Exploring the Relationship between Crassulacean Acid Metabolism (CAM) and Mineral Nutrition with a Special Focus on Nitrogen

The Nitrogen Preference of Cactus Pear (Opuntia ficus-indica): A Sand Culture Snapshot

Cactus pear (Opuntia-ficus indica (L.) Mill.) is an important agricultural crassulacean acid metabolism (CAM) species used as a source of food, forage, fodder, and secondary products and as a biofuel feedstock. However, the preferred source of nitrogen for this species, whether it be nitrate (NO3-), ammonium (NH4+), or a combination of both, is not well understood. To investigate the nitrate and ammonium preference of cactus pear, we grew cladodes in sand culture with deionized water as a control or with a cross-factorial set of nutrient solutions of 0.0, 2.5, 5.0, and 10.0 mmol of nitrate and/or ammonium for one month. We then assessed a set of physiological parameters including cladode growth, relative water content, chlorophyll, tissue acidity, soluble sugars, starch, nitrate, ammonium, glyoxylic acid, nitrate reductase activity, and nitrogen and carbon content. We found significant differences in all measured parameters except for cladode length, relative water content, and carbon content. Cladodes provided with only deionized water produced no new cladodes and showed decreased soluble sugar content, increased starch content, and increased tissue acidity. We also determined the relative steady-state transcript abundance of genes that encode enzymes involved in N metabolism and CAM. Compared with control cladodes, nutrient-supplied cladodes generally showed increased or variable steady-state mRNA expression of selected CAM-related genes and nitrogen-metabolism-related genes. Our results suggest that O. ficus-indica prefers fertilizers containing either equal concentrations nitrate and ammonium or more nitrate than ammonium.

Evaluation of succulent plants Echeveria elegans as a biomonitor of heavy metals and radionuclides

This work evaluates the use of Echeveria elegans as a biomonitor of metals and radionuclides, using semi-urban soils as a study area. The study area is exposed to various trace elements of concern for various social groups in nearby localities. The quantification of metals and radionuclides was performed by X-ray fluorescence spectrometry and gamma spectrometry, respectively. Cumulative frequency distribution curves, descriptive statistics, and multivariate analysis were used to estimate the local geochemical baseline and identify geochemical and anthropogenic patterns of metals and radionuclides from topsoil and E. elegans. The evaluation of contaminants and the contribution of possible exposure routes (topsoil and atmospheric deposition) was performed with the enrichment factor (EF) and the relative concentration factor (CFR). The results suggest that the plant does not present significant physical stress due to the environmental conditions to which it was exposed. Likewise, it can bioaccumulate heavy metals from natural and anthropogenic sources. The quantification of radionuclides in the plant is below the detection limits, indicating a low bioavailability and transfer factor. The CFR and EF results showed that the plant accumulates metals from the topsoil and atmospheric deposition. The bioaccumulation mechanism would be related to the functioning of Crassulaceae Acid Metabolism (CAM). In topsoil, the organic acids of the plant would modify the solubility of the metals present in an insoluble form in the soil, acting as ligands and, subsequently, following the transport route of these metabolites. In atmospheric deposition, the metals deposited in the leaves would be incorporated into the plant through the opening of the stomata because of the capture of CO2 (at night, day, or during environmental stress) by the CAM. Overall, the evidence showed that the succulent can be used as a biomonitor of heavy metals. However, additional studies are required to determine its usefulness as a radionuclide biomonitor.

The Calvin-Benson-Bassham cycle in C4 and Crassulacean acid metabolism species

The Calvin-Benson-Bassham (CBB) cycle is the ancestral CO2 assimilation pathway and is found in all photosynthetic organisms. Biochemical extensions to the CBB cycle have evolved that allow the resulting pathways to act as CO2 concentrating mechanisms, either spatially in the case of C4 photosynthesis or temporally in the case of Crassulacean acid metabolism (CAM). While the biochemical steps in the C4 and CAM pathways are known, questions remain on their integration and regulation with CBB cycle activity. The application of omic and transgenic technologies is providing a more complete understanding of the biochemistry of C4 and CAM species and will also provide insight into the CBB cycle in these plants. As the global population increases, new solutions are required to increase crop yields and meet demands for food and other bioproducts. Previous work in C3 species has shown that increasing carbon assimilation through genetic manipulation of the CBB cycle can increase biomass and yield. There may also be options to improve photosynthesis in species using C4 photosynthesis and CAM through manipulation of the CBB cycle in these plants. This is an underexplored strategy and requires more basic knowledge of CBB cycle operation in these species to enable approaches for increased productivity.

Growth and nitrogen metabolism in Sophora japonica (L.) as affected by salinity under different nitrogen forms

Sophora japonica is a leguminous tree species native to China. To explore the nitrogen (N) source preference and its impact on stress tolerance, a hydroponic experiment was designed in which S. japonica seedlings were supplied with sole ammonium (NH₄⁺) or sole nitrate (NO₃^-) nutrition under 75 mM NaCl-induced salt stress. The growth and N metabolism performance were investigated. In the absence of NaCl, plants fed NH₄⁺ showed better root growth than those fed NO₃^-, but there was no difference in aerial part growth. Salinity inhibited the root growth of NH₄⁺-fed plants and the shoot growth of NO₃^--fed plants, while the total N accumulation was suppressed under either N form. Specifically, in NH₄⁺-fed plants, salinity significantly increased the net photosynthetic rate, root NH₄⁺ content and root antioxidant enzyme activities. Higher nitrate reductase (NR) activities but lower glutamate synthetase (GS) activities were observed in both leaves and roots. Leaf AMT1.1 and AMT2.1a in NH₄⁺-fed plants positively reacted to salt stress, whereas the expression of four AMTs was reduced or remained unchanged in roots. In contrast, salinity suppressed the net photosynthetic rate, antioxidant enzyme activities, and GS activity in the leaves of NO₃^--fed plants. Upregulation of NPF1.2, NPF2.11, NPF4.6 and NPF7.3, as well as unaltered NR activity, caused higher NO₃^- content in the leaves. Moreover, NR and glutamate synthase (GOGAT) activities together with the transcription of most NRTs were promoted by salinity in the roots of NO₃^--fed plants. Additionally, compared to those treated with NH₄⁺, in response to salinity, NO₃^--treated seedlings showed more intensive repression of the net photosynthetic rate, chlorophyll content, and both shoot and root growth. Overall, these results suggest that S. japonica plants grew better in NH₄⁺ medium than in NO₃^- medium, and the different N metabolism responses improved S. japonica tolerance to salinity with NH₄⁺ application. This study provides new insights for understanding the mechanism of salt tolerance, breeding resistant varieties of S. japonica, and developing scientific fertilization management strategies during the seedling cultivation period.

Comparative analyses of the metabolite and ion concentrations in nectar, nectaries, and leaves of 36 bromeliads with different photosynthesis and pollinator types

Floral nectar contains mainly sugars as well as smaller amounts of amino acids and further compounds. The nectar composition varies between different plant species and it is related to the pollination type of the plant. In addition to this, other factors can influence the composition. Nectar is produced in and secreted from nectaries. A few models exist to explain the origin of nectar for dicotyl plant species, a complete elucidation of the processes, however, has not yet been achieved. This is particularly true for monocots or plant species with CAM photosynthesis. To get closer to such an elucidation, nectar, nectaries, and leaves of 36 bromeliad species were analyzed for sugars, starch, amino acids, and inorganic ions. The species studied include different photosynthesis types (CAM/C3), different pollination types (trochilophilous/chiropterophilous), or different live forms. The main sugars in nectar and nectaries were glucose, fructose, and sucrose, the total sugar concentration was about twofold higher in nectar than in nectaries, which suggests that sugars are actively transported from the nectaries into the nectar. The composition of amino acids in nectar is already determined in the nectaries, but the concentration is much lower in nectar than in nectaries, which suggests selective retention of amino acids during nectar secretion. The same applies to inorganic ions. Statistical analyses showed that the photosynthesis type and the pollination type can explain more data variation in nectar than in nectaries and leaves. Furthermore, the pollinator type has a stronger influence on the nectar or nectary composition than the photosynthesis type. Trochilophilous C3 plants showed significant correlations between the nitrate concentration in leaves and the amino acid concentration in nectaries and nectar. It can be assumed that the more nitrate is taken up, the more amino acids are synthesized in leaves and transported to the nectaries and nectar. However, chiropterophilous C3 plants show no such correlation, which means that the secretion of amino acids into the nectar is regulated by further factors. The results help understand the physiological properties that influence nectaries and nectar as well as the manner of metabolite and ion secretion from nectaries to nectar.

Salsipaludibacter albus gen. nov., sp. nov., a novel actinobacterial strain isolate from a Portuguese solar saltern and proposal of Salsipaludibacteraceae fam. nov. and Salsipaludibacterales ord. nov

A novel micro-organism designated AS10T was isolated from dry salt collected from Aveiro saltern in the north of Portugal. Cells were Gram-stain-positive, non-motile, non-endospore-forming, rod-shaped and aerobic. Strain AS10T was characterized by long filaments of rod-shaped cells, presenting also coccoid cellular forms at the end of the filaments, unveiling some pleomorphism. Rod-shaped cells varied from 0.3 to 0.6 µm wide and from 0.6 to 2 µm long. Growth of AS10T occurred at 15–40 °C (optimum, 20–30 °C), 0–10% (w/v) NaCl (optimum, 2%) and pH 4.5–11.0 (optimum, pH 8.0–11.0). The peptidoglycan type was A1ϒ-type with 3-hydroxy-diaminopimelic acid. The major fatty acids were C16:0, iso-C14:0, C17:0 and C14:0. The major respiratory quinone was MK-9(H4). Phylogenetic analysis based on 16S rRNA gene sequences showed that strain AS10T was similar to actinobacterial members of the class Nitriliruptoria , with Nitriliruptor alkaliphilus ANL-iso2T being the closest relative the species with a sequence pairwise similarity of 91.21%. Average nucleotide identity, average amino acid identity and in silico DNA–DNA hybridization values between strain AS10T and N. alkaliphilus ANL-iso2T were 71.34, 53.57 and 18.90%, respectively. The genome DNA G+C content of AS10T was 71.8 mol%. Based on genomic, phylogenetic, phenotypic and chemotaxonomic studies, we describe a new species of a novel genus represented by strain AS10T (=LMG 31937T=CECT 30148T) for which we propose the name Salsipaludibacter albus gen. nov., sp. nov. We also propose that this organism represents a new family named Salsipaludibacteraceae fam. nov. of a novel order named Salsipaludibacterales ord. nov.

The Combination of Untargeted Metabolomics and Machine Learning Predicts the Biosynthesis of Phenolic Compounds in Bryophyllum Medicinal Plants (Genus Kalanchoe)

Phenolic compounds constitute an important family of natural bioactive compounds responsible for the medicinal properties attributed to Bryophyllum plants (genus Kalanchoe, Crassulaceae), but their production by these medicinal plants has not been characterized to date. In this work, a combinatorial approach including plant tissue culture, untargeted metabolomics, and machine learning is proposed to unravel the critical factors behind the biosynthesis of phenolic compounds in these species. The untargeted metabolomics revealed 485 annotated compounds that were produced by three Bryophyllum species cultured in vitro in a genotype and organ-dependent manner. Neurofuzzy logic (NFL) predictive models assessed the significant influence of genotypes and organs and identified the key nutrients from culture media formulations involved in phenolic compound biosynthesis. Sulfate played a critical role in tyrosol and lignan biosynthesis, copper in phenolic acid biosynthesis, calcium in stilbene biosynthesis, and magnesium in flavanol biosynthesis. Flavonol and anthocyanin biosynthesis was not significantly affected by mineral components. As a result, a predictive biosynthetic model for all the Bryophyllum genotypes was proposed. The combination of untargeted metabolomics with machine learning provided a robust approach to achieve the phytochemical characterization of the previously unexplored species belonging to the Bryophyllum subgenus, facilitating their biotechnological exploitation as a promising source of bioactive compounds.

From Ethnomedicine to Plant Biotechnology and Machine Learning: The Valorization of the Medicinal Plant Bryophyllum sp

The subgenus Bryophyllum includes about 25 plant species native to Madagascar, and is widely used in traditional medicine worldwide. Different formulations from Bryophyllum have been employed for the treatment of several ailments, including infections, gynecological disorders, and chronic diseases, such as diabetes, neurological and neoplastic diseases. Two major families of secondary metabolites have been reported as responsible for these bioactivities: phenolic compounds and bufadienolides. These compounds are found in limited amounts in plants because they are biosynthesized in response to different biotic and abiotic stresses. Therefore, novel approaches should be undertaken with the aim of achieving the phytochemical valorization of Bryophyllum sp., allowing a sustainable production that prevents from a massive exploitation of wild plant resources. This review focuses on the study of phytoconstituents reported on Bryophyllum sp.; the application of plant tissue culture methodology as a reliable tool for the valorization of bioactive compounds; and the application of machine learning technology to model and optimize the full phytochemical potential of Bryophyllum sp. As a result, Bryophyllum species can be considered as a promising source of plant bioactive compounds, with enormous antioxidant and anticancer potential, which could be used for their large-scale biotechnological exploitation in cosmetic, food, and pharmaceutical industries.

Frameworks on Patterns of Grasslands’ Sensitivity to Forecast Extreme Drought

Climate models have predicted the future occurrence of extreme drought (ED). The management, conservation, or restoration of grasslands following ED requires a robust prior knowledge of the patterns and mechanisms of sensitivity—declining rate of ecosystem functions due to ED. Yet, the global-scale pattern of grasslands’ sensitivity to any ED event remains unresolved. Here, frameworks were built to predict the sensitivity patterns of above-ground net primary productivity (ANPP) spanning the global precipitation gradient under ED. The frameworks particularly present three sensitivity patterns that could manipulate (weaken, strengthen, or erode) the orthodox positive precipitation–productivity relationship which exists under non-drought (ambient) condition. First, the slope of the relationship could become steeper via higher sensitivity at xeric sites than mesic and hydric ones. Second, if the sensitivity emerges highest in hydric, followed by mesic, then xeric, a weakened slope, flat line, or negative slope would emerge. Lastly, if the sensitivity emerges unexpectedly similar across the precipitation gradient, the slope of the relationship would remain similar to that of the ambient condition. Overall, the frameworks provide background knowledge on possible differences or similarities in responses of grasslands to forecast ED, and could stimulate increase in conduct of experiments to unravel the impacts of ED on grasslands. More importantly, the frameworks indicate the need for reconciliation of conflicting hypotheses of grasslands’ sensitivity to ED through global-scale experiments.

Combining Medicinal Plant In Vitro Culture with Machine Learning Technologies for Maximizing the Production of Phenolic Compounds

We combined machine learning and plant in vitro culture methodologies as a novel approach for unraveling the phytochemical potential of unexploited medicinal plants. In order to induce phenolic compound biosynthesis, the in vitro culture of three different species of Bryophyllum under nutritional stress was established. To optimize phenolic extraction, four solvents with different MeOH proportions were used, and total phenolic content (TPC), flavonoid content (FC) and radical-scavenging activity (RSA) were determined. All results were subjected to data modeling with the application of artificial neural networks to provide insight into the significant factors that influence such multifactorial processes. Our findings suggest that aerial parts accumulate a higher proportion of phenolic compounds and flavonoids in comparison to roots. TPC was increased under ammonium concentrations below 15 mM, and their extraction was maximum when using solvents with intermediate methanol proportions (55–85%). The same behavior was reported for RSA, and, conversely, FC was independent of culture media composition, and their extraction was enhanced using solvents with high methanol proportions (>85%). These findings confer a wide perspective about the relationship between abiotic stress and secondary metabolism and could serve as the starting point for the optimization of bioactive compound production at a biotechnological scale.

Machine Learning Unmasked Nutritional Imbalances on the Medicinal Plant Bryophyllum sp. Cultured in vitro

Plant nutrition is a crucial factor that is usually underestimated when designing plant in vitro culture protocols of unexploited plants. As a complex multifactorial process, the study of nutritional imbalances requires the use of time-consuming experimental designs and appropriate statistical and multiple regression analysis for the determination of critical parameters, whose results may be difficult to interpret when the number of variables is large. The use of machine learning (ML) supposes a cutting-edge approach to investigate multifactorial processes, with the aim of detecting non-linear relationships and critical factors affecting a determined response and their concealed interactions. Thus, in this work we applied artificial neural networks coupled to fuzzy logic, known as neurofuzzy logic, to determine the critical factors affecting the mineral nutrition of medicinal plants belonging to Bryophyllum subgenus cultured in vitro. The application of neurofuzzy logic algorithms facilitate the interpretation of the results, as the technology is able to generate useful and understandable "IF-THEN" rules, that provide information about the factor(s) involved in a certain response. In this sense, ammonium, sulfate, molybdenum, copper and sodium were the most important nutrients that explain the variation in the in vitro culture establishment of the medicinal plants in a species-dependent manner. Thus, our results indicate that Bryophyllum spp. display a fine-tuning regulation of mineral nutrition, that was reported for the first time under in vitro conditions. Overall, neurofuzzy model was able to predict and identify masked interactions among such factors, providing a source of knowledge (helpful information) from the experimental data (non-informative per se), in order to make the exploitation and valorization of medicinal plants with high phytochemical potential easier.