Mass Spectrometry-based Identification Research Articles

Novel Ralstonia species from human infections: improved matrix-assisted laser desorption/ionization time-of-flight mass spectrometry-based identification and analysis of antimicrobial resistance patterns.

A collection of 161 Ralstonia isolates, including 90 isolates from persons with cystic fibrosis, 27 isolates from other human clinical samples, 8 isolates from the hospital environment, 7 isolates from industrial samples, and 19 environmental isolates, was subjected to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) identification and yielded confident species level identification scores for only 62 (39%) of the isolates, including four that proved misidentified subsequently. Whole-genome sequence analysis of 32 representative isolates for which no confident MALDI-TOF MS species level identification was obtained revealed the presence of seven novel Ralstonia species, including three and four that were isolated from cystic fibrosis or other human clinical samples, respectively, and provided the basis for updating an in-house MALDI-TOF MS database. A reanalysis of all mass spectra with the updated MALDI-TOF MS database increased the percentage of isolates with confident species level identification up to 77%. The antimicrobial susceptibility of 30 isolates mainly representing novel human clinical and environmental Ralstonia species was tested toward 17 antimicrobial agents and demonstrated that the novel Ralstonia species were generally multi-resistant, yet susceptible to trimethoprim/sulfamethoxazole, ciprofloxacin, and tigecycline. An analysis of genomic antimicrobial resistance genes in 32 novel and publicly available genome sequences revealed broadly distributed beta-lactam resistance determinants.IMPORTANCEThe present study demonstrated that a commercial matrix-assisted laser desorption/ionization time-of-flight mass spectrometry identification database can be tailored to improve the identification of Ralstonia species. It also revealed the presence of seven novel Ralstonia species, including three and four that were isolated from cystic fibrosis or other human clinical samples, respectively. An analysis of minimum inhibitory concentration values demonstrated that the novel Ralstonia species were generally multi-resistant but susceptible to trimethoprim/sulfamethoxazole, ciprofloxacin, and tigecycline.

MALDI-TOF Mass Spectrometry-Based Identification of Aerobic Mesophilic Bacteria in Raw Unpreserved and Preserved Milk

The number of aerobic mesophilic bacteria in milk is one of the indicators of the hygienic quality of milk. The aim of this work was to determine such aerobic mesophilic bacteria and their number in raw unpreserved milk and milk preserved with sodium azide. In 40 collected samples, the total number of aerobic mesophilic bacteria was determined using the classical method of counting colonies on a nutrient medium according to the international standard HRN EN ISO 4833-1:2013. The results showed a trend of decreasing the number of grown colonies in milk preserved with sodium azide. MALDI-TOF mass spectrometry also successfully identified 392 bacterial colonies in raw unpreserved milk samples and 330 colonies in preserved milk samples. Of these, 30 genera and 54 bacterial species were identified in the raw unpreserved milk samples, while 27 genera and 41 bacterial species were identified in the preserved samples. By using a collective approach, the present study provided a more detailed insight into milk’s hygienic quality and the presence of certain species before and after the preservation with sodium azide.

The proteome of the blood–brain barrier in rat and mouse: highly specific identification of proteins on the luminal surface of brain microvessels by in vivo glycocapture

BackgroundThe active transport of molecules into the brain from blood is regulated by receptors, transporters, and other cell surface proteins that are present on the luminal surface of endothelial cells at the blood–brain barrier (BBB). However, proteomic profiling of proteins present on the luminal endothelial cell surface of the BBB has proven challenging due to difficulty in labelling these proteins in a way that allows efficient purification of these relatively low abundance cell surface proteins.MethodsHere we describe a novel perfusion-based labelling workflow: in vivo glycocapture. This workflow relies on the oxidation of glycans present on the luminal vessel surface via perfusion of a mild oxidizing agent, followed by subsequent isolation of glycoproteins by covalent linkage of their oxidized glycans to hydrazide beads. Mass spectrometry-based identification of the isolated proteins enables high-confidence identification of endothelial cell surface proteins in rats and mice.ResultsUsing the developed workflow, 347 proteins were identified from the BBB in rat and 224 proteins in mouse, for a total of 395 proteins in both species combined. These proteins included many proteins with transporter activity (73 proteins), cell adhesion proteins (47 proteins), and transmembrane signal receptors (31 proteins). To identify proteins that are enriched in vessels relative to the entire brain, we established a vessel-enrichment score and showed that proteins with a high vessel-enrichment score are involved in vascular development functions, binding to integrins, and cell adhesion. Using publicly-available single-cell RNAseq data, we show that the proteins identified by in vivo glycocapture were more likely to be detected by scRNAseq in endothelial cells than in any other cell type. Furthermore, nearly 50% of the genes encoding cell-surface proteins that were detected by scRNAseq in endothelial cells were also identified by in vivo glycocapture.ConclusionsThe proteins identified by in vivo glycocapture in this work represent the most complete and specific profiling of proteins on the luminal BBB surface to date. The identified proteins reflect possible targets for the development of antibodies to improve the crossing of therapeutic proteins into the brain and will contribute to our further understanding of BBB transport mechanisms.

Enhancing Mass spectrometry-based tumor immunopeptide identification: machine learning filter leveraging HLA binding affinity, aliphatic index and retention time deviation

Accurately identifying neoantigens is crucial for developing effective cancer vaccines and improving tumor immunotherapy. Mass spectrometry-based immunopeptidomics has emerged as a promising approach to identifying human leukocyte antigen (HLA) peptides presented on the surface of cancer cells, but false-positive identifications remain a significant challenge. In this study, liquid chromatography-tandem mass spectrometry-based proteomics and next-generation sequencing were utilized to identify HLA-presenting neoantigenic peptides resulting from non-synonymous single nucleotide variations in tumor tissues from 18 patients with renal cell carcinoma or pancreatic cancer. Machine learning was utilized to evaluate Mascot identifications through the prediction of MS/MS spectral consistency, and four descriptors for each candidate sequence: the max Mascot ion score, predicted HLA binding affinity, aliphatic index and retention time deviation, were selected as important features in filtering out identifications with inadequate fragmentation consistency. This suggests that incorporating rescoring filters based on peptide physicochemical characteristics could enhance the identification rate of MS-based immunopeptidomics compared to the traditional Mascot approach predominantly used for proteomics, indicating the potential for optimizing neoantigen identification pipelines as well as clinical applications.

Mass Spectrometry-Based Precise Identification of Citrullinated Histones via Limited Digestion and Biotin Derivative Tag Enrichment.

Histone citrullination is an essential epigenetic post-translational modification (PTM) that affects many important physiological and pathological processes, but effective tools to study histone citrullination are greatly limited due to several challenges, including the small mass shift caused by this PTM and its low abundance in biological systems. Although previous studies have reported frequent occurrences of histone citrullination, these methods failed to provide a high-throughput and site-specific strategy to detect histone citrullination. Recently, we developed a biotin thiol tag that enabled precise identification of protein citrullination coupled with mass spectrometry. However, very few histone citrullination sites were identified, likely due to the highly basic nature of these proteins. In this study, we develop a novel method utilizing limited digestion and biotin derivative tag enrichment to facilitate direct in vivo identification of citrullination sites on histones. We achieve improved coverage of histone identification via partial enzymatic digestion and lysine block by dimethylation. With biotin tag-assisted chemical derivatization and enrichment, we also achieve precise annotation of histone citrullination sites with high confidence. We further compare different fragmentation methods and find that the electron-transfer-dissociation-based approach enables the most in-depth analysis and characterization. In total, we unambiguously identify 18 unique citrullination sites on histones in human astrocytoma U87 cells, including 15 citrullinated sites being detected for the first time. Some of these citrullination sites are observed to exhibit noticeable alterations in response to DNA damage, which demonstrates the superiority of our strategy in understanding the roles of histone citrullination in critical biological processes.

PFKP deubiquitination and stabilization by USP5 activate aerobic glycolysis to promote triple-negative breast cancer progression

BackgroundTriple-negative breast cancer (TNBC) remains the most challenging subtype of breast cancer and lacks definite treatment targets. Aerobic glycolysis is a hallmark of metabolic reprogramming that contributes to cancer progression. PFKP is a rate-limiting enzyme involved in aerobic glycolysis, which is overexpressed in various types of cancers. However, the underlying mechanisms and roles of the posttranslational modification of PFKP in TNBC remain unknown.MethodsTo explore whether PFKP protein has a potential role in the progression of TNBC, protein levels of PFKP in TNBC and normal breast tissues were examined by CPTAC database analysis, immunohistochemistry staining (IHC), and western blotting assay. Further CCK-8 assay, colony formation assay, EDU incorporation assay, and tumor xenograft experiments were used to detect the effect of PFKP on TNBC progression. To clarify the role of the USP5-PFKP pathway in TNBC progression, ubiquitin assay, co-immunoprecipitation (Co-IP), mass spectrometry-based protein identification, western blotting assay, immunofluorescence microscopy, in vitro binding assay, and glycolysis assay were conducted.ResultsHerein, we showed that PFKP protein was highly expressed in TNBC, which was associated with TNBC progression and poor prognosis of patients. In addition, we demonstrated that PFKP depletion significantly inhibited the TNBC progression in vitro and in vivo. Importantly, we identified that PFKP was a bona fide target of deubiquitinase USP5, and the USP5-mediated deubiquitination and stabilization of PFKP were essential for cancer cell aerobic glycolysis and TNBC progression. Moreover, we found a strong positive correlation between the expression of USP5 and PFKP in TNBC samples. Notably, the high expression of USP5 and PFKP was significantly correlated with poor clinical outcomes.ConclusionsOur study established the USP5-PFKP axis as an important regulatory mechanism of TNBC progression and provided a rationale for future therapeutic interventions in the treatment of TNBC.

Human robotic surgery with intraoperative tissue identification using rapid evaporation ionisation mass spectrometry

Instantaneous, continuous, and reliable information on the molecular biology of surgical target tissue could significantly contribute to the precision, safety, and speed of the intervention. In this work, we introduced a methodology for chemical tissue identification in robotic surgery using rapid evaporative ionisation mass spectrometry. We developed a surgical aerosol evacuation system that is compatible with a robotic platform enabling consistent intraoperative sample collection and assessed the feasibility of this platform during head and neck surgical cases, using two different surgical energy devices. Our data showed specific, characteristic lipid profiles associated with the tissue type including various ceramides, glycerophospholipids, and glycerolipids, as well as different ion formation mechanisms based on the energy device used. This platform allows continuous and accurate intraoperative mass spectrometry-based identification of ablated/resected tissue and in combination with robotic registration of images, time, and anatomical positions can improve the current robot-assisted surgical platforms and guide surgical strategy.

Mass spectrometry in clinical laboratory: applications and future prospects

Innovations in laboratory medicine face additional challenges due to the unmet need for extremely precise methods of disease diagnosis. Developments in mass spectrometry-based disease biomarker identification are constantly expanding the field of clinical diagnosis. More mass spectrometry-based in vitro diagnostics are anticipated to move from the bench to the bedside shortly, although several are currently incorporated into standard clinical procedures. The molecular detection by mass spectrometry technique is very effective in diagnosis of the disease and therapeutic monitoring because of its extremely high sensitivity, specificity, and short turnaround time. Mass spectrometry is a potent analytical instrument that may be used to analyse a variety of materials and matrices; its use in clinical laboratory medicine applications is rising. For clinical prognostics and diagnostic purposes, mass spectrometry imaging has been widely utilized to distinguish between healthy and diseased tissues. Modern single-cell studies will benefit from its cutting-edge applications, which will offer comprehensive cellular biochemical data for mechanistic comprehension and, eventually, the development of therapeutic interventions. Within the field of laboratory medicine, the application of mass spectrometry is crucial, especially in terms of diagnostics and therapeutic drug monitoring. This review on the clinical application of mass spectrometry and its future prospects promises an insightful exploration of the evolving landscape of mass spectrometry in clinical settings, delving into its current applications and shedding light on its potential future advancements, for which a comprehensive search in the PubMed, ScienceDirect, and Web of Science databases was conducted.

Mechanistic and kinetic aspects of florfenicol degradation by [rad]OH: Chloride moiety resistance

Antibiotic residues in aquatic environments can be effectively degraded by hydroxyl radical (OH)-based advanced oxidation processes (AOPs). However, the reaction kinetics and mechanisms have not been comprehensive determined due to the limitations of conventional competition kinetic methods and mass spectrometry-based product identification, as these methods fail to exclude interference from secondary radicals and are unable to capture unstable intermediates or transient species. In this study, these limitations were overcome using laser flash photolysis (LFP) and density functional theory (DFT) calculations, allowing accurate determination of the OH-initiated reaction kinetics and degradation mechanisms of florfenicol (FF), a model veterinary antibiotic compound that is frequently detected in the environment. Based on the LFP experiment results, the second order rate constant (k) between OH and FF was determined to be 1.96 × 109 M−1 s−1 by tracking the typical signal of (SCN)2−. Furthermore, DFT calculations revealed two distinct mechanisms for OH addition to the benzene ring and identified hydrogen atom abstraction (HAA) reaction from chiral carbons as being the most favorable initial reaction for OH. In addition, the destruction of chlorine moiety occurred via hydroxylation-chlorine abstraction, rather than direct chlorine abstraction or substitution reactions. The resistance of chlorine moiety to degradation during the initial oxidation process, resulted in the formation of chlorine-containing by-products. This study provided a novel approach to comprehensively investigate the mechanisms of emerging contaminants elimination during OH-based AOPs.

Two-Dimensional Polyacrylamide Gel Electrophoresis Coupled with Nanoliquid Chromatography-Tandem Mass Spectrometry-Based Identification of Differentially Expressed Proteins and Tumorigenic Pathways in the MCF7 Breast Cancer Cell Line Transfected for Jumping Translocation Breakpoint Protein Overexpression.

The identification of new genes/proteins involved in breast cancer (BC) occurrence is widely used to discover novel biomarkers and understand the molecular mechanisms of BC initiation and progression. The jumping translocation breakpoint (JTB) gene may act both as a tumor suppressor or oncogene in various types of tumors, including BC. Thus, the JTB protein could have the potential to be used as a biomarker in BC, but its neoplastic mechanisms still remain unknown or controversial. We previously analyzed the interacting partners of JTBhigh protein extracted from transfected MCF7 BC cell line using SDS-PAGE complemented with in-solution digestion, respectively. The previous results suggested the JTB contributed to the development of a more aggressive phenotype and behavior for the MCF7 BC cell line through synergistic upregulation of epithelial-mesenchymal transition (EMT), mitotic spindle, and fatty acid metabolism-related pathways. In this work, we aim to complement the previously reported JTB proteomics-based experiments by investigating differentially expressed proteins (DEPs) and tumorigenic pathways associated with JTB overexpression using two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). Statistically different gel spots were picked for protein digestion, followed by nanoliquid chromatography-tandem mass spectrometry (nLC-MS/MS) analysis. We identified six DEPs related to the JTBhigh condition vs. control that emphasize a pro-tumorigenic (PT) role. Twenty-one proteins, which are known to be usually overexpressed in cancer cells, emphasize an anti-tumorigenic (AT) role when low expression occurs. According to our previous results, proteins that have a PT role are mainly involved in the activation of the EMT process. Interestingly, JTB overexpression has been correlated here with a plethora of significant upregulated and downregulated proteins that sustain JTB tumor suppressive functions. Our present and previous results sustain the necessity of the complementary use of different proteomics-based methods (SDS-PAGE, 2D-PAGE, and in-solution digestion) followed by tandem mass spectrometry to avoid their limitations, with each method leading to the delineation of specific clusters of DEPs that may be merged for a better understanding of molecular pathways and neoplastic mechanisms related to the JTB's role in BC initiation and progression.

Subcellular proteomics for determining iron-limited remodeling of plastids in the model diatom Thalassiosira pseudonana (Bacillariophyta).

Diatoms are important primary producers in the world's oceans, yet their growth is constrained in large regions by low bioavailable iron (Fe). Low-Fe stress-induced limitation of primary production is due to requirements for Fe in components of essential metabolic pathways including photosynthesis and other chloroplast plastid functions. Studies have shown that under low-Fe stress, diatoms alter plastid-specific processes, including components of electron transport. These physiological changes suggest changes of protein content and in protein abundances within the diatom plastid. While in silico predictions provide putative information on plastid-localized proteins, knowledge of diatom plastid proteins remains limited in comparison to well-studied model photosynthetic organisms. To address this, we employed shotgun proteomics to investigate the proteome of subcellular plastid-enriched fractions from Thalassiosira pseudonana to gain a better understanding of how the plastid proteome is remodeled in response to Fe limitation. Using mass spectrometry-based peptide identification and quantification, we analyzed T. pseudonana grown under Fe-replete and -limiting conditions. Through these analyses, we inferred the relative quantities of each protein, revealing that Fe limitation regulates major metabolic pathways in the plastid, including the Calvin cycle. Additionally, we observed changes in the expression of light-harvesting proteins. In silico localization predictions of proteins identified in this plastid-enriched proteome allowed for an in-depth comparison of theoretical versus observed plastid-localization, providing evidence for the potential of additional protein import pathways into the diatom plastid.

All ions must serve: The role of various regimes of data acquisition in joint classifier for intraoperative mass spectrometry-based glial tumour identification

Background: Ambient ionisation mass spectrometry, in combination with machine learning techniques, provides a promising tool for rapid intraoperative tumour tissue identification. However, deficiency of non-tumour control samples leads to the classifiers overfitting, especially in neurosurgical applications. Ensemble learning approaches based on the analysis of multimodal mass spectrometry data are able to overcome the overfitting problem through the extended time of data acquisition. In this work, the contribution of each regime of the data acquisition and the requirements for the metrics for further mass spectrometry set-up optimisation are evaluated. Methods: Two independent datasets of the multimodal molecular profiles, a total of 81 glial tumour and non-tumour pathological tissues, were analysed in a cross-validation set-up. The XGboost algorithm was used to build classifiers, and their performance was evaluated using different testing and validating sets. The individual classifiers for each mass spectrometry regime were aggregated into joint classifiers. The impact of each regime was evaluated by the exclusion of specific regimes from the aggregation. Results: The aggregated classifiers with excluded regimes show lower accuracy for most, but not all, excluded regimes. False positive rates have been found to be increased in most cases proving the strong effect of the ensemble learning approach on the overcoming of the “small sample size” problem. Conclusions: The impact of each group of regimes – with different ion polarity, resolution or mass range of spectra was found to be non-linear. It might be attributed to biochemical reasons as well as to the physical limitation of mass analysers. The required metrics for the evaluation of each regime contribution to the classification efficiency should be a numerical estimation of how the classifier depends on any given regime and could not be estimated only by excluding any group of regimes at all.

Genetically encoded photocatalytic protein labeling enables spatially-resolved profiling of intracellular proteome

Mapping the subcellular organization of proteins is crucial for understanding their biological functions. Herein, we report a reactive oxygen species induced protein labeling and identification (RinID) method for profiling subcellular proteome in the context of living cells. Our method capitalizes on a genetically encoded photocatalyst, miniSOG, to locally generate singlet oxygen that reacts with proximal proteins. Labeled proteins are conjugated in situ with an exogenously supplied nucleophilic probe, which serves as a functional handle for subsequent affinity enrichment and mass spectrometry-based protein identification. From a panel of nucleophilic compounds, we identify biotin-conjugated aniline and propargyl amine as highly reactive probes. As a demonstration of the spatial specificity and depth of coverage in mammalian cells, we apply RinID in the mitochondrial matrix, capturing 477 mitochondrial proteins with 94% specificity. We further demonstrate the broad applicability of RinID in various subcellular compartments, including the nucleus and the endoplasmic reticulum (ER). The temporal control of RinID enables pulse-chase labeling of ER proteome in HeLa cells, which reveals substantially higher clearance rate for secreted proteins than ER resident proteins.

Application of MALDI-TOF MS for enumerating bacterial constituents of defined consortia

Characterization of live biotherapeutic product (LBP) batches typically includes a measurement of viability, such as colony forming units (CFU). However, strain-specific CFU enumeration assays can be complicated by the presence of multiple organisms in a single product with similar growth requirements. To overcome specific challenges associated with obtaining strain-specific CFU values from multi-strain mixtures, we developed a method combining mass spectrometry-based colony identification with a traditional CFU assay. This method was assessed using defined consortia made from up to eight bacterial strains. Among four replicate batches of an eight-strain mixture, observed values differed from expected values by less than 0.4 log10 CFU among all strains measured (range of differences, -0.318 to + 0.267). The average difference between observed and expected values was + 0.0308 log10 CFU, with 95% limits of agreement from -0.347 to 0.408 (Bland–Altman analysis). To estimate precision, a single batch of eight-strain mixture was assayed in triplicate by three different users, for a total of nine measurements. Pooled standard deviation values ranged from 0.067 to 0.195 log10 CFU for the eight strains measured, and user averages did not differ significantly. Leveraging emerging mass-spectrometry-based colony identification tools, a novel method for simultaneous enumeration and identification of viable bacteria from mixed-strain consortia was developed and tested. This study demonstrates the potential for this approach to generate accurate and consistent measurements of up to eight bacterial strains simultaneously and may provide a flexible platform for future refinements and modifications.Key points• Enumeration of live biotherapeutics is essential for product quality and safety.• Conventional CFU counting may not differentiate between strains in microbial products.• This approach was developed for direct enumeration of mixed bacterial strains simultaneously.

UHPLC-Quadrupole-Exactive-Orbitrap-MS/MS-based putative identification for Eucommiae Folium (Duzhongye) and its quality-marker candidate for pharmacopeia.

Eucommiae Folium (Duzhongye) is a traditional Chinese medicine with a long history of use in China. However, its quality-marker (Q-marker) in Chinese Pharmacopoeia is poorly defined nowadays. The study therefore conducted an ultra-high-performance liquid chromatography coupled with hybrid quadrupole-orbitrap tandem mass spectrometry (UHPLC-Quadrupole-Exactive-Orbitrap MS/MS) analysis to obtain accurate data. The obtained data were then compared with authentic standards library using Xcalibur 4.1 software package and TraceFinder General Quan. Through the comparison, the study has putatively identified 26 bioactive compounds, which include 17 flavonoid derivatives (catechin, quercetin 3-gentiobioside, quercetin 3-O-β-D-glucose-7-O-β-D-gentiobioside, taxifolin, myricetin 3-O-galactoside, myricitrin, hyperoside, rutin, isoquercitrin, quercetin 3-O-β-xylopyranoside, quercitrin, isorhamnetin 3-O-β-D-glucoside, quercetin, kaempferol, S-eriodictyol, S-naringenin, and phloridzin), four caffeoylquinic acids (neochlorogenic acid, chlorogenic acid, isochlorogenic acid A, and isochlorogenic acid C), two alkaloids (vincamine and jervine), one lignan (pinoresinol), one xanthone (cowaxanthone B), and one steroid (cholesteryl acetate). Of these, flavonoid isoquercitrin is recommended as the new and additional pharmacopoeia Q-marker candidate, which can not only overcome the unreliability of old Q-marker but also recognize the possible counterfeit. This article is protected by copyright. All rights reserved.

De novo assembled transcriptomics assisted label-free quantitative proteomics analysis reveals sex-specific proteins in the intestinal tissue of Haemaphysalis qinghaiensis.

The hard tick Haemaphysalis qinghaiensis is the vector of a wide variety of infectious agents, such as spirochetes and other bacteria as well as viruses in the western plateau of China. Tick midgut is the key tissue involved in the host-pathogen-vector interface. Multiple midgut proteins are related to key functions in blood digestion, tick survival, and tick-borne pathogen transmission. However, information on the sex-specific proteins expressed in the midgut tissue of H. qinghaiensis for which the genome has not been sequenced is limited. Hence, we assembled and characterized the transcriptome of the H. qinghaiensis midgut and identified the differentially expressed genes (DEGs) in female and male ticks. The sequencing of the mRNA for this nonmodel species is essential for producing a protein database for mass spectrometry-based identification. Here, we combined high-throughput parallel sequencing and label-free quantitative proteomics analysis to extensively characterize the tick midgut using massive RNA sequencing and mass spectrometry, which allowed the detection of genes and proteins. A total of 279,186 transcripts were annotated into 125,790 coding sequences (CDSs), which were manually curated into 96 different gene families. A total of 12,837 DEGs between the two sexes were found by RNA-seq analysis. Of these, 5401 were upregulated genes, while 7436 were downregulated genes. The most common molecular functions were those related to the endocrine system, translation, signal transduction, transport, and catabolism. Meanwhile, the most common biological processes were related to cellular processes, metabolic processes, cellular anatomical entities, and cargo receptor activities. An analysis of the label-free protein quantitation dataset showed 272 upregulated proteins and 46 downregulated proteins when the fold-change was >2.0 (LC-MS/MS). Association analysis of the transcriptome and proteome with GO functional enrichment showed that the majority of the genes (proteins) were those related to catalytic activity, binding, cellular processes, metabolic processes, and responses to stimuli. This study aims to elucidate the digestive physiology of H. qinghaiensis as well as its physiological sexual dimorphism. This will allow the identification of protein candidates with physiological importance that could be used as targets to control the vector as well as the transmission of tick-borne pathogens to humans and animals.

Modeling Lower-Order Statistics to Enable Decoy-Free FDR Estimation in Proteomics.

One of the chief objectives in mass spectrometry-based peptide identification in proteomics is the statistical validation of top-scoring peptide-spectrum matches (PSMs) in the form of false discovery rate (FDR) estimation. Existing methods construct a null model that captures the characteristics of incorrect target PSMs to estimate the FDR, most often with the help of decoys. Decoy-based methods, however, increase the computational cost and rely on the difficult-to-verify assumption that decoy PSMs constitute a sufficient and representative sample of the population of possible incorrect target PSMs. On the other hand, the possibility of FDR estimation assisted by the plentiful non-top-scoring PSMs, which are almost always incorrect, has been scarcely explored. In this work, we propose a novel decoy-free procedure for developing null models for top-scoring PSMs using the transformed e-value (TEV) score and the distributions of non-top-scoring target PSMs. The method relies on a theoretically derivable relationship between the parameters of the distributions of lower-order statistics of the TEV score and a necessary empirical optimization to fit a single parameter to actual data. The framework was tested on multiple different data sets and two search engines. We present evidence that our method is comparable to and occasionally outperforms popular decoy-free and decoy-based methods in FDR estimation.

Changes in a Protein Profile Can Account for the Altered Phenotype of the Yeast Saccharomyces cerevisiae Mutant Lacking the Copper-Zinc Superoxide Dismutase.

Copper-zinc superoxide dismutase (SOD1) is an antioxidant enzyme that catalyzes the disproportionation of superoxide anion to hydrogen peroxide and molecular oxygen (dioxygen). The yeast Saccharomyces cerevisiae lacking SOD1 (Δsod1) is hypersensitive to the superoxide anion and displays a number of oxidative stress-related alterations in its phenotype. We compared proteomes of the wild-type strain and the Δsod1 mutant employing two-dimensional gel electrophoresis and detected eighteen spots representing differentially expressed proteins, of which fourteen were downregulated and four upregulated. Mass spectrometry-based identification enabled the division of these proteins into functional classes related to carbon metabolism, amino acid and protein biosynthesis, nucleotide biosynthesis, and metabolism, as well as antioxidant processes. Detailed analysis of the proteomic data made it possible to account for several important morphological, biochemical, and physiological changes earlier observed for the SOD1 mutation. An example may be the proposed additional explanation for methionine auxotrophy. It is concluded that protein comparative profiling of the Δsod1 yeast may serve as an efficient tool in the elucidation of the mutation-based systemic alterations in the resultant S. cerevisiae phenotype.

Biotic transformation products of sulfonamides in environmental water samples: High-resolution mass spectrometry-based tentative identification by a suspect screening approach

The presence of pharmaceuticals in the aquatic environment is mainly due to their release from the effluents of the wastewater treatment plants (WWTPs), which are unable to completely remove them and their transformation products (TPs). Sulfonamides (SAs) are a synthetic antibacterial class used for the treatment of both human and animal infections; they have often been reported in surface water, thus contributing to the antibiotic resistance emergency. Monitoring SA TPs should be important as well because they could still exert some pharmaceutical activity; however, many TPs are still unknown since several transformation processes are possible (e. g. human and animal metabolism, WWTP activities, environmental factors etc.). In this work, three of the most used SAs, i.e., sulfamethoxazole (SMX), sulfapyridine (SPY), and sulfadiazine (SDZ), were incubated for 20 days in a batch reactor with activated sludge under controlled conditions. Then, the water sample was extracted and analyzed by ultra-high performance liquid chromatography-high resolution mass spectrometry in the data dependent acquisition (DDA) mode. Starting from the literature data, the possible transformation pathways were studied, and for each SA, a list of TPs was hypothesized and used for the identification. The raw data files were processed with Compound Discoverer, and 44 TPs (18, 13, and 13 TPs for SMX, SPY, and SDZ, respectively), including multiple TPs, were manually validated. To overcome the limitation of the DDA, the identified TPs were used in an inclusion list to analyze WWTP samples by a suspect screening approach. In this way, 4 SMX TPs and 5 SPY TPs were tentatively identified together with their parent compounds. Among these TPs, 5 of 9 were acetylated forms, in agreement with previous literature reporting that acetylation is the predominant SA transformation.

Major benznidazole metabolites in patients treated for Chagas disease: Mass spectrometry-based identification, structural analysis and detoxification pathways

Benznidazole is the drug of choice for the treatment of Chagas disease, but its metabolism in humans is unclear. Here, we identified and characterized the major benznidazole metabolites and their biosynthetic mechanisms in humans by analyzing the ionic profiles of urine samples from patients and untreated donors through reversed-phase UHPLC-ESI-QTOF-MS and UHPLC-ESI-QqLIT-MS. A strategy for simultaneous detection and fragmentation of characteristic positive and negative ions was employed using information-dependent acquisitions (IDA). Selected precursor ions, neutral losses, and MS3 experiments complemented the study. A total of six phase-I and ten phase-II metabolites were identified and structurally characterized in urine of benznidazole-treated patients. Based on creatinine-corrected ion intensities, nitroreduction to amino-benznidazole (M1) and its subsequent N-glucuronidation to M5 were the main metabolic pathways, followed by imidazole-ring cleavage, oxidations, and cysteine conjugations. This extensive exploration of benznidazole metabolites revealed potentially toxic structures in the form of glucuronides and glutathione derivatives, which may be associated with recurrent treatment adverse events; this possibility warrants further exploration in future clinical trials. Incorporation of this knowledge of the benznidazole metabolic profile into clinical pharmacology trials could lead to improved treatments, facilitate the study of possible drug-drug interactions, and even mitigation of adverse drug reactions.