Nitrogen Stress Conditions Research Articles

Carotenoid accumulation in aerial microalga Coelastrella rubescens KGU-H009 in light- and nitrogen-stress conditions

Some natural carotenoids remain unexplored in terms of their function because they occur only in trace amounts, or their stereochemistry is unclear. It is expected that scientists will discover new physiological activities that have a positive impact on human heath by analysis of such carotenoids. The purpose of this study was to analyze the carotenoids synthesized by the novel aerial microalga Coelastrella rubescens KGU–H009, and the dynamics of their accumulation. Cultivation experiments were conducted for 7 days at 25 °C, combining different light conditions with the presence or absence of nitrate ions. Short-term (2-h) cultivation was also performed, and tests were conducted with the addition of the inhibitor of photosynthesis 3-(3,4-dichlorophenyl)-1, 1-dimethylurea (DCMU). Strain KGU-H009 exhibited its highest carotenoid content (34.5 mg g−1) in the presence of nitrogen sources and strong light. Upon nitrogen source depletion, the content of zeaxanthin and β-carotene decreased, while the content of astaxanthin and adonixanthin increased. Strain KGU-H009 exhibited reversible control of the xanthophyll cycle to adapt to changes in light intensity, but the xanthophyll cycle was inhibited by the addition of DCMU. Strain KGU-H009 demonstrated the ability to synthesize carotenoids involved in both light harvesting and photoprotection, suggesting its adaptability to environmental change.

Effects of nitrogen starvation on growth and biochemical composition of some microalgae species.

Nitrogen is one of the most important nutrient sources for the growth of microalgae. We studied the effects of nitrogen starvation on the growth responses, biochemical composition, and fatty acid profile of Dunaliella tertiolecta, Phaeodactylum tricornutum, and Nannochloropsis oculata. The lack of nitrogen caused changes in carbohydrate, protein, lipid, and fatty acid composition in all examined microalgae. The carbohydrate content increased 59% in D. tertiolecta, while the lipid level increased 139% in P. tricornutum under nitrogen stress conditions compared to the control groups. Nitrogen starvation increased the oligosaccharide and polysaccharide contents of D. tertiolecta 4.1-fold and 3.6-fold, respectively. Furthermore, triacylglycerol (TAG) levels in N. oculata and P. tricornutum increased 2.3-fold and 7.4-fold, respectively. The dramatic increase in the amount of TAG is important for the use of these microalgae as raw materials in biodiesel. Nitrogen starvation increased the amounts of oligosaccharides and polysaccharides of D. tertiolecta, while increased eicosapentaenoic acid (EPA) in N. oculata and docosahexaenoic acid (DHA) content in P. tricornutum. The amount of polyunsaturated fatty acids (PUFAs), EPA, DHA, oligosaccharides, and polysaccharides in microalgal species can be increased without using the too costly nitrogen source in the culture conditions, which can reduce the most costly of living feeding.

Estimating Leaf Chlorophyll Content of Winter Wheat from UAV Multispectral Images Using Machine Learning Algorithms under Different Species, Growth Stages, and Nitrogen Stress Conditions

The rapid and accurate estimation of leaf chlorophyll content (LCC), an important indicator of crop photosynthetic capacity and nutritional status, is of great significance for precise nitrogen fertilization management. To explore the existence of a versatile regression model that can be successfully used to estimate the LCC for different varieties under different growth stages and nitrogen stress conditions, a study was conducted in 2023 across the growing season for winter wheat with five species and five nitrogen application levels. Two machine learning regression algorithms, support vector machine (SVM) and random forest (RF), were used to establish the bridge between UAV-derived multispectral vegetation indices and ground truth LCC (relative chlorophyll content, SPAD), taking the multivariate linear regression (MLR) algorithm as a reference. The results show that the visible atmospherically resistant index, vegetative index, and normalized difference vegetation index had the highest correlation with ground truth LCC, with a Pearson’s correlation coefficient of 0.95. All three regression algorithms (MLR, RF, and SVM) performed well on the training dataset (R2: 0.932–0.944, RMSE: 3.96 to 4.37), but performed differently on validation datasets with different growth stages, species, and nitrogen application levels. Compared to winter wheat species and nitrogen application levels, the growth stages had the greatest influence on the generalization ability of LCC estimation models, especially for the dough stage. At the dough stage, compared to MLR and RF, SVM performed best, with R2 increasing by 0.27 and 0.10, respectively, and RMSE decreasing by 1.13 and 0.46, respectively. Overall, this study demonstrated that the combination of UAV-derived multispectral VIs and the SVM regression algorithm could be successfully applied to map the LCC of winter wheat for different species, growth stages, and nitrogen stress conditions. Ultimately, this research is significant as it shows the successful application of UAV data for mapping the LCC of winter wheat across diverse conditions, offering valuable insights for precision nitrogen fertilization management.

ROS and Ca2+ signaling involved in important lipid changes of Chlorella pyrenoidosa under nitrogen stress conditions.

Nitrogen stress altered important lipid parameters and related genes in Chlorella pyrenoidosa via ROS and Ca2+ signaling. The mutual interference between ROS and Ca2+ signaling was also uncovered. The changed mechanisms of lipid parameters (especially lipid classes and unsaturation of fatty acids) in microalgae are not completely well known under nitrogen stress. Therefore, Chlorella pyrenoidosa was exposed to 0, 0.5, 1 and 1.5 g L-1 NaNO3 for 4 days. Then, the physiological and biochemical changes were measured. It was shown that the total lipid contents, neutral lipid ratios as well as their related genes (accD and DGAT) increased obviously while the polar lipid ratios, degrees of unsaturation as well as their related genes (PGP and desC) decreased significantly in nitrogen stress groups. The obvious correlations supported that gene expressions should be the necessary pathways to regulate the lipid changes in C. pyrenoidosa under nitrogen stress. The changes in ROS and Ca2+ signaling as well as their significant correlations with corresponding genes and lipid parameters were analyzed. The results suggested that ROS and Ca2+ may regulate these gene expressions and lipid changes in C. pyrenoidosa under nitrogen stress conditions. This was verified by the subordinate tests with an ROS inhibitor and calcium reagents. It also uncovered the clues of mutual interference between ROS and Ca2+ signaling. To summarize, this study revealed the signaling pathways of important lipid changes in microalgae under N stress.

Genomic organization and expression profiles of nitrogen assimilation genes in Glycine max

Background Glutamine synthetase (GS), glutamate synthase (GOGAT), and nitrate reductase (NR) are key enzymes involved in nitrogen assimilation and metabolism in plants. However, the systematic analysis of these gene families lacked reports in soybean (Glycine max (L.) Merr.), one of the most important crops worldwide. Methods In this study, we performed genome-wide identification and characterization of GS, GOGAT, and NR genes in soybean under abiotic and nitrogen stress conditions. Results We identified a total of 10 GS genes, six GOGAT genes, and four NR genes in the soybean genome. Phylogenetic analysis revealed the presence of multiple isoforms for each gene family, indicating their functional diversification. The distribution of these genes on soybean chromosomes was uneven, with segmental duplication events contributing to their expansion. Within the nitrogen assimilation genes (NAGs) group, there was uniformity in the exon-intron structure and the presence of conserved motifs in NAGs. Furthermore, analysis of cis-elements in NAG promoters indicated complex regulation of their expression. RT-qPCR analysis of seven soybean NAGs under various abiotic stresses, including nitrogen deficiency, drought-nitrogen, and salinity, revealed distinct regulatory patterns. Most NAGs exhibited up-regulation under nitrogen stress, while diverse expression patterns were observed under salt and drought-nitrogen stress, indicating their crucial role in nitrogen assimilation and abiotic stress tolerance. These findings offer valuable insights into the genomic organization and expression profiles of GS, GOGAT, and NR genes in soybean under nitrogen and abiotic stress conditions. The results have potential applications in the development of stress-resistant soybean varieties through genetic engineering and breeding.

Yield -based evaluation of low nitrogen tolerance indices for screening of [Sorghum bicolor (L.) Moench] genotypes

Nitrogen stress is one of the key factors limiting sorghum crop productivity. To identify desirable sorghum genotypes best suited to nitrogen stress, the response of 300 sorghum landraces and two standard checks: KS78, and BCK60 were evaluated using yield-based indices. The experiment was conducted under nitrogen stress and ideal conditions for two years using a split-plot in RCBD design with two replications. Nitrogen treatments were assigned to the main plots, and sorghum genotypes were assigned to the subplots. Fourteen nitrogen stress screening indices, namely, the yield stability index (YSI), stress tolerance index (STI), modified stress tolerance index (KSTI), low nitrogen tolerance index (LNTI), relative decrease in yield (RDY), tolerance index (TOL), yield index (YI), stress susceptibility index (SSI), stress susceptibility percentage index (SSPI), and harmonic mean (HM), were computed using grain yield. The yield under optimal and stress conditions was significantly positively correlated with the HM, MP, GMP, STI, HM, YI, and modified STI. The results from the cluster analysis, PCA biplot, and 3D biplot classified the genotypes into three groups: nitrogen stress tolerant, nitrogen stress susceptible, and poor performers under both environments. Using STI, GMP, and MP, Genotypes (G80) ETSL101255, (G216) ETSL101006, (G35) ETSL101258, (G146) ETSL100813, and genotypes (G244) ETSL100292, (G161) ETSL100539, (G240) ETSL100890, (G93) ETSL101845, (G261) ETSL100625, (G248) ETSL100874, (G258) ETSL100752, (G142) ETSL100921, (G135) ETSL100307 were identified as top nitrogen stress tolerant, and susceptible genotypes respectively. We conclude that the indices MP, GMP, and STI can help in improving sorghum yield by selecting nitrogen efficient genotypes.

Spatio-temporal coherence of circadian clocks and temporal control of differentiation in Anabaena filaments.

Circadian clock arrays in multicellular filaments of the heterocyst-forming cyanobacterium Anabaena sp. strain PCC 7120 display remarkable spatio-temporal coherence under nitrogen-replete conditions. To shed light on the interplay between circadian clocks and the formation of developmental patterns, we followed the expression of a clock-controlled gene under nitrogen deprivation, at the level of individual cells. Our experiments showed that differentiation into heterocysts took place preferentially within a limited interval of the circadian clock cycle, that gene expression in different vegetative intervals along a developed filament was discoordinated, and that the circadian clock was active in individual heterocysts. Furthermore, Anabaena mutants lacking the kaiABC genes encoding the circadian clock core components produced heterocysts but failed in diazotrophy. Therefore, genes related to some aspect of nitrogen fixation, rather than early or mid-heterocyst differentiation genes, are likely affected by the absence of the clock. A bioinformatics analysis supports the notion that RpaA may play a role as master regulator of clock outputs in Anabaena, the temporal control of differentiation by the circadian clock and the involvement of the clock in proper diazotrophic growth. Together, these results suggest that under nitrogen-deficient conditions, the clock coherent unit in Anabaena is reduced from a full filament under nitrogen-rich conditions to the vegetative cell interval between heterocysts.IMPORTANCECircadian clocks, from unicellular organisms to animals, temporally align biological processes to day and night cycles. We study the dynamics of a circadian clock-controlled gene at the individual cell level in the multicellular filamentous cyanobacterium Anabaena, under nitrogen-stress conditions. Under these conditions, some cells along filaments differentiate to carry out atmospheric nitrogen fixation and lose their capability for oxygenic photosynthesis. We found that clock synchronization is limited to organismic units of contiguous photosynthetic cells, contrary to nitrogen-replete conditions in which clocks are synchronized over a whole filament. We provided evidence that the circadian clock regulates the process of differentiation, allowing it to occur preferentially within a limited time window during the circadian clock period. Lastly, we present evidence that the signal from the core clock to clock-regulated genes is conveyed in Anabaena as in unicellular cyanobacteria.

Genome-wide dissection and haplotype analysis identified candidate loci for nitrogen use efficiency under drought conditions in winter wheat.

Climate change causes extreme conditions like prolonged drought, which results in yield reductions due to its effects on nutrient balances such as nitrogen uptake and utilization by plants. Nitrogen (N) is a crucial nutrient element for plant growth and productivity. Understanding the mechanistic basis of nitrogen use efficiency (NUE) under drought conditions is essential to improve wheat (Triticum aestivum L.) yield. Here, we evaluated the genetic variation of NUE-related traits and photosynthesis response in a diversity panel of 200 wheat genotypes under drought and nitrogen stress conditions to uncover the inherent genetic variation and identify quantitative trait loci (QTLs) underlying these traits. The results revealed significant genetic variations among the genotypes in response to drought stress and nitrogen deprivation. Drought impacted plant performance more than N deprivation due to its effect on water and nutrient uptake. GWAS identified a total of 27 QTLs with a significant main effect on the drought-related traits, while 10 QTLs were strongly associated with the NUE traits. Haplotype analysis revealed two different haplotype blocks within the associated region on chromosomes 1B and 5A. The two haplotypes showed contrasting effects on N uptake and use efficiency traits. The in silico and transcript analyses implicated candidate gene coding for cold shock protein. This gene was the most highly expressed gene under several stress conditions, including drought stress. Upon validation, these QTLs on 1B and 5A could be used as a diagnostic marker for NUE and drought tolerance screening in wheat.

Root-Knot-Nematode-Encoded CEPs Increase Nitrogen Assimilation.

C-terminally encoded peptides (CEPs) are plant developmental signals that regulate growth and adaptive responses to nitrogen stress conditions. These small signal peptides are common to all vascular plants, and intriguingly have been characterized in some plant parasitic nematodes. Here, we sought to discover the breadth of root-knot nematode (RKN)-encoded CEP-like peptides and define the potential roles of these signals in the plant-nematode interaction, focusing on peptide activity altering plant root phenotypes and nitrogen uptake and assimilation. A comprehensive bioinformatic screen identified 61 CEP-like sequences encoded within the genomes of six root-knot nematode (RKN; Meloidogyne spp.) species. Exogenous application of an RKN CEP-like peptide altered A. thaliana and M. truncatula root phenotypes including reduced lateral root number in M. truncatula and inhibited primary root length in A. thaliana. To define the role of RKN CEP-like peptides, we applied exogenous RKN CEP and demonstrated increases in plant nitrogen uptake through the upregulation of nitrate transporter gene expression in roots and increased 15N/14N in nematode-formed root galls. Further, we also identified enhanced nematode metabolic processes following CEP application. These results support a model of parasite-induced changes in host metabolism and inform endogenous pathways to regulate plant nitrogen assimilation.

Remodeling of the 3D chromatin architecture in the marine microalga Nannochloropsis oceanica during lipid accumulation

BackgroundGenomic three-dimensional (3D) spatial organization plays a key role in shaping gene expression and associated chromatin modification, and it is highly sensitive to environmental stress conditions. In microalgae, exposure to nitrogen stress can drive lipid accumulation, yet the associated functional alterations in the spatial organization of the microalgal genome have yet to be effectively characterized.ResultsAccordingly, the present study employed RNA-seq, Hi-C, and ChIP-seq approaches to explore the relationship between 3D chromosomal architecture and gene expression during lipid accumulation in the marine microalga Nannochloropsis oceanica in response to nitrogen deprivation (ND). These analyses revealed that ND resulted in various changes in chromosomal organization, including A/B compartment transitions, topologically associating domain (TAD) shifts, and the disruption of short-range interactions. Significantly higher levels of gene expression were evident in A compartments and TAD boundary regions relative to B compartments and TAD interior regions, consistent with observed histone modification enrichment in these areas. ND-induced differentially expressed genes (DEGs) were notably enriched in altered TAD-associated regions and regions exhibiting differential genomic contact. These DEGs were subjected to Gene Ontology (GO) term analyses that indicated they were enriched in the ‘fatty acid metabolism’, ‘response to stress’, ‘carbon fixation’ and ‘photosynthesis’ functional categories, in line with the ND treatment conditions used to conduct this study. These data indicate that Nannochloropsis cells exhibit a clear association between chromatin organization and transcriptional activity under nitrogen stress conditions. Pronounced and extensive histone modifications were evident in response to ND. Observed changes in chromatin architecture were linked to shifts in histone modifications and gene expression.ConclusionsOverall, the reprogramming of many lipid metabolism-associated genes was evident under nitrogen stress conditions with respect to both histone modifications and chromosomal organization. Together these results revealed that higher-order chromatin architecture represents a new layer that can guide efforts to understand the transcriptional regulation of lipid metabolism in nitrogen-deprived microalgae.

Biotechnological product potential of Auxenochlorella protothecoides including biologically active compounds (BACs) under nitrogen stress conditions.

Nitrogen stress can influence microalgae's growth characteristics, and microalgae grown in nitrogen-deficient conditions may produce higher or lower levels of biotechnological products as a result of metabolic changes. In photoautotrophic and heterotrophic cultures, nitrogen limitation has been proven effective in promoting lipid accumulation. In spite of this, no study has demonstrated a significant correlation between lipid content and other biotechnological products such as bioactive compounds (BACs).This research examines a strategy for lipid accumulation as well as the potential production of BACs with antibacterial properties in parallel with that strategy. This concept involved the treatment of the microalga Auxenochlorella protothecoides with low and high concentrations of ammonium (NH4+). This particular experiment reached a maximum lipid content of 59.5% using a 0.8 mM NH4+ concentration, resulting in the yellowing of the chlorophyll levels. Agar diffusion assays were conducted to determine the antibacterial activity of different extracts derived from the biomass when stressed with different levels of nitrogen.Algal extracts prepared by a variety of solvents showed different levels of antibacterial activity against representative strains of both gram-negative (Escherichia coli) and gram-positive (Staphylococcus aureus) bacteria. Among the extracts tested, 500mg/L ethyl acetate extract had the greatest antibacterial activity against Escherichia coli. In order to identify the components responsible for the extract's antibacterial activity, fatty acid methyl ester (FAME) analysis was performed. It has been suggested that the lipid fraction may be a valuable indicator of these activities since some lipid components are known to possess antimicrobial properties. In this regard, it was found that the amount of polyunsaturated fatty acid (PUFA) significantly decreased by 53.4% under the conditions with the highest antibacterial activity observed.

MANAGEMENT OF NITROGEN STRESS IN COTTON (Gossypium hirsutum L.) USING GREENSEEKER TECHNOLOGY

This study was performed with GreenSeeker technology in order to determine the possibility of nitrogen stress management in cotton and to determine the differences between the normalized difference vegetative index (NDVI) and nitrogen doses determined with GreenSeeker, to determine the nitrogen deficiency and stress conditions by making use of the value of the NDVI in cotton production and to intervene when necessary and direct the producers in this regard. In the study six nitrogen doses (Control, 60, 120, 180, 240 and 300 kg ha-1) were used. The results showed significant differences between N applications for leaf chlorophyll content (SPAD), NDVI-2 (in the boll formation period), number of bolls (NB), seed cotton (SCY) and fiber yield (FY). On the other hand, there were non-significant differences in terms of (LA) area, NDVI-1 (in the beginning of the flowering), plant height (PH), node number of first fruiting branches (NNFFB), number of monopodial branches (NMB) and number of sympodial branches (NSB), number of nodes (NN), height to node ratio (HNR), seed cotton boll weight (SCBW) and ginning percentage (GP). The highest SCY and FY obtained were from doses of 180 and 120 kg ha-1 N, the highest leaf chlorophyll content and number of bolls obtained were from doses of 120 kg ha-1 N. The highest values of NDVI-2 obtained were from doses of 120, 240 and 300 kg ha-1 N, respectively. There were non-significant differences between N doses for values of the NDVI-1 of flowering, but significant differences observed for values of NDVI-2 of boll formation periods. The findings obtained from this research indicated that leaf chlorophyll and NDVI of the boll formation period can be used for determining differences due to varying N doses in cotton production.

Genome-wide analysis of long non-coding RNAs (lncRNAs) in tea plants (Camellia sinensis) lateral roots in response to nitrogen application.

Tea (Camellia sinensis) is one of the significant cash crops in China. As a leaf crop, nitrogen supply can not only increase the number of new shoots and leaves but also improve the tenderness of the former. However, a conundrum remains in science, which is the molecular mechanism of nitrogen use efficiency, especially long non-coding RNA (lncRNA). In this study, a total of 16,452 lncRNAs were identified through high-throughput sequencing analysis of lateral roots under nitrogen stress and control conditions, of which 9,451 were differentially expressed lncRNAs (DE-lncRNAs). To figure out the potential function of nitrogen-responsive lncRNAs, co-expression clustering was employed between lncRNAs and coding genes. KEGG enrichment analysis revealed nitrogen-responsive lncRNAs may involve in many biological processes such as plant hormone signal transduction, nitrogen metabolism and protein processing in endoplasmic reticulum. The expression abundance of 12 DE-lncRNAs were further verified by RT-PCR, and their expression trends were consistent with the results of RNA-seq. This study expands the research on lncRNAs in tea plants, provides a novel perspective for the potential regulation of lncRNAs on nitrogen stress, and valuable resources for further improving the nitrogen use efficiency of tea plants.

Genetic analysis and heterotic grouping of quality protein maize (Zea mays L.) inbred lines and derived hybrids under conditions of low soil nitrogen and drought stress

Genetic analysis and heterotic grouping of quality protein maize (Zea mays L.) inbred lines and derived hybrids under conditions of low soil nitrogen and drought stress

A microfluidic droplet array demonstrating high-throughput screening in individual lipid-producing microalgae

Microalgae are a group of photoautotrophic microorganisms which could use carbon dioxide for autosynthesis. They have been envisioned as one of the most prospective feedstock for renewable oil. However, great endeavors will still be needed to increase their economic feasibility. The screening of competitive species and suitable culture conditions are such issues. To greatly accelerate these rather laborious steps and also improve their experimental lump-sum-manner, we developed a microfluidic droplet-based 2 × 103 resolution “identification card”, which allowed high throughput real-time monitoring of individual algae among population. A novel fluid-blocking-based droplet generating and trapping performance were integrated in the platform which made it excellent in operational simplicity, rapidity and stability and full of the potentials in single-cell-isolation/screening. The developed platform was successfully used to screen three unicellular algae, namely, Isochrysis zhanjiangensis, Platymonas subcordiformis and Platymonas helgolandica var. tsingtaoensis. In situ bioassays of the lipid accumulation and cell proliferation at single cell level for interspecies comparison were possible. Furthermore, lipid-producing inhomogeneity was demonstrated among cells in the same specie and batch. Nitrogen stress condition can be identified that induce positive-skewed frequency distribution of lipid content, even among individual inhomogeneous cells over the typically used culture condition.

Calibrating APSIM for forage sorghum using remote sensing and field data under sub-optimal growth conditions

CONTEXTMechanistic sorghum models have been mostly used to estimate sorghum yield for grain sorghum for a range of genotype, management, and environmental conditions. There is a lack of model testing for crop growth and development responses for forage genotypes and information for phenological parameterization under sub-optimal water and nitrogen stress conditions in forage systems. OBJETIVEThe aims of this study were to (i) use NDVI to parametrize APSIM model to estimate forage sorghum phenology, (ii) calibrate APSIM to simulate green cover, intercepted solar radiation and aboveground biomass, and (iii) quantify the variance of inter-annual aboveground biomass and the effect of water availability on forage sorghum biomass under sub-optimal environment × management combinations. METHODSWe used climate, soil, management records and sorghum crop observations collected from farm and field experiments in Argentina and Australia. NDVI values were gathered from Sentinel-2 and a handheld optical sensor and then related to fAPAR measurements. Phenological stages were derived from fAPAR seasonal dynamics and implemented as input in the APSIM calibration. Finally, we assessed the temporal AGB variability through long-term simulations analysis. RESULTS AND CONCLUSIONSNDVI seasonal dynamics accurately represented the fraction of the absorbed photosynthetically active radiation (R2=0.92) and then, the remote-sensing parametrized APSIM model satisfactorily simulated crop phenology (CCC=0.75-0.92, NRMSE=9-22%). The model was also able to satisfactorily simulate crop growth (CCC=0.89 and NRMSE=24.8% for green cover; CCC=0.81 and NRMSE=34.6% for intercepted solar radiation; CCC=0.91 and NRMSE=37% for aboveground biomass). APSIM simulations during 22 years across 5 contrasting locations showed high inter-annual variability of aboveground biomass (CV=47%), mainly driven by inter-annual variation of soil water availability (CV=20%). Our study demonstrated that (i) remote sensing data was a reliable source for APSIM phenology parametrization, (ii) the model was able to satisfactorily simulate crop growth and development of forage sorghum under sub-optimal conditions across several genotype × environment × management combinations and (iii) water availability was the main driver of aboveground biomass inter-annual variance. SIGNIFICANCEGiven the pressure of the global human population to satisfy an increasing demand for food, our results provide a new path for the combined use of remote sensing and mechanistic modelling to improve forage sorghum biomass estimations in marginal environments.

Genome-Wide Identification and Functional Characterization of the Chloride Channel TaCLC Gene Family in Wheat (Triticum aestivum L.).

In plants, chloride channels (CLC) are involved in a series of specific functions, such as regulation of nutrient transport and stress tolerance. Members of the wheat Triticum aestivum L. CLC (TaCLC) gene family have been proposed to encode anion channels/transporters that may be related to nitrogen transportation. To better understand their roles, TaCLC family was screened and 23 TaCLC gene sequences were identified using a Hidden Markov Model in conjunction with wheat genome database. Gene structure, chromosome location, conserved motif, and expression pattern of the resulting family members were then analyzed. Phylogenetic analysis showed that the TaCLC family can be divided into two subclasses (I and II) and seven clusters (-a, -c1, -c2, -e, -f1, -f2, and -g2). Using a wheat RNA-seq database, the expression pattern of TaCLC family members was determined to be an inducible expression type. In addition, seven genes from seven different clusters were selected for quantitative real-time PCR (qRT-PCR) analysis under low nitrogen stress or salt stress conditions, respectively. The results indicated that the gene expression levels of this family were up-regulated under low nitrogen stress and salt stress, except the genes of TaCLC-c2 cluster which were from subfamily -c. The yeast complementary experiments illustrated that TaCLC-a-6AS-1, TaCLC-c1-3AS, and TaCLC-e-3AL all had anion transport functions for NO3 − or Cl−, and compensated the hypersensitivity of yeast GEF1 mutant strain YJR040w (Δgef1) in restoring anion-sensitive phenotype. This study establishes a theoretical foundation for further functional characterization of TaCLC genes and provides an initial reference for better understanding nitrate nitrogen transportation in wheat.

Dissecting the metabolic reprogramming of maize root under nitrogen-deficient stress conditions.

The growth and development of maize (Zea mays L.) largely depends on its nutrient uptake through the root. Hence, studying its growth, response, and associated metabolic reprogramming to stress conditions is becoming an important research direction. A genome-scale metabolic model (GSM) for the maize root was developed to study its metabolic reprogramming under nitrogen stress conditions. The model was reconstructed based on the available information from KEGG, UniProt, and MaizeCyc. Transcriptomics data derived from the roots of hydroponically grown maize plants were used to incorporate regulatory constraints in the model and simulate nitrogen-non-limiting (N+) and nitrogen-deficient (N-) condition. Model-predicted flux-sum variability analysis achieved 70% accuracy compared with the experimental change of metabolite levels. In addition to predicting important metabolic reprogramming in central carbon, fatty acid, amino acid, and other secondary metabolism, maize root GSM predicted several metabolites (l-methionine, l-asparagine, l-lysine, cholesterol, and l-pipecolate) playing a regulatory role in the root biomass growth. Furthermore, this study revealed eight phosphatidylcholine and phosphatidylglycerol metabolites which, even though not coupled with biomass production, played a key role in the increased biomass production under N-deficient conditions. Overall, the omics-integrated GSM provides a promising tool to facilitate stress condition analysis for maize root and engineer better stress-tolerant maize genotypes.

Ancient Relatives of Modern Maize From the Center of Maize Domestication and Diversification Host Endophytic Bacteria That Confer Tolerance to Nitrogen Starvation.

Plants can adapt to their surroundings by hosting beneficial bacteria that confer a selective advantage in stressful conditions. Endophytes are a class of beneficial bacteria that exist within the internal spaces of plants and many species can improve plant nitrogen use efficiency. Nitrogen is an essential plant macronutrient, and is often a limiting factor to plant growth, especially in cereal crops such as maize. Every year farmers apply over 100 million metric tonnes of synthetic nitrogen fertilizer to meet the growing demand for stable food crops. Breeding efforts in maize over the past several decades has focused heavily on yield in response to nitrogen inputs, and so may have selected against adaptations that allow plants to survive in nitrogen stressed conditions. Data suggests that our heavy dependence on synthetic nitrogen fertilizer is not sustainable in the long term, and so there is on-going research efforts to reduce and replace this currently essential part of modern agriculture. Bacteria that improve plant tolerance to nitrogen stressed environments would allow farmers to reduce the amount of fertilizer they apply. The selection of maize under high nitrogen conditions to create modern varieties may have caused the plant to lose these beneficial bacteria that allowed wild maize ancestors to thrive in low nitrogen soil. Here in this study, we examine the root and shoot microbiomes of the wild ancestor of all maize, Parviglumis, and an ancient Mexican landrace (Mixteco) from Oaxaca, the area of early maize diversification. Both of these maize genotypes have thrived for thousands of years with little to no nitrogen inputs and so we hypothesized that they host beneficial bacteria that allow them to thrive in nitrogen stressed conditions. We identified multiple root endophyte species from each ancient maize relative that increased the growth of annual ryegrass (model maize relative) under nitrogen starvation. Furthermore, research infers these strains were vertically transmitted to new generations of plants, potentially through seed, indicating selection pressure for Parviglumis and Mixteco to maintain them in their microbiome.

Evaluation of biochar addition and circulation control strengthening measures on efficiency and microecology of food waste treatment in anaerobic reactor

The process of strengthening an expanded granular sludge blanket (EGSB) reactor under ammonia nitrogen stress conditions and by adopting three strengthening measures, namely, opening the circulation (OC), adding modified biochar (MB), adding modified biochar along with opening the circulation (MBOC), to treat food waste was studied. When the ammonia nitrogen concentration of influent increased to 1200 mg/L, the removal rate of COD reduced to about 75%, while the removal rate of ammonia nitrogen was about 6%. The average COD removal rate of the anaerobic reactor in the last 5 days of each operating cycle i.e. OC, MB and MBOC, was 85.51%, 84.11% and 90.03%, respectively. At the 30th day of each treatment-OC, MB and MBOC, the protease content in the sludge was 44.61, 42.47, 46.24 NH2–N (mg)/mg, respectively. and the content of coenzyme F420 was 0.244, 0.217 and 0.267 mmol/g, respectively. Proteobacteria was the most abundant phylum in the stage I (OC), reaching 34.36%. It was accounted for 16.68% and 21.38%, respectively, in the stage II (MB) and stage III (MBOC). The dominant archaea in the three stages were Methanosaeta, whose abundance was 38.98% in stage I, which increased to 64.94% and 64.01% in stage II and III, respectively. Among the active carbohydrate enzymes, the gene abundance of Glycoside transferases in the MBOC stage was the largest among the three stages.