Revisiting the chlorophyll biosynthesis pathway using genome scale metabolic model of Oryza sativa japonica

Elucidating the impact of in vitro cultivation on Nicotiana tabacum metabolism through combined in silico modeling and multiomics analysis

The systematical characterization and understanding of the metabolic behaviors are the basis of the efficient plant metabolic engineering and synthetic biology. Genome-scale metabolic networks (GSMNs) are indispensable tools for the comprehensive characterization of overall metabolic profile. Here we first constructed a GSMN of tobacco, which is one of the most widely used plant chassis, and then combined the tobacco GSMN and multiomics analysis to systematically elucidate the impact of in-vitro cultivation on the tobacco metabolic network. In-vitro cultivation is a widely used technique for plant cultivation, not only in the field of basic research but also for the rapid propagation of valuable horticultural and pharmaceutical plants. However, the systemic effects of in-vitro cultivation on overall plant metabolism could easily be overlooked and are still poorly understood. We found that in-vitro tobacco showed slower growth, less biomass and suppressed photosynthesis than soil-grown tobacco. Many changes of metabolites and metabolic pathways between in-vitro and soil-grown tobacco plants were identified, which notably revealed a significant increase of the amino acids content under in-vitro condition. The in silico investigation showed that in-vitro tobacco downregulated photosynthesis and primary carbon metabolism, while significantly upregulated the GS/GOGAT cycle, as well as producing more energy and less NADH/NADPH to acclimate in-vitro growth demands. Altogether, the combination of experimental and in silico analyses offers an unprecedented view of tobacco metabolism, with valuable insights into the impact of in-vitro cultivation, enabling more efficient utilization of in-vitro techniques for plant propagation and metabolic engineering.

Transcriptomics and Genomics Analysis Uncover the Differentially Expressed Chlorophyll and Carotenoid-Related Genes in Celery

Celery (Apium graveolens L.), a plant from Apiaceae, is one of the most important vegetables and is grown worldwide. Carotenoids can capture light energy and transfer it to chlorophyll, which plays a central role in photosynthesis. Here, by performing transcriptomics and genomics analysis, we identified and conducted a comprehensive analysis of chlorophyll and carotenoid-related genes in celery and six representative species. Significantly, different contents and gene expression patterns were found among three celery varieties. In total, 237 and 290 chlorophyll and carotenoid-related genes were identified in seven species. No notable gene expansion of chlorophyll biosynthesis was detected in examined species. However, the gene encoding ζ-carotene desaturase (ZDS) enzyme in carotenoid was expanded in celery. Comparative genomics and RNA-seq analyses revealed 16 and 5 key genes, respectively, regulating chlorophyll and carotenoid. An intriguing finding is that chlorophyll and carotenoid-related genes were coordinately regulated by transcriptional factors, which could be distinctively classified into positive- and negative-regulation groups. Six CONSTANS (CO)-like transcription factors co-regulated chlorophyll and carotenoid-related genes were identified in celery. In conclusion, this study provides new insights into the regulation of chlorophyll and carotenoid by transcription factors.

Elucidating Plant-Microbe-Environment Interactions Through Omics-Enabled Metabolic Modelling Using Synthetic Communities

With a growing world population and increasing frequency of climate disturbance events, we are in dire need of methods to improve plant productivity, resilience, and resistance to both abiotic and biotic stressors, both for agriculture and conservation efforts. Microorganisms play an essential role in supporting plant growth, environmental response, and susceptibility to disease. However, understanding the specific mechanisms by which microbes interact with each other and with plants to influence plant phenotypes is a major challenge due to the complexity of natural communities, simultaneous competition and cooperation effects, signalling interactions, and environmental impacts. Synthetic communities are a major asset in reducing the complexity of these systems by simplifying to dominant components and isolating specific variables for controlled experiments, yet there still remains a large gap in our understanding of plant microbiome interactions. This perspectives article presents a brief review discussing ways in which metabolic modelling can be used in combination with synthetic communities to continue progress toward understanding the complexity of plant-microbe-environment interactions. We highlight the utility of metabolic models as applied to a community setting, identify different applications for both flux balance and elementary flux mode simulation approaches, emphasize the importance of ecological theory in guiding data interpretation, and provide ideas for how the integration of metabolic modelling techniques with big data may bridge the gap between simplified synthetic communities and the complexity of natural plant-microbe systems.

Comparative analysis morphology, anatomical structure and transcriptional regulatory network of chlorophyll biosynthesis in Oryza longistaminata, O. sativa and their F1 generation

Oryza longistaminata, a perennial wild species, is widely distributed in the African continent. It has strong tolerance to biotic and abiotic stresses, and high biomass production on poor soils. Chlorophyll biosynthesis is important for photosynthesis in rice. However, the chlorophyll biosynthesis and related gene profiles of O. longistaminata and its descendants remained unclear. Here, the F₁ generation of O. sativa and O. longistaminata were obtained. Then, the comparative analysis morphology, anatomical structure, and transcriptional regulatory networks of chlorophyll biosynthesis were detected and analyzed. Results showed that the F₁ generation has obvious long awn, similar with that of the male parent. The purple color of the long awn is different from that of the male parent. Microstructural results showed that the flag leaves of F₁ have large mesophyll cell gaps in the upper- and lower-positions, small mesophyll cell gaps in the middle position, and more chloroplasts. Increased chlorophyll content was also observed in the F₁ generation. In the lower-position flag leaves, the total chlorophyll contents of F₁ were 1.55 and 1.5 times those of O. sativa and O. longistaminata, respectively. POR, MgCH and HEMA1 showed higher expression levels than the other related genes selected in the chlorophyll biosynthesis pathway. The HEMA1 expression level in the middle-position flag leaves of O. longistaminata was the highest, and it was 2.83 and 2.51 times that of O. sativa and F₁, respectively. The expression level of DVR gene in lower-position flag leaves of F₁ were 93.16% and 95.06% lower than those of O. sativa and O. longistaminata, respectively. This study provided a potential reference for studying the photosynthesis and heterosis utilization of O. longistaminata.

Characterization of effects of genetic variants via genome-scale metabolic modelling

Genome-scale metabolic networks for model plants and crops in combination with approaches from the constraint-based modelling framework have been used to predict metabolic traits and design metabolic engineering strategies for their manipulation. With the advances in technologies to generate large-scale genotyping data from natural diversity panels and other populations, genome-wide association and genomic selection have emerged as statistical approaches to determine genetic variants associated with and predictive of traits. Here, we review recent advances in constraint-based approaches that integrate genetic variants in genome-scale metabolic models to characterize their effects on reaction fluxes. Since some of these approaches have been applied in organisms other than plants, we provide a critical assessment of their applicability particularly in crops. In addition, we further dissect the inferred effects of genetic variants with respect to reaction rate constants, abundances of enzymes, and concentrations of metabolites, as main determinants of reaction fluxes and relate them with their combined effects on complex traits, like growth. Through this systematic review, we also provide a roadmap for future research to increase the predictive power of statistical approaches by coupling them with mechanistic models of metabolism.

Biotechnological strategies for enhancing heavy metal tolerance in neglected and underutilized legume crops: A comprehensive review

Contamination of agricultural land and water by heavy metals due to rapid industrialization and urbanization including various natural processes have become one of the major constraints to crop growth and productivity. Several studies have reported that to counteract heavy metal stress, plants should be able to maneuver various physiological, biochemical and molecular processes to improve their growth and development under heavy metal stress. With the advent of modern biotechnological tools and techniques it is now possible to tailor legume and other plants overexpressing stress-induced genes, transcription factors, proteins, and metabolites that are directly involved in heavy metal stress tolerance. This review provides an in-depth overview of various biotechnological approaches and/or strategies that can be used for enhancing detoxification of the heavy metals by stimulating phytoremediation processes. Synthetic biology tools involved in the engineering of legume and other crop plants against heavy metal stress tolerance are also discussed herewith some pioneering examples where synthetic biology tools that have been used to modify plants for specific traits. Also, CRISPR based genetic engineering of plants, including their role in modulating the expression of several genes/ transcription factors in the improvement of abiotic stress tolerance and phytoremediation ability using knockdown and knockout strategies has also been critically discussed.

Deciphering rice metabolic flux reprograming under salinity stress via in silico metabolic modeling

Rice is one of the most economically important commodities globally. However, rice plants are salt susceptible species in which high salinity can significantly constrain its productivity. Several physiological parameters in adaptation to salt stress have been observed, though changes in metabolic aspects remain to be elucidated. In this study, rice metabolic activities of salt-stressed flag leaf were systematically characterized. Transcriptomics and metabolomics data were combined to identify disturbed pathways, altered metabolites and metabolic hotspots within the rice metabolic network under salt stress condition. Besides, the feasible flux solutions in different context-specific metabolic networks were estimated and compared. Our findings highlighted metabolic reprogramming in primary metabolic pathways, cellular respiration, antioxidant biosynthetic pathways, and phytohormone biosynthetic pathways. Photosynthesis and hexose utilization were among the major disturbed pathways in the stressed flag leaf. Notably, the increased flux distribution of the photorespiratory pathway could contribute to cellular redox control. Predicted flux statuses in several pathways were consistent with the results from transcriptomics, end-point metabolomics, and physiological studies. Our study illustrated that the contextualized genome-scale model together with multi-omics analysis is a powerful approach to unravel the metabolic responses of rice to salinity stress.

Dark/Light Treatments Followed by γ-Irradiation Increase the Frequency of Leaf-Color Mutants in Cymbidium

Radiation randomly induces chromosomal mutations in plants. However, it was recently found that the frequency of flower-color mutants could be specifically increased by upregulating anthocyanin pathway gene expression before radiation treatments. The mechanisms of chlorophyll biosynthesis and degradation are active areas of plant study because chlorophyll metabolism is closely connected to photosynthesis. In this study, we determined the dark/light treatment conditions that resulted in upregulation of the expression levels of six chlorophyll pathway genes, uroporphyrinogen III synthase (HEMD), uroporphyrinogen III decarboxylase (HEME2), NADPH-protochlorophyllide oxidoreductase (POR) A (PORA), chlorophyll synthase (CHLG), chlorophyllase (CLH2), and red chlorophyll catabolite reductase (RCCR), and measured their effects on the γ-irradiation-induced frequencies of leaf-color mutants in two Cymbidium cultivars. To degrade chlorophyll in rhizomes, 60–75 days of dark treatment were required. To upregulate the expressions of chlorophyll pathway genes, 10 days of light treatment appeared to be optimal. Dark/light treatments followed by γ-irradiation increased chlorophyll-related leaf mutants by 1.4- to 2.0-fold compared with γ-ray treatment alone. Dark/light treatments combined with γ-irradiation increased the frequency of leaf-color mutants in Cymbidium, which supports the wider implementation of a plant breeding methodology that increases the mutation frequency of a target trait by controlling the expression of target trait-related genes.

Transcriptome analysis of shade avoidance and shade tolerance in conifers

Gymnosperms respond differently to light intensity and R:FR; although some aspects of shade response appear conserved, yet underlying mechanisms seem to be diverse in gymnosperms as compared to angiosperms. Shade avoidance syndrome (SAS) is well-characterized in the shade intolerant model species Arabidopsis thaliana whereas much less is known about shade tolerance response (STR), yet regulation of SAS and STR with reference to conifers remains poorly understood. We conducted a comparative study of two conifer species with contrasting responses to shade, Scots pine (shade-intolerant) and Norway spruce (shade-tolerant), with the aim to understand mechanisms behind SAS and STR in conifers. Pine and spruce seedlings were grown under controlled light and shade conditions, and hypocotyl and seedling elongation following different light treatments were determined in both species as indicators of shade responses. Red to far-red light ratio (R:FR) was shown to trigger the shade response in Norway spruce. In Scots pine, we observed an interaction between R:FR and light intensity. RNA sequencing (RNA-Seq) data revealed that SAS and STR responses included changes in expression of genes involved primarily in hormone signalling and pigment biosynthesis. From the RNA-Seq analysis, we propose that although some aspects of shade response appear to be conserved in angiosperms and gymnosperms, yet the underlying mechanisms may be different in gymnosperms that warrants further research.

Nuclear genome sequence of the plastid-lacking cryptomonad Goniomonas avonlea provides insights into the evolution of secondary plastids

Background

The evolution of photosynthesis has been a major driver in eukaryotic diversification. Eukaryotes have acquired plastids (chloroplasts) either directly via the engulfment and integration of a photosynthetic cyanobacterium (primary endosymbiosis) or indirectly by engulfing a photosynthetic eukaryote (secondary or tertiary endosymbiosis). The timing and frequency of secondary endosymbiosis during eukaryotic evolution is currently unclear but may be resolved in part by studying cryptomonads, a group of single-celled eukaryotes comprised of both photosynthetic and non-photosynthetic species. While cryptomonads such as Guillardia theta harbor a red algal-derived plastid of secondary endosymbiotic origin, members of the sister group Goniomonadea lack plastids. Here, we present the genome of Goniomonas avonlea—the first for any goniomonad—to address whether Goniomonadea are ancestrally non-photosynthetic or whether they lost a plastid secondarily.

Results

We sequenced the nuclear and mitochondrial genomes of Goniomonas avonlea and carried out a comparative analysis of Go. avonlea, Gu. theta, and other cryptomonads. The Go. avonlea genome assembly is ~ 92 Mbp in size, with 33,470 predicted protein-coding genes. Interestingly, some metabolic pathways (e.g., fatty acid biosynthesis) predicted to occur in the plastid and periplastidal compartment of Gu. theta appear to operate in the cytoplasm of Go. avonlea, suggesting that metabolic redundancies were generated during the course of secondary plastid integration. Other cytosolic pathways found in Go. avonlea are not found in Gu. theta, suggesting secondary loss in Gu. theta and other plastid-bearing cryptomonads. Phylogenetic analyses revealed no evidence for algal endosymbiont-derived genes in the Go. avonlea genome. Phylogenomic analyses point to a specific relationship between Cryptista (to which cryptomonads belong) and Archaeplastida.

Conclusion

We found no convincing genomic or phylogenomic evidence that Go. avonlea evolved from a secondary red algal plastid-bearing ancestor, consistent with goniomonads being ancestrally non-photosynthetic eukaryotes. The Go. avonlea genome sheds light on the physiology of heterotrophic cryptomonads and serves as an important reference point for studying the metabolic “rewiring” that took place during secondary plastid integration in the ancestor of modern-day Cryptophyceae.

Electronic supplementary material

The online version of this article (10.1186/s12915-018-0593-5) contains supplementary material, which is available to authorized users.

Reconstruction of Oryza sativa indica Genome Scale Metabolic Model and Its Responses to Varying RuBisCO Activity, Light Intensity, and Enzymatic Cost Conditions

To combat decrease in rice productivity under different stresses, an understanding of rice metabolism is needed. Though there are different genome scale metabolic models (GSMs) of Oryza sativa japonica, no GSM with gene-protein-reaction association exist for Oryza sativa indica. Here, we report a GSM, OSI1136 of O.s. indica, which includes 3602 genes and 1136 metabolic reactions and transporters distributed across the cytosol, mitochondrion, peroxisome, and chloroplast compartments. Flux balance analysis of the model showed that for varying RuBisCO activity (Vc/Vo) (i) the activity of the chloroplastic malate valve increases to transport reducing equivalents out of the chloroplast under increased photorespiratory conditions and (ii) glyceraldehyde-3-phosphate dehydrogenase and phosphoglycerate kinase can act as source of cytosolic ATP under decreased photorespiration. Under increasing light conditions we observed metabolic flexibility, involving photorespiration, chloroplastic triose phosphate and the dicarboxylate transporters of the chloroplast and mitochondrion for redox and ATP exchanges across the intracellular compartments. Simulations under different enzymatic cost conditions revealed (i) participation of peroxisomal glutathione-ascorbate cycle in photorespiratory H2O2 metabolism (ii) different modes of the chloroplastic triose phosphate transporters and malate valve, and (iii) two possible modes of chloroplastic Glu-Gln transporter which were related with the activity of chloroplastic and cytosolic isoforms of glutamine synthetase. Altogether, our results provide new insights into plant metabolism.

Antioxidant Responses Induced by UVB Radiation in Deschampsia antarctica Desv

Deschampsia antarctica Desv. is one of two vascular plants that live in the Maritime Antarctic Territory and is exposed to high levels of ultraviolet-B (UVB) radiation. In this work, antioxidant physiology of D. antarctica was studied in response to UVB induced oxidative changes. Samples were collected from Antarctica and maintained in vitro culture during 2 years. Plants were sub-cultured in a hydroponic system and exposed to 21.4 kJ m^-2 day^-1, emulating summer Antarctic conditions. Results showed rapid and significant increases in reactive oxygen species (ROS) at 3 h, which rapidly decreased. No dramatic changes were observed in photosynthetic efficiency, chlorophyll content, and level of thiobarbituric acid reactive species (MDA). The enzymatic (superoxide dismutase, SOD and total peroxidases, POD) and non-enzymatic antioxidant activity (total phenolic) increased significantly in response to UVB treatment. These findings suggest that tolerance of D. antarctica to UVB radiation could be attributed to its ability to activate both enzymatic and non-enzymatic antioxidant systems.

Modeling Rice Metabolism: From Elucidating Environmental Effects on Cellular Phenotype to Guiding Crop Improvement

Crop productivity is severely limited by various biotic and abiotic stresses. Thus, it is highly needed to understand the underlying mechanisms of environmental stress response and tolerance in plants, which could be addressed by systems biology approach. To this end, high-throughput omics profiling and in silico modeling can be considered to explore the environmental effects on phenotypic states and metabolic behaviors of rice crops at the systems level. Especially, the advent of constraint-based metabolic reconstruction and analysis paves a way to characterize the plant cellular physiology under various stresses by combining the mathematical network models with multi-omics data. Rice metabolic networks have been reconstructed since 2013 and currently six such networks are available, where five are at genome-scale. Since their publication, these models have been utilized to systematically elucidate the rice abiotic stress responses and identify agronomic traits for crop improvement. In this review, we summarize the current status of the existing rice metabolic networks and models with their applications. Furthermore, we also highlight future directions of rice modeling studies, particularly stressing how these models can be used to contextualize the affluent multi-omics data that are readily available in the public domain. Overall, we envisage a number of studies in the future, exploiting the available metabolic models to enhance the yield and quality of rice and other food crops.