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Toxicology under the umbrella of proteomics and metabolomics

Kasprzyk-Pochopień Joanna, Piekoszewski Wojciech

Bio-Algorithms and Med-Systems

2025

Vol. 21, Special issue: OMICS innovations

1--7

Objective: The integration of omics technologies has opened new opportunities in toxicological research. This article aims to explore how toxico-proteomics and toxico-metabolomics contribute to the understanding of xenobiotic mechanisms, biomarker discovery, and modern risk assessment frameworks. Methods: Relevant literature was analysed to highlight recent advances in proteomics and metabolomics applied to toxicology. Particular attention was given to mass spectrometry-based approaches, spatial omics, in silico modelling, and combined omics strategies. Case examples from drug- and environment-related toxicology were used to illustrate practical applications. Results: High-resolution mass-spectrometry-based proteomics enables the sensitive detection of changes in protein levels, post-translational modifications, and proteinprotein interactions. Toxico-proteomic studies have clarified mechanisms of cardio-, hepato-, and atd-neurotoxic effects. Metabolomics supports the profiling of low molecular weight compounds and early responses to toxicants. Toxico-metabolomic analyses identified changes related to energy metabolism and amino acid metabolism. In vitro models and zebrafish embryos provided organ-specific insights. Integrating omics data has led to the identification of candidate biomarkers of exposure and toxic effects. Conclusions: Toxico-proteomics and toxico-metabolomics represent powerful tools for toxicology. Their application enhances the sensitivity of toxicity detection, reduces reliance on animal models, and supports the development of predictive strategies. As analytical platforms and computational tools continue to evolve, these disciplines are expected to play an increasingly central role in environmental and biomedical toxicology, with implications for diagnostics, therapeutics, and regulatory demands.

Multifaceted Landscape of Omics Data

Mudadla Tejaswi, Sharma Gayatri, Mishra Apoorva, Gola Shefali

Bio-Algorithms and Med-Systems

2024

Vol. 20, no. 1

22--36

Objective: This review aims to provide a comprehensive overview of omics fields - including genomics, epigenomics, transcriptomics, proteomics, metabolomics, single-cell multiomics, microbiomics, and radiomics - and to highlight the significance of integrating these datasets to tackle complex biological questions in systems biology and precision medicine. Methods: The review analyzes current literature across various omics domains, focusing on their individual contributions to cellular functions and their integration challenges. It discusses successful integration examples and addresses issues like data heterogeneity across databases. Results: Omics integration significantly enhances our understanding of biological systems, with each field offering unique insights. Despite challenges with data inconsistencies, successful cases show the potential of integrated omics in advancing personalized medicine, drug discovery, and disease research. Conclusions: Advancing omics integration is essential for breakthroughs in personalized medicine and complex disease studies. Interdisciplinary collaboration will be crucial to overcoming data challenges and realizing the full potential of omics in biomedical advancements.