Organic Carbon Amendments for Enhanced Biological Attenuation of Trace Organic Contaminants in Biochar-Amended Stormwater Biofilters.

This study sought to evaluate how dissolved organic carbon (DOC) affects attenuation of trace organic contaminants (TOrCs) in biochar-amended stormwater biofilters. It was hypothesized that (1) DOC-augmented runoff would demonstrate enhanced TOrC biodegradation and (2) biochar-amended sand bearing DOC-cultivated biofilms would achieve enhanced TOrC attenuation due to sorptive retention and biodegradation. Microcosm and column experiments were conducted utilizing actual runoff, DOC from straw and compost, and a suite of TOrCs. Biodegradation of TOrCs in runoff was more enhanced by compost DOC than straw DOC (particularly for atrazine, prometon, benzotriazole, and fipronil). 16S rRNA gene quantification and sequencing revealed that growth-induced microbial community changes were, among replicates, most consistent for compost-augmented microcosms and least consistent for raw runoff microcosms. Compost DOC most robustly enhanced utilization of TOrCs as carbon substrates, possibly due to higher residual nutrient levels upon TOrC exposure. Sand columns containing just 0.5 wt % biochar maintained sorptive TOrC retention in the presence of compost-DOC-cultivated biofilms, and TOrC removal was further enhanced by biological activity. Overall, these results suggest that coamendment with biochar and compost may robustly enhance TOrC attenuation in stormwater biofilters, a finding of significance for efforts to mitigate the impacts of runoff on water quality.

Microbial stratification and DOM removal in drinking water biofilters: Implications for enhanced performance.

Biofiltration is a low-cost, low-energy technology that employs a biologically activated bed of porous medium to reduce the biodegradable fraction of the dissolved organic matter (DOM) pool in source water, resulting in the production of drinking water. Microbial communities at different bed depths within the biofilter play crucial roles in the degradation and removal of dissolved organic carbon (DOC), ultimately impacting its performance. However, the relationships between the composition of microbial communities inhabiting different biofilter depths and their utilisation of various DOC fractions remain poorly understood. To address this knowledge gap, we conducted an experimental study where microbial communities from the upper (i.e., top 10 cm) and lower (i.e., bottom 10 cm) sections of a 30-cm long laboratory-scale biofilter were recovered. These communities were then individually incubated for 10 days using the same source water as the biofilter influent. Our study revealed that the bottom microbial community exhibited lower diversity yet had a co-occurrence network with a higher degree of interconnections among its members compared to the top microbial community. Moreover, we established a direct correlation between the composition and network structure of the microbial communities and their ability to utilise various DOM compounds within a DOM pool. Interestingly, although the bottom microbial community had only 20 % of the total cell abundance compared to the top community at the beginning of the incubation, it utilised and hence removed approximately 60 % more total DOC from the DOM pool than the top community. While both communities rapidly utilised labile carbon fractions, such as low-molecular-weight neutrals, the utilisation of more refractory carbon fractions, like high-molecular-weight humic substances with an average molecular weight of more than ca. 1451 g/mol, was exclusive to the bottom microbial community. By employing techniques that capture microbial diversity (i.e., flow cytometry and 16S rRNA amplicon sequencing) and considering the complexities of DOM (i.e., LCOCD), our study provides novel insights into how microbial community structure could influence the microbial-mediated processes of engineering significance in drinking water production. Finally, our findings could offer the opportunity to improve biofilter performances via engineering interventions that shape the compositions of biofilter microbial communities and enhance their utilisation and removal of DOM, most notably the more classically humified and refractory DOM compound groups.

Validating Flow Cytometry as a Method for Quantifying Bdellovibrio Predatory Bacteria and Its Prey for Microbial Ecology.

Bdellovibrio bacteriovorus is a predatory, Gram-negative bacteria that feeds on many pathogenic bacteria and has been investigated as a possible solution for mitigating biofilms in different fields. The application depends on more fundamental ecological studies into the dynamics between Bdellovibrio and their prey. To do so requires an accurate, reliable, and, preferably rapid, way of enumerating the cells. Flow cytometry (FCM) is potentially a rapid, accurate, and inexpensive tool for this, but it has yet to be validated in the enumeration of Bdellovibrio. In this study, we developed a protocol to measure the number of Bdellovibrio in samples of various densities using FCM and compared the results with those of other methods: optical density (OD), PFU assay (PFU), and quantitative PCR (qPCR). We observed a strong correlation between values obtained using FCM and PFU (ρ = 0.923) and FCM and qPCR (ρ = 0.987). Compared to optical density there was a much weaker correlation (ρ = 0.784), which was to be expected given the well-documented uncertainty in converting optical density (OD) to cell numbers. The FCM protocol was further validated by demonstrating its ability to distinguish and count mixed populations of Bdellovibrio and the prey Pseudomonas. Thus, the accuracy of FCM as well as its speed and reproducibility make it a suitable alternative for measuring Bdellovibrio cell numbers, especially where many samples are required to capture the dynamics of predator-prey interactions. IMPORTANCE The rise of antibiotic resistance and the unwanted growth of bacteria is a universally growing problem. Predatory bacteria can be used as a biological alternative to antibiotics because they grow by feeding on other bacteria. To apply this effectively requires further study and a deeper understanding of the forces that drive a prey population to elimination. Initially, such studies require more reliable methods to count these cells. Flow cytometry (FCM) is potentially a rapid, accurate, and inexpensive tool for this, but it has yet to be validated for predatory bacteria. This study develops a protocol to count the predatory bacteria Bdellovibrio bacteriovorus and its Pseudomonas prey using FCM and compare the results with those of other methods, demonstrating its ability for studies into B. bacteriovorus predation dynamics. This could lead to the use of B. bacteriovorus for killing bacterial biofilms in fields, such as drinking water and agriculture.

Breeding selection imposed a differential selective pressure on the wheat root-associated microbiome.

Plants-microbiome associations are the result of millions of years of co-evolution. Due to breeding-accelerated plant evolution in non-native and highly managed soil, plant-microbe links could have been lost. We hypothesized that post-domestication breeding of wheat changed the root-associated microbiome. To test this, we analyzed root-associated fungal and bacterial communities shortly after emergence of seedlings representing a transect of wheat evolution including modern wheat, landraces and ancestors. Numbers of observed microbial taxa were highest in landraces bred in low-input agricultural systems, and lowest in ancestors that had evolved in native soils. The microbial communities of modern cultivars were different from those of landraces and ancestors. Old wheat accessions enriched Acidobacteria and Actinobacteria, while modern cultivars enriched OTUs from Candidatus Saccharibacteria, Verrucomicrobia and Firmicutes. The fungal pathogens Fusarium, Neoascochyta and Microdochium enriched in modern cultivars. Both bacterial and fungal communities followed a neutral assembly model when bulk soil was considered as the source community, but accessions of the ancient Triticum turgidum and T. monococcum created a more isolated environment in their roots. In conclusion, wheat root-associated microbiomes have dramatically changed through a transect of breeding history.

Medium shapes the microbial community of water filters with implications for effluent quality.

Little is known about the forces that determine the assembly of diverse bacterial communities inhabiting drinking water treatment filters and how this affects drinking water quality. Two contrasting ecological theories can help to understand how natural microbial communities assemble; niche theory and neutral theory, where environmental deterministic factors or stochastic factors predominate respectively. This study investigates the development of the microbial community on two common contrasting filter materials (quartz sand and granular activated carbon-GAC), to elucidate the main factors governing their assembly, through the evaluation of environmental (i.e. filter medium type) and stochastic forces (random deaths, births and immigration). Laboratory-scale filter columns were used to mimic a rapid gravity filter; the microbiome of the filter materials, and of the filter influent and effluent, was characterised using next generation 16S rRNA gene amplicon sequencing and flow-cytometry. Chemical parameters (i.e. dissolved organic carbon, trihalomethanes formation) were also monitored to assess the final effluent quality. The filter communities seemed to be strongly assembled by selection rather than neutral processes, with only 28% of those OTUs shared with the source water detected on the filter medium following predictions using a neutral community model. GAC hosted a phylogenetically more diverse community than sand. The two filter media communities seeded the effluent water, triggering differences in both water quality and community composition of the effluents. Overall, GAC proved to be better than sand in controlling microbial growth, by promoting higher bacterial decay rates and hosting less bacterial cells, and showed better performance for putative pathogen control by leaking less Legionella cells into the effluent water.

Flow-cytometric quantification of microbial cells on sand from water biofilters.

Rapid quantification of absolute microbial cell abundances is important for a comprehensive interpretation of microbiome surveys and crucial to support theoretical modelling and the design of engineered systems. In this paper, we propose a protocol specifically optimised for the quantification of microbial abundances in water biofilters using flow cytometry (FCM). We optimised cell detachment from sand biofilter particles for FCM quantification through the evaluation of five chemical dispersants (NaCl, Triton-X100, CaCl2, sodium pyrophosphate (PP), Tween 80 combined with PP), different mechanical pre-treatments (low and high energy sonication and shaking) and two fixation methods (glutaraldehyde and ethanol). The developed protocol was cross-compared using other established and commonly employed methods for biomass quantification in water filter samples (adenosine triphosphate (ATP) quantification, real-time quantitative PCR (qPCR) and volatile solids (VS)). The highest microbial count was obtained by detaching the biofilm from biofilter grains and dispersing clusters into singles cells using Tween 80 and sodium pyrophosphate combined with four steps of high energy sonication (27W, for 80 s each step); glutaraldehyde was shown to be the best fixative solution. The developed protocol was reliable and highly reproducible and produced results that are comparable to data from alternative quantification methods. Indeed, high correlations were found with trends obtained through ATP and qPCR (ρ = 0.98 and ρ = 0.91) measurements. The VS content was confirmed as an inaccurate method to express biomass in sand samples since it correlated poorly with all the other three methods (ρ = 0.005 with FCM, 0.002 with ATP and 0.177 with qPCR). FCM and ATP showed the strongest agreement between absolute counts with a slope of the correlation equal to 0.7, while qPCR seemed to overestimate cell counts by a factor of ten. The rapidity and reproducibility of the method developed make its application ideal for routine quantification of microbial cell abundances on sand from water biofilters and thus useful in revealing the ecological patterns and quantifying the metabolic kinetics involved in such systems.