Spatially Enriched Paralog Rearrangements Argue Functionally Diverse Ribosomes Arise during Cold Acclimation in Arabidopsis

Streamlining Protein Fractional Synthesis Rates Using SP3 Beads and Stable Isotope Mass Spectrometry: A Case Study on the Plant Ribosome

Ribosomes are an archetypal ribonucleoprotein assembly. Due to ribosomal evolution and function, r-proteins share specific physicochemical similarities, making the riboproteome particularly suited for tailored proteome profiling methods. Moreover, the structural proteome of ribonucleoprotein assemblies reflects context-dependent functional features. Thus, characterizing the state of riboproteomes provides insights to uncover the context-dependent functionality of r-protein rearrangements, as they relate to what has been termed the ribosomal code, a concept that parallels that of the histone code, in which chromatin rearrangements influence gene expression. Compared to high-resolution ribosomal structures, omics methods lag when it comes to offering customized solutions to close the knowledge gap between structure and function that currently exists in riboproteomes. Purifying the riboproteome and subsequent shot-gun proteomics typically involves protein denaturation and digestion with proteases. The results are relative abundances of r-proteins at the ribosome population level. We have previously shown that, to gain insight into the stoichiometry of individual proteins, it is necessary to measure by proteomics bound r-proteins and normalize their intensities by the sum of r-protein abundances per ribosomal complex, i.e., 40S or 60S subunits. These calculations ensure that individual r-protein stoichiometries represent the fraction of each family/paralog relative to the complex, effectively revealing which r-proteins become substoichiometric in specific physiological scenarios. Here, we present an optimized method to profile the riboproteome of any organism as well as the synthesis rates of r-proteins determined by stable isotope-assisted mass spectrometry. Our method purifies the r-proteins in a reversibly denatured state, which offers the possibility for combined top-down and bottom-up proteomics. Our method offers a milder native denaturation of the r-proteome via a chaotropic GuHCl solution as compared with previous studies that use irreversible denaturation under highly acidic conditions to dissociate rRNA and r-proteins. As such, our method is better suited to conserve post-translational modifications (PTMs). Subsequently, our method carefully considers the amino acid composition of r-proteins to select an appropriate protease for digestion. We avoid non-specific protease cleavage by increasing the pH of our standardized r-proteome dilutions that enter the digestion pipeline and by using a digestion buffer that ensures an optimal pH for a reliable protease digestion process. Finally, we provide the R package ProtSynthesis to study the fractional synthesis rates of r-proteins. The package uses physiological parameters as input to determine peptide or protein fractional synthesis rates. Once the physiological parameters are measured, our equations allow a fair comparison between treatments that alter the biological equilibrium state of the system under study. Our equations correct peptide enrichment using enrichments in soluble amino acids, growth rates, and total protein accumulation. As a means of validation, our pipeline fails to find "false" enrichments in non-labeled samples while also filtering out proteins with multiple unique peptides that have different enrichment values, which are rare in our datasets. These two aspects reflect the accuracy of our tool. Our method offers the possibility of elucidating individual r-protein family/paralog abundances, PTM status, fractional synthesis rates, and dynamic assembly into ribosomal complexes if top-down and bottom-up proteomic approaches are used concomitantly, taking one step further into mapping the native and dynamic status of the r-proteome onto high-resolution ribosome structures. In addition, our method can be used to study the proteomes of all macromolecular assemblies that can be purified, although purification is the limiting step, and the efficacy and accuracy of the proteases may be limited depending on the digestion requirements. Key features • Efficient purification of the ribosomal proteome: streamlined procedure for the specific purification of the ribosomal proteome or complex Ome. • Accurate calculation of fractional synthesis rates: robust method for calculating fractional protein synthesis rates in macromolecular complexes under different physiological steady states. • Holistic ribosome methodology focused on plants: comprehensive approach that provides insights into the ribosomes and translational control of plants, demonstrated using cold acclimation [1]. • Tailored strategies for stable isotope labeling in plants: methodology focusing on materials and labeling considerations specific to free and proteinogenic amino acid analysis [2].

Dynamics of ribosome composition and ribosomal protein phosphorylation in immune signaling in Arabidopsis thaliana

In plants, the detection of microbe-associated molecular patterns (MAMPs) induces primary innate immunity by the activation of mitogen-activated protein kinases (MAPKs). We show here that the MAMP-activated MAPK MPK6 not only modulates defense through transcriptional regulation but also via the ribosomal protein translation machinery. To understand the effects of MPK6 on ribosomes and their constituent ribosomal proteins (RPs), polysomes, monosomes and the phosphorylation status of the RPs, MAMP-treated WT and mpk6 mutant plants were analysed. MAMP-activation induced rapid changes in RP composition of monosomes, polysomes and in the 60S ribosomal subunit in an MPK6-specific manner. Phosphoproteome analysis showed that MAMP-activation of MPK6 regulates the phosphorylation status of the P-stalk ribosomal proteins by phosphorylation of RPP0 and the concomitant dephosphorylation of RPP1 and RPP2. These events coincide with a significant decrease in the abundance of ribosome-bound RPP0s, RPP1s and RPP3s in polysomes. The P-stalk is essential in regulating protein translation by recruiting elongation factors. Accordingly, we found that RPP0C mutant plants are compromised in basal resistance to Pseudomonas syringae infection. These data suggest that MAMP-induced defense also involves MPK6-induced regulation of P-stalk proteins, highlighting a new role of ribosomal regulation in plant innate immunity.

A Molecular Orchestration of Plant Translation under Abiotic Stress

The complexities of translational strategies make this stage of implementing genetic information one of the most challenging to comprehend and, simultaneously, perhaps the most engaging. It is evident that this diverse range of strategies results not only from a long evolutionary history, but is also of paramount importance for refining gene expression and metabolic modulation. This notion is particularly accurate for organisms that predominantly exhibit biochemical and physiological reactions with a lack of behavioural ones. Plants are a group of organisms that exhibit such features. Addressing unfavourable environmental conditions plays a pivotal role in plant physiology. This is particularly evident with the changing conditions of global warming and the irrevocable loss or depletion of natural ecosystems. In conceptual terms, the plant response to abiotic stress comprises a set of elaborate and intricate strategies. This is influenced by a range of abiotic factors that cause stressful conditions, and molecular genetic mechanisms that fine-tune metabolic pathways allowing the plant organism to overcome non-standard and non-optimal conditions. This review aims to focus on the current state of the art in the field of translational regulation in plants under abiotic stress conditions. Different regulatory elements and patterns are being assessed chronologically. We deem it important to focus on significant high-performance techniques for studying the genetic information dynamics during the translation phase.

Transcriptome Analysis and QTL Mapping Identify Candidate Genes and Regulatory Mechanisms Related to Low-Temperature Germination Ability in Maize

Low-temperature germination ability (LTGA) is an important characteristic for spring sowing maize. However, few maize genes related to LTGA were confirmed, and the regulatory mechanism is less clear. Here, maize-inbred lines Ye478 and Q1 with different LTGA were used to perform transcriptome analysis at multiple low-temperature germination stages, and a co-expression network was constructed by weighted gene co-expression network analysis (WGCNA). Data analysis showed that 7964 up- and 5010 down-regulated differentially expressed genes (DEGs) of Ye478 were identified at low-temperature germination stages, while 6060 up- and 2653 down-regulated DEGs of Q1 were identified. Gene ontology (GO) enrichment analysis revealed that ribosome synthesis and hydrogen peroxide metabolism were enhanced and mRNA metabolism was weakened under low-temperature stress for Ye478, while hydrogen peroxide metabolism was enhanced and mRNA metabolism was weakened for Q1. DEGs pairwise comparisons between the two genotypes found that Ye478 performed more ribosome synthesis at low temperatures compared with Q1. WGCNA analysis based on 24 transcriptomes identified 16 co-expressed modules. Of these, the MEbrown module was highly correlated with Ye478 at low-temperature stages and catalase and superoxide dismutase activity, and the MEred, MEgreen, and MEblack modules were highly correlated with Ye478 across low-temperature stages, which revealed a significant association between LTGA and these modules. GO enrichment analysis showed the MEbrown and MEred modules mainly functioned in ribosome synthesis and cell cycle, respectively. In addition, we conducted quantitative trait loci (QTL) analysis based on a doubled haploid (DH) population constructed by Ye478 and Q1 and identified a major QTL explanting 20.6% of phenotype variance on chromosome 1. In this QTL interval, we found three, four, and three hub genes in the MEbrown, MEred, and MEgreen modules, of which two hub genes (Zm00001d031951, Zm00001d031953) related to glutathione metabolism and one hub gene (Zm00001d031617) related to oxidoreductase activity could be the candidate genes for LTGA. These biological functions and candidate genes will be helpful in understanding the regulatory mechanism of LTGA and the directional improvement of maize varieties for LTGA.

Protein interactome of 3',5'-cAMP reveals its role in regulating the actin cytoskeleton

Identification of protein interactors is ideally suited for the functional characterization of small molecules. 3',5'-cAMP is an evolutionary ancient signaling metabolite largely uncharacterized in plants. To tap into the physiological roles of 3',5'-cAMP, we used a chemo-proteomics approach, thermal proteome profiling (TPP), for the unbiased identification of 3',5'-cAMP protein targets. TPP measures shifts in the protein thermal stability upon ligand binding. Comprehensive proteomics analysis yielded a list of 51 proteins significantly altered in their thermal stability upon incubation with 3',5'-cAMP. The list contained metabolic enzymes, ribosomal subunits, translation initiation factors, and proteins associated with the regulation of plant growth such as CELL DIVISION CYCLE 48. To functionally validate obtained results, we focused on the role of 3',5'-cAMP in regulating the actin cytoskeleton suggested by the presence of actin among the 51 identified proteins. 3',5'-cAMP supplementation affected actin organization by inducing actin-bundling. Consistent with these results, the increase in 3',5'-cAMP levels, obtained either by feeding or by chemical modulation of 3',5'-cAMP metabolism, was sufficient to partially rescue the short hypocotyl phenotype of the actin2 actin7 mutant, severely compromised in actin level. The observed rescue was specific to 3',5'-cAMP, as demonstrated using a positional isomer 2',3'-cAMP, and true for the nanomolar 3',5'-cAMP concentrations reported for plant cells. In vitro characterization of the 3',5'-cAMP-actin pairing argues against a direct interaction between actin and 3',5'-cAMP. Alternative mechanisms by which 3',5'-cAMP would affect actin dynamics, such as by interfering with calcium signaling, are discussed. In summary, our work provides a specific resource, 3',5'-cAMP interactome, as well as functional insight into 3',5'-cAMP-mediated regulation in plants.

Intra-Varietal Diversity and Its Contribution to Wheat Evolution, Domestication, and Improvement in Wheat

Crop genetic diversity is essential for adaptation and productivity in agriculture. A previous study revealed that poor allele diversity in wheat commercial cultivars is a major barrier to its further improvement. Homologs within a variety, including paralogs and orthologs in polyploid, account for a large part of the total genes of a species. Homolog diversity, intra-varietal diversity (IVD), and their functions have not been elucidated. Common wheat, an important food crop, is a hexaploid species with three subgenomes. This study analyzed the sequence, expression, and functional diversity of homologous genes in common wheat based on high-quality reference genomes of two representative varieties, a modern commercial variety Aikang 58 (AK58) and a landrace Chinese Spring (CS). A total of 85,908 homologous genes, accounting for 71.9% of all wheat genes, including inparalogs (IPs), outparalogs (OPs), and single-copy orthologs (SORs), were identified, suggesting that homologs are an important part of the wheat genome. The levels of sequence, expression, and functional variation in OPs and SORs were higher than that of IPs, which indicates that polyploids have more homologous diversity than diploids. Expansion genes, a specific type of OPs, made a great contribution to crop evolution and adaptation and endowed crop with special characteristics. Almost all agronomically important genes were from OPs and SORs, demonstrating their essential functions for polyploid evolution, domestication, and improvement. Our results suggest that IVD analysis is a novel approach for evaluating intra-genomic variations, and exploitation of IVD might be a new road for plant breeding, especially for polyploid crops, such as wheat.

Engineering Ribosomes to Alleviate Abiotic Stress in Plants: A Perspective

As the centerpiece of the biomass production process, ribosome activity is highly coordinated with environmental cues. Findings revealing ribosome subgroups responsive to adverse conditions suggest this tight coordination may be grounded in the induction of variant ribosome compositions and the differential translation outcomes they might produce. In this perspective, we go through the literature linking ribosome heterogeneity to plants’ abiotic stress response. Once unraveled, this crosstalk may serve as the foundation of novel strategies to custom cultivars tolerant to challenging environments without the yield penalty.

[Formula: see text]: ComplexOme-Structural Network Interpreter used to study spatial enrichment in metazoan ribosomes

BACKGROUND

Upon environmental stimuli, ribosomes are surmised to undergo compositional rearrangements due to abundance changes among proteins assembled into the complex, leading to modulated structural and functional characteristics. Here, we present the ComplexOme-Structural Network Interpreter ([Formula: see text]), a computational method to allow testing whether ribosomal proteins (rProteins) that exhibit abundance changes under specific conditions are spatially confined to particular regions within the large ribosomal complex.

RESULTS

[Formula: see text] translates experimentally determined structures into graphs, with nodes representing proteins and edges the spatial proximity between them. In its first implementation, [Formula: see text] considers rProteins and ignores rRNA and other objects. Spatial regions are defined using a random walk with restart methodology, followed by a procedure to obtain a minimum set of regions that cover all proteins in the complex. Structural coherence is achieved by applying weights to the edges reflecting the physical proximity between purportedly contacting proteins. The weighting probabilistically guides the random-walk path trajectory. Parameter tuning during region selection provides the option to tailor the method to specific biological questions by yielding regions of different sizes with minimum overlaps. In addition, other graph community detection algorithms may be used for the [Formula: see text] workflow, considering that they yield different sized, non-overlapping regions. All tested algorithms result in the same node kernels under equivalent regions. Based on the defined regions, available abundance change information of proteins is mapped onto the graph and subsequently tested for enrichment in any of the defined spatial regions. We applied [Formula: see text] to the cytosolic ribosome structures of Saccharomyces cerevisiae, Oryctolagus cuniculus, and Triticum aestivum using datasets with available quantitative protein abundance change information. We found that in yeast, substoichiometric rProteins depleted from translating polysomes are significantly constrained to a ribosomal region close to the tRNA entry and exit sites.

CONCLUSIONS

[Formula: see text] offers a computational method to partition multi-protein complexes into structural regions and a statistical approach to test for spatial enrichments of any given subsets of proteins. [Formula: see text] is applicable to any multi-protein complex given appropriate structural and abundance-change data. [Formula: see text] is publicly available as a GitHub repository https://github.com/MSeidelFed/COSNet_i and can be installed using the python installer pip.