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The role of mass spectrometry in plant systems biology.

Large-scale analyses of proteins and metabolites are intimately bound to advancements in MS technologies. The aim of these non-targeted "omic" technologies is to extend our understanding beyond the analysis of only parts of the system. Here, metabolomics and proteomics emerged in parallel with the development of novel mass analyzers and hyphenated techniques such as gas chromatography coupled to time-of-flight mass spectrometry (GC-TOF-MS) and multidimensional liquid chromatography coupled to mass spectrometry (LC-MS). The analysis of (i) proteins (ii) phosphoproteins, and (iii) metabolites is discussed in the context of plant physiology and environment and with a focus on novel method developments. Recently published studies measuring dynamic (quantitative) behavior at these levels are summarized; for these works, the completely sequenced plants Arabidopsis thaliana and Oryza sativa (rice) have been the primary models of choice. Particular emphasis is given to key physiological processes such as metabolism, development, stress, and defense. Moreover, attempts to combine spatial, tissue-specific resolution with systematic profiling are described. Finally, we summarize the initial steps to characterize the molecular plant phenotype as a corollary of environment and genotype.

Mass Spectrometry↗

Atmospheric pressure molecular imaging by infrared MALDI mass spectrometry.

An atmospheric pressure (AP) MALDI imaging interface was developed for an orthogonal acceleration time-of-flight mass spectrometer and utilized to analyze peptides, carbohydrates, and other small biomolecules using infrared laser excitation. In molecular imaging experiments, the spatial distribution of mock peptide patterns was recovered with a detection limit of approximately 1 fmol/pixel from a variety of MALDI matrixes. With the use of oversampling for the image acquisition, a spatial resolution of 40 microm, 5 times smaller than the laser spot size, was achieved. This approach, however, required that the analyte was largely removed at the point of analysis before the next point was interrogated. Native water in plant tissue was demonstrated to be an efficient natural matrix for AP infrared laser desorption ionization. In soft fruit tissues from bananas, grapes, and strawberries, potassiated ions of the most abundant metabolites, small carbohydrates, and their clusters produced the strongest peaks in the spectra. Molecular imaging of a strawberry skin sample revealed the distribution of the sucrose, glucose/fructose, and citric acid species around the embedded seeds. Infrared AP MALDI mass spectrometric imaging without the addition of an artificial matrix enables the in vivo investigation of small biomolecules and biological processes (e.g., metabolomics) in their natural environment.

Journal Article↗

Pan-genomics and multi-omics for deciphering genetic variation and accelerating genetic improvement in ruminant livestock.

Livestock reference genomes have transformed the discovery of variants associated with production, reproduction, health, and environmental adaptation. Nevertheless, a single linear reference represents only one mosaic haplotype and incompletely captures sequence diversity within a species, particularly structural variants, copy-number changes, repeat-rich regions, and breed-specific sequences. Pangenomes address this limitation by integrating multiple high-quality assemblies or population-scale variants into a unified sequence or graph representation. Concurrently, multi-omics approaches connect genomic variation with transcriptomic, epigenomic, manuscriptproteomic, metabolomic, and microbiome responses, thereby improving biological interpretation of genotype-phenotype relationships. This review synthesizes recent progress in livestock pangenomics and multi-omics, with emphasis on cattle, goats, sheep, water buffalo, and chickens. It describes advances in long-read and haplotype-resolved sequencing, graph construction, structural-variant discovery and genotyping, functional annotation, and integrative analysis. Recent pangenome studies have uncovered substantial non-reference sequence, reduced reference bias, identified breed- and population-specific structural variants, and resolved candidate variants underlying pigmentation, body size, tail morphology, cashmere production, altitude adaptation, and other economically relevant traits. However, translation into routine breeding remains constrained by uneven population representation, inconsistent structural-variant definitions, limited functional annotation, computational demands, and insufficient validation across environments. Future progress will depend on diverse near-complete assemblies, graph-aware imputation and genomic prediction, long-read transcriptomics, single-cell and spatial omics, rigorous causal validation, and open, interoperable resources. Together, these developments can support more accurate, resilient, and biologically informed livestock improvement. Importantly, current dairy-cattle evidence indicates that pangenome-derived structural variants can substantially improve variant discovery and functional interpretation while yielding only marginal average gains in routine genomic prediction, favoring targeted augmentation rather than wholesale replacement of established SNP-based evaluations.

Animals↗

MRS as endogenous molecular imaging for brain and prostate tumors: FP6 project "eTUMOR".

Molecular imaging has become during the last years in an important tool for supporting cancer diagnosis and prognosis. PET and SPECT are the most common molecular imaging techniques, although very promising and specific biological molecular agent contrast for CT and MRI are being recently developed. However, the above imaging techniques require exogenous contrast agents and usually a sole molecular image can be obtained at once. On the contrary, in vivo magnetic resonance spectroscopy (MRS), in particular 1H MRS can simultaneously provide several molecular images using endogenous metabolites. In addition to biochemical spatial information from molecular imaging spectroscopy, MRS can also provide average metabolite profile of the selected affected tissue region. Initially MRS, especially 1H MRS, was extensively applied to complete and improve the diagnosis and prognosis of central nervous system (CNS) pathologies, in particular brain tumors. However, during the last years the MRS applications have been extent to the diagnosis of different very common cancer types such as breast, prostate, colon carcinoma, and ovarian, among others. Likewise, MRS has been also used for lymph node assessment. In this contribution, the added value of MRS for the diagnosis, prognosis, and treatment selection of two different, important types of cancer: (1) brain tumors and (2) prostate, will be presented and discussed. Brain tumors are the leading cause of death in children under 15, and although in adults, brain cancers are proportionately less common than other cancers, it is a devastating disease with high mortality. There is a great need to increase our understanding of brain tumor biology to improve diagnosis and to develop new treatments. 1H MRS is currently the only noninvasive method that can be used to investigate molecular profile of brain tumors and also provide molecular images, more than six in one acquisition, of the distribution of chemicals in a tumor, which are also generally heterogeneous. A summary of the applications of 1H MRS to the in vivo diagnosis and prognosis of brain tumors will be presented. In addition, examples of metabolite limits, infiltration and high cellularity location for neurosurgery applications by MRS molecular images will be shown. Likewise, new ex vivo methods of studying the detailed biochemistry of tumor biopsies as metabolomic (high resolution magic angle spinning [HR-MAS]) and transcriptomic (DNA microarrays) will be discussed as complementary to in vivo MRS (FP6 European project eTUMOR). A preliminary comparison between molecular images from PET and 1H MRS will be also presented. Finally, the application of 1H MRS to the improvement of prostate diagnosis and prognosis, the second leading cause of cancer death, will also discussed, with particular attention to the location cancer contribution from MRS molecular images.

Brain Neoplasms↗