Biological recovery of phosphorus (BioP-Rec) from wastewater streams using brewer's yeast on pilot-scale.

Most recent advances for phosphorus (P) recovery using brewery yeast on laboratory scale were used to scale up to a pilot-scale process (BioP-Rec module) and applied in a full-scale wastewater treatment plant (WWTP). A P balance was established for WWTP Markranstädt according to two thresholds: (1) the economic feasibility threshold for P recovery of 0.05 kg/m3 of free P, and (2) the German Sewage Sludge Ordinance (GSSO) threshold, which demands that all WWTPs with a P content in dry matter (DM) of biosolids of 20 gP/kgDM or higher in the coming years must perform mandatory P recovery. In terms of defined thresholds, return and excess sludges were identified as the most feasible WWTP process streams for P recovery. In a 1 m3 BioP-Rec module a 3 stage process was established. From the P-rich water-phase of the return sludge produced in stage 1, which contained 0.051 kg/m3 of free P, 77.56% was taken up by P-depleted brewer's yeast Saccharomyces pastorianus in 3 h in stage 2. In stage 3, the yeast was concentrated in 1 h to produce yeast sludge as a fertilizer product. We demonstrated a novel pilot-scale process for the production of bio-based P-rich fertilizer.

Residual cells and nutrient availability guide wound healing in bacterial biofilms.

Biofilms are multicellular heterogeneous bacterial communities characterized by social-like division of labor, and remarkable robustness with respect to external stresses. Increasingly often an analogy between biofilms and arguably more complex eukaryotic tissues is being drawn. One illustrative example of where this analogy can be practically useful is the process of wound healing. While it has been extensively studied in eukaryotic tissues, the mechanism of wound healing in biofilms is virtually unexplored. Combining experiments in Bacillus subtilis bacteria, a model organism for biofilm formation, and a lattice-based theoretical model of biofilm growth, we studied how biofilms recover after macroscopic damage. We suggest that nutrient gradients and the abundance of proliferating cells are key factors augmenting wound closure. Accordingly, in the model, cell quiescence, nutrient fluxes, and biomass represented by cells and self-secreted extracellular matrix are necessary to qualitatively recapitulate the experimental results for damage repair. One of the surprising experimental findings is that residual cells, persisting in a damaged area after removal of a part of the biofilm, prominently affect the healing process. Taken together, our results outline the important roles of nutrient gradients and residual cells on biomass regrowth on macroscopic scales of the whole biofilm. The proposed combined experiment-simulation framework opens the way to further investigate the possible relation between wound healing, cell signaling and cell phenotype alternation in the local microenvironment of the wound.

Environmental persistence assessment of heterocyclic polyaromatic hydrocarbons - Ultimate and primary biodegradability using adapted and non-adapted microbial communities.

Heterocyclic polyaromatic hydrocarbons (heterocyclic PAHs) are of increasing concern and their environmental and human health impacts should be assessed due to their widespread presence and potential persistence in the environment. This study investigated the ultimate and primary biodegradability of ten heterocyclic PAHs, nine of which were found to be non-readily biodegradable. To generate a microbial community capable of degrading such compounds, a bacterial inoculum isolated from the effluent of a wastewater treatment plant (WWTP) was adapted to a mixture of heterocyclic PAHs for one year. Throughout the adaptation process, bacterial samples were collected at different stages to conduct primary biodegradation, ultimate biodegradation, and inoculum toxicity tests. Interestingly, after one year of adaptation, the community developed the ability to mineralize carbazole, but in the same time showed an increasing sensitivity to the toxic effects of benzo[c]carbazole. In two consecutive primary biodegradation experiments, degradation of four heterocycles was observed, while no biodegradation was detected for five compounds in any of the tests. Furthermore, the findings of this work were compared with predictions from in silico models regarding biodegradation timeframe and sorption, and it was found that the models were partially successful in describing these processes. The results of study provide valuable insights into the persistence of a representative group of heterocyclic PAHs in aquatic environments, which contributes to the hazard assessment of this particular class of substances.

Development of an Automated Online Flow Cytometry Method to Quantify Cell Density and Fingerprint Bacterial Communities.

Cell density is an important factor in all microbiome research, where interactions are of interest. It is also the most important parameter for the operation and control of most biotechnological processes. In the past, cell density determination was often performed offline and manually, resulting in a delay between sampling and immediate data processing, preventing quick action. While there are now some online methods for rapid and automated cell density determination, they are unable to distinguish between the different cell types in bacterial communities. To address this gap, an online automated flow cytometry procedure is proposed for real-time high-resolution analysis of bacterial communities. On the one hand, it allows for the online automated calculation of cell concentrations and, on the other, for the differentiation between different cell subsets of a bacterial community. To achieve this, the OC-300 automation device (onCyt Microbiology, Zürich, Switzerland) was coupled with the flow cytometer CytoFLEX (Beckman Coulter, Brea, USA). The OC-300 performs the automatic sampling, dilution, fixation and 4',6-diamidino-2-phenylindole (DAPI) staining of a bacterial sample before sending it to the CytoFLEX for measurement. It is demonstrated that this method can reproducibly measure both cell density and fingerprint-like patterns of bacterial communities, generating suitable data for powerful automated data analysis and interpretation pipelines. In particular, the automated, high-resolution partitioning of clustered data into cell subsets opens up the possibility of correlation analysis to identify the operational or abiotic/biotic causes of community disturbances or state changes, which can influence the interaction potential of organisms in microbiomes or even affect the performance of individual organisms.

Ecological forces dictate microbial community assembly processes in bioreactor systems.

Microbial communities are indispensable for future biotechnology to produce valuable platform chemicals and reduce the exploitation of fossil resources. Yet, the stability of microbial communities in classical continuous reactor setups is best brief or non-existent. This is due to ecological forces such as stochastic and deterministic properties of communities that contribute to rapid changes in structure and function to varying degrees. The review highlights the differences between these two properties, provides tools for their estimation, and gives an outlook on overcoming instabilities of microbial communities in biotechnological reactor systems.

Combining Flow Cytometry and Metagenomics Improves Recovery of Metagenome-Assembled Genomes in a Cell Culture from Activated Sludge.

The recovery of metagenome-assembled genomes is biased towards the most abundant species in a given community. To improve the identification of species, even if only dominant species are recovered, we investigated the integration of flow cytometry cell sorting with bioinformatics tools to recover metagenome-assembled genomes. We used a cell culture of a wastewater microbial community as our model system. Cells were separated based on fluorescence signals via flow cytometry cell sorting into sub-communities: dominant gates, low abundant gates, and outer gates into subsets of the original community. Metagenome sequencing was performed for all groups. The unsorted community was used as control. We recovered a total of 24 metagenome-assembled genomes (MAGs) representing 11 species-level genome operational taxonomic units (gOTUs). In addition, 57 ribosomal operational taxonomic units (rOTUs) affiliated with 29 taxa at species level were reconstructed from metagenomic libraries. Our approach suggests a two-fold increase in the resolution when comparing sorted and unsorted communities. Our results also indicate that species abundance is one determinant of genome recovery from metagenomes as we can recover taxa in the sorted libraries that are not present in the unsorted community. In conclusion, a combination of cell sorting and metagenomics allows the recovery of MAGs undetected without cell sorting.

Automatic, fast, hierarchical, and non-overlapping gating of flow cytometric data with flowEMMi v2.

Flow cytometry has become a powerful technology for studying microbial community dynamics and ecology. These dynamics are tracked over long periods of time based on two-parameter community fingerprints consisting of subsets of cell distributions with similar cell properties. These subsets are highlighted by cytometric gates which are assembled into a gate template. Gate templates then are used to compare samples over time or between sites. The template is usually created manually by the operator which is time consuming, prone to human error and dependent on human expertise. Manual gating thus lacks reproducibility, which in turn might impact ecological downstream analyses such as various diversity parameters, turnover and nestedness or stability measures. We present a new version of our flowEMMi algorithm - originally designed for an automated construction of a gate template, which now (i) generates non-overlapping elliptical gates within a few minutes. Gate templates (ii) can be created for both single measurements and time-series measurements, allowing immediate downstream data analyses and on-line evaluation. Furthermore, it is possible to (iii) adjust gate sizes to Gaussian distribution confidence levels. This automatic approach (iv) makes the gate template creation objective and reproducible. Moreover, it can (v) generate hierarchies of gates. flowEMMi v2 is essential not only for exploratory studies, but also for routine monitoring and control of biotechnological processes. Therefore, flowEMMi v2 bridges a crucial bottleneck between automated cell sample collection and processing, and automated flow cytometric measurement on the one hand as well as automated downstream statistical analysis on the other hand.

Exploring the Extent of Phosphorus and Heavy Metal Uptake by Single Cells of Saccharomyces cerevisiae and Their Effects on Intrinsic Elements by SC-ICP-TOF-MS.

The effect of six heavy metals, namely, silver (Ag), lead (Pb), palladium (Pd), copper (Cu), nickel (Ni), and chromium (Cr), on phosphorus (P) uptake by yeast was investigated by single-cell analysis using inductively coupled plasma time-of-flight mass spectrometry (SC-ICP-TOF-MS). It was found that the P content in cells with 1.55 g L-1 P feeding after P starvation was increased by ∼70% compared to control cells. Heavy metals at 10 ppm, except Cu, had a negative impact on P accumulation by cells. Pd reduced the P content by 26% in single cells compared to control cells. Metal uptake was strongest for Ag and Pd (0.7 × 10-12 L cell-1) and weakest for Cr (0.05 × 10-12 L cell-1). Exposure to Cr markedly reduced (-50%) Mg in cells and had the greatest impact on the intrinsic element composition. The SC-ICP-TOF-MS shows the diversity of elemental content in single cells: for example, the P content under standard conditions varied between 12.4 and 890 fg cell-1. This technique allows studying both the uptake of elements and sublethal effects on physiology at a single-cell level.

Stabilizing microbial communities by looped mass transfer.

Building and changing a microbiome at will and maintaining it over hundreds of generations has so far proven challenging. Despite best efforts, complex microbiomes appear to be susceptible to large stochastic fluctuations. Current capabilities to assemble and control stable complex microbiomes are limited. Here, we propose a looped mass transfer design that stabilizes microbiomes over long periods of time. Five local microbiomes were continuously grown in parallel for over 114 generations and connected by a loop to a regional pool. Mass transfer rates were altered and microbiome dynamics were monitored using quantitative high-throughput flow cytometry and taxonomic sequencing of whole communities and sorted subcommunities. Increased mass transfer rates reduced local and temporal variation in microbiome assembly, did not affect functions, and overcame stochasticity, with all microbiomes exhibiting high constancy and increasing resistance. Mass transfer synchronized the structures of the five local microbiomes and nestedness of certain cell types was eminent. Mass transfer increased cell number and thus decreased net growth rates µ'. Subsets of cells that did not show net growth µ'SCx were rescued by the regional pool R and thus remained part of the microbiome. The loop in mass transfer ensured the survival of cells that would otherwise go extinct, even if they did not grow in all local microbiomes or grew more slowly than the actual dilution rate D would allow. The rescue effect, known from metacommunity theory, was the main stabilizing mechanism leading to synchrony and survival of subcommunities, despite differences in cell physiological properties, including growth rates.

Predicting the Presence and Abundance of Bacterial Taxa in Environmental Communities through Flow Cytometric Fingerprinting.

Microbiome management research and applications rely on temporally resolved measurements of community composition. Current technologies to assess community composition make use of either cultivation or sequencing of genomic material, which can become time-consuming and/or laborious in case high-throughput measurements are required. Here, using data from a shrimp hatchery as an economically relevant case study, we combined 16S rRNA gene amplicon sequencing and flow cytometry data to develop a computational workflow that allows the prediction of taxon abundances based on flow cytometry measurements. The first stage of our pipeline consists of a classifier to predict the presence or absence of the taxon of interest, with yielded an average accuracy of 88.13% ± 4.78% across the top 50 operational taxonomic units (OTUs) of our data set. In the second stage, this classifier was combined with a regression model to predict the relative abundances of the taxon of interest, which yielded an average R2 of 0.35 ± 0.24 across the top 50 OTUs of our data set. Application of the models to flow cytometry time series data showed that the generated models can predict the temporal dynamics of a large fraction of the investigated taxa. Using cell sorting, we validated that the model correctly associates taxa to regions in the cytometric fingerprint, where they are detected using 16S rRNA gene amplicon sequencing. Finally, we applied the approach of our pipeline to two other data sets of microbial ecosystems. This pipeline represents an addition to the expanding toolbox for flow cytometry-based monitoring of bacterial communities and complements the current plating- and marker gene-based methods. IMPORTANCE Monitoring of microbial community composition is crucial for both microbiome management research and applications. Existing technologies, such as plating and amplicon sequencing, can become laborious and expensive when high-throughput measurements are required. In recent years, flow cytometry-based measurements of community diversity have been shown to correlate well with those derived from 16S rRNA gene amplicon sequencing in several aquatic ecosystems, suggesting that there is a link between the taxonomic community composition and phenotypic properties as derived through flow cytometry. Here, we further integrated 16S rRNA gene amplicon sequencing and flow cytometry survey data in order to construct models that enable the prediction of both the presence and the abundances of individual bacterial taxa in mixed communities using flow cytometric fingerprinting. The developed pipeline holds great potential to be integrated into routine monitoring schemes and early warning systems for biotechnological applications.

Community and single cell analyses reveal complex predatory interactions between bacteria in high diversity systems.

A fundamental question in community ecology is the role of predator-prey interactions in food-web stability and species coexistence. Although microbial microcosms offer powerful systems to investigate it, interrogating the environment is much more arduous. Here, we show in a 1-year survey that the obligate predators Bdellovibrio and like organisms (BALOs) can regulate prey populations, possibly in a density-dependent manner, in the naturally complex, species-rich environments of wastewater treatment plants. Abundant as well as rarer prey populations are affected, leading to an oscillating predatory landscape shifting at various temporal scales in which the total population remains stable. Shifts, along with differential prey range, explain co-existence of the numerous predators through niche partitioning. We validate these sequence-based findings using single-cell sorting combined with fluorescent hybridization and community sequencing. Our approach should be applicable for deciphering community interactions in other systems.

Determination of elemental distribution and evaluation of elemental concentration in single Saccharomyces cerevisiae cells using single cell-inductively coupled plasma mass spectrometry.

Single-cell analysis using inductively coupled plasma mass spectrometry (SC-ICP-MS) is a method to obtain qualitative and quantitative information of the elemental content and distribution of single cells. Six intrinsic target elements were analyzed in yeast cells at different cell growth phases cultured in medium with different phosphorus concentrations (0, 7, 14 mM) to study its effect on cell growth and composition. SC-ICP-MS results were compared with those obtained by the acid digestion and the average ratio was 0.81. The limits of detection of this method were 0.08, 2.54, 12.5, 0.02, 0.02, and 0.08 fg cell-1 for Mg, P, K, Mn, Cu, and Zn, respectively. During the exponential growth phase, the cells exhibited higher elemental contents, wider distribution for most elements, and larger cell size in comparison to the stationary growth phase. Phosphorus-free conditions reduced the average P content in single cells of stationary growth phase from 650 to 80 fg. Phosphorus deficiency led to decreasing intracellular concentrations not only of P but also of K and Cu, and to increasing Zn concentration after 48 h. Mg maintained its concentration at ∼0.11 fg µm-3 and did not change significantly under the three investigated conditions after 48 h. Accordingly, Mg content was successfully used to estimate the intracellular concentration of other intrinsic elements in single yeast cells. SC-ICP-MS is suited to determine target elements in single yeast cells, and allows the study of heterogeneity of cell composition and effects of stressors on the elemental content, distribution, and concentrations of intrinsic elements.

New developments in biological phosphorus accessibility and recovery approaches from soil and waste streams.

Phosphorus (P) is a non-renewable resource and is on the European Union's list of critical raw materials. It is predicted that the P consumption peak will occur in the next 10 to 20 years. Therefore, there is an urgent need to find accessible sources in the immediate environment, such as soil, and to use alternative resources of P such as waste streams. While enormous progress has been made in chemical P recovery technologies, most biological technologies for P recovery are still in the developmental stage and are not reaching industrial application. Nevertheless, biological P recovery could offer good solutions as these technologies can return P to the human P cycle in an environmentally friendly way. This mini-review provides an overview of the latest approaches to make P available in soil and to recover P from plant residues, animal and human waste streams by exploiting the universal trait of P accumulation and P turnover in microorganisms and plants.

A framework for P-cycle assessment in wastewater treatment plants.

Phosphorus (P) in wastewater has a variety of negative effects and is usually permanently lost as a non-renewable resource. To mitigate future P shortage, P must be recovered from wastewater, preferably by bio-based technologies to avoid toxic side streams. A standardized procedure for the determination of P types and P concentrations in all liquid and solid process stages was established, which is applicable to all full-scale wastewater treatment plants (WWTPs). Based on this, an equally universal calculation framework for P-cycle assessment based on volume flow and mass load rates was designed to identify the most promising process streams for biological P recovery. As an example, in 16 process streams of a typical WWTP, concentrations of free, bound and total P were calculated and microbial communities were analyzed by flow cytometry over 748 days. The most promising process streams for the recovery of free P were anaerobic digester sludge, centrate and the water-extracts of the biosolids with 0.510 kg P m-3, 0.075 kg P m-3 and 1.023 kg P m-3, while the best process streams for the recovery of bound P were return sludge, excess sludge, anaerobic digester sludge, and the solids of the biosolids with 0.300 kg P m-3, 0.268 kg P m-3, 0.213 kg P m-3 and 1.336 kg P m-3, respectively. Microorganisms capable of P accumulation were active in all process stages and it was observed that chemical P precipitation antagonizes biological P removal. The framework for P-cycle assessment was able to identify process streams that are economically viable to make future in-stream technologies for biological P removal feasible.

The Impact of the Antibiotic Fosfomycin on Wastewater Communities Measured by Flow Cytometry.

Fosfomycin is a re-emergent antibiotic known to be effective against severe bacterial infections even when other antibiotics fail. To avoid overuse and thus the risk of new antibiotic resistance, the European Commission has recommended the intravenous use of fosfomycin only when other antibiotic treatments fail. A release of fosfomycin into the environment via wastewater from not only municipalities but also already from the producing pharmaceutical industry can seriously undermine a sustaining therapeutic value. We showed in long-term continuous-mode bioreactor cultivation and by using microbial community flow cytometry, microbial community ecology tools, and cell sorting that the micro-pollutant altered the bacterial wastewater community (WWC) composition within only a few generations. Under these conditions, fosfomycin was not readily degraded both at lower and higher concentrations. At the same time, operational reactor parameters and typical diversity parameters such as α- and intracommunity ß-diversity did not point to system changes. Nevertheless, an intrinsic compositional change occurred, caused by a turnover process in which higher concentrations of fosfomycin selected for organisms known to frequently harbor antibiotic resistance genes. A gfp-labeled Pseudomonas putida strain, used as the model organism and a possible future chassis for fosfomycin degradation pathways, was augmented and outcompeted in all tested situations. The results suggest that WWCs, as complex communities, may tolerate fosfomycin for a time, but selection for cell types that may develop resistance is very likely. The approach presented allows very rapid assessment and visualization of the impact of antibiotics on natural or managed microbial communities in general and on individual members of these communities in particular.

Bacterial mock communities as standards for reproducible cytometric microbiome analysis.

Flow cytometry has recently established itself as a tool to track short-term dynamics in microbial community assembly and link those dynamics with ecological parameters. However, instrumental configurations of commercial cytometers and variability introduced through differential handling of the cells and instruments frequently cause data set variability at the single-cell level. This is especially pronounced with microorganisms, which are in the lower range of optical resolution. Although alignment beads are valuable to generally minimize instrumental noise and align overall machine settings, an artificial microbial cytometric mock community (mCMC) is mandatory for validating lab workflows and enabling comparison of data between experiments, thus representing a necessary reference standard for the reproducible cytometric characterization of microbial communities, especially in long-term studies. In this study, the mock community consisted of two Gram-positive and two Gram-negative bacterial strains, which can be assembled with respective subsets of cells, including spores, in any selected ratio or concentration. The preparation of the four strains takes a maximum of 5 d, and the stains are storable with either PFA/ethanol fixation at -20 °C or drying at 4 °C for at least 6 months. Starting from this stock, an mCMC can be assembled within 1 h. Fluorescence staining methods are presented and representatively applied with two high-resolution cell sorters and three benchtop flow cytometers. Benchmarked data sets allow the use of bioinformatic evaluation procedures to decode community behavior or convey qualified cell sorting decisions for subsequent high-resolution sequencing or proteomic routines.

The Activation of Mucosal-Associated Invariant T (MAIT) Cells Is Affected by Microbial Diversity and Riboflavin Utilization in vitro.

Recent research has demonstrated that MAIT cells are activated by individual bacterial or yeasts species that possess the riboflavin biosynthesis pathway. However, little is known about the MAIT cell activating potential of microbial communities and the contribution of individual community members. Here, we analyze the MAIT cell activating potential of a human intestinal model community (SIHUMIx) as well as intestinal microbiota after bioreactor cultivation. We determined the contribution of individual SIHUMIx community members to the MAIT cell activating potential and investigated whether microbial stress can influence their MAIT cell activating potential. The MAIT cell activating potential of SIHUMIx was directly related to the relative species abundances in the community. We therefore suggest an additive relationship between the species abundances and their MAIT cell activating potential. In diverse microbial communities, we found that a low MAIT cell activating potential was associated with high microbial diversity and a high level of riboflavin demand and vice versa. We suggest that microbial diversity might affect MAIT cell activation via riboflavin utilization within the community. Microbial acid stress significantly reduced the MAIT cell activating potential of SIHUMIx by impairing riboflavin availability through increasing the riboflavin demand. We show that MAIT cells can perceive microbial stress due to changes in riboflavin utilization and that riboflavin availability might also play a central role for the MAIT cell activating potential of diverse microbiota.

Gastric bypass surgery in a rat model alters the community structure and functional composition of the intestinal microbiota independently of weight loss.

BACKGROUND: Roux-en-Y gastric bypass (RYGB) surgery is a last-resort treatment to induce substantial and sustained weight loss in cases of severe obesity. This anatomical rearrangement affects the intestinal microbiota, but so far, little information is available on how it interferes with microbial functionality and microbial-host interactions independently of weight loss. METHODS: A rat model was employed where the RYGB-surgery cohort is compared to sham-operated controls which were kept at a matched body weight by food restriction. We investigated the microbial taxonomy and functional activity using 16S rRNA amplicon gene sequencing, metaproteomics, and metabolomics on samples collected from theileum, the cecum, and the colon, and separately analysed the lumen and mucus-associated microbiota. RESULTS: Altered gut architecture in RYGB increased the relative occurrence of Actinobacteria, especially Bifidobacteriaceae and Proteobacteria, while in general, Firmicutes were decreased although Streptococcaceae and Clostridium perfringens were observed at relative higher abundances independent of weight loss. A decrease of conjugated and secondary bile acids was observed in the RYGB-gut lumen. The arginine biosynthesis pathway in the microbiota was altered, as indicated by the changes in the abundance of upstream metabolites and enzymes, resulting in lower levels of arginine and higher levels of aspartate in the colon after RYGB. CONCLUSION: The anatomical rearrangement in RYGB affects microbiota composition and functionality as well as changes in amino acid and bile acid metabolism independently of weight loss. The shift in the taxonomic structure of the microbiota after RYGB may be mediated by the resulting change in the composition of the bile acid pool in the gut and by changes in the composition of nutrients in the gut. Video abstract.