Fragmentation Spectra Research Articles

Qualitative Analysis of Real Drug Evidence Using DART-MS and the Inverted Library Search Algorithm.

Chromatographic-less mass spectrometry techniques like direct analysis in real-time mass spectrometry (DART-MS) are steadily being employed as seized drug screening tools. However, these newer analytical platforms require new computational methods to best make use of the collected data. The inverted library search algorithm (ILSA) is a recently developed method designed specifically for working with mass spectra of mixtures collected with DART-MS and has been implemented as a function in the NIST/NIJ DART-MS data interpretation tool (DIT). This paper demonstrates how DART-MS and the ILSA/DIT can be used to analyze seized drug evidence, while discussing insights gathered during the evaluation of 92 adjudicated case samples. The evaluation verified that the combination of DART-MS and the ILSA/DIT can be used as an informative tool to help analysts screen seized drug evidence but also revealed several factors─such as the influence of incorporating multiple in-source fragmentation spectra and the effect of scoring thresholds─an analyst must consider while employing these methods. Use cases demonstrating the benefit of the nonscoring metrics provided by the ILSA/DIT and demonstrating how the ILSA/DIT can be used to identify novel substances are also presented. A summary of considerations for using the ILSA/DIT for drug screening concludes this paper.

Prediction of peptide mass spectral libraries with machine learning.

The recent development of machine learning methods to identify peptides in complex mass spectrometric data constitutes a major breakthrough in proteomics. Longstanding methods for peptide identification, such as search engines and experimental spectral libraries, are being superseded by deep learning models that allow the fragmentation spectra of peptides to be predicted from their amino acid sequence. These new approaches, including recurrent neural networks and convolutional neural networks, use predicted in silico spectral libraries rather than experimental libraries to achieve higher sensitivity and/or specificity in the analysis of proteomics data. Machine learning is galvanizing applications that involve large search spaces, such as immunopeptidomics and proteogenomics. Current challenges in the field include the prediction of spectra for peptides with post-translational modifications and for cross-linked pairs of peptides. Permeation of machine-learning-based spectral prediction into search engines and spectrum-centric data-independent acquisition workflows for diverse peptide classes and measurement conditions will continue to push sensitivity and dynamic range in proteomics applications in the coming years.

N,N-Dimethylpentylone–an emerging NPS stimulant of concern in the United States

The objective of this study is to inform forensic toxicologists about the rise and proliferation of the new synthetic stimulant N,N-dimethylpentylone in postmortem investigations. For the majority of 2020 and 2021, eutylone was the dominant synthetic stimulant and the primary novel psychoactive substance (NPS) sold as “ecstasy”, “molly”, or “MDMA.” In September 2021, eutylone was recommended for international control, which created a shift internationally in the NPS stimulant drug market. After this notice of international control, eutylone positivity began to decline and identifications of the new synthetic stimulant N,N-dimethylpentylone began to increase. Synthetic stimulants have been deemed a risk to public health and with possible adverse effects including hallucinations, hyperthermia, arrythmias, and serotonin syndrome, which can lead to death. Beginning in Q4 2021, our laboratory initiated surveillance efforts to track the emergence and proliferation of N,N-dimethylpentylone, in addition to assessment of its associated harms and impacts. In collaboration between the CFSRE and NMS Labs, authentic toxicology samples were comprehensively tested for N,N-dimethylpentylone, other NPS, and commonly encountered drugs. Blood and urine samples were prepared using a single-step basic liquid-liquid extraction. Screening analysis was conducted using a Sciex TripleTOF® 5600+ liquid chromatograph time-of-flight mass spectrometer (LC-QTOF-MS). When possible, quantitative confirmations were performed using the method of standard addition with analysis via a Waters TQ-S Micro liquid chromatograph tandem quadrupole mass spectrometer (LC-QQQ-MS). By LC-QTOF-MS, N,N-dimethylpentylone was distinguishable from its isomers using retention time and/or fragment spectrum. By LC-QQQ-MS, a specialized method was developed to chromatographically separate all known isomers. Basic demographic and case information were available for select cases in collaboration with medical examiner offices. N,N-Dimethylpentylone was confirmed in 32 cases, including postmortem ( n = 26), DUID ( n = 1), and unknown ( n = 5) cases which were collected between August 2021 to March 2022. Cases originated from nine states, primarily Florida ( n = 17) and the Mid-Atlantic region of the United States ( n = 13). Individuals were largely male (62%), and age ranged between 27 to 52 years old. To date, N,N-dimethylpentylone was quantitated in five postmortem cases with concentrations ranging from 33 to 970 ng/mL (mean: 270 ± 400 ng/mL, median: 87 ng/mL). In addition, pentylone was confirmed in all five cases, affirming that this drug is a primary metabolite of N,N-dimethylpentylone. Pentylone concentrations ranged from 10 to 420 ng/mL (mean: 120 ± 170 ng/mL, median: 37 ng/mL). Notable drugs identified alongside N,N-dimethylpentylone in the 32 total cases were pentylone ( n = 23), fentanyl or other opioids ( n = 13), methamphetamine ( n = 11), and eutylone ( n = 5). In eight cases, there were no other drugs of interest identified with N,N-dimethylpentylone. N,N-Dimethylpentylone was first identified in a toxicology sample in the USA in Q3 2021. N,N-Dimethylpentylone is increasingly being identified in forensic toxicology samples, rising in positivity from 0% in Q3 2021 to 1.5% in Q1 2022, while eutylone fell from 9.2% to 2.5%. Concentrations observed in blood were high and consistent with other NPS stimulants reported. Laboratories may misidentify N,N-dimethylpentylone as N-ethylpentylone due to their isomeric relationship; however, it has been our experience that concurrent identification of pentylone may give a stronger indication that N,N-dimethylpentylone is present. This is due to the fact that pentylone is a metabolite of N,N-dimethylpentylone, and is not a metabolite of N-ethylpentylone. N,N-Dimethylpentylone is an increasingly prevalent synthetic stimulant being identified in forensic cases in the United States and around the world. Continued awareness about the emergence of new stimulants after international control is imperative as positivity will vary as previously prevalent drugs fade and new drug emerge. Undoubtedly, the emergence of N,N-dimethylpentylone depicts a shift in the international NPS market of stimulants.

Analytical strategy to document horse fatalities related to Oenanthe crocata poisoning

To report the analytical procedure that was developed and applied to identify oenanthotoxin (OT) and its metabolite 2,3-dihydro-oenanthotoxin (2,3DHOT) in biological and vegetal samples using both LC-DAD and LC-HRMS methods in two cases of equine fatal intoxication by Oenanthe crocata. : (case#1) a 7-year-old Arabian horse was found dead within one hour after the ingestion of «wild carrots», and was autopsied the following day. The gross and microscopic examination was unremarkable, except the presence of several root pieces in the animal's stomach. Sections of the same roots found on the site showed hexagonal subdivisions and a yellowish latex. These findings were consistent with Hemlock water-dropwort (Oenanthe crocata) and confirmed by an experienced botanist. (case#2) an 8-year-old pony was unexpectedly found dead and autopsied two days later. The body conservation was poor; the only significant finding was the presence of several root pieces of undetermined origin in the stomach. Autopsy samples (root pieces found in the stomach, stomach content, liver, kidney, and spleen of case#1; stomach content of case#2) were stored at -20 °C before analysis, while the on-site roots (case#1) were stored at room temperature. After grinding organ samples, 1 to 10 g were extracted using methanol (5 mL), vortex mixed for 30 seconds, and kept at 4 °C for 2 hours. These methanolic suspensions were centrifuged firstly at 2500 g for 10 min, then the supernatant was secondly centrifugated at 8000 g for 14 min. In order to enhance detection sensitivity, one mL of each supernatant from the liver, kidney, and spleen samples was dried under nitrogen and then each extract was resuspended with 100 μL of methanol. Extracts were analysed using two analytical methods (LC-DAD and LC-HRMS) both using the same ACQUITY HSS C18 column (150 × 2 mm, 20 μm) for chromatographic separation. The acquired data were analysed using Empower 3 (LC-DAD) and Unify and Progenesis QI softwares (LC-HRMS) for investigation of specific fragmentation spectra of identified substances. Thanks to combined analytical data (i.e. characteristic UV spectra [Kite. J Chrom B. 2006;838:63-70.] together with specific fragmentation HRMS spectra), oenanthotoxin (OT) and its hydrogenated metabolite, 2,3-dihydro-oenanthotoxin (2,3DHOT*), were identified (case#1) in roots found on the siteand in the stomach content, in the stomach content, kidney, and liver (*also in spleen), and (case#2) in the stomach content. In France, three species of the Apiaceae family can cause life threatening poisoning: the Hemlock (Cicuta virosa), the big Hemlock (Conium maculatum) and the Hemlock water-dropwort (Oenanthe crocata). In the latter one, OT and 2,3DHOT act as non-competitive antagonists of GABA receptors. Clinical signs of poisoning in horses (non-vomiting animals) are dominated by hypersalivation, mydriasis, muscle tremors, respiratory distress, and convulsions, but sometimes sudden death is observed. In humans, the clinical signs are completed/supplemented by ataxia, bruxism, hallucinations, nausea, and vomiting seizures; they occur between 15 min and 10 hours after ingestion [Schep. Clin Tox.2009;47:270–278.]. Analytical detection of Oenanthe crocata toxins in biological samples is a challenge due to their instability (e.g. OT and 2,3DHOT stabilities in post-mortem samples is unknown), the lack of commercially available analytical standards, and the exceptionally low response of these toxins using mass spectrometry detection. Nevertheless, identification of OT and 2,3DHOT can be performed using a combination of LC-DAD and LC-HMRS (for enhanced detection in organs, e.g. liver) methods, in order to support poisoning diagnosis. In this context, we consider that the reported analytical data can be helpful to diagnose oenanthotoxin poisonings.

Quantification of phosphatidylethanol combining dried blood spots sampling with Orbitrap-based LC-HRMS platform: Method validation and proficiency testing

Phosphatidylethanols (PEth) are phospholipids specifically synthetised by an enzymatic reaction in presence of ethanol. PEth is a mid-term direct biomarker for alcohol consumption or abstinence, leading to a growing interest for forensic toxicology purposes. Blood deposition onto a filter paper card as dried blood spots (DBS) allows PEth stabilisation which is otherwise easily degraded at room temperature. The goal of this study was to develop and validate a procedure for the quantification of PEth 16:0/18:1, the most abundant analogue, in DBS samples benefiting from the selectivity brought by Orbitrap-based high-resolution mass spectrometry (HRMS). Calibration samples and quality controls (QCs) are volumetrically spotted (10 μL) onto filter paper card (Whatman 903 protein saver) either using HemaXis DB10™ device, or using laboratory micropipette. The whole DBS is manually punched out and the PEth is then directly extracted using an in vial approach with 100 μL of PEth 16:0/18:1-D5 in methanol. Analyses are then performed by LC-HRMS in PRM mode using a QExactive Orbitrap platform. Validation was carried out on with respect to the Food and Drug Administration (FDA) criteria, using three different QC concentrations (39, 87 and 350 ng/mL) over three non-consecutive days. To assess the robustness of our method, an interlaboratory proficiency testing was carried out using 3 different commercial standards at 4 levels (50, 100, 200, and 300 ng/mL) of quality controls (QCs) provided by ACQ Science (Germany). The method was fully validated according to guidelines set forth by the FDA. Calibration curve was built using a weighting factor of 1/x. Trueness was measured between 100.1 and 103.6% for the tested concentrations. Repeatability and intermediate precision were found to be lower than 5%. Linearity was evaluated between the lower limit of quantification of 20 ng/mL and the upper limit of quantification of 2000 ng/mL with an R2 greater than 0.998. Recovery (RE) and matrix effect (ME) evaluated at 2 concentrations ranged from 76 to 99% and 8 to 10%, respectively. During the proficiency test, precision was evaluated below 8.0%, while the accuracy ranged from 93.8% to 105.9% and from 101 to 104.5% when compared with the expected concentration and the mean measured value of all the labs participating respectively. The validation results demonstrate that the use of Orbitrap-based PRM quantification present an interesting alternative over triple quadrupole platforms considered as the gold standard for LC-MS/MS quantitative approaches. Indeed, multiple reaction monitoring (MRM) and PRM provide comparable performance in terms of sensitivity, linearity, dynamic range, precision and repeatability. Moreover, the use of PRM provides access to the full fragmentation spectra without any preanalytical considerations. The proficiency testing results confirm the suitability of PRM mode showing great quantification performances. In addition, those results and especially the repeatability exhibit the precision of the volume control provided by the use of HemaXis™ device. This tool enables the standardisation of the DBS collection at the fingertip in a non-hospital environment either by minimally-trained medical staff or by the patient himself. A rapid, sensitive, and robust method was developed and fully validated for the detection and quantification of PEth 16:0/18:1 in DBS samples. The results of the validation process and the proficiency testing confirm that the use of DBS associated with HRMS PRM-based analyses does not hinder the analytical performances, while providing full information over the MS-MS spectra. The development of analytical tools enabling the use of DBS microsampling that can be performed in almost every environment opens new opportunities toward clinical and forensic toxicological applications.

Integration of protein context improves protein-based COVID-19 patient stratification

BackgroundClassification of disease severity is crucial for the management of COVID-19. Several studies have shown that individual proteins can be used to classify the severity of COVID-19. Here, we aimed to investigate whether integrating four types of protein context data, namely, protein complexes, stoichiometric ratios, pathways and network degrees will improve the severity classification of COVID-19.MethodsWe performed machine learning based on three previously published datasets. The first was a SWATH (sequential window acquisition of all theoretical fragment ion spectra) MS (mass spectrometry) based proteomic dataset. The second was a TMTpro 16plex labeled shotgun proteomics dataset. The third was a SWATH dataset of an independent patient cohort.ResultsBesides twelve proteins, machine learning also prioritized two complexes, one stoichiometric ratio, five pathways, and five network degrees, resulting a 25-feature panel. As a result, a model based on the 25 features led to effective classification of severe cases with an AUC of 0.965, outperforming the models with proteins only. Complement component C9, transthyretin (TTR) and TTR-RBP (transthyretin-retinol binding protein) complex, the stoichiometric ratio of SAA2 (serum amyloid A proteins 2)/YLPM1 (YLP Motif Containing 1), and the network degree of SIRT7 (Sirtuin 7) and A2M (alpha-2-macroglobulin) were highlighted as potential markers by this classifier. This classifier was further validated with a TMT-based proteomic data set from the same cohort (test dataset 1) and an independent SWATH-based proteomic data set from Germany (test dataset 2), reaching an AUC of 0.900 and 0.908, respectively. Machine learning models integrating protein context information achieved higher AUCs than models with only one feature type.ConclusionOur results show that the integration of protein context including protein complexes, stoichiometric ratios, pathways, network degrees, and proteins improves phenotype prediction.

Assessment of the similarity between in-source collision-induced dissociation (IS-CID) fragment ion spectra and tandem mass spectrometry (MS/MS) product ion spectra for seized drug identifications

The use of in-source collision-induced dissociation (IS-CID) with single-stage mass spectrometers has grown in popularity within the field of seized drug analysis as a pseudo-tandem mass spectrometry (MS/MS) analysis to gain structural information about unknown compounds. However, there is currently no statistical assessment of the similarity and thus, the comparability, of IS-CID fragment ion spectra and MS/MS product ions spectra for representative novel psychoactive substances (NPS), such as synthetic cannabinoids, synthetic cathinones, and fentanyl analogs. This study investigates the use of spectral comparisons, breakdown curves, and Pearson product-moment correlations (PPMCs) to assess the similarity between IS-CID fragment ion spectra and MS/MS product ion spectra both visually and statistically. In addition, this study also examines the repeatability of IS-CID fragment ion spectra relative to MS/MS product ion spectra to assess the short-term repeatability of IS-CID fragment ion spectra. The 95% confidence interval average PPMC for the highest pairwise comparison across this study was 0.9294 +/- 0.0106. The optimum comparison range between IS-CID fragment ion spectra and MS/MS product ion spectra was identified between a fragmentor voltage of 150–280 V and a collision energy of 0–22 eV. Similar repeatability of IS-CID fragment ion spectra (15.21%) and MS/MS product ion spectra (14.72%) was also observed. Demonstrating the achievable spectral similarity between IS-CID fragment ion spectra and MS/MS product ion spectra for representative NPS, as well as highlighting the potential deleterious effects of high activation conditions on spectral comparisons, will help inform analysts’ decisions regarding seized drug identifications based on IS-CID fragment ion spectra.

The Current State-of-the-Art Identification of Unknown Proteins Using Mass Spectrometry Exemplified on De Novo Sequencing of a Venom Protease from Bothrops moojeni.

(1) Background: The amino acid sequence elucidation of peptides from the gas phase fragmentation mass spectra, de novo sequencing, is a valuable method for the identification of unknown proteins complementary to Edman sequencing. It is increasingly used in shot-gun mass spectrometry (MS)-based proteomics experiments. We review the current state-of-the-art and use the identification of an unknown snake venom protein targeting the human tissue factor (TF) as an example to describe the analysis process based on manual spectrum interrogation. (2) Methods: The immobilized TF was incubated with a crude B. moojeni venom solution. The potential binding partners were eluted and further purified by gel electrophoresis. Edman degradation was performed to elucidate the N-terminus of the 31 kDa protein of interest. High-resolution MS with collision-induced dissociation was employed to generate peptide fragmentation spectra. Sequence tags were deduced and used for searches in the NCBI and Uniprot databases. Protein matches from the snake species were further validated by target MS/MS. (3) Results: Sequence tag D [K/Q] D [I/L] VDD [K/Q] led to a snake venom serine protease (SVSP) from lancehead B. jararaca (P81824). With target MS/MS, 24% of the SVSP sequence were confirmed; an additional 41% were tentatively assigned by data-independent MS. Edman sequencing provided information for 10 N-terminal amino acid residues, also confirming the match to SVSP. (4) Conclusions: The identification of unknown proteins continues to be a challenge despite major advances in MS instrumentation and bioinformatic tools. The main requirement is the generation of meaningful, high-quality MS peptide fragmentation spectra. These are used to elucidate sufficiently long sequence tags, which can subsequently be submitted to searches in protein databases. This basic method does not require extensive bioinformatics because peptide MS/MS spectra, especially of doubly-charged ions, can be analysed manually. We demonstrated the procedure with the elucidation of SVSP. While de novo sequencing quickly indicates the correct protein group, the validation of the entire protein sequence of amino acid-by-amino acid will take time. Reasons are the need to properly assign isobaric amino acid residues and modifications. With the ongoing efforts in genomics and transcriptomics and the availability of ever more data in public databases, the need for de novo MS sequencing will decrease. Still, not every animal and plant species will be sequenced, so the combination of MS and Edman sequencing will continue to be of importance for the identification of unknown proteins.

Effect of mobile phase pH on liquid chromatography retention of mepartricin related compounds and impurities as support to the structural investigation by liquid chromatography–mass spectrometry

Mepartricin is a semisynthetic polyene macrolide with antifungal and anti-protozoal activities, and it is widely used for the treatment of benign prostatic hyperplasia. Mepartricin is produced by synthetic methyl esterification of the more toxic partricin, and its activity is due to a complex of related compounds. Among them, the main ones are mepartricin B and mepartricin A which are characterized by the presence of a primary and a secondary amine group, respectively. In this work a previously reported HPLC-UV method was properly modified to make it MS-compatible. The selected conditions entail the use of a C18 reverse phase column, and a mobile phase composed by ammonium formate and acetonitrile, with the addition of heptafluorobutyric acid as modifier. The developed method was applied to the characterization of a mepartricin reference standard and a mepartricin experimental batch. All the UV responding peaks, 30 for the standard and 21 for the experimental batch, were successfully detected by MS, allowing to define their m/z values and acquire their fragmentation spectra. For the structural elucidation of isobaric species and, in particular, the identification of toxic partricin-related impurities, the presence of differently ionisable chemical groups was considered, as partricins contain free caboxy-groups, while mepartricins represent their estherified counterparts. A deep study of the effect of mobile phase pH on the chromatographic retention of partricin and mepartricin related compounds was performed in the pH range 2.5–6.5. This study allowed to successfully cluster all the detected species and asses, in the considered batch, the absence of other partricin-related impurities in addition to partricin B and partricin A.

A new vicilin-like allergen in hazelnut giving rise to a spectrum of IgE binding low molecular weight N-terminal fragments

A new vicilin-like allergen in hazelnut giving rise to a spectrum of IgE binding low molecular weight N-terminal fragments

Identification of the initial reactive sites of micellar and non-micellar casein exposed to microbial transglutaminase

To investigate the influence of the internal micellar structure on the course of enzymatic cross-linking especially in the initial phase of the reaction, casein micelles isolated from raw milk via ultracentrifugation were incubated with microbial transglutaminase (mTG) in comparison with non-micellar sodium caseinate. Reactive lysine and glutamine residues were identified using a label-free approach, based on the identification of isopeptides within tryptic hydrolysates by targeted HRMS as well as manual monitoring of fragmentation spectra. Identified reactive sites were furthermore weighted by tracking the formation of isopeptides over an incubation time of 15, 30, 45 and 60 min, respectively. Fifteen isopeptides formed in the early stage of mTG cross-linking of caseins were identified and further specified concerning the position of lysine and glutamine residues involved in the reaction. The results revealed lysine K176 and glutamine Q175 of β-casein as the most reactive residues, which might be located in a highly flexible region of the molecule based on different possible reaction partners identified in this study. Except for the isopeptide αs1 K34–αs2 Q101 in sodium caseinate (SC), all reactive sites were detected in micellar and in non-micellar casein, indicating that the initial phase of enzymatic cross-linking is not affected by micellar aggregation of caseins.Graphical abstract

Dysregulated Protein Phosphorylation in a Mouse Model of FTLD-Tau.

The neocortex of P301S mice, used as a model of fronto-temporal lobar degeneration linked to tau mutation (FTLD-tau), and wild-type mice, both aged 9 months, were analyzed with conventional label-free phosphoproteomics and SWATH-MS (sequential window acquisition of all theoretical fragment ion spectra mass spectrometry) to assess the (phospho)proteomes. The total number of identified dysregulated phosphoproteins was 328 corresponding to 524 phosphorylation sites. The majority of dysregulated phosphoproteins, most of them hyperphosphorylated, were proteins of the membranes, synapses, membrane trafficking, membrane vesicles linked to endo- and exocytosis, cytoplasmic vesicles, and cytoskeleton. Another group was composed of kinases. In contrast, proteins linked to DNA, RNA metabolism, RNA splicing, and protein synthesis were hypophosphorylated. Other pathways modulating energy metabolism, cell signaling, Golgi apparatus, carbohydrates, and lipids are also targets of dysregulated protein phosphorylation in P301S mice. The present results, together with accompanying immunohistochemical and Western-blotting studies, show widespread abnormal phosphorylation of proteins, in addition to protein tau, in P301S mice. These observations point to dysregulated protein phosphorylation as a relevant contributory pathogenic component of tauopathies.

Flexibility and fragmentation aware routing, core and spectrum allocation for hybrid AoD nodes in SDM-EONs.

Space division multiplexing elastic optical network (SDM-EON) enables high-capacity transmission, in which the network nodes should provide high switching flexibility while limiting the complexity and costs of nodes. Architecture on demand (AoD) nodes can meet these requirements but the slow configuration time of optical backplane in AoD nodes makes it difficult to serve latency-sensitive requests. In this paper, we propose a hybrid optical backplane based on micro-electromechanical systems (MEMS) and semiconductor optical amplifier (SOA) switches to provide fast configuration time for AoD nodes. Moreover, we propose quantitative measures of node switching flexibility in SDM-EONs and of link configuration speed in AoD nodes. Based on the hybrid backplane architecture and the measurement approaches, we propose a flexibility and fragmentation aware routing, spectrum and core allocation algorithm and an AoD synthesis algorithm. Simulation results show that the hybrid AoD nodes with support of spatial lane change can reduce network blocking probability. The AoD based on this hybrid backplane structure can improve the network performance by 32.8% compared to the AoD based on the traditional MEMS. Compared with traditional reconfigurable optical add/drop multiplexers (ROADMs), the hybrid AoD nodes can control the number of wavelength selective switch (WSS) ports.

Quantitative proteomic landscapes of primary and recurrent glioblastoma reveal a protumorigeneic role for FBXO2-dependent glioma-microenvironment interactions.

Recent efforts have described the evolution of glioblastoma from initial diagnosis to post-treatment recurrence on a genomic and transcriptomic level. However, the evolution of the proteomic landscape is largely unknown. Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) was used to characterize the quantitative proteomes of two independent cohorts of paired newly diagnosed and recurrent glioblastomas. Recurrence-associated proteins were validated using immunohistochemistry and further studied in human glioma cell lines, orthotopic xenograft models, and human organotypic brain slice cultures. External spatial transcriptomic, single-cell, and bulk RNA sequencing data were analyzed to gain mechanistic insights. Although overall proteomic changes were heterogeneous across patients, we identified BCAS1, INF2, and FBXO2 as consistently upregulated proteins at recurrence and validated these using immunohistochemistry. Knockout of FBXO2 in human glioma cells conferred a strong survival benefit in orthotopic xenograft mouse models and reduced invasive growth in organotypic brain slice cultures. In glioblastoma patient samples, FBXO2 expression was enriched in the tumor infiltration zone and FBXO2-positive cancer cells were associated with synaptic signaling processes. These findings demonstrate a potential role of FBXO2-dependent glioma-microenvironment interactions to promote tumor growth. Furthermore, the published datasets provide a valuable resource for further studies.

Simplifying MS1 and MS2 spectra to achieve lower mass error, more dynamic range, and higher peptide identification confidence on the Bruker timsTOF Pro.

For bottom-up proteomic analysis, the goal of analytical pipelines that process the raw output of mass spectrometers is to detect, characterise, identify, and quantify peptides. The initial steps of detecting and characterising features in raw data must overcome some considerable challenges. The data presents as a sparse array, sometimes containing billions of intensity readings over time. These points represent both signal and chemical or electrical noise. Depending on the biological sample’s complexity, tens to hundreds of thousands of peptides may be present in this vast data landscape. For ion mobility-based LC-MS analysis, each peptide is comprised of a grouping of hundreds of single intensity readings in three dimensions: mass-over-charge (m/z), mobility, and retention time. There is no inherent information about any associations between individual points; whether they represent a peptide or noise must be inferred from their structure. Peptides each have multiple isotopes, different charge states, and a dynamic range of intensity of over six orders of magnitude. Due to the high complexity of most biological samples, peptides often overlap in time and mobility, making it very difficult to tease apart isotopic peaks, to apportion the intensity of each and the contribution of each isotope to the determination of the peptide’s monoisotopic mass, which is critical for the peptide’s identification. Here we describe four algorithms for the Bruker timsTOF Pro that each play an important role in finding peptide features and determining their characteristics. These algorithms focus on separate characteristics that determine how candidate features are detected in the raw data. The first two algorithms deal with the complexity of the raw data, rapidly clustering raw data into spectra that allows isotopic peaks to be resolved. The third algorithm compensates for saturation of the instrument’s detector thereby recovering lost dynamic range, and lastly, the fourth algorithm increases confidence of peptide identifications by simplification of the fragment spectra. These algorithms are effective in processing raw data to detect features and extracting the attributes required for peptide identification, and make an important contribution to an analytical pipeline by detecting features that are higher quality and better segmented from other peptides in close proximity. The software has been developed in Python using Numpy and Pandas and made freely available with an open-source MIT license to facilitate experimentation and further improvement (DOI 10.5281/zenodo.6513126). Data are available via ProteomeXchange with identifier PXD030706.

Structure similarity and molecular networking analysis for the discovery of polyphenol biotransformation products of gut microbes

Intestinal bacteria can metabolize polyphenols into highly bioavailable derivatives, which provide potential health-promoting effects to the host. However, the metabolic pathways and related products in this process are still largely unclear. Polyphenols are generally characterized by the presence of many phenolic structural units, which makes it possible to explore correlations among compounds based on similar molecular networks. In this study, we developed a standard-oriented/database-assisted molecular networking (SODA-MN) method for iterative compound annotation analysis to explore the metabolic profiles of polyphenol-rich black raspberry extract metabolized by representative gut bacteria. Starting from a group of polyphenol metabolites, the SODA-MN method predicted the possible polyphenol derivatives by adding or deducting common biotransformation groups and iterative annotating of structure similarity based on fragmentation spectra. Our results showed that 48 polyphenol derivatives in the first round of analysis alone (fragmentation match≥5, spec score >0.5) can be annotated, which were associated with 13 detected polyphenol standards that served as seed compounds. Meanwhile, this method was applied to a time-course study to show the time-dependent changes of polyphenols metabolized by a mix of gut bacteria. In addition, the metabolic capabilities of polyphenols among four representative gut bacteria were compared via our newly developed method and differential polyphenol metabolites were detected. In summary, the SODA-MN method provides a new approach for the annotation of unknown compounds by structure similarity and molecular networking analysis. Our analysis results could provide identification of key polyphenol derivatives that may contribute to the mechanistic investigations of their functions and assist our understanding of how polyphenols and gut bacteria interact to promote human health.

A TD-CIS study of high-harmonic generation of uracil cation fragments

High-harmonic generation (HHG) spectroscopy was investigated from laser ablation plasmas of uracil targets in the experimental work of Hutchinson et al., [Phys. Chem. Chem. Phys. Comparison of high-order harmonic generation in uracil and thymine ablation plumes, 2013, 15, 12308] and of Lopez-Quintas et al., [Appl. Surf. Sci., Characterization of laser-induced plasmas of nucleobases: Uracil and thymine, 2014, 302, 299]. Inspired by these works we computed HHG spectra of uracil cation fragments by means of real-time time-dependent configuration interaction with single excitations (RT-TD-CIS) and continuum-optimal Gaussian basis sets. We calculated the rotationally-averaged HHG spectra of different cation fragments analysing the relation between HHG, geometry of the fragments (linear/nonlinear) and electron dynamics (bound and continuum energy states). Moreover, to simulate the complexity of a sample containing fragments upon ablation, we calculated weighted-rotationally-averaged HHG spectra where the contribution of each fragment is included through weights assigned accordingly to the experimental mass spectra.

Proteomics-based investigation of cerebrovascular molecular mechanisms in cerebral amyloid angiopathy by the FFPE-LMD-PCT-SWATH method

BackgroundCerebral amyloid angiopathy (CAA) occurs in 80% of patients with Alzheimer’s disease (AD) and is mainly caused by the abnormal deposition of Aβ in the walls of cerebral blood vessels. Cerebrovascular molecular mechanisms in CAA were investigated by using comprehensive and accurate quantitative proteomics.MethodsConcerning the molecular mechanisms specific to CAA, formalin-fixed paraffin-embedded (FFPE) sections were prepared from patients having AD neuropathologic change (ADNC) with severe cortical Aβ vascular deposition (ADNC +/CAA +), and from patients having ADNC without vascular deposition of Aβ (ADNC +/CAA −; so called, AD). Cerebral cortical vessels were isolated from FFPE sections using laser microdissection (LMD), processed by pressure cycling technology (PCT), and applied to SWATH (sequential window acquisition of all theoretical fragment ion spectra) proteomics.ResultsThe protein expression levels of 17 proteins in ADNC +/CAA +/H donors (ADNC +/CAA + donors with highly abundant Aβ in capillaries) were significantly different from those in ADNC +/CAA − and ADNC −/CAA − donors. Furthermore, we identified 56 proteins showing more than a 1.5-fold difference in average expression levels between ADNC +/CAA + and ADNC −/CAA − donors, and were significantly correlated with the levels of Aβ or Collagen alpha-2(VI) chain (COL6A2) (CAA markers) in 11 donors (6 ADNC +/CAA + and 5 ADNC −/CAA −). Over 70% of the 56 proteins showed ADNC +/CAA + specific changes in protein expression. The comparative analysis with brain parenchyma showed that more than 90% of the 56 proteins were vascular-specific pathological changes. A literature-based pathway analysis showed that 42 proteins are associated with fibrosis, oxidative stress and apoptosis. This included the increased expression of Heat shock protein HSP 90-alpha, CD44 antigen and Carbonic anhydrase 1 which are inhibited by potential drugs against CAA.ConclusionsThe combination of LMD-based isolation of vessels from FFPE sections, PCT-assisted sample processing and SWATH analysis (FFPE-LMD-PCT-SWATH method) revealed for the first time the changes in the expression of many proteins that are involved in fibrosis, ROS production and cell death in ADNC +/CAA + (CAA patients) vessels. The findings reported herein would be useful for developing a better understanding of the pathology of CAA and for promoting the discovery and development of drugs and biomarkers for CAA.

Upregulation of ribosome complexes at the blood-brain barrier in Alzheimer's disease patients

The cerebrovascular-specific molecular mechanism in Alzheimer’s disease (AD) was investigated by employing comprehensive and accurate quantitative proteomics. Highly purified brain capillaries were isolated from cerebral gray and white matter of four AD and three control donors, and examined by SWATH (sequential window acquisition of all theoretical fragment ion spectra) proteomics. Of the 29 ribosomal proteins that were quantified, 28 (RPLP0, RPL4, RPL6, RPL7A, RPL8, RPL10A, RPL11, RPL12, RPL14, RPL15, RPL18, RPL23, RPL27, RPL27A, RPL31, RPL35A, RPS2, RPS3, RPS3A, RPS4X, RPS7, RPS8, RPS14, RPS16, RPS20, RPS24, RPS25, and RPSA) were significantly upregulated in AD patients. This upregulation of ribosomal protein expression occurred only in brain capillaries and not in brain parenchyma. The protein expression of protein processing and N-glycosylation-related proteins in the endoplasmic reticulum (DDOST, STT3A, MOGS, GANAB, RPN1, RPN2, SEC61B, UGGT1, LMAN2, and SSR4) were also upregulated in AD brain capillaries and was correlated with the expression of ribosomal proteins. The findings reported herein indicate that the ribosome complex, the subsequent protein processing and N-glycosylation-related processes are significantly and specifically upregulated in the brain capillaries of AD patients.

Identification of Isomeric Biomolecules by Infrared Spectroscopy of Solvent-Tagged Ions

The difference in functionality of many isomeric biomolecules requires their analytical identification for life science studies. We present a universal approach for quantitative identification of different small- to medium-sized isomeric biomolecules that can be brought to the gas phase from solution by electrospray ionization (ESI). The method involves infrared (IR) fragment cold ion spectroscopy of analyte molecules that are incompletely desolvated by soft ESI. The use of solvent molecules as natural tags removes a need for adding to solutions any special compounds, which may interfere with liquid chromatography or mass spectrometric measurements. The tested peptides and especially monosaccharides and lipids exhibit highly isomer-specific IR fragment spectra of such noncovalent complexes, which were produced from water, methanol, acetonitrile, and 2-butanol solutions. The relative concentrations in solution mixtures of, for instance, two isomeric dipeptides can be quantified with the accuracy of 1.6% and 2.9% for the acquisition time of 25 min and, potentially, 5 s, respectively; for three isomeric phospho-octapeptides, the accuracy becomes 4.1% and 11% for 17 min and, potentially, 10 s measurements, respectively.