Identification and validation of small molecule analytes in mouse plasma by liquid chromatography-tandem mass spectrometry: A case study of misidentification of a short-chain fatty acid with a ketone body.

Recently, there has been growing interest in short-chain fatty acids (SCFA) and ketone bodies (KB) due to their potential use as biomarkers of health and disease. For instance, these diet-related metabolites can be used to monitor and reduce the risk of immune response, diabetes, or cardiovascular diseases. Given the interest in these metabolites, different targeted metabolomic methods based on UPLC-MS/MS have been developed in recent years to detect and quantify SCFA and KB. In this case study, we discovered that applying an existing validated, targeted UPLC-MS/MS method to mouse plasma, resulted in a fragment ion (194 m/z) being originally misidentified as acetic acid (a SCFA), when its original source was 3-hydroxybutyric acid (a KB). Therefore, we report a modified, optimized LC method that can separate both signals. In addition, the metabolite coverage was expanded in this method to detect up to eight SCFA: acetic, propanoic, butyric, isobutyric, 2-methylbutyric, valeric, isovaleric, and hexanoic acids, two KB: 3-hydroxybutyric, and acetoacetic acids, and one related metabolite: 3-hydroxy-3-methylbutyric acid. The optimization of this method increased the selectivity of the UPLC-MS/MS method towards the misidentified compound. These findings encourage the scientific community to increase efforts in validating the original precursor of small molecule fragments in targeted methods.

A role for PchHI as the ABC transporter in iron acquisition by the siderophore pyochelin in Pseudomonas aeruginosa.

Iron is an essential nutrient for bacterial growth but poorly bioavailable. Bacteria scavenge ferric iron by synthesizing and secreting siderophores, small compounds with a high affinity for iron. Pyochelin (PCH) is one of the two siderophores produced by the opportunistic pathogen Pseudomonas aeruginosa. After capturing a ferric iron molecule, PCH-Fe is imported back into bacteria first by the outer membrane transporter FptA and then by the inner membrane permease FptX. Here, using molecular biology, 55 Fe uptake assays, and LC-MS/MS quantification, we first find a role for PchHI as the heterodimeric ABC transporter involved in the siderophore-free iron uptake into the bacterial cytoplasm. We also provide the first evidence that PCH is able to reach the bacterial periplasm and cytoplasm when both FptA and FptX are expressed. Finally, we detected an interaction between PchH and FptX, linking the ABC transporter PchHI with the inner permease FptX in the PCH-Fe uptake pathway. These results pave the way for a better understanding of the PCH siderophore pathway, giving future directions to tackle P. aeruginosa infections.

Lipid Metabolite Biomarkers in Cardiovascular Disease: Discovery and Biomechanism Translation from Human Studies.

Lipids represent a valuable target for metabolomic studies since altered lipid metabolism is known to drive the pathological changes in cardiovascular disease (CVD). Metabolomic technologies give us the ability to measure thousands of metabolites providing us with a metabolic fingerprint of individual patients. Metabolomic studies in humans have supported previous findings into the pathomechanisms of CVD, namely atherosclerosis, apoptosis, inflammation, oxidative stress, and insulin resistance. The most widely studied classes of lipid metabolite biomarkers in CVD are phospholipids, sphingolipids/ceramides, glycolipids, cholesterol esters, fatty acids, and acylcarnitines. Technological advancements have enabled novel strategies to discover individual biomarkers or panels that may aid in the diagnosis and prognosis of CVD, with sphingolipids/ceramides as the most promising class of biomarkers thus far. In this review, application of metabolomic profiling for biomarker discovery to aid in the diagnosis and prognosis of CVD as well as metabolic abnormalities in CVD will be discussed with particular emphasis on lipid metabolites.

A hydrogel-based in vitro assay for the fast prediction of antibiotic accumulation in Gram-negative bacteria.

The pipeline of antibiotics has been for decades on an alarmingly low level. Considering the steadily emerging antibiotic resistance, novel tools are needed for early and easy identification of effective anti-infective compounds. In Gram-negative bacteria, the uptake of anti-infectives is especially limited. We here present a surprisingly simple in vitro model of the Gram-negative bacterial envelope, based on 20% (w/v) potato starch gel, printed on polycarbonate 96-well filter membranes. Rapid permeability measurements across this polysaccharide hydrogel allowed to correctly predict either high or low accumulation for all 16 tested anti-infectives in living Escherichia coli. Freeze-fracture TEM supports that the macromolecular network structure of the starch hydrogel may represent a useful surrogate of the Gram-negative bacterial envelope. A random forest analysis of in vitro data revealed molecular mass, minimum projection area, and rigidity as the most critical physicochemical parameters for hydrogel permeability, in agreement with reported structural features needed for uptake into Gram-negative bacteria. Correlating our dataset of 27 antibiotics from different structural classes to reported MIC values of nine clinically relevant pathogens allowed to distinguish active from nonactive compounds based on their low in vitro permeability specifically for Gram-negatives. The model may help to identify poorly permeable antimicrobial candidates before testing them on living bacteria.

Subcellular Quantification of Uptake in Gram-Negative Bacteria.

Infections by Gram-negative pathogens represent a major health care issue of growing concern due to a striking lack of novel antibacterial agents over the course of the last decades. The main scientific problem behind the rational optimization of novel antibiotics is our limited understanding of small molecule translocation into, and their export from, the target compartments of Gram-negative species. To address this issue, a versatile, label-free assay to determine the intracellular localization and concentration of a given compound has been developed for Escherichia coli and its efflux-impaired ΔTolC mutant. The assay applies a fractionation procedure to antibiotic-treated bacterial cells to obtain periplasm, cytoplasm, and membrane fractions of high purity, as demonstrated by Western Blots of compartment-specific marker proteins. This is followed by an LC-MS/MS-based quantification of antibiotic content in each compartment. Antibiotic amounts could be converted to antibiotic concentrations by assuming that an E. coli cell is a cylinder flanked by two half spheres and calculating the volumes of bacterial compartments. The quantification of antibiotics from different classes, namely ciprofloxacin, tetracycline, trimethoprim, and erythromycin, demonstrated pronounced differences in uptake quantities and distribution patterns across the compartments. For example, in the case of ciprofloxacin, a higher amount of compound was located in the cytoplasm than in the periplasm (592 ± 50 pg vs 277 ± 13 pg per 3.9 × 109 cells), but owing to the smaller volume of the periplasmic compartment, its concentration in the cytoplasm was much lower (37 ± 3 vs 221 ± 10 pg/µL for the periplasm). For erythromycin and tetracycline, differences in MICs between WT and ΔTolC mutant strains were not reflected by equal differences in uptake, illustrating that additional experimental data are needed to predict antibiotic efficacy. We believe that our assay, providing the antibiotic concentration at the compartment in which the drug target is expressed, constitutes an essential piece of information for a more rational optimization of novel antibiotics against Gram-negative infections.