(Per)chlorate reduction by an acetogenic bacterium, Sporomusa sp., isolated from an underground gas storage

A mesophilic bacterium, strain An4, was isolated from an underground gas storage reservoir with methanol as substrate and perchlorate as electron acceptor. Cells were Gram-negative, spore-forming, straight to curved rods, 0.5–0.8 μm in diameter, and 2–8 μm in length, growing as single cells or in pairs. The cells grew optimally at 37°C, and the pH optimum was around 7. Strain An4 converted various alcohols, organic acids, fructose, acetoin, and H2/CO2 to acetate, usually as the only product. Succinate was decarboxylated to propionate. The isolate was able to respire with (per)chlorate, nitrate, and CO2. The G+C content of the DNA was 42.6 mol%. Based on the 16S rRNA gene sequence analysis, strain An4 was most closely related to Sporomusa ovata (98% similarity). The bacterium reduced perchlorate and chlorate completely to chloride. Key enzymes, perchlorate reductase and chlorite dismutase, were detected in cell-free extracts

Genome analysis and physiological comparison of Alicycliphilus denitrificans strains BC and K601T

The genomes of the Betaproteobacteria Alicycliphilus denitrificans strains BC and K601T have been sequenced to get insight into the physiology of the two strains. Strain BC degrades benzene with chlorate as electron acceptor. The cyclohexanol-degrading denitrifying strain K601T is not able to use chlorate as electron acceptor, while strain BC cannot degrade cyclohexanol. The 16S rRNA sequences of strains BC and K601T are identical and the fatty acid methyl ester patterns of the strains are similar. Basic Local Alignment Search Tool (BLAST) analysis of predicted open reading frames of both strains showed most hits with Acidovorax sp. JS42, a bacterium that degrades nitro-aromatics. The genomes include strain-specific plasmids (pAlide201 in strain K601T and pAlide01 and pAlide02 in strain BC). Key genes of chlorate reduction in strain BC were located on a 120 kb megaplasmid (pAlide01), which was absent in strain K601T. Genes involved in cyclohexanol degradation were only found in strain K601T. Benzene and toluene are degraded via oxygenase-mediated pathways in both strains. Genes involved in the meta-cleavage pathway of catechol are present in the genomes of both strains. Strain BC also contains all genes of the ortho-cleavage pathway. The large number of mono- and dioxygenase genes in the genomes suggests that the two strains have a broader substrate range than known thus far.This research was supported by the Technology Foundation, the Applied Science Division (STW) of the Netherlands Organization for Scientific Research (NWO), project number 08053, the graduate school WIMEK (Wageningen Institute for Environment and Climate Research, which is part of SENSE Research School for Socio-Economic and Natural Sciences of the Environment, www.wimek-new.wur.nl and www.sense.nl), SKB (Dutch Centre for Soil Quality Management and Knowledge Transfer, www.skbodem.nl) and the Consolider project CSD-2007-00055. The research was incorporated in the TRIAS (TRIpartite Approaches 469 toward Soil systems processes) program (http://www.nwo.nl/en/research-and-results/programmes/alw/trias-tripartite-approach-to-soil-system-processes/index. html). Flávia Talarico Saia was supported by a FAPESP (the State of São Paulo Research Foundation) scholarship (2006-01997/5). The work conducted by the DOE JGI is supported by the Office of Science of the United States Department of Energy under contract number DE-AC02-05CH11231. Alfons Stams acknowledges support by an ERC (European Research Counsil) advanced grant (project 323009). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Probabilistische risicobeoordeling voor nieuwe en bestaande stoffen: Voorbeeldberekeningen

In de EU-methodiek van risicobeoordeling voor nieuwe en bestaande stoffen wordt "risico" gekarakteriseerd als het deterministische quotient van blootstelling en effect (PEC/PNEC of "Margin of Safety"). Vanuit wetenschappelijk oogpunt is het aan te bevelen om de onzekerheid in het risicoquotient expliciet in de besluitvorming mee te nemen. De voor- en nadelen van probabilistische risicobeoordeling in dit kader zijn al uitgebreid besproken in eerder werk. Om de voordelen van een probabilistisch risicokader te demonstreren worden in dit rapport voorbeeldberekeningen voor twee stoffen gegeven: dibutylftatlaat (DBP, een bestaande stof) en een notificatie van een nieuwe stof. De uitgewerkte voorbeelden tonen aan dat een probabilistisch risicokader met weinig extra inspanning haalbaar is en meer relevante informatie geeft. Het deterministische risicoquotient bleek tamelijk worst case te zijn; i.h.a. hoger dan het 95e percentiel van de waarschijnlijkheidsverdeling. Gevoeligheidsanalyse bleek een krachtig instrument te zijn om de voornaamste bronnen van onzekerheid te identificeren en is daardoor belangrijk voor een efficiente teststrategie.In the risk assessment methods for new and existing chemicals in the EU, "risk" is characterised by means of the deterministic quotient of exposure and effects (PEC/PNEC or Margin of Safety). From a scientific viewpoint, the uncertainty in the risk quotient should be accounted for explicitly in the decision making. The advantages and disadvantages of probabilistic risk assessment in this legal framework have been extensively discussed in earlier work. To demonstrate the benefits of a probabilistic risk framework, example assessments for two substances are presented in this report: dibutylphthalate (DBP, an existing chemical) and a new chemical notification. The worked-out examples show that a probabilistic risk framework is feasible with relatively little extra effort and provides more relevant information. The deterministic risk quotients turned out to be quite worst case; generally higher than the 95th percentile of the probability distributions. Sensitivity analysis proves to be a powerful tool to identify the main sources of uncertainty and thus for efficient further testing.DG

Probabilistische risicobeoordeling voor nieuwe en bestaande stoffen: Voorbeeldberekeningen

In the risk assessment methods for new and existing chemicals in the EU, "risk" is characterised by means of the deterministic quotient of exposure and effects (PEC/PNEC or Margin of Safety). From a scientific viewpoint, the uncertainty in the risk quotient should be accounted for explicitly in the decision making. The advantages and disadvantages of probabilistic risk assessment in this legal framework have been extensively discussed in earlier work. To demonstrate the benefits of a probabilistic risk framework, example assessments for two substances are presented in this report: dibutylphthalate (DBP, an existing chemical) and a new chemical notification. The worked-out examples show that a probabilistic risk framework is feasible with relatively little extra effort and provides more relevant information. The deterministic risk quotients turned out to be quite worst case; generally higher than the 95th percentile of the probability distributions. Sensitivity analysis proves to be a powerful tool to identify the main sources of uncertainty and thus for efficient further testing.In de EU-methodiek van risicobeoordeling voor nieuwe en bestaande stoffen wordt "risico" gekarakteriseerd als het deterministische quotient van blootstelling en effect (PEC/PNEC of "Margin of Safety"). Vanuit wetenschappelijk oogpunt is het aan te bevelen om de onzekerheid in het risicoquotient expliciet in de besluitvorming mee te nemen. De voor- en nadelen van probabilistische risicobeoordeling in dit kader zijn al uitgebreid besproken in eerder werk. Om de voordelen van een probabilistisch risicokader te demonstreren worden in dit rapport voorbeeldberekeningen voor twee stoffen gegeven: dibutylftatlaat (DBP, een bestaande stof) en een notificatie van een nieuwe stof. De uitgewerkte voorbeelden tonen aan dat een probabilistisch risicokader met weinig extra inspanning haalbaar is en meer relevante informatie geeft. Het deterministische risicoquotient bleek tamelijk worst case te zijn; i.h.a. hoger dan het 95e percentiel van de waarschijnlijkheidsverdeling. Gevoeligheidsanalyse bleek een krachtig instrument te zijn om de voornaamste bronnen van onzekerheid te identificeren en is daardoor belangrijk voor een efficiente teststrategie