11 research outputs found
Environmental sensing and response genes in cnidaria : the chemical defensome in the sea anemone Nematostella vectensis
Author Posting. © The Author(s), 2008. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Cell Biology and Toxicology 24 (2008): 483-502, doi:10.1007/s10565-008-9107-5.The starlet sea anemone Nematostella vectensis has been recently established as a
new model system for the study of the evolution of developmental processes, as cnidaria
occupy a key evolutionary position at the base of the bilateria. Cnidaria play important
roles in estuarine and reef communities, but are exposed to many environmental stressors.
Here I describe the genetic components of a ‘chemical defensome’ in the genome of
N. vectensis, and review cnidarian molecular toxicology. Gene families that defend
against chemical stressors and the transcription factors that regulate these genes have
been termed a ‘chemical defensome,’ and include the cytochromes P450 and other
oxidases, various conjugating enyzymes, the ATP-dependent efflux transporters,
oxidative detoxification proteins, as well as various transcription factors. These genes
account for about 1% (266/27200) of the predicted genes in the sea anemone genome,
similar to the proportion observed in tunicates and humans, but lower than that observed
in sea urchins. While there are comparable numbers of stress-response genes, the stress
sensor genes appear to be reduced in N. vectensis relative to many model protostomes
and deuterostomes. Cnidarian toxicology is understudied, especially given the important
ecological roles of many cnidarian species. New genomic resources should stimulate the
study of chemical stress sensing and response mechanisms in cnidaria, and allow us to
further illuminate the evolution of chemical defense gene networks.WHOI Ocean Life Institute and NIH R01-ES01591
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Simulation of Deepwater Horizon oil plume reveals substrate specialization within a complex community of hydrocarbon degraders
The Deepwater Horizon (DWH) accident released an estimated 4.1 million barrels of oil and 1010 mol of natural gas into the Gulf of Mexico, forming deep-sea plumes of dispersed oil droplets and dissolved gases that were largely degraded by bacteria. During the course of this 3-mo disaster a series of different bacterial taxa were enriched in succession within deep plumes, but the metabolic capabilities of the different populations that controlled degradation rates of crude oil components are poorly understood. We experimentally reproduced dispersed plumes of fine oil droplets in Gulf of Mexico seawater and successfully replicated the enrichment and succession of the principal oil-degrading bacteria observed during the DWH event. We recovered near-complete genomes, whose phylogeny matched those of the principal biodegrading taxa observed in the field, including the DWH Oceanospirillales (now identified as a Bermanella species), multiple species of Colwellia, Cycloclasticus, and other members of Gammaproteobacteria, Flavobacteria, and Rhodobacteria. Metabolic pathway analysis, combined with hydrocarbon compositional analysis and species abundance data, revealed substrate specialization that explained the successional pattern of oildegrading bacteria. The fastest-growing bacteria used short-chain alkanes. The analyses also uncovered potential cooperative and competitive relationships, even among close relatives. We conclude that patterns of microbial succession following deep ocean hydrocarbon blowouts are predictable and primarily driven by the availability of liquid petroleum hydrocarbons rather than natural gases
Caffeine as an environmental indicator for assessing urban aquatic ecosystems Cafeína como indicador ambiental prospectivo para avaliar ecossistemas aquáticos urbanos
This study aimed to evaluate the co-occurrence of caffeine and the extent of its influence as compared to other traditional water quality parameters (microbiological and physico-chemical) in order to characterize it as an efficient indicator of anthropic pollution of urban aquatic environments. Caffeine is an ingredient in a variety of beverages (coffee, tea, and caffeinated soft drinks) and numerous food products (chocolate, pastries, and dairy desserts). Although the human body metabolizes this stimulant efficiently, between 0.5 and 10.0% is excreted, mostly in the urine. Analysis of water samples from the Leopoldina Basin and Guanabara Bay revealed a significant difference between areas not commonly affected by nutrient enrichment or sewage inputs and areas chronically influenced by sewage discharges and elevated eutrophication. Monitoring caffeine will be fundamental in stressed urban aquatic environments where frequent accidental ruptures of sewer lines and discharges of untreated effluents impede effective water quality evaluation with traditional indicators.<br>Este estudo visou avaliar a co-ocorrência de cafeína e a extensão de sua influência frente a outros parâmetros tradicionais de qualidade de água (microbiológicos e físico-químicos), de modo a caracterizá-la como um eficiente indicador de poluição de origem antrópica em ambientes aquáticos urbanos. Cafeína é um componente de uma variedade de bebidas (café, chá e bebidas cafeinadas) e de numerosos produtos alimentícios (chocolate, massas e sobremesas). Embora o corpo humano seja eficiente na metabolização deste estimulante, entre 0,5-10,0% são excretados, principalmente na urina. A análise de amostras da Bacia Hidrográfica da Leopoldina e Baía de Guanabara, Rio de Janeiro, Brasil, revelou uma significante diferença entre áreas não comumente afetadas por enriquecimento de nutrientes ou esgoto, contra áreas cronicamente influenciadas por descargas de esgoto e eutrofização elevada. O monitoramento de cafeína será fundamental em ambientes aquáticos urbanos estressados, onde freqüentes rupturas acidentais de linhas de esgoto e descargas de efluentes não-tratados impedem a efetividade de avaliação da qualidade hídrica com os indicadores recomendados