The copper-resistance determinant (pco) of Escherichia coli plasmid pRJ1004 was cloned and sequenced. Tn1000 transposon mutagenesis identified four complementation groups, mutations in any of which eliminated copper resistance. DNA sequence analysis showed that the four complementation groups contained six open reading frames, designated pco-ABCDRS. The protein product sequences derived from the nucleotide sequence show close homology between this copper-resistance system and the cop system of a plasmid pPT23D of Pseudomonas syringae pv. tomato. The PcoR and PcoS protein sequences show homology to the family of two-component sensor/responder phosphokinase regulatory systems. A seventh reading frame (pcoE) was identified from DNA sequence data, and lies downstream of a copper-regulated promoter. Transport assays with 64Cu(II) showed that the resistant cells containing the plasmid had reduced copper accumulation during the log phase of growth, while increased accumulation had previously been observed during stationary phase. Chromosomal mutants defective in cellular copper management were obtained and characterized. In two of these mutants pco resistance was rendered totally inactive, whilst in another two mutants pco complemented the defective genes. These data indicate that plasmid-borne copper resistance in E. coli is linked with chromosomal systems for copper management.

The cutA locus, presumably involved in copper tolerance in Escherichia coli, was characterized by a mutation leading to copper sensitivity. Copper-accumulation measurements with radioactive 64Cu2+ showed increased uptake by cutA copper-sensitive mutant cells, and reduced uptake when the cutA mutation was complemented in trans. The locus was mapped using complementation of the cutA mutant to partial copper tolerance with wild-type chromosomal fragments. The 3.2 kb DNA region involved in cutA was sequenced and analysed, revealing three significant open reading frames, none of which had been previously published. The products of all three open reading frames were identified, when synthesized with the T7 phage promoter expression system, as polypeptides of about 50 kDa, 24 kDa, and 13 kDa, consistent with the sizes predicted from the DNA sequences. The 50 kDa and 24 kDa polypeptides were found in the bacterial inner membrane, and the 13 kDa polypeptide with the cytoplasmic fraction. In addition to being required for copper tolerance, cutA affects tolerance levels to zinc, nickel, cobalt and cadmium salts. Transcriptional fusions of cutA with the lux operon showed induction by copper, zinc, nickel, cobalt and, to a lesser extent, cadmium, manganese and silver salts.

No abstract

Bacterial resistances to metals are heterogeneous in both their genetic and biochemical bases. Metal resistance may be chromosomally-, plasmid- or transposon-encoded, and one or more genes may be involved: at the biochemical level at least six different mechanisms are responsible for resistance. Various types of resistance mechanisms can occur singly or in combination and for a particular metal different mechanisms of resistance can occur in the same species. To understand better the diverse responses of bacteria to metal ion challenge we have constructed a qualitative model for the selection of metal resistance in bacteria. How a bacterium becomes resistant to a particular metal depends on the number and location of cellular components sensitive to the specific metal ion. Other important selective factors include the nature of the uptake systems for the metal, the role and interactions of the metal in the normal metabolism of the cell and the availability of plasmid (or transposon) encoded resistance mechanisms. The selection model presented is based on the interaction of these factors and allows predictions to be made about the evolution of metal resistance in bacterial populations. It also allows prediction of the genetic basis and of mechanisms of resistance which are in substantial agreement with those in well-documented populations. The interaction of, and selection for resistance to, toxic substances in addition to metals, such as antibiotics and toxic analogues, involve similar principles to those concerning metals. Potentially, models for selection of resistance to any substance can be derived using this approach.