Pseudomonas pseudoalcaligenes KF707 is naturally resistant to the toxic metalloid tellurite, but the mechanisms of resistance are not known. In this study we report the isolation of a KF707 mutant (T5) with hyperresistance to tellurite. In order to characterize the bacterial response and the pathways leading to tolerance, we utilized Phenotype MicroArray technology (Biolog) and a metabolomic technique based on nuclear magnetic resonance spectroscopy. The physiological states of KF707 wild-type and T5 cells exposed to tellurite were also compared in terms of viability and reduced thiol content. Our analyses showed an extensive change in metabolism upon the addition of tellurite to KF707 cultures as well as different responses when the wild-type and T5 strains were compared. Even in the absence of tellurite, T5 cells displayed a "poised" physiological status, primed for tellurite exposure and characterized by altered intracellular levels of glutathione, branched-chain amino acids, and betaine, along with increased resistance to other toxic metals and metabolic inhibitors. We conclude that hyperresistance to tellurite in P. pseudoalcaligenes KF707 is correlated with the induction of the oxidative stress response, resistance to membrane perturbation, and reconfiguration of cellular metabolism.Genomic studies have provided a rationale for the ability of bacteria to adapt to environmental changes or adverse conditions, such as exposure to toxic metals (8). Although valuable, these investigations have shortcomings for the assignment of regulatory or metabolic functions to novel genes (23). As a consequence, transcriptomics, proteomics, and metabolomic analyses need to be undertaken, in order to measure the functional cellular units in response to genetic as well as environmental perturbations. The metabolome is defined as the quantitative collection of the low-molecular-weight molecules (metabolites) required for growth and normal function of a cell (24). On the basis of this definition, metabolomics is the characterization and quantification of the cellular metabolome and provides a snapshot of the metabolic status of a cell in a particular physiological condition (14). Nuclear magnetic resonance (NMR) spectroscopy is widely used in metabolomics, as it allows for the identification and quantification of a broad range of cellular metabolites simultaneously (15).

Sinorhizobium meliloti is a soil bacterium that fixes atmospheric nitrogen in plant roots. The high genetic diversity of its natural populations has been the subject of extensive analysis. Recent genomic studies of several isolates revealed a high content of variable genes, suggesting a correspondingly large phenotypic differentiation among strains of S. meliloti. Here, using the Phenotype MicroArray (PM) system, hundreds of different growth conditions were tested in order to compare the metabolic capabilities of the laboratory reference strain Rm1021 with those of four natural S. meliloti isolates previously analyzed by comparative genomic hybridization (CGH). The results of PM analysis showed that most phenotypic differences involved carbon source utilization and tolerance to osmolytes and pH, while fewer differences were scored for nitrogen, phosphorus, and sulfur source utilization. Only the variability of the tested strain in tolerance to sodium nitrite and ammonium sulfate of pH 8 was hypothesized to be associated with the genetic polymorphisms detected by CGH analysis. Colony and cell morphologies and the ability to nodulate Medicago truncatula plants were also compared, revealing further phenotypic diversity. Overall, our results suggest that the study of functional (phenotypic) variability of S. meliloti populations is an important and complementary step in the investigation of genetic polymorphism of rhizobia and may help to elucidate rhizobial evolutionary dynamics, including adaptation to diverse environments.Sinorhizobium meliloti is a soil bacterium belonging to the Rhizobiales group of the Alphaproteobacteria subdivision, which includes pathogens, such as Bartonella and Brucella, and several plant-associated bacteria of relevant agricultural importance, such as Agrobacterium, Ochrobactrum, Bradyrhizobium, Mesorhizobium, and Rhizobium (21). S. meliloti forms nitrogenfixing nodules on the roots of leguminous plants of the genera Medicago, Melilotus, and Trigonella, and it is probably the beststudied model system for the rhizobium-legume symbiosis. S. meliloti is distributed worldwide and is present in many soil types, both in association with legumes and in free-living form (40). The ubiquitous occurrence of this species suggested a wide metabolic capability allowing adaptation to very different environmental and nutritional conditions. S. meliloti has been the subject of extensive genetic, biochemical, and metabolic research (25). The sequencing of the strain Rm1021 genome (4, 11, 17, 18) provided a solid foundation for a number of molecular studies of the genetic basis of plant-bacterium interactions and of the response of S. meliloti to environmental stimuli. Moreover, the genetic diversity of natural populations of S. meliloti has been the subject of extensive analyses (1-3, 8, 12, 24, 38, 42). These investigations showed that S. meliloti populations are very diverse and that S. meliloti strains harbor a high number of different mobile genetic elements, such as insertion sequences, transposons...

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Transcripts of ribosomal RNA have been used for assessing the structure and dynamics of active bacterial populations; however, it remains unclear whether the information provided by community profiling derived from RNA is different from that derived from DNA, particularly when a selective pressure is applied on the bacterial community. In the present work, terminal-restriction fragment length polymorphism (T-RFLP) community profiles based on DNA and RNA extracted from soil microcosms treated with a toxic concentration of chromate were compared. Microcosms of a nonpolluted agricultural soil and of a heavy-metal-rich soil (serpentine) were treated with chromate and DNA and RNA were extracted. T-RFLP analysis was performed on amplified and retro-amplified 16SrRNA gene sequences, and band profiles obtained from samples of DNA and of RNA were compared. Some of the T-RFLP bands, identified as peculiar peaks in the profiles, were cloned and sequenced for taxonomic interpretation. Results indicated that: (1) community profiles derived from RNA and DNA were partly overlapping; (2) there was a strong correlation between the dynamics shown by RNA- and DNA-based T-RFLP profiles; (3) chromate addition exerted a clear effect on both agricultural and serpentine soil bacterial communities, either at the DNA and at the RNA level; however, the profiles derived from RNA showed sharper differences between treated and control samples than that of DNA-based profiles.