Correlations between heart sound components and hemodynamic variables.

Although the esophageal stethoscope is used for continuous auscultation during general anesthesia, few studies have investigated phonocardiographic data as a continuous hemodynamic index. In this study, we aimed to induce hemodynamic variations and clarify the relationship between the heart sounds and hemodynamic variables through an experimental animal study. Changes in the cardiac contractility and vascular resistance were induced in anesthetized pigs by administering dobutamine, esmolol, phenylephrine, and nicardipine. In addition, a decrease in cardiac output was induced by restricting the venous return by clamping the inferior vena cava (IVC). The relationship between the hemodynamic changes and changes in the heart sound indices was analyzed. Experimental data from eight pigs were analyzed. The mean values of the correlation coefficients of changes in S1 amplitude (ΔS1amp) with systolic blood pressure (ΔSBP), pulse pressure (ΔPP), and ΔdP/dt during dobutamine administration were 0.94, 0.96, and 0.96, respectively. The mean values of the correlation coefficients of ΔS1amp with ΔSBP, ΔPP, and ΔdP/dt during esmolol administration were 0.80, 0.82, and 0.86, respectively. The hemodynamic changes caused by the administration of phenylephrine and nicardipine did not correlate significantly with changes in the heart rate. The S1 amplitude of the heart sound was significantly correlated with the hemodynamic changes caused by the changes in cardiac contractility but not with the variations in the vascular resistance. Heart sounds can potentially provide a non-invasive monitoring method to differentiate the cause of hemodynamic variations.

Construction of Condition-Specific Gene Regulatory Network Using Kernel Canonical Correlation Analysis.

Gene expression profile or transcriptome can represent cellular states, thus understanding gene regulation mechanisms can help understand how cells respond to external stress. Interaction between transcription factor (TF) and target gene (TG) is one of the representative regulatory mechanisms in cells. In this paper, we present a novel computational method to construct condition-specific transcriptional networks from transcriptome data. Regulatory interaction between TFs and TGs is very complex, specifically multiple-to-multiple relations. Experimental data from TF Chromatin Immunoprecipitation sequencing is useful but produces one-to-multiple relations between TF and TGs. On the other hand, co-expression networks of genes can be useful for constructing condition transcriptional networks, but there are many false positive relations in co-expression networks. In this paper, we propose a novel method to construct a condition-specific and combinatorial transcriptional network, applying kernel canonical correlation analysis (kernel CCA) to identify multiple-to-multiple TF-TG relations in certain biological condition. Kernel CCA is a well-established statistical method for computing the correlation of a group of features vs. another group of features. We, therefore, employed kernel CCA to embed TFs and TGs into a new space where the correlation of TFs and TGs are reflected. To demonstrate the usefulness of our network construction method, we used the blood transcriptome data for the investigation on the response to high fat diet in a human and an arabidopsis data set for the investigation on the response to cold/heat stress. Our method detected not only important regulatory interactions reported in previous studies but also novel TF-TG relations where a module of TF is regulating a module of TGs upon specific stress.

Application of Light-Emitting Diodes for Improving the Nutritional Quality and Bioactive Compound Levels of Some Crops and Medicinal Plants.

Light is a key factor that affects phytochemical synthesis and accumulation in plants. Due to limitations of the environment or cultivated land, there is an urgent need to develop indoor cultivation systems to obtain higher yields with increased phytochemical concentrations using convenient light sources. Light-emitting diodes (LEDs) have several advantages, including consumption of lesser power, longer half-life, higher efficacy, and wider variation in the spectral wavelength than traditional light sources; therefore, these devices are preferred for in vitro culture and indoor plant growth. Moreover, LED irradiation of seedlings enhances plant biomass, nutrient and secondary metabolite levels, and antioxidant properties. Specifically, red and blue LED irradiation exerts strong effects on photosynthesis, stomatal functioning, phototropism, photomorphogenesis, and photosynthetic pigment levels. Additionally, ex vitro plantlet development and acclimatization can be enhanced by regulating the spectral properties of LEDs. Applying an appropriate LED spectral wavelength significantly increases antioxidant enzyme activity in plants, thereby enhancing the cell defense system and providing protection from oxidative damage. Since different plant species respond differently to lighting in the cultivation environment, it is necessary to evaluate specific wavebands before large-scale LED application for controlled in vitro plant growth. This review focuses on the most recent advances and applications of LEDs for in vitro culture organogenesis. The mechanisms underlying the production of different phytochemicals, including phenolics, flavonoids, carotenoids, anthocyanins, and antioxidant enzymes, have also been discussed.

StressGenePred: a twin prediction model architecture for classifying the stress types of samples and discovering stress-related genes in arabidopsis.

BACKGROUND: Recently, a number of studies have been conducted to investigate how plants respond to stress at the cellular molecular level by measuring gene expression profiles over time. As a result, a set of time-series gene expression data for the stress response are available in databases. With the data, an integrated analysis of multiple stresses is possible, which identifies stress-responsive genes with higher specificity because considering multiple stress can capture the effect of interference between stresses. To analyze such data, a machine learning model needs to be built. RESULTS: In this study, we developed StressGenePred, a neural network-based machine learning method, to integrate time-series transcriptome data of multiple stress types. StressGenePred is designed to detect single stress-specific biomarker genes by using a simple feature embedding method, a twin neural network model, and Confident Multiple Choice Learning (CMCL) loss. The twin neural network model consists of a biomarker gene discovery and a stress type prediction model that share the same logical layer to reduce training complexity. The CMCL loss is used to make the twin model select biomarker genes that respond specifically to a single stress. In experiments using Arabidopsis gene expression data for four major environmental stresses, such as heat, cold, salt, and drought, StressGenePred classified the types of stress more accurately than the limma feature embedding method and the support vector machine and random forest classification methods. In addition, StressGenePred discovered known stress-related genes with higher specificity than the Fisher method. CONCLUSIONS: StressGenePred is a machine learning method for identifying stress-related genes and predicting stress types for an integrated analysis of multiple stress time-series transcriptome data. This method can be used to other phenotype-gene associated studies.

HTRgene: a computational method to perform the integrated analysis of multiple heterogeneous time-series data: case analysis of cold and heat stress response signaling genes in Arabidopsis.

BACKGROUND: Integrated analysis that uses multiple sample gene expression data measured under the same stress can detect stress response genes more accurately than analysis of individual sample data. However, the integrated analysis is challenging since experimental conditions (strength of stress and the number of time points) are heterogeneous across multiple samples. RESULTS: HTRgene is a computational method to perform the integrated analysis of multiple heterogeneous time-series data measured under the same stress condition. The goal of HTRgene is to identify "response order preserving DEGs" that are defined as genes not only which are differentially expressed but also whose response order is preserved across multiple samples. The utility of HTRgene was demonstrated using 28 and 24 time-series sample gene expression data measured under cold and heat stress in Arabidopsis. HTRgene analysis successfully reproduced known biological mechanisms of cold and heat stress in Arabidopsis. Also, HTRgene showed higher accuracy in detecting the documented stress response genes than existing tools. CONCLUSIONS: HTRgene, a method to find the ordering of response time of genes that are commonly observed among multiple time-series samples, successfully integrated multiple heterogeneous time-series gene expression datasets. It can be applied to many research problems related to the integration of time series data analysis.

PropaNet: Time-Varying Condition-Specific Transcriptional Network Construction by Network Propagation.

Transcription factor (TF) has a significant influence on the state of a cell by regulating multiple down-stream genes. Thus, experimental and computational biologists have made great efforts to construct TF gene networks for regulatory interactions between TFs and their target genes. Now, an important research question is how to utilize TF networks to investigate the response of a plant to stress at the transcription control level using time-series transcriptome data. In this article, we present a new computational network, PropaNet, to investigate dynamics of TF networks from time-series transcriptome data using two state-of-the-art network analysis techniques, influence maximization and network propagation. PropaNet uses the influence maximization technique to produce a ranked list of TFs, in the order of TF that explains differentially expressed genes (DEGs) better at each time point. Then, a network propagation technique is used to select a group of TFs that explains DEGs best as a whole. For the analysis of Arabidopsis time series datasets from AtGenExpress, we used PlantRegMap as a template TF network and performed PropaNet analysis to investigate transcriptional dynamics of Arabidopsis under cold and heat stress. The time varying TF networks showed that Arabidopsis responded to cold and heat stress quite differently. For cold stress, bHLH and bZIP type TFs were the first responding TFs and the cold signal influenced histone variants, various genes involved in cell architecture, osmosis and restructuring of cells. However, the consequences of plants under heat stress were up-regulation of genes related to accelerating differentiation and starting re-differentiation. In terms of energy metabolism, plants under heat stress show elevated metabolic process and resulting in an exhausted status. We believe that PropaNet will be useful for the construction of condition-specific time-varying TF network for time-series data analysis in response to stress. PropaNet is available at http://biohealth.snu.ac.kr/software/PropaNet.

The mRNA and miRNA transcriptomic landscape of Panax ginseng under the high ambient temperature.

BACKGROUND: Ginseng is a popular traditional herbal medicine in north-eastern Asia. It has been used for human health for over thousands of years. With the rise in global temperature, the production of Korean ginseng (Panax ginseng C.A.Meyer) in Korea have migrated from mid to northern parts of the Korean peninsula to escape from the various higher temperature related stresses. Under the high ambient temperature, vegetative growth was accelerated, which resulted in early flowering. This precocious phase change led to yield loss. Despite of its importance as a traditional medicine, biological mechanisms of ginseng has not been well studied and even the genome sequence of ginseng is yet to be determined due to its complex genome structure. Thus, it is challenging to investigate the molecular biology mechanisms at the transcript level. RESULTS: To investigate how ginseng responds to the high ambient temperature environment, we performed high throughput RNA sequencing and implemented a bioinformatics pipeline for the integrated analysis of small-RNA and mRNA-seq data without a reference genome. By performing reverse transcriptase (RT) PCR and sanger sequencing of transcripts that were assembled using our pipeline, we validated that their sequences were expressed in our samples. Furthermore, to investigate the interaction between genes and non-coding small RNAs and their regulation status under the high ambient temperature, we identified potential gene regulatory miRNAs. As a result, 100,672 contigs with significant expression level were identified and 6 known, 214 conserved and 60 potential novel miRNAs were predicted to be expressed under the high ambient temperature. CONCLUSION: Collectively, we have found that development, flowering and temperature responsive genes were induced under high ambient temperature, whereas photosynthesis related genes were repressed. Functional miRNAs were down-regulated under the high ambient temperature. Among them are miR156 and miR396 that target flowering (SPL6/9) and growth regulating genes (GRF) respectively.

Transcriptional Network Analysis Reveals Drought Resistance Mechanisms of AP2/ERF Transgenic Rice.

This study was designed to investigate at the molecular level how a transgenic version of rice "Nipponbare" obtained a drought-resistant phenotype. Using multi-omics sequencing data, we compared wild-type rice (WT) and a transgenic version (erf71) that had obtained a drought-resistant phenotype by overexpressing OsERF71, a member of the AP2/ERF transcription factor (TF) family. A comprehensive bioinformatics analysis pipeline, including TF networks and a cascade tree, was developed for the analysis of multi-omics data. The results of the analysis showed that the presence of OsERF71 at the source of the network controlled global gene expression levels in a specific manner to make erf71 survive longer than WT. Our analysis of the time-series transcriptome data suggests that erf71 diverted more energy to survival-critical mechanisms related to translation, oxidative response, and DNA replication, while further suppressing energy-consuming mechanisms, such as photosynthesis. To support this hypothesis further, we measured the net photosynthesis level under physiological conditions, which confirmed the further suppression of photosynthesis in erf71. In summary, our work presents a comprehensive snapshot of transcriptional modification in transgenic rice and shows how this induced the plants to acquire a drought-resistant phenotype.

AKR1B10-inhibitory Selaginella tamariscina extract and amentoflavone decrease the growth of A549 human lung cancer cells in vitro and in vivo.

ETHNOPHARMACOLOGICAL RELEVANCE: Selaginella tamariscina (P.Beauv.) Spring is a traditional medicinal plant used to treat various human diseases, including cancer, in Asia. The detailed molecular mechanism underlying the anti-cancer effects of this plant and the anti-cancer action of the combinatorial treatment of S. tamariscina and doxorubicin have not yet been investigated. AIM OF THE STUDY: We evaluated the inhibitory activity of S. tamariscina extract (STE) and its major compound, amentoflavone, on human aldo-keto reductase family 1B10 (AKR1B10), which is a detoxification enzyme involved in drug resistance, to evaluate their anti-cancer effects and their potential as adjuvant agents for doxorubicin cancer chemotherapy. MATERIALS AND METHODS: We tested the AKR1B10 inhibitory activity of STE and amentoflavone via an in vitro biochemical assay using recombinant human AKR1B10. We tested the anti-proliferative activity in A549, NCI-H460, SKOV-3, and MCF-7 human cancer cells, which contain different expression levels of AKR1B10, and determined the combination index to evaluate whether the addition of STE and amentoflavone is synergistic or antagonistic to the anti-cancer action of doxorubicin. We finally evaluated the in vivo anti-tumor effects of STE in a nude mouse xenograft model of A549 cells. RESULTS: STE and amentoflavone potently inhibited human AKR1B10 and synergistically increased the doxorubicin anti-proliferative effect in A549 and NCI-H460 human lung cancer cells that express a high level of AKR1B10 mRNA and protein. STE also significantly inhibited A549 tumor growth in animal experiments. CONCLUSION: Our results suggest that STE and amentoflavone could be potential anti-cancer agents that target AKR1B10 and might be candidate adjuvant agents to boost the anti-cancer effect of doxorubicin.

A highly efficient sorbitol dehydrogenase from Gluconobacter oxydans G624 and improvement of its stability through immobilization.

A sorbitol dehydrogenase (GoSLDH) from Gluconobacter oxydans G624 (G. oxydans G624) was expressed in Escherichia coli BL21(DE3)-CodonPlus RIL. The complete 1455-bp codon-optimized gene was amplified, expressed, and thoroughly characterized for the first time. GoSLDH exhibited Km and kcat values of 38.9 mM and 3820 s(-1) toward L-sorbitol, respectively. The enzyme exhibited high preference for NADP(+) (vs. only 2.5% relative activity with NAD(+)). GoSLDH sequencing, structure analyses, and biochemical studies, suggested that it belongs to the NADP(+)-dependent polyol-specific long-chain sorbitol dehydrogenase family. GoSLDH is the first fully characterized SLDH to date, and it is distinguished from other L-sorbose-producing enzymes by its high activity and substrate specificity. Isothermal titration calorimetry showed that the protein binds more strongly to D-sorbitol than other L-sorbose-producing enzymes, and substrate docking analysis confirmed a higher turnover rate. The high oxidation potential of GoSLDH for D-sorbitol was confirmed by cyclovoltametric analysis. Further, stability of GoSLDH significantly improved (up to 13.6-fold) after cross-linking of immobilized enzyme on silica nanoparticles and retained 62.8% residual activity after 10 cycles of reuse. Therefore, immobilized GoSLDH may be useful for L-sorbose production from D-sorbitol.

Clustering and evolutionary analysis of small RNAs identify regulatory siRNA clusters induced under drought stress in rice.

MOTIVATION: Drought tolerance is an important trait related to growth and yield in crop. Until now, drought related research has focused on coding genes. However, non-coding RNAs also respond significantly to environmental stimuli such as drought stress. Unfortunately, characterizing the role of siRNAs under drought stress is difficult since a large number of heterogenous siRNA species are expressed under drought stress and non-coding RNAs have very weak evolutionary conservation. Thus, to characterize the role of siRNAs, we need a well designed biological and bioinformatics strategy. In this paper, to characterize the function of siRNAs we developed and used a bioinformatics pipeline that includes a genomic-location based clustering technique and an evolutionary conservation tool. RESULTS: By comparing the wild type Nipponbare and two drought resistant rice varities, we found that 21 nt and 24 nt siRNAs are significantly expressed in the three rice plants but at different time points under a short-term (0, 1, and 6 hrs) drought treatment. siRNAs were up-regulated in the wild type at an early stage while the up-regulation was delayed in the two drought tolerant plants. Genes targeted by up-regulated siRNAs were related to oxidation reduction and proteolysis, which are well known to be associated with water deficit phenotypes. More interestingly, we found that siRNAs were located in intronic regions as clusters and were of high evolutionary conservation among monocot grass plants. In summary, we show that siRNAs are important respondents to drought stress and regulate genes related to the drought tolerance in water deficit conditions.

Characterization of a Mannose-6-Phosphate Isomerase from Bacillus amyloliquefaciens and Its Application in Fructose-6-Phosphate Production.

The BaM6PI gene encoding a mannose-6-phosphate isomerase (M6PI, EC 5.3.1.8) was cloned from Bacillus amyloliquefaciens DSM7 and overexpressed in Escherichia coli. The enzyme activity of BaM6PI was optimal at pH and temperature of 7.5 and 70°C, respectively, with a kcat/Km of 13,900 s-1 mM-1 for mannose-6-phosphate (M6P). The purified BaM6PI demonstrated the highest catalytic efficiency of all characterized M6PIs. Although M6PIs have been characterized from several other sources, BaM6PI is distinguished from other M6PIs by its wide pH range and high catalytic efficiency for M6P. The binding orientation of the substrate M6P in the active site of BaM6PI shed light on the molecular basis of its unusually high activity. BaM6PI showed 97% substrate conversion from M6P to fructose-6-phosphate demonstrating the potential for using BaM6PI in industrial applications.

Enhanced piezoelectric properties of vertically aligned single-crystalline NKN nano-rod arrays.

Piezoelectric materials capable of converting between mechanical and electrical energy have a great range of potential applications in micro- and nano-scale smart devices; however, their performance tends to be greatly degraded when reduced to a thin film due to the large clamping force by the substrate and surrounding materials. Herein, we report an effective method for synthesizing isolated piezoelectric nano-materials as means to relax the clamping force and recover original piezoelectric properties of the materials. Using this, environmentally friendly single-crystalline NaxK1-xNbO3 (NKN) piezoelectric nano-rod arrays were successfully synthesized by conventional pulsed-laser deposition and demonstrated to have a remarkably enhanced piezoelectric performance. The shape of the nano-structure was also found to be easily manipulated by varying the energy conditions of the physical vapor. We anticipate that this work will provide a way to produce piezoelectric micro- and nano-devices suitable for practical application, and in doing so, open a new path for the development of complex metal-oxide nano-structures.

High output piezo/triboelectric hybrid generator.

Recently, piezoelectric and triboelectric energy harvesting devices have been developed to convert mechanical energy into electrical energy. Especially, it is well known that triboelectric nanogenerators have a simple structure and a high output voltage. However, whereas nanostructures improve the output of triboelectric generators, its fabrication process is still complicated and unfavorable in term of the large scale and long-time durability of the device. Here, we demonstrate a hybrid generator which does not use nanostructure but generates much higher output power by a small mechanical force and integrates piezoelectric generator into triboelectric generator, derived from the simultaneous use of piezoelectric and triboelectric mechanisms in one press-and-release cycle. This hybrid generator combines high piezoelectric output current and triboelectric output voltage, which produces peak output voltage of ~370 V, current density of ~12 µA · cm(-2), and average power density of ~4.44 mW · cm(-2). The output power successfully lit up 600 LED bulbs by the application of a 0.2 N mechanical force and it charged a 10 µF capacitor to 10 V in 25 s. Beyond energy harvesting, this work will provide new opportunities for developing a small, built-in power source in self-powered electronics such as mobile electronics.

Enhanced Output Power of PZT Nanogenerator by Controlling Surface Morphology of Electrode.

Piezoelectric power generation using Pb(Zr,Ti)O3(PZT) nanowires grown on Nb-doped SrTiO3(nb:STO) substrate has been demonstrated. The epitaxial PZT nanowires prepared by a hydrothermal method, with a diameter and length of approximately 300 nm and 7 µm, respecively, were vertically aligned on the substrate. An embossed Au top electrode was applied to maximize the effective power generation area for non-uniform PZT nanowires. The PZT nanogenerator produced output power density of 0.56 µW/cm2 with a voltage of 0.9 V and current of 75 nA. This research suggests that the morphology control of top electrode can be useful to improve the efficiency of piezoelectric power generation.

Crystal structure and substrate specificity of D-galactose-6-phosphate isomerase complexed with substrates.

D-Galactose-6-phosphate isomerase from Lactobacillus rhamnosus (LacAB; EC 5.3.1.26), which is encoded by the tagatose-6-phosphate pathway gene cluster (lacABCD), catalyzes the isomerization of D-galactose-6-phosphate to D-tagatose-6-phosphate during lactose catabolism and is used to produce rare sugars as low-calorie natural sweeteners. The crystal structures of LacAB and its complex with D-tagatose-6-phosphate revealed that LacAB is a homotetramer of LacA and LacB subunits, with a structure similar to that of ribose-5-phosphate isomerase (Rpi). Structurally, LacAB belongs to the RpiB/LacAB superfamily, having a Rossmann-like αßα sandwich fold as has been identified in pentose phosphate isomerase and hexose phosphate isomerase. In contrast to other family members, the LacB subunit also has a unique α7 helix in its C-terminus. One active site is distinctly located at the interface between LacA and LacB, whereas two active sites are present in RpiB. In the structure of the product complex, the phosphate group of D-tagatose-6-phosphate is bound to three arginine residues, including Arg-39, producing a different substrate orientation than that in RpiB, where the substrate binds at Asp-43. Due to the proximity of the Arg-134 residue and backbone Cα of the α6 helix in LacA to the last Asp-172 residue of LacB with a hydrogen bond, a six-carbon sugar-phosphate can bind in the larger pocket of LacAB, compared with RpiB. His-96 in the active site is important for ring opening and substrate orientation, and Cys-65 is essential for the isomerization activity of the enzyme. Two rare sugar substrates, D-psicose and D-ribulose, show optimal binding in the LacAB-substrate complex. These findings were supported by the results of LacA activity assays.

New steroidal glycoside ester and aliphatic acid from the fruits of Lycium chinense.

Two new compounds stigmast-5-en-3ß-ol-3-O-ß-D-(2'-n-triacontanoyl) glucopyranoside (1) and 19,21-dimethyl triacont-17,22,24,26,28-pentaene-1-oic acid (2), along with the three known compounds n-tetracosanyl octadec-9-enoate (3), ß-sitosterol, and ß-sitosterol-3-O-ß-D-glucoside, have been isolated from the methanol extract of Lycium chinense fruits. The structures of these phytoconstituents have been established on the basis of spectral data analysis and chemical reactions.

Immunotoxicity activity from the essential oils of coriander (Coriandrum sativum) seeds.

The seeds of the Coriandrum sativum were extracted and the essential oil composition and immunotoxicity effects were studied. The analysis of the essential oil was conducted by gas chromatography-mass spectroscopy, which revealed 33 components, representing 99.99% of the total oil from the seeds of coriander. The major components are linalool (55.09%), α-pinene (7.49%), 2,6-Octadien-1-ol, 3,7-dimethyl-, acetate, (E)- (5.70%), geraniol (4.83%), 3-Cyclohexene-1-methanol, α,α,4-trimethyl- (4.72%), hexadecanoic acid (2.65%), tetradecanoic acid (2.49%), 2-α-pinene (2.39%), citronellyl acetate (1.77%), and undecanal (1.29%). The seed oil had significant toxic effects against the larvae of Aedes aegypti with an LC(50) value of 21.55 ppm and LC(90) value of 38.79 ppm. The above data indicate that the major components in the essential oil of coriander play an important role as immunotoxicity on the A. aegypti.

Structural and functional analysis of phytotoxin toxoflavin-degrading enzyme.

Pathogenic bacteria synthesize and secrete toxic low molecular weight compounds as virulence factors. These microbial toxins play essential roles in the pathogenicity of bacteria in various hosts, and are emerging as targets for antivirulence strategies. Toxoflavin, a phytotoxin produced by Burkholderia glumae BGR1, has been known to be the key factor in rice grain rot and wilt in many field crops. Recently, toxoflavin-degrading enzyme (TxDE) was identified from Paenibacillus polymyxa JH2, thereby providing a possible antivirulence strategy for toxoflavin-mediated plant diseases. Here, we report the crystal structure of TxDE in the substrate-free form and in complex with toxoflavin, along with the results of a functional analysis. The overall structure of TxDE is similar to those of the vicinal oxygen chelate superfamily of metalloenzymes, despite the lack of apparent sequence identity. The active site is located at the end of the hydrophobic channel, 9 Å in length, and contains a Mn(II) ion interacting with one histidine residue, two glutamate residues, and three water molecules in an octahedral coordination. In the complex, toxoflavin binds in the hydrophobic active site, specifically the Mn(II)-coordination shell by replacing a ligating water molecule. A functional analysis indicated that TxDE catalyzes the degradation of toxoflavin in a manner dependent on oxygen, Mn(II), and the reducing agent dithiothreitol. These results provide the structural features of TxDE and the early events in catalysis.

Screening 64 cultivars Catharanthus roseus for the production of vindoline, catharanthine, and serpentine.

The leaves of Catharanthus roseus (L.) G. Don. are a valuable source of the terpenoid indole alkaloid (TIA) anticancer drugs, vinblastine and vincristine. In particular, the precursor molecules vindoline and catharanthine are harvested from leaves and used for the semisynthetic production of vinblastine and vincristine. Because of this application, catharanthine and vindoline can be used to screen for high-yielding TIA cultivars. In this study, we compared the TIA concentrations in the leaves of 64 different cultivars of C. roseus in the soil experiments. The highest concentration of serpentine was found in Cooler Rose Hot (461±46 µg/g DW). Concentrations of vindoline (2082±113 µg/g DW) and catharanthine (2903±384 µg/g DW) were highest in Pacifica Peach. To eliminate the abiotic and biotic effects of the soils on the plant growth, sterile agar experiments were performed to investigate the TIA concentrations and mRNA transcript levels of selected TIA pathway genes. Six cultivars were investigated (two each of the high level, mid level, and low level producers of TIAs).