Novel technologies for metabolomics: More for less

The human metabolome provides a direct physiological read-out of an individual's actual health state and includes biomarkers that may predict disease or response to a treatment. The discovery and validation of these metabolomic biomarkers requires large-scale cohort studies, typically involving thousands of samples. This analytical challenge drives novel technological developments to enable faster, cheaper, and more comprehensive metabolomic analysis: more for less.This review summarises recent (2012–2018) developments towards this goal in all aspects of the analytical workflow, in relation to NMR but primarily to mass spectrometry (MS). Recent trends include miniaturisation and automation of extraction techniques, online coupling to fast analysis methods including direct infusion ion mobility MS, integrated microfluidic devices, and sharing and standardizing metabolomics software and data.The technological advances in metabolomics support its widespread application, integration with other -omics fields, and ultimately disease prediction and precision medicine.Pharmacolog

A high-throughput, ultrafast, and online three-phase electro-extraction method for analysis of trace level pharmaceuticals

Sample preparation is often reported as the main bottleneck of analytical processes. To meet the requirements of both high-throughput and high sensitivity, improved sample-preparation methods capable of fast analyte preconcentration are urgently needed. To this end, a new three-phase electroextraction (EE) method is presented that allows for ultrafast electroextraction hyphenated to flow-injection analysis mass spectrometry (FIA-MS). Four model compounds, i.e., propranolol, amitriptyline, bupivacaine, and oxeladin, were used to optimize and evaluate the method. Within only 30 s extraction time, enrichment factors (EF) of 105-569 and extraction recoveries (ER) of 10.2%-55.7% were achieved for these analytes, with limits of detection (LODs) ranging from 0.36 to 3.21 ng mL(-1), good linear response function (R-2 > 0.99), low relative standard deviation (0.6%-17.8%) and acceptable accuracy (73-112%). Finally, the optimized three-phase EE method was successfully applied to human urine and plasma samples. Our three-phase electroextraction method is simple to construct and offers ultrafast, online extraction of trace amounts of analytes from biological samples, and therefore has great potential for high-throughput analysis. (C) 2021 The Authors. Published by Elsevier B.V.Analytical BioScience

De kwaliteit van de therapeutische relatie voorspelt uitkomst van psychotherapie bij depressie

Om een optimale afname in depressieve symptomen te bewerkstelligen is een goede therapeutische relatie van belang. Er wordt verwacht dat het vroeg meten van de kwaliteit van deze relatie tijdens behandeling de behandeluitkomst krachtiger kan voorspellen. Ook wordt verwacht dat waargenomen therapeutkenmerken gerelateerd zijn aan hoe de patiënt de therapeutische relatie waardeert. Matig tot ernstig depressieve patiënten werden volgens een toevalsprocedure toegewezen aan cognitieve gedragstherapie (cgt) of kortdurende psychoanalytische steungevende psychotherapie (kpsp). Meetmomenten waren er bij baseline, week 1, 2, 4 en 8 om de waargenomen betrouwbaarheid, expertise en attrac­tivi­teit van de therapeut, de kwaliteit van de therapeutische relatie en depressieve klachten te monitoren. De therapeutische relatie hangt vanaf de eerste week matig sterk samen met depressieve klachten later in behandeling (r’s -0,28 tot -0,42, p’s < 0,01). De voorspellende waarde is het grootst na twee weken (vier sessies). Ook is de kwaliteit van de vroege therapeutische relatie sterk voorspellend voor de therapeutische relatie later. Symptoomverandering in de eerste twee sessies van de behandeling is niet voorspellend voor de kwaliteit van de therapeutische relatie na twee sessies. Ten slotte wordt een matige tot sterke relatie gezien tussen waargenomen therapeutkenmerken bij aanvang en de therapeutische relatie. Het in een vroeg stadium monitoren en optimaliseren van de therapeutische relatie tijdens behandeling lijkt van belang voor sterkere symptoomreductie. Een afkapscore van de therapeutische relatie, het beste na twee weken, zou mogelijk antwoord kunnen geven op de vraag of de kwaliteit voldoende dan wel onvoldoende is. Aanbevolen wordt om waargenomen therapeutkenmerken mee te nemen in toekomstige analyses om meer te begrijpen van de invloed van de therapeutische relatie op symptoomverandering. Dit zou eventueel nog eerder in de behandeling interveniëren mogelijk maken

Automated segmented-flow analysis: NMR with a novel fluoropolymer flow cell for high-throughput screening

High-throughput analysis in fields such as industrial biotechnology, combinatorial chemistry, and life sciences is becoming increasingly important. Nuclear magnetic resonance (NMR) spectroscopy is a powerful technique providing exhaustive molecular information on complex samples. Flow NMR in particular is a cost and time-efficient method for large screenings. In this study, we have developed a novel 3.0 mm inner diameter polychlorotrifluoroethylene (PCTFE) flow cell for a segmented-flow analysis (SFA) - NMR automated platform. The platform uses FC-72 fluorinated oil and fluoropolymer components to achieve a fully fluorinated flow path. Samples were repeatably transferred from 96-deepwell plates to the flow cell by displacing a fixed volume of oil, with a transfer time of 42 s. 1H spectra were acquired fully automated with 500 and 600 MHz NMR spectrometers. The spectral performance of the novel PCTFE cell was equal to that of commercial glass cells. Peak area repeatability was excellent with a relative standard deviation of 0.1-0.5% for standard samples, and carryover was below 0.2% without intermediate washing. The sample temperature was conditioned by using a thermostated transfer line in order to reduce the equilibration time in the probe and increase the throughput. Finally, analysis of urine samples demonstrated the applicability of this platform for screening complex matrices.Analytical BioScience

Towards a comprehensive characterisation of the human internal chemical exposome: Challenges and perspectives

The holistic characterisation of the human internal chemical exposome using high-resolution mass spectrometry (HRMS) would be a step forward to investigate the environmental AE tiology of chronic diseases with an unprecedented precision. HRMS-based methods are currently operational to reproducibly profile thousands of endogenous metabolites as well as externally-derived chemicals and their biotransformation products in a large number of biological samples from human cohorts. These approaches provide a solid ground for the discovery of unrecognised biomarkers of exposure and metabolic effects associated with many chronic diseases. Nevertheless, some limitations remain and have to be overcome so that chemical exposomics can provide unbiased detection of chemical exposures affecting disease susceptibility in epidemiological studies. Some of these limitations include (i) the lack of versatility of analytical techniques to capture the wide diversity of chemicals; (ii) the lack of analytical sensitivity that prevents the detection of exogenous (and endogenous) chemicals occurring at (ultra) trace levels from restricted sample amounts, and (iii) the lack of automation of the annotation/identification process. In this article, we discuss a number of technological and methodological limitations hindering applications of HRMS-based methods and propose initial steps to push towards a more comprehensive characterisation of the internal chemical exposome. We also discuss other challenges including the need for harmonisation and the difficulty inherent in assessing the dynamic nature of the internal chemical exposome, as well as the need for establishing a strong international collaboration, high level networking, and sustainable research infrastructure. A great amount of research, technological development and innovative bio-informatics tools are still needed to profile and characterise the "invisible" (not profiled), "hidden" (not detected) and "dark" (not annotated) components of the internal chemical exposome and concerted efforts across numerous research fields are paramount

Development of a fast, online three-phase electroextraction hyphenated to fast liquid chromatography-mass spectrometry for analysis of trace-level acid pharmaceuticals in plasma

Sample preparation is a challenge for high-throughput analysis, especially for volume-limited samples with low-abundant analytes. Ideally, sample preparation enriches the analytes of interest while removing the interferents to reduce the matrix effect and improve both sensitivity and quantification. In this study, a three-phase electroextraction (EE) method hyphenated to fast online liquid chromatography -mass spectrometry (LC-MS) was developed. Four model acidic drugs of relevance for drug monitoring in plasma, i.e. naproxen, fenoprofen, flurbiprofen, and ibuprofen, were utilized for the optimization and evaluation of the method. A Design of Experiment approach (Box-Behnken design) was used to optimize the critical parameters of the method, i.e., the type of organic solvent, pH of the sample and acceptor phase, and the extraction voltage and time. Good fitness (P 0.95) was observed for the developed quadratic model. Extraction could be achieved in less than 2 min (115 s) with enrichment factors (EF) up to 190 and extraction recoveries (ER) up to 38% for academic samples. Additionally, the optimized three-phase EE method was successfully applied to spiked plasma samples with lowabundant (50 ng mL-1) analytes and a low sample volume of 15 mL plasma in 10-fold diluted samples. Finally, two crucial contributors to the matrix effect of three-phase EE application on plasma samples were determined. Specifically, the ion-suppression effect in the MS source was reduced by the fast LC separation, and the matrix effect during extraction was negligible for the diluted protein-precipitated plasma samples. The developed three-phase EE method is easy to operate and provides fast and online extraction of trace-level acidic analytes from volume-limited biological samples. Therefore, this method can provide a potential solution for sample-preparation bottlenecks in high-throughput bioanalysis workflows. (c) 2021 Published by Elsevier B.V.Analytical BioScience

An automated online three-phase electro-extraction setup with machine-vision process monitoring hyphenated to LC-MS analysis

Sample preparation is a labor-intensive and time-consuming procedure, especially for the bioanalysis of small-volume samples with low-abundant analytes. To minimize losses and dilution, sample preparation should ideally be hyphenated to downstream on-line analysis such as liquid chromatography-mass spectrometry (LC-MS). In this study, an automated three-phase electro-extraction (EE) method coupled to machine vision was developed, integrated with a robotic autosampler hyphenated to LC-MS. Eight model compounds, i.e. amitriptyline, clemastine, clomipramine, haloperidol, loperamide, propranolol, oxeladin, and verapamil were utilized for the optimization and evaluation of the automated EE setup. The stability of automated EE was evaluated by monitoring the acceptor droplet size by machine vision and recording the current during EE. A Design of Experiment approach (Box-Behnken design) was utilized to optimize the critical parameters of the EE method, i. e., the ratio of formic acid in the sample to acceptor phase, extraction voltage, and extraction time. The developed quadratic models showed good fitness (p 0.95). Automated EE could be achieved in less than 2 min with enrichment factors (EF) up to 387 and extraction recoveries (ER) up to 97% for academic samples. Finally, the optimized EE method was successfully applied to both spiked human urine and plasma samples with low-concentration (50 ng mL(-1)) analytes and a low starting sample volume of 20 mu L of plasma and urine in 10-fold diluted samples. The developed automated EE setup is easy to operate, provides a fast extraction method for analytes from volume-limited biological samples, and is hyphenated with on-line LC-MS analysis. Therefore, this method can provide fast and automated sample preparation to solve bottlenecks in high-throughput bioanalysis workflows

Cancer intravasation-on-a-chip : a LEGO house for tumors!

The process where cancer cells leave the primary tumor and invade to the blood vessel. As shown in figure 1, intravasation is highly regulated by the micro-environment of the tumor. An important component of the micro-environment is the extracellular matrix (ECM) which can be seen as the building structure of a LEGO house. A proper model for cancer intravasation requires a proper model for the micro-environment, or in other words, a right LEGO house for cancer cells to live in! To model the process, microfluidics is used because there is: •more control on the biochemical content, •less human error by automating the experiments, •more complex designs, •and less ethical issues, it is a LEGO house! The GOAL is to study how the mechanical properties of the extracellular matrix regulate the tumor intravasation by using a microfluidic chip