Arsenic and chromium resistance mechanisms in the Micrococcus luteus group

High arsenic(As)and chromium(Cr)concentrations are currently receiving attention because of their negative effects on the environment and human health.Microorganisms inhabiting contaminated environments have developed resistance mechanisms against the toxicity of these pollutants.Indeed,members of the bacterial genus Micrococcus have been isolated from different toxic metal-contaminated environments;however,knowledge concerning its resistance mechanisms to As and Cr toxicity remains limited.Micrococcus luteus strains(An24,Mh,NE2TL6,and NE2TTS4)were isolated from the endosphere and soil of two heavy metal-contaminated sites in Mexico to identify differences in the resistance mechanisms by the M.luteus group.The strains were resistant to As(As^(3+)and As^(5+)),chromate,dichromate,cobalt,copper,nickel,and zinc.Genome analysis indicated that the heavy metal-resistant strains(An24,Mh,NE2TL6,and NE2TTS4)could be assigned to the M.luteus group and had more heavy metal-resistant genes(transporters,chaperones,and enzymes)compared to reference strains of the M.luteus group,M.luteus NCTC 2665^(T)and Micrococcus endophyticus JCM 16951^(T).The resistant bacteria were able to biotransform As^(3+)and As^(5+)through a carbon source-dependent mechanism.The biotransformation of As5+was potentially carried out in the cytoplasm through a thioredoxin-dependent pathway,which may be coupled with biosorption.A qualitative analysis of organic acids(OAs)identified a change in the OA profile of the metal-resistant strains that was As-or Cr-dependent.Our genomic and phenotypic findings suggest that the four M.luteus group strains evaluated in the current study have developed resistance mechanisms that may enable their survival in contaminated sites.

Application of formal languages in polynomial transformations of instances between NP-complete problems

We propose the usage of formal languages for expressing instances of NP-complete problems for their application in polynomial transformations. The proposed approach, which consists of using formal language theory for polynomial transformations, is more robust, more practical, and faster to apply to real problems than the theory of polynomial transformations. In this paper we propose a methodology for transforming instances between NP-complete problems, which differs from Garey and Johnson's. Unlike most transformations which are used for proving that a problem is NP-complete based on the NP-completeness of another problem, the proposed approach is intended for extrapolating some known characteristics, phenomena, or behaviors from a problem A to another problem B. This extrapolation could be useful for predicting the performance of an algorithm for solving B based on its known performance for problem A, or for taking an algorithm that solves A and adapting it to solve B.