MegaGO: A Fast Yet Powerful Approach to Assess Functional Gene Ontology Similarity across Meta-Omics Data Sets

Proceedings of the EuBIC-MS developers meeting 2023

The 2023 European Bioinformatics Community for Mass Spectrometry (EuBIC-MS) Developers Meeting was held from January 15th to January 20th, 2023, in Congressi Stefano Franscin at Monte Verità in Ticino, Switzerland. The participants were scientists and developers working in computational mass spectrometry (MS), metabolomics, and proteomics. The 5-day program was split between introductory keynote lectures and parallel hackathon sessions focusing on "Artificial Intelligence in proteomics" to stimulate future directions in the MS-driven omics areas. During the latter, the participants developed bioinformatics tools and resources addressing outstanding needs in the community. The hackathons allowed less experienced participants to learn from more advanced computational MS experts and actively contribute to highly relevant research projects. We successfully produced several new tools applicable to the proteomics community by improving data analysis and facilitating future research.

Biodiversity Analysis of Metaproteomics Samples with Unipept: A Comprehensive Tutorial

Metaproteomics has become a crucial omics technology for studying microbiomes. In this area, the Unipept ecosystem, accessible at https://unipept.ugent.be , has emerged as a valuable resource for analyzing metaproteomic data. It offers in-depth insights into both taxonomic distributions and functional characteristics of complex ecosystems. This tutorial explains essential concepts like Lowest Common Ancestor (LCA) determination and the handling of peptides with missed cleavages. It also provides a detailed, step-by-step guide on using the Unipept Web application and Unipept Desktop for thorough metaproteomics analyses. By integrating theoretical principles with practical methodologies, this tutorial empowers researchers with the essential knowledge and tools needed to fully utilize metaproteomics in their microbiome studies.

Metaproteomics to understand how microbiota function: The crystal ball predicts a promising future

In the medical, environmental, and biotechnological fields, microbial communities have attracted much attention due to their roles and numerous possible applications. The study of these communities is challenging due to their diversity and complexity. Innovative methods are needed to identify the taxonomic components of individual microbiota, their changes over time, and to determine how microoorganisms interact and function. Metaproteomics is based on the identification and quantification of proteins, and can potentially provide this full picture. Due to the wide molecular panorama and functional insights it provides, metaproteomics is gaining momentum in microbiome and holobiont research. Its full potential should be unleashed in the coming years with progress in speed and cost of analyses. In this exploratory crystal ball exercise, I discuss the technical and conceptual advances in metaproteomics that I expect to drive innovative research over the next few years in microbiology. I also debate the concepts of 'microbial dark matter' and 'Metaproteomics-Assembled Proteomes (MAPs)' and present some long-term prospects for metaproteomics in clinical diagnostics and personalized medicine, environmental monitoring, agriculture, and biotechnology.

Intracellular Protein S-Nitrosylation—A Cells Response to Extracellular S100B and RAGE Receptor

Human S100B is a small, multifunctional protein. Its activity, inside and outside cells, contributes to the biology of the brain, muscle, skin, and adipocyte tissues. Overexpression of S100B occurs in Down Syndrome, Alzheimer’s disease, Creutzfeldt–Jakob disease, schizophrenia, multiple sclerosis, brain tumors, epilepsy, melanoma, myocardial infarction, muscle disorders, and sarcopenia. Modulating the activities of S100B, related to human diseases, without disturbing its physiological functions, is vital for drug and therapy design. This work focuses on the extracellular activity of S100B and one of its receptors, the Receptor for Advanced Glycation End products (RAGE). The functional outcome of extracellular S100B, partially, depends on the activation of intracellular signaling pathways. Here, we used Biotin Switch Technique enrichment and mass-spectrometry-based proteomics to show that the appearance of the S100B protein in the extracellular milieu of the mammalian Chinese Hamster Ovary (CHO) cells, and expression of the membrane-bound RAGE receptor, lead to changes in the intracellular S-nitrosylation of, at least, more than a hundred proteins. Treatment of the wild-type CHO cells with nanomolar or micromolar concentrations of extracellular S100B modulates the sets of S-nitrosylation targets inside cells. The cellular S-nitrosome is tuned differently, depending on the presence or absence of stable RAGE receptor expression. The presented results are a proof-of-concept study, suggesting that S-nitrosylation, like other post-translational modifications, should be considered in future research, and in developing tailored therapies for S100B and RAGE receptor-related diseases.

Toxicogenomic profiling after sublethal exposure to nerve- and muscle-targeting insecticides reveals cardiac and neuronal developmental effects in zebrafish embryos

For specific primary modes of action (MoA) in environmental non-target organisms, EU legislation restricts the usage of active substances of pesticides or biocides. Corresponding regulatory hazard assessments are costly, time consuming and require large numbers of non-human animal studies. Currently, predictive toxicology of development compounds relies on their chemical structure and provides little insights into toxicity mechanisms that precede adverse effects. Using the zebrafish embryo model, we characterized transcriptomic responses to a range of sublethal concentrations of six nerve- and muscle-targeting insecticides with different MoA (abamectin, carbaryl, chlorpyrifos, fipronil, imidacloprid & methoxychlor). Our aim was to identify affected biological processes and suitable biomarker candidates for MoA-specific signatures. Abamectin showed the most divergent signature among the tested insecticides, linked to lipid metabolic processes. Differentially expressed genes (DEGs) after imidacloprid exposure were primarily associated with immune system and inflammation. In total, 222 early responsive genes to either MoA were identified, many related to three major processes: (1) cardiac muscle cell development and functioning (tcap, desma, bag3, hspb1, hspb8, flnca, myoz3a, mybpc2b, actc2, tnnt2c), (2) oxygen transport and hypoxic stress (alas2, hbbe1.1, hbbe1.3, hbbe2, hbae3, igfbp1a, hif1al) and (3) neuronal development and plasticity (npas4a, egr1, btg2, ier2a, vgf). The thyroidal function related gene dio3b was upregulated by chlorpyrifos and downregulated by higher abamectin concentrations. Important regulatory genes for cardiac muscle (tcap) and forebrain development (npas4a) were the most frequently ifferentially expressed across all insecticide treatments. We consider the identified gene sets as useful early warning biomarker candidates, i.e. for developmental toxicity targeting heart and brain in aquatic vertebrates. Our findings provide a better understanding about early molecular events in response to the analyzed MoA. Perceptively, this promotes the development for sensitive and informative biomarker-based in vitro assays for toxicological MoA prediction and AOP refinement, without the suffering of adult fish.

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

HAZOP Ontology Semantic Similarity Algorithm Based on ACO-GRNN

Hazard and operability (HAZOP) is an important safety analysis method, which is widely used in the safety evaluation of petrochemical industry. The HAZOP analysis report contains a large amount of expert knowledge and experience. In order to realize the effective expression and reuse of knowledge, the knowledge ontology is constructed to store the risk propagation path and realize the standardization of knowledge expression. On this basis, a comprehensive algorithm of ontology semantic similarity based on the ant clony optimization generalized neural network (ACO-GRNN) model is proposed to improve the accuracy of semantic comparison. This method combines the concept name, semantic distance, and improved attribute coincidence calculation method, and ACO-GRNN is used to train the weights of each part, avoiding the influence of manual weighting. The results show that the Pearson coefficient of this method reaches 0.9819, which is 45.83% higher than the traditional method. It could solve the problems of semantic comparison and matching, and lays a good foundation for subsequent knowledge retrieval and reuse.

The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS): an open community for bioinformatics training and research

The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS; eubic-ms.org) was founded in 2014 to unite European computational mass spectrometry researchers and proteomics bioinformaticians working in academia and industry. EuBIC-MS maintains educational resources (proteomics-academy.org) and organises workshops at national and international conferences on proteomics and mass spectrometry. Furthermore, EuBIC-MS is actively involved in several community initiatives such as the Human Proteome Organization's Proteomics Standards Initiative (HUPO-PSI). Apart from these collaborations, EuBIC-MS has organised two Winter Schools and two Developers' Meetings that have contributed to the strengthening of the European mass spectrometry network and fostered international collaboration in this field, even beyond Europe. Moreover, EuBIC-MS is currently actively developing a community-driven standard dedicated to mass spectrometry data annotation (SDRF-Proteomics) that will facilitate data reuse and collaboration. This manuscript highlights what EuBIC-MS is, what it does, and what it already has achieved. A warm invitation is extended to new researchers at all career stages to join the EuBIC-MS community on its Slack channel (eubic.slack.com).