Eco-physiological characterization of fluorescence in situ hybridization probe-targeted denitrifiers in activated sludge using culture-independent methods

The r/K selection theory and its application in biological wastewater treatment processes

Understanding the characteristics of functional organisms is the key to managing and updating biological processes for wastewater treatment. This review, for the first time, systematically characterized two typical types of strategists in wastewater treatment ecosystems via the r/K selection theory and provided novel strategies for selectively enriching microbial community. Functional organisms involved in nitrification (e.g., Nitrosomonas and Nitrosococcus), anammox (Candidatus Brocadia), and methanogenesis (Methanosarcinaceae) are identified as r-strategists with fast growth capacities and low substrate affinities. These r-strategists can achieve high pollutant removal loading rates. On the other hand, other organisms such as Nitrosospira spp., Candidatus Kuenenia, and Methanosaetaceae, are characterized as K-strategists with slow growth rates but high substrate affinities, which can decrease the pollutant concentration to low levels. More importantly, K-strategists may play crucial roles in the biodegradation of recalcitrant organic pollutants. The food-to-microorganism ratio, mass transfer, cell size, and biomass morphology are the key factors determining the selection of r-/K-strategists. These factors can be related with operating parameters (e.g., solids and hydraulic retention time), biomass morphology (biofilm or granules), and operating modes (continuous-flow or sequencing batch), etc., to achieve the efficient acclimation of targeted r-/K-strategists. For practical applications, the concept of substrate flux was put forward to further benefit the selective enrichment of r-/K-strategists, fulfilling effective management and improvement of engineered pollution control bioprocesses. Finally, the future perspectives regarding the development of the r/K selection theory in wastewater treatment processes were discussed.

Molecular Biomarkers and Influential Factors of Denitrification in a Full-Scale Biological Nitrogen Removal Plant

Three denitrifying bacteria, Paracoccus spp., Thauera spp., Pseudomonas-like spp., and two functional genes, nitrate reductase (narG and napA), were studied as potential biomarkers for total nitrogen removal. These bacterial genera and the functional genes showed significant negative correlations with total nitrogen in the effluent (TN_eff). Thauera spp. had the highest correlation (r = −0.793, p < 0.001) with TN_eff, and narG-like and napA genes also showed significant correlations (r = −0.663 and −0.643, respectively), suggesting functional genes have equal validity to 16S rRNA genes in monitoring denitrification performance. The most explanatory variables were a combination of constituents, with temperature emerging as the most important in Pearson’s correlation and redundancy analysis. Thauera spp. had the highest correlation with temperature (r = 0.739) followed closely by Paracoccus spp. (r = 0.705). Denitrification was also significantly affected by pH (r = 0.369), solids retention time (r = −0.377), total nitrogen_in (r = 0.635), and organic matter in the influent (biochemical oxygen demand and chemical oxygen demand; r = 0.320 and 0.522, respectively). Our data verified that major denitrifiers’ 16S rRNA genes and nitrate reductase genes were better biomarkers than the biomass concentration, and any of the biomarkers could track denitrification in real time.

Microbial ecology of denitrification in biological wastewater treatment

Globally, denitrification is commonly employed in biological nitrogen removal processes to enhance water quality. However, substantial knowledge gaps remain concerning the overall community structure, population dynamics and metabolism of different organic carbon sources. This systematic review provides a summary of current findings pertaining to the microbial ecology of denitrification in biological wastewater treatment processes. DNA fingerprinting-based analysis has revealed a high level of microbial diversity in denitrification reactors and highlighted the impacts of carbon sources in determining overall denitrifying community composition. Stable isotope probing, fluorescence in situ hybridization, microarrays and meta-omics further link community structure with function by identifying the functional populations and their gene regulatory patterns at the transcriptional and translational levels. This review stresses the need to integrate microbial ecology information into conventional denitrification design and operation at full-scale. Some emerging questions, from physiological mechanisms to practical solutions, for example, eliminating nitrous oxide emissions and supplementing more sustainable carbon sources than methanol, are also discussed. A combination of high-throughput approaches is next in line for thorough assessment of wastewater denitrifying community structure and function. Though denitrification is used as an example here, this synergy between microbial ecology and process engineering is applicable to other biological wastewater treatment processes.

Enrichment of a K-strategist microbial population able to biodegrade p-nitrophenol in a sequencing batch reactor

The biological treatment of a high-strength p-nitrophenol (PNP) wastewater in an aerobic Sequencing Batch Reactor (SBR) has been studied. A specific operational strategy was applied with the main aim of developing a K-strategist PNP-degrading activated sludge. The enrichment of a K-strategist microbial population was performed using a non-acclimated biomass coming from a municipal WWTP as inoculum, and following a feeding strategy in which the PNP-degrading biomass was under endogenous conditions during more than 50% of the aerobic reaction phase. Hundred per cent of PNP removal was achieved in the whole operating period with a maximum specific PNP loading rate of 0.26 g PNP g(-1)VSS d(-1). A kinetic characterization of the obtained PNP-degrading population was carried out using respirometry assays in specifically designed batch tests. With the experimental data obtained a kinetic model including substrate inhibition has been used to describe the time-course of the PNP concentration and specific oxygen uptake rate (SOUR), simultaneously. The kinetic parameters obtained through optimization, validated with an additional respirometric test, were k(max)=1.02 mg PNP mg(-1) COD d(-1), K(s)=1.6 mg PNP L(-1) and K(i)=54 mg PNP L(-1). The values obtained for the K(s) and k(max) are lower than those reported in the literature for mixed populations, meaning that the biomass is a K-strategist type, and therefore demonstrating the success of the operational strategy imposed to obtain such a K-strategist population. Moreover, our measured K(i) value is higher than those reported by most of the bibliographic references; therefore the acclimated activated sludge used in this work was evidently more adapted to PNP inhibition than the other reported cultures.