Over the past decade, several technological advances have impacted plant science research, as revolutionary experimental and quantitative methodologies have been developed such as cross-linking interaction, single-cell isolation, mass spectrometry imaging, ion mobility assays, etc. Methodological innovations in high-throughput mass spectrometry have allowed faster and more confident annotation of molecules which, together with new applications development, has been used to detect a broader range of analytes. Both improved analytical isolation methods and bioinformatics analyses have helped the deeper characterization of post-translational modifications of proteins and the refinement of molecular structures and their interactions. Quantitative mass spectrometry-based proteomics is now being used to investigate new aspects of biological processes, from cells to organelles. New AI-based and machine-learning algorithms have deeply impacted the quantification of mass spectrometry data and proteomics meta-analyses. At the same time, integration with other omics data types is expanding the impact of mass spectrometry research.The greater accessibility of distributed scientific infrastructures worldwide and the increased availability of cutting-edge instruments and powerful IT clusters have prompted an expansion of proteomics applications in plant research. Mass spectrometry-based methodologies coupled with automation, computer-based tools, and deep learning AI algorithms has enabled new promising perspectives of biotechnological applications in plant science. Plant system biology can probe new potential interactions between biomolecules (proteins, metabolites, nucleic acids, etc.) to enhance comprehension of plant cellular and physiological processes and to establish bases for synthetic biology development.This Research Topic offers a forum to highlight recent high-throughput mass-spectrometry advances and the latest computational biology methods to investigate plant biomolecular aspects at multiple scales. The target applications range from fundamental plant science to plant pathology, plant improvement (breeding, genetic engineering), and adaptation to climate change.We welcome all types of contributions on “omics” themes, including, but not limited to, the following:- Advances in mass spectrometry analytical configuration (i.e. cross-linking interaction, single-cell isolation, mass spectrometry imaging, ion mobility coupling, etc.) coupled with computer-based applications to investigate biological complexity.- Application and development of single-cell proteomics and metabolomics to elucidate plant biochemistry.- Development of mass spectrometry-based methods and computational approaches to investigate plant molecular interactions at multiple scales.- Multi-omics integration of mass spectrometry-based methods and new computational methods for systems biology analyses.- Mass spectrometry applications using deep learning algorithms and AI tools to enhance plant science knowledge.- New and improved computer-based tools that open novel perspectives for mass spectrometry analyses.
Over the past decade, several technological advances have impacted plant science research, as revolutionary experimental and quantitative methodologies have been developed such as cross-linking interaction, single-cell isolation, mass spectrometry imaging, ion mobility assays, etc. Methodological innovations in high-throughput mass spectrometry have allowed faster and more confident annotation of molecules which, together with new applications development, has been used to detect a broader range of analytes. Both improved analytical isolation methods and bioinformatics analyses have helped the deeper characterization of post-translational modifications of proteins and the refinement of molecular structures and their interactions. Quantitative mass spectrometry-based proteomics is now being used to investigate new aspects of biological processes, from cells to organelles. New AI-based and machine-learning algorithms have deeply impacted the quantification of mass spectrometry data and proteomics meta-analyses. At the same time, integration with other omics data types is expanding the impact of mass spectrometry research.The greater accessibility of distributed scientific infrastructures worldwide and the increased availability of cutting-edge instruments and powerful IT clusters have prompted an expansion of proteomics applications in plant research. Mass spectrometry-based methodologies coupled with automation, computer-based tools, and deep learning AI algorithms has enabled new promising perspectives of biotechnological applications in plant science. Plant system biology can probe new potential interactions between biomolecules (proteins, metabolites, nucleic acids, etc.) to enhance comprehension of plant cellular and physiological processes and to establish bases for synthetic biology development.This Research Topic offers a forum to highlight recent high-throughput mass-spectrometry advances and the latest computational biology methods to investigate plant biomolecular aspects at multiple scales. The target applications range from fundamental plant science to plant pathology, plant improvement (breeding, genetic engineering), and adaptation to climate change.We welcome all types of contributions on “omics” themes, including, but not limited to, the following:- Advances in mass spectrometry analytical configuration (i.e. cross-linking interaction, single-cell isolation, mass spectrometry imaging, ion mobility coupling, etc.) coupled with computer-based applications to investigate biological complexity.- Application and development of single-cell proteomics and metabolomics to elucidate plant biochemistry.- Development of mass spectrometry-based methods and computational approaches to investigate plant molecular interactions at multiple scales.- Multi-omics integration of mass spectrometry-based methods and new computational methods for systems biology analyses.- Mass spectrometry applications using deep learning algorithms and AI tools to enhance plant science knowledge.- New and improved computer-based tools that open novel perspectives for mass spectrometry analyses.