Populations genomics analysis of legume host preference for specific rhizobial genotypes in the Rhizobium leguminosarum bv. viciae symbioses

Rhizobium leguminosarum bv. viciae establishes root nodule symbioses with several legume genera. Although most isolates are equally effective in establishing symbioses with all host genera, previous evidence suggests that hosts select specific rhizobial genotypes among those present in the soil. We have used population genomics to further investigate this observation. P. sativum, L. culinaris, V. sativa, and V. faba plants were used to trap rhizobia from a well-characterized soil, and pooled genomic DNAs from one-hundred isolates from each plant were sequenced. Sequence reads were aligned to the R. leguminosarum bv. viciae 3841 reference genome. High overall conservation of sequences was observed in all subpopulations, although several multigenic regions were absent from the soil population. A large fraction (16-22%) of sequence reads could not be recruited to the reference genome, suggesting that they represent sequences specific to that particular soil population. Although highly conserved, the 16S-23S rRNA gene region presented single nucleotide polymorphisms (SNPs) regarding the reference genome, but no striking differences could be found among plant-selected subpopulations. Plant-specific SNP patterns were, however, clearly observed within the nod gene cluster, supporting the existence of a plant preference for specific rhizobial genotypes. This was also shown after genome-wide analysis of SNP patterns.

Hybridizing concentrated solar power (CSP) with biogas and biomethane as an alternative to natural gas: Analysis of environmental performance using LCA

Concentrating Solar Power (CSP) plants typically incorporate one or various auxiliary boilers operating in parallel to the solar field to facilitate start up operations, provide system stability, avoid freezing of heat transfer fluid (HTF) and increase generation capacity. The environmental performance of these plants is highly influenced by the energy input and the type of auxiliary fuel, which in most cases is natural gas (NG). Replacing the NG with biogas or biomethane (BM) in commercial CSP installations is being considered as a means to produce electricity that is fully renewable and free from fossil inputs. Despite their renewable nature, the use of these biofuels also generates environmental impacts that need to be adequately identified and quantified. This paper investigates the environmental performance of a commercial wet-cooled parabolic trough 50 MWe CSP plant in Spain operating according to two strategies: solar-only, with minimum technically viable energy non-solar contribution; and hybrid operation, where 12 % of the electricity derives from auxiliary fuels (as permitted by Spanish legislation). The analysis was based on standard Life Cycle Assessment (LCA) methodology (ISO 14040-14040). The technical viability and the environmental profile of operating the CSP plant with different auxiliary fuels was evaluated, including: NG; biogas from an adjacent plant; and BM withdrawn from the gas network. The effect of using different substrates (biowaste, sewage sludge, grass and a mix of biowaste with animal manure) for the production of the biofuels was also investigated. The results showed that NG is responsible for most of the environmental damage associated with the operation of the plant in hybrid mode. Replacing NG with biogas resulted in a significant improvement of the environmental performance of the installation, primarily due to reduced impact in the following categories: natural land transformation, depletion of fossil resources, and climate change. However, despite the renewable nature of the biofuels, other environmental categories like human toxicity, eutrophication, acidification and marine ecotoxicity scored higher when using biogas and BM.

Integrated plant monitoring to improve plant operation strategy and results

The more and more demanding conditions in the power generation sector requires to apply all the available technologies to optimize processes and reduce costs. An integrated asset management strategy, combining technical analysis and operation and maintenance management can help to improve plant performance, flexibility and reliability. In order to deploy such a model it is necessary to combine plant data and specific equipment condition information, with different systems devoted to analyze performance and equipment condition, and take advantage of the results to support operation and maintenance decisions. This model that has been dealt in certain detail for electricity transmission and distribution networks, is not yet broadly extended in the power generation sector, as proposed in this study for the case of a combined power plant. Its application would turn in direct benefit for the operation and maintenance and for the interaction to the energy market

Metagenomic Anlaysis of microsymbiont selection by the legume plant host

Rhizobium leguminosarum bv.viciae is able to establish nitrogen-fixing symbioses with legumes of the genera Pisum, Lens, Lathyrus and Vicia. Classic studies using trap plants (Laguerre et al., Young et al.) provided evidence that different plant hosts are able to select different rhizobial genotypes among those available in a given soil. However, these studies were necessarily limited by the paucity of relevant biodiversity markers. We have now reappraised this problem with the help of genomic tools. A well-characterized agricultural soil (INRA Bretennieres) was used as source of rhizobia. Plants of Pisum sativum, Lens culinaris, Vicia sativa and V. faba were used as traps. Isolates from 100 nodules were pooled, and DNA from each pool was sequenced (BGI-Hong Kong; Illumina Hiseq 2000, 500 bp PE libraries, 100 bp reads, 12 Mreads). Reads were quality filtered (FastQC, Trimmomatic), mapped against reference R. leguminosarum genomes (Bowtie2, Samtools), and visualized (IGV). An important fraction of the filtered reads were not recruited by reference genomes, suggesting that plant isolates contain genes that are not present in the reference genomes. For this study, we focused on three conserved genomic regions: 16S-23S rDNA, atpD and nodDABC, and a Single Nucleotide Polymorphism (SNP) analysis was carried out with meta / multigenomes from each plant. Although the level of polymorphism varied (lowest in the rRNA region), polymorphic sites could be identified that define the specific soil population vs. reference genomes. More importantly, a plant-specific SNP distribution was observed. This could be confirmed with many other regions extracted from the reference genomes (data not shown). Our results confirm at the genomic level previous observations regarding plant selection of specific genotypes. We expect that further, ongoing comparative studies on differential meta / multigenomic sequences will identify specific gene components of the plant-selected genotypes

Effect of the Legume Plant Host on Rhizobial Soil Population Dynamics

Rhizobium leguminosarum bv viciae (Rlv) is a soil bacterium able to establish specific root-nodule symbioses with legumes of four different genera: Pisum, Vicia, Lens and Lathyrus. Rlv isolates from nodules of any of these legumes can nodulate any of them; however, it has been shown that plants select specific rhizobial genotypes from those present in the soil (1,2). We have previously shown this at the genomic level by following a population genomics approach. Pool genomic sequences from 100 isolates from each of four plant species: P. sativum, L. culinaris, V. faba and V. sativa, show different, specific profiles at the single nucleotide polymorphism (SNP) level for relevant genes. In this work, the extent of Rlv selection from a well-characterized soil population by different legume plant hosts: P. sativum, L. culinaris, V. faba and V. sativa, after a medium-term mesocosm study is described. Direct soil isolates from each of these mesocosm studies have been tested for specific rhizobial genes (glnII and fnrN) and symbiotic genes (nodC and nifH). Different populations were characterized further by Sanger sequencing of both the rpoB phylogenetic marker gene and the symbiotic genes nodC and nifH. The distribution and size of the rhizobial population for each legume host showed changes during the medium-term mesocosm study. Particularly, a non-symbiotic group of rhizobia was enriched by all four hosts, in contrast to the symbiotic rhizobia profile, which was specific for each legume plant host.

The Pangenome of the Plant-Selected Rhizobium leguminosarum bv viciae Sub-popuations

Rhizobium leguminosarum bv viciae (Rlv) is a bacterium able to establish effective symbioses with four different legume genera: Pisum, Lens, Lathyrus and Vicia. Classic studies using trap plants have previously shown that, given a choice, different plants prefer specific genotypes of rhizobia, which are adapted to the host (1, 2). In previous work we have performed a Pool-Seq analysis bases on pooled DNA samples from Rlv nodule isolates obtained from Pisum sativum, Lens culinaris, Vicia fava and V. sativa plants, used as rhizobial traps. This experiment allowed us to test the host preference hypothesis: different plant hosts select specific sub-populations of rhizobia from the available population present in a given soil. We have observed that plant-selected sub-populations are different at the single nucleotide polymorphism (SNP) level. We have selected individual isolates from each sub-population (9 fava-bean isolates, 14 pea isolates 9 vetch isolates and 9 lentil isolates) and sequenced their genomes at draft level (ca. 30x, 90 contigs). Genomic analyses have been carried out using J-species and CMG-Biotools. All the isolates had similar genome size (7.5 Mb) and number of genes (7,300). The resulting Average Nucleotide Identity (ANIm) tree showed that Rhizobium leguminosarum bv viciae is a highly diverse group. Each plant-selected subpopulation showed a closed pangenome and core genomes of similar size (11,500 and 4,800 genes, respectively). The addition of all four sub-population results in a larger, closed pangenome of 19,040 genes and a core genome of similar size (4,392 genes). Each sub-population contains a characteristic set of genes but no universal, plant-specific genes were found. The core genome obtained from all four sub-populations is probably a representative core genome for Rhizobium leguminosarum, given that the reference genome (Rhizobium leguminosarum bv. viciae strain 3841) contains most of the core genome. We have also analyzed the symbiotic cluster (nod), and different nod cluster genotypes were found in each sub-population. Supported by MINECO (Consolider-Ingenio 2010, MICROGEN Project, CSD2009-00006).

Hybrid wind-diesel power plant valuation and optimization using real option theory and dynamic programming

El sistema de energía eólica-diesel híbrido tiene un gran potencial en la prestación de suministro de energía a comunidades remotas. En comparación con los sistemas tradicionales de diesel, las plantas de energía híbridas ofrecen grandes ventajas tales como el suministro de capacidad de energía extra para "microgrids", reducción de los contaminantes y emisiones de gases de efecto invernadero, y la cobertura del riesgo de aumento inesperado del precio del combustible. El principal objetivo de la presente tesis es proporcionar nuevos conocimientos para la evaluación y optimización de los sistemas de energía híbrido eólico-diesel considerando las incertidumbres. Dado que la energía eólica es una variable estocástica, ésta no puede ser controlada ni predecirse con exactitud. La naturaleza incierta del viento como fuente de energía produce serios problemas tanto para la operación como para la evaluación del valor del sistema de energía eólica-diesel híbrido. Por un lado, la regulación de la potencia inyectada desde las turbinas de viento es una difícil tarea cuando opera el sistema híbrido. Por otro lado, el bene.cio económico de un sistema eólico-diesel híbrido se logra directamente a través de la energía entregada a la red de alimentación de la energía eólica. Consecuentemente, la incertidumbre de los recursos eólicos incrementa la dificultad de estimar los beneficios globales en la etapa de planificación. La principal preocupación del modelo tradicional determinista es no tener en cuenta la incertidumbre futura a la hora de tomar la decisión de operación. Con lo cual, no se prevé las acciones operativas flexibles en respuesta a los escenarios futuros. El análisis del rendimiento y simulación por ordenador en el Proyecto Eólico San Cristóbal demuestra que la incertidumbre sobre la energía eólica, las estrategias de control, almacenamiento de energía, y la curva de potencia de aerogeneradores tienen un impacto significativo sobre el rendimiento del sistema. En la presente tesis, se analiza la relación entre la teoría de valoración de opciones y el proceso de toma de decisiones. La opción real se desarrolla con un modelo y se presenta a través de ejemplos prácticos para evaluar el valor de los sistemas de energía eólica-diesel híbridos. Los resultados muestran que las opciones operacionales pueden aportar un valor adicional para el sistema de energía híbrida, cuando esta flexibilidad operativa se utiliza correctamente. Este marco se puede aplicar en la optimización de la operación a corto plazo teniendo en cuenta la naturaleza dependiente de la trayectoria de la política óptima de despacho, dadas las plausibles futuras realizaciones de la producción de energía eólica. En comparación con los métodos de valoración y optimización existentes, el resultado del caso de estudio numérico muestra que la política de operación resultante del modelo de optimización propuesto presenta una notable actuación en la reducción del con- sumo total de combustible del sistema eólico-diesel. Con el .n de tomar decisiones óptimas, los operadores de plantas de energía y los gestores de éstas no deben centrarse sólo en el resultado directo de cada acción operativa, tampoco deberían tomar decisiones deterministas. La forma correcta es gestionar dinámicamente el sistema de energía teniendo en cuenta el valor futuro condicionado en cada opción frente a la incertidumbre. ABSTRACT Hybrid wind-diesel power systems have a great potential in providing energy supply to remote communities. Compared with the traditional diesel systems, hybrid power plants are providing many advantages such as providing extra energy capacity to the micro-grid, reducing pollution and greenhouse-gas emissions, and hedging the risk of unexpected fuel price increases. This dissertation aims at providing novel insights for assessing and optimizing hybrid wind-diesel power systems considering the related uncertainties. Since wind power can neither be controlled nor accurately predicted, the energy harvested from a wind turbine may be considered a stochastic variable. This uncertain nature of wind energy source results in serious problems for both the operation and value assessment of the hybrid wind-diesel power system. On the one hand, regulating the uncertain power injected from wind turbines is a difficult task when operating the hybrid system. On the other hand, the economic profit of a hybrid wind-diesel system is achieved directly through the energy delivered to the power grid from the wind energy. Therefore, the uncertainty of wind resources has increased the difficulty in estimating the total benefits in the planning stage. The main concern of the traditional deterministic model is that it does not consider the future uncertainty when making the dispatch decision. Thus, it does not provide flexible operational actions in response to the uncertain future scenarios. Performance analysis and computer simulation on the San Cristobal Wind Project demonstrate that the wind power uncertainty, control strategies, energy storage, and the wind turbine power curve have a significant impact on the performance of the system. In this dissertation, the relationship between option pricing theory and decision making process is discussed. A real option model is developed and presented through practical examples for assessing the value of hybrid wind-diesel power systems. Results show that operational options can provide additional value to the hybrid power system when this operational flexibility is correctly utilized. This framework can be applied in optimizing short term dispatch decisions considering the path-dependent nature of the optimal dispatch policy, given the plausible future realizations of the wind power production. Comparing with the existing valuation and optimization methods, result from numerical example shows that the dispatch policy resulting from the proposed optimization model exhibits a remarkable performance in minimizing the total fuel consumption of the wind-diesel system. In order to make optimal decisions, power plant operators and managers should not just focus on the direct outcome of each operational action; neither should they make deterministic decisions. The correct way is to dynamically manage the power system by taking into consideration the conditional future value in each option in response to the uncertainty.