Optimal Collision Energy Research Articles

Online ligand screening for cytochrome C from herbal medicines through “four-in-one” measurement

Affinity-oriented online ligand screening with LC coupled to different detectors is widely popular to capture active compounds from herbal medicines (HMs). However, false-positive extensively occurs because insufficient information is recorded for the existence and stability of ligand-protein complex. Here, efforts were made to advance the hit confidences via configuring post-column infusion-LC–energy-resolved-affinity MS (PCI-LC–ER-AMS) to achieve “four-in-one” monitoring of: 1) response decrement of potential ligands; 2) response decrement of protein; 3) ions relating to ligand-protein complexes; and 4) ligand-protein binding strength. Ligand fishing for Cyt C from HMs was conducted as a proof-of-concept. For utility justification, a mimic sample containing twelve well-defined ligands and two negative controls underwent LC separation and met Cyt C prior to Qtof-MS measurements. Compared to Cyt C- or ligand-free assay, twelve ligands instead of negative controls showed response decrements that were consistent with twelve negative peaks observed at retention times corresponding to the ligands in Cyt C ion current chromatogram. Serial ions correlating to each ligand-Cyt C complex were observed. After recording breakdown graphs, optimal collision energy (OCE) corresponding to the non-covalent bond dissociation was positively correlated with binding strength. Two HMs including Scutellariae Radix (SR) and Aconiti Lateralis Radix Preparata were investigated. Consequently, 24 compounds were merely fished from SR, and particularly, flavonoid glycosides exhibited greater OCEs and also binding strengths over aglycones. Affinity assays and cellular evaluations consolidated the significant interactions between each captured compound and Cyt C. Overall, PCI-LC–ER-AMS is eligible for confidence-enhanced online ligand screening for Cyt C from HMs through “four-in-one” measurement.

A Reverse Thinking Based on Partially Methylated Aldononitrile Acetates to Analyze Glycoside Linkages of Polysaccharides Using Liquid Chromatography-Multiple Reaction Monitoring Mass Spectrometry.

Glycoside linkage analyses of medicine and food homologous plant polysaccharides have always been a key point and a difficulty of structural characterization. The gas chromatography-mass spectrometry (GC-MS) method is one of the commonly used traditional techniques to determine glycoside linkages via partially methylated alditol acetates and aldononitrile acetates (PMAAs and PMANs). Due to the simplicity of derivatization and the highly structural asymmetry of PMANs, reverse thinking is proposed using liquid chromatography-electrospray ionization-multiple reaction monitoring mass spectrometry (LC-ESI-MRM-MS) for the first time to directly determine the neutral and acidic glycosyl linkages of polysaccharides. The complete characterization of glycoside linkages deduced from PMANs was achieved using a combination of tR values, characteristic MRM ion pairs, diagnostic ESI+-MS/MS fragmentation ions (DFIs), and optimal collision energy (OCE). The DFI and OCE parameters were confirmed to be effective for the auxiliary discrimination of some isomers of the PMANs. The practicality of LC-ESI+-MRM-MS was further verified by analyzing the glycoside linkages of polysaccharides in five medicine and food homologous plants. This method can serve as an alternative to GC-MS for the simultaneous determination of neutral and acidic glycosyl linkages in polysaccharides.

Quantitative comparison of bile acid glucuronides sub-metabolome between intrahepatic cholestasis and healthy pregnant women.

Because of the pathological indication and the physiological functions, bile acids (BAs) have occupied the research hotspot in recent decades. Although extensive efforts have been paid onto BAs sub-metabolome characterization, as the subfamily, BA glucuronides (gluA-BAs) profile is seldom concerned. Here, we made efforts to develop a LC-MS/MS program enabling quantitative gluA-BAs sub-metabolome characterization and to explore the differential species in serum between intrahepatic cholestasis of pregnancy (ICP) patients and healthy subjects. To gain as many authentic gluA-BAs as possible, liver microsomes from humans, rats, and mice were deployed to conjugate glucuronyl group to authentic BAs through in vitro incubation. Eighty gluA-BAs were captured and subsequently served as authentic compounds to correlate MS/MS spectral behaviors to structural features using squared energy-resolved MS program. Optimal collision energy (OCE) of [M-H]->[M-H-176.1]- was jointly administrated by [M-H]- mass and glucuronidation site, and identical exciting energies corresponding to 50% survival rate of 1st-generation fragment ion (EE50) were observed merely when the aglycone of a gluA-BA was consistent with the suspected structure. Through integrating high-resolution m/z, OCE, and EE50 information to identify gluA-BAs in a BAs pool, 97 ones were found and identified, and further, quantitative program was built for all annotated gluA-BAs by assigning OCEs to [M-H]->[M-H-176.1]- ion transitions. Quantitative gluA-BAs sub-metabolome of ICP was different from that of the healthy group. More GCDCA-3-G, GDCA-3-G, TCDCA-7-G, TDCA-3-G, and T-β-MCA-3-G were distributed in the ICP group. Above all, this study not only offered a promising analytical tool for in-depth gluA-BAs sub-metabolome characterization, but also clarified gluA-BAs allowing the differentiation of ICP and healthy subjects.

MSe Collision Energy Optimization for the Analysis of Membrane Proteins Using HDX-cIMS.

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) has evolved as an essential technique in structural proteomics. The use of ion mobility separation (IMS) coupled to HDX-MS has increased the applicability of the technique to more complex systems and has been shown to improve data quality and robustness. The first step when running any HDX-MS workflow is to confirm the sequence and retention time of the peptides resulting from the proteolytic digestion of the nondeuterated protein. Here, we optimized the collision energy ramp of HDMSE experiments for membrane proteins using a Waters SELECT SERIES cIMS-QTOF system following an HDX workflow using Phosphorylase B, XylE transporter, and Smoothened receptor (SMO) as model systems. Although collision energy (CE) ramp 10-50 eV gave the highest amount of positive identified peptides when using Phosphorylase B, XylE, and SMO, results suggest optimal CE ramps are protein specific, and different ramps can produce a unique set of peptides. We recommend cIMS users use different CE ramps in their HDMSE experiments and pool the results to ensure maximum peptide identifications. The results show how selecting an appropriate CE ramp can change the sequence coverage of proteins ranging from 4 to 94%.

A strategy of combining energy‐resolved mass spectrometry and density functional theory for the recognition of forsythoside isomers

RationaleIsomerism is very common in nature, and the mass spectrometry (MS) behavior of isomers is highly similar, making their spectral analysis and identification difficult. Computational chemistry can effectively assist the study of MS spectra and molecule structures. Herein, three isomers of forsythoside (For‐A, For‐H, and For‐I) were successfully identified using energy‐resolved MS combined with density functional theory (DFT).MethodsThe MS scan spectra of the isomers were collected in electrospray ionization MS. The possible positive/negative ion adduct sites were investigated using the DFT method, and the molecular formation energy of each precursor ion was obtained. In the multireaction monitoring mode, the spectra of the common precursor ion → product ion pair of the three isomers were acquired under different collision energy, and the optimal collision energy (OCE) and maximum relative intensity (MRI) of each product ion were obtained. The energy of the broken chemical bond was calculated.ResultsThe experimental data showed that the product ions of [M + H]+ of the three isomers have the greatest differences in OCE and MRI and were the most suitable to distinguish the three isomers. The DFT data showed that there was a good positive correlation between the bond fragmentation energy calculated by the quasi‐molecular ion model and OCE. The results indicated that the energy of precursor ions and corresponding fragments could be correlated with their experimental spectra.ConclusionsA strategy of combining energy‐resolved MS and DFT was implemented on the recognition of forsythoside isomers, and this strategy was expected to be applied to the identification of more isomers.

Can We Boost N-Glycopeptide Identification Confidence? Smart Collision Energy Choice Taking into Account Structure and Search Engine.

High confidence and reproducibility are still challenges in bottom-up mass spectrometric N-glycopeptide identification. The collision energy used in the MS/MS measurements and the database search engine used to identify the species are perhaps the two most decisive factors. We investigated how the structural features of N-glycopeptides and the choice of the search engine influence the optimal collision energy, delivering the highest identification confidence. We carried out LC-MS/MS measurements using a series of collision energies on a large set of N-glycopeptides with both the glycan and peptide part varied and studied the behavior of Byonic, pGlyco, and GlycoQuest scores. We found that search engines show a range of behavior between peptide-centric and glycan-centric, which manifests itself already in the dependence of optimal collision energy on m/z. Using classical statistical and machine learning methods, we revealed that peptide hydrophobicity, glycan and peptide masses, and the number of mobile protons also have significant and search-engine-dependent influence, as opposed to a series of other parameters we probed. We envisioned an MS/MS workflow making a smart collision energy choice based on online available features such as the hydrophobicity (described by retention time) and glycan mass (potentially available from a scout MS/MS). Our assessment suggests that this workflow can lead to a significant gain (up to 100%) in the identification confidence, particularly for low-scoring hits close to the filtering limit, which has the potential to enhance reproducibility of N-glycopeptide analyses. Data are available via MassIVE (MSV000093110).

Application of Skyline software for detecting prohibited substances in doping control analysis.

As the number of prohibited drugs has been progressively increasing and analytical methods for detecting such substances are renewed continuously for doping control, the need for more sensitive and accurate doping analysis has increased. To address the urgent need for high throughput and accurate analysis, liquid chromatography with tandem mass spectrometry is actively utilized in case of most of the newly designated prohibited substances. However, because all mass spectrometer vendors provide data processing software that is incapable of handling other instrumental data, it is difficult to cover all doping analysis procedures, from method development to result reporting, on one platform. Skyline is an open-source and vendor-neutral software program invented for the method development and data processing of targeted proteomics. Recently, the utilization of Skyline has been expanding for the quantitative analysis of small molecules and lipids. Herein, we demonstrated Skyline as a simple platform for unifying overall doping control, including the optimization of analytical methods, monitoring of data quality, discovery of suspected doping samples, and validation of analytical methods for detecting newly prohibited substances. For method optimization, we selected the optimal collision energies for 339 prohibited substances. Notably, 195 substances exhibited a signal intensity increase of >110% compared with the signal intensity of the original collision energy. All data related to method validation and quantitative analysis were efficiently visualized, extracted, or calculated using Skyline. Moreover, a comparison of the time consumed and the number of suspicious samples screened in the initial test procedure highlighted the advantages of using Skyline over the commercially available software TraceFinder in doping control.

Characterization of the metabolic fate of sinapic acid in rats.

Sinapic acid (SA) is ubiquitously distributed in the plant kingdom as a free organic acid and more frequently as a biosynthetic pioneer for SA derivatives, e.g., SA esters. Broad biological and pharmacological activities have been disclosed for SA. Because of the metabolism lability property, metabolites instead of the parent compound should be the primary forms after oral treatment of SA, and those metabolites should also be rapidly observed from SA following administration of SA derivative. Hence, the metabolites might provide a primary contribution to the pharmacological properties of SA; however, the metabolite profile remains unclear. Here, our efforts were devoted to addressing this issue through deploying online energy-resolved mass spectrometry (ER-MS) to accomplish isomer identification which is the key issue hindering metabolite identification, notably those conjugated metabolites. After recording breakdown graphs of concerned fragment ions with online ER-MS, the positive correlations between optimal collision energy (OCE) and bond dissociation energy (BDE) were applied to assign candidate structures to isomeric signals. Moreover, in vitro metabolism with liver cellular subfractions, UV-triggered cis-/trans-configuration transformation, and wet-chemistry hydrogenation were carried out to justify the structures. As a result, sixteen metabolites (M1-M16) were found and confirmatively identified in rat plasma and urine following SA administration, and sulfation, glucuronidation, demethylation, reduction, and dihydroxylation served as the primary metabolic channels. Noteworthily, greater distribution occurred for sulfation and glucuronidation products while inferior distributions were observed for phase I metabolites, and the half-life (T1/2) of most metabolites was greater than that of SA. This study provides a comprehensive insight into the metabolic fate of SA. More importantly, the fortification of online ER-MS and quantum structure calculation to the conventional LC-MS program is eligible to achieve unambiguous identification of isomeric metabolites.

Optimum collision energies for proteomics: The impact of ion mobility separation.

Ion mobility spectrometry (IMS) is a widespread separation technique used in various research fields. It can be coupled to liquid chromatography-mass spectrometry (LC-MS/MS) methods providing an additional separation dimension. During IMS, ions are subjected to multiple collisions with buffer gas, which may cause significant ion heating. The present project addresses this phenomenon from the bottom-up proteomics point of view. We performed LC-MS/MS measurements on a cyclic ion mobility mass spectrometer with varied collision energy (CE) settings both with and without IMS. We investigated the CE dependence of identification score, using Byonic search engine, for more than 1000 tryptic peptides from HeLa digest standard. We determined the optimal CE values-giving the highest identification score-for both setups (i.e., with and without IMS). Results show that lower CE is advantageous when IMS separation is applied, by 6.3 V on average. This value belongs to the one-cycle separation configuration, and multiple cycles may supposedly have even larger impact. The effect of IMS is also reflected in the trends of optimal CE values versus m/z functions. The parameters suggested by the manufacturer were found to be almost optimal for the setup without IMS; on the other hand, they are obviously too high with IMS. Practical consideration on setting up a mass spectrometric platform hyphenated to IMS is also presented. Furthermore, the two CID (collision induced dissociation) fragmentation cells of the instrument-located before and after the IMS cell-were also compared, and we found that CE adjustment is needed when the trap cell is used for activation instead of the transfer cell. Data have been deposited in the MassIVE repository (MSV000090944).

Deciphering and investigating fragment mechanism of quinolones using multi-collision energy mass spectrometry and computational chemistry strategy.

Quinolones show characteristic fragments in mass spectrometry (MS) analysis due to their common core structures, and energy-dependent differences among these fragments are generated through the same fragmentation pathway of different molecules. Computational chemistry, which provides quantitative results of molecule parameters, is helpful for investigating the mechanisms of chemistry. MS/MS spectra of five quinolones, namely norfloxacin (NOR), enoxacin (ENO), enrofloxacin (ENR), gatifloxacin (GAT), and lomefloxacin (LOM), were acquired for deciphering fragmentation pathways under multi-collision energy (CE). Computational methods were used for excluding little possibility pathways from the point of view of energy and stable conformations, whereas optimized collision energy (OCE) and maximum relative intensity (MRI) of major competitive fragments were investigated and confirmed using computational results. Fragmentation results of NOR, ENO, ENR, and GAT were deciphered using experimental and computational data, of which fragmentation regularities were summarized. Fragmentation pathways of LOM were deciphered under the guidance of foregoing regularities. Meanwhile, the whole process was validated by comparing OCE and MRI and computational energy results, which showed good agreement. A strategy for explaining quinolone fragmentation results of multi-CE values and deciphering fragment mechanism using computational methods was developed. Relevant data and strategy may provide ideas for how to design and decipher new drug molecules with similar structures.

High-level structural analysis of proanthocyanidins using full collision energy ramp-MS2 spectrum

Proanthocyanidins (PACs) refer to a group of polyphenols consisting of flavan-3-ol units, and are ubiquitously distributed in fruits, vegetables, nuts and grains. PACs possess high-level structural diversity because of the fickle linkage manners amongst units, the polymerization degree and stereoisomeric forms, thus leading to a great challenge for structural analysis. Although LC−MS/MS currently serves as the workhorse to profile PACs in complicated matrices, it’s still challenging to achieve confirmatively structural annotation even employing the cutting-edged high-resolution MS/MS techniques, and the key technical obstacle lies at isomeric discrimination. To pursue as many auxiliary structural clues as possible, full collision energy ramp-MS2 (FCER-MS2) spectrum was conceptually designed here to involve all mass fragmentation behaviors of a given compound, such as m/z, optimal collision energy (OCE) and the maximal relative ion intensity (RIImax) aiming to advance the structural annotation confidences of PACs through reliably differentiating isomers. Thirteen authentic compounds were collected to mine relationships between chemical structures and FCER-MS2 spectra that were correlated by three progressive steps: (1) recording MS/MS spectrum by LC–Q-TOF-MS; (2) proposing mass fragmentation pathways to assign those obvious fragment ion species; and (3) acquiring breakdown graph for each concerned fragment ion species by programming online energy-resolved mass spectrometry to compose FCER-MS2 spectrum. Afterwards, the rules were applied for PACs-focused chemical characterization of a medicinal herb namely Indigofera stachyodes (Chinese name: Xuerenshen), and as a result, 22 PACs were captured and more importantly, isomerically identified by deciphering FCER-MS2 spectra. Therefore, FCER-MS2 spectrum provides a promising way to achieve in-depth isomeric discrimination of, but not limited to, PACs.

Full Collision Energy Ramp-MS2 Spectrum in Structural Analysis Relying on MS/MS.

Albeit frequently being overlooked, MS2 spectrum variation against collision energy (CE) implies auxiliary structural clues for m/z values. Online energy-resolved MS (ER-MS) provides the opportunity to acquire the trajectory of ion intensity against CE for any fragment ion of interest, thus exactly offering the desired momentum to empower the conventional MS2 spectrum at a certain CE forward to a full-CE ramp MS2 spectrum (FCER-MS2). Efforts were made here to construct an FCER-MS2 spectrum and to evaluate its potential toward structural analysis. Flavonoids were employed as a proof of concept. MS2 spectra of 76 compounds were recorded by LC-Q-Exactive-MS, and online ER-MS was subsequently programmed using LC-Qtrap-MS to build a breakdown graph for each obvious fragment ion. After defining the greatest value amongst all regressive apices as 100%, the normalized breakdown graphs comprised an FCER-MS2 spectrum for each compound. The FCER-MS2 spectrum contained the MS2 spectrum at any CE as well as optimal CE (OCE) and maximal relative ion intensity (RIImax) of each fragment ion. Except the pronounced isomeric discrimination potential, either OCE or RIImax reflected certain structural properties, such as aglycone, glycosidic bond, and hydroxy, methoxy, and glycosyl substituents. These rules were subsequently applied for flavonoid-focused characterization of a famous herbal medicine, namely Scutellariae Radix, and high-level structural annotation was accomplished for 75 flavonoids. Above all, the FCER-MS2 spectrum includes m/z, OCEs, and RIImax features, thus facilitating confidence-advanced structural analysis.

Crime Scene Investigation: Simulated Post-mortem LC–MS/MS Analysis of Cocaine and Cocaine Metabolites in Synthetic Human Serum

This laboratory experiment introduces upper-division undergraduate analytical chemistry students to liquid chromatography–tandem mass spectrometry (LC–MS/MS) in a forensic application: the analysis of cocaine and metabolites of cocaine in simulated serum ostensibly from drug overdose victims. For this investigation, students developed the analytical methods. First, the students determined the multiple reaction monitoring (MRM) transitions and optimized collision energy. The MS methods developed were then added to an LC method for LC–MS/MS quantitation with a 2.5 min run time. Students successfully quantified the drugs and metabolites, and they were able to identify which samples indicated cocaine use and overdose.

Isomeric discrimination of kaempferol versus luteolin by online energy-resolved mass spectrometry

Isomers are widely distributed in Chinese herbal medicines,and can be discriminated by energy-resolved mass spectrometry( ER-MS). However,ER-MS was performed through direct injection of reference compounds with syringe pump,which encountered a significant technical barrier for high-throughput and automated measurements. Herein,online ER-MS was conducted using LC-MS platform,and a pair of isomers,kaempferol vs luteolin,were employed as a case study to illustrate and assess the utility of online ER-MS for isomeric discrimination. High-resolution tandem mass spectrometry data of both flavonoids were acquired on LC-QE-Orbitrap-MS,and the fragmentation pathways responsible for the primary fragment ions were proposed. The primary signal in MS1 occurred at m/z 285( [M-H]-),and the primary signals of either compound generated by retro-Diels-Alder fragmentation were observed at m/z 151 and 133. The spectral information was subsequently transferred onto LC-Qtrap-MS platform to carry out online ER-MS. Two precursor-to-product ion transition candidates were constructed as m/z 285>151 and 285>133,and either afterward derived a set of pseudo-ion transitions( PITs) and so forth,exactly corresponding to a series of progressive collision energies( eg-5,-8,-11 e V,and so on). All PITs were typed into the monitoring list of multiple reaction monitoring program to generate the peak area datasets. Either dataset was normalized using the highest values in the set and imported into Graph Pad Prism software to plot the Gaus-sian-shaped curve that was termed as the break-down graph. The apex of the regressive curve was termed as optimal collision energy( OCE). The OCE values corresponding to m/z 285>151 were calculated as-29. 06 e V and-35. 71 e V for kaempferol and luteolin,respectively. In the case of m/z 285>133,the OCEs were yielded as-44. 15 e V for kaempferol and-49. 01 e V for luteolin. With re-ference to their chemical structures,the location of hydroxyl group was regarded to be responsible for the differences of either m/z 285>151 or 285>133 between the isomers,attributing to their different bond properties. Above all,online ER-MS offers an eligible tool for isomeric discrimination,and provides meaningful information for the accurate chemical composition characterization based on LC-MS,which is not limited to Chinese herbal medicines.

Integrated Strategy Drives Direct Infusion-Tandem Mass Spectrometry as an Eligible Tool for Shotgun Pseudo-Targeted Metabolomics of Medicinal Plants.

Direct infusion (DI) has an extraordinary high-throughput advantage. Pseudo-targeted metabolomics (PTM) has been demonstrated integrating the merits of both nontargeted and targeted metabolomics. Herein, we attempted to implant DI into the PTM concept to configure a new strategy allowing shotgun PTM. First, a versatile MS/MSALL program was applied to acquire MS1 and MS2 spectra. Second, online energy-resolved MS (online ER-MS) was conducted to obtain breakdown graph as well as optimal collision energy (OCE) for each ion transition paired by precursor ion and the dominant product ion. Third, selected reaction monitoring (SRM) was responsible to output a quantitative dataset with a constant length. Moreover, breakdown graph also served as orthogonal structural evidence when matching MS2 spectra between DI-MS/MS and an in-house library to strengthen structural annotation confidence. To evaluate and illustrate the utility of the new strategy toward shotgun PTM of medicinal plants, in-depth chemome comparison was conducted within three Cistanche species, all of which are edible medicinal plants and playing essential roles for turning the deserts into the oases. A total of 185 variables participated in the quantitative measurement program. Each diagnostic ion pair was featured with an OCE. Significant species differences occurred, and echinacoside, acteoside, isoacteoside, 2'-acetyl-acteoside, tubuloside B, mannitol, sucrose, betaine, malate, as well as choline were found to be confirmative chemical markers offering primary contributions toward the species discrimination. After cross-validation with LC-MS/MS, DI-MS/MS fortified with the new strategy is an eligible tool for shotgun PTM, beyond Cistanche plants.

Liquid chromatography–three-dimensional mass spectrometry enables confirmative structural annotation of cistanoside F metabolites in rat

Clarification the existence forms, including prototype and metabolite(s) is the prerequisite for understanding in-depth the therapeutic mechanisms of a given agent, particularly when oral administration. However, it is still a long distance for unambiguous structural identification of metabolites even employing the cutting-edge MS/MS technique, and the determinant obstacle is produced by its inherent isomer-blind disadvantage. To tackle with this drawback, online energy-resolved mass spectrometry (online ER-MS) was introduced to enable isomeric discrimination after that high-resolution MS/MS provided empirical molecular formula as well as substructures. In-depth metabolic characterization of cistanoside F (CF), an effective natural product, was conducted as a proof-of-concept for the new strategy namely three-dimensional MS that was configured by MS1, MS2 and online ER-MS as 1st, 2nd, and 3rd dimensions, respectively. Sensitive metabolite detection was assisted by predictive multiple-reaction monitoring function on Qtrap-MS, and the empirical formulas of all metabolites were calculated from the quasi-molecular ions yielded from IT-TOF-MS. Subsequently, substructures of each metabolite were constructed by combining the calculated element compositions and the well-defined mass fragmentation pathways. Finally, online ER-MS was responsible to generate optimal collision energies for bonds-of-interest, and enabled rational selection among candidate structures. A total of thirteen metabolites were detected and confirmatively identified in rat after oral treatment of CF using LC–3D MS. Acyl-migration, hydrolysis and sulfation played key roles for the metabolic fate of CF. More importantly, LC–3D MS is an eligible tool to achieve confidence-enhanced structural annotation of metabolites in biological matrices because of the unique isomeric differentiation ability from online ER-MS.

Confirmative Structural Annotation for Metabolites of (R)-7,3'-Dihydroxy-4'-methoxy-8-methylflavane, A Natural Sweet Taste Modulator, by Liquid Chromatography-Three-Dimensional Mass Spectrometry.

Flavonoids occupy the largest family of natural products and possess a broad spectrum of health benefits. Their metabolites are sometimes the truly effective molecules in vivo. It is still challenging, however, to unambiguously identify flavonoid metabolites using conventional LC-MS/MS. Herein, we aimed to pursue auxiliary structural clues to m/z values in both MS1 and MS2 spectra through LC coupled to three-dimensional MS (LC-3D MS). MS1, as the first dimension, was in charge of suggesting theoretical molecular formulas, MS2, the as second dimension, was responsible for offering substructures, and exactly, online energy-resolved MS (ER-MS), as the third dimension, provided optimal collision energies (OCEs) that reflected the linkage manners among the substructures. Metabolic characterization of a natural sweet taste modulator, namely, (R)-7,3'-dihydroxy-4'-methoxy-8-methylflavane (DHMMF), was conducted as a proof-of-concept. Extensive efforts, such as full MS1 and MS2 scans on IT-TOF-MS and predictive selected-reaction monitoring mode on Qtrap-MS, were made for in-depth metabolite mining. Seventeen metabolites (M1-M17) were captured from DHMMF-treated biological samples, including 17 (M1-M17), 10 (M4-M9, M11, M13, M14, and M16), and 2 (M5 and M10) metabolites from urine, plasma, and feces, respectively. Their structures were configured by integrating MS1, MS2, and OCE information. Except M10, all metabolites were new compounds. LC-MS/MS-guided chromatographic purification yielded three glucuronyl-conjugated metabolites (M5, M8, and M11), and NMR spectroscopic assays consolidated the structures transmitted from LC-3D MS. Demethylation, glucuronidation, and sulfation occurred as the primary metabolic pathways of DHMMF. Above all, LC-3D MS bridged LC-MS/MS from putatively structural annotation toward confidence-enhanced identification, beyond the metabolite characterization of flavonoids.

First-Line Toxicological Screening with Fully Automated Extraction.

In clinical toxicology, laboratories need screening methods allowing unambiguous identification of the compounds in a short turnaround time to either confirm or exclude the hypothesis of drug overdose or poisoning with a toxicant. We developed a fully automated screening procedure designed to identify and quantify in a single run 245 compounds of interest in clinical toxicology. Sample extraction was carried out by a programmable liquid handler directly coupled to a liquid chromatography-tandem mass spectrometry (LC-MS-MS) system. Data acquisition was performed in the positive and negative ionization modes with up to 15 multiple reaction monitoring (MRM) transitions per compound, each with optimized collision energy to enable both qualitative library searching and quantitation. The method was validated according to the ISO 15189 requirements and was applied to real patient samples (n=127). The 15 MRM transitions per compound provided higher confidence for the identification of all the compounds. The quantitative method was fully validated with satisfactory intra- and inter-assay imprecision and inaccuracy with CV% lower than 20%. For only nine molecules, imprecision and inaccuracy were relatively high but never exceeded 31.7%. Comparison with dedicated quantitative methods using conventional MRM monitoring performed using 127 patient samples (n=175 pairs of measured concentrations) showed excellent correlation (R2=0.96). A robustness study showed that calibration curves prepared for up to 1 month yielded uncertainty < 20%. Retention times ranged from 0.89min for metformin to 9.72min for difenacoum. The automated sample preparation required 8min and was followed by 10min chromatographic separation. This first-line screening procedure yields high confidence in compound detection and should be useful in core labs facing clinical toxicology situations where rapid and reliable results are needed.

Improving Peptide Fragmentation for Hydrogen-Deuterium Exchange Mass Spectrometry Using a Time-Dependent Collision Energy Calculator.

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) is becoming a popular technique for interrogating biological systems. In recent years, advancements have been made to increase peptide coverage for proteins that resist digestion such as antibodies and membrane proteins. These methods commonly include using alternative digestion enzymes or longer chromatographic gradients, which may be expensive or time-consuming to implement. Here, we recommend an efficient proteomics-based approach to increase peptide confidence and coverage. A major filtering parameter for peptides in HDX is the number of product ions detected; this is a result of the collision energy (CE) applied within the MS. A traditional linear ramp achieves optimal CE for only short periods of time. More product ions will be created and detected if optimal CE can be achieved for a longer period of time. As a result, the coverage, redundancy, and data confidence are all increased. We achieved this by implementing a mobility-dependent CE look up table (LUT) which increases the CE as a function of mobility. We developed a program to calculate the optimal CE for a set of peptides and MS settings based on initial reference samples. We demonstrated the utility of the CE LUT on three protein samples including the soluble phosphorylase B, IgG2, and the membrane-stabilized AcrB. We showed that applying a CE LUT provided 8.5-50% more peptides compared to a linear CE ramp. The results demonstrate that a time-dependent CE LUT is a quick and inexpensive method to increase data confidence and peptide abundance for HDX-MS experiments.

Retention Time and Optimal Collision Energy Advance Structural Annotation Relied on LC-MS/MS: An Application in Metabolite Identification of an Antidementia Agent Namely Echinacoside.

The structural annotation of metabolites now relies heavily on HR-MS/MS information, resulting in ambiguous identities in most cases. More auxiliary evidence is therefore desired to achieve confirmative identification. Herein, we made an attempt to involve retention time (tR) along with optimal collision energy (OCE) as the additionally structural clues, and the applicability validation was conducted via confidence-enhanced metabolite characterization of echinacoside, an antidementia drug candidate within clinical trials. Quantitative structure-retention relationships (QSRR) were modeled via assaying 184 authentic compounds on RPLC, HILIC, and serially coupled RPLC and HILIC (RPLC-HILIC). Online energy-resolved MS was developed to yield breakdown graphs for selected ion transitions, and OCE was demonstrated to be superior to CE50 toward pointedly denoting the bonds-of-interest. Nineteen metabolites (M1-M19) were confidently identified in biological samples from echinacoside-treated rats by analyzing m/z values first to yield empirical formulas and substructures, and tR and OCE subsequently contributed to sift the candidate structures. Structural identification was validated by oral administration of three relevant compounds in parallel and chromatographic purification as well. Above all, the integration of retention and dissociation behaviors enabled promoting one step forward for structural annotation confidences merely relied on HR-MS/MS.