Dataset Information

Proteome and Interactome Linked to Metabolism, Genetic Information Processing, and Abiotic Stress in Gametophytes of Two Woodferns.

ABSTRACT: Ferns and lycophytes have received scant molecular attention in comparison to angiosperms. The advent of high-throughput technologies allowed an advance towards a greater knowledge of their elusive genomes. In this work, proteomic analyses of heart-shaped gametophytes of two ferns were performed: the apomictic Dryopteris affinis ssp. affinis and its sexual relative Dryopteris oreades. In total, a set of 218 proteins shared by these two gametophytes were analyzed using the STRING database, and their proteome associated with metabolism, genetic information processing, and responses to abiotic stress is discussed. Specifically, we report proteins involved in the metabolism of carbohydrates, lipids, and nucleotides, the biosynthesis of amino acids and secondary compounds, energy, oxide-reduction, transcription, translation, protein folding, sorting and degradation, and responses to abiotic stresses. The interactome of this set of proteins represents a total network composed of 218 nodes and 1792 interactions, obtained mostly from databases and text mining. The interactions among the identified proteins of the ferns D. affinis and D. oreades, together with the description of their biological functions, might contribute to a better understanding of the function and development of ferns as well as fill knowledge gaps in plant evolution.

SUBMITTER: Ojosnegros S

PROVIDER: S-EPMC10419320 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Proteome and Interactome Linked to Metabolism, Genetic Information Processing, and Abiotic Stress in Gametophytes of Two Woodferns.

Ojosnegros Sara S Alvarez José Manuel JM Grossmann Jonas J Gagliardini Valeria V Quintanilla Luis G LG Grossniklaus Ueli U Fernández Helena H

International journal of molecular sciences 20230804 15

Ferns and lycophytes have received scant molecular attention in comparison to angiosperms. The advent of high-throughput technologies allowed an advance towards a greater knowledge of their elusive genomes. In this work, proteomic analyses of heart-shaped gametophytes of two ferns were performed: the apomictic Dryopteris affinis ssp. affinis and its sexual relative Dryopteris oreades. In total, a set of 218 proteins shared by these two gametophytes were analyzed using the ST ...[more]

PMID: 37569809

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Project description:HIGHLIGHTS: Major environmental and genetic factors determining stress-related protein abundance are discussed.Major aspects of protein biological function including protein isoforms and PTMs, cellular localization and protein interactions are discussed.Functional diversity of protein isoforms and PTMs is discussed. Abiotic stresses reveal profound impacts on plant proteomes including alterations in protein relative abundance, cellular localization, post-transcriptional and post-translational modifications (PTMs), protein interactions with other protein partners, and, finally, protein biological functions. The main aim of the present review is to discuss the major factors determining stress-related protein accumulation and their final biological functions. A dynamics of stress response including stress acclimation to altered ambient conditions and recovery after the stress treatment is discussed. The results of proteomic studies aimed at a comparison of stress response in plant genotypes differing in stress adaptability reveal constitutively enhanced levels of several stress-related proteins (protective proteins, chaperones, ROS scavenging- and detoxification-related enzymes) in the tolerant genotypes with respect to the susceptible ones. Tolerant genotypes can efficiently adjust energy metabolism to enhanced needs during stress acclimation. Stress tolerance vs. stress susceptibility are relative terms which can reflect different stress-coping strategies depending on the given stress treatment. The role of differential protein isoforms and PTMs with respect to their biological functions in different physiological constraints (cellular compartments and interacting partners) is discussed. The importance of protein functional studies following high-throughput proteome analyses is presented in a broader context of plant biology. In summary, the manuscript tries to provide an overview of the major factors which have to be considered when interpreting data from proteomic studies on stress-treated plants.

Project description:Recent studies of cellular networks have revealed modular organizations of genes and proteins. For example, in interactome networks, a module refers to a group of interacting proteins that form molecular complexes and/or biochemical pathways and together mediate a biological process. However, it is still poorly understood how biological information is transmitted between different modules. We have developed information flow analysis, a new computational approach that identifies proteins central to the transmission of biological information throughout the network. In the information flow analysis, we represent an interactome network as an electrical circuit, where interactions are modeled as resistors and proteins as interconnecting junctions. Construing the propagation of biological signals as flow of electrical current, our method calculates an information flow score for every protein. Unlike previous metrics of network centrality such as degree or betweenness that only consider topological features, our approach incorporates confidence scores of protein-protein interactions and automatically considers all possible paths in a network when evaluating the importance of each protein. We apply our method to the interactome networks of Saccharomyces cerevisiae and Caenorhabditis elegans. We find that the likelihood of observing lethality and pleiotropy when a protein is eliminated is positively correlated with the protein's information flow score. Even among proteins of low degree or low betweenness, high information scores serve as a strong predictor of loss-of-function lethality or pleiotropy. The correlation between information flow scores and phenotypes supports our hypothesis that the proteins of high information flow reside in central positions in interactome networks. We also show that the ranks of information flow scores are more consistent than that of betweenness when a large amount of noisy data is added to an interactome. Finally, we combine gene expression data with interaction data in C. elegans and construct an interactome network for muscle-specific genes. We find that genes that rank high in terms of information flow in the muscle interactome network but not in the entire network tend to play important roles in muscle function. This framework for studying tissue-specific networks by the information flow model can be applied to other tissues and other organisms as well.

Dataset Information

Proteome and Interactome Linked to Metabolism, Genetic Information Processing, and Abiotic Stress in Gametophytes of Two Woodferns.

Publications

Proteome and Interactome Linked to Metabolism, Genetic Information Processing, and Abiotic Stress in Gametophytes of Two Woodferns.

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