Parameter Optimization for Feature and Hit Generation in a General Unknown Screening Method—Proof of Concept Study Using a Design of Experiment Approach for a High Resolution Mass Spectrometry Procedure after Data Independent Acquisition

Definitive Screening Designs to Optimize Library-Free DIA-MS Identification and Quantification of Neuropeptides

Method optimization is crucial for successful mass spectrometry (MS) analysis. However, extensive method assessments, altering various parameters individually, are rarely performed due to practical limitations regarding time and sample quantity. To maximize sample space for optimization while maintaining reasonable instrumentation requirements, a definitive screening design (DSD) is leveraged for systematic optimization of data-independent acquisition (DIA) parameters to maximize crustacean neuropeptide identifications. While DSDs require several injections, a library-free methodology enables surrogate sample usage for comprehensive optimization of MS parameters to assess biomolecules from limited samples. We identified several parameters contributing significant first- or second-order effects to method performance, and the DSD model predicted ideal values to implement. These increased reproducibility and detection capabilities enabled the identification of 461 peptides, compared to 375 and 262 peptides identified through data-dependent acquisition (DDA) and a published DIA method for crustacean neuropeptides, respectively. Herein, we demonstrate a DSD optimization workflow, using standard material, not reliant on spectral libraries for the analysis of any low abundance molecules from previous samples of limited availability. This extends the DIA method to low abundance isoforms dysregulated or only detectable in disease samples, thus improving characterization of previously inaccessible biomolecules, such as neuropeptides. Data are available via ProteomeXchange with identifier PXD038520.

LC-QTOF-MS Presumptive Identification of Synthetic Cannabinoids without Reference Chromatographic Retention/Mass Spectral Information. II. Evaluation of a Computational Approach for Predicting and Identifying Unknown High-Resolution Product Ion Mass Spectra

Despite liquid chromatography-high-resolution tandem mass spectrometry (MS2) enables untargeted acquisition, data processing in toxicological screenings is almost invariably performed in targeted mode. We developed a computational approach based on open source chemometrics software that, starting from a suspected synthetic cannabinoid (SC) determined formula, searches for isomers in different new psychoactive substances web databases, predicts retention time (RT) and high-resolution MS2 spectrum, and compares them with the unknown providing a rank-ordered candidates list. R was applied on 105 SC measured data to develop and validate a multiple linear regression quantitative structure-activity relationship model predicting RT. Competitive Fragmentation Modeling for Metabolite Identification (CFM-ID) freeware was used to predict/compare spectra with Jaccard similarity index. Data-dependent acquisition was performed with an Agilent Infinity 1290 LC-6550 iFunnel Q-TOF MS with ZORBAX Eclipse-Plus C18 (100 × 2.1 mm2/1.8 µm) in water/acetonitrile/ammonium formate gradient. Ability of the combined RT/MS2 prediction to identify unknowns was evaluated on SC standards (with leave-one-out from the RT model) and on unexpected SC encountered in real cases. RT prediction reduced the number of isomers retrieved from a group of new psychoactive substances web databases to one-third (2,792 ± 3,358→845 ± 983) and differentiated between SC isomers when spectra were not selective (4F-MDMB-BUTINACA, 4F-MDMB-BUTINACA 2'-indazole isomer) or unavailable (4CN-Cumyl-B7AICA, 4CN-Cumyl-BUTINACA). When comparing 30/40 eV measured spectra of 99 SC against RT-selected, CFM-ID predicted spectra of isomers, the right candidate ranked 1st on median and 4th on average; 54% and 88% of times the right match ranked 1st or within the first 5 matches, respectively. To our knowledge, this is the first case of extensive chemometrics application to toxicological screening. In most cases, presumptive identification (being based on computation, it requires further information for confirmation) of unexpected SC was achieved without reference measured information. This method is currently the closest possible to true unbiased/untargeted screening. The bottleneck of the method is the processing time required to predict mass spectra (ca. 30-35 s/compound using a 64-bit 2.50-GHz Intel® Core™ i5-7200U CPU). However, strategies can be implemented to reduce prediction processing time.

Optimization of Factor Combinations for Stem Cell Differentiations on a Design-of-Experiment Microfluidic Chip

Directed differentiation of stem cells plays a vital role in cell replacement therapy. Many activators and inhibitors targeting different signaling pathways have been identified to contribute to each step of differentiation. Most studies relied on empirically optimizing the combinations of the aforementioned factors for each step to optimize the efficiency of differentiation, which are time-consuming and nonsystematic. Design-of-experiment (DOE) is a powerful strategy to identify the critical combinations from multiple factors systematically. However, it is prohibitively complicated for typical laboratories, given a large number of potential combinations. Here, we develop a multilayer polymethyl methacrylate-based, reusable microfluidic chip to directly facilitate the DOE in the differentiation of stem cells. The chip consists of an inlet layer and multiple disperse layers. Different solutions are injected simultaneously to the chip through the inlet layer. Subsequently, the channels in the disperse layers split and recombine the flow streams to generate solution combinations based on hard-wired DOE designs. We demonstrated that it is in quantitative agreement with the designs using fluorescent dyes. Moreover, we constructed a human-induced pluripotent stem reporter cell line to improve the consistency of the cellular state measurements and use the chip to identify critical factors for cell differentiation to definitive endoderm (DE). We found that the differentiation efficiencies under various factor combinations are significantly different, and CHIR99201 and GDF8 are the most critical factors for differentiation to DE. Our method is potentially applicable to the optimization of factor combinations for multi-step stem cell differentiation and combinatorial drug screening.

Comparison of the Polyphenolic Profile of Medicago sativa L. and Trifolium pratense L. Sprouts in Different Germination Stages Using the UHPLC-Q Exactive Hybrid Quadrupole Orbitrap High-Resolution Mass Spectrometry

Identification and quantification of polyphenols in plant material are of great interest since they make a significant contribution to its total bioactivity. In the present study, an UPLC-Orbitrap-MS/MS approach using the variable data acquisition mode (vDIA) was developed and applied for rapid separation, identification, and quantification of the main polyphenolic compounds in Medicago sativa L. and Trifolium pratense L. sprouts in different germination stages. Based on accurate MS data and fragment ions identification strategy, a total of 29 compounds were identified by comparing their accurate masses, fragment ions, retention times, and literatures. Additionally, a number of 30 compounds were quantified by comparing to the reference standards. Data were statistically analysed. For both plant species, the sprouts of the third germination day are valuable sources of bioactive compounds and could be used in phytotherapy and nutrition. Although Trifolium pratense L. (Red Clover) is considered to be a reference for natural remedies in relieving menopause disorders, alfalfa also showed a high level of biological active compounds with estrogenic activity.

Comparison of data acquisition modes with Orbitrap high-resolution mass spectrometry for targeted and non-targeted residue screening in aquacultured eel

RATIONALE

A current trend in monitoring chemical contaminants in animal products is to use high-resolution mass spectrometry (HRMS). In this study, several HRMS data acquistion modes using Orbitrap MS for simultaneous full-scan MS in combination with MS2 analysis were evaulated for their effectiveness in detecting and identifying both targeted and non-targeted veterinary drug residues in aquacultured eel samples.

METHODS

Sample preparation consisted of an acidic acetonitrile extraction with solid-phase extraction cleanup for analysis using LC/HRMS. Different data acquisition methods, including full-scan MS with non-targeted all ion fragmentation (AIF), multiplexed or variable data-independent analysis (mDIA or vDIA), targeted data-dependent MS2 (DDMS2), and parallel reaction monitoring (PRM) acquisition, were explored. The methods were evaluated with fortified eel tissue and imported eel samples to determine how many analytes could be detected and identified.

RESULTS

For non-targeted data acquisition, the number of analytes detected using DIA methods matched the results obtained by AIF, but the resulting product ion scans were more diagnostic because characteristic ions were predominant in the DIA MS2 spectra. In targeted analysis for a limited list of 68 compounds, full-scan MS followed by PRM was advantageous compared with DDMS2 because high-quality MS2 spectra were generated for almost all the analytes at target testing levels.

CONCLUSIONS

For residue screening, AIF has fast MS1 scan speed with adequate detection of product ions but may lead to false positive findings. DIA methods are better suited to monitor for both targeted and non-targeted compounds because they generate more characteristic MS2 spectra for retrospective library searching. For follow-up targeted analysis, PRM is prefered over DDMS2 when searching for a limited set of compounds.

Using Sesame Seed Oil to Preserve and Preconcentrate Cannabinoids for Paper Spray Mass Spectrometry

Cannabinoids present a unique set of analytical challenges. An increasing number of states have voted to decriminalize recreational marijuana use, creating a need for new kinds of rapid testing. At the same time, synthetic compounds with activity similar to THC, termed synthetic cannabinoids, have become more prevalent and pose significant health risks. A rapid method capable of detecting both natural and synthetic cannabinoids would be useful in cases of driving under the influence of drugs, where it might not be obvious whether the suspect consumed marijuana, a synthetic cannabinoid, or both. Paper spray mass spectrometry is an ambient ionization technique which allows for the direct ionization of analyte from a biofluid spot on a piece of paper. Natural cannabinoids like THC, however, are labile and rapidly disappear from dried sample spots, making it difficult to detect them at clinically relevant levels. Presented here is a method to concentrate and preserve THC and synthetic cannabinoids in urine and oral fluid on paper for analysis by paper spray mass spectrometry. Sesame seed oil was investigated both as a means of preserving THC and as part of a technique, termed paper strip extraction, wherein urine or oral fluid is flowed through an oil spot on a strip of paper to preconcentrate cannabinoids. This technique preserved THC in dried biofluid samples for at least 27 days at room temperature; paper spray MS/MS analysis of these preserved dried spots was capable of detecting THC and synthetic cannabinoids at low ng/mL concentrations, making it suitable as a rapid screening technique. The technique was adapted to be used with a commercially available autosampler.