delivery carriers for bioactive molecules. In this study, we selected corn as it is inexpensive to grow and mass-produced globally. Super sweet corn was homogenized in water to obtain corn juice, which was then centrifuged, filtered through a 0.45-μm-pore size syringe filter, and ultracentrifuged to obtain NPs derived from corn, or corn-derived NPs (cNPs). cNPs obtained were approximately 80 nm in diameter and negatively charged (- 17 mV). cNPs were taken up by various types of cells, including colon26 tumor cells and RAW264.7 macrophage-like cells, with selective reduction of the proliferation of colon26 cells. Moreover, cNPs induced tumor necrosis factor-α release from RAW264.7 cells. cNPs and RAW264.7 in combination significantly suppressed the proliferation of colon26/fluc cells. Daily intratumoral injections of cNPs significantly suppressed the growth of subcutaneous colon26 tumors in mice, with no significant body weight loss. These results indicate excellent anti-tumor activity of cNPs.

Immediate and sensitive detection of sporulated Bacillus subtilis by microwave release and tandem mass spectrometry of dipicolinic acid

Spore lysis of Bacillus species is achieved by brief (1 min) microwave irradiation while tandem mass spectrometry (MS/MS) allows identification of the characteristic spore marker, dipicolinic acid. This rapid measurement, made on 10⁵-10⁸ spores, has significant implications for biothreat recognition.

Multiple reaction monitoring profiling (MRM profiling): Small molecule exploratory analysis guided by chemical functionality

Small molecules, including metabolites and lipids, provide information on metabolic pathways and active biological processes in living organisms. They are often diagnostic of disease. Current exploratory methods for metabolomics and lipidomics mostly rely on separation using liquid or gas chromatography (LC or GC) coupled with mass spectrometers capable of acquiring high resolution data to generate an enormous data, but at the cost of lengthy processing and data acquisition. Even though many molecules can be identified and quantified by these methods, the laborious protocols for purification, identification, and validation limit the accessible sample chemical information. To improve the speed and efficiency of exploratory metabolomics and lipidomics, multiple reaction monitoring profiling (MRM profiling) has been developed. This strategy involves a three-stage workflow which starts by considering the metabolome as a collection of functional groups. The Discovery Stage interrogates a representative sample mixture for functional groups using the functional group specific precursor ion (Prec) scans and neutral loss (NL) scans. This experiment usually uses a triple quadrupole mass spectrometer without chromatography, i.e. by direct sample infusion. In the second Screening Stage, the main features seen in the Prec and NL scans are organized into lists of precursor ion/product ion transitions (MRMs) which are then used for the fast, specific, and sensitive interrogation of each individual sample. Data analysis by univariate and multivariate statistical methods is used to identify the most informative MRMs and so classify the individual samples. The compounds (biomarkers) which are responsible for the most informative MRMs in particular sample classes can be investigated in an optional third Identification Stage i.e. in a structural identification study. MRM profiling benefits from the much smaller number of functional groups compared to the number of individual metabolites existing in biological samples (where most metabolites are still unknown), resulting in acquisition of a much smaller data set and a shorter analysis time. The application of MRM Profiling to several biological and clinical problems is used to illustrate its features.

Multiple reaction monitoring profiling as an analytical strategy to investigate lipids in extracellular vesicles

Extracellular vesicles (EVs) convey information used in cell-to-cell interactions. Lipid analysis of EVs remains challenging because of small sample amounts available. Lipid discovery using traditional mass spectrometry platforms based on liquid chromatography and high mass resolution typically employs milligram sample amounts. We report a simple workflow for lipid profiling of EVs based on multiple reaction monitoring (MRM) profiling that uses microgram amounts of sample. After liquid-liquid extraction, individual EV samples were injected directly into the electrospray ionization (ESI) ion source at low flow rates (10 μl/min) and screened for 197 MRM transitions chosen to be a characteristic of several classes of lipids. This choice was based on a discovery experiment, which applied 1,419 MRMs associated with multiple lipid classes to a representative pooled sample. EVs isolated from 12 samples of human lymphocytes and 16 replicates from six different rat cells lines contained an estimated amount of total lipids of 326 to 805 μg. Samples showed profiles that included phosphatidylcholine (PC), sphingomyelin (SM), cholesteryl ester (CE), and ceramide (Cer) lipids, as well as acylcarnitines. The lipid profiles of human lymphocyte EVs were distinguishable using principal component and cluster analysis in terms of prior antibody and drug exposure. Lipid profiles of rat cell lines EV's were distinguishable by their tissue of origin.

Lipidomic Profiling of the Epidermis in a Mouse Model of Dermatitis Reveals Sexual Dimorphism and Changes in Lipid Composition before the Onset of Clinical Disease

Atopic dermatitis (AD) is a multifactorial disease associated with alterations in lipid composition and organization in the epidermis. Multiple variants of AD exist with different outcomes in response to therapies. The evaluation of disease progression and response to treatment are observational assessments with poor inter-observer agreement highlighting the need for molecular markers. SHARPIN-deficient mice (Sharpin^cpdm) spontaneously develop chronic proliferative dermatitis with features similar to AD in humans. To study the changes in the epidermal lipid-content during disease progression, we tested 72 epidermis samples from three groups (5-, 7-, and 10-weeks old) of cpdm mice and their WT littermates. An agnostic mass-spectrometry strategy for biomarker discovery termed multiple-reaction monitoring (MRM)-profiling was used to detect and monitor 1,030 lipid ions present in the epidermis samples. In order to select the most relevant ions, we utilized a two-tiered filter/wrapper feature-selection strategy. Lipid categories were compressed, and an elastic-net classifier was used to rank and identify the most predictive lipid categories for sex, phenotype, and disease stages of cpdm mice. The model accurately classified the samples based on phospholipids, cholesteryl esters, acylcarnitines, and sphingolipids, demonstrating that disease progression cannot be defined by one single lipid or lipid category.

Exacerbation of Nanoparticle-Induced Acute Pulmonary Inflammation in a Mouse Model of Metabolic Syndrome

Nanotechnology has the capacity to revolutionize numerous fields and processes, however, exposure-induced health effects are of concern. The majority of nanoparticle (NP) safety evaluations have been performed utilizing healthy models and have demonstrated the potential for pulmonary toxicity. A growing proportion of individuals suffer diseases that may enhance their susceptibility to exposures. Specifically, metabolic syndrome (MetS) is increasingly prevalent and is a risk factor for the development of chronic diseases including type-2 diabetes, cardiovascular disease, and cancer. MetS is a combination of conditions which includes dyslipidemia, obesity, hypertension, and insulin resistance. Due to the role of lipids in inflammatory signaling, we hypothesize that MetS-associated dyslipidemia may modulate NP-induced immune responses. To examine this hypothesis, mice were fed either a control diet or a high-fat western diet (HFWD) for 14-weeks. A subset of mice were treated with atorvastatin for the final 7-weeks to modulate lipids. Mice were exposed to silver NPs (AgNPs) via oropharyngeal aspiration and acute toxicity endpoints were evaluated 24-h post-exposure. Mice on the HFWD demonstrated MetS-associated alterations such as increased body weight and cholesterol compared to control-diet mice. Cytometry analysis of bronchoalveolar lavage fluid (BALF) demonstrated exacerbation of AgNP-induced neutrophilic influx in MetS mice compared to healthy. Additionally, enhanced proinflammatory mRNA expression and protein levels of monocyte chemoattractant protein-1, macrophage inflammatory protein-2, and interleukin-6 were observed in MetS mice compared to healthy following exposure. AgNP exposure reduced mRNA expression of enzymes involved in lipid metabolism, such as arachidonate 5-lipoxygenase and arachidonate 15-lipoxygenase in both mouse models. Exposure to AgNPs decreased inducible nitric oxide synthase gene expression in MetS mice. An exploratory lipidomic profiling approach was utilized to screen lipid mediators involved in pulmonary inflammation. This assessment indicates the potential for reduced levels of lipids mediators of inflammatory resolution (LMIR) in the MetS model compared to healthy mice following AgNP exposure. Statin treatment inhibited enhanced inflammatory responses as well as alterations in LMIR observed in the MetS model due to AgNP exposure. Taken together our data suggests that MetS exacerbates the acute toxicity induced by AgNPs exposure possibly via a disruption of LMIR leading to enhanced pulmonary inflammation.

Discrimination of antibiotic-resistant Gram-negative bacteria with a novel 3D nano sensing array

Triple optical response of a nano-composite facilitates discrimination of antibiotic-resistant Gram-negative bacteria from normal ones based on a sensing array technique.

Adaption of the Aristotle Classifier for Accurately Identifying Highly Similar Bacteria Analyzed by MALDI-TOF MS

MALDI-TOF MS has shown great utility for rapidly identifying microbial species. It can be used to successfully type bacteria and fungi from a variety of sources more rapidly and cost-effectively than traditional methods. One area where improvements are necessary is in the typing of highly similar samples, such as those samples from the same genus but different species or samples from within a single species but from different strains. One promising way to address this current limitation is by using advanced machine learning techniques. In this work, we adapt a newly developed machine learning tool, the Aristotle Classifier, to bacterial classification of MALDI-TOF MS data. This tool was originally developed for classifying glycomics and glycoproteomics data, so we modified it to be well-suited for assigning mass spectral data from bacterial proteins. The classifier exceeds existing benchmarks in classifying bacteria, and it shows particularly strong performance when the samples to be identified are highly similar. The combination of mass spectrometry data and tools like the Aristotle Classifier could ameliorate the ambiguities associated with challenging bacterial classification problems.