Targeting determinants of dosage compensation in Drosophila

The dosage compensation complex (DCC) in Drosophila melanogaster is responsible for up-regulating transcription from the single male X chromosome to equal the transcription from the two X chromosomes in females. Visualization of the DCC, a large ribonucleoprotein complex, on male larval polytene chromosomes reveals that the complex binds selectively to many interbands on the X chromosome. The targeting of the DCC is thought to be in part determined by DNA sequences that are enriched on the X. So far, lack of knowledge about DCC binding sites has prevented the identification of sequence determinants. Only three binding sites have been identified to date, but analysis of their DNA sequence did not allow the prediction of further binding sites. We have used chromatin immunoprecipitation to identify a number of new DCC binding fragments and characterized them in vivo by visualizing DCC binding to autosomal insertions of these fragments, and we have demonstrated that they possess a wide range of potential to recruit the DCC. By varying the in vivo concentration of the DCC, we provide evidence that this range of recruitment potential is due to differences in affinity of the complex to these sites. We were also able to establish that DCC binding to ectopic high-affinity sites can allow nearby low-affinity sites to recruit the complex. Using the sequences of the newly identified and previously characterized binding fragments, we have uncovered a number of short sequence motifs, which in combination may contribute to DCC recruitment. Our findings suggest that the DCC is recruited to the X via a number of binding sites of decreasing affinities, and that the presence of high-and moderate-affinity sites on the X may ensure that lower-affinity sites are occupied in a context-dependent manner. Our bioinformatics analysis suggests that DCC binding sites may be composed of variable combinations of degenerate motifs

Maxent Estimation of Aquatic Escherichia Coli Stream Impairment

Background: The leading cause of surface water impairment in United States’ rivers and streams is pathogen contamination. Although use of fecal indicators has reduced human health risk, current approaches to identify and reduce exposure can be improved. One important knowledge gap within exposure assessment is characterization of complex fate and transport processes of fecal pollution. Novel modeling processes can inform watershed decision-making to improve exposure assessment. Methods: We used the ecological model, Maxent, and the fecal indicator bacterium Escherichia coli to identify environmental factors associated with surface water impairment. Samples were collected August, November, February, and May for 8 years on Sinking Creek in Northeast Tennessee and analyzed for 10 water quality parameters and E. coli concentrations. Univariate and multivariate models estimated probability of impairment given the water quality parameters. Model performance was assessed using area under the receiving operating characteristic (AUC) and prediction accuracy, defined as the model’s ability to predict both true positives (impairment) and true negatives (compliance). Univariate models generated action values, or environmental thresholds, to indicate potential E. coli impairment based on a single parameter. Multivariate models predicted probability of impairment given a suite of environmental variables, and jack-knife sensitivity analysis removed unresponsive variables to elicit a set of the most responsive parameters. Results: Water temperature univariate models performed best as indicated by AUC, but alkalinity models were the most accurate at correctly classifying impairment. Sensitivity analysis revealed that models were most sensitive to removal of specific conductance. Other sensitive variables included water temperature, dissolved oxygen, discharge, and NO3. The removal of dissolved oxygen improved model performance based on testing AUC, justifying development of two optimized multivariate models; a 5-variable model including all sensitive parameters, and a 4-variable model that excluded dissolved oxygen. Discussion: Results suggest that E. coli impairment in Sinking Creek is influenced by seasonality and agricultural run-off, stressing the need for multi-month sampling along a stream continuum. Although discharge was not predictive of E. coli impairment alone, its interactive effect stresses the importance of both flow dependent and independent processes associated with E. coli impairment. This research also highlights the interactions between nutrient and fecal pollution, a key consideration for watersheds with multiple synergistic impairments. Although one indicator cannot mimic the plethora of existing pathogens in water, incorporating modeling can fine tune an indicator’s utility, providing information concerning fate, transport, and source of fecal pollution while prioritizing resources and increasing confidence in decision making. Methods We used the ecological model, Maxent, and the fecal indicator bacterium Escherichia coli to identify environmental factors associated with surface water impairment. Samples were collected August, November, February, and May for 8 years on Sinking Creek in Northeast Tennessee and analyzed for 10 water quality parameters and E. coli concentrations. Univariate and multivariate models estimated probability of impairment given the water quality parameters. Model performance was assessed using area under the receiving operating characteristic (AUC) and prediction accuracy, defined as the model’s ability to predict both true positives (impairment) and true negatives (compliance). Univariate models generated action values, or environmental thresholds, to indicate potential E. coli impairment based on a single parameter. Multivariate models predicted probability of impairment given a suite of environmental variables, and jack-knife sensitivity analysis removed unresponsive variables to elicit a set of the most responsive parameters. Results Water temperature univariate models performed best as indicated by AUC, but alkalinity models were the most accurate at correctly classifying impairment. Sensitivity analysis revealed that models were most sensitive to removal of specific conductance. Other sensitive variables included water temperature, dissolved oxygen, discharge, and NO3. The removal of dissolved oxygen improved model performance based on testing AUC, justifying development of two optimized multivariate models; a 5-variable model including all sensitive parameters, and a 4-variable model that excluded dissolved oxygen. Discussion Results suggest that E. coli impairment in Sinking Creek is influenced by seasonality and agricultural run-off, stressing the need for multi-month sampling along a stream continuum. Although discharge was not predictive of E. coli impairment alone, its interactive effect stresses the importance of both flow dependent and independent processes associated with E. coli impairment. This research also highlights the interactions between nutrient and fecal pollution, a key consideration for watersheds with multiple synergistic impairments. Although one indicator cannot mimic theplethora of existing pathogens in water, incorporating modeling can fine tune an indicator’s utility, providing information concerning fate, transport, and source of fecal pollution while prioritizing resources and increasing confidence in decision making

Technical note: Development of a gradient tube method for examining microbial population structures in floating sulphur biofilms

Floating biofilms occur in thin layers of between 50 μm and 500 μm on the surface of certain organic, sulphidic aquatic environments and, at times, may only be several cells deep. While these structures may be important in terms of energy flow pathways, and possibly also in wastewater treatment operations, little is known about their structural/functional properties. This is due, in part, to their flimsy nature but also to methodological constraints related to their sampling and manipulation. We have investigated floating sulphur biofilms that appear as white layers on the surface of anoxic sulphidic organic wastewaters and describe here the development of a novel gradient tube method for investigating these systems. This approach enables testing of the hypothesis that these floating sulphur biofilms are complex well-differentiated structures rather than disordered dispersions of microbial biomass as has been previously thought. Furthermore, if the former is correct, they would seem to resemble the structure and functionality of comparable complex bioflms that are attached to solid substrates. The gradient tube method involves the establishment of apposing gradients of sulphide and oxygen that are expanded across a tube of agarose 10 cm in length; this simulates the oxic/anoxic interface that occurs over only several micrometres in the natural biofilm system. A plug of sulphide-enriched agarose is first placed in the base of the tube. Samples of the floating sulphur biofilm are then mixed into agarose growth medium and, before it sets, this is overlaid on top of the plug. The tubes are then open capped and incubated. A variety of different microbial populations may thus become established in the separate physiological niches that are set up in this way within the gradient tube. The populations may be quite robustly sampled by extruding and then sectioning the agarose plug. This expansion of the biofilm enables more detailed molecular phylogenetic studies of the populations found in the various niches within the biofilm and also measurement of physico-chemical parameters within the system.Keywords: gradient tube method, floating biofilms, floating sulphur biofilms, microbial ecology, sulphur biotechnology, acid mine drainage wastewater

The Inherent Tracer Fingerprint of Captured CO2.

Carbon capture and storage (CCS) is the only currently available technology that can directly reduce anthropogenic CO2 emissions arising from fossil fuel combustion. Monitoring and verification of CO2 stored in geological reservoirs will be a regulatory requirement and so the development of reliable monitoring techniques is essential. The isotopic and trace gas composition - the inherent fingerprint - of captured CO2 streams is a potentially powerful, low cost geochemical technique for tracking the fate of injected gas in CCS projects; carbon and oxygen isotopes, in particular, have been used as geochemical tracers in a number of pilot CO2 storage sites, and noble gases are known to be powerful tracers of natural CO2 migration. However, the inherent tracer fingerprint in captured CO2 streams has yet to be robustly investigated and documented and key questions remain, including how consistent is the fingerprint, what controls it, and will it be retained en route to and within the storage reservoir? Here we present the first systematic measurements of the carbon and oxygen isotopes and the trace noble gas composition of anthropogenic CO2 captured from combustion power stations and fertiliser plants. The analysed CO2 is derived from coal, biomass and natural gas feedstocks, using amine capture, oxyfuel and gasification processes, from six different CO2 capture plants spanning four different countries. We find that δ13C values are primarily controlled by the δ13C of the feedstock while δ18O values are predominantly similar to atmospheric O2. Noble gases are of low concentration and exhibit relative element abundances different to expected reservoir baselines and air, with isotopic compositions that are similar to air or fractionated air. The use of inherent tracers for monitoring and verification was provisionally assessed by analysing CO2 samples produced from two field storage sites after CO2 injection. These experiments at Otway, Australia, and Aquistore, Canada, highlight the need for reliable baseline data. Noble gas data indicates noble gas stripping of the formation water and entrainment of Kr and Xe from an earlier injection experiment at Otway, and inheritance of a distinctive crustal radiogenic noble gas fingerprint at Aquistore. This fingerprint can be used to identify unplanned migration of the CO2 to the shallow subsurface or surface

Inherent tracers for carbon capture and storage in sedimentary formations: composition and applications

Inherent tracers - the “natural” isotopic and trace gas composition of captured CO₂ streams – are potentially powerful tracers for use in CCS technology. This review outlines for the first time the expected carbon isotope and noble gas compositions of captured CO₂ streams from a range of feedstocks, CO₂-generating processes and carbon capture techniques. The C-isotope composition of captured CO₂ will be most strongly controlled by the feedstock, but significant isotope fractionation is possible during capture; noble gas concentrations will be controlled by the capture technique employed. Comparison with likely baseline data suggests that CO₂ generated from fossil fuel feedstocks will often have δ13C distinguishable from storage reservoir CO₂. Noble gases in amine-captured CO₂ streams are likely to be low concentration, with isotopic ratios dependant on the feedstock, but CO₂ captured from oxyfuel plants may be strongly enriched in Kr and Xe which are potentially valuable subsurface tracers. CO₂ streams derived from fossil fuels will have noble gas isotope ratios reflecting a radiogenic component that will be difficult to distinguish in the storage reservoir, but inheritance of radiogenic components will provide an easily recognisable signature in the case of any unplanned migration into shallow aquifers or to the surface

Stepping into the Same River Twice: Field Evidence for the Repeatability of a CO2 Injection Test

A single well characterisation test was conducted at the CO2CRC Otway storage site in Victoria, Australia, in 2011 and repeated in 2014. The near-well permeability was found to have declined nearly 60% since the 2011 test, while the residual saturation inferred from a variety of techniques was lower in 2014. There was a significant change in water chemistry, suggesting an alteration of near-well reservoir properties. Possible reasons for these changes are explored, and the implications for other field tests are discussed

Microplastic in Surface Waters of Urban Rivers: Concentration, Sources, and Associated Bacterial Assemblages

The ecological dynamics of microplastic (\u3c5 mm) are well documented in marine ecosystems, but the sources, abundance, and ecological role of microplastic in rivers are unknown and likely to be substantial. Microplastic fibers (e.g., synthetic fabrics) and pellets (e.g., abrasives in personal care products) are abundant in wastewater treatment plant (WWTP) effluent, and can serve as a point source of microplastic in rivers. The buoyancy, hydrophobic surface, and long transport distance of microplastic make it a novel substrate for the selection and dispersal of unique microbial assemblages. We measured microplastic concentration and bacterial assemblage composition on microplastic and natural surfaces upstream and downstream of WWTP effluent sites at nine rivers in Illinois, United States. Microplastic concentration was higher downstream of WWTP effluent outfall sites in all but two rivers. Pellets, fibers, and fragments were the dominant microplastic types, and polymers were identified as polypropylene, polyethylene, and polystyrene. Mean microplastic flux was 1,338,757 pieces per day, although the flux was highly variable among nine sites (min = 15,520 per day, max = 4,721,709 per day). High-throughput sequencing of 16S rRNA genes showed bacterial assemblage composition was significantly different among microplastic, seston, and water column substrates. Microplastic bacterial assemblages had lower taxon richness, diversity, and evenness than those on other substrates, and microplastic selected for taxa that may degrade plastic polymers (e.g., Pseudomonas) and those representing common human intestinal pathogens (e.g., Arcobacter). Effluent from WWTPs in rivers is an important component of the global plastic “life cycle,” and microplastic serves as a novel substrate that selects and transports distinct bacterial assemblages in urban rivers. Rates of microplastic deposition, consumption by stream biota, and the metabolic capacity of microplastic biofilms in rivers are unknown and merit further research