Metallic copper as an antimicrobial surface

Bacteria, yeasts, and viruses are rapidly killed on metallic copper surfaces, and the term "contact killing" has been coined for this process. While the phenomenon was already known in ancient times, it is currently receiving renewed attention. This is due to the potential use of copper as an antibacterial material in health care settings. Contact killing was observed to take place at a rate of at least 7 to 8 logs per hour, and no live microorganisms were generally recovered from copper surfaces after prolonged incubation. The antimicrobial activity of copper and copper alloys is now well established, and copper has recently been registered at the U.S. Environmental Protection Agency as the first solid antimicrobial material. In several clinical studies, copper has been evaluated for use on touch surfaces, such as door handles, bathroom fixtures, or bed rails, in attempts to curb nosocomial infections. In connection to these new applications of copper, it is important to understand the mechanism of contact killing since it may bear on central issues, such as the possibility of the emergence and spread of resistant organisms, cleaning procedures, and questions of material and object engineering. Recent work has shed light on mechanistic aspects of contact killing. These findings will be reviewed here and juxtaposed with the toxicity mechanisms of ionic copper. The merit of copper as a hygienic material in hospitals and related settings will also be discussed.

Structure and function of CinD (YtjD) of Lactococcus lactis, a copper-induced nitroreductase involved in defense against oxidative stress

In Lactococcus lactis IL1403, 14 genes are under the control of the copper-inducible CopR repressor. This so-called CopR regulon encompasses the CopR regulator, two putative CPx-type copper ATPases, a copper chaperone, and 10 additional genes of unknown function. We addressed here the function of one of these genes, ytjD, which we renamed cinD (copper-induced nitroreductase). Copper, cadmium, and silver induced cinD in vivo, as shown by real-time quantitative PCR. A knockout mutant of cinD was more sensitive to oxidative stress exerted by 4-nitroquinoline-N-oxide and copper. Purified CinD is a flavoprotein and reduced 2,6-dichlorophenolindophenol and 4-nitroquinoline-N-oxide with k(cat) values of 27 and 11 s(-1), respectively, using NADH as a reductant. CinD also exhibited significant catalase activity in vitro. The X-ray structure of CinD was resolved at 1.35 A and resembles those of other nitroreductases. CinD is thus a nitroreductase which can protect L. lactis against oxidative stress that could be exerted by nitroaromatic compounds and copper.

Copper induction of lactate oxidase of Lactococcus lactis: a novel metal stress response

Lactococcus lactis IL1403, a lactic acid bacterium widely used for food fermentation, is often exposed to stress conditions. One such condition is exposure to copper, such as in cheese making in copper vats. Copper is an essential micronutrient in prokaryotes and eukaryotes but can be toxic if in excess. Thus, copper homeostatic mechanisms, consisting chiefly of copper transporters and their regulators, have evolved in all organisms to control cytoplasmic copper levels. Using proteomics to identify novel proteins involved in the response of L. lactis IL1403 to copper, cells were exposed to 200 muM copper sulfate for 45 min, followed by resolution of the cytoplasmic fraction by two-dimensional gel electrophoresis. One protein strongly induced by copper was LctO, which was shown to be a NAD-independent lactate oxidase. It catalyzed the conversion of lactate to pyruvate in vivo and in vitro. Copper, cadmium, and silver induced LctO, as shown by real-time quantitative PCR. A copper-regulatory element was identified in the 5' region of the lctO gene and shown to interact with the CopR regulator, encoded by the unlinked copRZA operon. Induction of LctO by copper represents a novel copper stress response, and we suggest that it serves in the scavenging of molecular oxygen.

Copper and human health: biochemistry, genetics, and strategies for modeling dose-response relationships

Copper (Cu) and its alloys are used extensively in domestic and industrial applications. Cu is also an essential element in mammalian nutrition. Since both copper deficiency and copper excess produce adverse health effects, the dose-response curve is U-shaped, although the precise form has not yet been well characterized. Many animal and human studies were conducted on copper to provide a rich database from which data suitable for modeling the dose-response relationship for copper may be extracted. Possible dose-response modeling strategies are considered in this review, including those based on the benchmark dose and categorical regression. The usefulness of biologically based dose-response modeling techniques in understanding copper toxicity was difficult to assess at this time since the mechanisms underlying copper-induced toxicity have yet to be fully elucidated. A dose-response modeling strategy for copper toxicity was proposed associated with both deficiency and excess. This modeling strategy was applied to multiple studies of copper-induced toxicity, standardized with respect to severity of adverse health outcomes and selected on the basis of criteria reflecting the quality and relevance of individual studies. The use of a comprehensive database on copper-induced toxicity is essential for dose-response modeling since there is insufficient information in any single study to adequately characterize copper dose-response relationships. The dose-response modeling strategy envisioned here is designed to determine whether the existing toxicity data for copper excess or deficiency may be effectively utilized in defining the limits of the homeostatic range in humans and other species. By considering alternative techniques for determining a point of departure and low-dose extrapolation (including categorical regression, the benchmark dose, and identification of observed no-effect levels) this strategy will identify which techniques are most suitable for this purpose. This analysis also serves to identify areas in which additional data are needed to better define the characteristics of dose-response relationships for copper-induced toxicity in relation to excess or deficiency.

Is differentiation of frequently encountered foreign bodies in corpses possible by Hounsfield density measurement?

The radiological determination of foreign objects in corpses can be difficult if they are fragmented or deformed. With multislice computed tomography, radiodensities--referred to as Hounsfield units (HU)--can be measured. We examined the possibility of differentiating 21 frequently occurring foreign bodies, such as metals, rocks, and different manmade materials by virtue of their HU values. Gold, steel, and brass showed mean HU values of 30671-30710 (upper measurable limit), mean HU values for steel, silver, copper, and limestone were 20346, 16949, 14033, and 2765, respectively. The group consisting of objects, such as aluminum, tarmac, car front-window glass, and other rocks, displayed mean HU values of 2329-2131 HU. The mean HU value of bottle glass and car side-window glass was 2088, whereas windowpane glass was 493. HU value determination may therefore help in preautopsy differentiation between case-relevant and irrelevant foreign bodies and thus be useful for autopsy planning and extraction of the objects in question.

Elemental and Lead Isotopic Data of Copper Finds from the Singen Cemetery, Germany – a Methodological Approach to Investigate Early Bronze Age Trade Networks

We report a trace element - Pb isotope analytical (LIA) database on the "Singen Copper", a peculiar type of copper found in the North Alpine realm, from its type locality, the Early Bronze Age Singen Cemetery (Germany). What distinguishes “Singen Copper” from other coeval copper types? (i) is it a discrete metal lot with a uniform provenance (if so, can its provenance be constrained)? (ii) was it manufactured by a special, unique metallurgical process that can be discriminated from others? Trace element concentrations can give clues on the ore types that were mined, but they can be modified (more or less intentionally) by metallurgical operations. A more robust indicator are the ratios of chemically similar elements (e.g. Co/Ni, Bi/Sb, etc.), since they should remain nearly constant during metallurgical operations, and are expected to behave homogeneously in each mineral of a given mining area, but their partition amongst the different mineral species is known to cause strong inter-element fractionations. We tested the trace element ratio pattern predicted by geochemical arguments on the Brixlegg mining area. Brixlegg itself is not compatible with the Singen Copper objects, and we only report it because it is a rare instance of a mining area for which sufficient trace element analyses are available in the literature. We observe that As/Sb in fahlerz varies by a factor 1.8 above/below median; As/Sb in enargite varies by a factor of 2.5 with a 10 times higher median. Most of the 102 analyzed metal objects from Singen are Sb-Ni-rich, corresponding to “antimony-nickel copper” of the literature. Other trace element concentrations vary by > 100 times, ratios by factors > 50. Pb isotopic compositions are all significantly different from each other. They do not form a single linear array and require > 3 ore batches that certainly do not derive from one single mining area. Our data suggest a heterogeneous provenance of “Singen copper”. Archaeological information limits the scope to Central European sources. LIA requires a diverse supply network from many mining localities, including possibly Brittany. Trace element ratios show more heterogeneity than LIA; this can be explained either by deliberate selection of one particular ore mineral (from very many sources) or by processing of assorted ore minerals from a smaller number of sources, with the unintentional effect that the quality of the copper would not be constant, as the metallurgical properties of alloys would vary with trace element concentrations.