Multimodal biomarker discovery for active Onchocerca volvulus infection.

The neglected tropical disease onchocerciasis, or river blindness, is caused by infection with the filarial nematode Onchocerca volvulus. Current estimates indicate that 17 million people are infected worldwide, the majority of them living in Africa. Today there are no non-invasive tests available that can detect ongoing infection, and that can be used for effective monitoring of elimination programs. In addition, to enable pharmacodynamic studies with novel macrofilaricide drug candidates, surrogate endpoints and efficacy biomarkers are needed but are non-existent. We describe the use of a multimodal untargeted mass spectrometry-based approach (metabolomics and lipidomics) to identify onchocerciasis-associated metabolites in urine and plasma, and of specific lipid features in plasma of infected individuals (O. volvulus infected cases: 68 individuals with palpable nodules; lymphatic filariasis cases: 8 individuals; non-endemic controls: 20 individuals). This work resulted in the identification of elevated concentrations of the plasma metabolites inosine and hypoxanthine as biomarkers for filarial infection, and of the urine metabolite cis-cinnamoylglycine (CCG) as biomarker for O. volvulus. During the targeted validation study, metabolite-specific cutoffs were determined (inosine: 34.2 ng/ml; hypoxanthine: 1380 ng/ml; CCG: 29.7 ng/ml) and sensitivity and specificity profiles were established. Subsequent evaluation of these biomarkers in a non-endemic population from a different geographical region invalidated the urine metabolite CCG as biomarker for O. volvulus. The plasma metabolites inosine and hypoxanthine were confirmed as biomarkers for filarial infection. With the availability of targeted LC-MS procedures, the full potential of these 2 biomarkers in macrofilaricide clinical trials, MDA efficacy surveys, and epidemiological transmission studies can be investigated.

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.

2-Methyl-pentanoyl-carnitine (2-MPC): a urine biomarker for patent Ascaris lumbricoides infection.

Infections with intestinal worms, such as Ascaris lumbricoides, affect hundreds of millions of people in all tropical and subtropical regions of the world. Through large-scale deworming programs, World Health Organization aims to reduce moderate-to-heavy intensity infections below 1%. Current diagnosis and monitoring of these control programs are solely based on the detection of worm eggs in stool. Here we describe how metabolome analysis was used to identify the A. lumbricoides-specific urine biomarker 2-methyl pentanoyl carnitine (2-MPC). This biomarker was found to be 85.7% accurate in determining infection and 90.5% accurate in determining a moderate-to-heavy infection. Our results also demonstrate that there is a correlation between 2-MPC levels in urine and A. lumbricoides DNA detected in stool. Furthermore, the levels of 2-MPC in urine were shown to rapidly and strongly decrease upon administration of a standard treatment (single oral dose of 400 mg albendazole). In an Ascaris suum infection model in pigs, it was found that, although 2-MPC levels were much lower compared to humans, there was a significant association between urinary 2-MPC levels and both worm counts (p = 0.023) and the number of eggs per gram (epg) counts (p < 0.001). This report demonstrates that urinary 2-MPC can be considered an A. lumbricoides-specific biomarker that can be used to monitor infection intensity.

Analytical techniques for multiplex analysis of protein biomarkers.

INTRODUCTION: The importance of biomarkers for pharmaceutical drug development and clinical diagnostics is more significant than ever in the current shift toward personalized medicine. Biomarkers have taken a central position either as companion markers to support drug development and patient selection, or as indicators aiming to detect the earliest perturbations indicative of disease, minimizing therapeutic intervention or even enabling disease reversal. Protein biomarkers are of particular interest given their central role in biochemical pathways. Hence, capabilities to analyze multiple protein biomarkers in one assay are highly interesting for biomedical research. AREAS COVERED: We here review multiple methods that are suitable for robust, high throughput, standardized, and affordable analysis of protein biomarkers in a multiplex format. We describe innovative developments in immunoassays, the vanguard of methods in clinical laboratories, and mass spectrometry, increasingly implemented for protein biomarker analysis. Moreover, emerging techniques are discussed with potentially improved protein capture, separation, and detection that will further boost multiplex analyses. EXPERT COMMENTARY: The development of clinically applied multiplex protein biomarker assays is essential as multi-protein signatures provide more comprehensive information about biological systems than single biomarkers, leading to improved insights in mechanisms of disease, diagnostics, and the effect of personalized medicine.

Determination of variability due to biological and technical variation in urinary extracellular vesicles as a crucial step in biomarker discovery studies.

Urinary extracellular vesicles (EVs) are an attractive source of biomarkers for urological diseases. A crucial step in biomarker discovery studies is the determination of the variation parameters to perform a sample size calculation. In this way, a biomarker discovery study with sufficient statistical power can be performed to obtain biologically significant biomarkers. Here, a variation study was performed on both the protein and lipid content of urinary EVs of healthy individuals, aged between 52 and 69 years. Ultrafiltration (UF) in combination with size exclusion chromatography (SEC) was used to isolate the EVs from urine. Different experimental variation set-ups were used in this variation study. The calculated standard deviations (SDs) of the 90% least variable peptides and lipids did not exceed 2 and 1.2, respectively. These parameters can be used in a sample size calculation for a well-designed biomarker discovery study at the cargo of EVs.

Psoralen and Ultraviolet A Light Treatment Directly Affects Phosphatidylinositol 3-Kinase Signal Transduction by Altering Plasma Membrane Packing.

Psoralen and ultraviolet A light (PUVA) are used to kill pathogens in blood products and as a treatment of aberrant cell proliferation in dermatitis, cutaneous T-cell lymphoma, and graft-versus-host disease. DNA damage is well described, but the direct effects of PUVA on cell signal transduction are poorly understood. Because platelets are anucleate and contain archetypal signal transduction machinery, they are ideally suited to address this. Lipidomics on platelet membrane extracts showed that psoralen forms adducts with unsaturated carbon bonds of fatty acyls in all major phospholipid classes after PUVA. Such adducts increased lipid packing as measured by a blue shift of an environment-sensitive fluorescent probe in model liposomes. Furthermore, the interaction of these liposomes with lipid order-sensitive proteins like amphipathic lipid-packing sensor and α-synuclein was inhibited by PUVA. In platelets, PUVA caused poor membrane binding of Akt and Bruton's tyrosine kinase effectors following activation of the collagen glycoprotein VI and thrombin protease-activated receptor (PAR) 1. This resulted in defective Akt phosphorylation despite unaltered phosphatidylinositol 3,4,5-trisphosphate levels. Downstream integrin activation was furthermore affected similarly by PUVA following PAR1 (effective half-maximal concentration (EC50), 8.4 ± 1.1 versus 4.3 ± 1.1 µm) and glycoprotein VI (EC50, 1.61 ± 0.85 versus 0.26 ± 0.21 µg/ml) but not PAR4 (EC50, 50 ± 1 versus 58 ± 1 µm) signal transduction. Our findings were confirmed in T-cells from graft-versus-host disease patients treated with extracorporeal photopheresis, a form of systemic PUVA. In conclusion, PUVA increases the order of lipid phases by covalent modification of phospholipids, thereby inhibiting membrane recruitment of effector kinases.

Lipidomics of tobacco leaf and cigarette smoke.

Detailed lipidomics experiments were performed on the extracts of cured tobacco leaf and of cigarette smoke condensate (CSC) using high-resolution liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (LC-Q-TOF MS). Following automated solid-phase extraction (SPE) fractionation of the lipid extracts, over 350 lipids could be annotated. From a large-scale study on 22 different leaf samples, it was determined that differentiation based on curing type was possible for both the tobacco leaf and the CSC extracts. Lipids responsible for the classification were identified and the findings were correlated to proteomics data acquired from the same tobacco leaf samples. Prediction models were constructed based on the lipid profiles observed in the 22 leaf samples and successfully allowed for curing type classification of new tobacco leaves. A comparison of the leaf and CSC data provided insight into the lipidome changes that occur during the smoking process. It was determined that lipids which survive the smoking process retain the same curing type trends in both the tobacco leaf and CSC data.

Profiling over 1500 lipids in induced lung sputum and the implications in studying lung diseases.

Induced lung sputum is a valuable matrix in the study of respiratory diseases. Although the methodology of sputum collection has evolved to a point where it is repeatable and responsive to inflammation, its use in molecular profiling studies is still limited. Here, an in-depth lipid profiling of induced lung sputum using high-resolution liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (LC-Q-TOF MS) is described. An enormous complexity in lipid composition could be revealed. Over 1500 intact lipids, originating from 6 major lipid classes, have been accurately identified in 120 µL of induced sputum. By number and measured intensity, glycerophospholipids represent the largest lipid class, followed by sphingolipids, glycerolipids, fatty acyls, sterol lipids, and prenol lipids. Several prenol lipids, originating from tobacco, could be detected in the lung sputum of smokers. To illustrate the utility of the methodology in studying respiratory diseases, a comparative lipid screening was performed on lung sputum extracts in order to study the effect of Chronic Obstructive Pulmonary Disease (COPD) on the lung barrier lipidome. Results show that sphingolipid expression in induced sputum significantly differs between smokers with and without COPD.

Profiling and characterizing skin ceramides using reversed-phase liquid chromatography-quadrupole time-of-flight mass spectrometry.

An LC-MS based method for the profiling and characterization of ceramide species in the upper layer of human skin is described. Ceramide samples, collected by tape stripping of human skin, were analyzed by reversed-phase liquid chromatography coupled to high-resolution quadrupole time-of-flight mass spectrometry operated in both positive and negative electrospray ionization mode. All known classes of ceramides could be measured in a repeatable manner. Furthermore, the data set showed several undiscovered ceramides, including a class with four hydroxyl functionalities in its sphingoid base. High-resolution MS/MS fragmentation spectra revealed that each identified ceramide species is composed of several skeletal isomers due to variation in carbon length of the respective sphingoid bases and fatty acyl building blocks. The resulting variety in skeletal isomers has not been previously demonstrated. It is estimated that over 1000 unique ceramide structures could be elucidated in human stratum corneum. Ceramide species with an even and odd number of carbon atoms in both chains were detected in all ceramide classes. Acid hydrolysis of the ceramides, followed by LC-MS analysis of the end-products, confirmed the observed distribution of both sphingoid bases and fatty acyl groups in skin ceramides. The study resulted in an accurate mass retention time library for targeted profiling of skin ceramides. It is furthermore demonstrated that targeted data processing results in an improved repeatability versus untargeted data processing (72.92% versus 62.12% of species display an RSD < 15%).

Metabolomics to unveil and understand phenotypic diversity between pathogen populations.

Leishmaniasis is a debilitating disease caused by the parasite Leishmania. There is extensive clinical polymorphism, including variable responsiveness to treatment. We study Leishmania donovani parasites isolated from visceral leishmaniasis patients in Nepal that responded differently to antimonial treatment due to differing intrinsic drug sensitivity of the parasites. Here, we present a proof-of-principle study in which we applied a metabolomics pipeline specifically developed for L. donovani to characterize the global metabolic differences between antimonial-sensitive and antimonial-resistant L. donovani isolates. Clones of drug-sensitive and drug-resistant parasite isolates from clinical samples were cultured in vitro and harvested for metabolomics analysis. The relative abundance of 340 metabolites was determined by ZIC-HILIC chromatography coupled to LTQ-Orbitrap mass spectrometry. Our measurements cover approximately 20% of the predicted core metabolome of Leishmania and additionally detected a large number of lipids. Drug-sensitive and drug-resistant parasites showed distinct metabolic profiles, and unsupervised clustering and principal component analysis clearly distinguished the two phenotypes. For 100 metabolites, the detected intensity differed more than three-fold between the 2 phenotypes. Many of these were in specific areas of lipid metabolism, suggesting that the membrane composition of the drug-resistant parasites is extensively modified. Untargeted metabolomics has been applied on clinical Leishmania isolates to uncover major metabolic differences between drug-sensitive and drug-resistant isolates. The identified major differences provide novel insights into the mechanisms involved in resistance to antimonial drugs, and facilitate investigations using targeted approaches to unravel the key changes mediating drug resistance.

Towards an unbiased metabolic profiling of protozoan parasites: optimisation of a Leishmania sampling protocol for HILIC-orbitrap analysis.

Comparative metabolomics of Leishmania species requires the simultaneous identification and quantification of a large number of intracellular metabolites. Here, we describe the optimisation of a comprehensive metabolite extraction protocol for Leishmania parasites and the subsequent optimisation of the analytical approach, consisting of hydrophilic interaction liquid chromatography coupled to LTQ-orbitrap mass spectrometry. The final optimised protocol starts with a rapid quenching of parasite cells to 0 °C, followed by a triplicate washing step in phosphate-buffered saline. The intracellular metabolome of 4 × 10(7) parasites is then extracted in cold chloroform/methanol/water 20/60/20 (v/v/v) for 1 h at 4 °C, resulting in both cell disruption and comprehensive metabolite dissolution. Our developed metabolomics platform can detect approximately 20% of the predicted Leishmania metabolome in a single experiment in positive and negative ionisation mode.

The potential of metabolomics for Leishmania research in the post-genomics era.

The post-genomics era has provided researchers with access to a new generation of tools for the global characterization and understanding of pathogen diversity. This review provides a critical summary of published Leishmania post-genomic research efforts to date, and discusses the potential impact of the addition of metabolomics to the post-genomic toolbox. Metabolomics aims at understanding biology by comprehensive metabolite profiling. We present an overview of the design and interpretation of metabolomics experiments in the context of Leishmania research. Sample preparation, measurement techniques, and bioinformatics analysis of the generated complex datasets are discussed in detail. To illustrate the concepts and the expected results of metabolomics analyses, we also present an overview of comparative metabolic profiles of drug-sensitive and drug-resistant Leishmania donovani clinical isolates.

Joint GC-MS and LC-MS platforms for comprehensive plant metabolomics: repeatability and sample pre-treatment.

Metabolomics nowadays mostly comprises the application of both LC-MS and GC-MS based approaches. Here we investigate different extraction set-ups for these two established analytical platforms in the field of plant metabolomics. Six extraction approaches for Arabidopsis thaliana leaves, varying in extraction solvent composition, extraction temperature and order of solvent addition within the extraction sequence, were analyzed on the two platforms. Our aim was to establish the most suitable analysis protocol, practicable for both LC-MS and GC-MS analysis, in order to obtain as extensive as possible metabolome coverage. One single sample preparation procedure would save time and valuable sample while still offering the complementary datasets generated by GC-MS and LC-MS. All extraction approaches were evaluated based on the following criteria: number of detected m/z-retention time pairs, heat maps of the detected peaks, and residual enzymatic activity of invertase and phosphatase in the plant leaf extracts. Unsupervised principal component analysis (PCA) was used to evaluate grouping trends between the different extraction approaches. Quality controls, a blend of aliquots of the different extracts, were used to establish a paired evaluation of the repeatability performance of the GC-MS and LC-MS analysis. We conclude that the use of chloroform in the extraction solvent is counterproductive in an untargeted LC-MS metabolomics approach as is heating. Below room temperature (instead of heated) extraction does not significantly degrade GC-MS performance but one should be more cautious with respect to residual enzymatic activity in the plant extract.

Improved analyte detectability of proteins and peptide lysates by means of multiple large-volume injection in LC-MS.

A 'multiple (trapping) large-volume injection' approach was developed for the analysis of peptides and proteins. In this way, a maximally 10-fold gain in sensitivity could be achieved. The system involves the use of an automated 10-port switching valve in combination with a 1 mm i.d. trapping/guard column and a 1 mm i.d. x 150 mm analytical column. The optimized multiple injection/loading procedure allows quantitative measurements of peptides and protein lysates. Linear calibration curves (R(2) > or = 0.988) over a minimum of two orders of magnitude were generated for a range of peptide and protein standards with sensitivities equal to or even exceeding, those generally achieved only through increasing miniaturization (quantification limit > or = 0.5 pmol/mL).

LC-MS metabolic profiling of Arabidopsis thaliana plant leaves and cell cultures: optimization of pre-LC-MS procedure parameters.

This study treats the optimization of methods for homogenizing Arabidopsis thaliana plant leaves as well as cell cultures, and extracting their metabolites for metabolomics analysis by conventional liquid chromatography electrospray ionization mass spectrometry (LC-ESI/MS). Absolute recovery, process efficiency and procedure repeatability have been compared between different pre-LC-MS homogenization/extraction procedures through the use of samples fortified before extraction with a range of representative metabolites. Hereby, the magnitude of the matrix effect observed in the ensuing LC-MS based metabolomics analysis was evaluated. Based on relative recovery and repeatability of key metabolites, comprehensiveness of extraction (number of m/z-retention time pairs) and clean-up potential of the approach (minimum matrix effects), the most appropriate sample pre-treatment was adopted. It combines liquid nitrogen homogenization for plant leaves with thermomixer based extraction using MeOH/H(2)O 80/20. As such, an efficient and highly reproducible LC-MS plant metabolomics set-up is achieved, as illustrated by the obtained results for both LC-MS (8.88%+/-5.16 versus 7.05%+/-4.45) and technical variability (12.53%+/-11.21 versus 9.31%+/-6.65) data in a comparative investigation of A. thaliana plant leaves and cell cultures, respectively.

Evaluation of hydrophilic interaction chromatography versus reversed-phase chromatography in a plant metabolomics perspective.

The metabolomics goal, the unbiased relative quantification of all metabolites in a biological system, still lacks a universal analytical approach. In the LC-MS line of approach, one of the major problems encountered is the polar nature of a large group of (plant) metabolites. Here, we investigate the potential of hydrophilic interaction chromatography (HILIC) and compare its qualities with extended polarity RP chromatography. Two opposite LC phase compositions (Atlantis dC18 vs. TSKgel Amide-80) are compared in a plant metabolomics setting. Both performed equally well with regard to retentive capacities, but variation in peak area was about 5% higher for the HILIC approach. Focussing on matrix effects (ME) on the other hand, it was observed that this well-known problem in RP LC-MS metabolomics was not reduced on using hydrophilic interaction chromatography.

Broad-spectrum separations in metabolomics using enhanced polar LC stationary phases: a dedicated evaluation using plant metabolites.

In metabolomics, major efforts are invested in the development of suitable analytical approaches. A tendency towards the use of LC-MS is nowadays very obvious. A great majority of the metabolites of interest are polar to highly polar in nature. We focus on the so-called 'extended polarity' reversed LC phases, developed specifically to allow better retention characteristics for polar compounds. Several of these phases (Atlantis dC18, Inertsil ODS-3, Zorbax XDB, Alltima HP C18) are tested for different column dimension variations (0.5, 1.0, 2.1 mm id) in a specific LC-MS metabolomics setting. Important chromatographic and mass spectrometric quality parameters such as capacity factor, separation efficiency, peak symmetry, sensitivity, and mass accuracy are taken into account. All phases show adequate retention of polar compounds and also perform well with highly aqueous mobile phase compositions. On comparing 1.0 and 2.1 mm id columns, it is clear that the potential gain in sensitivity is not achieved. Using a Lockspray device, accurate mass measurement with a Q-TOF micro is feasible within a mass range of 12 ppm if signal intensities of compound and lockmass are equated. Finally, the extended polarity RP approach in metabolomics experiments is endorsed using real plant extracts.