Matrix-assisted laser desorption/ionization matrix incorporation evaluation algorithm for improved peak coverage and signal-to-noise ratio in mass spectrometry imaging.

RATIONALE: Despite decades of implementation, the selection of optimal sample preparation conditions for matrix-assisted laser desorption/ionization (MALDI) imaging is still ambiguous due to the lack of a universal and comprehensive evaluation methodology. Thus, numerous experiments with different matrix application conditions accompany a translation of the method to novel sample types and matrices. METHODS: Mouse brain tissues were covered with 9-aminoacridine through sublimation, followed by recrystallization in vapors of 5% (v/v) methanol solution in water. The samples were analyzed by MALDI time-of-flight mass spectrometry, and the efficiency of lipid and small-molecule ionization was evaluated with different metrics. RESULTS: We first investigate the dependency of matrix density and recrystallization conditions on the thickness of an analyte-empty matrix layer to roughly evaluate the laser shot number required to obtain an intense signal with minimal noise. Then, we introduce metrics for the analysis of small imaging datasets (small sample regions) of model samples based on median quantity of peaks in spectra (medQP) and weighted median signal-to-noise ratio (wmSNR). The evaluation of small regions and taking median values for metrics help overcome the sample heterogeneity and allow for the simultaneous comparison of different acquisition parameters. CONCLUSIONS: Here, we propose a methodology based on gradual laser ablation of small regions of sample and further implementation of weighted signal-to-noise ratio to assess various matrix application conditions. The proposed approach helps reduce the number of test samples required to determine optimal sample preparation conditions and improve the overall quality of images.

Investigating the Metabolism of Plants Germinated in Heavy Water, D2O, and H218O-Enriched Media Using High-Resolution Mass Spectrometry.

Mass spectrometry has been an essential technique for the investigation of the metabolic pathways of living organisms since its appearance at the beginning of the 20th century. Due to its capability to resolve isotopically labeled species, it can be applied together with stable isotope tracers to reveal the transformation of particular biologically relevant molecules. However, low-resolution techniques, which were used for decades, had limited capabilities for untargeted metabolomics, especially when a large number of compounds are labelled simultaneously. Such untargeted studies may provide new information about metabolism and can be performed with high-resolution mass spectrometry. Here, we demonstrate the capabilities of high-resolution mass spectrometry to obtain insights on the metabolism of a model plant, Lepidium sativum, germinated in D2O and H218O-enriched media. In particular, we demonstrated that in vivo labeling with heavy water helps to identify if a compound is being synthesized at a particular stage of germination or if it originates from seed content, and tandem mass spectrometry allows us to highlight the substructures with incorporated isotope labels. Additionally, we found in vivo labeling useful to distinguish between isomeric compounds with identical fragmentation patterns due to the differences in their formation rates that can be compared by the extent of heavy atom incorporation.

Untargeted Lipidomics after D2O Administration Reveals the Turnover Rate of Individual Lipids in Various Organs of Living Organisms.

The administration of low doses of D2O to living organisms was used for decades for the investigation of metabolic pathways and for the measurement of the turnover rate for specific compounds. Usually, the investigation of the deuterium uptake in lipids is performed by measuring the deuteration level of the palmitic acid residue using GC-MS instruments, and to our knowledge, the application of the modern untargeted LC-MS/MS lipidomics approaches was only reported a few times. Here, we investigated the deuterium uptake for >500 lipids for 13 organs and body liquids of mice (brain, lung, heart, liver, kidney, spleen, plasma, urine, etc.) after 4 days of 100% D2O administration. The maximum deuteration level was observed in the liver, plasma, and lung, while in the brain and heart, the deuteration level was lower. Using MS/MS, we demonstrated the incorporation of deuterium in palmitic and stearic fragments in lipids (PC, PE, TAG, PG, etc.) but not in the corresponding free forms. Our results were analyzed based on the metabolic pathways of lipids.

Simple In Vitro 18O Labeling for Improved Mass Spectrometry-Based Drug Metabolites Identification: Deep Drug Metabolism Study.

The identification of drug metabolites formed with different in vitro systems by HPLC-MS is a standard step in preclinical research. In vitro systems allow modeling of real metabolic pathways of a drug candidate. Despite the emergence of various software and databases, identification of compounds is still a complex task. Measurement of the accurate mass, correlation of chromatographic retention times and fragmentation spectra are often insufficient for identification of compounds especially in the absence of reference materials. Metabolites can "slip under the nose", since it is often not possible to reliably confirm that a signal belongs to a metabolite and not to other compounds in complex systems. Isotope labeling has proved to be a tool that aids in small molecule identification. The introduction of heavy isotopes is done with isotope exchange reactions or with complicated synthetic schemes. Here, we present an approach based on the biocatalytic insertion of oxygen-18 isotope under the action of liver microsomes enzymes in the presence of 18O2. Using the local anesthetic bupivacaine as an example, more than 20 previously unknown metabolites were reliably discovered and annotated in the absence of the reference materials. In combination with high-resolution mass spectrometry and modern methods of mass spectrometric metabolism data processing, we demonstrated the ability of the proposed approach to increase the degree of confidence in interpretating metabolism data.

Incorporation of a Disposable ESI Emitter into Inline Cartridge Extraction Mass Spectrometry Improves Throughput and Spectra Stability.

Rapid and reliable methods for detecting tumor margins are crucial for neuro-oncology. Several mass spectrometry-based methods have been recently proposed to address this problem. Inline Cartridge Extraction (ICE) demonstrates the potential for clinical application, based on ex-vivo analysis of dissected tissues, but requires time-consuming steps to avoid cross-contamination. In this work, a method of incorporating a disposable electrospray emitter into the ICE cartridge by PEEK sleeves melting is developed. It reduces total analysis time and improves throughput. The proposed setup also improves the robustness of the ICE molecular profiling as demonstrated with human glial tumor samples in that stability and reproducibility of the spectra were increased.

Amine additives for improved in-ESI H/D exchange.

In-ESI H/D exchange is a convenient technique for analyzing small-molecular complex mixtures. However, such experiments do not yield sufficient levels of exchange or require an elevated temperature of the ion transfer capillary. Increased temperature may result in unexpected additional exchanges of -CH groups that may complicate the interpretation of the H/D exchange data used for identification. Gas-phase H/D exchange depends on the gas-phase basicity of the deuterating agent. In-ESI exchange involves both droplet-phase and gas-phase mechanisms, depending on a particular ion source setup and the deuterating agent used. Therefore, the addition of strong bases to the reaction mixture should facilitate in-ESI exchange. This work aimed to investigate the capabilities of different amines to improve in-ESI H/D exchange compared with pure D2O and to choose an amine modifier to increase the extent of H/D exchange. It was shown that such additives substantially enhanced the extent of H/D exchange in small molecules, peptides, and proteins even without heating the capillary. It was found that the extent of exchange increases in the following order: tertiary amines < secondary amines < primary amines. Therefore, we suggest that amines act as deuterating agents after being exchanged with D2O. These findings may improve H/D exchange applications, especially in small molecule analysis. The observation of improved H/D exchange with amine additives in peptides and proteins may become a subject of future research.

Determination of Brain Tissue Samples Storage Conditions for Reproducible Intraoperative Lipid Profiling.

Ex-vivo molecular profiling has recently emerged as a promising method for intraoperative tissue identification, especially in neurosurgery. The short-term storage of resected samples at room temperature is proposed to have negligible influence on the lipid molecular profiles. However, a detailed investigation of short-term molecular profile stability is required to implement molecular profiling in a clinic. This study evaluates the effect of storage media, temperature, and washing solution to determine conditions that provide stable and reproducible molecular profiles, with the help of ambient ionization mass spectrometry using rat cerebral cortex as model brain tissue samples. Utilizing normal saline for sample storage and washing media shows a positive effect on the reproducibility of the spectra; however, the refrigeration shows a negligible effect on the spectral similarity. Thus, it was demonstrated that up to hour-long storage in normal saline, even at room temperature, ensures the acquisition of representative molecular profiles using ambient ionization mass spectrometry.

Spherical Sampler Probes Enhance the Robustness of Ambient Ionization Mass Spectrometry for Rapid Drugs Screening.

Ambient ionization mass spectrometry has become one of the most promising approaches for rapid and high-throughput screening of small molecules in complex biological matrices for emergency medicine, forensics, and food and agriculture applications. The simple procedures for sample collection and ionization without additional pretreatment are vital in these fields. Many efforts have been devoted to modifying various ambient ionization techniques to simplify the procedures and improve the robustness and sensitivity of the methods. Here, we demonstrate the implementation of rigid spherical sampler probes to improve the robustness of touch spray ionization mass spectrometry. The sphericity of the probes increases the stability of the cone-jet mode of electrospray, reduces the requirements for fine positioning of a sampler in the ion source, and decreases the possibility of corona discharge occurrence. The utilization of spherical sampler probes allows fast, non-invasive sampling, followed by rapid analysis for various drugs of different chemical classes in complex biological matrices, such as the whole blood or sebum collected from the skin surface. The linearity of the analytical signal response from drug concentration confirms the possibility of creating a simple semiquantitative method for small molecules monitoring using spherical sampler probes.

Mass spectrometry based proteome profiling of the exhaled breath condensate for lung cancer biomarkers search.

INTRODUCTION: Lung cancer remains the most prevalent cause of cancer mortality worldwide mainly due to insufficient availability of early screening methods for wide-scale application. Exhaled breath condensate (EBC) is currently considered as one of the promising targets for early screening and is particularly attractive due to its absolutely noninvasive collection and possibility for long-term frozen storage. EBC proteome analysis can provide valuable information about the (patho)physiological changes in the respiratory system and may help to identify in time a high risk of lung cancer. Mass spectrometry (MS) profiling of EBC proteome seems to have no alternative in obtaining the most extensive data and characteristic marker panels for screening. AREAS COVERED: This special report summarizes the data of several proteomic studies of EBC in normal and lung cancer (from 2012 to 2021, PubMed), focuses on the possible reasons for the significant discrepancy in the results, and discusses some aspects for special attention in further studies. EXPERT OPINION: The significant discrepancy in the results of various studies primarily highlights the need to create standardized protocols for the collection and preparation of EBC for proteomic analysis. The application of quantitative and targeted LC-MS/MS based approaches seems to be the most promising in further EBC proteomic studies.

Speciation of organosulfur compounds in carbonaceous chondrites.

Despite broad application of different analytical techniques for studies on organic matter of chondrite meteorites, information about composition and structure of individual compounds is still very limited due to extreme molecular diversity of extraterrestrial organic matter. Here we present the first application of isotopic exchange assisted Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) for analysis of alkali extractable fraction of insoluble organic matter (IOM) of the Murchison and Allende meteorites. This allowed us to determine the individual S-containing ions with different types of sulfur atoms in IOM. Thiols, thiophenes, sulfoxides, sulfonyls and sulfonates were identified in both samples but with different proportions, which contribution corroborated with the hydrothermal and thermal history of the meteorites. The results were supported by XPS and thermogravimetric analysis coupled to FTICR MS. The latter was applied for the first time for analysis of chondritic IOM. To emphasize the peculiar extraterrestrial origin of IOM we have compared it with coal kerogen, which is characterized by the comparable complexity of molecular composition but its aromatic nature and low oxygen content can be ascribed almost exclusively to degradation of biomacromolecules.

Transfer learning for small molecule retention predictions.

Small molecule retention time prediction is a sophisticated task because of the wide variety of separation techniques resulting in fragmented data available for training machine learning models. Predictions are typically made with traditional machine learning methods such as support vector machine, random forest, or gradient boosting. Another approach is to use large data sets for training with a consequent projection of predictions. Here we evaluate the applicability of transfer learning for small molecule retention prediction as a new approach to deal with small retention data sets. Transfer learning is a state-of-the-art technique for natural language processing (NLP) tasks. We propose using text-based molecular representations (SMILES) widely used in cheminformatics for NLP-like modeling on molecules. We suggest using self-supervised pre-training to capture relevant features from a large corpus of one million molecules followed by fine-tuning on task-specific data. Mean absolute error (MAE) of predictions was in range of 88-248 s for tested reversed-phase data sets and 66 s for HILIC data set, which is comparable with MAE reported for traditional machine learning models based on descriptors or projection approaches on the same data.

Rapid estimation of tumor cell percentage in brain tissue biopsy samples using inline cartridge extraction mass spectrometry.

Tumor cell percentage (TCP) is an essential characteristic of biopsy samples that directly affects the sensitivity of molecular testing in clinical practice. Apart from clarifying diagnoses, rapid evaluation of TCP combined with various neuronavigation systems can be used to support decision making in neurosurgery. It is known that ambient mass spectrometry makes it possible to rapidly distinguish healthy from malignant tissues. In connection with this, here we demonstrate the possibility of using non-imaging ambient mass spectrometry to evaluate TCP in glial tumor tissues with a high degree of confidence. Molecular profiles of histologically annotated human glioblastoma tissue samples were obtained using the inline cartridge extraction ambient mass spectrometry approach. XGBoost regressors were trained to evaluate tumor cell percentage. Using cross-validation, it was estimated that the TCP was determined by the regressors with a precision of approximately 90% using only low-resolution data. This result demonstrates that ambient mass spectrometry provides an accurate method todetermine TCP in dissected tissues even without implementing mass spectrometry imaging. The application of such techniques offers the possibility to automate routine tissue screening and TCP evaluation to boost the throughput of pathology laboratories. Rapid estimation of tumor cell percentage during neurosurgery.

Normalization methods for reducing interbatch effect without quality control samples in liquid chromatography-mass spectrometry-based studies.

Data normalization is an essential part of a large-scale untargeted mass spectrometry metabolomics analysis. Autoscaling, Pareto scaling, range scaling, and level scaling methods for liquid chromatography-mass spectrometry data processing were compared with the most common normalization methods, including quantile normalization, probabilistic quotient normalization, and variance stabilizing normalization. These methods were tested on eight datasets from various clinical studies. The efficiency of the data normalization was assessed by the distance between clusters corresponding to batches and the distance between clusters corresponding to clinical groups in the space of principal components, as well as by the number of features with a pairwise statistically significant difference between the batches and the number of features with a pairwise statistically significant difference between clinical groups. Autoscaling demonstrated the most effective reduction in interbatch variation and can be preferable to probabilistic quotient or quantile normalization in liquid chromatography-mass spectrometry data.

Antiviral activity of natural humic substances and shilajit materials against HIV-1: Relation to structure.

Natural products, such as humic substances (HS) and shilajit, are known to possess antiviral activity. Humic-like components are often called as carriers of biological activity of shilajit. The goal of this study was to evaluate anti-HIV activity of well characterized HS isolated from coal, peat, and peloids, and compare it to that of water-soluble organic matter (OM) isolated from different samples of Shilajit. The set of humic materials included 16 samples of different fractional composition: humic acid (HA), hymatomelanic acid (HMA), fulvic acid (FA). The set of shilajit OM included 19 samples of different geographic origin and level of alteration. The HIV-1 p24 antigen assay and cell viability test were used for assessment of antiviral activity. The HIV-1 Bru strain was used to infect CEM-SS cells. The obtained EC50 values varied from 0.37 to 1.4 mg L-1 for the humic materials, and from 14 to 142 mg L-1 for the shilajit OM. Hence, all humic materials used in this study outcompeted largely the shilajit materials with respect to anti-HIV activity: For the humic materials, the structure-activity relationships revealed strong correlation between the EC50 values and the content of aromatic carbon indicating the most important role of aromatic structures. For shilajit OM, the reverse relationship was obtained indicating the different mechanism of shilajit activity. The FTICRMS molecular assignments were used for ChEMBL data mining in search of the active humic molecules. As potential carriers of antiviral activity were identified aromatic structures with alkyl substituents, terpenoids, N-containing analogs of typical flavonoids, and aza-podophyllotoxins. The conclusion was made that the typical humic materials and Shilajit differ greatly in molecular composition, and the humic materials have substantial preferences as a natural source of antiviral agents as compared to shilajit.

Relative Quantitation of Beta-Amyloid Peptide Isomers with Simultaneous Isomerization of Multiple Aspartic Acid Residues by Matrix Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry.

Matrix assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry can be used for rapid quantitation of peptides with various post-translational modifications (PTM), even if they do not shift the mass of the native peptide. Previously, it was shown that MALDI-TOF MS can be used for quantitation of isoD7 beta-amyloid 1-42 peptide. On the basis of the differences in the collision-induced dissociation fragmentation pattern of native Aß, isoD7 Aß, isoD23 Aß, and isoD7_23 peptide (a di-isomerized peptide with both isomerization of D7 and D23 residues), we developed a MALDI-TOF-based method for simultaneous quantitation of all of these isoforms. Using multivariate regression for analysis of fragment MS data, the method allows the determination of the molar fractions of all of these isoforms with up to 16% error for mixtures with 2 pmol total amount of the beta-amyloid peptide.

Machine learning to predict retention time of small molecules in nano-HPLC.

Retention time is an important parameter for identification in untargeted LC-MS screening. Precise retention time prediction facilitates the annotation process and is well known for proteomics. However, the lack of available experimental information for a long time has limited the prediction accuracy for small molecules. Recently introduced large databases for small-molecule retention times make possible reliable machine learning-based predictions for the whole diversity of compounds. Applying simple projections may expand these predictions on various LC systems and conditions. In our work, we describe a complex approach to predict retention times for nano-HPLC that includes the consequent deployment of binary and regression gradient boosting models trained on the METLIN small-molecule dataset and simple projection of the results with a small number of easily available compounds onto nano-HPLC separations. The proposed model outperforms previous attempts to use machine learning for predictions with a 46-s mean absolute error. The overall performance after transfer to nano-LC conditions is less than 155 s (10.8%) in terms of the median absolute (relative) error. To illustrate the applicability of the described approach, we successfully managed to eliminate averagely 25 to 42% of false-positives with a filter threshold derived from ROC curves. Thus, the proposed approach should be used in addition to other well-established in silico methods and their integration may broaden the range of correctly identified molecules.

The Structure of Blood Coagulation Factor XIII Is Adapted to Oxidation.

The blood coagulation factor XIII (FXIII) plays a critical role in supporting coagulation and fibrinolysis due to both the covalent crosslinking of fibrin polymers, rendering them resistant to plasmin lysis, and the crosslinking of fibrin to proteins of the fibrinolytic system. The hypochlorite-mediated oxidation of the blood coagulation factor XIII (FXIII) at the different stages of its enzymatic activation is studied for the first time in this paper. The consolidated results obtained with the aid of MS/MS, electrophoresis, and colorimetry demonstrate that in the process of FXIII's conversion into FXIIIa, the vulnerability of FXIII to hypochlorite-induced oxidation increased as follows: native FXIII < FXIII + Ca2+ << FXIII + Ca2+/thrombin. The modification sites were detected among all the structural regions of the catalytic FXIII-A subunit, except for the activation peptide, and embraced several sushi domains of the FXIII-B subunit. Oxidized amino acid residues belonging to FXIII-A are surface-exposed residues and can perform an antioxidant role. The regulatory FXIII-B subunits additionally contribute to the antioxidant defense of the catalytic center of the FXIII-A subunits. Taken together, the present data along with the data from previous studies demonstrate that the FXIII proenzyme structure is adapted to oxidation.

SERPINA1 Peptides in Urine as A Potential Marker of Preeclampsia Severity.

Preeclampsia (PE) is a multisystem disorder associated with pregnancy and its frequency varies from 5 to 20 percent of pregnancies. Although a number of preeclampsia studies have been carried out, there is no consensus about disease etiology and pathogenesis so far. Peptides of SERPINA1 (α1-antitrypsin) in urine remain one of the most promising peptide markers of PE. In this study the diagnostic potential of urinary α1-antitrypsin peptides in PE was evaluated. The urinary peptidome composition of 79 pregnant women with preeclampsia (PE), chronic arterial hypertension (CAH), and a control group was investigated. Mann-Whitney U-test (p < 0.05) revealed seven PE specific SERPINA1 peptides demonstrating 52% sensitivity and 100% specificity. SERPINA1 in urine has been associated with the most severe forms of preeclampsia (p = 0.014), in terms of systolic hypertension (p = 0.01) and proteinuria (p = 0.006). According to Spearman correlation analysis, the normalized intensity of SERPINA1 urinary peptides has a similar diagnostic pattern with known diagnostic PE markers, such as sFLT/PLGF. SERPINA1 peptides were not urinary excreted in superimposed PE (PE with CAH), which is a milder form of PE. An increase in expression of SERPINA1 in the structural elements of the placenta during preeclampsia reflects a protective mechanism against hypoxia. Increased synthesis of SERPINA1 in the trophoblast leads to protein accumulation in fibrinoid deposits. It may block syncytial knots and placenta villi, decreasing trophoblast invasion. Excretion of PE specific SERPINA1 peptides is associated with syncytiotrophoblast membrane destruction degradation and increased SERPINA1 staining. It confirms that the placenta could be the origin of SERPINA1 peptides in urine. Significant correlation (p < 0.05) of SERPINA1 expression in syncytiotrophoblast membrane and cytoplasm with the main clinical parameters of severe PE proves the role of SERPINA1 in PE pathogenesis. Estimation of SERPINA1 peptides in urine can be used as a diagnostic test of the severity of the condition to determine further treatment, particularly the need for urgent surgical delivery.

The high-resolution mass spectrometry study of the protein composition of amyloid-like urine aggregates associated with preeclampsia.

The study of protein misfolding and post-translational processing abnormalities is a promising diagnostic approach for socially significant pathologies associated with the accumulation of abnormal forms of proteins. Recently, it was shown that amyloid-like aggregates can be observed in the urine of pregnant women with preeclampsia, which is the most severe hypertensive complication that can lead to fateful outcomes. The protein composition of urine aggregates may clarify the molecular mechanisms underlying the pathology and has not yet been studied in detail. Using a proteomic approach based on high-resolution mass spectrometry, we studied the protein composition of amyloid-like structures that aggregate in the presence of Congo red azo-dye in the urine of pregnant women with preeclampsia. Fragments of ß-sheets of α-1-antitrypsin, complement 3, haptoglobin, ceruloplasmin, and trypstatin were identified as most likely targets for Congo red binding.

Inline cartridge extraction for rapid brain tumor tissue identification by molecular profiling.

The development of perspective diagnostic techniques in medicine requires efficient high-throughput biological sample analysis methods. Here, we present an inline cartridge extraction that facilitates the screening rate of mass spectrometry shotgun lipidomic analysis of tissue samples. We illustrate the method by its application to tumor tissue identification in neurosurgery. In perspective, this high-performance method provides new possibilities for the investigation of cancer pathogenesis and metabolic disorders.