Comportamento do carbono orgânico e de atributos químicos, físicos e microbiológicos de um solo arenoso em área de conversão pastagem - Eucalipto

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Black carbon affects the cycling of non-black carbon in soil

Black carbon (BC) is an important fraction of many soils worldwide and plays an important role in global C biogeochemistry. However, few studies have examined how it influences the mineralization of added organic matter (AOM) and its incorporation into soil physical fractions and whether BC decomposition is increased by AOM. BC-rich Anthrosols and BC-poor adjacent soils from the Central Amazon (Brazil) were incubated for 532 days either with or without addition of (13)C-isotopically different plant residue. Total C mineralization from the BC-rich Anthrosols with AOM was 25.5% (P < 0.05) lower than with mineralization from the BC-poor adjacent soils. The AOM contributed to a significantly (P < 0.05) higher proportion to the total C mineralized in the BC-rich Anthrosols (91-92%) than the BC-poor adjacent soils (69-80%). The AOM was incorporated more rapidly in BC-rich than BC-poor soils from the separated free light fraction through the intra-aggregate light fraction into the stable organo-mineral fraction and up to 340% more AOM was found in the organo-mineral fraction. This more rapid stabilization was observed despite a significantly (P < 0.05) lower metabolic quotient for BC-rich Anthrosols. The microbial biomass (MB) was up to 125% greater (P < 0.05) in BC-rich Anthrosols than BC-poor adjacent soils. To account for increased MB adsorption onto BC during fumigation extraction, a correction factor was developed via addition of a (13)C-enriched microbial culture. The recovery was found to be 21-41 % lower (P < 0.05) for BC-rich than BC-poor soils due to re-adsorption of MB onto BC. Mineralization of native soil C was enhanced to a significantly greater degree in BC-poor adjacent soils compared to BC-rich Anthrosols as a result of AOM. No positive priming by way of cometabolism due to AOM could be found for aged BC in the soils. (C) 2009 Elsevier Ltd. All rights reserved.

Efeito da aplicação de composto orgânico sobre a qualidade do solo cultivado com cana-de-açúcar (Saccharum spp.)

A dinâmica ambiental possui capacidade limitada de reciclagem e a crescente utilização resíduos agroindustriais, especialmente na agricultura, pode levar a situações de poluição do solo e demais componentes ambientais. A manutenção da produtividade de ecossistemas agrícolas e naturais depende do processo de transformação da matéria orgânica e, por conseguinte, da biomassa microbiana do solo, e que é responsável pela decomposição e mineralização de resíduos no mesmo. A dinâmica natural dos microrganismos do solo, em constante mudança e adaptação, os torna um indicador sensível às mudanças resultantes de diferentes práticas de manejo agrícola. Sendo assim, conhecer essas alterações e suas interferências é fundamental para identificar estratégias adequadas de manejo, apontando técnicas de utilização adequadas. O objetivo deste trabalho foi avaliar a qualidade de um solo agrícola, cultivado com três variedades de cana-de-açúcar (Saccharum spp.), comparando a utilização de adubação mineral frente à utilização de fertilizante orgânico composto no período final de formação dos perfilhos (120 dias após o plantio). Foi implantado, em condições de campo, o cultivo de cana-de-açúcar (cana planta), utilizando as variedades RB 867515, RB 962869 e RB 855453, onde cada variedade foi cultivada de três formas distintas, sendo elas: plantio controle (CT) sem aplicação de insumos para adubação; plantio orgânico (OG) com aplicação de fertilizante orgânico; e plantio convencional (CV) com aplicação de adubação mineral, seguindo recomendações de adubação após análise química inicial do solo local. Cada parcela possuía 37 m2, com 5 sulcos de 5,0 m de comprimento e espaçamento de 1,5 m entrelinhas, sendo os três sulcos centrais formando a área útil. De acordo com a variedade e o tipo de adubação, foram formados nove tratamentos: T1 86CT, T2 96CT, T3 85CT, T4 6OG, T5 96OG, T6 85OG, T7 86CV, T8 96CV e T9 85CV, com delineamento estatístico de blocos ao acaso e quatro repetições. Os parâmetros químicos do solo analisados foram macronutrientes e micronutrientes; os parâmetros microbiológicos foram carbono da biomassa microbiana (CBM), respiração basal do solo (RBS), quociente metabólico (qCO2), número mais provável de fungos e bactérias do solo (NMP); e, por fim, a produtividade agrícola (t/ha). Os resultados foram submetidos a análise de variância (ANOVA) e à comparação das médias através do teste de Tukey (10%). Também foi realizada a análise de variância dos dados e correlação cofenética de Pearson para formação de dendogramas. Com base no período estudado, considerado como fase crítica da formação do canavial, concluiu-se que os parâmetros químicos que evidenciaram alterações no solo foram pH e os macronutrientes Mg, Al e SB, sendo os tratamentos orgânicos equivalentes e/ou melhores que os tratamentos convencionais. Para os parâmetros microbiológicos, o NMP de fungos apresentou os maiores valores nos tratamentos convencionais e controle. A produtividade agrícola não foi influenciada pelos diferentes tratamentos e insumos utilizados, independente da variedade de cana-de-açúcar utilizada. Por fim, foram observadas correlações positivas entre as variáveis CTC e quociente metabólico (qCO2) apontando potencial melhoria da qualidade do solo, com o emprego de insumos orgânicos

Tab. 1+2+3: Selected principal soil properties in the oil exploitation region of KomiArcticOil (Usinsk) in the Russian tundra

Oil polluted and not oil polluted soils (crude oil hydrocarbons contents: 20-92500 mg/kg dry soil mass) under natural grass and forest vegetation and in a bog in the Russian tundra were compared in their principal soil ecological parameters, the oil content and the microbial indicators. CFE biomass-C, dehydrogenase and arylsulfatase activity were enhanced with the occurrence of crude oil. Using these parameters for purposes of controlling remediation and recultivation success it is not possible to distinguish bctween promotion of microbial activity by oil carbon or soil organic carbon (SOC). For this reason we think that these parameters are not appropriate to indicate a soil damage by an oil impact. In contrast the metabolie quotient (qC02), calculated as the ratio between soil basal respiration and the SIR biomass-C was adequate to indicate a high crude oil contamination in soil. Also, the ß-glucosidase activity (parameter ß-GL/SOC) was correlated negatively with oil in soil. The indication of a soil damage by using the stress parameter qCO, or the specific enzyme activities (activity/SOC) minimizes the promotion effect of the recent SOC content on microbial parameters. Both biomass methods (SIR, CFE) have technical problems in application for crude oil-contaminated and subarctic soils. CFE does not reflect the low C_mic level of the cold tundra soils. We recommend to test every method for its suitability before any data collection in series as well as application for cold soils and the application of ecophysiological ratios as R_mic/C_mic, C_mic/SOC or enzymatic activity/SOC instead of absolute data.

Rhizosphere properties of maize genotypes with contrasting phosphorus efficiency

An experiment was conducted in a growth chamber to evaluate characteristics of the rhizosphere of maize genotypes contrasting in P-use efficiency, by determining length and density of root hairs, the rhizosphere pH and the functional diversity of rhizosphere bacteria. A sample of a Red Oxisol was limed and fertilized with N, K and micronutrients. In the treatment with the highest P level, 174 mg kg-1 P was added. Each experimental unit corresponded to a PVC rhizobox filled with 2.2 dm-3 soil. The experiment was completely randomized with three replications in a 5 x 2 factorial design, corresponding to five genotypes (H1, H2 and H3 = P-efficient hybrids, H4 and H5 = P-inefficient hybrids) and two P levels (low = 3 mg dm-3, high = 29 mg dm-3). It was found that 18 days after transplanting, the nodal roots of the hybrids H3 and H2 had the longest root hairs. In general, the pH in the rhizosphere of the different genotypes was higher than in non-rhizosphere soil, irrespective of the P level. The pH was higher in the rhizosphere of lateral than of nodal roots. At low P levels, the pH variation of the hybrids H2, H4 and H5 was greater in rhizospheric than in non-rhizospheric soil. The functional microbial activity in the rhizosphere of the hybrids H3 and H5 was highest. At low soil P levels, the indices of microbial functional diversity were also higher. The microbial metabolic profile in the rhizosphere of hybrids H1, H2, H3, and H5 remained unaltered when the plants were grown at low P. The variations in the rhizosphere properties could not be related to patterns of P-use efficiency in the tested genotypes.

Predicting the profile of nutrients available for absorption: from nutrient requirement to animal response and environmental impact

Current feed evaluation systems for dairy cattle aim to match nutrient requirements with nutrient intake at pre-defined production levels. These systems were not developed to address, and are not suitable to predict, the responses to dietary changes in terms of production level and product composition, excretion of nutrients to the environment, and nutrition related disorders. The change from a requirement to a response system to meet the needs of various stakeholders requires prediction of the profile of absorbed nutrients and its subsequent utilisation for various purposes. This contribution examines the challenges to predicting the profile of nutrients available for absorption in dairy cattle and provides guidelines for further improved prediction with regard to animal production responses and environmental pollution. The profile of nutrients available for absorption comprises volatile fatty acids, long-chain fatty acids, amino acids and glucose. Thus the importance of processes in the reticulo-rumen is obvious. Much research into rumen fermentation is aimed at determination of substrate degradation rates. Quantitative knowledge on rates of passage of nutrients out of the rumen is rather limited compared with that on degradation rates, and thus should be an important theme in future research. Current systems largely ignore microbial metabolic variation, and extant mechanistic models of rumen fermentation give only limited attention to explicit representation of microbial metabolic activity. Recent molecular techniques indicate that knowledge on the presence and activity of various microbial species is far from complete. Such techniques may give a wealth of information, but to include such findings in systems predicting the nutrient profile requires close collaboration between molecular scientists and mathematical modellers on interpreting and evaluating quantitative data. Protozoal metabolism is of particular interest here given the paucity of quantitative data. Empirical models lack the biological basis necessary to evaluate mitigation strategies to reduce excretion of waste, including nitrogen, phosphorus and methane. Such models may have little predictive value when comparing various feeding strategies. Examples include the Intergovernmental Panel on Climate Change (IPCC) Tier II models to quantify methane emissions and current protein evaluation systems to evaluate low protein diets to reduce nitrogen losses to the environment. Nutrient based mechanistic models can address such issues. Since environmental issues generally attract more funding from governmental offices, further development of nutrient based models may well take place within an environmental framework.

Rifaximin modulates the colonic microbiota of patients with Crohn's disease: an in vitro approach using a continuous culture colonic model system.

Rifaximin, a rifamycin derivative, has been reported to induce clinical remission of active Crohn's disease (CD), a chronic inflammatory bowel disorder. In order to understand how rifaximin affects the colonic microbiota and its metabolism, an in vitro human colonic model system was used in this study. We investigated the impact of the administration of 1800 mg/day of rifaximin on the faecal microbiota of four patients affected by colonic active CD [Crohn's disease activity index (CDAI > 200)] using a continuous culture colonic model system. We studied the effect of rifaximin on the human gut microbiota using fluorescence in situ hybridization, quantitative PCR and PCR–denaturing gradient gel electrophoresis. Furthermore, we investigated the effect of the antibiotic on microbial metabolic profiles, using 1H-NMR and solid phase microextraction coupled with gas chromatography/mass spectrometry, and its potential genotoxicity and cytotoxicity, using Comet and growth curve assays. Rifaximin did not affect the overall composition of the gut microbiota, whereas it caused an increase in concentration of Bifidobacterium, Atopobium and Faecalibacterium prausnitzii. A shift in microbial metabolism was observed, as shown by increases in short-chain fatty acids, propanol, decanol, nonanone and aromatic organic compounds, and decreases in ethanol, methanol and glutamate. No genotoxicity or cytotoxicity was attributed to rifaximin, and conversely rifaximin was shown to have a chemopreventive role by protecting against hydrogen peroxide-induced DNA damage. We demonstrated that rifaximin, while not altering the overall structure of the human colonic microbiota, increased bifidobacteria and led to variation of metabolic profiles associated with potential beneficial effects on the host.

Molecular models of protein targets from Mycobacterium tuberculosis

Structural characterization of enzymes that belong to microbial metabolic pathways is very important for structure-based drug design since some of these proteins may be present in the bacterial genome, but absent in humans. Thus, metabolic pathways became potential targets for drug design. The motivation of this work is the fact that Mycobacterium tuberculosis is the cause of the deaths of millions of people in the world, so that the structural characterization of protein targets to propose new drugs has become essential. DBMODELING is a relational database, created to highlight the importance of methods of molecular modeling applied to the Mycobacterium tuberculosis genome with the aim of proposing protein-ligand docking analysis. There are currently more than 300 models for proteins from Mycobacterium tuberculosis genome in the database. The database contains a detailed description of the reaction catalyzed by each enzyme and their atomic coordinates. Information about structures, a tool for animated gif image, a table with a specification of the metabolic pathway, modeled protein, inputs used in modeling, and analysis methods used in this project are available in the database for download. The search tool can be used for reseachers to find specific pathways or enzymes.

SKPDB: A structural database of shikimate pathway enzymes

Background: The functional and structural characterisation of enzymes that belong to microbial metabolic pathways is very important for structure-based drug design. The main interest in studying shikimate pathway enzymes involves the fact that they are essential for bacteria but do not occur in humans, making them selective targets for design of drugs that do not directly impact humans.Description: The ShiKimate Pathway DataBase (SKPDB) is a relational database applied to the study of shikimate pathway enzymes in microorganisms and plants. The current database is updated regularly with the addition of new data; there are currently 8902 enzymes of the shikimate pathway from different sources. The database contains extensive information on each enzyme, including detailed descriptions about sequence, references, and structural and functional studies. All files (primary sequence, atomic coordinates and quality scores) are available for downloading. The modeled structures can be viewed using the Jmol program.Conclusions: The SKPDB provides a large number of structural models to be used in docking simulations, virtual screening initiatives and drug design. It is freely accessible at http://lsbzix.rc.unesp.br/skpdb/. © 2010 Arcuri et al; licensee BioMed Central Ltd.

Uso de resíduos orgânicos como recondicionante de subsolo degradado e efeito na atividade microbiana, micorrização e crescimento do barbatimão

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Metais pesados, atributos químicos e bioquímicos em latossolos e plantas de milho após aplicação de lodo de esgoto por dezesseis anos consecutivos

Pós-graduação em Agronomia (Produção Vegetal) - FCAV

Halogenated aliphatic and aromatic aerobic biodegradation via direct metabolism and cometabolism: batch and continuous tests

In this thesis the application of biotechnological processes based on microbial metabolic degradation of halogenated compound has been investigated. Several studies showed that most of these pollutants can be biodegraded by single bacterial strains or mixed microbial population via aerobic direct metabolism or cometabolism using as a growth substrates aromatic or aliphatic hydrocarbons. The enhancement of two specific processes has been here object of study in relation with its own respective scenario described as follow: 1st) the bioremediation via aerobic cometabolism of soil contaminated by a high chlorinated compound using a mixed microbial population and the selection and isolation of consortium specific for the compound. 2nd) the implementation of a treatment technology based on direct metabolism of two pure strains at the exact point source of emission, preventing dilution and contamination of large volumes of waste fluids polluted by several halogenated compound minimizing the environmental impact. In order to verify the effect of these two new biotechnological application to remove halogenated compound and purpose them as a more efficient alternative continuous and batch tests have been set up in the experimental part of this thesis. Results obtained from the continuous tests in the second scenario have been supported by microbial analysis via Fluorescence in situ Hybridisation (FISH) and by a mathematical model of the system. The results showed that both process in its own respective scenario offer an effective solutions for the biological treatment of chlorinate compound pollution.

Full-scale biological phosphorus removal: quantification of storage polymers, microbial performance and metabolic modelling

Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica

Understanding the microbial ecology and ecophysiology of enhanced biological phosphorus removal processes through metabolic modelling and experimental studies

Dissertation to obtain the degree of Master in Chemical and Biochemical Engineering

Tapping the wealth of microbial data in high-throughput metabolic model reconstruction

Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.