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.

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.

Bacterial Community Diversity Dynamics Highlight Degrees of Nestedness and Turnover Patterns.

Bacterial communities change their structure rapidly due to short generation times of their members. How bacteria assemble to certain structures provides insight into ecological mechanisms that shape a bacterial community. Microbial community flow cytometry was used to create community fingerprints based on subcommunity distributions and to visualize the dynamic variations of 10 independently grown communities under equal conditions. Inventory diversity values were recorded by α- and γ-diversity whereas the degree of subsistence of subcommunities (nestedness) and the degree of gain or loss of subcommunities (turnover) was calculated as multi-sites ß-diversity terms ßNES and ßSIM . Numbers of unique subcommunities of pairwise samples were determined by intra- and inter-community ß-diversity values. Although all communities were exposed to niche-differentiating conditions they assembled to disparate structures. In our study, the turnover coefficients were high (> 0.6), while the nestedness coefficients were complementary low in the separate 10 bioreactors. Intra- and inter-community ß-diversity values indicated fast community shifts. Microbial community flow cytometry straightforwardly identifies the dominance and subsistence of subsets of cells in a community or the degree of their replacement. The calculation of either turnover or nestedness patterns might have implications in medical, biotechnological, or environmental research. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

flowEMMi: an automated model-based clustering tool for microbial cytometric data.

BACKGROUND: Flow cytometry (FCM) is a powerful single-cell based measurement method to ascertain multidimensional optical properties of millions of cells. FCM is widely used in medical diagnostics and health research. There is also a broad range of applications in the analysis of complex microbial communities. The main concern in microbial community analyses is to track the dynamics of microbial subcommunities. So far, this can be achieved with the help of time-consuming manual clustering procedures that require extensive user-dependent input. In addition, several tools have recently been developed by using different approaches which, however, focus mainly on the clustering of medical FCM data or of microbial samples with a well-known background, while much less work has been done on high-throughput, online algorithms for two-channel FCM. RESULTS: We bridge this gap with flowEMMi, a model-based clustering tool based on multivariate Gaussian mixture models with subsampling and foreground/background separation. These extensions provide a fast and accurate identification of cell clusters in FCM data, in particular for microbial community FCM data that are often affected by irrelevant information like technical noise, beads or cell debris. flowEMMi outperforms other available tools with regard to running time and information content of the clustering results and provides near-online results and optional heuristics to reduce the running-time further. CONCLUSIONS: flowEMMi is a useful tool for the automated cluster analysis of microbial FCM data. It overcomes the user-dependent and time-consuming manual clustering procedure and provides consistent results with ancillary information and statistical proof.

Neutral mechanisms and niche differentiation in steady-state insular microbial communities revealed by single cell analysis.

In completely insular microbial communities, evolution of community structure cannot be shaped by the immigration of new members. In addition, when those communities are run in steady state, the influence of environmental factors on their assembly is reduced. Therefore, one would expect similar community structures under steady-state conditions. Yet, in parallel setups, variability does occur. To reveal ecological mechanisms behind this phenomenon, five parallel reactors were studied at the single-cell level for about 100 generations and community structure variations were quantified by ecological measures. Whether community variability can be controlled was tested by implementing soft temperature stressors as potential synchronizers. The low slope of the lognormal rank-order abundance curves indicated a predominance of neutral mechanisms, i.e., where species identity plays no role. Variations in abundance ranks of subcommunities and increase in inter-community pairwise ß-diversity over time support this. Niche differentiation was also observed, as indicated by steeper geometric-like rank-order abundance curves and increased numbers of correlations between abiotic and biotic parameters during initial adaptation and after disturbances. Still, neutral forces dominated community assembly. Our findings suggest that complex microbial communities in insular steady-state environments can be difficult to synchronize and maintained in their original or desired structure, as they are non-equilibrium systems.

The intestinal microbiota determines the colitis-inducing potential of T-bet-deficient Th cells in mice.

Conflicting evidence has been provided as to whether induction of intestinal inflammation by adoptive transfer of naïve T cells into Rag-/- mice requires expression of the transcription factor T-bet by the T cells. Here, we formally show that the intestinal microbiota composition of the Rag-/- recipient determines whether or not T-bet-deficient Th cells can induce colitis and we have resolved the differences of the two microbiomes, permissive or non-permissive to T-bet-independent colitis. Our data highlight the dominance of the microbiota over particular T cell differentiation programs in the pathogenesis of chronic intestinal inflammation.

Key sub-community dynamics of medium-chain carboxylate production.

BACKGROUND: The carboxylate platform is a promising technology for substituting petrochemicals in the provision of specific platform chemicals and liquid fuels. It includes the chain elongation process that exploits reverse ß-oxidation to elongate short-chain fatty acids and forms the more valuable medium-chain variants. The pH value influences this process through multiple mechanisms and is central to effective product formation. Its influence on the microbiome dynamics was investigated during anaerobic fermentation of maize silage by combining flow cytometric short interval monitoring, cell sorting and 16S rRNA gene amplicon sequencing. RESULTS: Caproate and caprylate titres of up to 6.12 g L-1 and 1.83 g L-1, respectively, were achieved in a continuous stirred-tank reactor operated for 241 days. Caproate production was optimal at pH 5.5 and connected to lactate-based chain elongation, while caprylate production was optimal at pH 6.25 and linked to ethanol utilisation. Flow cytometry recorded 31 sub-communities with cell abundances varying over 89 time points. It revealed a highly dynamic community, whereas the sequencing analysis displayed a mostly unchanged core community. Eight key sub-communities were linked to caproate or caprylate production (rS > | ± 0.7|). Amongst other insights, sorting and subsequently sequencing these sub-communities revealed the central role of Bifidobacterium and Olsenella, two genera of lactic acid bacteria that drove chain elongation by providing additional lactate, serving as electron donor. CONCLUSIONS: High-titre medium-chain fatty acid production in a well-established reactor design is possible using complex substrate without the addition of external electron donors. This will greatly ease scaling and profitable implementation of the process. The pH value influenced the substrate utilisation and product spectrum by shaping the microbial community. Flow cytometric single cell analysis enabled fast, short interval analysis of this community and was coupled with 16S rRNA gene amplicon sequencing to reveal the major role of lactate-producing bacteria.

A cytometric approach to follow variation and dynamics of the salivary microbiota.

Microbial flow cytometry is an established fast and economic technique for complex ecosystem studies and enables visualization of rapidly changing community structures by measuring characteristics of single microbial cells. Cytometric evaluation routines are available such as flowCyBar which are useful for automatic data processing. Here, a cytometric workflow was established which allows to routinely analyze salivary microbiomes on the example of ten oral healthy subjects. First, saliva was collected within a 3-month period, cytometrically analyzed and the evolution of the microbiomes followed as well as the calculation of their intra- and inter-subject similarity. Second, the respective microbiomes were stressed by exposition to high sugar or acid concentrations and immediate changes were recorded. Third, bactericide solutions were tested on their impact on the microbiomes. In all three set ups huge intra-individual variations in cytometric community structures were found to be largely absent, even under stress, while inter-individual diversity was obvious. The bacterial cell counts of saliva samples were found to vary between 3.0×107 and 6.2×108 cells per sample and subject in undisturbed environments. The application of the two bactericides did not cause noteworthy diversity changes but the loss in cell numbers by about 50% was high after treatment. Illumina® sequencing of whole microbiomes or sorted sub-microbiomes revealed typical phyla such as Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes and Fusobacteria. This approach is useful for fast monitoring of individual salivary microbiomes and automatic calculation of intra- and inter-individual dynamic changes and variability and opens insight into ecological principles leading to their sustainment in their individual environment.

Herb-drug interactions: a novel algorithm-assisted information system for pharmacokinetic drug interactions with herbal supplements in cancer treatment.

PURPOSE: To develop a system to estimate the risk of herb-drug interactions that includes the available evidence from clinical and laboratory studies, transparently delineates the algorithm for the risk estimation, could be used in practice settings and allows for adaptation and update. METHODS: We systematically searched Drugbank, Transformer, Drug Information Handbook, European and German Pharmacopoeia and MEDLINE for studies on herb-drug interactions of five common medicinal plants (coneflower, ginseng, milk thistle, mistletoe and St. John's wort). A diverse set of data were independently extracted by two researchers and subsequently analysed by a newly developed algorithm. Results are displayed in the form of interaction risk categories. The development of the algorithm was guided by an expert panel consensus process. RESULTS: From 882 publications retrieved by the search, 154 studies were eligible and provided 529 data sets on herbal interactions. The developed algorithm prioritises results from clinical trials over case reports over in vitro investigations and considers type of study, consistency of study results and study outcome for clinical trials as well as identification, permeability, bioavailability, and interaction potency of an identified herbal perpetrator for in vitro investigations. Risk categories were assigned to and dynamically visualised in a colour-coded matrix format. CONCLUSIONS: The novel algorithm allows to transparently generate and dynamically display herb-drug interaction risks based on the available evidence from clinical and laboratory pharmacologic studies. It provides health professionals with readily available and easy updatable information about the risk of pharmacokinetic interactions between herbs and oncologic drugs.

High-resolution microbiota flow cytometry reveals dynamic colitis-associated changes in fecal bacterial composition.

Using high-resolution flow cytometry of bacterial shape (forward scatter) and DNA content (DAPI staining), we detected dramatic differences in the fecal microbiota composition during murine colitis that were validated using 16S rDNA sequencing. This innovative method provides a fast and inexpensive tool to interrogate the microbiota on the single-cell level.

Heterogenic response of prokaryotes toward silver nanoparticles and ions is facilitated by phenotypes and attachment of silver aggregates to cell surfaces.

Tons of anthropogenic silver nanoparticles (AgNPs) are assumed to be released into the environment due to their use in many consumer products. AgNPs are known to be toxic toward microorganisms and thus may harm their specific functions in ecosystems. Here we explore the impact of AgNPs on functioning of single cells in microbial populations at doses typically found in anthropogenic environments. The response of single cells to AgNPs was analyzed by flow cytometry and using the fluorescent dyes propidium iodide and DiBAC4 (3) as markers for cell membrane disintegration and depolarization, respectively. The effects of 10-nm and 30-nm AgNPs on three bacterial species (Mycobacterium frederiksbergense, Pseudomonas putida, and Escherichia coli) showed that the populations split into affected cells and others not showing any malfunction, with varying abundances depending on strains and cell growth states. Further, the dissolution of AgNPs measured with 3 KDa ultrafiltration and inductively coupled plasma-mass-spectrometry to distinguish particle-related effects from toxicity of dissolved Ag revealed that Ag ions were the principal toxicant. AgNP aggregate formation was followed by dynamic light scattering and the aggregates' attachment to cell surfaces was visualized by transmission electron microscopy and scanning electron microscopy-energy dispersive X-ray spectroscopy. An increased AgNP-affected cell fraction relative to the Ag ion impact was identified. The study shows that individual cells in a population cope differently with AgNP induced stress by evolving heterogeneous phenotypes. The response is linked to cell death and cell energy depletion depending on cell type and cell growth states. The attachment of AgNP aggregates to cell surfaces seems to amplify the heterogeneous response. © 2017 International Society for Advancement of Cytometry.

Flow cytometric quantification, sorting and sequencing of methanogenic archaea based on F420 autofluorescence.

BACKGROUND: The widely established production of CH4 from renewable biomass in industrial scale anaerobic reactors may play a major role in the future energy supply. It relies on methanogenic archaea as key organisms which represent the bottleneck in the process. The quantitative analysis of these organisms can help to maximize process performance, uncover disturbances before failure, and may ultimately lead to community-based process control schemes. Existing qPCR and fluorescence microscopy-based methods are very attractive but can be cost-intensive and laborious. RESULTS: In this study we present an autofluorescence-based, flow cytometric method for the fast low-cost quantification of methanogenic archaea in complex microbial communities and crude substrates. The method was applied to a methanogenic enrichment culture (MEC) and digester samples (DS). The methanogenic archaea were quantified using the distinct fluorescence of their cofactor F420 in a range from 3.7 × 108 (± 3.3 × 106) cells mL-1 and 1.8 x 109 (± 1.1 × 108) cells mL-1. We evaluated different fixation methods and tested the sample stability. Stable abundance and fluorescence intensity were recorded up to 26 days during aerobic storage in PBS at 6 °C. The discrimination of the whole microbial community from the ubiquitous particle noise was facilitated by SYBR Green I staining and enabled calculation of relative abundances of methanogenic archaea of up to 9.64 ± 0.23% in the MEC and up to 4.43 ± 0.74% in the DS. The metaprofiling of the mcrA gene reinforced the results. CONCLUSIONS: The presented method allows for fast and reliable quantification of methanogenic archaea in microbial communities under authentic digester conditions and can thus be useful for process monitoring and control in biogas digesters.

Species-sorting and mass-transfer paradigms control managed natural metacommunities.

A complex microbial system consisting of six different interconnected localities was thoroughly investigated at full scale for over a year. The metacommunity concept originating from macro-ecology was used to uncover mechanisms of community assembly by observing microbial interrelationships in and between the different localities via correlation and network analysis. The individual-based observation approach was applied using high-throughput microbial community cytometry in addition to next generation sequencing. We found robust α-diversity values for each of the six localities and high ß-diversity values despite directed connectivity between localities, classifying for endpoint assembly of organisms in each locality. Endpoint characteristics were based on subcommunities with high cell numbers whereas those with lower cell numbers were involved in dispersal. Perturbation caused abiotic parameters to alter local community assembly with especially the rare cells announcing community restructuration processes. The mass-effect paradigm as part of the metacommunity concept was identified by an increase in interlocality biotic correlations under perturbation which, however, did not unbalance the predominant species-sorting paradigm in the studied full scale metacommunity. Data as generated in this study might contribute to the development of individual-based models for controlling managed multispecies natural systems in future.

Copy number variability of expression plasmids determined by cell sorting and Droplet Digital PCR.

BACKGROUND: Plasmids are widely used for molecular cloning or production of proteins in laboratory and industrial settings. Constant modification has brought forth countless plasmid vectors whose characteristics in terms of average plasmid copy number (PCN) and stability are rarely known. The crucial factor determining the PCN is the replication system; most replication systems in use today belong to a small number of different classes and are available through repositories like the Standard European Vector Architecture (SEVA). RESULTS: In this study, the PCN was determined in a set of seven SEVA-based expression plasmids only differing in the replication system. The average PCN for all constructs was determined by Droplet Digital PCR and ranged between 2 and 40 per chromosome in the host organism Escherichia coli. Furthermore, a plasmid-encoded EGFP reporter protein served as a means to assess variability in reporter gene expression on the single cell level. Only cells with one type of plasmid (RSF1010 replication system) showed a high degree of heterogeneity with a clear bimodal distribution of EGFP intensity while the others showed a normal distribution. The heterogeneous RSF1010-carrying cell population and one normally distributed population (ColE1 replication system) were further analyzed by sorting cells of sub-populations selected according to EGFP intensity. For both plasmids, low and highly fluorescent sub-populations showed a remarkable difference in PCN, ranging from 9.2 to 123.4 for ColE1 and from 0.5 to 11.8 for RSF1010, respectively. CONCLUSIONS: The average PCN determined here for a set of standardized plasmids was generally at the lower end of previously reported ranges and not related to the degree of heterogeneity. Further characterization of a heterogeneous and a homogeneous population demonstrated considerable differences in the PCN of sub-populations. We therefore present direct molecular evidence that the average PCN does not represent the true number of plasmid molecules in individual cells.

Facilitated gate setting by sequential dot plot scanning.

Microbial communities comprising thousands of unknown organisms can be studied flow cytometrically by applying just one fluorescent parameter and using scatter characteristics of cells. Resulting 2D-plots need to represent high numbers of cells to detect the many subcommunities, even rare ones that might be present in the sample. Evaluation of such data can be faulty and subjective due to the low number of parameters available for data discrimination and the high numbers of overlaying events. Here, we describe a procedure that helps to evaluate such data using facilitated gate setting by sequential dot-plot scanning.

Accurate determination of plasmid copy number of flow-sorted cells using droplet digital PCR.

Many biotechnological processes rely on the expression of a plasmid-based target gene. A constant and sufficient number of plasmids per cell is desired for efficient protein production. To date, only a few methods for the determination of plasmid copy number (PCN) are available, and most of them average the PCN of total populations disregarding heterogeneous distributions. Here, we utilize the highly precise quantification of DNA molecules by droplet digital PCR (ddPCR) and combine it with cell sorting using flow cytometry. A duplex PCR assay was set up requiring only 1000 sorted cells for precise determination of PCN. The robustness of this method was proven by thorough optimization of cell sorting, cell disruption, and PCR conditions. When non plasmid-harboring cells of Pseudomonas putida KT2440 were spiked with different dilutions of the expression plasmid pA-EGFP_B, a PCN from 1 to 64 could be accurately detected. As a proof of principle, induced cultures of P. putida KT2440 producing an EGFP-fused model protein by means of the plasmid pA-EGFP_B were investigated by flow cytometry and showed two distinct subpopulations, fluorescent and nonfluorescent cells. These two subpopulations were sorted for PCN determination with ddPCR. A remarkably diverging plasmid distribution was found within the population, with nonfluorescent cells showing a much lower PCN (≤1) than fluorescent cells (PCN of up to 5) under standard conditions.

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.