Seasonal profile of common pharmaceuticals in edible bivalve molluscs.

Pharmaceuticals are recognised as environmental contaminants of emerging concern (CECs) due to their increasing presence in the aquatic environment, along with high bioactivity linked to their therapeutic use. Therefore, information on environmental levels is urgently required. This study examined the presence of a range of common pharmaceuticals in oysters and mussels intended for human consumption from England and Wales using stable isotope dilution tandem mass spectrometry. A range of compounds were detected in bivalve tissue, with the Selective Serotonin Reuptake Inhibitor antidepressant sertraline being most abundant, reaching a maximum concentration of 22.1 ng/g wet weight shellfish tissue. Levels of all pharmaceuticals showed seasonal and geographical patterns. A dietary risk assessment revealed that the levels of pharmaceuticals identified in bivalve molluscs represent a clear hazard, but not a risk for the consumer. This study highlights the requirement for further monitoring of the presence of pharmaceuticals and other CECs in bivalve molluscs.

Scenarios of intermittent E. coli contamination from sewer overflows to shellfish growing waters: The Dart Estuary case study.

Sewage overflows (SOs) and Combined Sewer Overflows (CSOs) significantly contribute to the bacterial contamination of coastal waters, which is of especial concern for aquaculture, a growing industry worldwide. Hydrodynamic and water quality models were used to investigate impacts of CSO discharge frequency and duration, river discharge and tides on Escherichia coli levels at shellfish farming sites in the Dart Estuary (UK), being the employed methodology generally applicable. High E. coli contamination occurred during neap tides and high river discharges due to higher retention and lower bacterial decay. Synchronicity of CSO spills affected the duration of the pollution episodes rather than peak concentrations, more influenced by discharges of the neighbouring CSOs. During peak discharges, E. coli concentrations could be 10 times higher than during average flows. CSO spills were more frequent when rainfall was >20 mm. Model outputs combined with rainfall forecasts can indicate microbiological contamination risk in the aquaculture sites.

Strategies to reduce norovirus (NoV) contamination from oysters under depuration conditions.

Depuration of oysters can effectively reduce levels of E. coli, however, may not be effective in safeguarding against viral contamination (EFSA, 2012). These trials assess the removal of Norovirus Genogroups I and II (NoV GI and GII) and F + RNA bacteriophage genogroup II (FRNAP-II) from oysters under depuration using molecular and viability assay methods. Our results show consistently better removal of NoV GII compared with Nov GI. We found approximately 46% removal of NoV GII at 18 °C after 2 days and 60% after 5 days compared with a maximum of 16% NoV GI removal. Twice the rate of NoV GII removal was achieved at 18 °C compared with 8 °C after 5 days. Results suggest better NoV removal when depuration water salinity is close to that prevailing in the harvesting area. Trials investigating algal feeding, light/dark and disturbance from pump vibration did not show any significant effect. We found that FRNAP-II was more readily removed than NoV. No significant difference was found between the rate of removal (as measured by RT-qPCR) and inactivation (as measured by bioassay) of FRNAP-II. This indicates that reduction in FRNAP-II may be primarily due to physical removal (or destruction) rather than in situ inactivation of the virus.

Escherichia coli testing and enumeration in live bivalve shellfish - Present methods and future directions.

A wide variety of pathogenic agents such as bacteria, viruses and parasites can be greatly concentrated in filter feeding bivalve molluscan shellfish (BMS), that are grown in faecally contaminated waters. Human health risks associated with the consumption of BMS are also compounded by the traditional pattern of consuming them raw or lightly cooked. Because of these well-established food safety risks, food legislation such as that in Europe stipulates that BMS production areas are monitored for faecal contamination and classified accordingly. In this review we provide information regarding the background and use of methods for determining and quantifying Escherichia coli (E. coli) in shellfish matrices, focussing on the Most Probable Number (MPN) based approach. This review also discusses other techniques for determining E. coli in food matrices, as well as specific tests across a range of other food microbiology applications. This information draws on several sources: published peer-reviewed reports, data derived from proficiency testing/ring trials, depuration and challenge studies, as well as specific examples from BMS classification and long-term monitoring studies. We also provide a discussion on possible avenues for future direction regarding testing methods in this food microbiology sector.

Development of novel metabolite-responsive transcription factors via transposon-mediated protein fusion.

Naturally evolved metabolite-responsive biosensors enable applications in metabolic engineering, ranging from screening large genetic libraries to dynamically regulating biosynthetic pathways. However, there are many metabolites for which a natural biosensor does not exist. To address this need, we developed a general method for converting metabolite-binding proteins into metabolite-responsive transcription factors-Biosensor Engineering by Random Domain Insertion (BERDI). This approach takes advantage of an in vitro transposon insertion reaction to generate all possible insertions of a DNA-binding domain into a metabolite-binding protein, followed by fluorescence activated cell sorting to isolate functional biosensors. To develop and evaluate the BERDI method, we generated a library of candidate biosensors in which a zinc finger DNA-binding domain was inserted into maltose binding protein, which served as a model well-studied metabolite-binding protein. Library diversity was characterized by several methods, a selection scheme was deployed, and ultimately several distinct and functional maltose-responsive transcriptional biosensors were identified. We hypothesize that the BERDI method comprises a generalizable strategy that may ultimately be applied to convert a wide range of metabolite-binding proteins into novel biosensors for applications in metabolic engineering and synthetic biology.

Predicting the Dynamics and Heterogeneity of Genomic DNA Content within Bacterial Populations across Variable Growth Regimes.

For many applications in microbial synthetic biology, optimizing a desired function requires careful tuning of the degree to which various genes are expressed. One challenge for predicting such effects or interpreting typical characterization experiments is that in bacteria such as E. coli, genome copy number varies widely across different phases and rates of growth, which also impacts how and when genes are expressed from different loci. While such phenomena are relatively well-understood at a mechanistic level, our quantitative understanding of such processes is essentially limited to ideal exponential growth. In contrast, common experimental phenomena such as growth on heterogeneous media, metabolic adaptation, and oxygen restriction all cause substantial deviations from ideal exponential growth, particularly as cultures approach the higher densities at which industrial biomanufacturing and even routine screening experiments are conducted. To meet the need for predicting and explaining how gene dosage impacts cellular functions outside of exponential growth, we here report a novel modeling strategy that leverages agent-based simulation and high performance computing to robustly predict the dynamics and heterogeneity of genomic DNA content within bacterial populations across variable growth regimes. We show that by feeding routine experimental data, such as optical density time series, into our heterogeneous multiphasic growth simulator, we can predict genomic DNA distributions over a range of nonexponential growth conditions. This modeling strategy provides an important advance in the ability of synthetic biologists to evaluate the role of genomic DNA content and heterogeneity in affecting the performance of existing or engineered microbial functions.

Engineering Modular Biosensors to Confer Metabolite-Responsive Regulation of Transcription.

Efforts to engineer microbial factories have benefitted from mining biological diversity and high throughput synthesis of novel enzymatic pathways, yet screening and optimizing metabolic pathways remain rate-limiting steps. Metabolite-responsive biosensors may help to address these persistent challenges by enabling the monitoring of metabolite levels in individual cells and metabolite-responsive feedback control. We are currently limited to naturally evolved biosensors, which are insufficient for monitoring many metabolites of interest. Thus, a method for engineering novel biosensors would be powerful, yet we lack a generalizable approach that enables the construction of a wide range of biosensors. As a step toward this goal, we here explore several strategies for converting a metabolite-binding protein into a metabolite-responsive transcriptional regulator. By pairing a modular protein design approach with a library of synthetic promoters and applying robust statistical analyses, we identified strategies for engineering biosensor-regulated bacterial promoters and for achieving design-driven improvements of biosensor performance. We demonstrated the feasibility of this strategy by fusing a programmable DNA binding motif (zinc finger module) with a model ligand binding protein (maltose binding protein), to generate a novel biosensor conferring maltose-regulated gene expression. This systematic investigation provides insights that may guide the development of additional novel biosensors for diverse synthetic biology applications.

A sensitive switch for visualizing natural gene silencing in single cells.

RNA interference is a natural gene expression silencing system that appears throughout the tree of life. As the list of cellular processes linked to RNAi grows, so does the demand for tools to accurately measure RNAi dynamics in living cells. We engineered a synthetic RNAi sensor that converts this negative regulatory signal into a positive output in living mammalian cells, thereby allowing increased sensitivity and activation. Furthermore, the circuit's modular design allows potentially any microRNA of interest to be detected. We demonstrated that the circuit responds to an artificial microRNA and becomes activated when the RNAi target is replaced by a natural microRNA target (miR-34) in U2OS osteosarcoma cells. Our studies extend the application of rationally designed synthetic switches to RNAi, providing a sensitive way to visualize the dynamics of RNAi activity rather than just the presence of miRNA molecules.

Dynamic coordination of innate immune signaling and insulin signaling regulates systemic responses to localized DNA damage.

Metazoans adapt to changing environmental conditions and to harmful challenges by attenuating growth and metabolic activities systemically. Recent studies in mice and flies indicate that endocrine signaling interactions between insulin/IGF signaling (IIS) and innate immune signaling pathways are critical for this adaptation, yet the temporal and spatial hierarchy of these signaling events remains elusive. Here, we identify and characterize a program of signaling interactions that regulates the systemic response of the Drosophila larva to localized DNA damage. We provide evidence that epidermal DNA damage induces an innate immune response that is kept in check by systemic repression of IIS activity. IIS repression induces NFκB/Relish signaling in the fat body, which is required for recovery of IIS activity in a second phase of the systemic response to DNA damage. This systemic response to localized DNA damage thus coordinates growth and metabolic activities across tissues, ensuring growth homeostasis and survival of the animal.