777 research outputs found

    SO2426 is a positive regulator of siderophore expression in \u3cem\u3eShewanella oneidensis\u3c/em\u3e MR-1

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    Background The Shewanella oneidensis MR-1 genome encodes a predicted orphan DNA-binding response regulator, SO2426. Previous studies with a SO2426-deficient MR-1 strain suggested a putative functional role for SO2426 in the regulation of iron acquisition genes, in particular, the siderophore (hydroxamate) biosynthesis operon so3030-3031-3032. To further investigate the functional role of SO2426 in iron homeostasis, we employed computational strategies to identify putative gene targets of SO2426 regulation and biochemical approaches to validate the participation of SO2426 in the control of siderophore biosynthesis in S. oneidensis MR-1. Results In silico prediction analyses revealed a single 14-bp consensus motif consisting of two tandem conserved pentamers (5\u27-CAAAA-3\u27) in the upstream regulatory regions of 46 genes, which were shown previously to be significantly down-regulated in a so2426 deletion mutant. These genes included so3030 and so3032, members of an annotated siderophore biosynthetic operon in MR-1. Electrophoretic mobility shift assays demonstrated that the SO2426 protein binds to its motif in the operator region of so3030. A short form of SO2426, beginning with a methionine at position 11 (M11) of the originally annotated coding sequence for SO2426, was also functional in binding to its consensus motif, confirming previous 5\u27 RACE results that suggested that amino acid M11 is the actual translation start codon for SO2426. Alignment of SO2426 orthologs from all sequenced Shewanella spp. showed a high degree of sequence conservation beginning at M11, in addition to conservation of a putative aspartyl phosphorylation residue and the helix-turn-helix (HTH) DNA-binding domain. Finally, the so2426 deletion mutant was unable to synthesize siderophores at wild-type rates upon exposure to the iron chelator 2,2\u27-dipyridyl. Conclusions Collectively, these data support the functional characterization of SO2426 as a positive regulator of siderophore-mediated iron acquisition and provide the first insight into a coordinate program of multiple regulatory schemes controlling iron homeostasis in S. oneidensis MR-1

    High-level chromate resistance in Arthrobacter sp. strain FB24 requires previously uncharacterized accessory genes

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    <p>Abstract</p> <p>Background</p> <p>The genome of <it>Arthrobacter </it>sp. strain FB24 contains a chromate resistance determinant (CRD), consisting of a cluster of 8 genes located on a 10.6 kb fragment of a 96 kb plasmid. The CRD includes <it>chrA</it>, which encodes a putative chromate efflux protein, and three genes with amino acid similarities to the amino and carboxy termini of ChrB, a putative regulatory protein. There are also three novel genes that have not been previously associated with chromate resistance in other bacteria; they encode an oxidoreductase (most similar to malate:quinone oxidoreductase), a functionally unknown protein with a WD40 repeat domain and a lipoprotein. To delineate the contribution of the CRD genes to the FB24 chromate [Cr(VI)] response, we evaluated the growth of mutant strains bearing regions of the CRD and transcript expression levels in response to Cr(VI) challenge.</p> <p>Results</p> <p>A chromate-sensitive mutant (strain D11) was generated by curing FB24 of its 96-kb plasmid. Elemental analysis indicated that chromate-exposed cells of strain D11 accumulated three times more chromium than strain FB24. Introduction of the CRD into strain D11 conferred chromate resistance comparable to wild-type levels, whereas deletion of specific regions of the CRD led to decreased resistance. Using real-time reverse transcriptase PCR, we show that expression of each gene within the CRD is specifically induced in response to chromate but not by lead, hydrogen peroxide or arsenate. Higher levels of <it>chrA </it>expression were achieved when the <it>chrB </it>orthologs and the WD40 repeat domain genes were present, suggesting their possible regulatory roles.</p> <p>Conclusion</p> <p>Our findings indicate that chromate resistance in <it>Arthrobacter </it>sp. strain FB24 is due to chromate efflux through the ChrA transport protein. More importantly, new genes have been identified as having significant roles in chromate resistance. Collectively, the functional predictions of these additional genes suggest the involvement of a signal transduction system in the regulation of chromate efflux and warrants further study.</p

    Robust extraction of baseline signal of atmospheric trace species using local regression

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    The identification of atmospheric trace species measurements that are representative of well-mixed background air masses is required for monitoring atmospheric composition change at background sites. We present a statistical method based on robust local regression that is well suited for the selection of background measurements and the estimation of associated baseline curves. The bootstrap technique is applied to calculate the uncertainty in the resulting baseline curve. The non-parametric nature of the proposed approach makes it more flexible than other commonly used statistical data filtering methods. Application to carbon monoxide (CO) measured from 1996 to 2009 at the high-alpine site Jungfraujoch (Switzerland, 3580m asl.), and to measurements of 1,1-difluoroethane (HFC-152a) from Jungfraujoch (2000 to 2009) and Mace Head (Ireland, 1995 to 2009) demonstrates the feasibility and usefulness of the proposed approach. The determined average annual change of CO at Jungfraujoch for the 1996 to 2009 period as estimated from filtered annual mean CO concentrations is -2.2 1.1 ppb/yr. For comparison, the linear trend of unfiltered CO measurements at Jungfraujoch for this time period is -2.9 1.3 ppb/yr

    Effects of relative humidity on aerosol light scattering in the Arctic

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    Aerosol particles experience hygroscopic growth in the ambient atmosphere. Their optical properties – especially the aerosol light scattering – are therefore strongly dependent on the ambient relative humidity (RH). In-situ light scattering measurements of long-term observations are usually performed under dry conditions (RH&amp;gt;30–40%). The knowledge of this RH effect is of eminent importance for climate forcing calculations or for the comparison of remote sensing with in-situ measurements. This study combines measurements and model calculations to describe the RH effect on aerosol light scattering for the first time for aerosol particles present in summer and fall in the high Arctic. For this purpose, a field campaign was carried out from July to October 2008 at the Zeppelin station in Ny-Ålesund, Svalbard. The aerosol light scattering coefficient &amp;sigma;&lt;sub&gt;sp&lt;/sub&gt;(&amp;lambda;) was measured at three distinct wavelengths (λ=450, 550, and 700 nm) at dry and at various, predefined RH conditions between 20% and 95% with a recently developed humidified nephelometer (WetNeph) and with a second nephelometer measuring at dry conditions with an average RH&amp;lt;10% (DryNeph). In addition, the aerosol size distribution and the aerosol absorption coefficient were measured. The scattering enhancement factor &lt;i&gt;f&lt;/i&gt;(RH, &amp;lambda;) is the key parameter to describe the RH effect on &amp;sigma;&lt;sub&gt;sp&lt;/sub&gt;(&amp;lambda;) and is defined as the RH dependent &amp;sigma;&lt;sub&gt;sp&lt;/sub&gt;(RH, &amp;lambda;) divided by the corresponding dry &amp;sigma;&lt;sub&gt;sp&lt;/sub&gt;(RH&lt;sub&gt;dry&lt;/sub&gt;, &amp;lambda;). During our campaign the average &lt;i&gt;f&lt;/i&gt;(RH=85%, λ=550 nm) was 3.24&amp;plusmn;0.63 (mean &amp;plusmn; standard deviation), and no clear wavelength dependence of &lt;i&gt;f&lt;/i&gt;(RH, &amp;lambda;) was observed. This means that the ambient scattering coefficients at RH=85% were on average about three times higher than the dry measured in-situ scattering coefficients. The RH dependency of the recorded &lt;i&gt;f&lt;/i&gt;(RH, &amp;lambda;) can be well described by an empirical one-parameter equation. We used a simplified method to retrieve an apparent hygroscopic growth factor &lt;i&gt;g&lt;/i&gt;(RH), defined as the aerosol particle diameter at a certain RH divided by the dry diameter, using the WetNeph, the DryNeph, the aerosol size distribution measurements and Mie theory. With this approach we found, on average, &lt;i&gt;g&lt;/i&gt;(RH=85%) values to be 1.61&amp;plusmn;0.12 (mean&amp;plusmn;standard deviation). No clear seasonal shift of &lt;i&gt;f&lt;/i&gt;(RH, &amp;lambda;) was observed during the 3-month period, while aerosol properties (size and chemical composition) clearly changed with time. While the beginning of the campaign was mainly characterized by smaller and less hygroscopic particles, the end was dominated by larger and more hygroscopic particles. This suggests that compensating effects of hygroscopicity and size determined the temporal stability of &lt;i&gt;f&lt;/i&gt;(RH, &amp;lambda;). During sea salt influenced periods, distinct deliquescence transitions were observed. At the end we present a method on how to transfer the dry in-situ measured aerosol scattering coefficients to ambient values for the aerosol measured during summer and fall at this location

    Better constraints on sources of carbonaceous aerosols using a combined 14C – macro tracer analysis in a European rural background site

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    The source contributions to carbonaceous PM2.5 aerosol were investigated at a European background site at the edge of the Po Valley, in Northern Italy, during the period January - December 2007. Carbonaceous aerosol was described as the sum of eight source components: primary (1) and secondary (2) biomass burning organic carbon, biomass burning elemental carbon (3), primary (4) and secondary (5) fossil fuel burning organic carbon, fossil fuel burning elemental carbon (6), primary (7) and secondary (8) biogenic organic carbon. The concentration of each component was quantified using a set of macro tracers (organic carbon OC, elemental carbon EC, and levoglucosan), micro tracers (arabitol and mannitol), and 14C measurements. This was the first time that 14C measurements were performed on a long time series of data able to represent the entire annual cycle. This set of 6 tracers, together with assumed uncertainty ranges of the ratios of OC-to-EC, and the fraction of modern carbon in the 8 source categories, provides strong constraints to the source contributions to carbonaceous aerosol. The uncertainty of contributions was assessed with a Quasi-Monte Carlo (QMC) method accounting for the variability of OC and EC emission factors, and the uncertainty of reference fractions of modern carbon. During winter biomass burning composed 50% of the total carbon (TC) concentration, while in summer secondary biogenic OC accounted for 45% of TC. The contribution of primary biogenic aerosol particles was negligible during the entire year. Moreover, aerosol associated with fossil fuel burning represented 26% and 43% of TC in winter and summer, respectively. The comparison of source apportionment results in different urban and rural areas showed that the sampling site was mainly affected by local aerosol sources during winter and regional air masses from the nearby Po Valley in summer. This observation was further confirmed by back-trajectory analysis applying the Potential Source Contribution Function method to identify potential source regions. The contribution of secondary organic aerosol (SOA) to the organic mass (OM) was significant during the entire year. SOA accounted for 23% and 83% of OM during winter and summer, respectively. While the summer SOA was dominated by biogenic sources, winter SOA was mainly due to biomass and fossil fuel burning. This indicates that the oxidation of intermediate volatility organic compounds co-emitted with primary organics is a significant source of SOA, as suggested by recent model results and Aerosol Mass Spectrometer measurements in urban regions. Comparison with previous global model simulations, indicates a strong underestimate of wintertime primary aerosol emissions in this region.JRC.H.2-Air and Climat
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