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Multiple heavy metal contamination is an increasingly common global problem. Heavy metals have the potential to disrupt microbially mediated biogeochemical cycling. However, systems-level studies on the effects of combinations of heavy metals on bacteria are lacking. For this study, we focused on the Oak Ridge Reservation (ORR; Oak Ridge, TN, USA) subsurface which is contaminated with several heavy metals and high concentrations of nitrate. Using a native Bacillus cereus isolate that represents a dominant species at this site, we assessed the combined impact of eight metal contaminants, all at site-relevant concentrations, on cell processes through an integrated multi-omics approach that included discovery proteomics, targeted metabolomics, and targeted gene-expression profiling. The combination of eight metals impacted cell physiology in a manner that could not have been predicted from summing phenotypic responses to the individual metals. Exposure to the metal mixture elicited a global iron starvation response not observed during individual metal exposures. This disruption of iron homeostasis resulted in decreased activity of the iron-cofactor-containing nitrate and nitrite reductases, both of which are important in biological nitrate removal at the site. We propose that the combinatorial effects of simultaneous exposure to multiple heavy metals is an underappreciated yet significant form of cell stress in the environment with the potential to disrupt global nutrient cycles and to impede bioremediation efforts at mixed waste sites. Our work underscores the need to shift from single- to multi-metal studies for assessing and predicting the impacts of complex contaminants on microbial systems.

Globally, multiple heavy metal contamination is an increasingly common problem. As heavy metals have the potential to disrupt microbially-mediated biogeochemical cycling, it is critical to understand their impact on microbial physiology. However, systems-level studies on the effects of a combination of heavy metals on bacteria are lacking. Here, we use a native Bacillus cereus isolate from the subsurface of the Oak Ridge Reservation (ORR; Oak Ridge, TN, USA) — representing a highly abundant species at the site— to assess the combined impact of eight metal contaminants. Using this metal mixture and individual metals, all at concentrations based on the ORR site geochemistry, we performed growth experiments and proteomic analyses of the B. cereus strain, in combination with targeted MS-based metabolomics and gene expression profiling. The combination of eight metals impacts cell physiology in a manner that could not have been predicted from summing phenotypic responses to the individual metals. Specifically, exposure to the metal mixture elicited global iron starvation responses not observed in any of the individual metal treatments. As nitrate is also a significant contaminant at the ORR site and nitrate and nitrite reductases are iron-containing enzymes, we also examined the effects of the metal mixture on reduction of nitrogen oxides. We found that the metal mixture inhibits the activity of these enzymes through a combination of direct enzymatic damage and post-transcriptional and post-translational regulation. Altogether, these data suggest that metal mixture studies are critical for understanding how multiple rather than individual metals influence microbial processes in the environment.

Multiple heavy metal contamination is an increasingly common global problem. Heavy metals have the potential to disrupt microbially mediated biogeochemical cycling. However, systems-level studies on the effects of combinations of heavy metals on bacteria are lacking. For this study, we focused on the Oak Ridge Reservation (ORR; Oak Ridge, TN, USA) subsurface which is contaminated with several heavy metals and high concentrations of nitrate. Using a native Bacillus cereus isolate that represents a dominant species at this site, we assessed the combined impact of eight metal contaminants, all at site-relevant concentrations, on cell processes through an integrated multi-omics approach that included discovery proteomics, targeted metabolomics, and targeted gene-expression profiling. The combination of eight metals impacted cell physiology in a manner that could not have been predicted from summing phenotypic responses to the individual metals. Exposure to the metal mixture elicited a global iron starvation response not observed during individual metal exposures. This disruption of iron homeostasis resulted in decreased activity of the iron-cofactor-containing nitrate and nitrite reductases, both of which are important in biological nitrate removal at the site. We propose that the combinatorial effects of simultaneous exposure to multiple heavy metals is an underappreciated yet significant form of cell stress in the environment with the potential to disrupt global nutrient cycles and to impede bioremediation efforts at mixed waste sites. Our work underscores the need to shift from single- to multi-metal studies for assessing and predicting the impacts of complex contaminants on microbial systems.

Surface-enhanced Raman scattering (SERS) is one of the most effective methods for applications in optical sensors and chemical analysis. However, control of the optimal conditions of substrates and the selection of chemical probes are two major challenges which have yet to be solved. In this work, using a simple seeded growth method, nanoparticles with different sizes and shapes were produced. The SERS enhancement factor for each nanoparticle size and shape obtained was evaluated based on three different analytes, methylene blue, Nile blue A and Rhodamine B. We found a maximum enhancement factor on the order of 106 for the case of silver nanorods and Rhodamine B. Considering the SERS performance for silver nanospheres, we observed a systematic increase in the sequence methylene blue-Nile blue A-Rhodamine B. The reason behind the enhanced efficiency is that the maximum of the surface plasmon resonance band of Rhodamine B is the closest to the Raman excitation wavelength. The study also demonstrates that a decrease in size of spherical nanoparticles can lead to an increased enhancement, resulting from a larger surface area for a smaller particle size. Compared with silver nanospheres, silver nanorods yielded a better SERS enhancement factor, as a result of shape anisotropy which significantly enhance the local field hotspots. For low concentration, the intensity of Raman bands increases linearly with increasing dye concentration, which could be useful for applications involving chemical sensors.

This paper proposes a novel time- and energy-efficient identification protocol for dense radio frequency identification (RFID) systems. The protocol is designed based on a conventional $M$ -ary collision tree, where tags involving a collision are classified into other $M$ subtrees. We additionally incorporate a newly designed transmission mechanism, by which each tag only responds to the reader by a small number of bits for a collision detection. The mechanism relies on a collision window supported by tag cardinality estimation, and the Manchester encoding, which is widely used for RFID systems. Thanks to the mechanism, the number of bits transmitted by tags can be significantly reduced, which improves the overall system performance in terms of both time and energy consumption. Theoretical analysis and computer simulation are performed to validate the correctness of the mechanism. The obtained results are compared with those of conventional protocols, which confirm the effectiveness of the proposed protocol.

This paper proposes a novel time- and energy-efficient identification protocol in dense radio frequency identifi-cation (RFID) systems. The protocol is based on the conventional M-ary collision tree (MCT) where tags involving a collision are classified into other M sub-trees. Nevertheless, different from the MCT, we design a transmission mechanism by which each tag only responds to the reader by a small number of bits for a collision detection. The mechanism is relied on a collision window and Manchester encoding that are widely used for RFID systems. Thanks to the mechanism, the number of bits transmitted by tags is significantly reduced, which improves the overall system performance in terms of both time and energy consumption. Performance analysis is investigated to validate the correctness of the mechanism. Computer simulations are also performed using Monte-Carlo method. The obtained results are then compared with those of the MCT to confirm the effectiveness of the proposed protocol.

The addition of water and methanol to the carbonyl substituents in the dicationic bis(arene)ruthenium complexes [(p-cymene)Ru(C6H5CHO)][OTf]2 (1) and [(p-cymene)Ru(C6H5C(O)CH3)][OTf]2 (2) is remarkably favorable-the equilibrium constants for these reactions are 1 million times greater than those for uncomplexed benzaldehyde and acetophenone. The addition of methanol to the carbonyl group in the o-anisaldehyde complex, [(p-cymene)Ru(C6H4{OCH3}CHO)][OTf]2 (6), occurs with a high degree of kinetic selectivity (94% de).