An adaptive teosinte mexicana introgression modulates phosphatidylcholine levels and is associated with maize flowering time.

Native Americans domesticated maize (Zea mays ssp. mays) from lowland teosinte parviglumis (Zea mays ssp. parviglumis) in the warm Mexican southwest and brought it to the highlands of Mexico and South America where it was exposed to lower temperatures that imposed strong selection on flowering time. Phospholipids are important metabolites in plant responses to low-temperature and phosphorus availability and have been suggested to influence flowering time. Here, we combined linkage mapping with genome scans to identify High PhosphatidylCholine 1 (HPC1), a gene that encodes a phospholipase A1 enzyme, as a major driver of phospholipid variation in highland maize. Common garden experiments demonstrated strong genotype-by-environment interactions associated with variation at HPC1, with the highland HPC1 allele leading to higher fitness in highlands, possibly by hastening flowering. The highland maize HPC1 variant resulted in impaired function of the encoded protein due to a polymorphism in a highly conserved sequence. A meta-analysis across HPC1 orthologs indicated a strong association between the identity of the amino acid at this position and optimal growth in prokaryotes. Mutagenesis of HPC1 via genome editing validated its role in regulating phospholipid metabolism. Finally, we showed that the highland HPC1 allele entered cultivated maize by introgression from the wild highland teosinte Zea mays ssp. mexicana and has been maintained in maize breeding lines from the Northern United States, Canada, and Europe. Thus, HPC1 introgressed from teosinte mexicana underlies a large metabolic QTL that modulates phosphatidylcholine levels and has an adaptive effect at least in part via induction of early flowering time.

Allele-specific Expression Reveals Multiple Paths to Highland Adaptation in Maize.

Maize is a staple food of smallholder farmers living in highland regions up to 4,000 m above sea level worldwide. Mexican and South American highlands are two major highland maize growing regions, and population genetic data suggest the maize's adaptation to these regions occurred largely independently, providing a case study for convergent evolution. To better understand the mechanistic basis of highland adaptation, we crossed maize landraces from 108 highland and lowland sites of Mexico and South America with the inbred line B73 to produce F1 hybrids and grew them in both highland and lowland sites in Mexico. We identified thousands of genes with divergent expression between highland and lowland populations. Hundreds of these genes show patterns of convergent evolution between Mexico and South America. To dissect the genetic architecture of the divergent gene expression, we developed a novel allele-specific expression analysis pipeline to detect genes with divergent functional cis-regulatory variation between highland and lowland populations. We identified hundreds of genes with divergent cis-regulation between highland and lowland landrace alleles, with 20 in common between regions, further suggesting convergence in the genes underlying highland adaptation. Further analyses suggest multiple mechanisms contribute to this convergence in gene regulation. Although the vast majority of evolutionary changes associated with highland adaptation were region specific, our findings highlight an important role for convergence at the gene expression and gene regulation levels as well.

Gene regulatory effects of a large chromosomal inversion in highland maize.

Chromosomal inversions play an important role in local adaptation. Inversions can capture multiple locally adaptive functional variants in a linked block by repressing recombination. However, this recombination suppression makes it difficult to identify the genetic mechanisms underlying an inversion's role in adaptation. In this study, we used large-scale transcriptomic data to dissect the functional importance of a 13 Mb inversion locus (Inv4m) found almost exclusively in highland populations of maize (Zea mays ssp. mays). Inv4m was introgressed into highland maize from the wild relative Zea mays ssp. mexicana, also present in the highlands of Mexico, and is thought to be important for the adaptation of these populations to cultivation in highland environments. However, the specific genetic variants and traits that underlie this adaptation are not known. We created two families segregating for the standard and inverted haplotypes of Inv4m in a common genetic background and measured gene expression effects associated with the inversion across 9 tissues in two experimental conditions. With these data, we quantified both the global transcriptomic effects of the highland Inv4m haplotype, and the local cis-regulatory variation present within the locus. We found diverse physiological effects of Inv4m across the 9 tissues, including a strong effect on the expression of genes involved in photosynthesis and chloroplast physiology. Although we could not confidently identify the causal alleles within Inv4m, this research accelerates progress towards understanding this inversion and will guide future research on these important genomic features.

Molecular Parallelism Underlies Convergent Highland Adaptation of Maize Landraces.

Convergent phenotypic evolution provides some of the strongest evidence for adaptation. However, the extent to which recurrent phenotypic adaptation has arisen via parallelism at the molecular level remains unresolved, as does the evolutionary origin of alleles underlying such adaptation. Here, we investigate genetic mechanisms of convergent highland adaptation in maize landrace populations and evaluate the genetic sources of recurrently selected alleles. Population branch excess statistics reveal substantial evidence of parallel adaptation at the level of individual single-nucleotide polymorphism (SNPs), genes, and pathways in four independent highland maize populations. The majority of convergently selected SNPs originated via migration from a single population, most likely in the Mesoamerican highlands, while standing variation introduced by ancient gene flow was also a contributor. Polygenic adaptation analyses of quantitative traits reveal that alleles affecting flowering time are significantly associated with elevation, indicating the flowering time pathway was targeted by highland adaptation. In addition, repeatedly selected genes were significantly enriched in the flowering time pathway, indicating their significance in adapting to highland conditions. Overall, our study system represents a promising model to study convergent evolution in plants with potential applications to crop adaptation across environmental gradients.

ROOT PENETRATION INDEX 3, a major quantitative trait locus associated with root system penetrability in Arabidopsis.

Soil mechanical impedance precludes root penetration, confining root system development to shallow soil horizons where mobile nutrients are scarce. Using a two-phase-agar system, we characterized Arabidopsis responses to low and high mechanical impedance at three root penetration stages. We found that seedlings whose roots fail to penetrate agar barriers show a significant reduction in leaf area, root length, and elongation zone and an increment in root diameter, while those capable of penetrating show only minor morphological effects. Analyses using different auxin-responsive reporter lines, exogenous auxins, and inhibitor treatments suggest that auxin responsiveness and PIN-mediated auxin distribution play an important role in regulating root responses to mechanical impedance. The assessment of 21 Arabidopsis accessions revealed that primary root penetrability varies widely among accessions. To search for quantitative trait loci (QTLs) associated to root system penetrability, we evaluated a recombinant inbred population derived from Landsberg erecta (Ler-0, with a high primary root penetrability) and Shahdara (Sha, with a low primary root penetrability) accessions. QTL analysis revealed a major-effect QTL localized in chromosome 3, ROOT PENETRATION INDEX 3 (q-RPI3), which accounted for 29.98% (logarithm of odds=8.82) of the total phenotypic variation. Employing an introgression line (IL-321) with a homozygous q-RPI3 region from Sha in the Ler-0 genetic background, we demonstrated that q-RPI3 plays a crucial role in root penetrability. This multiscale study reveals new insights into root plasticity during the penetration process in hard agar layers, natural variation, and genetic architecture behind primary root penetrability in Arabidopsis.

Thermal Water Prospection with UAV, Low-Cost Sensors and GIS. Application to the Case of La Hermida.

The geothermal resource is one of the great sources of energy on the planet. The conventional prospecting of this type of energy is a slow process that requires a great amount of time and significant investments. Nowadays, geophysical techniques have experienced an important evolution due to the irruption of UAVs, which combined with infrared sensors can provide great contributions in this field. The novelty of this technology involves the lack of tested methodologies for their implementation in this type of activities. The research developed is focused on the proposal of a methodology for the exploration of hydrothermal resources in an easy, economic, and rapid way. The combination of photogrammetry techniques with visual and thermal images taken with UAVs allows the generation of temperature maps or thermal orthomosaics, which analyzed with GIS tools permit the quasi-automatic identification of zones of potential geothermal interest along rivers or lakes. The proposed methodology has been applied to a case study in La Hermida (Cantabria, Spain), where it has allowed the identification of an effluent with temperatures close to 40 °C, according to the verification measurements performed on the geothermal interest area. These results allow validation of the potential of the method, which is strongly influenced by the particular characteristics of the study area.

Penicillin-Binding Proteins, ß-Lactamases, and ß-Lactamase Inhibitors in ß-Lactam-Producing Actinobacteria: Self-Resistance Mechanisms.

The human society faces a serious problem due to the widespread resistance to antibiotics in clinical practice. Most antibiotic biosynthesis gene clusters in actinobacteria contain genes for intrinsic self-resistance to the produced antibiotics, and it has been proposed that the antibiotic resistance genes in pathogenic bacteria originated in antibiotic-producing microorganisms. The model actinobacteria Streptomyces clavuligerus produces the ß-lactam antibiotic cephamycin C, a class A ß-lactamase, and the ß lactamases inhibitor clavulanic acid, all of which are encoded in a gene supercluster; in addition, it synthesizes the ß-lactamase inhibitory protein BLIP. The secreted clavulanic acid has a synergistic effect with the cephamycin produced by the same strain in the fight against competing microorganisms in its natural habitat. High levels of resistance to cephamycin/cephalosporin in actinobacteria are due to the presence (in their ß-lactam clusters) of genes encoding PBPs which bind penicillins but not cephalosporins. We have revised the previously reported cephamycin C and clavulanic acid gene clusters and, in addition, we have searched for novel ß-lactam gene clusters in protein databases. Notably, in S. clavuligerus and Nocardia lactamdurans, the ß-lactamases are retained in the cell wall and do not affect the intracellular formation of isopenicillin N/penicillin N. The activity of the ß-lactamase in S. clavuligerus may be modulated by the ß-lactamase inhibitory protein BLIP at the cell-wall level. Analysis of the ß-lactam cluster in actinobacteria suggests that these clusters have been moved by horizontal gene transfer between different actinobacteria and have culminated in S. clavuligerus with the organization of an elaborated set of genes designed for fine tuning of antibiotic resistance and cell wall remodeling for the survival of this Streptomyces species. This article is focused specifically on the enigmatic connection between ß-lactam biosynthesis and ß-lactam resistance mechanisms in the producer actinobacteria.

Correlates of bird collisions with buildings across three North American countries.

Collisions with buildings cause up to 1 billion bird fatalities annually in the United States and Canada. However, efforts to reduce collisions would benefit from studies conducted at large spatial scales across multiple study sites with standardized methods and consideration of species- and life-history-related variation and correlates of collisions. We addressed these research needs through coordinated collection of data on bird collisions with buildings at sites in the United States (35), Canada (3), and Mexico (2). We collected all carcasses and identified species. After removing records for unidentified carcasses, species lacking distribution-wide population estimates, and species with distributions overlapping fewer than 10 sites, we retained 269 carcasses of 64 species for analysis. We estimated collision vulnerability for 40 bird species with ≥2 fatalities based on their North American population abundance, distribution overlap in study sites, and sampling effort. Of 10 species we identified as most vulnerable to collisions, some have been identified previously (e.g., Black-throated Blue Warbler [Setophaga caerulescens]), whereas others emerged for the first time (e.g., White-breasted Nuthatch [Sitta carolinensis]), possibly because we used a more standardized sampling approach than past studies. Building size and glass area were positively associated with number of collisions for 5 of 8 species with enough observations to analyze independently. Vegetation around buildings influenced collisions for only 1 of those 8 species (Swainson's Thrush [Catharus ustulatus]). Life history predicted collisions; numbers of collisions were greatest for migratory, insectivorous, and woodland-inhabiting species. Our results provide new insight into the species most vulnerable to building collisions, making them potentially in greatest need of conservation attention to reduce collisions and into species- and life-history-related variation and correlates of building collisions, information that can help refine collision management.

Correlaciones de las Colisiones de Aves contra Edificios en Tres Países de América del Norte Resumen Las colisiones contra los edificios causan hasta mil millones de fatalidades de aves al año en los Estados Unidos y en Canadá. Sin embargo, los esfuerzos por reducir estas colisiones se beneficiarían con estudios realizados a grandes escalas espaciales en varios sitios de estudio con métodos estandarizados y considerando las variaciones relacionadas a la historia de vida y a la especie y las correlaciones de las colisiones. Abordamos estas necesidades de investigación por medio de una recolección coordinada de datos sobre las colisiones de aves contra edificios en los Estados Unidos (35), Canadá (3) y México (2). Recolectamos todos los cadáveres y los identificamos hasta especie. Después de retirar los registros de cadáveres no identificados, las especies sin estimaciones poblacionales a nivel distribución y las especies con distribuciones traslapadas en menos de diez sitios, nos quedamos con 269 cadáveres de 64 especies para el análisis. Estimamos la vulnerabilidad a colisiones para 40 especies con ≥2 fatalidades con base en la abundancia poblacional para América del Norte, el traslape de su distribución entre los sitios de estudio y el esfuerzo de muestreo. De las diez especies que identificamos como las más vulnerables a las colisiones, algunas han sido identificadas previamente (Setophaga caerulescens), y otras aparecieron por primera vez (Sitta carolinensis), posiblemente debido a que usamos una estrategia de muestreo más estandarizada que en los estudios previos. El tamaño del edificio y el área del vidrio estuvieron asociados positivamente con el número de colisiones para cinco de ocho especies con suficientes observaciones para ser analizadas independientemente. La vegetación alrededor de los edificios influyó sobre las colisiones solamente para una de esas ocho especies Catharus ustulatus). Las historias de vida pronosticaron las colisiones; el número de colisiones fue mayor para las especies migratorias, insectívoras y aquellas que habitan en las zonas boscosas. Nuestros resultados proporcionan una nueva perspectiva hacia las especies más vulnerables a las colisiones contra edificios, lo que las pone en una necesidad potencialmente mayor de atención conservacionista para reducir estas colisiones y de estudio de las variaciones relacionadas con la especie y la historia de vida y las correlaciones de las colisiones contra edificios, información que puede ayudar a refinar el manejo de colisiones.

Digital Twin for Automatic Transportation in Industry 4.0.

Industry 4.0 is the fourth industrial revolution consisting of the digitalization of processes facilitating an incremental value chain. Smart Manufacturing (SM) is one of the branches of the Industry 4.0 regarding logistics, visual inspection of pieces, optimal organization of processes, machine sensorization, real-time data adquisition and treatment and virtualization of industrial activities. Among these tecniques, Digital Twin (DT) is attracting the research interest of the scientific community in the last few years due to the cost reduction through the simulation of the dynamic behaviour of the industrial plant predicting potential problems in the SM paradigm. In this paper, we propose a new DT design concept based on external service for the transportation of the Automatic Guided Vehicles (AGVs) which are being recently introduced for the Material Requirement Planning satisfaction in the collaborative industrial plant. We have performed real experimentation in two different scenarios through the definition of an Industrial Ethernet platform for the real validation of the DT results obtained. Results show the correlation between the virtual and real experiments carried out in the two scenarios defined in this paper with an accuracy of 97.95% and 98.82% in the total time of the missions analysed in the DT. Therefore, these results validate the model created for the AGV navigation, thus fulfilling the objectives of this paper.

Malate-dependent Fe accumulation is a critical checkpoint in the root developmental response to low phosphate.

Low phosphate (Pi) availability constrains plant development and seed production in both natural and agricultural ecosystems. When Pi is scarce, modifications of root system architecture (RSA) enhance the soil exploration ability of the plant and lead to an increase in Pi uptake. In Arabidopsis, an iron-dependent mechanism reprograms primary root growth in response to low Pi availability. This program is activated upon contact of the root tip with low-Pi media and induces premature cell differentiation and the arrest of mitotic activity in the root apical meristem, resulting in a short-root phenotype. However, the mechanisms that regulate the primary root response to Pi-limiting conditions remain largely unknown. Here we report on the isolation and characterization of two low-Pi insensitive mutants (lpi5 and lpi6), which have a long-root phenotype when grown in low-Pi media. Cellular, genomic, and transcriptomic analysis of low-Pi insensitive mutants revealed that the genes previously shown to underlie Arabidopsis Al tolerance via root malate exudation, known as SENSITIVE TO PROTON RHIZOTOXICITY (STOP1) and ALUMINUM ACTIVATED MALATE TRANSPORTER 1 (ALMT1), represent a critical checkpoint in the root developmental response to Pi starvation in Arabidopsis thaliana Our results also show that exogenous malate can rescue the long-root phenotype of lpi5 and lpi6 Malate exudation is required for the accumulation of Fe in the apoplast of meristematic cells, triggering the differentiation of meristematic cells in response to Pi deprivation.

Local Wireless Sensor Networks Positioning Reliability Under Sensor Failure.

Local Positioning Systems are collecting high research interest over the last few years. Its accurate application in high-demanded difficult scenarios has revealed its stability and robustness for autonomous navigation. In this paper, we develop a new sensor deployment methodology to guarantee the system availability in case of a sensor failure of a five-node Time Difference of Arrival (TDOA) localization method. We solve the ambiguity of two possible solutions in the four-sensor TDOA problem in each combination of four nodes of the system by maximizing the distance between the two possible solutions in every target possible location. In addition, we perform a Genetic Algorithm Optimization in order to find an optimized node location with a trade-off between the system behavior under failure and its normal operating condition by means of the Cramer Rao Lower Bound derivation in each possible target location. Results show that the optimization considering sensor failure enhances the average values of the convergence region size and the location accuracy by 31% and 22%, respectively, in case of some malfunction sensors regarding to the non-failure optimization, only suffering a reduction in accuracy of less than 5% under normal operating conditions.

Hybrid Memetic Algorithm for the Node Location Problem in Local Positioning Systems.

Local Positioning Systems (LPS) have shown excellent performance for applications that demand high accuracy. They rely on ad-hoc node deployments which fit the environment characteristics in order to reduce the system uncertainties. The obtainment of competitive results through these systems requires the solution of the Node Location Problem (finding the optimal cartesian coordinates of the architecture sensors). This problem has been assigned as NP-Hard, therefore a heuristic solution is recommended for addressing this complex problem. Genetic Algorithms (GA) have shown an excellent trade-off between diversification and intensification in the literature. However, in Non-Line-of-Sight (NLOS) environments in which there is not continuity in the fitness function evaluation of a particular node distribution among contiguous solutions, challenges arise for the GA during the exploration of new potential regions of the space of solutions. Consequently, in this paper, we first propose a Hybrid GA with a combination of the GA operators in the evolutionary process for the Node Location Problem. Later, we introduce a Memetic Algorithm (MA) with a Local Search (LS) strategy for exploring the most different individuals of the population in search of improving the previous results. Finally, we combine the Hybrid Genetic Algorithm (HGA) and Memetic Algorithm (MA), designing an enhanced novel methodology for solving the Node Location Problem, a Hybrid Memetic Algorithm (HMA). Results show that the HMA proposed in this article outperforms all of the individual configurations presented and attains an improvement of 14.2% in accuracy for the Node Location Problem solution in the scenario of simulations with regards to the previous GA optimizations of the literature.

Image processing and analysis methods for the Adolescent Brain Cognitive Development Study.

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.

Grasses suppress shoot-borne roots to conserve water during drought.

Many important crops are members of the Poaceae family, which develop root systems characterized by a high degree of root initiation from the belowground basal nodes of the shoot, termed the crown. Although this postembryonic shoot-borne root system represents the major conduit for water uptake, little is known about the effect of water availability on its development. Here we demonstrate that in the model C4 grass Setaria viridis, the crown locally senses water availability and suppresses postemergence crown root growth under a water deficit. This response was observed in field and growth room environments and in all grass species tested. Luminescence-based imaging of root systems grown in soil-like media revealed a shift in root growth from crown-derived to primary root-derived branches, suggesting that primary root-dominated architecture can be induced in S. viridis under certain stress conditions. Crown roots of Zea mays and Setaria italica, domesticated relatives of teosinte and S. viridis, respectively, show reduced sensitivity to water deficit, suggesting that this response might have been influenced by human selection. Enhanced water status of maize mutants lacking crown roots suggests that under a water deficit, stronger suppression of crown roots actually may benefit crop productivity.

Accuracy Analysis in Sensor Networks for Asynchronous Positioning Methods.

The accuracy requirements for sensor network positioning have grown over the last few years due to the high precision demanded in activities related with vehicles and robots. Such systems involve a wide range of specifications which must be met through positioning devices based on time measurement. These systems have been traditionally designed with the synchronization of their sensors in order to compute the position estimation. However, this synchronization introduces an error in the time determination which can be avoided through the centralization of the measurements in a single clock in a coordinate sensor. This can be found in typical architectures such as Asynchronous Time Difference of Arrival (A-TDOA) and Difference-Time Difference of Arrival (D-TDOA) systems. In this paper, a study of the suitability of these new systems based on a Cramér-Rao Lower Bound (CRLB) evaluation was performed for the first time under different 3D real environments for multiple sensor locations. The analysis was carried out through a new heteroscedastic noise variance modelling with a distance-dependent Log-normal path loss propagation model. Results showed that A-TDOA provided less uncertainty in the root mean square error (RMSE) in the positioning, while D-TDOA reduced the standard deviation and increased stability all over the domain.

3D Tdoa Problem Solution with Four Receiving Nodes.

Time difference of arrival (TDOA) positioning methods have experienced growing importance over the last few years due to their multiple applications in local positioning systems (LPSs). While five sensors are needed to determine an unequivocal three-dimensional position, systems with four nodes present two different solutions that cannot be discarded according to mathematical standards. In this paper, a new methodology to solve the 3D TDOA problems in a sensor network with four beacons is proposed. A confidence interval, which is defined in this paper as a sphere, is defined to use positioning algorithms with four different nodes. It is proven that the separation between solutions in the four-beacon TDOA problem allows the transformation of the problem into an analogous one in which more receivers are implied due to the geometric properties of the intersection of hyperboloids. The achievement of the distance between solutions needs the application of genetic algorithms in order to find an optimized sensor distribution. Results show that positioning algorithms can be used 96.7% of the time with total security in cases where vehicles travel at less than 25 m/s.

Genetic Algorithm Approach to the 3D Node Localization in TDOA Systems.

Positioning asynchronous architectures based on time measurements are reaching growing importance in Local Positioning Systems (LPS). These architectures have special relevance in precision applications and indoor/outdoor navigation of automatic vehicles such as Automatic Ground Vehicles (AGVs) and Unmanned Aerial Vehicles (UAVs). The positioning error of these systems is conditioned by the algorithms used in the position calculation, the quality of the time measurements, and the sensor deployment of the signal receivers. Once the algorithms have been defined and the method to compute the time measurements has been selected, the only design criteria of the LPS is the distribution of the sensors in the three-dimensional space. This problem has proved to be NP-hard, and therefore a heuristic solution to the problem is recommended. In this paper, a genetic algorithm with the flexibility to be adapted to different scenarios and ground modelings is proposed. This algorithm is used to determine the best node localization in order to reduce the Cramér-Rao Lower Bound (CRLB) with a heteroscedastic noise consideration in each sensor of an Asynchronous Time Difference of Arrival (A-TDOA) architecture. The methodology proposed allows for the optimization of the 3D sensor deployment of a passive A-TDOA architecture, including ground modeling flexibility and heteroscedastic noise consideration with sequential iterations, and reducing the spatial discretization to achieve better results. Results show that optimization with 15% of elitism and a Tournament 3 selection strategy offers the best maximization for the algorithm.

Characterization of the Jomthonic Acids Biosynthesis Pathway and Isolation of Novel Analogues in Streptomyces caniferus GUA-06-05-006A.

Jomthonic acids (JAs) are a group of natural products (NPs) with adipogenic activity. Structurally, JAs are formed by a modified ß-methylphenylalanine residue, whose biosynthesis involves a methyltransferase that in Streptomyces hygroscopicus has been identified as MppJ. Up to date, three JA members (A⁻C) and a few other natural products containing ß-methylphenylalanine have been discovered from soil-derived microorganisms. Herein, we report the identification of a gene (jomM) coding for a putative methyltransferase highly identical to MppJ in the chromosome of the marine actinobacteria Streptomyces caniferus GUA-06-05-006A. In its 5' region, jomM clusters with two polyketide synthases (PKS) (jomP1, jomP2), a nonribosomal peptide synthetase (NRPS) (jomN) and a thioesterase gene (jomT), possibly conforming a single transcriptional unit. Insertion of a strong constitutive promoter upstream of jomP1 led to the detection of JA A, along with at least two novel JA family members (D and E). Independent inactivation of jomP1, jomN and jomM abolished production of JA A, JA D and JA E, indicating the involvement of these genes in JA biosynthesis. Heterologous expression of the JA biosynthesis cluster in Streptomyces coelicolor M1152 and in Streptomyces albus J1074 led to the production of JA A, B, C and F. We propose a pathway for JAs biosynthesis based on the findings here described.

Effects of Chronic Administration of Capsaicin on Biomarkers of Kidney Injury in Male Wistar Rats with Experimental Diabetes.

Capsaicin is an agonist of the transient receptor potential vanilloid type 1 (TRPV1) channel, which has been related to the pathophysiology of kidney disease secondary to diabetes. This study aimed to evaluate the chronic effect of capsaicin administration on biomarkers of kidney injury in an experimental rat model of diabetes. Male Wistar rats were assigned to four groups: (1) healthy controls without diabetes (CON), (2) healthy controls plus capsaicin at 1 mg/kg/day (CON + CAPS), (3) experimental diabetes without capsaicin (DM), and (4) experimental diabetes plus capsaicin at 1 mg/kg/day (DM + CAPS). For each group, 24-h urine samples were collected to determine diuresis, albumin, cystatin C, ß2 microglobulin, epidermal growth factor (EGF), alpha (1)-acid glycoprotein, and neutrophil gelatinase-associated lipocalin (NAG-L). Blood samples were drawn to measure fasting glucose. After 8 weeks, the CON + CAPS and DM + CAPS groups showed increased diuresis compared to the CON and DM groups, but the difference was significant only in the DM + CAPS group. The two-way ANOVA only showed a statistically significant effect of CAPS on the urinary EGF levels, as well as a tendency to have a significant effect in the urinary NAG-L levels. The EGF levels decreased in both CAPS-treated groups, but the change was only significant in the CON + CAPS group vs. CON group; and the NAG-L levels were lower in both CAPS-treated groups. These results show that capsaicin had a diuretic effect in healthy and diabetic rats; additionally, it increased the urinary EGF levels and tended to decrease the urinary NAG-L levels.

Co-ordinated Changes in the Accumulation of Metal Ions in Maize (Zea mays ssp. mays L.) in Response to Inoculation with the Arbuscular Mycorrhizal Fungus Funneliformis mosseae.

Arbuscular mycorrhizal symbiosis is an ancient interaction between plants and fungi of the phylum Glomeromycota. In exchange for photosynthetically fixed carbon, the fungus provides the plant host with greater access to soil nutrients via an extensive network of root-external hyphae. Here, to determine the impact of the symbiosis on the host ionome, the concentration of 19 elements was determined in the roots and leaves of a panel of 30 maize varieties, grown under phosphorus-limiting conditions, with or without inoculation with the fungus Funneliformis mosseae. Although the most recognized benefit of the symbiosis to the host plant is greater access to soil phosphorus, the concentration of a number of other elements responded significantly to inoculation across the panel as a whole. In addition, variety-specific effects indicated the importance of plant genotype to the response. Clusters of elements were identified that varied in a co-ordinated manner across genotypes, and that were maintained between non-inoculated and inoculated plants.