An evaluation of primers for detecting denitrifiers via their functional genes.

Microbial populations provide nitrogen cycling ecosystem services at the nexus of agriculture, environmental quality and climate change. Denitrification, in particular, impacts socio-environmental systems in both positive and negative ways, through reduction of aquatic and atmospheric nitrogen pollution, but also reduction of soil fertility and production of greenhouse gases. However, denitrification rates are quite variable in time and space, and therefore difficult to model. Microbial ecology is working to improve the predictive ecology of denitrifiers by quantifying and describing the diversity of microbial functional groups. However, metagenomic sequencing has revealed previously undescribed diversity within these functional groups, and highlighted a need to reevaluate coverage of existing DNA primers for denitrification functional genes. We provide here a comprehensive in silico evaluation of primer sets that target diagnostic genes in the denitrification pathway. This analysis makes use of current DNA sequence data available for each functional gene. It contributes a comparative analysis of the strengths and limitations of each primer set for describing denitrifier functional groups. This analysis identifies genes for which development of new tools is needed, and aids in interpretation of existing datasets, both of which will facilitate application of molecular methods to further develop the predictive ecology of denitrifiers.

Evaluating the Development of Biocatalytic Technology for the Targeted Removal of Perchlorate from Drinking Water.

Removing micropollutants is challenging in part because of their toxicity at low concentrations. A biocatalytic approach could harness the high affinity of enzymes for their substrates to address this challenge. The potential of biocatalysis relative to mature (nonselective ion exchange, selective ion exchange, and whole-cell biological reduction) and emerging (catalysis) perchlorate-removal technologies was evaluated through a quantitative sustainable design framework, and research objectives were prioritized to advance economic and environmental sustainability. In its current undeveloped state, the biocatalytic technology was approximately 1 order of magnitude higher in cost and environmental impact than nonselective ion exchange. Biocatalyst production was highly correlated with cost and impact. Realistic improvement scenarios targeting biocatalyst yield, biocatalyst immobilization for reuse, and elimination of an electron shuttle could reduce total costs to $0.034 m-3 and global warming potential (GWP) to 0.051 kg CO2 eq m-3: roughly 6.5% of cost and 7.3% of GWP of the background from drinking water treatment and competitive with the best performing technology, selective ion exchange. With less stringent perchlorate regulatory limits, ion exchange technologies had increased cost and impact, in contrast to biocatalytic and catalytic technologies. Targeted advances in biocatalysis could provide affordable and sustainable treatment options to protect the public from micropollutants.

Antibiotics and Antibiotic Resistance in Agroecosystems: State of the Science.

We propose a simple causal model depicting relationships involved in dissemination of antibiotics and antibiotic resistance in agroecosystems and potential effects on human health, functioning of natural ecosystems, and agricultural productivity. Available evidence for each causal link is briefly summarized, and key knowledge gaps are highlighted. A lack of quantitative estimates of human exposure to environmental bacteria, in general, and antibiotic-resistant bacteria, specifically, is a significant data gap hindering the assessment of effects on human health. The contribution of horizontal gene transfer to resistance in the environment and conditions that might foster the horizontal transfer of antibiotic resistance genes into human pathogens also need further research. Existing research has focused heavily on human health effects, with relatively little known about the effects of antibiotics and antibiotic resistance on natural and agricultural ecosystems. The proposed causal model is used to elucidate gaps in knowledge that must be addressed by the research community and may provide a useful starting point for the design and analysis of future research efforts.

Seasonal Patterns in Microbial Community Composition in Denitrifying Bioreactors Treating Subsurface Agricultural Drainage.

Denitrifying bioreactors, consisting of water flow control structures and a woodchip-filled trench, are a promising approach for removing nitrate from agricultural subsurface or tile drainage systems. To better understand the seasonal dynamics and the ecological drivers of the microbial communities responsible for denitrification in these bioreactors, we employed microbial community "fingerprinting" techniques in a time-series examination of three denitrifying bioreactors over 2 years, looking at bacteria, fungi, and the denitrifier functional group responsible for the final step of complete denitrification. Our analysis revealed that microbial community composition responds to depth and seasonal variation in moisture content and inundation of the bioreactor media, as well as temperature. Using a geostatistical analysis approach, we observed recurring temporal patterns in bacterial and denitrifying bacterial community composition in these bioreactors, consistent with annual cycling. The fungal communities were more stable, having longer temporal autocorrelations, and did not show significant annual cycling. These results suggest a recurring seasonal cycle in the denitrifying bioreactor microbial community, likely due to seasonal variation in moisture content.

Swimming Motility Reduces Deposition to Silica Surfaces.

The transport and fate of bacteria in porous media is influenced by physicochemical and biological properties. This study investigated the effect of swimming motility on the attachment of cells to silica surfaces through comprehensive analysis of cell deposition in model porous media. Distinct motilities were quantified for different strains using global and cluster-based statistical analyses of microscopic images taken under no-flow condition. The wild-type, flagellated strain DJ showed strong swimming as a result of the actively swimming subpopulation whose average speed was 25.6 µm/s; the impaired swimming of strain DJ77 was attributed to the lower average speed of 17.4 µm/s in its actively swimming subpopulation; and both the nonflagellated JZ52 and chemically treated DJ cells were nonmotile. The approach and deposition of these bacterial cells were analyzed in porous media setups, including single-collector radial stagnation point flow cells (RSPF) and two-dimensional multiple-collector micromodels under well-defined hydrodynamic conditions. In RSPF experiments, both swimming and nonmotile cells moved with the flow when at a distance ≥20 µm above the collector surface. Closer to the surface, DJ cells showed both horizontal and vertical movement, limiting their contact with the surface, while chemically treated DJ cells moved with the flow to reach the surface. These results explain how wild-type swimming reduces attachment. In agreement, the deposition in micromodels was also lowest for DJ compared with those for DJ77 and JZ52. Wild-type swimming specifically reduced deposition on the upstream surfaces of the micromodel collectors. Conducted under environmentally relevant hydrodynamic conditions, the results suggest that swimming motility is an important characteristic for bacterial deposition and transport in the environment.

Spatial variation in the bacterial and denitrifying bacterial community in a biofilter treating subsurface agricultural drainage.

Denitrifying biofilters can remove agricultural nitrates from subsurface drainage, reducing nitrate pollution that contributes to coastal hypoxic zones. The performance and reliability of natural and engineered systems dependent upon microbially mediated processes, such as the denitrifying biofilters, can be affected by the spatial structure of their microbial communities. Furthermore, our understanding of the relationship between microbial community composition and function is influenced by the spatial distribution of samples.In this study we characterized the spatial structure of bacterial communities in a denitrifying biofilter in central Illinois. Bacterial communities were assessed using automated ribosomal intergenic spacer analysis for bacteria and terminal restriction fragment length polymorphism of nosZ for denitrifying bacteria.Non-metric multidimensional scaling and analysis of similarity (ANOSIM) analyses indicated that bacteria showed statistically significant spatial structure by depth and transect,while denitrifying bacteria did not exhibit significant spatial structure. For determination of spatial patterns, we developed a package of automated functions for the R statistical environment that allows directional analysis of microbial community composition data using either ANOSIM or Mantel statistics.Applying this package to the biofilter data, the flow path correlation range for the bacterial community was 6.4 m at the shallower, periodically in undated depth and 10.7 m at the deeper, continually submerged depth. These spatial structures suggest a strong influence of hydrology on the microbial community composition in these denitrifying biofilters. Understanding such spatial structure can also guide optimal sample collection strategies for microbial community analyses.

Adaptation of Delftia acidovorans for degradation of 2,4-dichlorophenoxyacetate in a microfluidic porous medium.

Delftia acidovorans MC1071 can productively degrade R-2-(2,4-dichlorophenoxy)propionate (R-2,4-DP) but not 2,4-dichlorophenoxyacetate (2,4-D) herbicides. This work demonstrates adaptation of MC1071 to degrade 2,4-D in a model two-dimensional porous medium (referred to here as a micromodel). Adaptation for 2,4-D degradation in the 2 cm-long micromodel occurred within 35 days of exposure to 2,4-D, as documented by substrate removal. The amount of 2,4-D degradation in the adapted cultures in two replicate micromodels (~10 and 20 % over 142 days) was higher than a theoretical maximum (4 %) predicted using published numerical simulation methods, assuming instantaneous biodegradation and a transverse dispersion coefficient obtained for the same pore structure without biomass present. This suggests that the presence of biomass enhances substrate mixing. Additional evidence for adaptation was provided by operation without R-2,4-DP, where degradation of 2,4-D slowly decreased over 20 days, but was restored almost immediately when R-2,4-DP was again provided. Compared to suspended growth systems, the micromodel system retained the ability to degrade 2,4-D longer in the absence of R-2,4-DP, suggesting slower responses and greater resilience to fluctuations in substrates might be expected in the soil environment than in a chemostat.

Nitrous oxide and methane production and consumption at five full-size denitrifying bioreactors treating subsurface drainage water.

Nitrate (NO3-) removal in denitrifying bioreactors is influenced by flow, water chemistry, and design, but it is not known how these widely varying factors impact the production of nitrous oxide (N2O) or methane (CH4) across sites. Woodchip bioreactors link the hydrosphere and atmosphere in this respect, so five full-size bioreactors in Illinois, USA, were monitored for NO3-, N2O, and CH4 to better document where this water treatment technology resides along the pollution swapping to climate smart spectrum. Both surface fluxes and dissolved forms of N2O and CH4 were measured (n = 7-11 sampling campaigns per site) at bioreactors ranging from <1 to nearly 5 years old and treating subsurface drainage areas from between 6.9 and 29 ha. Across all sites, N2O surface and dissolved volumetric production rates averaged 1.0 ± 1.6 mg N2O-N/m3-d and 24 ± 62 mg dN2O-N/m3-d, respectively, and CH4 production rates averaged 6.0 ± 26 mg CH4-C/m3-d and 310 ± 520 mg dCH4-C/m3-d for surface and dissolved, respectively. However, N2O was consistently consumed at one bioreactor, and only three of the five sites produced notable CH4. Surface fluxes of CH4 were significantly reduced by the presence of a soil cover. Bioreactor denitrification was relatively efficient, with only 0.51 ± 3.5 % of removed nitrate emitted as N2O (n = 48). Modeled indirect N2O emissions factors were significantly lower when a bioreactor was present versus absent (EF5: 0.0055 versus 0.0062 kg N2O-N/kg NO3-N; p = 0.0011). While further greenhouse gas research on bioreactors is recommended, this should not be used as an excuse to slow adoption efforts. Bioreactors provide a practical option for voluntary water quality improvement in the heavily tile-drained US Midwest and elsewhere.

Interactions between Clostridium beijerinckii and Geobacter metallireducens in co-culture fermentation with anthrahydroquinone-2, 6-disulfonate (AH2QDS) for enhanced biohydrogen production from xylose.

To enhance biohydrogen production, Clostridium beijerinckii was co-cultured with Geobacter metallireducens in the presence of the reduced extracellular electron shuttle anthrahydroquinone-2, 6-disulfonate (AH(2)QDS). In the co-culture system, increases of up to 52.3% for maximum cumulative hydrogen production, 38.4% for specific hydrogen production rate, 15.4% for substrate utilization rate, 39.0% for substrate utilization extent, and 34.8% for hydrogen molar yield in co-culture fermentation were observed compared to a pure culture of C. beijerinckii without AH(2)QDS. G. metallireducens grew in the co-culture system, resulting in a decrease in acetate concentration under co-culture conditions and a presumed regeneration of AH(2)QDS from AQDS. These co-culture results demonstrate metabolic crosstalk between the fermentative bacterium C. beijerinckii and the respiratory bacterium G. metallireducens and suggest a strategy for industrial biohydrogen production.

Perchlorate reduction using free and encapsulated Azospira oryzae enzymes.

Existing methods for perchlorate remediation are hampered by the common co-occurrence of nitrate, which is structurally similar and a preferred electron acceptor. In this work, the potential for perchlorate removal using cell-free bacterial enzymes as biocatalysts was investigated using crude cell lysates and soluble protein fractions of Azospira oryzae PS, as well as soluble protein fractions encapsulated in lipid and polymer vesicles. The crude lysates showed activities between 41 700 to 54 400 U L(-1) (2.49 to 3.06 U mg(-1) total protein). Soluble protein fractions had activities of 15 400 to 29 900 U L(-1) (1.70 to 1.97 U mg(-1)) and still retained an average of 58.2% of their original activity after 23 days of storage at 4 °C under aerobic conditions. Perchlorate was removed by the soluble protein fraction at higher rates than nitrate. Importantly, perchlorate reduction occurred even in the presence of 500-fold excess nitrate. The soluble protein fraction retained its function after encapsulation in lipid or polymer vesicles, with activities of 13.8 to 70.7 U L(-1), in agreement with theoretical calculations accounting for the volume limitation of the vesicles. Further, encapsulation mitigated enzyme inactivation by proteinase K. Enzyme-based technologies could prove effective at perchlorate removal from water cocontaminated with nitrate or sulfate.

Flagella-mediated differences in deposition dynamics for Azotobacter vinelandii in porous media.

A multiscale approach was designed to study the effects of flagella on deposition dynamics of Azotobacter vinelandii in porous media, independent of motility. In a radial stagnation point flow cell (RSPF), the deposition rate of a flagellated strain with limited motility, DJ77, was higher than that of a nonflagellated (Fla(-)) strain on quartz. In contrast, Fla(-) strain deposition exceeded that of DJ77 in two-dimensional silicon microfluidic models (micromodels) and in columns packed with glass beads. Both micromodel and column experiments showed decreasing deposition over time, suggesting that approaching cells were blocked from deposition by previously deposited cells. Modeling results showed that blocking became effective for DJ77 strain at lower ionic strengths (1 mM and 10 mM), while for the Fla(-) strain, blocking was similar at all ionic strengths. In late stages of micromodel experiments, ripening effects were also observed, and these appeared earlier for the Fla(-) strain. In RSPF and column experiments, deposition of the flagellated strain was influenced by ionic strength, while ionic strength dependence was not observed for the Fla(-) strain. The observations in all three setups suggested flagella affect deposition dynamics and, in particular, result in greater sensitivity to ionic strength.

Effects of the antimicrobial tylosin on the microbial community structure of an anaerobic sequencing batch reactor.

The effects of the antimicrobial tylosin on a methanogenic microbial community were studied in a glucose-fed laboratory-scale anaerobic sequencing batch reactor (ASBR) exposed to stepwise increases of tylosin (0, 1.67, and 167 mg/L). The microbial community structure was determined using quantitative fluorescence in situ hybridization (FISH) and phylogenetic analyses of bacterial 16S ribosomal RNA (rRNA) gene clone libraries of biomass samples. During the periods without tylosin addition and with an influent tylosin concentration of 1.67 mg/L, 16S rRNA gene sequences related to Syntrophobacter were detected and the relative abundance of Methanosaeta species was high. During the highest tylosin dose of 167 mg/L, 16S rRNA gene sequences related to Syntrophobacter species were not detected and the relative abundance of Methanosaeta decreased considerably. Throughout the experimental period, Propionibacteriaceae and high GC Gram-positive bacteria were present, based on 16S rRNA gene sequences and FISH analyses, respectively. The accumulation of propionate and subsequent reactor failure after long-term exposure to tylosin are attributed to the direct inhibition of propionate-oxidizing syntrophic bacteria closely related to Syntrophobacter and the indirect inhibition of Methanosaeta by high propionate concentrations and low pH.

Influence of rye cover cropping on denitrification potential and year-round field N2O emissions.

Cover cropping is beneficial for reducing soil erosion and nutrient losses, but there are conflicting reports on how cover cropping affects emissions of nitrous oxide (N2O), a potent greenhouse gas. In this study, we measured N2O fluxes over a full year in Illinois corn plots with and without rye cover crop. We compared these year-round measurements to N2O emissions predicted by the Intergovernmental Panel on Climate Change (IPCC) Tier 1 equation and the Denitrification-Decomposition (DNDC) model. In addition, we measured potential denitrification and N2O production rates. The field measurements showed typical N2O peaks shortly after fertilizer application, as well as a significant late-winter peak. Cover cropping significantly reduced all peak N2O fluxes, with decreases ranging from 39 to 95%. Neither model was able to accurately predict annual N2O fluxes or the decrease in N2O emissions from cover-cropped fields. In contrast to field measurements, lab assays found that cover cropping significantly increased potential denitrification by 90-127% and potential N2O production by 54-106%. The rye cover-cropped plots had lower soil nitrate and higher soil carbon. When limiting nitrate and excess carbon were provided in lab assays, the proportion of N2O resulting from denitrification decreased. These results suggest that the discrepancy between the observed decrease in field N2O emissions and the increase in denitrification potential may be due to the difference in available nutrients between the field and laboratory measurements. Overall, these results suggest the importance of late-winter peaks in N2O emissions and the potential of rye cover cropping to reduce N2O emissions from agricultural fields.

Making Waves: Biocatalysis and Biosorption: Opportunities and Challenges Associated with a New Protein-Based Toolbox for Water and Wastewater Treatment.

New water and wastewater treatment technologies are required to meet the demands created by emerging contaminants and resource recovery needs, yet technology development is a slow and uncertain process. Through evolution, nature has developed highly selective and fast-acting proteins that could help address these issues, but research and application have been limited, often due to assumptions about stability and economic feasibility. Here we highlight the potential advantages of cell-free, protein-based water and wastewater treatment processes (biocatalysis and biosorption), evaluate existing information about their economic feasibility, consider when a protein-based treatment process might be advantageous, and highlight key research needs.

Adsorption of extracellular chromosomal DNA and its effects on natural transformation of Azotobacter vinelandii.

To better understand the influence of environmental conditions on the adsorption of extracellular chromosomal DNA and its availability for natural transformation, the amount and conformation of adsorbed DNA were monitored under different conditions in parallel with transformation assays using the soil bacterium Azotobacter vinelandii. DNA adsorption was monitored using the technique of quartz crystal microbalance with dissipation (QCM-D). Both silica and natural organic matter (NOM) surfaces were evaluated in solutions containing either 100 mM NaCl or 1 mM CaCl(2). The QCM-D data suggest that DNA adsorbed to silica surfaces has a more compact and rigid conformation in Ca(2+) solution than in Na(+) solution and that the reverse is true when DNA is adsorbed to NOM surfaces. While the amounts of DNA adsorbed on a silica surface were similar for Ca(2+) and Na(+) solutions, the amount of DNA adsorbed on an NOM-coated surface was higher in Ca(2+) solution than in Na(+) solution. Transformation frequencies for dissolved DNA and DNA adsorbed to silica and to NOM were 6 x 10(-5), 5 x 10(-5), and 2.5 x 10(-4), respectively. For NOM-coated surfaces, transformation frequencies from individual experiments were 2- to 50-fold higher in the presence of Ca(2+) than in the presence of Na(+). The results suggest that groundwater hardness (i.e., Ca(2+) concentration) will affect the amount of extracellular DNA adsorbed to the soil surface but that neither adsorption nor changes in the conformation of the adsorbed DNA will have a strong effect on the frequency of natural transformation of A. vinelandii.

Effects of Swine manure on macrolide, lincosamide, and streptogramin B antimicrobial resistance in soils.

Current agricultural practices involve inclusion of antimicrobials in animal feed and result in manure containing antimicrobials and antimicrobial-resistant microorganisms. This work evaluated the effects of land application of swine manure on the levels of tetracycline, macrolide, and lincosamide antimicrobials and on macrolide, lincosamide, and streptogramin B (MLS(B)) resistance in field soil samples and laboratory soil batch tests. MLS(B) and tetracycline antimicrobials were quantified after solid-phase extraction using liquid chromatography-tandem mass spectrometry. The prevalence of the ribosomal modification responsible for MLS(B) resistance in the same samples was quantified using fluorescence in situ hybridization. Macrolide antimicrobials were not detected in soil samples, while tetracyclines were detected, suggesting that the latter compounds persist in soil. No significant differences in ribosomal methylation or presumed MLS(B) resistance were observed when amended and unamended field soils were compared, although a transient (<20-day) increase was observed in most batch tests. Clostridium cluster XIVa accounted for the largest fraction of resistant bacteria identified in amended soils. Overall, this study did not detect a persistent increase in the prevalence of MLS(B) resistance due to land application of treated swine manure.

Macrolide resistance in microorganisms at antimicrobial-free Swine farms.

To investigate the relationship between agricultural antimicrobial use and resistance, a variety of methods for quantification of macrolide-lincosamide-streptogramin B (MLS(B)) resistance were applied to organic swine farm manure samples. Fluorescence in situ hybridization was used to indirectly quantify the specific rRNA methylation resulting in MLS(B) resistance. Using this method, an unexpectedly high prevalence of ribosomal methylation and, hence, predicted MLS(B) resistance was observed in manure samples from two swine finisher farms that reported no antimicrobial use (37.6% +/- 6.3% and 40.5% +/- 5.4%, respectively). A culture-based method targeting relatively abundant clostridia showed a lower but still unexpectedly high prevalence of resistance at both farms (27.7% +/- 11.3% and 11.7% +/- 8.6%, respectively), while the prevalence of resistance in cultured fecal streptococci was low at both farms (4.0%). These differences in the prevalence of resistance across microorganisms suggest the need for caution when extrapolating from data obtained with indicator organisms. A third antimicrobial-free swine farm, a breeder-to-finisher operation, had low levels of MLS(B) resistance in manure samples with all methods used (<9%). Tetracycline antimicrobials were detected in manure samples from one of the finisher farms and may provide a partial explanation for the high level of MLS(B) resistance. Taken together, these findings highlight the need for a more fundamental understanding of the relationship between antimicrobial use and the prevalence of antimicrobial resistance.

Prediction of N2O emissions under different field management practices and climate conditions.

Due to the contributions of nitrous oxide (N2O) to global climate change and stratospheric ozone destruction, it is important to understand how climate and agricultural management affect N2O emissions. Although the process-based Denitrification Decomposition (DNDC) model is often used for quantifying emissions of N2O, the accuracy of these predictions remains in question, and it is not clear which input variables, environmental or field management, have the greatest effect on model performance. In this study, DNDC was evaluated for prediction of N2O fluxes from two climatically-different corn-field sites in the United States (a Colorado irrigated field and a Minnesota rainfed field). Besides climate, these sites offer the additional advantage that measurements are available for multiple field management practices, including fertilizer application, tillage, and crop rotation. This evaluation found that DNDC did not consistently, correctly predict daily-scale N2O fluxes. Cumulative growing season N2O fluxes were significantly under-predicted in Colorado and were both under- and over-predicted in Minnesota. Model calibration of four soil input parameters did not significantly improve N2O emission predictions at either site or time scale. Modeled and measured N2O fluxes and model error were all strongly correlated with precipitation. Over-predictions of N2O fluxes were associated with heavy precipitation and high modeled denitrification. Based on our results, model improvements to decrease model error for corn cropping systems in temperate climate zones should focus on better accounting for the effects of precipitation on denitrification. Despite discrepancies in daily and cumulative growing season N2O fluxes, DNDC correctly identified the only field management (fertilizer application rate) that significantly influenced the measured N2O fluxes.

Inhibitory effects of the macrolide antimicrobial tylosin on anaerobic treatment.

A laboratory-scale anaerobic sequencing batch reactor (ASBR) was operated using a glucose-based synthetic wastewater to study the effects of tylosin, a macrolide antimicrobial commonly used in swine production, on treatment performance. The experimental period was divided into three consecutive phases with different influent tylosin concentrations (0, 1.67, and 167 mg/L). The addition of 1.67 mg/L tylosin to the reactor had negligible effects on the overall treatment performance, that is, total methane production and effluent chemical oxygen demand did not change significantly (P < 0.05), yet analyses of individual ASBR cycles revealed a decrease in the rates of both methane production and propionate uptake after tylosin was added. The addition of 167 mg/L tylosin to the reactor resulted in a gradual decrease in methane production and the accumulation of propionate and acetate. Subsequent inhibition of methanogenesis was attributed to a decrease in the pH of the reactor. After the addition of 167 mg/L tylosin to the reactor, an initial decrease in the rate of glucose uptake during the ASBR cycle followed by a gradual recovery was observed. In batch tests, the specific biogas production with the substrate butyrate was completely inhibited in the presence of tylosin. This study indicated that tylosin inhibited propionate- and butyrate-oxidizing syntrophic bacteria and fermenting bacteria resulting in unfavorable effects on methanogenesis.

Characterizing Isozymes of Chlorite Dismutase for Water Treatment.

This work investigated the potential for biocatalytic degradation of micropollutants, focusing on chlorine oxyanions as model contaminants, by mining biology to identify promising biocatalysts. Existing isozymes of chlorite dismutase (Cld) were characterized with respect to parameters relevant to this high volume, low-value product application: kinetic parameters, resistance to catalytic inactivation, and stability. Maximum reaction velocities (Vmax) were typically on the order of 104 µmol min-1 (µmol heme)-1. Substrate affinity (Km) values were on the order of 100 µM, except for the Cld from Candidatus Nitrospira defluvii (NdCld), which showed a significantly lower affinity for chlorite. NdCld also had the highest susceptibility to catalytic inactivation. In contrast, the Cld from Ideonella dechloratans was least susceptible to catalytic inactivation, with a maximum turnover number of approximately 150,000, more than sevenfold higher than other tested isozymes. Under non-reactive conditions, Cld was quite stable, retaining over 50% of activity after 30 days, and most samples retained activity even after 90-100 days. Overall, Cld from I. dechloratans was the most promising candidate for environmental applications, having high affinity and activity, a relatively low propensity for catalytic inactivation, and excellent stability.