A targeted LC-MRM3 proteomic approach for the diagnosis of SARS-CoV-2 infection in nasopharyngeal swabs.

Since its first appearance, SARS-CoV-2 quickly spread around the world and the lack of adequate PCR testing capacities, especially during the early pandemic, led the scientific community to explore new approaches such as mass spectrometry (MS). We developed a proteomics workflow to target several tryptic peptides of the nucleocapsid protein (NCAP). A highly selective multiple reaction monitoring MRM3 strategy provided a sensitivity increase in comparison to conventional MRM acquisition. Our MRM3 approach was first tested on an Amsterdam public health cohort (alpha-variant, 760 participants) detecting viral NCAP peptides from nasopharyngeal swabs samples presenting a cycle threshold (Ct) value down to 35 with sensitivity and specificity of 94.2% and 100.0%, without immuno-purification. A second iteration of the MS-diagnostic test, able to analyze more than 400 samples per day, was clinically validated on a Leiden-Rijswijk public health cohort (delta-variant, 2536 participants) achieving 99.9% specificity and 93.1% sensitivity for patients with Ct-values up to 35. In this manuscript, we also developed and brought the first proof of the concept of viral variant monitoring in a complex matrix using targeted mass spectrometry.

Reconstruction of Glutathione Metabolism in the Neuronal Model of Rotenone-Induced Neurodegeneration Using Mass Isotopologue Analysis with Hydrophilic Interaction Liquid Chromatography-Zeno High-Resolution Multiple Reaction Monitoring.

Accurate reconstruction of metabolic pathways is an important prerequisite for interpreting metabolomics changes and understanding the diverse biological processes in disease models. A tracer-based metabolomics strategy utilizes stable isotope-labeled precursors to resolve complex pathways by tracing the labeled atom(s) to downstream metabolites through enzymatic reactions. Isotope enrichment analysis is informative and achieved by counting total labeled atoms and acquiring the mass isotopologue distribution (MID) of the intact metabolite. However, quantitative analysis of labeled metabolite substructures/moieties (MS2 fragments) can offer more valuable insights into the reaction connections through measuring metabolite transformation. In order to acquire the isotopic labeling information at the intact metabolite and moiety level simultaneously, we developed a method that couples hydrophilic interaction liquid chromatography (HILIC) with Zeno trap-enabled high-resolution multiple reaction monitoring (MRMHR). The method enabled accurate and reproducible MID quantification for intact metabolites as well as their fragmented moieties, with notably high sensitivity in the MS2 fragmentation mode based on the measurement of 13C- or 15N-labeled cellular samples. The method was applied to human-induced pluripotent stem cell-derived neurons to trace the fate of 13C/15N atoms from D-13C6-glucose/L-15N2-glutamine added to the media. With the MID analysis of both intact metabolites and fragmented moieties, we validated the pathway reconstruction of de novo glutathione synthesis in mid-brain neurons. We discovered increased glutathione oxidization from both basal and newly synthesized glutathione pools under neuronal oxidative stress. Furthermore, the significantly decreased de novo glutathione synthesis was investigated and associated with altered activities of several key enzymes, as evidenced by suppressed glutamate supply via glucose metabolism and a diminished flux of glutathione synthetic reaction in the neuronal model of rotenone-induced neurodegeneration.

Cov2MS: An Automated and Quantitative Matrix-Independent Assay for Mass Spectrometric Measurement of SARS-CoV-2 Nucleocapsid Protein.

The pandemic readiness toolbox needs to be extended, targeting different biomolecules, using orthogonal experimental set-ups. Here, we build on our Cov-MS effort using LC-MS, adding SISCAPA technology to enrich proteotypic peptides of the SARS-CoV-2 nucleocapsid (N) protein from trypsin-digested patient samples. The Cov2MS assay is compatible with most matrices including nasopharyngeal swabs, saliva, and plasma and has increased sensitivity into the attomole range, a 1000-fold improvement compared to direct detection in a matrix. A strong positive correlation was observed with qPCR detection beyond a quantification cycle of 30-31, the level where no live virus can be cultured. The automatable sample preparation and reduced LC dependency allow analysis of up to 500 samples per day per instrument. Importantly, peptide enrichment allows detection of the N protein in pooled samples without sensitivity loss. Easily multiplexed, we detect variants and propose targets for Influenza A and B detection. Thus, the Cov2MS assay can be adapted to test for many different pathogens in pooled samples, providing longitudinal epidemiological monitoring of large numbers of pathogens within a population as an early warning system.

A pragmatic trial testing a tailored non pharmacologic therapies on nocturnal behavioral and psychological symptoms associated with dementia.

We compared the efficacy of tailored non pharmacological therapies (NPT) on specific nocturnal behavioral and psychological symptoms of dementia (BPSD). This retrospective 1-year study included 84 older dependent patients institutionalized in 7 long-term care home. Dedicated assistants, who were taught by experts how to use NPT, were asked to record the occurrence of each BPSD episode, to choose a given NPT on the basis of their knowledge of the patient and the type of BPSD and to estimate its efficacy. Wandering was the most prevalent BPSD followed by agitation/aggression and screaming. The most used therapy was cognitive stimulation, followed by multisensory stimulation, reminiscence and Montessori-based. Regarding wandering, multisensory stimulation was found to be the most efficacious NPT significantly different from Montessori-based, cognitive stimulation or reminiscence. With regards to agitation/aggression or screaming, Montessori-based was found to be the most efficacious NPT significantly different from multisensory stimulation, reminiscence and cognitive stimulation.

Evaluation of ion mobility in capillary electrophoresis coupled to mass spectrometry for the identification in metabolomics.

Currently, feature annotation remains one of the main challenges in untargeted metabolomics. In this context, the information provided by high-resolution mass spectrometry (HRMS) in addition to accurate mass can improve the quality of metabolite annotation, and MS/MS fragmentation patterns are widely used. Accurate mass and a separation index, such as retention time or effective mobility (µeff ), in chromatographic and electrophoretic approaches, respectively, must be used for unequivocal metabolite identification. The possibility of measuring collision cross-section (CCS) values by using ion mobility (IM) is becoming increasingly popular in metabolomic studies thanks to the new generation of IM mass spectrometers. Based on their similar separation mechanisms involving electric field and the size of the compounds, the complementarity of DT CCSN2 and µeff needs to be evaluated. In this study, a comparison of DT CCSN2 and µeff was achieved in the context of feature identification ability in untargeted metabolomics by capillary zone electrophoresis (CZE) coupled with HRMS. This study confirms the high correlation of DT CCSN2 with the mass of the studied metabolites as well as the orthogonality between accurate mass and µeff , making this combination particularly interesting for the identification of several endogenous metabolites. The use of IM-MS remains of great interest for facilitating the annotation of neutral metabolites present in the electroosmotic flow (EOF) that are poorly or not separated by CZE.

New insights into the conversion of electropherograms to the effective electrophoretic mobility scale.

CE-MS is increasingly gaining momentum as an analytical tool in metabolomics, due to its ability to obtain information about the most polar elements in biological samples. This has been helped by improvements of robustness in peak identification by means of mobility-scale representations of the electropherograms (mobilograms). As a necessary step toward facilitating the use of CE-MS for untargeted metabolomics data, the authors previously developed and introduced ROMANCE, a software automating mobilogram generation for large untargeted datasets through a simple and self-contained user interface. Herein, we introduce a new version of ROMANCE including new features such as compatibility with other types of data (targeted MS data and 2D UV-Vis absorption-like electropherograms), and the much needed additional flexibility in the transformation parameters (including field ramping and the use of secondary markers), more measurement conditions (depending on detection and integration modes), and most importantly tackling the issue of quantitative peak conversion. First, we present a review of the current theoretical framework with regard to peak characterization, and we develop new formulas for multiple marker peak area corrections, for anticipating peak position precision, and for assessing peak shape distortion. Then, the new version of the software is presented and validated experimentally. We contrast the multiple marker mobility transformations with previous results, finding increased peak position precision, and finally we showcase an application to actual untargeted metabolomics data.

Capillary Electrophoresis-Mass Spectrometry for Metabolomics: Possibilities and Perspectives.

Capillary electrophoresis-mass spectrometry (CE-MS) is a very useful analytical technique for the selective and highly efficient profiling of polar and charged metabolites in a wide range of biological samples. Compared to other analytical techniques, the use of CE-MS in metabolomics is relatively low as the approach is still regarded as technically challenging and not reproducible. In this chapter, the possibilities of CE-MS for metabolomics are highlighted with special emphasis on the use of recently developed interfacing designs. The utility of CE-MS for targeted and untargeted metabolomics studies is demonstrated by discussing representative and recent examples in the biomedical and clinical fields. The potential of CE-MS for large-scale and quantitative metabolomics studies is also addressed. Finally, some general conclusions and perspectives are given on this strong analytical separation technique for probing the polar metabolome.

Capillary Electrophoresis-Mass Spectrometry at Trial by Metabo-Ring: Effective Electrophoretic Mobility for Reproducible and Robust Compound Annotation.

Capillary zone electrophoresis-mass spectrometry (CE-MS) is a mature analytical tool for the efficient profiling of (highly) polar and ionizable compounds. However, the use of CE-MS in comparison to other separation techniques remains underrepresented in metabolomics, as this analytical approach is still perceived as technically challenging and less reproducible, notably for migration time. The latter is key for a reliable comparison of metabolic profiles and for unknown biomarker identification that is complementary to high resolution MS/MS. In this work, we present the results of a Metabo-ring trial involving 16 CE-MS platforms among 13 different laboratories spanning two continents. The goal was to assess the reproducibility and identification capability of CE-MS by employing effective electrophoretic mobility (µeff) as the key parameter in comparison to the relative migration time (RMT) approach. For this purpose, a representative cationic metabolite mixture in water, pretreated human plasma, and urine samples spiked with the same metabolite mixture were used and distributed for analysis by all laboratories. The µeff was determined for all metabolites spiked into each sample. The background electrolyte (BGE) was prepared and employed by each participating lab following the same protocol. All other parameters (capillary, interface, injection volume, voltage ramp, temperature, capillary conditioning, and rinsing procedure, etc.) were left to the discretion of the contributing laboratories. The results revealed that the reproducibility of the µeff for 20 out of the 21 model compounds was below 3.1% vs 10.9% for RMT, regardless of the huge heterogeneity in experimental conditions and platforms across the 13 laboratories. Overall, this Metabo-ring trial demonstrated that CE-MS is a viable and reproducible approach for metabolomics.

Quantitative CE analysis of punicalagin in Combretum aculeatum extracts traditionally used in Senegal for the treatment of tuberculosis.

Mycobacterium tuberculosis is the causative agent of tuberculosis, an infectious bacterial disease, which most commonly affects the lungs. In the search for novel active compounds or medicines against tuberculosis, an ethnopharmacological survey combined with a host-pathogen assay has recently highlighted the potency of an aqueous extract of Combretum aculeatum. C. aculeatum is used in traditional medicine and has demonstrated a significant in vitro antimycobacterial activity. Punicalagin, an ellagitannin, was isolated and found to be related to the biological activity of the extract. An analytical method for the evaluation of punicalagin in C. aculeatum was developed by capillary electrophoresis. After method optimization, the quantification of punicalagin was achieved for the evaluation of various plant extracts to determine the content of punicalagin related to the extraction modes and conditions, origin of the plant material, and harvesting period. The developed method demonstrated that the leaves presented the highest punicalagin content compared to the seeds and stems. A decoction of 30 min in boiling water was found to be the best extraction mode of C. aculeatum.

ROMANCE: A new software tool to improve data robustness and feature identification in CE-MS metabolomics.

The use of capillary electrophoresis coupled to mass spectrometry (CE-MS) in metabolomics remains an oddity compared to the widely adopted use of liquid chromatography. This technique is traditionally regarded as lacking the reproducibility to adequately identify metabolites by their migration times. The major reason is the variability of the velocity of the background electrolyte, mainly coming from shifts in the magnitude of the electroosmotic flow and from the suction caused by electrospray interfaces. The use of the effective electrophoretic mobility is one solution to overcome this issue as it is a characteristic feature of each compound. To date, such an approach has not been applied to metabolomics due to the complexity and size of CE-MS data obtained in such studies. In this paper, ROMANCE (RObust Metabolomic Analysis with Normalized CE) is introduced as a new software for CE-MS-based metabolomics. It allows the automated conversion of batches of CE-MS files with minimal user intervention. ROMANCE converts the x-axis of each MS file from the time into the effective mobility scale and the resulting files are already pseudo-aligned, present normalized peak areas and improved reproducibility, and can eventually follow existing metabolomic workflows. The software was developed in Scala, so it is multi-platform and computationally-efficient. It is available for download under a CC license. In this work, the versatility of ROMANCE was demonstrated by using data obtained in the same and in different laboratories, as well as its application to the analysis of human plasma samples.

Development of a New Extraction Device Based on Parallel-Electromembrane Extraction.

A new device for parallel-electromembrane extraction (Pa-EME) was developed to enable simultaneous and high-throughput extraction of ionic and ionizable compounds from biofluids. The new system is composed of a reusable conductive well-plate used as an acceptor compartment and a filtration well-plate used as a donor compartment. A design of experiments was implemented to optimize the main experimental parameters (agitation, voltage, and time) with standard solutions in formic acid 50 mM. The stirring rate was found the primary influent parameter. The Pa-EME device showed excellent extraction yields from 84% to 101% with RSD lower than 7.5% on model compounds. Optimized parameters were then applied to plasma samples and process efficiencies from 59% to 62% and RSD of less than 8.0% were obtained. The whole extraction process took less than 20 min to prepare 8 samples simultaneously, greatly enhancing the sample preparation throughput (<3 min per sample).

Sample preparation for polar metabolites in bioanalysis.

Sample preparation is a primary step of any bioanalytical workflow, especially in metabolomics analysis where maximum information has to be obtained without spoiling the analytical instrument. Because of their biological implication, highly polar metabolites, such as amino acids, nucleobases, and catecholamines seem to attract growing interest in the field of comprehensive metabolomics analysis although their extraction from the matrix remains a real challenge. In this paper, we discuss about the actual practice and issues of hydrophilic metabolites' extraction, including new solutions and perspectives to improve their phase transfer from a complex biological sample to a clean extract prior to analysis.

Dynamic-Electromembrane Extraction: A Technical Development for the Extraction of Neuropeptides.

In this work, a dynamic-electromembrane extraction (d-EME) device was developed for the extraction of neuropeptides. On the basis of a thin polypropylene hollow fiber (50 µm of wall-thickness and 280 µm i.d.), this setup allowed for a continual renewal of the acceptor compartment. Because of the reduced size of the device, high preconcentration factors were obtained (up to 50-fold). The extraction remained constant regardless of the extraction time (from 15 to 45 min); accordingly, this new setup minimized the effect of electrolysis on extraction performance while enabling high extraction yield (up to 72%) for most lipophilic neuropeptides.

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 < 0.001, R2 > 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 µL 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.

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 < 0.02, R2 > 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 low-abundant (50 ng mL-1) analytes and a low sample volume of 15 µL 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.

Profiling acidic metabolites by capillary electrophoresis-mass spectrometry in low numbers of mammalian cells using a novel chemical derivatization approach.

The simultaneous analysis of a broad range of polar ionogenic metabolites using capillary electrophoresis-mass spectrometry (CE-MS) can be challenging, as two different analytical methods are often required, that is, one for cations and one for anions. Even though CE-MS has shown to be an effective method for cationic metabolite profiling, the analysis of small anionic metabolites often results in relatively low sensitivity and poor repeatability. In this work, a novel derivatization strategy based on trimethylmethaneaminophenacetyl bromide was developed to enable CE-MS analysis of carboxylic acid metabolites using normal CE polarity (i.e., cathode in the outlet) and detection by mass spectrometry in positive ionization mode. Optimization of derivatization conditions was performed using a response surface methodology after which the optimized method (incubation time 50 min, temperature 90°C, and pH 10) was used for the analysis of carboxylic acid metabolites in extracts from HepG2 cells. For selected metabolites, detection limits were down to 8.2 nM, and intraday relative standard deviation values for replicates (n = 3) for peak areas were below 21.5%. Metabolites related to glycolysis, tricarboxylic acid cycle, and anaerobic respiration pathways were quantified in 250,000 cell lysates, and could still be detected in extracts from only 25,000 HepG2 cell lysates (∼70 cell lysates injected).

Evaluation of a nanoflow interface based on the triple-tube coaxial sheath-flow sprayer for capillary electrophoresis-mass spectrometry coupling in metabolomics.

The performance of an original CE-MS interface that allows the in-axis positioning of the electrospray with respect to the MS inlet was evaluated. The variations in the geometrical alignment of this configuration in the absence of a nebulizing gas afforded a significant reduction in the sheath-liquid flow rate from 3 µL/min to as low as 300 nL/min. The sheath liquid and BGE were respectively composed of H2O-iPrOHCH3COOH 50:50:1 (v/v/v) and 10% acetic acid (pH 2.2). A significant gain in sensitivity was obtained, and it was correlated to the effective mobility of the analytes. Compounds with low mobility values showed a greater sensitivity gain. Special attention was paid to the detection of proteinogenic amino acids. Linear response functions were obtained from 15 ng/mL to 500 ng/mL. The limits of quantification, as low as 34.3 ng/mL, were improved by a factor of up to six compared to the conventional configuration. The in-axis setup was ultimately applied to the absolute quantification of four important amino acids, alanine, tyrosine, methionine and valine, in standard reference material (NIST plasma). The accuracies ranged from 78 to 113%, thus demonstrating the potential of this configuration for metabolomics.

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 (R2 > 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.

Cov-MS: A Community-Based Template Assay for Mass-Spectrometry-Based Protein Detection in SARS-CoV-2 Patients.

Rising population density and global mobility are among the reasons why pathogens such as SARS-CoV-2, the virus that causes COVID-19, spread so rapidly across the globe. The policy response to such pandemics will always have to include accurate monitoring of the spread, as this provides one of the few alternatives to total lockdown. However, COVID-19 diagnosis is currently performed almost exclusively by reverse transcription polymerase chain reaction (RT-PCR). Although this is efficient, automatable, and acceptably cheap, reliance on one type of technology comes with serious caveats, as illustrated by recurring reagent and test shortages. We therefore developed an alternative diagnostic test that detects proteolytically digested SARS-CoV-2 proteins using mass spectrometry (MS). We established the Cov-MS consortium, consisting of 15 academic laboratories and several industrial partners to increase applicability, accessibility, sensitivity, and robustness of this kind of SARS-CoV-2 detection. This, in turn, gave rise to the Cov-MS Digital Incubator that allows other laboratories to join the effort, navigate, and share their optimizations and translate the assay into their clinic. As this test relies on viral proteins instead of RNA, it provides an orthogonal and complementary approach to RT-PCR using other reagents that are relatively inexpensive and widely available, as well as orthogonally skilled personnel and different instruments. Data are available via ProteomeXchange with identifier PXD022550.

Electromembrane Extraction of Highly Polar Compounds: Analysis of Cardiovascular Biomarkers in Plasma.

Cardiovascular diseases (CVDs) represent a major concern in today's society, with more than 17.5 million deaths reported annually worldwide. Recently, five metabolites related to the gut metabolism of phospholipids were identified as promising predictive biomarker candidates for CVD. Validation of those biomarker candidates is crucial for applications to the clinic, showing the need for high-throughput analysis of large numbers of samples. These five compounds, trimethylamine N-oxide (TMAO), choline, betaine, l-carnitine, and deoxy-l-carnitine (4-trimethylammoniobutanoic acid), are highly polar compounds and show poor retention on conventional reversed phase chromatography, which can lead to strong matrix effects when using mass spectrometry detection, especially when high-throughput analysis approaches are used with limited separation of analytes from interferences. In order to reduce the potential matrix effects, we propose a novel fast parallel electromembrane extraction (Pa-EME) method for the analysis of these metabolites in plasma samples. The evaluation of Pa-EME parameters was performed using multi segment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS). Recoveries up to 100% were achieved, with variability as low as 2%. Overall, this study highlights the necessity of protein precipitation prior to EME for the extraction of highly polar compounds. The developed Pa-EME method was evaluated in terms of concentration range and response function, as well as matrix effects using fast-LC-MS/MS. Finally, the developed workflow was compared to conventional sample pre-treatment, i.e., protein precipitation using methanol, and fast-LC-MS/MS. Data show very strong correlations between both workflows, highlighting the great potential of Pa-EME for high-throughput biological applications.