Modes of cytometric bacterial DNA pattern: a tool for pursuing growth

Application of flow cytometry for rapid, high-throughput, multiparametric analysis of environmental microbiomes

Quantification of the abundance and understanding of the dynamics of the microbial communities is essential to establish a basis for microbiome characterization. The conventional techniques used for the quantification of microbes are complicated and time-consuming. With scientific advancement, many techniques evolved and came into account. Among them, flow cytometry is a robust, high-throughput technique through which microbial dynamics, morphology, microbial distribution, physiological characteristics, and many more attributes can be studied in a high-throughput manner with comparatively less time and resources. Flow cytometry, when combined with other omics-based methods, offers a rapid and efficient platform to analyze and understand the composition of microbiome at the cellular level. The microbial diversity observed through flow cytometry will not be equivalent to that obtained by sequencing methods, but this integrated approach holds great potential for high throughput characterization of microbiomes. Flow cytometry is regarded as an established characterization tool in haematology, oncology, immunology, and medical microbiology research; however, its application in environmental microbiology is yet to be explored. This comprehensive review aims to delve into the diverse environmental applications of flow cytometry across various domains, including but not limited to bioremediation, landfills, anaerobic digestion, industrial bioprocesses, water quality regulation, and soil quality regulation. By conducting an in-depth analysis, this article seeks to shed light on the potential benefits and challenges associated with the utilization of flow cytometry in addressing environmental concerns.

Digital models in biotechnology: Towards multi-scale integration and implementation

Industrial biotechnology encompasses a large area of multi-scale and multi-disciplinary research activities. With the recent megatrend of digitalization sweeping across all industries, there is an increased focus in the biotechnology industry on developing, integrating and applying digital models to improve all aspects of industrial biotechnology. Given the rapid development of this field, we systematically classify the state-of-art modelling concepts applied at different scales in industrial biotechnology and critically discuss their current usage, advantages and limitations. Further, we critically analyzed current strategies to couple cell models with computational fluid dynamics to study the performance of industrial microorganisms in large-scale bioprocesses, which is of crucial importance for the bio-based production industries. One of the most challenging aspects in this context is gathering intracellular data under industrially relevant conditions. Towards comprehensive models, we discuss how different scale-down concepts combined with appropriate analytical tools can capture intracellular states of single cells. We finally illustrated how the efforts could be used to develop digitals models suitable for both cell factory design and process optimization at industrial scales in the future.

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 β-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.

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.

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.

Quantitation and Comparison of Phenotypic Heterogeneity Among Single Cells of Monoclonal Microbial Populations

Phenotypic heterogeneity within microbial populations arises even when the cells are exposed to putatively constant and homogeneous conditions. The outcome of this phenomenon can affect the whole function of the population, resulting in, for example, new "adapted" metabolic strategies and impacting its fitness at given environmental conditions. Accounting for phenotypic heterogeneity becomes thus necessary, due to its relevance in medical and applied microbiology as well as in environmental processes. Still, a comprehensive evaluation of this phenomenon requires a common and unique method of quantitation, which allows for the comparison between different studies carried out with different approaches. Consequently, in this study, two widely applicable indices for quantitation of heterogeneity were developed. The heterogeneity coefficient (HC) is valid when the population follows unimodal activity, while the differentiation tendency index (DTI) accounts for heterogeneity implying outbreak of subpopulations and multimodal activity. We demonstrated the applicability of HC and DTI for heterogeneity quantitation on stable isotope probing with nanoscale secondary ion mass spectrometry (SIP-nanoSIMS), flow cytometry, and optical microscopy datasets. The HC was found to provide a more accurate and precise measure of heterogeneity, being at the same time consistent with the coefficient of variation (CV) applied so far. The DTI is able to describe the differentiation in single-cell activity within monoclonal populations resolving subpopulations with low cell abundance, individual cells with similar phenotypic features (e.g., isotopic content close to natural abundance, as detected with nanoSIMS). The developed quantitation approach allows for a better understanding on the impact and the implications of phenotypic heterogeneity in environmental, medical and applied microbiology, microbial ecology, cell biology, and biotechnology.

Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion.

Long-Term Behavior of Defined Mixed Cultures of Geobacter sulfurreducens and Shewanella oneidensis in Bioelectrochemical Systems

This work aims to investigate the long-term behavior of interactions of electrochemically active bacteria in bioelectrochemical systems. The electrochemical performance and biofilm characteristics of pure cultures of Geobacter sulfurreducens and Shewanella oneidensis are being compared to a defined mixed culture of both organisms. While S. oneidensis pure cultures did not form cohesive and stable biofilms on graphite anodes and only yielded 0.034 ± 0.011 mA/cm² as maximum current density by feeding of each 5 mM lactate and acetate, G. sulfurreducens pure cultures formed 69 μm thick, area-wide biofilms with 10 mM acetate as initial substrate concentration and yielded a current of 0.39 ± 0.09 mA/cm². Compared to the latter, a defined mixed culture of both species was able to yield 38% higher maximum current densities of 0.54 ± 0.07 mA/cm² with each 5 mM lactate and acetate. This increase in current density was associated with a likewise increased thickness of the anodic biofilm to approximately 93 μm. It was further investigated whether a sessile incorporation of S. oneidensis into the mixed culture biofilm, which has been reported previously for short-term experiments, is long-term stable. The results demonstrate that S. oneidensis was not stably incorporated into the biofilm; rather, the planktonic presence of S. oneidensis has a positive effect on the biofilm growth of G. sulfurreducens and thus on current production.

Gene Expansion and Positive Selection as Bacterial Adaptations to Oligotrophic Conditions

By combining a genome-centric metagenomic approach with a culture-based approach, we investigated the genomic adaptations of prevalent populations in an engineered oligotrophic freshwater system. We found evidence for widespread positive selection on genes involved in phosphorus and carbon scavenging pathways and for gene expansions in motility and environmental sensing to be important genomic adaptations of the abundant taxon in this system. In addition, microscopic and flow cytometric analysis of the first freshwater representative of this population (Ramlibacter aquaticus LMG 30558^T) demonstrated phenotypic plasticity, possibly due to the metabolic versatility granted by its larger genome, to be a strategy to cope with nutrient limitation. Our study clearly demonstrates the need for the use of a broad set of genomic tools combined with culture-based physiological characterization assays to investigate and validate genomic adaptations.

We examined the genomic adaptations of prevalent bacterial taxa in a highly nutrient- and ion-depleted freshwater environment located in the secondary cooling water system of a nuclear research reactor. Using genome-centric metagenomics, we found that none of the prevalent bacterial taxa were related to typical freshwater bacterial lineages. We also did not identify strong signatures of genome streamlining, which has been shown to be one of the ecoevolutionary forces shaping the genome characteristics of bacterial taxa in nutrient-depleted environments. Instead, focusing on the dominant taxon, a novel Ramlibacter sp. which we propose to name Ramlibacter aquaticus, we detected extensive positive selection on genes involved in phosphorus and carbon scavenging pathways. These genes were involved in the high-affinity phosphate uptake and storage into polyphosphate granules, metabolism of nitrogen-rich organic matter, and carbon/energy storage into polyhydroxyalkanoate. In parallel, comparative genomics revealed a high number of paralogs and an accessory genome significantly enriched in environmental sensing pathways (i.e., chemotaxis and motility), suggesting extensive gene expansions in R. aquaticus. The type strain of R. aquaticus (LMG 30558^T) displayed optimal growth kinetics and productivity at low nutrient concentrations, as well as substantial cell size plasticity. Our findings with R. aquaticus LMG 30558^T demonstrate that positive selection and gene expansions may represent successful adaptive strategies to oligotrophic environments that preserve high growth rates and cellular productivity.

IMPORTANCE By combining a genome-centric metagenomic approach with a culture-based approach, we investigated the genomic adaptations of prevalent populations in an engineered oligotrophic freshwater system. We found evidence for widespread positive selection on genes involved in phosphorus and carbon scavenging pathways and for gene expansions in motility and environmental sensing to be important genomic adaptations of the abundant taxon in this system. In addition, microscopic and flow cytometric analysis of the first freshwater representative of this population (Ramlibacter aquaticus LMG 30558^T) demonstrated phenotypic plasticity, possibly due to the metabolic versatility granted by its larger genome, to be a strategy to cope with nutrient limitation. Our study clearly demonstrates the need for the use of a broad set of genomic tools combined with culture-based physiological characterization assays to investigate and validate genomic adaptations.

Detection of microbial disturbances in a drinking water microbial community through continuous acquisition and advanced analysis of flow cytometry data

Detecting disturbances in microbial communities is an important aspect of managing natural and engineered microbial communities. Here, we implemented a custom-built continuous staining device in combination with real-time flow cytometry (RT-FCM) data acquisition, which, combined with advanced FCM fingerprinting methods, presents a powerful new approach to track and quantify disturbances in aquatic microbial communities. Through this new approach we were able to resolve various natural community and single-species microbial contaminations in a flow-through drinking water reactor. Next to conventional FCM metrics, we applied metrics from a recently developed fingerprinting technique in order to gain additional insight into the microbial dynamics during these contamination events. Importantly, we found that multiple community FCM metrics based on different statistical approaches were required to fully characterize all contaminations. Furthermore we found that for accurate cell concentration measurements and accurate inference from the FCM metrics (coefficient of variation ≤ 5%), at least 1000 cells should be measured, which makes the achievable temporal resolution a function of the prevalent bacterial concentration in the system-of-interest. The integrated RT-FCM acquisition and analysis approach presented herein provides a considerable improvement in the temporal resolution by which microbial disturbances can be observed and simultaneously provides a multi-faceted toolset to characterize such disturbances.

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 β‐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.

Population heterogeneity in microbial bioprocesses: origin, analysis, mechanisms, and future perspectives

Population heterogeneity is omnipresent in all bioprocesses even in homogenous environments. Its origin, however, is only so well understood that potential strategies like bet-hedging, noise in gene expression and division of labour that lead to population heterogeneity can be derived from experimental studies simulating the dynamics in industrial scale bioprocesses. This review aims at summarizing the current state of the different parts of single cell studies in bioprocesses. This includes setups to visualize different phenotypes of single cells, computational approaches connecting single cell physiology with environmental influence and special cultivation setups like scale-down reactors that have been proven to be useful to simulate large-scale conditions. A step in between investigation of populations and single cells is studying subpopulations with distinct properties that differ from the rest of the population with sub-omics methods which are also presented here. Moreover, the current knowledge about population heterogeneity in bioprocesses is summarized for relevant industrial production hosts and mixed cultures, as they provide the unique opportunity to distribute metabolic burden and optimize production processes in a way that is impossible in traditional monocultures. In the end, approaches to explain the underlying mechanism of population heterogeneity and the evidences found to support each hypothesis are presented. For instance, population heterogeneity serving as a bet-hedging strategy that is used as coordinated action against bioprocess-related stresses while at the same time spreading the risk between individual cells as it ensures the survival of least a part of the population in any environment the cells encounter.

Lagrangian Trajectories to Predict the Formation of Population Heterogeneity in Large-Scale Bioreactors

Successful scale-up of bioprocesses requires that laboratory-scale performance is equally achieved during large-scale production to meet economic constraints. In industry, heuristic approaches are often applied, making use of physical scale-up criteria that do not consider cellular needs or properties. As a consequence, large-scale productivities, conversion yields, or product purities are often deteriorated, which may prevent economic success. The occurrence of population heterogeneity in large-scale production may be the reason for underperformance. In this study, an in silico method to predict the formation of population heterogeneity by combining computational fluid dynamics (CFD) with a cell cycle model of Pseudomonas putida KT2440 was developed. The glucose gradient and flow field of a 54,000 L stirred tank reactor were generated with the Euler approach, and bacterial movement was simulated as Lagrange particles. The latter were statistically evaluated using a cell cycle model. Accordingly, 72% of all cells were found to switch between standard and multifork replication, and 10% were likely to undergo massive, transcriptional adaptations to respond to extracellular starving conditions. At the same time, 56% of all cells replicated very fast, with µ ≥ 0.3 h^-1 performing multifork replication. The population showed very strong heterogeneity, as indicated by the observation that 52.9% showed higher than average adenosine triphosphate (ATP) maintenance demands (12.2%, up to 1.5 fold). These results underline the potential of CFD linked to structured cell cycle models for predicting large-scale heterogeneity in silico and ab initio.

Reevaluating multicolor flow cytometry to assess microbial viability

Flow cytometry is a rapid and quantitative method to determine bacterial viability. Although different stains can be used to establish viability, staining protocols are inconsistent and lack a general optimization approach. Very few "true" multicolor protocols, where dyes are combined in one sample, have been developed for microbiological applications. In this mini-review, the discrepancy between protocols for cell-permeant nucleic acid and functional stains are discussed as well as their use as viability dyes. Furthermore, optimization of staining protocols for a specific setup are described. Original data using the red-excitable SYTO dyes SYTO 59 to 64 and SYTO 17, combined with functional stains, for double and triple staining applications is also included. As each dye and dye combination behaves differently within a certain combination of medium matrix, microorganism, and instrument, protocols need to be tuned to obtain reproducible results. Therefore, single, double, and triple stains are reviewed, including the different parameters that influence staining such as stain kinetics, optimal stain concentration, and the effect of the chelator EDTA as membrane permeabilizer. In the last section, we highlight the need to investigate the stability of multicolor assays to ensure correct results as multiwell autoloaders are now commonly used.

Applications of flow cytometry to characterize bacterial physiological responses

Although reports of flow cytometry (FCM) applied to bacterial analysis are increasing, studies of FCM related to human cells still vastly outnumber other reports. However, current advances in FCM combined with a new generation of cellular reporter probes have made this technique suitable for analyzing physiological responses in bacteria. We review how FCM has been applied to characterize distinct physiological conditions in bacteria including responses to antibiotics and other cytotoxic chemicals and physical factors, pathogen-host interactions, cell differentiation during biofilm formation, and the mechanisms governing development pathways such as sporulation. Since FCM is suitable for performing studies at the single-cell level, we describe how this powerful technique has yielded invaluable information about the heterogeneous distribution of differently and even specialized responding cells and how it may help to provide insights about how cell interaction takes place in complex structures, such as those that prevail in bacterial biofilms.

Cytometric patterns reveal growth states of Shewanella putrefaciens

Bacterial growth is often difficult to estimate beyond classical cultivation approaches. Low cell numbers, particles or coloured and dense media may disturb reliable growth assessment. Further difficulties appear when cells are attached to surfaces and detachment is incomplete.

Therefore, flow cytometry was tested and used for analysis of bacterial growth on the single-cell level. Shewanella putrefaciens was cultivated as a model organism in planktonic or biofilm culture. Materials of smooth and rough surfaces were used for biofilm cultivation. Both aerobic and anaerobic as well as feast and famine conditions were applied. Visualization of growth was also done using Environmental Scanning and Phase Contrast Microscopy. Bioinformatic tools were applied for data interpretation.

Cytometric proliferation patterns based on distributions of DNA contents per cell corresponded distinctly to the various lifestyles, electron acceptors and substrates tested. Therefore, cell cycling profiles of S. putrefaciens were found to mirror growth conditions.

The cytometric patterns were consistently detectable with exception of some biofilm types whose resolution remained challenging. Corresponding heat maps proved to be useful for clear visualization of growth behaviour under all tested conditions. Therefore, flow cytometry in combination with bioinformatic tools proved to be powerful means to determine various growth states of S. putrefaciens, even in constrained environments. The approach is universal and will also be applicable for other bacterial species.

Subpopulation-proteomics reveal growth rate, but not cell cycling, as a major impact on protein composition in Pseudomonas putida KT2440

Population heterogeneity occurring in industrial microbial bioprocesses is regarded as a putative effector causing performance loss in large scale. While the existence of subpopulations is a commonly accepted fact, their appearance and impact on process performance still remains rather unclear. During cell cycling, distinct subpopulations differing in cell division state and DNA content appear which contribute individually to the efficiency of the bioprocess. To identify stressed or impaired subpopulations, we analyzed the interplay of growth rate, cell cycle and phenotypic profile of subpopulations by using flow cytometry and cell sorting in conjunction with mass spectrometry based global proteomics. Adjusting distinct growth rates in chemostats with the model strain Pseudomonas putida KT2440, cells were differentiated by DNA content reflecting different cell cycle stages. The proteome of separated subpopulations at given growth rates was found to be highly similar, while different growth rates caused major changes of the protein inventory with respect to e.g. carbon storage, motility, lipid metabolism and the translational machinery. In conclusion, cells in various cell cycle stages at the same growth rate were found to have similar to identical proteome profiles showing no significant population heterogeneity on the proteome level. In contrast, the growth rate clearly determines the protein composition and therefore the metabolic strategy of the cells.

Cytometric fingerprints: evaluation of new tools for analyzing microbial community dynamics

Optical characteristics of individual bacterial cells of natural communities can be measured with flow cytometry (FCM) in high throughput. The resulting data are visualized in cytometric histograms. These histograms represent individual cytometric fingerprints of microbial communities, e.g., at certain time points or microenvironmental conditions. Up to now four tools for analyzing the variation in these cytometric fingerprints are available but have not yet been systematically compared regarding application: Dalmatian Plot, Cytometric Histogram Image Comparison (CHIC), Cytometric Barcoding (CyBar), and FlowFP. In this article these tools were evaluated concerning (i) the required experience of the operator in handling cytometric data sets, (ii) the detection level of changes, (iii) time demand for analysis, and (iv) software requirements. As an illustrative example, FCM was used to characterize the microbial community structure of electroactive microbial biofilms. Their cytometric fingerprints were determined, analyzed with all four tools, and correlated to experimental and functional parameters. The source of inoculum (four different types of wastewater samples) showed the strongest influence on the microbial community structure and biofilm performance while the choice of substrate (acetate or lactate) had no significant effect in the present study. All four evaluation tools were found suitable to monitor structural changes of natural microbial communities. The Dalmatian Plot was shown to be most sensitive to operator impact but nevertheless provided an overview on community shifts. CHIC, CyBar, and FlowFP showed less operator dependence and gave highly resolved information on community structure variation on different detection levels. In conclusion, experimental and productivity parameters correlated with the biofilm structures and practical process integration details were available from cytometric fingerprint analysis.

From single cells to microbial population dynamics: modelling in biotechnology based on measurements of individual cells

The development of dynamic modelling of microbial populations in bioprocesses is reviewed. In the 1960s Arnold Fredrickson established the theoretical basis of such models, and other researchers have subsequently advanced them. This review explores the relationships that describe cell proliferation and evaluates the importance of the application of flow cytometry to the fundamental parameterisation of the models for their use in bioprocess engineering. The section "Individual-Based Modelling" discusses recent theoretical developments. Delay-differential equations are demonstrated to describe accurately temporal variation of the cell proliferation cycle and specialised approaches and related iconography are applied to stochastic and deterministic modelling of stages of cellular development. Synchronised cultures of the bacterium Cupriavidus necator were prepared and monitored using a flow cytometer. The data obtained demonstrate that cell proliferation could be simulated quantitatively using the developed model.

You are what you talk: quorum sensing induces individual morphologies and cell division modes in Dinoroseobacter shibae

Dinoroseobacter shibae, a member of the Roseobacter clade abundant in marine environments, is characterized by a pronounced pleomorphism. Cell shapes range from variable-sized ovoid rods to long filaments with a high copy number of chromosomes. Time-lapse microscopy shows cells dividing either by binary fission or by budding from the cell poles. Here we demonstrate that this morphological heterogeneity is induced by quorum sensing (QS). D. shibae utilizes three acylated homoserine lactone (AHL) synthases (luxI1-3) to produce AHLs with unsaturated C18 side chains. A ΔluxI1-knockout strain completely lacking AHL biosynthesis was uniform in morphology and divided by binary fission only. Transcriptome analysis revealed that expression of genes responsible for control of cell division was reduced in this strain, providing the link between QS and the observed phenotype. In addition, flagellar biosynthesis and type IV secretion system (T4SS) were downregulated. The wild-type phenotype and gene expression could be restored through addition of synthetic C18-AHLs. Their effectiveness was dependent on the number of double bonds in the acyl side chain and the regulated trait. The wild-type expression level of T4SS genes was fully restored even by an AHL with a saturated C18 side chain that has not been detected in D. shibae. QS induces phenotypic individualization of D. shibae cells rather than coordinating the population. This strategy might be beneficial in unpredictably changing environments, for example, during algal blooms when resource competition and grazing exert fluctuating selective pressures. A specific response towards non-native AHLs might provide D. shibae with the capacity for complex interspecies communication.

Monitoring functions in managed microbial systems by cytometric bar coding

Cytometric monitoring of microbial community dynamics can be used to estimate stability of technical microbial processes like biogas production by analysis of segregated cell abundance changes. In this study, structure variations of a biogas community were cytometrically recorded over 9 months and found to be of diagnostic value for process details. The reactor regime was intentionally disturbed with regard to substrate overload or H(2)S accumulation. A single-cell based approach called cytometric bar coding (CyBar) for fast identification of reactive subcommunities was used. Functionality of specific subcommunities was uncovered by processing CyBar data with abiotic reactor parameters using Spearman's correlation coefficient. Twenty subcommunities showed a discrete and divergent behavior. For example, a 4-fold substrate overload increased the cell number of two acidogenic index subcommunities to 176 and 193% within three days. Supplementary analyses were done using DNA fingerprinting, cloning, and sequencing. Bioreactor perturbations were shown to create cell abundance changes in subcommunities rather than variations in their phylogenetic composition. The used workflow and macros are ready-to-use tools and allow on-site monitoring and interpretation of variation in microbial community functions within a few hours.

Monitoring of population dynamics of Corynebacterium glutamicum by multiparameter flow cytometry

Phenotypic variation of microbial populations is a well-known phenomenon and may have significant impact on the success of industrial bioprocesses. Flow cytometry (FC) and the large repertoire of fluorescent dyes bring the high-throughput analysis of multiple parameters in single bacterial cells into reach. In this study, we evaluated a set of different fluorescent dyes for suitability in FC single cell analysis of the biotechnological platform organism Corynebacterium glutamicum. Already simple scattering properties of C. glutamicum cells in the flow cytometer were shown to provide valuable information on the growth activity of analysed cells. Furthermore, we used DAPI staining for a FC-based determination of the DNA content of C. glutamicum cells grown on standard minimal or complex media. Characteristic DNA patterns were observed mirroring the typical uncoupled DNA synthesis in the logarithmic (log) growth phase and are in agreement with a symmetric type of cell division of C. glutamicum. Application of the fluorescent dyes Syto 9, propidium iodide, and DiOC₂(3) allowed the identification of subpopulations with reduced viability and membrane potential within early log and stationary phase populations. The presented data highlight the potential of FC-based analyses for online monitoring of C. glutamicum bioprocesses and provide a first reference for future applications and protocols.

A flow cytometric method for viability assessment of Staphylococcus aureus and Burkholderia cepacia in mixed culture

Mixed bacterial communities are commonly encountered in microbial infections of humans. Knowledge on the composition of species and viability of each species in these communities allows for a detailed description of the complexity of interspecies dynamics and contributes to the assessment of the severity of infections. Several assays exist for quantification of specific species in mixed communities, including analysis of quantitative terminal restriction fragment length polymorphisms. While this method allows for species-specific cell enumeration, it cannot provide viability data. In this study, flow cytometry was applied to assess the viability of Staphylococcus aureus and Burkholderia cepacia in mixed culture by membrane integrity analysis using SYBR® Green I and propidium iodide staining. Both bacteria are relevant to pulmonary infections of cystic fibrosis patients. Fluorescence staining was optimized separately for each species in pure culture due to differences between species in cell wall structure and metabolic capabilities. To determine viability of species in mixed culture, a protocol was established as a compromise between optimum conditions determined before for pure cultures. This protocol allowed the detection of viable and dead cells of both species, exhibiting an intact and a permeabilized membrane, respectively. To discriminate between S. aureus and B. cepacia, the protocol was combined with Gram-specific fluorescent staining using wheat germ agglutinin. The established three-color staining method was successfully tested for viability determination of S. aureus and B. cepacia in mixed culture cultivations. In addition, growth of both species was monitored by quantitative terminal restriction fragment length polymorphisms. The obtained data revealed alterations in viability during cultivations for different growth phases and suggest interspecies effects in mixed culture. Overall, this method allows for rapid simultaneous Gram-differentiation and viability assessment of bacterial mixed cultures and is therefore suitable for the analysis of dynamics of mixed communities of medical, environmental, and biotechnological relevance.

Antibacterial effects of poly(2-(dimethylamino ethyl)methacrylate) against selected gram-positive and gram-negative bacteria

Antimicrobial coatings can reduce the occurrence of medical device-related bacterial infections. Poly(2-(dimethylamino ethyl)methacrylate) (pDMAEMA) is one such polymer that is being researched in this regard. The aims of this study were to (1) elucidate pDMAEMA's antimicrobial activity against a range of Gram-positive and Gram-negative bacteria and (2) to investigate its antimicrobial mode of action. The methods used include determination of minimum inhibitory concentration (MIC) values against various bacteria and the effect of pH and temperature on antimicrobial activity. The ability of pDMAEMA to permeabilise bacterial membranes was determined using the dyes 1-N-phenyl-naphthylamine and calcein-AM. Flow cytometry was used to investigate pDMAEMA's capacity to be internalized by bacteria and to determine effects on bacterial cell cycling. pDMAEMA was bacteriostatic against Gram-negative bacteria with MIC values between 0.1-1 mg/mL. MIC values against Gram-positive bacteria were variable. pDMAEMA was active against Gram-positive bacteria around its pK(a) and at lower pH values, while it was active against Gram-negative bacteria around its pK(a) and at higher pH values. pDMAEMA inhibited bacterial growth by binding to the outside of the bacteria, permeabilizing the outer membrane and disrupting the cytoplasmic membrane. By incorporating pDMAEMA with erythromycin, it was found that the efficacy of the latter was increased against Gram-negative bacteria. Together, the results illustrate that pDMAEMA acts in a similar fashion to other cationic biocides.

Advanced tool for characterization of microbial cultures by combining cytomics and proteomics

Flow cytometry approaches are applicable to recover sub-populations of microbial cultures in a purified form. To examine the characteristics of each sorted cell population, Omics technologies can be used for comprehensively monitoring cellular physiology, adaptation reactions, and regulated processes. In this study, we combined flow cytometry and gel-free proteomic analysis to investigate an artificial mixed bacterial culture consisting of Escherichia coli K-12 and Pseudomonas putida KT2440. Therefore, a filter-based device technique and an on-membrane digestion protocol were combined in conjunction with liquid chromatography and mass spectrometry. This combination enabled us to identify 903 proteins from sorted E. coli K-12 and 867 proteins from sorted P. putida KT2440 bacteria from only 5 x 10(6) cells of each. Comparative proteomic analysis of sorted and non-sorted samples was done to prove that sorting did not significantly influence the bacterial proteome profile. We further investigated the physicochemical properties, namely M (r), pI, hydropathicity, and transmembrane helices of the proteins covered. The on-membrane digestion protocol applied did not require conventional detergents or urea, but exhibited similar recovery of all protein classes as established protocols with non-sorted bacterial samples.

Origin and analysis of microbial population heterogeneity in bioprocesses

Heterogeneity of industrial production cultures is accepted to a certain degree; however, the underlying mechanisms are seldom perceived or included in the development of new bioprocess control strategies. Population heterogeneity and its basics, perceptible in the diverse proficiency of cells, begins with asymmetric birth and is found to recess during the life cycle. Since inefficient subpopulations have significant impact on the productivity of industrial cultures, cellular heterogeneity needs to be detected and quantified by using high speed detection tools like flow cytometry. Possible origins of population heterogeneity, sophisticated fluorescent techniques for detection of individual cell states, and cutting-edge Omics-technologies for extended information beyond the resolution of fluorescent labelling are highlighted.

The use of DRAQ5 to monitor intracellular DNA in Escherichia coli by flow cytometry

Flow cytometry provides a rapid and high-content multiparameter analysis of individual microorganisms within a population. In the past years, several fluorescent stains were developed in order to monitor DNA content distribution and cell-cycle phases, mainly in eukaryotic cells. Recently, due to its low detection limits, several of these fluorescent stains were also applied to prokaryotic cells. In this study, the ability of a novel far-red fluorescent stain DRAQ5 in assessing intracellular DNA content distribution in Escherichia coli DH5alpha was evaluated. The results showed that a DRAQ5-labelled live E. coli suspension can be obtained by incubation of 1 x 10(6) cells/mL with 5 microM DRAQ5 in PBS buffer supplemented with EDTA (pH = 7.4) during 30 min at 37 degrees C. Flow cytometric analysis of fixed E. coli cells revealed that ethanol should be used in detriment of glutaraldehyde for DRAQ5 labelling. After the analysis of RNase and DNase digested samples, DRAQ5 was proven to be a specific DNA labelling stain. The present study demonstrates that the use of DRAQ5 as a DNA-labelling stain provides an easy assessment of intracellular DNA content and cell-cycle phases in gram-negative bacteria such as E. coli.

Dynamics of polyphosphate-accumulating bacteria in wastewater treatment plant microbial communities detected via DAPI (4',6'-diamidino-2-phenylindole) and tetracycline labeling

Wastewater treatment plants with enhanced biological phosphorus removal represent a state-of-the-art technology. Nevertheless, the process of phosphate removal is prone to occasional failure. One reason is the lack of knowledge about the structure and function of the bacterial communities involved. Most of the bacteria are still not cultivable, and their functions during the wastewater treatment process are therefore unknown or subject of speculation. Here, flow cytometry was used to identify bacteria capable of polyphosphate accumulation within highly diverse communities. A novel fluorescent staining technique for the quantitative detection of polyphosphate granules on the cellular level was developed. It uses the bright green fluorescence of the antibiotic tetracycline when it complexes the divalent cations acting as a countercharge in polyphosphate granules. The dynamics of cellular DNA contents and cell sizes as growth indicators were determined in parallel to detect the most active polyphosphate-accumulating individuals/subcommunities and to determine their phylogenetic affiliation upon cell sorting. Phylotypes known as polyphosphate-accumulating organisms, such as a "Candidatus Accumulibacter"-like phylotype, were found, as well as members of the genera Pseudomonas and Tetrasphaera. The new method allows fast and convenient monitoring of the growth and polyphosphate accumulation dynamics of not-yet-cultivated bacteria in wastewater bacterial communities.

Modeling synchronous growth of bacterial populations in phased cultivation

The phasing technique is a method for synchronizing cell populations in a bioreactor. Periodic changes of substrate supply and depletion can provoke a cell cycle phasing of originally stochastic scattered proliferation patterns. Synchronized cell populations characterized by changes in DNA content distribution can be monitored by flow cytometry. Thus, studies of the dynamics of single cells in specific cell cycle phases are facilitated. Here we present an age structured model framework investigating synchronized populations using delay differential equations. Applying the framework not only cell populations synchronously increasing under balanced growth conditions, but also synchronized cultures growing in continuous phasing experiments can be described. A process model developed for describing phased cultures was fitted to growth data obtained from a synchronous cultivation of Cupriavidus necator. Its potential utility is demonstrated by a quantitative process description and by its ability to identify ways in which the grade of synchrony could be improved.