Compounds In Biofluids Research Articles

Multiresolution functional characterization and correction of biofouling for improved biosensing efficacy

Multielectrode electrochemical biosensors promise on-the-spot inspection of target compounds in biofluids, reducing costs in personalized healthcare. However, sensor sensitivity may decrease after each use due to biofouling, where chemical attachments on sensor electrodes curtail sensing signals. Current biofouling characterization techniques rely on time-consuming offline tests and analysis, making them impractical for on-the-spot signal correction. Alternatively, we propose to statistically model and correct the biofouling-induced signal changes. However, in addition to biofouling, the signals are influenced by multiple sources of variation, each with different levels of impact. To effectively characterize and separate biofouling effects from the major sources of variability, we establish a multiresolution functional mixed-effect model based on domain knowledge. A biosensing signal is first decomposed into a smooth trend and local peaks. The smooth trend models the effects of population-level biofluid composition, as well as patient and electrode effects to isolate variability sources. Changes in local peak location and amplitude indicate biofouling. These local peaks are modeled using a sparse subset of high-order functional terms. By modeling the changes of those high-order terms, we can characterize and predict the biofouling between consecutive measurements. We propose a sequential parameter estimation procedure that ensures model identifiability. A nonparametric regression model is developed for biofouling prediction. The proposed strategy is validated through simulation and real case studies, effectively correcting biofouling-affected signals from new patients.

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.

Personalized Metabolic Profile by Synergic Use of NMR and HRMS.

A new strategy that takes advantage of the synergism between NMR and UHPLC–HRMS yields accurate concentrations of a high number of compounds in biofluids to delineate a personalized metabolic profile (SYNHMET). Metabolite identification and quantification by this method result in a higher accuracy compared to the use of the two techniques separately, even in urine, one of the most challenging biofluids to characterize due to its complexity and variability. We quantified a total of 165 metabolites in the urine of healthy subjects, patients with chronic cystitis, and patients with bladder cancer, with a minimum number of missing values. This result was achieved without the use of analytical standards and calibration curves. A patient’s personalized profile can be mapped out from the final dataset’s concentrations by comparing them with known normal ranges. This detailed picture has potential applications in clinical practice to monitor a patient’s health status and disease progression.

Setup of a Serotonin 2A Receptor (5-HT2AR) Bioassay: Demonstration of Its Applicability To Functionally Characterize Hallucinogenic New Psychoactive Substances and an Explanation Why 5-HT2AR Bioassays Are Not Suited for Universal Activity-Based Screening of Biofluids for New Psychoactive Substances.

Classic or serotonergic hallucinogens comprise the third largest number of reported new psychoactive substances (NPS), according to the United Nations Office on Drugs and Crime. While being structurally very divergent, they share activation of the serotonin 2A receptor (5-HT2AR), a G protein-coupled receptor, as their main pharmacological mechanism. Here, we report on the development of a 5-HT2AR bioassay, which monitors β-arrestin2 recruitment to the receptor via a split-luciferase system, as a measure of receptor activation. Possible applications of the bioassay would lie in the characterization of serotonergic hallucinogens and the screening of these compounds in biofluids based on their serotonergic activity, rather than on their specific structures. The developed bioassay allowed the determination of the potency and efficacy of representatives of different classes of hallucinogens (LSD, 5-MeO-DALT, mescaline) and of a selected group of 2C hallucinogens and their corresponding NBOMes, with EC50 values from the subnanomolar (NBOMes) to micromolar (mescaline) range. When implementing the bioassay for the screening of plasma, a pronounced receptor activation was already observed in blank samples, which could be ascribed to endogenous serotonin, as suggested by annihilation of this activity by a 5-HT2AR antagonist or after incubation with MAO-A (monoamine oxidase-A). The presence and degradability by MAO-A of serotonin in plasma extracts were confirmed by LC-HRMS. Due to the possible metabolism of certain hallucinogens by MAO-A, which would cause a bias in the detectability of compounds in biofluids, the main application potential of this bioassay lies in the characterization of these scarcely characterized serotonergic hallucinogens.

Volatile organic compounds of biofluids for detecting lung cancer by an electronic nose based on artificial neural network.

Lung cancer (LC) incidence represents 11.5% of all new cancers, resulting in 1.72 million deaths worldwide in 2015. With the aim to investigate the capability of the electronic nose (e-nose) technology for detecting and differentiating complex mixtures of volatile organic compounds in biofluids ex-vivo, we enrolled 50 patients with suspected LC and 50 matching controls. Tissue biopsy was taken from suspicious lung mass for histopathological evaluation and blood, exhaled breath, and urine samples were collected from all participants and qualitatively processed using e-nose. Odor-print patterns were further analysed using the principal component analysis (PCA) and artificial neural network (ANN) analysis. Adenocarcinoma, non-small cell LC and squamous cell carcinoma were the predominant pathological types among LC patients. PCA cluster-plots showed a clear distinction between LC patients and controls for all biological samples; where the overall success ratios of classification for principal components #1 and #2 were: 95.46, 82.01, and 91.66% for blood, breath and urine samples, respectively. Moreover, ANN showed a better discrimination between LC patients and controls with success ratios of 95.74, 91.67 and 100% for blood, breath and urine samples, respectively. The e-nose is an easy noninvasive tool, capable of identifying LC patients from controls with great precision.

In-capillary microextraction for direct mass spectrometry analysis of biological samples

Slug flow microextraction (SFME)-nanoESI was originally explored as a single-step sampling ionization method for MS analysis of biofluids. In this work, a comprehensive study and development of the SFME has been carried out. Revers-phase SFME was developed to analyze chemical compounds in oil samples. A three-phase SFME system was introduced as a suitable approach for analyzing polar compounds in biofluids. The impacts by the capillary inner diameter, solvent and sample properties were also investigated, leading the use of fused silica capillaries for performing SFME.

Recent Progress in Wearable Fully Textile Chemical Sensors

AbstractIn the new era of Internet of Things, there is a great demand for the development of novel chemical wearable sensors, in particular, for personalized medical diagnostics with point‐of‐care devices. This paper provides an overview on the recent developments in this field, focusing on fully textile chemical sensors, i.e., sensors directly incorporated into a garment/fabric/fiber. The recent results are summarized by grouping them in three broad categories according to their working principle: (i) electrochemical sensors; (ii) transistor‐based sensors; and (iii) resistance‐based sensors. Wearable chemical sensors can be used to detect external dangerous vapor/agents, or to control and monitor the concentration of specific compounds in biofluids for safety and healthcare applications. One of the main issues of such applications is sensor operation in a complex medium containing many interfering compounds. To this end, recent novel approaches to enhance the selectivity of fully textile wearable sensors are reviewed: enzyme‐based approach, selective membrane, and a potentiodynamic method. Finally, a critical overview is given about the major open issues that have to be overcome in order to reach a high technology readiness level.

High-Throughput Screening and Quantitation of Target Compounds in Biofluids by Coated Blade Spray-Mass Spectrometry.

Most contemporary methods of screening and quantitating controlled substances and therapeutic drugs in biofluids typically require laborious, time-consuming, and expensive analytical workflows. In recent years, our group has worked toward developing microextraction (μe)-mass spectrometry (MS) technologies that merge all of the tedious steps of the classical methods into a simple, efficient, and low-cost methodology. Unquestionably, the automation of these technologies allows for faster sample throughput, greater reproducibility, and radically reduced analysis times. Coated blade spray (CBS) is a μe technology engineered for extracting/enriching analytes of interest in complex matrices, and it can be directly coupled with MS instruments to achieve efficient screening and quantitative analysis. In this study, we introduced CBS as a technology that can be arranged to perform either rapid diagnostics (single vial) or the high-throughput (96-well plate) analysis of biofluids. Furthermore, we demonstrate that performing 96-CBS extractions at the same time allows the total analysis time to be reduced to less than 55 s per sample. Aiming to validate the versatility of CBS, substances comprising a broad range of molecular weights, moieties, protein binding, and polarities were selected. Thus, the high-throughput (HT)-CBS technology was used for the concomitant quantitation of 18 compounds (mixture of anabolics, β-2 agonists, diuretics, stimulants, narcotics, and β-blockers) spiked in human urine and plasma samples. Excellent precision (∼2.5%), accuracy (≥90%), and linearity (R2 ≥ 0.99) were attained for all the studied compounds, and the limits of quantitation (LOQs) were within the range of 0.1 to 10 ng·mL-1 for plasma and 0.25 to 10 ng·mL-1 for urine. The results reported in this paper confirm CBS's great potential for achieving subsixty-second analyses of target compounds in a broad range of fields such as those related to clinical diagnosis, food, the environment, and forensics.

Foodomics Application: Analysis of Dietary Components of the DASH Diet Pre and Post Consumption

Background/ObjectiveWhile the benefit of improving the diet through the intake of different food groups such as fruits and vegetables is well established, many nutrient specific intervention studies have failed to demonstrate the effectiveness of specific foods in preventing or altering disease progression. This may be due to exposome and microbiome variations between individuals, and the lack of dependable biomarkers relating non‐nutritive dietary compounds to health benefits. Additionally, robust analysis techniques have not been implemented to identify the vast multitude of compounds in foods and to elucidate their health‐related fate. Foodomics attempts to fill these research challenges through the analysis of individual foods and their resulting metabolic signatures following intake. We hypothesized that individual foods will produce unique identifiable molecular compounds in biofluids, which will provide signatures of intake and lead to the identification of bioactive compounds that may impact health.MethodsIn a clinical cross‐over feeding study using the Dietary Approaches to Stop Hypertension (DASH) diet, participants were randomized to consume a 7‐day rotational controlled diet in which the primary source of protein was either pork or white meat (chicken and fish) for six weeks, followed by a washout for four weeks, and then consumption of the alternate meat source diet for six weeks. To interrogate diet samples for foodomics analysis, lypholization and methanol extraction were conducted on 14 composite daily diets and 12 selected individual foods. Untargeted metabolomic analysis was conducted on the extracted food samples and archived urine samples of 10 study participants, pre‐ and post‐diet intervention, using liquid chromatography mass spectrometry (LC/MS) with a SB‐AQ column in positive ion mode.ResultsA total of 10948 unique metabolites were detected in the individual foods, ranging from 833 compounds detected in tilapia and 1998 compounds detected in cucumbers, with over 4000 compounds detected in the composite diets. Each food produced unique metabolites; for example, caffeic acid, a cardioprotectant, was found only in blueberries, and specific acylcarnitines were protein source dependent. Metabolite signatures of each individual food and the composite diets were also detectable in the urine. Comparison of pre‐ and post‐diet urine metabolites revealed changes in the abundance of 74 and 183 metabolites from the white meat and pork diets, respectively, with 13 metabolites that correlated with observed reductions in blood pressure in the study participants.ConclusionThis novel foodomics analysis demonstrated that LC/MS analysis of individual foods and composite diets produced unique metabolite signatures detectable in urine. Those metabolites may lead to biomarkers that not only indicate consumption, but may also help elucidate the role of individual foods in the exposome and health outcomes, including changes in blood pressure.Support or Funding InformationFunding provided by discretionary funding from the Krebs & Reisdorph Labs, NIH/NCATS Colorado CTSA Grant UL1 TR001082, & Pork Checkoff Funds

Black phosphorus-assisted laser desorption ionization mass spectrometry for the determination of low-molecular-weight compounds in biofluids.

Quantitative analysis of small molecules by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been a challenging task due to matrix-derived interferences in low m/z region and poor reproducibility of MS signal response. In this study, we developed an approach by applying black phosphorus (BP) as a matrix-assisted laser desorption ionization (MALDI) matrix for the quantitative analysis of small molecules for the first time. Black phosphorus-assisted laser desorption/ionization mass spectrometry (BP/ALDI-MS) showed clear background and exhibited superior detection sensitivity toward quaternary ammonium compounds compared to carbon-based materials. By combining stable isotope labeling (SIL) strategy with BP/ALDI-MS (SIL-BP/ALDI-MS), a variety of analytes labeled with quaternary ammonium group were sensitively detected. Moreover, the isotope-labeled forms of analytes also served as internal standards, which broadened the analyte coverage of BP/ALDI-MS and improved the reproducibility of MS signals. Based on these advantages, a reliable method for quantitative analysis of aldehydes from complex biological samples (saliva, urine, and serum) was successfully established. Good linearities were obtained for five aldehydes in the range of 0.1-20.0μM with correlation coefficients (R (2)) larger than 0.9928. The LODs were found to be 20 to 100nM. Reproducibility of the method was obtained with intra-day and inter-day relative standard deviations (RSDs) less than 10.4%, and the recoveries in saliva samples ranged from 91.4 to 117.1%. Taken together, the proposed SIL-BP/ALDI-MS strategy has proved to be a reliable tool for quantitative analysis of aldehydes from complex samples. Graphical Abstract An approach for the determination of small molecules was developed by using black phosphorus (BP) as a matrix-assisted laser desorption ionization (MALDI) matrix.

Metabolic phenotype of rats exposed to heroin and potential markers of heroin abuse

BackgroundMetabolomics allows the high-throughput analysis of low molecular mass compounds in biofluids, which can reflect the metabolic response of the body to heroin exposure and potentially reveal biomarkers of heroin abuse. MethodsHeroin was administered to Sprague-Dawley rats in increasing doses from 3 to 16.5mgkg−1d−1 (i.p.) for 10 days, then withdrawn and re-administered for 4 days. The analytes in serum and urine were profiled using gas chromatography–mass spectrometry, and metabolic patterns were evaluated based on the metabolomics data. ResultsBoth the administration and withdrawal of heroin resulted in aberrant behaviour in the rats; however, the rats gradually became adapted to heroin. Metabolomics data showed that heroin administration caused deviations in the metabolic patterns, whereas heroin withdrawal restored the metabolic patterns towards baseline. Re-administration of heroin caused the metabolic patterns to deviate again. Analysis of the metabolites revealed that heroin induced an acceleration of the tricarboxylic acid cycle and the metabolism of free fatty acids that may contribute to the reduction in observed body weight in the heroin group. Heroin administration decreased tryptophan and 5-hydroxytryptamine levels in peripheral serum but increased urinary tryptophan and 5-hydroxyindoleacetate. Withdrawal of heroin for 4 days efficiently restored all metabolites to baseline, except serum myo-inositol-1-phosphate, threonate, and hydroxyproline in the urine. ConclusionsHeroin administration significantly perturbed metabolic pathways, elevated energy metabolism, whereas heroin withdrawal restored all but a few metabolites to baseline. These peripheral metabolites were indicated as the surrogates characterising the metabolic effect of heroin on central nervous system function.

Gas chromatography time-of-flight mass spectrometry based metabolomic approach to evaluating toxicity of triptolide

Metabolomics allows high-throughput analysis of low-molecular-weight compounds in biofluids that reflect the physiological status and biochemical metabolism of living systems. Hence it has the potential to evaluate toxicity and clarifies the metabolism-related toxic mechanisms. In this study a promising candidate drug parent, triptolide, was given to Sprague–Dawley rats as a model toxicant at a single dose of 0.6, or 2.4 mg/kg, i.g. Both routine biochemical assays and histopathological inspection showed time-dependent hepatic toxicity at the higher dose, but no obvious toxicity at the lower dose. Meanwhile, serum metabolome was profiled using the non-targeted metabolomic tool, gas chromatography time-of-flight mass spectrometry. Based on the acquired metabolomic data, mathematical models were calculated and the metabolic patterns of serum were evaluated using projection to latent structure-discriminant analysis. The relative distance of each treated group from the normal control was calculated to provide a measure of toxicity. Treatment with triptolide at either the higher or lower dose caused deviations in the metabolic pattern and resulted in perturbation of taurine, creatinine, free fatty acids, β-hydroxybutyrate, tricarboxylic acid cycle intermediates, and amino acids. This finding indicates the dysfunction of β-oxidation of free fatty acids and impairment of the mitochondria and confirms the hepatic toxicity of triptolide. The identified toxic markers and the calculated relative distance values quantitatively demonstrated dose- and time-dependent toxicity, whereas the scores plot of the model provided the qualitative information. The metabolomic approach was non-invasive and more sensitive than routine toxic assessment, and the results of both methods correlated well.

Simultaneous measurement of three N-acylethanolamides in human bio-matrices using ultra performance liquid chromatography-tandem mass spectrometry

Endocannabinoids including N-acylethanolamides (NAEs) are a family of lipid-related signaling molecules implicated in many physiological and disease states which elicit their activities via the cannabinoid receptors. Anandamide (N-arachidonoylethanolamine, AEA) is the most characterized endocannabinoid and has been detected in many tissues and bio-fluids including human plasma and the central nervous system. The endocannabinoid-like NAEs, oleoylethanolamide (OEA) and palmitoylethanolamide (PEA) are described as entourage compounds because they illicit similar physiological effects to AEA but have little or no affinity for cannabinoid receptors. As entourage compounds, levels of these NAEs can greatly influence the efficacy of AEA yet there are few studies which measure these compounds in bio-fluids. Here we describe a rapid, highly sensitive, specific and highly reproducible ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for the analysis of AEA, OEA, and PEA in human bio-fluids including plasma, serum, breast milk, and amniotic fluids. This validated method using deuterated (AEA-d(8), OEA-d(2), and PEA-d(4)) internal standards, represents an improvement over previous analyses in terms of run time (4 min), limit of detection (0.9 fmol on column for AEA and PEA and 4.4 fmol on column for OEA), precision (relative standard deviations of peak areas: 3.1% (AEA), 2.9% (OEA), and 5.4% (PEA) for 133 fmol on column) and accuracy (95.1-104.9%). The sensitivity and precision of the validated method described here suggests that this method is suitable for the analysis of AEA, OEA, and PEA in clinical samples and may be utilized for the investigation of bio-matrices containing limited amounts of NAEs.

On-line Coupling of Three-Dimensional Liq- uid Chromatography Based Sample Prepar- ation with Reversed-Phase Liquid Chromato- graphy for the Determination of Enkephalin Derivatives as Model Compounds in Biofluids

In bioanalysis sample preparation frequently is the most time consuming and laborious step. As a result, automated and/or on-line sample preparation techniques are preferred. Here, an automated 3D-sample preparation procedure is described for the determination of enkephalin derivatives in spiked human plasma. The sample preparation procedure consists of an initial treatment based on the exclusion principle. The required selectivity is obtained in a subsequent step by combining a strong cation-exchanger with a reversed-phase column. Detection is performed by using UV absorbance at 200 nm or by using electrospray-ionization mass spectrometry. Human plasma samples, which are only five-fold diluted and acidified to 5% v/v acetic acid, can be injected into the system without any problems. As a result, off-line manual labor-intensive sample preparation steps, which generally form the bottleneck in bioanalysis, are reduced to a less than a one-minute liquid-handling process. The developed 3D-sample preparation RP–LC procedure shows good repeatability in the retention time (<0.5% RSD) and peak area response (<1.3% RSD) for the determination of enkephalin derivatives in spiked human plasma samples. Limits of detection of the procedure were 200 nmol·L−1 using UV detection and 10 nmol·L−1 using mass spectrometric detection.