Next Article in Journal
Effects of Kiwifruit Rootstocks with Opposite Tolerance on Physiological Responses of Grafting Combinations under Waterlogging Stress
Next Article in Special Issue
45S rDNA Diversity In Natura as One Step towards Ribosomal Heterogeneity in Arabidopsis thaliana
Previous Article in Journal
Correction: Villalobos-González et al. Photoprotection Is Achieved by Photorespiration and Modification of the Leaf Incident Light, and Their Extent Is Modulated by the Stomatal Sensitivity to Water Deficit in Grapevines. Plants 2022, 11, 1050
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Perspective

Engineering Ribosomes to Alleviate Abiotic Stress in Plants: A Perspective

by
Leticia Dias-Fields
and
Katarzyna P. Adamala
*
Department of Genetics, Cell Biology, and Development, University of Minnesota, 6-160 Jackson Hall, 321 Church Street SE, Minneapolis, MN 55455, USA
*
Author to whom correspondence should be addressed.
Plants 2022, 11(16), 2097; https://doi.org/10.3390/plants11162097
Submission received: 26 July 2022 / Revised: 10 August 2022 / Accepted: 10 August 2022 / Published: 12 August 2022
(This article belongs to the Special Issue Ribosome Heterogeneity in Plants)

Abstract

:
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.

1. Introduction

Environmental stressors have a major negative impact on plants’ life cycle [1]. They prevent the crops from delivering 70% of their production potential. This means that the actual crop yield average corresponds to only 30% of what would be in the absence of environmental stress [2,3,4,5]. Considering not only the impossibility of having an environment free of abiotic disturbances but also the current aggravation due the global warming, the urgency for new tolerant cultivars becomes unquestionable. To reach this goal in a fast and efficient manner, approaches such as synthetic biology technologies should be made use of.
Synthetic biology proposes to go beyond genetic engineering by manipulating not only genes but whole metabolic systems and their regulatory pathways [6]. The ribosome has been a primer target of synthetic biology efforts [7], mainly due to its capability to synthesize protein at an extraordinary rate and accuracy [8]. So far, the efforts were mainly directed to use its workforce to add nonstandard amino acids to a protein or even translate another kind of polymers [9,10,11,12,13]. However, rising evidence of ribosome subpopulations responding to environment stress in plants have opened new harnessing possibilities [14,15,16,17,18].
The ribosome is the workhorse of translation machinery [19]. While it was initially understood as an invariant and passive organelle, comprehension about its role has gotten new colors in the last decades [20,21,22]. The differential expression of individual ribosome components that was detected in many organisms, including plants, led to the acknowledgment of ribosome heterogeneity [21,23,24,25,26,27,28,29]. Additionally, details stating that its activity is strongly linked with external signals have also been uncovered [30,31,32,33,34,35,36]. Now, efforts have been put into understanding better how the ribosome variety serves to fulfill the cell demands in a dynamic environment [37].
As immobile beings, plants rely only on internal processes to deal with environmental pressures [38,39]. Itdemands an efficient response system built on a finely tuned gene expression. Among all the levels of gene expression regulation, the translational one stood out as an important via to attenuate the cell apoptosis process triggered by abiotic stress [40]. Free of the energy and time costs charged by the de novo mRNA synthesis, the translational regulation can be faster and more dynamic [41,42]. In addition, the absence of alterations in mRNA levels allows a prompt recovery when the stress factors are removed or reduced [43,44].
Cells’ primary demand in plants going through adversities is to safeguard energy [45]. They do that by suppressing energetically consumptive processes such as protein synthesis [41]. This way, the energy before invested in growth is redirected to physiological adaptations that help the plant thrive through harsh conditions [46]. Although quite efficient to guarantee survival, the resulting stress tolerance is achieved at productivity expenses [47].
In the world’s actual scenario, it presents a huge challenge to farmers and scientists. The rapid expansion of population requires an increasing agricultural output, but global climate deterioration does not favor it. Therefore, the food security of the next generations depends on the creation of cultivars that conjugate two conflicting traits under adverse conditions, tolerance, and high yield, which is an ambitious task that requires creative strategies to be accomplished.
The tight coupling with external stimuli and its pivotal regulatory role in cellular proliferation place the ribosome as a converter between environment status and mass accumulation. Once understood and decoded, this capability can be engineered to construct ribosome variants that may set an atypical growth pace in response to abiotic stress signaling. This establishes thus the basis for the creation of stress-tolerant cultivars which are also productive under hostile environments (Figure 1).
Although quite promising, harnessing ribosomes to promote plant tolerance demands a deeper knowledge of plant ribosomes heterogeneity and its association with abiotic stress response. In this perspective, we review our current understanding about it. The goal here is to outline what is already known and discuss what is still to be caught in order to make this approach feasible.

2. Ribosome Heterogeneity: A Platform for Custom Stress-Responsive Ribosomes

The noncanonical compositions of translation machinery classify as ribosome heterogeneity [48]. It includes any level of variations in ribosomal ribonucleic acid (rRNA) or ribosomal proteins (RP) [24,49,50]. Identifying what alterations make a ribosome responsive to stress and how they drive the translatome to meet the plant physiological demands in a disturbed environment is the foundation that the prospect of customizing ribosomes to increase plant resilience is built on (Figure 1).
The way ribosome heterogeneity works for gene regulation is still a controversial matter. Two contrasting explanations were proposed: the “insufficiency” and the “specialization” hypotheses [48]. The “insufficiency hypothesis” defends that structural changes produce inoperative ribosomes [49]. A deficit of functional ribosomes is thus established, and the translation preference becomes determined for the majority by the mRNA sensitivity to ribosome concentration. As reviewed by Ferretti and Karbstein (2019) [51], the extent to which the expression of a gene is affected by the ribosome availability is defined by its 5′ untranslated region (UTR) content and size.
UTR elements as Kozak sequences and upstream open reading frame (uORF) play a great part in the translation efficiency [52]. The Kozak motif is the consensus distribution of nucleotides surrounding the translation initiation site (TIS) [53]. The more conserved it is, the stronger the signal of TIS recognition is transmitted and the more intense the ribosome recruitment is [54]. That is why genes carrying an optimal Kozak motif in their UTR are most likely to be successfully translated even under ribosome low availability [55]. In plants, Gupta et al. (2016) [56] identified GCNAUGGC, AANAUGGC, and GCNAUGGC as Kozak consensus sequences for monocots, dicots, and plants in general, respectively.
The uORFs are found in 24–30% of the total plant mRNAs [57]. Their presence tends to attenuate the rate of protein synthesis, which attaches to them a regulatory attribute already reported to be involved in the plant response to abiotic stress [58,59,60,61,62,63,64]. They typically cause the stalling, or simply the dissociation, of ribosomes. In these cases, in order to have the main ORFs (mORFs) expressed, the translation needs to be reinitiated [62,65]. It requires an abundance of functional ribosomes and a UTR big enough to allow them to bound, reacquire the translation initiation factors, and then resume the scanning for the main start codon [66]. Accordingly, genes with long 5′ UTR as well as the ones carrying uORF or weak Kozak sequences are more dependent on the ribosome concentration to be translated [51,67]. In Srivastava et al. (2018) [57], the function specificity and UTR length data of plant genes were analyzed, crossed, and organized in categories. The results showed that in Arabidopsis and rice, the genes involved in stress response bear short (1–500 bp) and medium (1001–2000 bp) UTR, respectively, suggesting that their translation products are much more likely to be prioritized in the case of ribosome numbers decreasing.
In the specialization hypothesis though, the ribosomes are the ones that deal out the cards of translation preference. Unlike the insufficiency hypothesis that sees the ribosome structural alterations as a source of functional corruption, the specialization one states they are a source of functional diversity which can be manifested by deviant translational fidelity, speed, and/or mRNA selectivity [21,23].
Both classes of heterogeneous ribosomes, nonfunctional and specialized, exert regulation even through different action modes. It is not simple to distinguish which of the phenomena is responsible for each certain translation outcome [51]. In plants, the phenotypes derived from knockout/knockdown of specific RP mutation generally share some developmental anomalies such as impaired growth, reduced cell proliferation, and increased nuclear ploidy in leaf cells [49,68]. The high similarity between these phenotypes and those resulting from general ribosomal depletion leaves room for questioning whether the regulatory activity associated with specialized ribosomes is actually coming from a scarcity of functional ribosomes rather than from a distinct performance.
In fact, the integration of the two hypotheses is the more reasonable explanation of how ribosome heterogeneity modulates the translation. Regulation is an extremely complex process that involves intricate pathways triggered by a profusion of signals of different intensities and duration. It is expected then, as an important piece of this movement, that the ribosome constitution and activity be impacted in as many ways as diverse as the cell signaling. All these things considered, it can be assumed that either specialized or nonfunctional heterogeneous ribosomes work together to line up the proteome with the cell’s demands that are constantly changing.

3. The Plant Ribosome and Its Vocation to Stress Response Regulation

The ribosomes are large cellular complex products of RNA and protein association. Two moieties, one large (60S) and one small (40S), compose the eukaryotic ribosome. The large subunit consists of 25S/28S, 5.8S, and 5S ribosomal RNA conjugated with 47 proteins. The small subunit is the set of 18S RNA plus 33 proteins [69]. This elaborated structure opens vast possibilities to merge component variants, thus creating heterogeneity that may lead to singular translational activities.
Below, some specific features of plant ribosomes and their biogenesis are listed, and the evidence associating them with abiotic stress response is addressed. Their convergence point is that they all render resources to convert external signals into ribosome variability through changes in the rRNA synthesis, rRNA modifications, and/or protein content.

3.1. Ribosomal Proteins Heterogeneity: Variety to Face Adversity

Each RP that compounds the plant ribosome is codified by multiple genes which are members of several small families [70]. In their analysis, Carroll et al. (2008) [71] found that in Arabidopsis, the 33 RPs from the small subunit and the 48 ones from the large subunit are codified by 102 and 146 genes, respectively, averaging three predicted genes for each RP type. Even though the multigenic nature of RPs is commonly found in eukaryotes, most of the gene copies are pseudogenes [72,73,74]. The plants, however, are an exception to this pattern by having most of the RPs’ gene copies expressed and functional [70,75].
The gene sub-/neo-functionalization is promoted by polyploidization, the multiplication of whole chromosome sets [76,77,78]. Polyploidization is a widespread and recurring phenomenon in the plant kingdom that might be responsible for taking the plant RPs variability to this further level [68,79,80].
Initially seen only as the cement units that kept the rRNA together, shaping the ribosome, the RPs’ biological roles on and even off their contribution to translation have been acknowledged [81]. As they attach to or release from the ribosome subunits, the RPs confer not only new structural but mainly new functional conformations to the ribosome [82]. As reviewed by Byrne (2009) and Horiguchi et al. (2012) [49,68], experiments with RP-defective mutants revealed that the alterations in the number of specific RP families and/or paralogs, an event known as substoichiometry, produced abnormal developmental phenotypes in plants. Proteomic examinations in plants submitted to abiotic stress were also performed. They detected that RPs and ribosome biogenesis factors are among the major protein groups that are differentially abundant between stress-susceptible and stress-tolerant plant genotypes [83].
Although ribosome assembly is highly coordinated with cellular needs, Martinez-Seidel et al. (2020) [48] brought attention to the importance of considering the ribosome turnover to realistically assess the impact of RP changes in the plant response to environmental stress. In Arabidopsis, the mean half-life of RPs is 3–4 days [84]. Meaning that the de novo synthesis of substoichiometric ribosome subfamilies responsive to stress may not happen immediately after the external signal reception. Another possibility raised by the same authors is that alterations/replacements may also occur only to the proteins located on the ribosome surface. This way, once the ribosome core is preserved and reused, the generation of stress-specialized ribosome groups would be faster.

3.2. Plant Ribosome Stress Response: Finer, as It Should Be

Critical to the cell cycle progression, the ribosome biogenesis consumes 80% of an active eukaryotic cell’s energy and is highly sensitive to external stimuli [85,86]. The ribosome stress, also called nucleolar stress, happens when perturbations in the nucleolar morphology and/or function compromise the ribosomal biogenesis [87]. These perturbations can be created by a plethora of stress conditions such as changes in temperature and energy status, hypoxia, nutrient starvation, DNA damage, and UV light, among others [88,89,90].
In animals, the best-characterized response pathway to the ribosome stress is led by the p53 transcription factor. Known as the guardian of the genome due to its important role in cell cycle control and DNA repair [91], p53 is suppressed by MDM2 in unstressed cells. Upon ribosome stress, however, RPs are released from the nucleolus into the nucleoplasm, causing MDM2 inhibition and consequently p53 accumulation. Once stable, p53 induces the expression of a cohort of genes that are involved in cell cycle arrest, senescence, and/or apoptosis setting; this way, the cell responds to ribosome stress [92].
The p53 or MDM2 homologs are not found in plants. However, studies have demonstrated there are multiple proteins playing a very similar role in plant cells. Some of these proteins belong to the NAC family. NAC is a plant-specific transcription factor family largely involved in stress response [93,94,95,96,97]. As reviewed by Obayashi and Sugiyama (2018) [98], NAC transcriptions factors ANAC008, ANAC002, ANAC053, and ANAC082 are key mediators in Arabidopsis response to DNA damage, oxidative stress, and ribosome biogenesis disruptions, respectively. The same mechanisms are governed by p53 in animal cells.
The large number of factors in the plant cell performing the same function that is accomplished by only one protein in the animal cell may infer a finer level of response to nucleolar stress in plants. It corroborates with the several pieces of evidence presenting the plant nucleolus as a stress sensor by eliciting and modulating pathway response to drought, salinity, temperature variation, and others (reviewed by Kalinina et al. (2018) [90]).

3.3. Plant Nucleolar Vacuole: A Cavity Stuffed with Ribosome Heterogeneity

Plant nucleolus contains a structure that distinguishes it from the other ones. It is the nucleolar cavity, a vacuole in the center of the nucleolus whose function is still little known [90,99]. The nucleolar cavity has been indicated as a place of storage and temporal sequestration for mainly small nucleolar (snoRNA), among other biochemical factors such as spliceosomal small nuclear RNAs (snRNAs) and elements of the ubiquitin–proteasome system [100,101,102,103,104].
The snoRNAs have pivotal participation in the rRNA production by marking rRNA molecules to be modified [105]. The modifications are changes in the chemical composition of ribonucleic acid. They are part of a process called maturation which comprises a series of processing steps that lead to the releasing of individual mature rRNA strands from their precursor form, one long polycistronic molecule [106].
The effects of modifications are not limited to the chemical arrangement of rRNA molecules though. Usually clustered in functional rRNA regions as the binding sites for tRNA, the modifications apply a selection pressure on the other translation machinery components [105]. Translation factors, RPs, and tRNA that associate with rRNA may be compatible only with specific sets of rRNA modifications. It can establish a myriad of rRNA-interactor combinations which, in turn, may diversify the translation steering [107].
Studies have been showing that variations in the rRNA modification patterns are responsive to environmental stimuli in eukaryotic cells [108,109,110,111]. This shed new light on the putative function of the plant nucleolar cavity. Once it bears snoRNA, the guiders of rRNA modifications, the nucleolar cavity may perform as a bank of ribosome potential heterogeneity and consequently a booster of plant responsiveness to the environment.

3.4. TOR and SnRKs: The Connectors of Stress Signaling and Ribosome Biogenesis Regulation

Target of Rapamycin (TOR) is a protein kinase that works as a hub sensor and metabolism programmer in eukaryotic cells [112,113]. It catalyzes numerous processes according to the cellular nutrient status and environmental conditions [114]. Firstly found in yeast and animals [115,116,117,118], TOR has been a subject of great interest in plant research after findings placed it as a key coordinator of ribosome biogenesis and cellular adjustments to abiotic cues also in Arabidopsis [119,120,121,122,123,124]. Unable to move away from unfavorable environments, the plants demand an exquisite synchronization between these two processes. In order to survive, they must be extremely receptive to the signals from outside and efficient in converting them to cell growth adaptations. The data published so far point to TOR and sucrose-non-fermenting-1-related protein kinases (SnRKs) as the ones that drive plants toward this achievement [125].
The TOR active engagement in the regulation of plant ribosome biogenesis has been attested by plenty of studies. Ren et al. (2011, 2013) [122,126] and Kim et al. (2014) [123] showed in Arabidopsis that rRNA synthesis is regulated by TOR, as previously demonstrated in yeast and mammals [127,128]. The TOR control over the expression of plant RPs was reported by Xiong et al. (2013) [129], Dobrenel et al. (2016) [130], and Bakshi et al. (2020) [131]. Furthermore, TOR involvement in the coordination between nucleotide biosynthesis and the cell demands for ribosome biogenesis was supported by data from Busche et al. (2021) [132].
Under challenging environmental circumstances, TOR works together with SnRKs transducing the induced signaling and modulating the plant response [125]. The SnRKs are the plant components of the SNF1-type kinases family, which also comprises AMPK and SNF1 itself, which are mammalian and yeast proteins, respectively [133]. They are divided into three subgroups—SnRK1, SnRK2, and SnRK3 [133]—totaling 38 members [134]. Groups 2 and 3 do not have animal or fungi correspondents [135].
The TOR-SnRK1 is a widely accepted pathway to explain the regulation of energy homeostasis in plant cells. Essentially, TOR and SnRK1 work closely to activate/inhibit energy-consuming (anabolic) or energy-releasing (catabolic) reactions in a “yin–yang” dynamic guided by cell energy status and phytohormones such as abscisic acid (ABA), the chief mediator of plant responses against environmental pressures [136,137,138]. Even though some research results have presented discrepancies from this model, as reviewed by [125], it is commonly acknowledged that TOR, activated by high sugar availability and low ABA levels, promotes anabolic routes such as ribosome biogenesis and protein synthesis [113,139,140,141]. SnRK1, on the other hand, is activated by the opposite conditions and triggers the catabolic pathways as autophagy, the degradation and recycling of damaged cellular components after a stress episode [142,143,144].
Regarding SnRK2 and SnRK3, extensive research has made clear they play a significant part in the ABA signal pathway [134,145,146,147,148,149,150,151,152,153]. As plant-exclusive members of SnRKs kinases, their performance can be understood as an evolutionary level up in plant responsiveness to external conditions [135,154].
The accumulating data demonstrate how plant ribosome activity is firmly coordinated with environmental factors through TOR and SnRKs orchestration. As a high energy demanding process, the ribosome biogenesis is under a constant regulation to help plant cells maintain the balance between energy storage and expenditure [155]. This regulation becomes even tighter under limiting conditions once the success of plant acclimation, and hence survival, is directly related to its ability to manage energy consumption [156].

4. Ribosome Heterogeneity and Abiotic Stress Regulation in Plants: What Is Already Known?

While much remains to be discovered, valuable data linking plant ribosome variability to environmental stress have been uncovered. Kawasaki et al. (2001) [18], Moin et al. (2016, 2017) [157,158], and Saha et al. (2017) [16] showed that ribosomal proteins are differentially expressed in rice submitted to osmotic and ionic stresses. Moin et al. (2017) [158] went further and also validated the influence of an RP gene, RPL23A, on rice’s capability to convert water into biomass. Rice plants overexpressing RPL23A performed better than the control ones when exposed to simulated drought and salinity conditions by presenting an increase in fresh weight, root length, and proline and chlorophyll contents.
The expression of RP genes was also reported to be induced by low temperatures in Brassica napus [159], soybean [14], rice [160], barley [161], and Arabidopsis [162], demonstrating that RP can be considered as potential targets for manipulation of tolerance in multiple crops. Moreover, Martinez-Seidel et al. (2021a, 2021b) [161,162] observed in barley and Arabidopsis, respectively, that significant changes in the relative amount of specific RP paralogs were triggered by cold acclimation, which could imply the generation of cold-induced ribosomes characterized by substoichiometric proteome composition. The ribosome regions where these alternative proteoforms are located and their effect on the translation flow were investigated by Martinez-Seidel et al. (2021b) [162]. The results showed that polypeptide exit tunnel (PET), P-stalk, and head portions of ribosome have their functionality limited by the structural remodeling provoked by cold stimulus.
The transcriptome analysis carried out by Garcia-Molina et al. (2020) [163] identified that translational components, especially ribosome proteins, are largely represented among the hubs found in the network of genes expressed in Arabidopsis plants under high light, heat, and cold stress. Hubs are the most highly connected genes in the co-expression network. They occupy a central role in signaling transduction by promoting the interaction between gene expression modules and hence the overlapping of stress response pathways [164].
Certainly, the structural proteins are the most documented source of heterogeneity in plant ribosomes so far, but they are not the only ones. Although the evidence of other sorts of variability are still short, some inferences can be made from the study of translation factors. As mediators of ribosome biogenesis and assembly, the translation factor’s responsiveness to the environment signals may reflect on ribosome diverse configurations. This idea is strengthened by the fact that in plants, the ribosome biogenesis count on plant-exclusive translation factors [165] and the rRNA processing is secured by alternative routes [68,166], suggesting that plant ribosomes may present a vast and specific repertoire of heterogeneity.
Arabidopsis REI1-LIKE proteins (REIL1 and REIL2), for instance, are ribosomal biogenesis factors that act in the rRNA processing. It turns out that they are also heavily involved with the plant response to cold stress [167,168,169]. The REIL proteins are required to keep the rRNA maturation process on even under low temperatures, thus preventing a severe growth downturn and stimulating cold tolerance in plants [170].
Another ribosomal biogenesis factor reported as responsive to stress is NOG1, nucleolar GTP-binding protein 1. This small GTPase is essential to the rRNA maturation [171]. Its silencing caused the over-accumulation of pre-rRNA processing intermediates and a subsequent decrease in mature rRNAs in Nicotiana Benthamiana [172]. In Arabidopsis, Lee et al. (2017, 2018) [173,174] showed that NOG1 also regulates the guard cell aperture in response to biotic and abiotic stimuli. Pant et al. (2022) [175] demonstrated that the overexpression of NOG1 conferred drought tolerance to rice.
In Manzano et al. (2020) [176], Arabidopsis mutants from NUC1 and NUC2 genes, both coding for ribosome biogenesis regulators, were submitted to two lighting regimes (red light and darkness). The results indicated that the darkness compromised the ribosome synthesis in particular. Plants exposed to red light, a ribosome synthesis activator, showed more resilience only when NUC2 function was preserved. Interestingly, the purpose of this research was to identify genetic backgrounds that can be advantageous to the plants’ adaptation to spaceflight. The plants are the key enablers of longer human missions to space due to the vital resources they can provide (biomass, revitalized atmosphere, purified water, and waste recycling) [177]. However, plant cultivation in such unique conditions (microgravity, weak magnetic field, darkness) is hardly manageable. Ground experiments such as the ones performed by Manzano et al. (2020) [176] are a useful complement to the ones that have been carried out in space.
Even though no direct evidence of ribosome heterogeneity was produced from them, the studies that applied polysome or ribosome profiling approaches are noteworthy for proving that abiotic stressors can induce differential translational landscapes [178]. The polysome profiling uses sucrose-gradient centrifugation to separate the translatome. The translated transcripts, heavier due to ribosome association, are deposited in the bottom, isolated, and then quantified [179].Through ribosome profiling, however, the measuring of the translatome is carried out in a sequencing-based manner [180]. Nucleases degrade the portions of the mRNA that are not coupled with the translation machinery, and the remaining fractions, ~30 nt translating sequences known as ribosome footprints, are sequenced [181]. Unlike polysome profiling, this methodology enables a high-resolution mapping of the mRNA segments actively recruited by ribosome that may include the identification of alternative start codons and novel open reading frames [182].
Translational activity under stressed and unstressed conditions was compared using these techniques and revealed that many abiotic stressors such as hypoxia [60,183,184], light deprivation [59], water deficit [58,185], salinity [186,187], and heat [187,188] strongly drive the selection of translating mRNA pools. In addition, some important regulatory cues such as the active translation of uORFs as a strategy to quickly adjust the translatome to environmental changes were detected by Liu et al. (2013), Juntawong et al. (2014), and Lei et al. (2015) [58,59,60] through ribosome profiling.

5. Ribosome Heterogeneity and Abiotic Stress Regulation in Plants: What Is Next?

Breaking the code of plant ribosome heterogeneity induced by abiotic stress is the main requisite to successfully outline ribosome engineering projects aiming to breed cultivars for superior performance under fluctuating environments. It is a continuous pursuit that should follow some guiding points:
  • Manipulating the ribosomes is modifying a system:
    The role of a heterogeneous ribosome subgroup in the plant response to abiotic stress can only be fairly characterized under the prism of a whole regulatory system.
    The ribosome heterogeneity applies a translational selection on mRNA pools which are themselves the product of transcriptional regulation. Therefore, to identify which ribosome feature is worth being engineered, it is necessary not only to understand its impact on a certain translation outcome but also how it relates to the other regulation layers.
  • The complexity of abiotic stressors must be addressed:
    Although they meet the goals of basic science, most of the studies limit the spectrum of plant response to abiotic stresses by analyzing each type of them individually. A single kind of stress at a time is the opposite scenario of what happens in nature. The environmental conditions are essentially unstable. The plants usually have to tackle different abiotic stressors simultaneously. Thus, their reaction in this case is surely not the same as when only one stress is applied, as demonstrated by Rasmussen et al. (2013) [189]. So, for plant breeding purposes, the investigations of ribosome heterogeneity induced by a combination of environmental stress must be intensified. This way, the ribosome engineering can be centered on data that reflect more consistently the conditions found in the field.
  • Synthetic biology techniques should be optimized for plant research:
    While techniques such as CRISPR/Cas have been broadly used to precisely edit the genome of crop species and develop more sustainable cultivars [190], other ones remain to be mastered by plant research. Methods of in vitro ribosome synthesis such as the “Integrated synthesis, assembly, and translation” (iSAT) [191,192] and “In vitro ribosome synthesis and evolution” (RISE) [193] enable the production and investigation of ribosome variants. Once optimized and fully explored by plant biologists, significant advances in the knowledge of plant ribosomes can be achieved through them.

Author Contributions

Conceptualization, L.D.-F.; writing—original draft preparation, L.D.-F.; writing—review and editing, K.P.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

This work was supported by NSF award 1840301 RoL:FELS:RAISE, Building and Modeling Synthetic Bacterial Cells, and the NSF Center for Genetically Encoded Materials.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Yadav, S.; Modi, P.; Dave, A.; Vijapura, A.; Patel, D.; Patel, M. Effect of Abiotic Stress on Crops. In Sustainable Crop Production; Hasanuzzaman, M., Fujita, M., Teixeira Filho, M.C.M., Nogueira, T.A.R., Galindo, F.S., Eds.; IntechOpen: London, UK, 2020. [Google Scholar] [CrossRef]
  2. Boyer, J.S. Plant Productivity and Environment. Science 1982, 218, 443–448. [Google Scholar] [CrossRef] [PubMed]
  3. Shinozaki, K.; Uemura, M.; Bailey-Serres, J.; Bray, E.A.; Weretilnyk, E. Responses to abiotic stress. In Biochemistry and Molecular Biology of Plants; Buchanan, B.B., Gruissem, W., Jones, R.L., Eds.; Wiley & Sons: Hoboken, NJ, USA, 2015; pp. 1051–1100. [Google Scholar]
  4. Vij, S.; Tyagi, A.K. Emerging trends in the functional genomics of the abiotic stress response in crop plants. Plant Biotechnol. J. 2007, 5, 361–380. [Google Scholar] [CrossRef] [PubMed]
  5. Zurbriggen, M.D.; Hajirezaei, M.-R.; Carrillo, N. Engineering the future. Development of transgenic plants with enhanced tolerance to adverse environments. Biotechnol. Genet. Eng. Rev. 2010, 27, 33–56. [Google Scholar] [CrossRef] [PubMed]
  6. Mortimer, J.C. Plant synthetic biology could drive a revolution in biofuels and medicine. Exp. Biol. Med. 2019, 244, 323–331. [Google Scholar] [CrossRef] [PubMed]
  7. D’Aquino, A.E.; Kim, D.S.; Jewett, M.C. Engineered Ribosomes for Basic Science and Synthetic Biology. Annu. Rev. Chem. Biomol. Eng. 2018, 9, 311–340. [Google Scholar] [CrossRef]
  8. Prabhakar, A.; Choi, J.; Wang, J.; Petrov, A.; Puglisi, J.D. Dynamic basis of fidelity and speed in translation: Coordinated multistep mechanisms of elongation and termination: Dynamic Basis of Fidelity and Speed in Translation. Protein Sci. 2017, 26, 1352–1362. [Google Scholar] [CrossRef]
  9. Ohta, A.; Murakami, H.; Higashimura, E.; Suga, H. Synthesis of Polyester by Means of Genetic Code Reprogramming. Chem. Biol. 2007, 14, 1315–1322. [Google Scholar] [CrossRef]
  10. Liu, C.C.; Schultz, P.G. Adding New Chemistries to the Genetic Code. Annu. Rev. Biochem. 2010, 79, 413–444. [Google Scholar] [CrossRef]
  11. Neumann, H.; Wang, K.; Davis, L.; Garcia-Alai, M.; Chin, J.W. Encoding multiple unnatural amino acids via evolution of a quadruplet-decoding ribosome. Nature 2010, 464, 441–444. [Google Scholar] [CrossRef]
  12. Zhang, Y.; Ptacin, J.L.; Fischer, E.C.; Aerni, H.R.; Caffaro, C.E.; Jose, K.S.; Feldman, A.W.; Turner, C.R.; Romesberg, F.E. A semi-synthetic organism that stores and retrieves increased genetic information. Nature 2017, 551, 644–647. [Google Scholar] [CrossRef]
  13. O’Donoghue, P.; Ling, J.; Wang, Y.-S.; Söll, D. Upgrading protein synthesis for synthetic biology. Nat. Chem. Biol. 2013, 9, 594–598. [Google Scholar] [CrossRef] [PubMed]
  14. Kim, K.-Y.; Park, S.-W.; Chung, Y.-S.; Chung, C.-H.; Kim, J.-I.; Lee, J.-H. Molecular cloning of low-temperature-inducible ribosomal proteins from soybean. J. Exp. Bot. 2004, 55, 1153–1155. [Google Scholar] [CrossRef] [PubMed]
  15. Wang, J.; Lan, P.; Gao, H.; Zheng, L.; Li, W.; Schmidt, W. Expression changes of ribosomal proteins in phosphate- and iron-deficient Arabidopsis roots predict stress-specific alterations in ribosome composition. BMC Genom. 2013, 14, 783. [Google Scholar] [CrossRef] [PubMed]
  16. Saha, A.; Das, S.; Moin, M.; Dutta, M.; Bakshi, A.; Madhav, M.S.; Kirti, P.B. Genome-Wide Identification and Comprehensive Expression Profiling of Ribosomal Protein Small Subunit (RPS) Genes and their Comparative Analysis with the Large Subunit (RPL) Genes in Rice. Front. Plant Sci. 2017, 8, 1553. [Google Scholar] [CrossRef]
  17. Cherepneva, G.N.; Schmidt, K.-H.; Kulaeva, O.N.; Oelmüller, R.; Kusnetsov, V. Expression of the ribosomal proteins S14, S16, L13a and L30 is regulated by cytokinin and abscisic acid: Implication of the involvement of phytohormones in translational processes. Plant Sci. 2003, 165, 925–932. [Google Scholar] [CrossRef]
  18. Kawasaki, S.; Borchert, C.; Deyholos, M.; Wang, H.; Brazille, S.; Kawai, K.; Galbraith, D.; Bohnert, H.J. Gene Expression Profiles during the Initial Phase of Salt Stress in Rice. Plant Cell 2001, 13, 889–905. [Google Scholar] [CrossRef]
  19. Wilson, D.; Cate, J.H.D. The Structure and Function of the Eukaryotic Ribosome. Cold Spring Harb. Perspect. Biol. 2012, 4, a011536. [Google Scholar] [CrossRef]
  20. Genuth, N.R.; Barna, M. Heterogeneity and specialized functions of translation machinery: From genes to organisms. Nat. Rev. Genet. 2018, 19, 431–452. [Google Scholar] [CrossRef]
  21. Genuth, N.R.; Barna, M. The Discovery of Ribosome Heterogeneity and Its Implications for Gene Regulation and Organismal Life. Mol. Cell 2018, 71, 364–374. [Google Scholar] [CrossRef]
  22. Calamita, P.; Gatti, G.; Miluzio, A.; Scagliola, A.; Biffo, S. Translating the Game: Ribosomes as Active Players. Front. Genet. 2018, 9, 533. [Google Scholar] [CrossRef]
  23. Emmott, E.; Jovanovic, M.; Slavov, N. Ribosome Stoichiometry: From Form to Function. Trends Biochem. Sci. 2019, 44, 95–109. [Google Scholar] [CrossRef] [PubMed]
  24. Shi, Z.; Fujii, K.; Kovary, K.M.; Genuth, N.R.; Röst, H.L.; Teruel, M.N.; Barna, M. Heterogeneous Ribosomes Preferentially Translate Distinct Subpools of mRNAs Genome-wide. Mol. Cell 2017, 67, 71–83.e7. [Google Scholar] [CrossRef] [PubMed]
  25. Gunderson, J.H.; Sogin, M.L.; Wollett, G.; Hollingdale, M.; de la Cruz, V.F.; Waters, A.P.; McCutchan, T.F. Structurally Distinct, Stage-Specific Ribosomes Occur in Plasmodium. Science 1987, 238, 933–937. [Google Scholar] [CrossRef]
  26. Ramagopal, S. Induction of cell-specific ribosomal proteins in aggregation-competent nonmorphogenetic Dictyostelium discoideum. Biochem. Cell Biol. 1990, 68, 1281–1287. [Google Scholar] [CrossRef] [PubMed]
  27. Williams, M.; Sussex, I.M. Developmental regulation of ribosomal protein L16 genes in Arabidopsis thaliana. Plant J. 1995, 8, 65–76. [Google Scholar] [CrossRef]
  28. Milne, A.N.; Mak, W.W.; Wong, J.T.-F. Variation of ribosomal proteins with bacterial growth rate. J. Bacteriol. 1975, 122, 89–92. [Google Scholar] [CrossRef]
  29. Bortoluzzi, S.; D’Alessi, F.; Romualdi, C.; Danieli, G.A. Differential expression of genes coding for ribosomal proteins in different human tissues. Bioinformatics 2001, 17, 1152–1157. [Google Scholar] [CrossRef]
  30. Pb, K.; Moin, M.; Bakshi, A.; Saha, A. Ribosomal Proteins and their Extra Ribosomal Functions in Abiotic Stress Tolerance of Plants. Mod. Concepts Dev. Agron. 2019, 4, 1024–1038. [Google Scholar] [CrossRef]
  31. Salih, K.J.; Duncan, O.; Li, L.; O’Leary, B.; Fenske, R.; Trösch, J.; Millar, A.H. Impact of oxidative stress on the function, abundance, and turnover of the Arabidopsis 80S cytosolic ribosome. Plant J. 2020, 103, 128–139. [Google Scholar] [CrossRef]
  32. Terhorst, A.; Sandikci, A.; Neurohr, G.E.; Whittaker, C.A.; Szórádi, T.; Holt, L.J.; Amon, A. The Environmental Stress Response Regulates Ribosome Content in Cell Cycle-Arrested S. Cerevisiae. bioRxiv 2021. [Google Scholar] [CrossRef]
  33. El-Sharoud, W.M. Ribosome Inactivation for Preservation: Concepts and Reservations. Sci. Prog. 2004, 87, 137–152. [Google Scholar] [CrossRef] [PubMed]
  34. Wigge, P.A.; Guillaume-Schoepfer, D.; Jaeger, K.E.; Geng, F.; Doccula, F.G.; Costa, A.; Webb, A.A. Ribosomes Act as Cryosensors in Plants. bioRxiv 2020. [Google Scholar] [CrossRef]
  35. Hang, R.; Wang, Z.; Deng, X.; Liu, C.; Yan, B.; Yang, C.; Song, X.; Mo, B.; Cao, X. Ribosomal RNA Biogenesis and Its Response to Chilling Stress in Oryza sativa. Plant Physiol. 2018, 177, 381–397. [Google Scholar] [CrossRef] [PubMed]
  36. Liu, G.; Yan, P.; Du, Q.; Wang, Y.; Guo, Y.; Fu, Z.; Wang, H.; Tang, J. Pre-rRNA processing and its response to temperature stress in maize. J. Exp. Bot. 2019, 71, 1363–1374. [Google Scholar] [CrossRef]
  37. Camacho, R.A.U.; Lokdarshi, A.; von Arnim, A.G. Translational gene regulation in plants: A green new deal. Wiley Interdiscip. Rev. RNA 2020, 11, e1597. [Google Scholar] [CrossRef]
  38. Zhang, H.; Zhu, J.; Gong, Z.; Zhu, J.-K. Abiotic stress responses in plants. Nat. Rev. Genet. 2022, 23, 104–119. [Google Scholar] [CrossRef]
  39. Huey, R.; Carlson, M.; Crozier, L.G.; Frazier, M.R.; Hamilton, H.; Harley, C.; Hoang, A.; Kingsolver, J.G. Plants Versus Animals: Do They Deal with Stress in Different Ways? Integr. Comp. Biol. 2002, 42, 415–423. [Google Scholar] [CrossRef]
  40. Graber, T.E.; Holcik, M. Cap-independent regulation of gene expression in apoptosis. Mol. BioSyst. 2007, 3, 825–834. [Google Scholar] [CrossRef]
  41. Muñoz, A.; Castellano, M.M. Regulation of Translation Initiation under Abiotic Stress Conditions in Plants: Is It a Conserved or Not so Conserved Process among Eukaryotes? Comp. Funct. Genom. 2012, 2012, 406357. [Google Scholar] [CrossRef]
  42. Floris, M.; Mahgoub, H.; Lanet, E.; Robaglia, C.; Menand, B. Post-transcriptional Regulation of Gene Expression in Plants during Abiotic Stress. Int. J. Mol. Sci. 2009, 10, 3168–3185. [Google Scholar] [CrossRef]
  43. Juntawong, P.; Bailey-Serres, J. Dynamic Light Regulation of Translation Status in Arabidopsis thaliana. Front. Plant Sci. 2012, 3, 66. [Google Scholar] [CrossRef] [PubMed]
  44. Piques, M.; Schulze, W.X.; Höhne, M.; Usadel, B.; Gibon, Y.; Rohwer, J.; Stitt, M. Ribosome and transcript copy numbers, polysome occupancy and enzyme dynamics in Arabidopsis. Mol. Syst. Biol. 2009, 5, 314. [Google Scholar] [CrossRef] [PubMed]
  45. I Zandalinas, S.; Balfagón, D.; Gómez-Cadenas, A.; Mittler, R. Plant responses to climate change: Metabolic changes under combined abiotic stresses. J. Exp. Bot. 2022, 73, 3339–3354. [Google Scholar] [CrossRef] [PubMed]
  46. Sormani, R.; Masclaux-Daubresse, C.; Daniele-Vedele, F.; Chardon, F. Transcriptional Regulation of Ribosome Components Are Determined by Stress According to Cellular Compartments in Arabidopsis thaliana. PLoS ONE 2011, 6, e28070. [Google Scholar] [CrossRef]
  47. Zhang, H.; Zhao, Y.; Zhu, J.-K. Thriving under Stress: How Plants Balance Growth and the Stress Response. Dev. Cell 2020, 55, 529–543. [Google Scholar] [CrossRef] [PubMed]
  48. Martinez-Seidel, F.; Golovchuk, O.B.; Hsieh, Y.-C.; Kopka, J. Systematic Review of Plant Ribosome Heterogeneity and Specialization. Front. Plant Sci. 2020, 11, 948. [Google Scholar] [CrossRef]
  49. Horiguchi, G.; Van Lijsebettens, M.; Candela, H.; Micol, J.L.; Tsukaya, H. Ribosomes and translation in plant developmental control. Plant Sci. 2012, 191–192, 24–34. [Google Scholar] [CrossRef] [PubMed]
  50. Gerst, J.E. Pimp My Ribosome: Ribosomal Protein Paralogs Specify Translational Control. Trends Genet. 2018, 34, 832–845. [Google Scholar] [CrossRef]
  51. Ferretti, M.; Karbstein, K. Does functional specialization of ribosomes really exist? RNA 2019, 25, 521–538. [Google Scholar] [CrossRef] [PubMed]
  52. Kawaguchi, R. mRNA sequence features that contribute to translational regulation in Arabidopsis. Nucleic Acids Res. 2005, 33, 955–965. [Google Scholar] [CrossRef] [PubMed]
  53. Kozak, M. Point mutations define a sequence flanking the AUG initiator codon that modulates translation by eukaryotic ribosomes. Cell 1986, 44, 283–292. [Google Scholar] [CrossRef]
  54. Hernández, G.; Osnaya, V.G.; Pérez-Martínez, X. Conservation and Variability of the AUG Initiation Codon Context in Eukaryotes. Trends Biochem. Sci. 2019, 44, 1009–1021. [Google Scholar] [CrossRef] [PubMed]
  55. Acevedo, J.M.; Hoermann, B.; Schlimbach, T.; Teleman, A.A. Changes in global translation elongation or initiation rates shape the proteome via the Kozak sequence. Sci. Rep. 2018, 8, 4018. [Google Scholar] [CrossRef] [PubMed]
  56. Gupta, P.; Rangan, L.; Ramesh, T.V.; Gupta, M. Comparative analysis of contextual bias around the translation initiation sites in plant genomes. J. Theor. Biol. 2016, 404, 303–311. [Google Scholar] [CrossRef] [PubMed]
  57. Srivastava, A.K.; Lu, Y.; Zinta, G.; Lang, Z.; Zhu, J.-K. UTR-Dependent Control of Gene Expression in Plants. Trends Plant Sci. 2018, 23, 248–259. [Google Scholar] [CrossRef]
  58. Lei, L.; Shi, J.; Chen, J.; Zhang, M.; Sun, S.; Xie, S.; Li, X.; Zeng, B.; Peng, L.; Hauck, A.; et al. Ribosome profiling reveals dynamic translational landscape in maize seedlings under drought stress. Plant J. 2015, 84, 1206–1218. [Google Scholar] [CrossRef] [PubMed]
  59. Liu, M.-J.; Wu, S.-H.; Wu, J.-F.; Lin, W.-D.; Wu, Y.-C.; Tsai, T.-Y.; Tsai, H.-L.; Wu, S.-H. Translational Landscape of Photomorphogenic Arabidopsis. Plant Cell 2013, 25, 3699–3710. [Google Scholar] [CrossRef] [PubMed]
  60. Juntawong, P.; Girke, T.; Bazin, J.; Bailey-Serres, J. Translational dynamics revealed by genome-wide profiling of ribosome footprints in Arabidopsis. Proc. Natl. Acad. Sci. USA 2014, 111, E203–E212. [Google Scholar] [CrossRef]
  61. Zhang, T.; Wu, A.; Yue, Y.; Zhao, Y. uORFs: Important Cis-Regulatory Elements in Plants. Int. J. Mol. Sci. 2020, 21, 6238. [Google Scholar] [CrossRef]
  62. von Arnim, A.G.; Jia, Q.; Vaughn, J.N. Regulation of plant translation by upstream open reading frames. Plant Sci. 2014, 214, 1–12. [Google Scholar] [CrossRef]
  63. Um, T.; Park, T.; Shim, J.; Kim, Y.; Lee, G.-S.; Choi, I.-Y.; Kim, J.-K.; Seo, J.; Park, S. Application of Upstream Open Reading Frames (uORFs) Editing for the Development of Stress-Tolerant Crops. Int. J. Mol. Sci. 2021, 22, 3743. [Google Scholar] [CrossRef] [PubMed]
  64. Zhang, H.; Si, X.; Ji, X.; Fan, R.; Liu, J.; Chen, K.; Wang, D.; Gao, C. Genome editing of upstream open reading frames enables translational control in plants. Nat. Biotechnol. 2018, 36, 894–898. [Google Scholar] [CrossRef] [PubMed]
  65. Kurihara, Y. uORF Shuffling Fine-Tunes Gene Expression at a Deep Level of the Process. Plants 2020, 9, 608. [Google Scholar] [CrossRef] [PubMed]
  66. Young, S.K.; Wek, R.C. Upstream Open Reading Frames Differentially Regulate Gene-specific Translation in the Integrated Stress Response. J. Biol. Chem. 2016, 291, 16927–16935. [Google Scholar] [CrossRef] [PubMed]
  67. Mills, E.W.; Green, R. Ribosomopathies: There’s strength in numbers. Science 2017, 358, eaan2755. [Google Scholar] [CrossRef] [PubMed]
  68. Byrne, M.E. A role for the ribosome in development. Trends Plant Sci. 2009, 14, 512–519. [Google Scholar] [CrossRef] [PubMed]
  69. Weis, B.L.; Kovacevic, J.; Missbach, S.; Schleiff, E. Plant-Specific Features of Ribosome Biogenesis. Trends Plant Sci. 2015, 20, 729–740. [Google Scholar] [CrossRef] [PubMed]
  70. Barakat, A.; Szick-Miranda, K.; Chang, I.-F.; Guyot, R.; Blanc, G.; Cooke, R.; Delseny, M.; Bailey-Serres, J. The Organization of Cytoplasmic Ribosomal Protein Genes in the Arabidopsis Genome. Plant Physiol. 2001, 127, 398–415. [Google Scholar] [CrossRef] [PubMed]
  71. Carroll, A.J.; Heazlewood, J.L.; Ito, J.; Millar, A.H. Analysis of the Arabidopsis Cytosolic Ribosome Proteome Provides Detailed Insights into Its Components and Their Post-translational Modification. Mol. Cell. Proteom. 2008, 7, 347–369. [Google Scholar] [CrossRef]
  72. Wool, I.G.; Chan, Y.-L.; Glück, A. Structure and evolution of mammalian ribosomal proteins. Biochem. Cell Biol. 1995, 73, 933–947. [Google Scholar] [CrossRef]
  73. Harrison, P.M.; Hegyi, H.; Balasubramanian, S.; Luscombe, N.M.; Bertone, P.; Echols, N.; Johnson, T.; Gerstein, M. Molecular Fossils in the Human Genome: Identification and Analysis of the Pseudogenes in Chromosomes 21 and 22. Genome Res. 2002, 12, 272–280. [Google Scholar] [CrossRef] [PubMed]
  74. Zhang, Z.; Harrison, P.; Gerstein, M. Identification and analysis of over 2000 ribosomal protein pseudogenes in the human genome. Genome Res. 2002, 12, 1466–1482. [Google Scholar] [CrossRef] [PubMed]
  75. Wu, J.; Matsui, E.; Yamamoto, K.; Nagamura, Y.; Kurata, N.; Takuji, S.; Minobe, Y. Genomic organization of 57 ribosomal protein genes in rice (Oryza sativa L.) through RFLP mapping. Genome 1995, 38, 1189–1200. [Google Scholar] [CrossRef]
  76. Zhang, K.; Wang, X.; Cheng, F. Plant Polyploidy: Origin, Evolution, and Its Influence on Crop Domestication. Hortic. Plant J. 2019, 5, 231–239. [Google Scholar] [CrossRef]
  77. Ohno, S. Evolution by Gene Duplication; Springer: Berlin/Heidelberg, Germany, 1970. [Google Scholar]
  78. Cheng, F.; Wu, J.; Cai, X.; Liang, J.; Freeling, M.; Wang, X. Gene retention, fractionation and sub genome differences in polyploid plants. Nat. Plants 2018, 4, 258–268. [Google Scholar] [CrossRef]
  79. Blanc, G.; Wolfe, K. Functional Divergence of Duplicated Genes Formed by Polyploidy during Arabidopsis Evolution. Plant Cell 2004, 16, 1679–1691. [Google Scholar] [CrossRef]
  80. Thomas, B.C.; Pedersen, B.; Freeling, M. Following tetraploidy in an Arabidopsis ancestor, genes were removed preferentially from one homeolog leaving clusters enriched in dose-sensitive genes. Genome Res. 2006, 16, 934–946. [Google Scholar] [CrossRef]
  81. Brodersen, D.E.; Nissen, P. The social life of ribosomal proteins: The Social Life of Ribosomal Proteins. FEBS J. 2005, 272, 2098–2108. [Google Scholar] [CrossRef]
  82. McIntosh, K.B.; Bonham-Smith, P.C. Ribosomal protein gene regulation: What about plants? Can. J. Bot. 2006, 84, 342–362. [Google Scholar] [CrossRef]
  83. Kosová, K.; Vítámvás, P.; Urban, M.O.; Prášil, I.T.; Renaut, J. Plant Abiotic Stress Proteomics: The Major Factors Determining Alterations in Cellular Proteome. Front. Plant Sci. 2018, 9, 122. [Google Scholar] [CrossRef]
  84. Salih, K.J.; Duncan, O.; Li, L.; Trösch, J.; Millar, A.H. The composition and turnover of the Arabidopsis thaliana 80S cytosolic ribosome. Biochem. J. 2020, 477, 3019–3032. [Google Scholar] [CrossRef] [PubMed]
  85. Lu, L.; Yi, H.; Chen, C.; Yan, S.; Yao, H.; He, G.; Li, G.; Jiang, Y.; Deng, T.; Deng, X. Nucleolar stress: Is there a reverse version? J. Cancer 2018, 9, 3723–3727. [Google Scholar] [CrossRef] [PubMed]
  86. Moss, T.; Stefanovsky, V.Y. At the Center of Eukaryotic Life. Cell 2002, 109, 545–548. [Google Scholar] [CrossRef]
  87. Boulon, S.; Westman, B.J.; Hutten, S.; Boisvert, F.-M.; Lamond, A.I. The Nucleolus under Stress. Mol. Cell 2010, 40, 216–227. [Google Scholar] [CrossRef]
  88. Sáez-Vásquez, J.; Delseny, M. Ribosome Biogenesis in Plants: From Functional 45S Ribosomal DNA Organization to Ribosome Assembly Factors. Plant Cell 2019, 31, 1945–1967. [Google Scholar] [CrossRef]
  89. Yang, K.; Yang, J.; Yi, J. Nucleolar Stress: Hallmarks, sensing mechanism and diseases. Cell Stress 2018, 2, 125–140. [Google Scholar] [CrossRef]
  90. Kalinina, N.O.; Makarova, S.; Makhotenko, A.; Love, A.J.; Taliansky, M. The Multiple Functions of the Nucleolus in Plant Development, Disease and Stress Responses. Front. Plant Sci. 2018, 9, 132. [Google Scholar] [CrossRef]
  91. Lane, D.P. p53, guardian of the genome. Nature 1992, 358, 15–16. [Google Scholar] [CrossRef]
  92. Golomb, L.; Volarevic, S.; Oren, M. p53 and ribosome biogenesis stress: The essentials. FEBS Lett. 2014, 588, 2571–2579. [Google Scholar] [CrossRef]
  93. Garapati, P.; Xue, G.-P.; Munné-Bosch, S.; Balazadeh, S. Transcription Factor ATAF1 in Arabidopsis Promotes Senescence by Direct Regulation of Key Chloroplast Maintenance and Senescence Transcriptional Cascades. Plant Physiol. 2015, 168, 1122–1139. [Google Scholar] [CrossRef]
  94. Lee, S.; Seo, P.J.; Lee, H.-J.; Park, C.-M. A NAC transcription factor NTL4 promotes reactive oxygen species production during drought-induced leaf senescence in Arabidopsis. Plant J. 2012, 70, 831–844. [Google Scholar] [CrossRef] [PubMed]
  95. Balazadeh, S.; Wu, A.; Mueller-Roeber, B. Salt-triggered expression of the ANAC092-dependent senescence regulon in Arabidopsis thaliana. Plant Signal. Behav. 2010, 5, 733–735. [Google Scholar] [CrossRef] [PubMed]
  96. Yoshiyama, K.O. SOG1: A master regulator of the DNA damage response in plants. Genes Genet. Syst. 2015, 90, 209–216. [Google Scholar] [CrossRef] [PubMed]
  97. Yoshiyama, K.O.; Kobayashi, J.; Ogita, N.; Ueda, M.; Kimura, S.; Maki, H.; Umeda, M. ATM-mediated phosphorylation of SOG1 is essential for the DNA damage response in Arabidopsis. EMBO Rep. 2013, 14, 817–822. [Google Scholar] [CrossRef]
  98. Ohbayashi, I.; Sugiyama, M. Plant Nucleolar Stress Response, a New Face in the NAC-Dependent Cellular Stress Responses. Front. Plant Sci. 2018, 8, 2247. [Google Scholar] [CrossRef]
  99. Shaw, P.; Brown, J. Nucleoli: Composition, Function, and Dynamics. Plant Physiol. 2012, 158, 44–51. [Google Scholar] [CrossRef]
  100. Beven, A.F.; Lee, R.; Razaz, M.; Leader, D.J.; Brown, J.W.; Shaw, P.J. The organization of ribosomal RNA processing correlates with the distribution of nucleolar snRNAs. J. Cell Sci. 1996, 109, 1241–1251. [Google Scholar] [CrossRef]
  101. Beven, A.F.; Simpson, G.G.; Brown, J.W.S.; Shaw, P.J. The organization of spliceosomal components in the nuclei of higher plants. J. Cell Sci. 1995, 108, 509–551. [Google Scholar] [CrossRef] [PubMed]
  102. Lorković, Z.J.; Barta, A. Role of Cajal Bodies and Nucleolus in the Maturation of the U1 snRNP in Arabidopsis. PLoS ONE 2008, 3, e3989. [Google Scholar] [CrossRef]
  103. Stępiński, D. Immunofluorescent localization of ubiquitin and proteasomes in nucleolar vacuoles of soybean root meristematic cells. Eur. J. Histochem. 2012, 56, e13. [Google Scholar] [CrossRef] [PubMed]
  104. Stępiński, D. Functional ultrastructure of the plant nucleolus. Protoplasma 2014, 251, 1285–1306. [Google Scholar] [CrossRef]
  105. Terns, M.P.; Terns, R.M. Small nucleolar RNAs: Versatile trans-acting molecules of ancient evolutionary origin. Gene Expr. 2002, 10, 17–39. [Google Scholar] [PubMed]
  106. Henras, A.K.; Plisson-Chastang, C.; O’Donohue, M.-F.; Chakraborty, A.; Gleizes, P.-E. An overview of pre-ribosomal RNA processing in eukaryotes: Pre-Ribosomal RNA Processing in Eukaryotes. Wiley Interdiscip. Rev. RNA 2015, 6, 225–242. [Google Scholar] [CrossRef] [PubMed]
  107. Sloan, K.E.; Warda, A.S.; Sharma, S.; Entian, K.-D.; Lafontaine, D.L.J.; Bohnsack, M.T. Tuning the ribosome: The influence of rRNA modification on eukaryotic ribosome biogenesis and function. RNA Biol. 2017, 14, 1138–1152. [Google Scholar] [CrossRef]
  108. Carlile, T.M.; Rojas-Duran, M.F.; Zinshteyn, B.; Shin, H.; Bartoli, K.M.; Gilbert, W.V. Pseudouridine profiling reveals regulated mRNA pseudouridylation in yeast and human cells. Nature 2014, 515, 143–146. [Google Scholar] [CrossRef]
  109. Schwartz, S.; Bernstein, D.A.; Mumbach, M.R.; Jovanovic, M.; Herbst, R.H.; León-Ricardo, B.X.; Engreitz, J.M.; Guttman, M.; Satija, R.; Lander, E.S.; et al. Transcriptome-wide Mapping Reveals Widespread Dynamic-Regulated Pseudouridylation of ncRNA and mRNA. Cell 2014, 159, 148–162. [Google Scholar] [CrossRef] [PubMed]
  110. Wu, G.; Xiao, M.; Yang, C.; Yu, Y.-T. U2 snRNA is inducibly pseudouridylated at novel sites by Pus7p and snR81 RNP. EMBO J. 2011, 30, 79–89. [Google Scholar] [CrossRef]
  111. Yu, Y.-T.; Meier, U.T. RNA-guided isomerization of uridine to pseudouridine—pseudouridylation. RNA Biol. 2014, 11, 1483–1494. [Google Scholar] [CrossRef] [PubMed]
  112. Wullschleger, S.; Loewith, R.; Hall, M.N. TOR Signaling in Growth and Metabolism. Cell 2006, 124, 471–484. [Google Scholar] [CrossRef] [PubMed]
  113. Shi, L.; Wu, Y.; Sheen, J. TOR signaling in plants: Conservation and innovation. Development 2018, 145, dev160887. [Google Scholar] [CrossRef] [PubMed]
  114. Caldana, C.; Li, Y.; Leisse, A.; Zhang, Y.; Bartholomaeus, L.; Fernie, A.R.; Willmitzer, L.; Giavalisco, P. Systemic analysis of inducible target of rapamycin mutants reveal a general metabolic switch controlling growth in Arabidopsis thaliana. Plant J. 2013, 73, 897–909. [Google Scholar] [CrossRef] [PubMed]
  115. Kunz, J.; Henriquez, R.; Schneider, U.; Deuter-Reinhard, M.; Movva, N.R.; Hall, M.N. Target of rapamycin in yeast, TOR2, is an essential phosphatidylinositol kinase homolog required for G1 progression. Cell 1993, 73, 585–596. [Google Scholar] [CrossRef]
  116. Sabatini, D.M.; Erdjument-Bromage, H.; Lui, M.; Tempst, P.; Snyder, S.H. RAFT1: A mammalian protein that binds to FKBP12 in a rapamycin-dependent fashion and is homologous to yeast TORs. Cell 1994, 78, 35–43. [Google Scholar] [CrossRef]
  117. Chiu, M.I.; Katz, H.; Berlin, V. RAPT1, a mammalian homolog of yeast Tor, interacts with the FKBP12/rapamycin complex. Proc. Natl. Acad. Sci. USA 1994, 91, 12574–12578. [Google Scholar] [CrossRef]
  118. Heitman, J.; Movva, N.R.; Hall, M.N. Targets for Cell Cycle Arrest by the Immunosuppressant Rapamycin in Yeast. Science 1991, 253, 905–909. [Google Scholar] [CrossRef]
  119. Dong, P.; Xiong, F.; Que, Y.; Wang, K.; Yu, L.; Li, Z.; Ren, M. Expression profiling and functional analysis reveals that TOR is a key player in regulating photosynthesis and phytohormone signaling pathways in Arabidopsis. Front. Plant Sci. 2015, 6, 677. [Google Scholar] [CrossRef] [PubMed]
  120. Dobrenel, T.; Marchive, C.; Sormani, R.; Moreau, M.; Mozzo, M.; Montané, M.; Menand, B.; Robaglia, C.; Meyer, C. Regulation of plant growth and metabolism by the TOR kinase. Biochem. Soc. Trans. 2011, 39, 477–481. [Google Scholar] [CrossRef]
  121. Fu, L.; Wang, P.; Xiong, Y. Target of Rapamycin Signaling in Plant Stress Responses. Plant Physiol. 2020, 182, 1613–1623. [Google Scholar] [CrossRef] [PubMed]
  122. Ren, M.; Qiu, S.; Venglat, P.; Xiang, D.; Feng, L.; Selvaraj, G.; Datla, R. Target of Rapamycin Regulates Development and Ribosomal RNA Expression through Kinase Domain in Arabidopsis. Plant Physiol. 2011, 155, 1367–1382. [Google Scholar] [CrossRef] [PubMed]
  123. Kim, Y.-K.; Kim, S.; Shin, Y.-J.; Hur, Y.-S.; Kim, W.-Y.; Lee, M.-S.; Cheon, C.-I.; Verma, D.P.S. Ribosomal Protein S6, a Target of Rapamycin, Is Involved in the Regulation of rRNA Genes by Possible Epigenetic Changes in Arabidopsis. J. Biol. Chem. 2014, 289, 3901–3912. [Google Scholar] [CrossRef]
  124. Menand, B.; Desnos, T.; Nussaume, L.; Berger, F.; Bouchez, D.; Meyer, C.; Robaglia, C. Expression and disruption of the Arabidopsis TOR (target of rapamycin) gene. Proc. Natl. Acad. Sci. USA 2002, 99, 6422–6427. [Google Scholar] [CrossRef]
  125. Rodriguez, M.S.; Parola, R.; Andreola, S.; Pereyra, C.; Martínez-Noël, G. TOR and SnRK1 signaling pathways in plant response to abiotic stresses: Do they always act according to the “yin-yang” model? Plant Sci. 2019, 288, 110220. [Google Scholar] [CrossRef]
  126. Ren, M.; Venglat, P.; Qiu, S.; Feng, L.; Cao, Y.; Wang, E.; Xiang, D.; Wang, J.; Alexander, D.; Chalivendra, S.; et al. Target of Rapamycin Signaling Regulates Metabolism, Growth, and Life Span in Arabidopsis. Plant Cell 2013, 24, 4850–4874. [Google Scholar] [CrossRef]
  127. Urban, J.; Soulard, A.; Huber, A.; Lippman, S.; Mukhopadhyay, D.; Deloche, O.; Wanke, V.; Anrather, D.; Ammerer, G.; Riezman, H.; et al. Sch9 Is a Major Target of TORC1 in Saccharomyces cerevisiae. Mol. Cell 2007, 26, 663–674. [Google Scholar] [CrossRef] [PubMed]
  128. Hay, N.; Sonenberg, N. Upstream and Downstream of mTOR. Genes Dev. 2004, 18, 1926–1945. [Google Scholar] [CrossRef]
  129. Xiong, Y.; McCormack, M.P.; Li, L.; Hall, Q.; Xiang, C.; Sheen, J. Glucose–TOR signalling reprograms the transcriptome and activates meristems. Nature 2013, 496, 181–186. [Google Scholar] [CrossRef]
  130. Dobrenel, T.; Mancera-Martínez, E.; Forzani, C.; Azzopardi, M.; Davanture, M.; Moreau, M.; Schepetilnikov, M.; Chicher, J.; Langella, O.; Zivy, M.; et al. The Arabidopsis TOR Kinase Specifically Regulates the Expression of Nuclear Genes Coding for Plastidic Ribosomal Proteins and the Phosphorylation of the Cytosolic Ribosomal Protein S6. Front. Plant Sci. 2016, 7, 1611. [Google Scholar] [CrossRef]
  131. Bakshi, A.; Moin, M.; Madhav, M.S.; Gayatri, M.B.; Reddy, A.B.M.; Datla, R.; Kirti, P.B. Target of Rapamycin: Function in Abiotic Stress Tolerance in Arabidopsis and Its Involvement in a Possible Cross-Talk with Ribosomal Proteins. bioRxiv 2020. [Google Scholar] [CrossRef]
  132. Busche, M.; Scarpin, M.R.; Hnasko, R.; Brunkard, J.O. TOR coordinates nucleotide availability with ribosome biogenesis in plants. Plant Cell 2021, 33, 1615–1632. [Google Scholar] [CrossRef]
  133. Halford, N.G.; Hardie, G. SNF1-related protein kinases: Global regulators of carbon metabolism in plants? Plant Mol. Biol. 1998, 37, 735–748. [Google Scholar] [CrossRef]
  134. Hrabak, E.M.; Chan, C.W.; Gribskov, M.; Harper, J.F.; Choi, J.H.; Halford, N.G.; Kudla, J.; Luan, S.; Nimmo, H.; Sussman, M.R.; et al. The Arabidopsis CDPK-SnRK Superfamily of Protein Kinases. Plant Physiol. 2003, 132, 666–680. [Google Scholar] [CrossRef]
  135. Halford, N.G.; Hey, S.J. Snf1-related protein kinases (SnRKs) act within an intricate network that links metabolic and stress signalling in plants. Biochem. J. 2009, 419, 247–259. [Google Scholar] [CrossRef]
  136. Baena-González, E.; Hanson, J. Shaping plant development through the SnRK1–TOR metabolic regulators. Curr. Opin. Plant Biol. 2017, 35, 152–157. [Google Scholar] [CrossRef]
  137. Broeckx, T.; Hulsmans, S.; Rolland, F. The plant energy sensor: Evolutionary conservation and divergence of SnRK1 structure, regulation, and function. J. Exp. Bot. 2016, 67, 6215–6252. [Google Scholar] [CrossRef]
  138. Robaglia, C.; Thomas, M.; Meyer, C. Sensing nutrient and energy status by SnRK1 and TOR kinases. Curr. Opin. Plant Biol. 2012, 15, 301–307. [Google Scholar] [CrossRef]
  139. Wu, Y.; Shi, L.; Li, L.; Fu, L.; Liu, Y.; Xiong, Y.; Sheen, J. Integration of nutrient, energy, light, and hormone signalling via TOR in plants. J. Exp. Bot. 2019, 70, 2227–2238. [Google Scholar] [CrossRef]
  140. Schepetilnikov, M.; Ryabova, L.A. Recent Discoveries on the Role of TOR (Target of Rapamycin) Signaling in Translation in Plants. Plant Physiol. 2018, 176, 1095–1105. [Google Scholar] [CrossRef]
  141. Caldana, C.; Martins, M.C.M.; Mubeen, U.; Urrea-Castellanos, R. The magic ‘hammer’ of TOR: The multiple faces of a single pathway in the metabolic regulation of plant growth and development. J. Exp. Bot. 2019, 70, 2217–2225. [Google Scholar] [CrossRef]
  142. Pu, Y.; Soto-Burgos, J.; Bassham, D.C. Regulation of autophagy through SnRK1 and TOR signaling pathways. Plant Signal. Behav. 2017, 12, e1395128. [Google Scholar] [CrossRef]
  143. Nukarinen, E.; Nägele, T.; Pedrotti, L.; Wurzinger, B.; Mair, A.; Landgraf, R.; Börnke, F.; Hanson, J.; Teige, M.; Baena-González, E.; et al. Quantitative phosphoproteomics reveals the role of the AMPK plant ortholog SnRK1 as a metabolic master regulator under energy deprivation. Sci. Rep. 2016, 6, 31697. [Google Scholar] [CrossRef]
  144. Tomé, F.; Nã¤Gele, T.; Adamo, M.C.; Garg, A.; Marco-Llorca, C.; Nukarinen, E.; Pedrotti, L.; Peviani, A.; Simeunovic, A.; Tatkiewicz, A.; et al. The low energy signaling network. Front. Plant Sci. 2014, 5, 353. [Google Scholar] [CrossRef]
  145. Belda-Palazón, B.; Adamo, M.; Valerio, C.; Ferreira, L.J.; Confraria, A.; Reis-Barata, D.; Rodrigues, A.; Meyer, C.; Rodriguez, P.L.; Baena-González, E. A dual function of SnRK2 kinases in the regulation of SnRK1 and plant growth. Nat. Plants 2020, 6, 1345–1353. [Google Scholar] [CrossRef]
  146. Nakashima, K.; Yamaguchi-Shinozaki, K. ABA signaling in stress-response and seed development. Plant Cell Rep. 2013, 32, 959–970. [Google Scholar] [CrossRef]
  147. Todaka, D.; Shinozaki, K.; Yamaguchi-Shinozaki, K. Recent advances in the dissection of drought-stress regulatory networks and strategies for development of drought-tolerant transgenic rice plants. Front. Plant Sci. 2015, 6, 84. [Google Scholar] [CrossRef]
  148. Yoshida, T.; Fujita, Y.; Maruyama, K.; Mogami, J.; Todaka, D.; Shinozaki, K.; Yamaguchi-Shinozaki, K. Four Arabidopsis AREB/ABF transcription factors function predominantly in gene expression downstream of SnRK2 kinases in abscisic acid signalling in response to osmotic stress. Plant Cell Environ. 2015, 38, 35–49. [Google Scholar] [CrossRef]
  149. Fujii, H.; Zhu, J.-K. Arabidopsis mutant deficient in 3 abscisic acid-activated protein kinases reveals critical roles in growth, reproduction, and stress. Proc. Natl. Acad. Sci. USA 2009, 106, 8380–8385. [Google Scholar] [CrossRef]
  150. Kim, K.-N.; Lee, J.-S.; Han, H.; Choi, S.A.; Go, S.J.; Yoon, I.S. Isolation and characterization of a novel rice Ca2+-regulated protein kinase gene involved in responses to diverse signals including cold, light, cytokinins, sugars and salts. Plant Mol. Biol. 2003, 52, 1191–1202. [Google Scholar] [CrossRef] [PubMed]
  151. Nakashima, K.; Fujita, Y.; Kanamori, N.; Katagiri, T.; Umezawa, T.; Kidokoro, S.; Maruyama, K.; Yoshida, T.; Ishiyama, K.; Kobayashi, M.; et al. Three Arabidopsis SnRK2 Protein Kinases, SRK2D/SnRK2. 2, SRK2E/SnRK2. 6/OST1 and SRK2I/SnRK2. 3, Involved in ABA Signaling are Essential for the Control of Seed Development and Dormancy. Plant Cell Physiol. 2009, 50, 1345–1363. [Google Scholar] [CrossRef]
  152. Furihata, T.; Maruyama, K.; Fujita, Y.; Umezawa, T.; Yoshida, R.; Shinozaki, K.; Yamaguchi-Shinozaki, K. Abscisic acid-dependent multisite phosphorylation regulates the activity of a transcription activator AREB1. Proc. Natl. Acad. Sci. USA 2006, 103, 1988–1993. [Google Scholar] [CrossRef] [PubMed]
  153. Kobayashi, Y.; Murata, M.; Minami, H.; Yamamoto, S.; Kagaya, Y.; Hobo, T.; Yamamoto, A.; Hattori, T. Abscisic acid-activated SNRK2 protein kinases function in the gene-regulation pathway of ABA signal transduction by phosphorylating ABA response element-binding factors. Plant J. 2005, 44, 939–949. [Google Scholar] [CrossRef] [PubMed]
  154. Wang, C.; Liu, Y.; Li, S.-S.; Han, G.-Z. Insights into the Origin and Evolution of the Plant Hormone Signaling Machinery. Plant Physiol. 2015, 167, 872–886. [Google Scholar] [CrossRef] [PubMed]
  155. Lempiäinen, H.; Shore, D. Growth control and ribosome biogenesis. Curr. Opin. Cell Biol. 2009, 21, 855–863. [Google Scholar] [CrossRef] [PubMed]
  156. De Block, M.; Van Lijsebettens, M. Energy efficiency and energy homeostasis as genetic and epigenetic components of plant performance and crop productivity. Curr. Opin. Plant Biol. 2011, 14, 275–282. [Google Scholar] [CrossRef] [PubMed]
  157. Moin, M.; Bakshi, A.; Saha, A.; Kumar, M.U.; Reddy, A.R.; Rao, K.V.; Siddiq, E.A.; Kirti, P.B. Activation tagging in indica rice identifies ribosomal proteins as potential targets for manipulation of water-use efficiency and abiotic stress tolerance in plants: Activation Tagging Identifies Ribosomal Protein Genes. Plant Cell Environ. 2016, 39, 2440–2459. [Google Scholar] [CrossRef] [PubMed]
  158. Moin, M.; Bakshi, A.; Madhav, M.S.; Kirti, P.B. Expression Profiling of Ribosomal Protein Gene Family in Dehydration Stress Responses and Characterization of Transgenic Rice Plants Overexpressing RPL23A for Water-Use Efficiency and Tolerance to Drought and Salt Stresses. Front. Chem. 2017, 5, 97. [Google Scholar] [CrossRef]
  159. Saez-Vasquez, J.; Gallois, P.; Delseny, M. Accumulation and nuclear targeting of BnC24, a Brassica napus ribosomal protein corresponding to a mRNA accumulating in response to cold treatment. Plant Sci. 2000, 156, 35–46. [Google Scholar] [CrossRef]
  160. Moin, M.; Bakshi, A.; Saha, A.; Dutta, M.; Madhav, S.M.; Kirti, P.B. Rice Ribosomal Protein Large Subunit Genes and Their Spatio-temporal and Stress Regulation. Front. Plant Sci. 2016, 7, 1284. [Google Scholar] [CrossRef]
  161. Martinez-Seidel, F.; Suwanchaikasem, P.; Nie, S.; Leeming, M.G.; Firmino, A.A.P.; Williamson, N.A.; Kopka, J.; Roessner, U.; Boughton, B.A. Membrane-Enriched Proteomics Link Ribosome Accumulation and Proteome Reprogramming With Cold Acclimation in Barley Root Meristems. Front. Plant Sci. 2021, 12, 656683. [Google Scholar] [CrossRef]
  162. Martinez-Seidel, F.; Beine-Golovchuk, O.; Hsieh, Y.-C.; Eshraky, K.; Gorka, M.; Cheong, B.-E.; Jimenez-Posada, E.; Walther, D.; Skirycz, A.; Roessner, U.; et al. Spatially Enriched Paralog Rearrangements Argue Functionally Diverse Ribosomes Arise during Cold Acclimation in Arabidopsis. Int. J. Mol. Sci. 2021, 22, 6160. [Google Scholar] [CrossRef]
  163. Garcia-Molina, A.; Kleine, T.; Schneider, K.; Mühlhaus, T.; Lehmann, M.; Leister, D. Translational Components Contribute to Acclimation Responses to High Light, Heat, and Cold in Arabidopsis. iScience 2020, 23, 101331. [Google Scholar] [CrossRef]
  164. Vandereyken, K.; Van Leene, J.; De Coninck, B.; Cammue, B.P.A. Hub Protein Controversy: Taking a Closer Look at Plant Stress Response Hubs. Front. Plant Sci. 2018, 9, 694. [Google Scholar] [CrossRef]
  165. Palm, D.; Streit, D.; Shanmugam, T.; Weis, B.L.; Ruprecht, M.; Simm, S.; Schleiff, E. Plant-specific ribosome biogenesis factors in Arabidopsis thaliana with essential function in rRNA processing. Nucleic Acids Res. 2019, 47, 1880–1895. [Google Scholar] [CrossRef] [PubMed]
  166. Weis, B.L.; Palm, D.; Missbach, S.; Bohnsack, M.T.; Schleiff, E. atBRX1-1 and atBRX1-2 are involved in an alternative rRNA processing pathway in Arabidopsis thaliana. RNA 2015, 21, 415–425. [Google Scholar] [CrossRef] [PubMed]
  167. Golovchuk, O.B.; Firmino, A.A.P.; Dąbrowska, A.; Schmidt, S.; Erban, A.; Walther, D.; Zuther, E.; Hincha, D.K.; Kopka, J. Plant Temperature Acclimation and Growth Rely on Cytosolic Ribosome Biogenesis Factor Homologs. Plant Physiol. 2018, 176, 2251–2276. [Google Scholar] [CrossRef]
  168. Cheong, B.E.; Beine-Golovchuk, O.; Gorka, M.; Ho, W.W.H.; Martinez-Seidel, F.; Firmino, A.A.P.; Skirycz, A.; Roessner, U.; Kopka, J. Arabidopsis REI-LIKE proteins activate ribosome biogenesis during cold acclimation. Sci. Rep. 2021, 11, 2410. [Google Scholar] [CrossRef] [PubMed]
  169. Schmidt, S.; Dethloff, F.; Beine-Golovchuk, O.; Kopka, J. The REIL1 and REIL2 Proteins of Arabidopsis thaliana Are Required for Leaf Growth in the Cold. Plant Physiol. 2013, 163, 1623–1639. [Google Scholar] [CrossRef] [PubMed]
  170. Yu, H.; Kong, X.; Huang, H.; Wu, W.; Park, J.; Yun, D.-J.; Lee, B.-H.; Shi, H.; Zhu, J.-K. STCH4/REIL2 Confers Cold Stress Tolerance in Arabidopsis by Promoting rRNA Processing and CBF Protein Translation. Cell Rep. 2020, 30, 229–242.e5. [Google Scholar] [CrossRef]
  171. Klingauf-Nerurkar, P.; Gillet, L.C.; Portugal-Calisto, D.; Oborská-Oplová, M.; Jäger, M.; Schubert, O.T.; Pisano, A.; Peña, C.; Rao, S.; Altvater, M.; et al. The GTPase Nog1 co-ordinates the assembly, maturation and quality control of distant ribosomal functional centers. eLife 2020, 9, e52474. [Google Scholar] [CrossRef]
  172. Guo, J.; Han, S.; Zhao, J.; Xin, C.; Zheng, X.; Liu, Y.; Wang, Y.; Qu, F. Essential role of NbNOG1 in ribosomal RNA processing: NOG1 and Ribosomal RNA Processing in Plants. J. Integr. Plant Biol. 2018, 60, 1018–1022. [Google Scholar] [CrossRef]
  173. Lee, S.; Senthil-Kumar, M.; Kang, M.; Rojas, C.M.; Tang, Y.; Oh, S.; Choudhury, S.R.; Lee, H.-K.; Ishiga, Y.; Allen, R.D.; et al. The small GTPase, nucleolar GTP-binding protein 1 (NOG1), has a novel role in plant innate immunity. Sci. Rep. 2017, 7, 9260. [Google Scholar] [CrossRef]
  174. Lee, S.; Rojas, C.M.; Oh, S.; Kang, M.; Choudhury, S.R.; Lee, H.-K.; Allen, R.D.; Pandey, S.; Mysore, K.S. Nucleolar GTP-Binding Protein 1-2 (NOG1-2) Interacts with Jasmonate-ZIMDomain Protein 9 (JAZ9) to Regulate Stomatal Aperture during Plant Immunity. Int. J. Mol. Sci. 2018, 19, 1922. [Google Scholar] [CrossRef] [PubMed]
  175. Pant, B.D.; Lee, S.; Lee, H.-K.; Krom, N.; Pant, P.; Jang, Y.; Mysore, K.S. Overexpression of Arabidopsis nucleolar GTP-binding 1 (NOG1) proteins confers drought tolerance in rice. Plant Physiol. 2022, 189, 988–1004. [Google Scholar] [CrossRef] [PubMed]
  176. Manzano, A.; Villacampa, A.; Sáez-Vásquez, J.; Kiss, J.Z.; Medina, F.J.; Herranz, R. The Importance of Earth Reference Controls in Spaceflight -Omics Research: Characterization of Nucleolin Mutants from the Seedling Growth Experiments. iScience 2020, 23, 101686. [Google Scholar] [CrossRef] [PubMed]
  177. Mitchell, C.A. Bioregenerative life-support systems. Am. J. Clin. Nutr. 1994, 60, 820S–824S. [Google Scholar] [CrossRef] [PubMed]
  178. Sablok, G.; Powell, J.J.; Kazan, K. Emerging Roles and Landscape of Translating mRNAs in Plants. Front. Plant Sci. 2017, 8, 1443. [Google Scholar] [CrossRef] [PubMed]
  179. Chassé, H.; Boulben, S.; Costache, V.; Cormier, P.; Morales, J. Analysis of translation using polysome profiling. Nucleic Acids Res. 2017, 45, e15. [Google Scholar] [CrossRef]
  180. King, H.A.; Gerber, A.P. Translatome profiling: Methods for genome-scale analysis of mRNA translation. Brief. Funct. Genom. 2014, 15, 22–31. [Google Scholar] [CrossRef]
  181. Kage, U.; Powell, J.J.; Gardiner, D.M.; Kazan, K. Ribosome profiling in plants: What is not lost in translation? J. Exp. Bot. 2020, 71, 5323–5332. [Google Scholar] [CrossRef] [PubMed]
  182. Brar, G.A.; Weissman, J.S. Ribosome profiling reveals the what, when, where and how of protein synthesis. Nat. Rev. Mol. Cell Biol. 2015, 16, 651–664. [Google Scholar] [CrossRef]
  183. Branco-Price, C.; Kawaguchi, R.; Ferreira, R.B.; Bailey-Serres, J. Genome-wide Analysis of Transcript Abundance and Translation in Arabidopsis Seedlings Subjected to Oxygen Deprivation. Ann. Bot. 2005, 96, 647–660. [Google Scholar] [CrossRef] [PubMed]
  184. Branco-Price, C.; Kaiser, K.A.; Jang, C.J.H.; Larive, C.K.; Bailey-Serres, J. Selective mRNA translation coordinates energetic and metabolic adjustments to cellular oxygen deprivation and reoxygenation in Arabidopsis thaliana. Plant J. 2008, 56, 743–755. [Google Scholar] [CrossRef] [PubMed]
  185. Kawaguchi, R.; Girke, T.; Bray, E.A.; Bailey-Serres, J. Differential mRNA translation contributes to gene regulation under non-stress and dehydration stress conditions in Arabidopsis thaliana. Plant J. 2004, 38, 823–839. [Google Scholar] [CrossRef]
  186. Yang, X.; Song, B.; Cui, J.; Wang, L.; Wang, S.; Luo, L.; Gao, L.; Mo, B.; Yu, Y.; Liu, L. Comparative ribosome profiling reveals distinct translational landscapes of salt-sensitive and -tolerant rice. BMC Genom. 2021, 22, 612. [Google Scholar] [CrossRef]
  187. Matsuura, H.; Ishibashi, Y.; Shinmyo, A.; Kanaya, S.; Kato, K. Genome-Wide Analyses of Early Translational Responses to Elevated Temperature and High Salinity in Arabidopsis thaliana. Plant Cell Physiol. 2010, 51, 448–462. [Google Scholar] [CrossRef] [PubMed]
  188. Chen, Y.; Liu, M.; Dong, Z. Preferential Ribosome Loading on the Stress-Upregulated mRNA Pool Shapes the Selective Translation under Stress Conditions. Plants 2021, 10, 304. [Google Scholar] [CrossRef] [PubMed]
  189. Rasmussen, S.; Barah, P.; Suarez-Rodriguez, M.C.; Bressendorff, S.; Friis, P.; Costantino, P.; Bones, A.M.; Nielsen, H.B.; Mundy, J. Transcriptome responses to combinations of stresses in Arabidopsis thaliana. Plant Physiol. 2013, 161, 1783–1794. [Google Scholar] [CrossRef]
  190. Zhu, H.; Li, C.; Gao, C. Applications of CRISPR–Cas in agriculture and plant biotechnology. Nat. Rev. Mol. Cell Biol. 2020, 21, 661–677. [Google Scholar] [CrossRef] [PubMed]
  191. Jewett, M.C.; Fritz, B.R.; Timmerman, L.E.; Church, G.M. In vitro integration of ribosomal RNA synthesis, ribosome assembly, and translation. Mol. Syst. Biol. 2013, 9, 678. [Google Scholar] [CrossRef] [PubMed]
  192. Fritz, B.R.; Jewett, M.C. The impact of transcriptional tuning on in vitro integrated rRNA transcription and ribosome construction. Nucleic Acids Res. 2014, 42, 6774–6785. [Google Scholar] [CrossRef] [PubMed]
  193. Hammerling, M.; Fritz, B.R.; Yoesep, D.J.; Kim, D.S.; Carlson, E.D.; Jewett, M.C. In vitro ribosome synthesis and evolution through ribosome display. Nat. Commun. 2020, 11, 1108. [Google Scholar] [CrossRef] [PubMed]
Figure 1. The crosstalk between ribosome heterogeneity and abiotic stress response in plants (Figure created with BioRender.com, accessed on 25 July 2022).
Figure 1. The crosstalk between ribosome heterogeneity and abiotic stress response in plants (Figure created with BioRender.com, accessed on 25 July 2022).
Plants 11 02097 g001
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Dias-Fields, L.; Adamala, K.P. Engineering Ribosomes to Alleviate Abiotic Stress in Plants: A Perspective. Plants 2022, 11, 2097. https://doi.org/10.3390/plants11162097

AMA Style

Dias-Fields L, Adamala KP. Engineering Ribosomes to Alleviate Abiotic Stress in Plants: A Perspective. Plants. 2022; 11(16):2097. https://doi.org/10.3390/plants11162097

Chicago/Turabian Style

Dias-Fields, Leticia, and Katarzyna P. Adamala. 2022. "Engineering Ribosomes to Alleviate Abiotic Stress in Plants: A Perspective" Plants 11, no. 16: 2097. https://doi.org/10.3390/plants11162097

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop