The aim of the study was to determine the potential of community-level physiological profiles (CLPPs) methodology as an assay for characterization of the metabolic diversity of wastewater samples and to link the metabolic diversity patterns to efficiency of select onsite biological wastewater facilities. Metabolic fingerprints obtained from the selected samples were used to understand functional diversity implied by the carbon substrate shifts. Three different biological facilities of onsite wastewater treatment were evaluated: fixed bed reactor (technology A), trickling filter/biofilter system (technology B), and aerated filter system (the fluidized bed reactor, technology C). High similarities of the microbial community functional structures were found among the samples from the three onsite wastewater treatment plants (WWTPs), as shown by the diversity indices. Principal components analysis (PCA) showed that the diversity and CLPPs of microbial communities depended on the working efficiency of the wastewater treatment technologies. This study provided an overall picture of microbial community functional structures of investigated samples in WWTPs and discerned the linkages between microbial communities and technologies of onsite WWTPs used. The results obtained confirmed that metabolic profiles could be used to monitor treatment processes as valuable biological indicators of onsite wastewater treatment technologies efficiency. This is the first step toward understanding relations of technology types with microbial community patterns in raw and treated wastewaters.

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The scope of this study was to apply the Biolog system to identify and characterize a Serratia strain isolated from the surface of black plastic pieces which constitute the fluidized bed filter (onsite wastewater technology, OSWT). The preliminary isolation of the strain was done in the medium with tetracycline at a 16 mg/l concentration. To characterize the isolated strain, the following Biolog methods were applied: (1) EcoPlates microplates for evaluation of physiological profiling, (2) GEN III OmniLog® ID System for identification of the isolate, and (3) phenotypic microarrays (PM) technology for evaluation of sensitivity to antibiotics (PM11 and PM12). Results were recorded using the original OmniLog® software. The Serratia strain was identified as Serratia marcescens ss marcescens with similarity index 0.569. The same identification was obtained by the 16S rDNA analysis. PM analysis showed an enhancement of phenotype (resistance or growth) of this strain to 35 antibiotics. The loss of phenotype (sensitivity or non-growth) was observed only for 5 antibiotics: lomefloxacin (0.4 µg/ml), enoxacin (0.9 µg/ml), nalidixic acid (18.0 µg/ml), paromomycin (25.0 µg/ml) and novobiocin (1100 µg/ml). This study acknowledges that the methods proposed by the Biolog system allow correct and complete identification and characterization of the microbes isolated from different environments. Phenotypic microarrays could be successfully used as a new tool for identification of the multi-antibiotic resistance of bacteria and for determination of the minimal inhibition concentrations (MIC).

The scope of the study was to apply Phenotype Biolog MicroArray (PM) technology to test the antibiotic sensitivity of the bacterial strains isolated from on-site wastewater treatment facilities. In the first step of the study, the percentage values of resistant bacteria from total heterotrophic bacteria growing on solid media supplemented with various antibiotics were determined. In the untreated wastewater, the average shares of kanamycin-, streptomycin-, and tetracycline-resistant bacteria were 53, 56, and 42%, respectively. Meanwhile, the shares of kanamycin-, streptomycin-, and tetracycline-resistant bacteria in the treated wastewater were 39, 33, and 29%, respectively. To evaluate the antibiotic susceptibility of the bacteria present in the wastewater, using the phenotype microarrays (PMs), the most common isolates from the treated wastewater were chosen: Serratia marcescens ss marcescens, Pseudomonas fluorescens, Stenotrophomonas maltophilia, Stenotrophomonas rhizophila, Microbacterium flavescens, Alcaligenes faecalis ss faecalis, Flavobacterium hydatis, Variovorax paradoxus, Acinetobacter johnsonii, and Aeromonas bestiarum. The strains were classified as multi-antibiotic-resistant bacteria. Most of them were resistant to more than 30 antibiotics from various chemical classes. Phenotype microarrays could be successfully used as an additional tool for evaluation of the multi-antibiotic resistance of environmental bacteria and in preliminary determination of the range of inhibition concentration.