High-multiplexed monitoring of protein biomarkers in the sentinel Gammarus fossarum by targeted scout-MRM assay, a new vision for ecotoxicoproteomics

Delineating protein biomarkers for gastric cancers: A catalogue of mass spectrometry-based markers and assessing their suitability for targeted proteomics applications

Gastric cancer (GC) is a global health concern. To facilitate improved management of GCs protein biomarkers have been identified through mass spectrometry-based proteomics platforms. In order to exhibit clinical utility of such data, we congregated over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the mass spectrometry platforms, association of the protein with infectious agents, protein identifiers, sample size and clinical characters of samples used with details on validation. Development of targeted proteomics methods is the cornerstone for pursuing these markers into clinical utility. Therefore, we developed Protein Biomarker Matrix for Gastric Cancer (PBMGC), a simple catalogue of robustness of each protein. This analysis yielded the identification of robust tissue, serum, urine and prognostic protein panels which can be further tested for their clinical utility. We also ascertained proteotypic tryptic peptides of 5631 proteins suitable for developing MRM assays. Extensive characterization of these peptides was carried out to record peptide ions, mass/charge and enhanced specific peptide features. With the vision of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). Users can browse and download the data and improve GCPDB by submitting recently published data. SIGNIFICANCE: Mass spectrometry-based proteomics platforms have accumulated substantial data on protein differential regulation in gastric cancer (GC) clinical samples. The utility of such data in clinical applications is limited by search for suitable biomarker panels for assessing GCs. We assembled over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the corresponding details including mass spectrometry platforms, status on the association of the protein with infectious agents, protein identifiers from different databases, sample size and clinical characters of samples used in test and control conditions along with details on their validation. Towards the vision of utilizing these markers in clinical assays, Protein Biomarker Matrix for Gastric Cancer (PBMGC) was developed and clinically relevant multi-protein panels were identified. We also demonstrated identification and characterization of tryptic proteotypic tryptic peptides of 5631 proteins biomarkers of GCs which are suitable for development of multiple reaction monitoring (MRM) assays in a SCIEX QTRAP instrument. With the moto of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). The users can browse and download details on different markers and improve GCPDB by submitting recently published data. Such an analysis could lay a cornerstone for building more such resources or conduct such analysis in different clinical conditions to uptake and develop targeted proteomics as the method of choice for clinical applications.

Multilayer Annotation Strategy AnnoSePS: Disentangling the Intricate Structure of Selenium-Containing Polysaccharides Based on Preferential Fragmentation Patterns

Precision mapping of selenium at structural and position levels poses significant challenges in selenium-containing polysaccharide identification. Due to the absence of reference spectra, database-centric approaches are still limited in the discovery of selenium binding sites and distinction among different isomeric structures. A multilayer annotation strategy, AnnoSePS, is proposed for achieving the identification of seleno-substituent and the unbiased profiling of polysaccharides. Applying Snoop-triggered multiple reaction monitoring (Snoop-MRM) identified multidimensional monosaccharides in selenium-containing polysaccharides. Galactose, galacturonic acid, and glucose were the predominant monosaccharides with a molar ratio of 25.19, 19.45, and 11.72, respectively. Selenium present in seleno-rhamnose was found to substitute the hydroxyl group located at C-1 positions through the formation of a Se-H bond. Ions C6H9O3Se-, C6H7O3Se-, C5H5O3Se-, C4H5O2Se-, C3H5O2Se-, C2H3O2Se-, and CHOSe- were defined as the characteristic fragments of seleno-rhamnose. The agglomerative hierarchical clustering algorithm is applied to group spectra from each run based on the characteristic information. Preferential fragmentation patterns in mass spectrometry are revealed by training a probabilistic model. A list of candidate oligosaccharides is generated by step-by-step browsing through the transition pairs for all reference spectra and applying the transitions (addition, insertion, removal, and substitution) to reference structures. Combining time course analyses revealed the linkage composition of selenium-containing oligosaccharides. Glycosidic linkages were annotated based on a synthesis-driven approach. T-Galactose (16.67 ± 5.23%) and T-Galacturonic acid (11.54 ± 4.66%) were the predominant linkage residues. As the database-independent mapping strategy, AnnoSePS makes it possible to comprehensively interrogate spectral data and dissect the fine structure of selenium-containing polysaccharides.

Concomitant investigation of crustacean amphipods lipidome and metabolome during the molting cycle by Zeno SWATH data-independent acquisition coupled with electron activated dissociation and machine learning

BACKGROUND

DIA (Data-Independent Acquisition) is a powerful technique in Liquid Chromatography coupled with high-resolution tandem Mass Spectrometry (LC-MS/MS) initially developed for proteomics studies and recently emerging in metabolomics and lipidomics. It provides a comprehensive and unbiased coverage of molecules with improved reproducibility and quantitative accuracy compared to Data-Dependent Acquisition (DDA). Combined with the Zeno trap and Electron-Activated Dissociation (EAD), DIA enhances data quality and structural elucidation compared to conventional fragmentation under CID. These tools were applied to study the lipidome and metabolome of the freshwater amphipod Gammarus fossarum, successfully discriminating stages and highlighting significant biological features. Despite being underused, DIA, along with the Zeno trap and EAD, holds great potential for advancing research in the omics field.

RESULTS

DIA combined with the Zeno trap enhances detection reproducibility compared to conventional DDA, improving fragmentation spectra quality and putative identifications. LC coupled with Zeno-SWATH-DIA methods were used to characterize molecular changes in reproductive cycle of female gammarids. Multivariate data analysis including Principal Component Analysis and Partial Least Square Discriminant Analysis successfully identified significant features. EAD fragmentation helped to identify unknown features and to confirm their molecular structure using fragmentation spectra database annotation or machine learning. EAD database matching accurately annotated five glycerophospholipids, including the position of double bonds on fatty acid chain moieties. SIRIUS database predicted structures of unknown features based on experimental fragmentation spectra to compensate for database incompleteness.

SIGNIFICANCE

Reproducible detection of features and confident identification of putative compounds are pivotal stages within analytical pipelines. The DIA approach combined with Zeno pulsing enhances detection sensitivity and targeted fragmentation with EAD in positive polarity provides orthogonal fragmentation information. In our study, Zeno-DIA and EAD thereby facilitated a comprehensive and insightful exploration of pertinent biological molecules associated with the reproductive cycle of gammarids. The developed methodology holds great promises for identifying informative biomarkers on the health status of an environmental sentinel species.

Electron-activated dissociation (EAD) for the complementary annotation of metabolites and lipids through data-dependent acquisition analysis and feature-based molecular networking, applied to the sentinel amphipod Gammarus fossarum

The past decades have marked the rise of metabolomics and lipidomics as the -omics sciences which reflect the most phenotypes in living systems. Mass spectrometry-based approaches are acknowledged for both quantification and identification of molecular signatures, the latter relying primarily on fragmentation spectra interpretation. However, the high structural diversity of biological small molecules poses a considerable challenge in compound annotation. Feature-based molecular networking (FBMN) combined with database searches currently sets the gold standard for annotation of large datasets. Nevertheless, FBMN is usually based on collision-induced dissociation (CID) data, which may lead to unsatisfying information. The use of alternative fragmentation methods, such as electron-activated dissociation (EAD), is undergoing a re-evaluation for the annotation of small molecules, as it gives access to additional fragmentation routes. In this study, we apply the performances of data-dependent acquisition mass spectrometry (DDA-MS) under CID and EAD fragmentation along with FBMN construction, to perform extensive compound annotation in the crude extracts of the freshwater sentinel organism Gammarus fossarum. We discuss the analytical aspects of the use of the two fragmentation modes, perform a general comparison of the information delivered, and compare the CID and EAD fragmentation pathways for specific classes of compounds, including previously unstudied species. In addition, we discuss the potential use of FBMN constructed with EAD fragmentation spectra to improve lipid annotation, compared to the classic CID-based networks. Our approach has enabled higher confidence annotations and finer structure characterization of 823 features, including both metabolites and lipids detected in G. fossarum extracts.

Identification and organ-specific patterns of expression of two metallothioneins in the sentinel species Gammarus fossarum

Metal pollution is a major concern for aquatic environments. Widespread contamination by various trace metal ions has been described in freshwater streams as well as their subsequent bioaccumulation, potentially leading to toxicity and trophic transfer. Metallothioneins constitute an evolutionary conserved family of low molecular weight, cysteine-rich, metal-chelating proteins, whose known physiological functions are the maintenance of the homeostasis of essential metals, the detoxification of non-essential metals, and the protection against oxidative stress and free radicals. In this study, we identified two metallothionein-coding transcripts, mt1 and mt2, in the transcriptome of the amphipod Gammarus fossarum, a sentinel species widely used to assess the quality of watersheds. For the first time, we investigated the organ-specific patterns of expression of these two mt transcripts at the individual level in the gills and the caeca of this small crustacean. In silico analysis and experimental exposures to environmentally relevant concentrations of cadmium, zinc and silver showed that G. fossarum mt1 induction is stronger after Cd exposure compared to the other tested metals. G. fossarum mt1 was more significantly induced in the caeca than in the gills of exposed organisms for any metal exposure, while G. fossarum mt2 was, at least at the individual level, more inducible in the gills than in the caeca of G. fossarum exposed to Cd and Zn. Our results provide new genetic resources that will help to improve the understanding of metal homeostasis in this sentinel species.

Scout triggered multiple reaction monitoring mass spectrometry for the rapid transfer of large multiplexed targeted methods in metabolomics

The field of metabolomics based on mass spectrometry has grown considerably in recent years due to the need to detect and, above all, quantify a very large number of metabolites, simultaneously. Up to now, targeted multiplexed analysis on complex samples by Liquid Chromatography coupled with tandem Mass Spectrometry (LC-MS/MS) has relied almost exclusively on compound detection based on absolute retention times, as in the Scheduled-MRM (sMRM) approach. Those methods turn out to be poorly transferable from one instrument to another and result in a time-consuming and tedious method development involving a significant number of critical parameters that need specific re-optimisation. To address this challenge, we introduce a novel acquisition mode called scout-triggered MRM (stMRM). In stMRM, a marker transition is used to trigger MS analysis for a group of dependent target analytes. These marker transitions are strategically distributed throughout the chromatographic run, and the dependent analytes are associated based on their retention times. The result is a targeted assay that remains robust even in the presence of retention time shifts. A 3 to 5-fold increase in the number of detected transitions associated to plasma metabolites was obtained when transferring from a direct application of a published sMRM to a stMRM method. This significant improvement highlights the universal applicability of the stMRM method, as it can be implemented on any LC system without the need for extensive method development. We subsequently illustrate the robustness of stMRM in modified chromatographic elution conditions. Despite a large change in metabolite's selectivity, the multiplexed assay successfully recovered 70% of the monitored transitions when consequently modifying the gradient method. These findings demonstrate the versatility and adaptability of stMRM, opening new avenues for the development of highly multiplexed LC-MS/MS methods in metabolomics. These methods are characterized by their analytical transparency and straightforward implementation using existing literature data.

Protecting our environment, a motivating outdoor game for proteomics!

The global Earth ecosystem faces many intertwined threats, primarily anthropogenic pollution, drastic reduction of wild spaces, faster spread of pathogens, and global climate warming. Ecotoxicology, the integration of toxicology and ecology, aims to describe the effects of toxicants on organisms, whether at the level of the population, the community, the ecosystem, or the biosphere. Sentinel species are employed to assess threats to life, giving advance warning of danger. In this issue of Proteomics, Wilde and collaborators (Proteomics 2022, 22, https://doi.org/10.1002/pmic.202100289) present a comprehensive coverage of the proteome of the crustacean Daphnia magna, a species used to evaluate aquatic pollution. This study illustrates how current shotgun proteomics technology allows straightforward quantitation of any protein for whole animals or dissected organs, making global molecular phenotyping a reality for animals. Tandem mass spectrometry operated in data-independent acquisition can be used to compare the response of sentinels to various environmental conditions. The current low number of well-annotated animal or plant genomes, the high diversity of genetic backgrounds of each species, and the paucity of knowledge about protein functions for most of the relevant sentinels pose huge challenges for data interpretation. As a result, ecology and ecotoxicology today constitute an exceptional field for proteomics.

Can Proteomics Be Considered as a Valuable Tool to Assess the Toxicity of Nanoparticles in Marine Bivalves?

Exposure to nanoparticles (NPs) has been identified as a major concern for marine ecosystems. Because of their peculiar physico-chemical features, NPs are accumulated in marine organisms, which suffer a variety of adverse effects. In particular, bivalve mollusks represent a unique target for NPs, mainly because they are suspension-feeders with highly developed processes for cellular internalization of nano- and micrometric particles. Several studies have demonstrated that the uptake and the accumulation of NPs can induce sub-lethal effects towards marine bivalves. However, to understand the real risk of NP exposures the application of the so-called “omics” techniques (e.g., proteomics, genomics, metabolomics, lipidomics) has been suggested. In particular, proteomics has been used to study the effects of NPs and their mechanism(s) of action in marine bivalves, but to date its application is still limited. The present review aims at summarizing the state of the art concerning the application of proteomics as a tool to investigate the effects of nanoparticles on the proteome of marine bivalves, and to critically discuss the advantages and limitations of proteomics in this field of research. Relying on results obtained by studies that applied proteomics on bivalve tissues, proteomics application needs to be considered cautiously as a promising and valuable tool to shed light on toxicity and mechanism(s) of action of NPs. Although on one hand, the analysis of the current literature demonstrated undeniable strengths, potentiality and reliability of proteomics, on the other hand a number of limitations suggest that some gaps of knowledge need to be bridged, and methodological and technical improvements are necessary before proteomics can be readily and routinely applied to nanotoxicology studies.