An Automated Nanowell-Array Workflow for Quantitative Multiplexed Single-Cell Proteomics Sample Preparation at High Sensitivity.

Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lags. Here, we introduce the proteoCHIP, a universal option for single-cell proteomics sample preparation including multiplexed labeling up to 16-plex with high sensitivity and throughput. The automated processing using a commercial system combining single-cell isolation and picoliter dispensing, the cellenONE, reduces final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error-prone manual sample handling and overcoming evaporation. The specialized proteoCHIP design allows direct injection of single cells via a standard autosampler resulting in around 1500 protein groups per TMT10-plex with reduced or eliminated need for a carrier proteome. We evaluated the effect of wider precursor isolation windows at single-cell input levels and found that using 2 Da isolation windows increased overall sensitivity without significantly impacting interference. Using the dedicated mass spectrometry acquisition strategies detailed here, we identified on average close to 2000 proteins per TMT10-plex across 170 multiplexed single cells that readily distinguished human cell types. Overall, our workflow combines highly efficient sample preparation, chromatographic and ion mobility-based filtering, rapid wide-window data-dependent acquisition analysis, and intelligent data analysis for optimal multiplexed single-cell proteomics. This versatile and automated proteoCHIP-based sample preparation approach is sufficiently sensitive to drive biological applications of single-cell proteomics and can be readily adopted by proteomics laboratories.

Automated micro-solid-phase extraction clean-up and gas chromatography-tandem mass spectrometry analysis of pesticides in foods extracted with ethyl acetate.

Generic extraction methods for the multi-compound pesticide analysis of food have found their solid place in laboratories. Ethyl acetate and acetonitrile extraction methods have been developed as fast and easy to handle standard multi-compound methods, both feature benefits and limitations. The direct injection to gas chromatography can be impaired by a high burden of coextracted matrix, resulting in deterioration of the chromatographic system and matrix effects, requiring frequent maintenance. Therefore, common clean-up methods, such as dispersive solid-phase extraction, freeze-out of fats, or gel permeation chromatography, have been applied in clean-up. Automated clean-up using micro-solid-phase extraction (µSPE) is a recent development with several demonstrated advantages when employed in the analysis of pesticides and other contaminants in foods extracted with acetonitrile, but it has not yet been evaluated in this application using ethyl acetate for extraction. In this study, an automated procedure using µSPE cartridges was developed and established on an x,y,z robotic sampler for the raw extract clean-up and preparation of diluted samples for injection on a GC-MS/MS system. Validation experiments for 212 pesticides, polychlorinated biphenyls, and polycyclic aromatic hydrocarbons in lettuce, avocado, raspberry, paprika, egg, and liver extracts were performed using µSPE with MgSO4, PSA, C18, and CarbonX. The performance in routine operation is briefly discussed.

Multi-dimensional technology - Recent advances and applications for biotherapeutic characterization.

This review provides an overview of the latest advancements and applications in multi-dimensional liquid chromatography coupled with mass spectrometry (mD-LC-MS), covering aspects such as inter-laboratory studies, digestion strategy, trapping column, and multi-level analysis. The shift from an offline to an online workflow reduces sample processing artifacts, analytical variability, analysis time, and the labor required for data acquisition. Over the past few years, this technique has demonstrated sufficient maturity for application across a diverse range of complex products. Moreover, there is potential for this strategy to evolve into an integrated process analytical technology tool for the real-time monitoring of monoclonal antibody quality. This review also identifies emerging trends, including its application to new modalities, the possibility of evaluating biological activity within the mD-LC set-up, and the consideration of multi-dimensional capillary electrophoresis as an alternative to mD-LC. As mD-LC-MS continues to evolve and integrate emerging trends, it holds the potential to shape the next generation of analytical tools, offering exciting possibilities for enhanced characterization and monitoring of complex biopharmaceutical products.

Rapid and Online Microvolume Flow-Through Dialysis Probe for Sample Preparation in Veterinary Drug Residue Analysis.

A rapid and online microvolume flow-through dialysis probe designed for sample preparation in the analysis of veterinary drug residues is introduced. This study addresses the need for efficient and green sample preparation methods that reduce chemical waste and reagent use. The dialysis probe integrates with liquid chromatography and mass spectrometry (LC-MS) systems, facilitating automated, high-throughput analysis. The dialysis method utilizes minimal reagent volumes per sample, significantly reducing the generation of solvent waste compared to traditional sample preparation techniques. Several veterinary drugs were spiked into tissue homogenates and analyzed to validate the probe's efficacy. A diagnostic sensitivity of >97% and specificity of >95% were obtained for this performance evaluation. The results demonstrated the effective removal of cellular debris and particulates, ensuring sample integrity and preventing instrument clogging. The automated dialysis probe yielded recovery rates between 27 and 77% for multiple analytes, confirming its potential to streamline veterinary drug residue analysis, while adhering to green chemistry principles. The approach highlights substantial improvements in both environmental impact and operational efficiency, presenting a viable alternative to conventional sample preparation methods in regulatory and research applications.

Automated microextraction by packed sorbent of endocrine disruptors in wastewater using a high-throughput robotic platform followed by liquid chromatography-tandem mass spectrometry.

An automated microextraction by packed sorbent followed by liquid chromatography-tandem mass spectrometry (MEPS-LC-MS/MS) method was developed for the determination of four endocrine disruptors-parabens, benzophenones, and synthetic phenolic antioxidants-in wastewater samples. The method utilizes a lab-made repackable MEPS device and a multi-syringe robotic platform that provides flexibility to test small quantities (2 mg) of multiple extraction phases and enables high-throughput capabilities for efficient method development. The overall performance of the MEPS procedure, including the investigation of influencing variables and the optimization of operational parameters for the robotic platform, was comprehensively studied through univariate and multivariate experiments. Under optimized conditions, the target analytes were effectively extracted from a small sample volume of 1.5 mL, with competitive detectability and analytical confidence. The limits of detection ranged from 0.15 to 0.30 ng L-1, and the intra-day and inter-day relative standard deviations were between 3 and 21%. The method's applicability was successfully demonstrated by determining methylparaben, propylparaben, butylated hydroxyanisole, and oxybenzone in wastewater samples collected from the São Carlos (SP, Brazil) river. Overall, the developed method proved to be a fast, sensitive, reliable, and environmentally friendly analytical tool for water quality monitoring.

Determination of parabens in wastewater samples via robot-assisted dynamic single-drop microextraction and liquid chromatography-tandem mass spectrometry.

Dynamic single-drop microextraction (SDME) was automatized employing an Arduino-based lab-made Cartesian robot and implemented to determine parabens in wastewater samples in combination with liquid chromatography-tandem mass spectrometry. A dedicated Arduino sketch controls the auto-performance of all the stages of the SDME process, including syringe filling, drop exposition, solvent recycling, and extract collection. Univariate and multivariate experiments investigated the main variables affecting the SDME performance, including robot-dependent and additional operational parameters. Under selected conditions, limit of detections were established at 0.3 µg/L for all the analytes, and the method provided linear responses in the range between 0.6 and 10 µg/L, with adequate reproducibility, measured as intraday relative standard deviations (RSDs) between 5.54% and 17.94%, (n = 6), and inter-days RSDs between 8.97% and 16.49% (n = 9). The robot-assisted technique eased the control of dynamic SDME, making the process more feasible, robust, and reliable so that the developed setup demonstrated to be a competitive strategy for the automated extraction of organic pollutants from water samples.

Identification of high-value generating molecules from the wastes of tuna fishery industry by liquid chromatography and gas chromatography hyphenated techniques with automated sample preparation.

The present work aims to a promising re-utilization of the massive waste derived from the tuna fishing industry, for which by-products can represent more than 50% of the original material. Due to the considerable content in polyunsaturated fatty acids and noble proteins, such wastes can be used as primary source of functional ingredients in the production of nutraceuticals. The composition of the lipid and protein tuna fractions was investigated by means of gas chromatography-mass spectrometry and high-performance liquid chromatography-tandem mass spectrometry methods (in wastes and edible parts), and a preliminary characterization of potential bioactive peptides was achieved. Automated sample preparation allowed speeding up the analytical workflow, while allowing for highly sensitive and selective lipid characterization. The ω3 fatty acid content was found higher in waste products compared to the muscle, in terms of fatty acids as well as complex lipids. As for peptides, extraction by isoelectric solubilization/precipitation was performed, followed by enzymatic digestion and high-performance liquid chromatography-tandem mass spectrometry analysis. Furthermore, the use of bioinformatics tools highlighted the presence of potential antimicrobial peptides in the samples investigated.

Fully automated sample preparation procedure to measure drugs of abuse in plasma by liquid chromatography tandem mass spectrometry.

For the analysis of drugs and pharmaceutical compounds in biological matrices, extraction procedures are typically used for LC-MS/MS analysis often requiring manual steps in sample preparation. In this study, we report a fully automated extraction method carried out by a programable liquid handler directly coupled to an LC-MS/MS system for the determination of 42 components (illicit drugs and/or metabolites) (plus 20 deuterated internal standards). The acquisition was performed in positive ionization mode with up to 15 MRM transitions per compound, each with optimized collision energy (MRM spectrum mode) to enable qualitative library searching in addition to quantitation. After placing the sample tube into the system, no further intervention was necessary: automated preparation used 50 µL of blood or plasma with 3 µL of extracted sample injected for analysis. The method was validated according to the requirements of ISO 15189. The limit of detection and quantification was 1-5 ng/mL depending on the compound. Stability experiments found that historic calibration curve data files could accurately quantify for up to 1 month with less than 20% uncertainty. Comparison to a QuEChERS method was made using patient samples providing a regression correlation R2 = 0.98 between the two methods. This approach was successfully designed to support parallel sample preparation and analysis therefore significantly increasing sample throughput and reduced cycle times. Graphical abstract ᅟ.

A robotic protocol for high-throughput processing of samples for selected reaction monitoring assays.

Selected reaction monitoring mass spectrometry (SRM-MS) is a sensitive and accurate method for the quantification of targeted proteins in biological specimens. However, the sample throughput and reliability of this technique is limited by the complexity of sample preparation, as well as instrumentation and data processing. Modern robotic equipment allows for rapid and accurate processing of large number of samples and makes SRM-MS assay applicable in epidemiological studies. Herein, we describe an automated sample processing platform developed in the context of an SRM-MS protocol for the assay of complement factor H protein and its variants in human plasma. We report detailed performance data on plasma digestion, sample cleanup and optimized robotic handling implemented on a Biomek® NXp Workstation. Method validation was assessed with isotopically labeled peptide standards and had high reproducibility of intra-day assay (CVs from 2.7 to 17.5% with median CV of 5.3%) and inter-day assay (CVs from 4.8 to 17.6 with median CV of 7.2%) for all peptides.

Recent advances in proteomics: towards the human proteome.

After the successful completion of the Human Genome project in 2003, the next major challenge was to understand when and where the encoded proteins were expressed, and to generate a map of the complex, interconnected pathways, networks and molecular systems (the human proteome) that, taken together, control the workings of all cells, tissues, organs and organisms. Proteomics will be fundamental for such studies. This review summarizes the key discoveries that laid down the foundations for proteomics as we now know it, and describes key recent technological advances that will undoubtedly contribute to achieving the initial goal of the Human Proteome Organization of identifying and characterizing at least one protein product and representative post-translational modifications, single amino acid polymorphisms and splice variant isoforms from the 20,300 human protein-coding genes within the next 10 years. Successful unraveling of the human proteome will undoubtedly improve our understanding of human biology at the cellular level and lay the foundations for improved diagnostic, prognostic, therapeutic and preventive medical outcomes as we enter the era of personalized medicine.

Determination of Patulin in Apple Juice and Apple-Derived Products Using a Robotic Sample Preparation System and LC-APCI-MS/MS.

Patulin, a toxic mycotoxin, can contaminate apple-derived products. The FDA has established an action level of 50 ppb (ng/g) for patulin in apple juice and apple juice products. To effectively monitor this mycotoxin, there is a need for adequate analytical methods that can reliably and efficiently determine patulin levels. In this work, we developed an automated sample preparation workflow followed by liquid chromatography-atmospheric pressure chemical ionization tandem mass spectrometry (LC-APCI-MS/MS) detection to identify and quantify patulin in a single method, further expanding testing capabilities for monitoring patulin in foods compared to traditional optical methods. Using a robotic sample preparation system, apple juice, apple cider, apple puree, apple-based baby food, applesauce, fruit rolls, and fruit jam were fortified with 13C-patulin and extracted using dichloromethane (DCM) without human intervention, followed by an LC-APCI-MS/MS analysis in negative ionization mode. The method achieved a limit of quantification of 4.0 ng/g and linearity ranging from 2 to 1000 ng/mL (r2 > 0.99). Quantitation was performed with isotope dilution using 13C-patulin as an internal standard and solvent calibration standards. Average recoveries (relative standard deviations, RSD%) in seven spike matrices were 95% (9%) at 10 ng/g, 110% (5%) at 50 ng/g, 101% (7%) at 200 ng/g, and 104% (4%) at 1000 ng/g (n = 28). The ranges of within-matrix and between-matrix variability (RSD) were 3-8% and 4-9%, respectively. In incurred samples, the identity of patulin was further confirmed with a comparison of the information-dependent acquisition-enhanced product ion (IDA-EPI) MS/MS spectra to a reference standard. The metrological traceability of the patulin measurements in an incurred apple cider (21.1 ± 8.0 µg/g) and apple juice concentrate (56.6 ± 15.6 µg/g) was established using a certified reference material and calibration data to demonstrate data confidence intervals (k = 2, 95% confidence interval).

Point-of-need mastitis pathogen biosensing in bovine milk: From academic sample preparation novelty to industry prototype field testing.

Bovine mastitis is an inflammation of the mammary gland, and it is the most common infectious disease in dairy cattle. Mastitis reduces milk yield and quality, costing dairy farmers millions of dollars each year. The aim of this study was to develop a point-of-need test for identifying mastitis pathogens that is field portable, cost-effective and can be used with minimal training. Using a proprietary polymer-based milk sample preparation method to rapidly extract pathogen DNA in milk samples, we demonstrated quantitative Polymerase Chain Reaction (qPCR) assays for six common bovine bacterial mastitis pathogens: Staphylococcus aureus, Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Mycoplasma bovis and Escherichia coli. We also implemented this sample preparation method on a prototype point-of-need system in a proof-of-concept field trial to evaluate user experience. Importantly, the protype system enabled a sample-to-result turnaround time of within 70 min to quantitatively detect all six target pathogens. The key advantage of our point-of-need prototype system is being culture-independent yet providing automated milk sample preparation for molecular identification of key mastitis pathogens by non-expert users. Our point-of-need prototype system showed a good correlation to laboratory-based qPCR for target pathogen detection outcomes, thus potentially removing the need for milk samples to be transported off-site for laboratory testing. Above all, we successfully achieved our objective of developing a point-of-need biosensor technology for mastitis and increased its readiness level with industry partners towards technology commercialization.

Enhanced Electrophoretic Depletion of Sodium Dodecyl Sulfate with Methanol for Membrane Proteome Analysis by Mass Spectrometry.

Membrane proteins are underrepresented during proteome characterizations, primarily owing to their lower solubility. Sodium dodecyl sulfate (SDS) is favored to enhance protein solubility but interferes with downstream analysis by mass spectrometry. Here, we present an improved workflow for SDS depletion using transmembrane electrophoresis (TME) while retaining a higher recovery of membrane proteins. Though higher levels of organic solvent lower proteome solubility, we found that the inclusion of 40% methanol provided optimal solubility of membrane proteins, with 86% recovery relative to extraction with SDS. Incorporating 40% methanol during the electrophoretic depletion of SDS by TME also maximized membrane protein recovery. We further report that methanol accelerates the rate of detergent removal, allowing TME to deplete SDS below 100 ppm in under 3 min. This is attributed to a three-fold elevation in the critical micelle concentration (CMC) of SDS in the presence of methanol, combined with a reduction in the SDS to protein binding ratio in methanol (0.3 g SDS/g protein). MS analysis of membrane proteins isolated from the methanol-assisted workflow revealed enhanced proteome detection, particularly for proteins whose pI contributed a minimal net charge and therefore possessed reduced solubility in a purely aqueous solvent. This protocol presents a robust approach for the preparation of membrane proteins by maximizing their solubility in MS-compatible solvents, offering a tool to advance membrane proteome characterization.

Development of Simultaneous Drug Concentration Measurement Method Using an Automated Pretreatment Liquid Chromatography/Tandem Mass Spectrometry System for Therapeutic Drug Monitoring.

Therapeutic drug monitoring (TDM) is a personalized treatment approach that involves optimizing drug dosages based on patient-specific factors, such as drug plasma concentrations, therapeutic efficacy, or adverse reactions. The plasma concentration of drugs is determined using liquid chromatography/tandem mass spectrometry (LC-MS/MS) or various immunoassays. Compared with immunoassays, LC-MS/MS requires more pretreatment time as the number of samples increases. Recently, fully automated pretreatment LC-MS/MS systems have been developed to automatically perform whole-sample pretreatment for LC-MS/MS analysis. In this study, we developed a method for simultaneous concentration determination of five analytes (clozapine, mycophenolic acid, sunitinib, N-desethylsunitinib, and voriconazole) using LC-MS/MS for clinical TDM using a fully automated LC-MS/MS pretreatment system. In the developed method, the intra- and inter-assay relative error (RE) values ranged between -14.8% and 11.3%; the intra- and inter-assay coefficient of variation (CV) values were <8.8% and <10.5%, respectively. The analytes showed good stability, with RE values ranging between -13.6% and 10.9% and CV values <8.9%. Furthermore, the plasma concentrations in clinical samples using this method and the conventional manual pretreatment method showed similar results. Therefore, the method developed in this study could be considered a useful pretreatment method for routine TDM in patients.

The Development of a 3D Printer-Inspired, Microgravity-Compatible Sample Preparation Device for Future Use Inside the International Space Station.

Biological testing on the International Space Station (ISS) is necessary in order to monitor the microbial burden and identify risks to crew health. With support from a NASA Phase I Small Business Innovative Research contract, we have developed a compact prototype of a microgravity-compatible, automated versatile sample preparation platform (VSPP). The VSPP was built by modifying entry-level 3D printers that cost USD 200-USD 800. In addition, 3D printing was also used to prototype microgravity-compatible reagent wells and cartridges. The VSPP's primary function would enable NASA to rapidly identify microorganisms that could affect crew safety. It has the potential to process samples from various sample matrices (swab, potable water, blood, urine, etc.), thus yielding high-quality nucleic acids for downstream molecular detection and identification in a closed-cartridge system. When fully developed and validated in microgravity environments, this highly automated system will allow labor-intensive and time-consuming processes to be carried out via a turnkey, closed system using prefilled cartridges and magnetic particle-based chemistries. This manuscript demonstrates that the VSPP can extract high-quality nucleic acids from urine (Zika viral RNA) and whole blood (human RNase P gene) in a ground-level laboratory setting using nucleic acid-binding magnetic particles. The viral RNA detection data showed that the VSPP can process contrived urine samples at clinically relevant levels (as low as 50 PFU/extraction). The extraction of human DNA from eight replicate samples showed that the DNA extraction yield is highly consistent (there was a standard deviation of 0.4 threshold cycle when the extracted and purified DNA was tested via real-time polymerase chain reaction). Additionally, the VSPP underwent 2.1 s drop tower microgravity tests to determine if its components are compatible for use in microgravity. Our findings will aid future research in adapting extraction well geometry for 1 g and low g working environments operated by the VSPP. Future microgravity testing of the VSPP in the parabolic flights and in the ISS is planned.

Urine-HILIC: Automated Sample Preparation for Bottom-Up Urinary Proteome Profiling in Clinical Proteomics.

Urine provides a diverse source of information related to a patient's health status and is ideal for clinical proteomics due to its ease of collection. To date, most methods for the preparation of urine samples lack the throughput required to analyze large clinical cohorts. To this end, we developed a novel workflow, urine-HILIC (uHLC), based on an on-bead protein capture, clean-up, and digestion without the need for bottleneck processing steps such as protein precipitation or centrifugation. The workflow was applied to an acute kidney injury (AKI) pilot study. Urine from clinical samples and a pooled sample was subjected to automated sample preparation in a KingFisher™ Flex magnetic handling station using the novel approach based on MagReSyn® HILIC microspheres. For benchmarking, the pooled sample was also prepared using a published protocol based on an on-membrane (OM) protein capture and digestion workflow. Peptides were analyzed by LCMS in data-independent acquisition (DIA) mode using a Dionex Ultimate 3000 UPLC coupled to a Sciex 5600 mass spectrometer. The data were searched in Spectronaut™ 17. Both workflows showed similar peptide and protein identifications in the pooled sample. The uHLC workflow was easier to set up and complete, having less hands-on time than the OM method, with fewer manual processing steps. Lower peptide and protein coefficient of variation was observed in the uHLC technical replicates. Following statistical analysis, candidate protein markers were filtered, at ≥8.35-fold change in abundance, ≥2 unique peptides and ≤1% false discovery rate, and revealed 121 significant, differentially abundant proteins, some of which have known associations with kidney injury. The pilot data derived using this novel workflow provide information on the urinary proteome of patients with AKI. Further exploration in a larger cohort using this novel high-throughput method is warranted.

Automated HPLC-MS/MS assay for the simultaneous determination of ten plasma antibiotic concentrations.

Therapeutic drug monitoring (TDM) of antibiotics (ATB) in patients with serious bacterial infections allows optimization of the efficacy of the treatment while reducing the risk of toxicity. Notably, early measurement of plasma beta-lactam concentration has been shown to be associated with reduced mortality in intensive care patients. In this context, a rapid, robust, and accurate assay method is essential for daily TDM. A fully automated procedure for quantification of the plasma concentrations of ten ATB was developed. The ATB were divided into two calibration pools, with Pool 1: aztreonam, ceftobiprole, cefoxitin, avibactam, tazobactam and Pool 2: metronidazole, ceftriaxone, daptomycin, ceftolozane, moxifloxacin. Sample preparation consisting of acetonitrile plasma protein precipitation and H20 dilution was applied to all analytes. This procedure was carried out by an automated sample preparation system directly coupled to a liquid chromatography-tandem mass spectrometry (LC-MS/MS) system. Since the instrument extracts sample n while sample n-1 is in the LC-MS/MS system, the delay between obtaining the results for two samples corresponds to the analytical run time, which is less than 7 min. The method was validated according to the Food and Drug Administration guidelines. The method was sensitive (lower limit of quantification 0.1-1 mg/L, depending on the ATB), accurate (intra/inter-assay bias -14.8 to 14.2 %) and precise (intra/inter-assay CVs 1.27 to 16.3 %). Application of the TDM assay was illustrated by the report of an intensive care patient treated with the ceftazidime/aztreonam/avibactam combination. Four assays were performed in 8 days with results returned within 24 h to quickly manage the dose regimen in this patient. An automated, simple, rapid, robust LC-MS/MS analysis was developed and validated for the simultaneous quantification of plasma concentrations of 10 ATB and was applied with success to perform TDM. This method provides a shorter turnaround time than classic sample batch-based analytical methods.

Automated workflow utilizing saponification and improved epoxidation for the sensitive determination of mineral oil saturated and aromatic hydrocarbons in edible oils and fats.

Refined edible oils and fats are known to contain olefins resisting the typical epoxidation used for the sample preparation of mineral oil saturated and aromatic hydrocarbons (MOSH and MOAH). These olefins can be misinterpreted as MOAH and are therefore an important reason for inconsistent results between laboratories. Collaborative trials confirm this assumption for low MOAH contents near the quantitation limits regularly. In the scope of this work, a new epoxidation approach was developed. Persistent olefins in refined oils could be successfully epoxidized with performic acid. The reaction kinetics was investigated using model substances for biogenic olefins and MOAH. It was rationalized why certain olefins resist epoxidation and which MOAH can potentially get lost. A prominent peak cluster in the MOAH fraction of refined palm oils could be identified by means of GC-MS and explained why it cannot be epoxidized. Based upon this, an automated and streamlined workflow for sample preparation and analysis was composed tackling major problems identified in previously published methods. Optimized and miniaturized saponification, extraction, epoxidation, and enrichment paired with online LC-GC-FID led to a robust method that was tested and validated for edible oils and fats (RSDR < 7% for MOSH and MOAH at values of 14.9 and 2.1 mg/kg, respectively). Due to increased sample amount and minimized blank values, quantitation limits below 1 mg/kg for MOSH and MOAH were achieved. The trueness of the method was verified by analyzing collaborative trial samples.

Fully Automated Quantitative Measurement of Serum Organic Acids via LC-MS/MS for the Diagnosis of Organic Acidemias: Establishment of an Automation System and a Proof-of-Concept Validation.

Gas chromatography-mass spectrometry has been widely used to analyze hundreds of organic acids in urine to provide a diagnostic basis for organic acidemia. However, it is difficult to operate in clinical laboratories on a daily basis due to sample pretreatment processing. Therefore, we aimed to develop a fully automated system for quantifying serum organic acids using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The pretreatment CLAM-2030 device was connected to an LC-MS/MS system for processing serum under optimized conditions, which included derivatizing serum organic acids using 3-Nitrophenylhydrazine. The derivatized organic acids were separated on a reverse-phase Sceptor HD-C column and detected using negative-ion electrospray ionization multiple reaction monitoring MS. The automated pretreatment-LC-MS/MS system processed serum in less than 1 h and analyzed 19 serum organic acids, which are used to detect organic acidemias. The system exhibited high quantitative sensitivity ranging from approximately 2 to 100 µM with a measurement reproducibility of 10.4% CV. Moreover, a proof-of-concept validation of the system was performed using sera from patients with propionic acidemia (n = 5), methylmalonic acidemia (n = 2), and 3-methylcrotonylglycinuria (n = 1). The levels of marker organic acids specific to each disease were significantly elevated in the sera of the patients compared to those in control samples. The automated pretreatment-LC-MS/MS system can be used as a rapid in-hospital system to measure organic acid levels in serum for the diagnosis of organic acidemias.

Optimization of Automated Sample Preparation for Vitamin D Determination on a Biomek i7 Workstation.

Vitamin D belongs to the fat-soluble vitamins and is an integral part of bone metabolism. In the human body, a decreased vitamin D level can be an additional risk factor for diseases like cancer, diabetes, and mental diseases. As a result, an enormous increase in the demand for vitamin D testing has been observed in recent years, increasing the demand for powerful methods for vitamin D determination at the same time.Automation is the key factor in increasing sample throughput. This study compares three fully automated sample preparation methods for the determination of 25(OH)D2 and 25(OH)D3 in plasma and serum samples. Starting from a semiautomated reference method, the method is tested manually and subsequently fully automated on the Biomek i7 Workstation by integrating a centrifuge and a positive pressure extractor into the workstation. Alternatively, the centrifugation for the separation of protein aggregates and supernatant is replaced by a filter plate. Finally, the sample throughput is further increased by using phospholipid removal cartridges. The results show that phospholipid removal significantly increases the recovery rates in liquid chromatography-mass spectrometry. With the phospholipid removal cartridges, recovery rates of 97.36% for 25(OH)D2 and 102.5% for 25(OH)D3 were achieved, whereas with the automated classic automated preparation method, the recovery rates were 83.31% for 25(OH)D2 and 86.54% for 25(OH)D3. In addition to the technical evaluation, the different methods were also examined with regard to their economic efficiency. Finally, the qualitative and quantitative performance of the developed methods is benchmarked with a selected semiautomatic reference method.