Effects of spatial heterogeneity on the dynamics of a microbial feeding interaction

A mathematical model for an ideal chemostat in which one microbial population feeds on another and where Monod's model is used for the specific growth rates of both populations predicts a less stable behavior for the system than the one observed experimentally. Various factors have been proposed as being the reason for the increased stability of such systems. In this work, the effect of spatial heterogeneity on the dynamics of the microbial feeding interaction is studied. It is concluded that spatial heterogeneity has a stabilizing effect on the system. This effect combined with other factors could be the reason for the increased stability observed in systems where a microbial feeding interaction occurs.     

Microbial co-operation in the rhizosphere

Soil microbial populations are immersed in a framework of interactions known to affect plant fitness and soil quality. They are involved in fundamental activities that ensure the stability and productivity of both agricultural systems and natural ecosystems. Strategic and applied research has demonstrated that certain co-operative microbial activities can be exploited, as a low-input biotechnology, to help sustainable, environmentally-friendly, agro-technological practices. Much research is addressed at improving understanding of the diversity, dynamics, and significance of rhizosphere microbial populations and their co-operative activities. An analysis of the co-operative microbial activities known to affect plant development is the general aim of this review. In particular, this article summarizes and discusses significant aspects of this general topic, including (i) the analysis of the key activities carried out by the diverse trophic and functional groups of micro-organisms involved in co-operative rhizosphere interactions; (ii) a critical discussion of the direct microbe-microbe interactions which results in processes benefiting sustainable agro-ecosystem development; and (iii) beneficial microbial interactions involving arbuscular mycorrhiza, the omnipresent fungus-plant beneficial symbiosis. The trends of this thematic area will be outlined, from molecular biology and ecophysiological issues to the biotechnological developments for integrated management, to indicate where research is needed in the future.     

A novel system for monitoring the influence of oxygen tension on the microflora of grass silage

A novel method was devised to examine the effect of low concentrations of oxygen on microbial populations in grass silage, as reflected by the aerobic stability of the product. The aim of this system was to simulate the micro-aerobic conditions which influence the selective multiplication of the indigenous microflora of grass silage, particularly in situations where the pathogen Listeria monocytogenes has already established. Ensiled grass in laboratory silos was flushed with a regulated flow of premixed gases of varying oxygen concentrations at regular intervals. The silos could be individually removed periodically in the ensiling process without disturbing the integrity of the system. The ensiled grass was then examined for microbial content, with specific interest given to the effect on L. monocytogenes.     

Competition of two microbial populations for a single resource in a chemostat when one of them exhibits wall attachment

It is known that two microbial populations competing for a single resource in a homogeneous environment with time-invariant inputs cannot coexist in a steady state. The case where two microbial populations compete for a single resource in a chemostat but one of them exhibits attachment to the chemostat walls is studied theoretically. Because of the cells' attachment to the walls, the environment is no longer homogeneous. The present article considers the case where the attached cells form no more than a monolayer. Other situations occur, often frequently, but we do not consider them here. Two models are used to represent the attachment to the walls: the Topiwala-Hamer model and a model which assumes that the attachment of microbial cells to the solid surfaces is a reversible process. The first model does not allow the population that exhibits wall attachment to wash out from the chemostat, in contrast to the second model (which nevertheless reduces to the first one in the limit). It has been found that in most of the possible cases for both models, the two competitors can coexist in a stable steady state for a wide range of the operating parameters space. The results of the stability analysis are discussed and analytical expressions for the conditions and the boundaries of the domains of stable coexistence are given for all the possible situations that may arise.     

Dynamics of microbial community composition and function during in situ bioremediation of a uranium-contaminated aquifer

A pilot-scale system was established to examine the feasibility of in situ U(VI) immobilization at a highly contaminated aquifer (U.S. DOE Integrated Field Research Challenge site, Oak Ridge, TN). Ethanol was injected intermittently as an electron donor to stimulate microbial U(VI) reduction, and U(VI) concentrations fell to below the Environmental Protection Agency drinking water standard (0.03 mg liter(-1)). Microbial communities from three monitoring wells were examined during active U(VI) reduction and maintenance phases with GeoChip, a high-density, comprehensive functional gene array. The overall microbial community structure exhibited a considerable shift over the remediation phases examined. GeoChip-based analysis revealed that Fe(III)-reducing bacterial (FeRB), nitrate-reducing bacterial (NRB), and sulfate-reducing bacterial (SRB) functional populations reached their highest levels during the active U(VI) reduction phase (days 137 to 370), in which denitrification and Fe(III) and sulfate reduction occurred sequentially. A gradual decrease in these functional populations occurred when reduction reactions stabilized, suggesting that these functional populations could play an important role in both active U(VI) reduction and maintenance of the stability of reduced U(IV). These results suggest that addition of electron donors stimulated the microbial community to create biogeochemical conditions favorable to U(VI) reduction and prevent the reduced U(IV) from reoxidation and that functional FeRB, SRB, and NRB populations within this system played key roles in this process.     

Automatic determination of glucose, ethanol, amino nitrogen, and ammonia. Cell counting and data processing

Automated methods for analysis of growth kinetics and culture media of yeast populations are presented. Assays of sugar, alcohol, amino nitrogen, and ammonia are described. Microbial growth was automatically sized with a continuously working cell counter. The data thus obtained are processed by a computer program which evaluates metabolic parameters and carbon balances at any time of growth. The system can be applied to batch and continuous cultures and allows extension to microbial populations other than yeasts.     

Aerobic Heterotrophic Bacterial Populations of Sewage and Activated Sludge: V. Analysis of Population Structure and Activity

Two procedures, the confidence interval method and Mountford's index, were tested in analyses of the microbial populations of 11 laboratory activated sludges acclimated to aromatic compounds. The two methods gave somewhat different results but indicated that the populations were quite dissimilar. The activity of seven of the sludges correlated well with the population structure. Some considerations in analysis of microbial population structure are discussed.     

Application of Denaturing High-Performance Liquid Chromatography in Microbial Ecology: Fermentor Sludge, Compost, and Soil Community Profiling

Genetic fingerprinting methods, such as denaturing gradient gel electrophoresis (DGGE), are used in microbial ecology for the analysis of mixed microbial communities but are associated with various problems. In the present study we used a new alternative method: denaturing high-performance liquid chromatography (dHPLC). This method was previously shown to work with samples from water and gut flora but had not yet been applied to complex environmental samples. In contrast to other publications dealing with dHPLC, we used a commonly available HPLC system. Samples from different origins (fermentor sludge, compost, and soil), all ecologically significant, were tested, and the 16S rRNA gene was amplified via PCR. After optimization of the HPLC elution conditions, amplicons of pure cultures and mixed microbial populations could be separated successfully. Systematic differentiation was carried out by a cloning approach, since fraction collection of the peaks did not result in satisfactory fragment separation. dHPLC was evaluated as a tool for microbial community analysis on a genetic level and demonstrated major improvements compared to gel-based fingerprinting methods, such as DGGE, that are commonly used in microbial ecology.     

Staining procedures for flow cytometric monitoring of bacterial populations

Dual or multiple parameter flow cytometric analysis is developing into a powerful method for characterizing microbial populations. The distinguishing of the populations only by assignment of size/shape measurements by scattered ligth renders as not satisfactory. To differentiate between the cells, the employment of a specific fluorescence marker is absolutely necessary. Methods are presented for the flow cytometric determination of DNA and the polymer poly-β-hydroxybutyrate (PHB) content in three different bacterial strains. The measurement of the 3β-hydroxysterol content enables the differentation between yeast and bacterial organisms in mixed microbial populations. Monitoring the ratio of live to dead bacterial cells in soil or water samples, e.g. in pure culture systems, is shown.     

Biodiversity of soil microbial communities in agricultural systems

The productivity and health of agricultural systems depend greatly upon the functional processes carried out by soil microorganisms and soil microbial communities. The biodiversity of the soil microbial communities and the effect of diversity on the stability of the agricultural system, is unknown. Taxonomic approaches to estimating biodiversity of soil microbial communities are limited by difficulties in defining suitable taxonomic units and the apparent non-culturability of the majority of the microbial species present in the soil. Analysis of functional diversity may be a more meaningful approach but is also limited by the need to culture organisms. Approaches which do not rely on culturing organisms such as fatty acid analysis and 16S/18S rRNA analysis have provided an insight into the extent of genetic diversity within communities and may be useful in the analysis of community structure. Scale effects, including successional processes associated with organic matter decomposition, local effects associated with abiotic soil factors, and regional effects including the effect of agricultural management practices, on the diversity of microbial communities are considered. Their impact is important in relation to the minimum biodiversity required to maintain system function.     

Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA.

We describe a new molecular approach to analyzing the genetic diversity of complex microbial populations. This technique is based on the separation of polymerase chain reaction-amplified fragments of genes coding for 16S rRNA, all the same length, by denaturing gradient gel electrophoresis (DGGE). DGGE analysis of different microbial communities demonstrated the presence of up to 10 distinguishable bands in the separation pattern, which were most likely derived from as many different species constituting these populations, and thereby generated a DGGE profile of the populations. We showed that it is possible to identify constituents which represent only 1% of the total population. With an oligonucleotide probe specific for the V3 region of 16S rRNA of sulfate-reducing bacteria, particular DNA fragments from some of the microbial populations could be identified by hybridization analysis. Analysis of the genomic DNA from a bacterial biofilm grown under aerobic conditions suggests that sulfate-reducing bacteria, despite their anaerobicity, were present in this environment. The results we obtained demonstrate that this technique will contribute to our understanding of the genetic diversity of uncharacterized microbial populations.     

Functionally stable and phylogenetically diverse microbial enrichments from microbial fuel cells during wastewater treatment

Microbial fuel cells (MFCs) are devices that exploit microorganisms as biocatalysts to recover energy from organic matter in the form of electricity. One of the goals of MFC research is to develop the technology for cost-effective wastewater treatment. However, before practical MFC applications are implemented it is important to gain fundamental knowledge about long-term system performance, reproducibility, and the formation and maintenance of functionally-stable microbial communities. Here we report findings from a MFC operated for over 300 days using only primary clarifier effluent collected from a municipal wastewater treatment plant as the microbial resource and substrate. The system was operated in a repeat-batch mode, where the reactor solution was replaced once every two weeks with new primary effluent that consisted of different microbial and chemical compositions with every batch exchange. The turbidity of the primary clarifier effluent solution notably decreased, and 97% of biological oxygen demand (BOD) was removed after an 8-13 day residence time for each batch cycle. On average, the limiting current density was 1000 mA/m(2), the maximum power density was 13 mW/m(2), and coulombic efficiency was 25%. Interestingly, the electrochemical performance and BOD removal rates were very reproducible throughout MFC operation regardless of the sample variability associated with each wastewater exchange. While MFC performance was very reproducible, the phylogenetic analyses of anode-associated electricity-generating biofilms showed that the microbial populations temporally fluctuated and maintained a high biodiversity throughout the year-long experiment. These results suggest that MFC communities are both self-selecting and self-optimizing, thereby able to develop and maintain functional stability regardless of fluctuations in carbon source(s) and regular introduction of microbial competitors. These results contribute significantly toward the practical application of MFC systems for long-term wastewater treatment as well as demonstrating MFC technology as a useful device to enrich for functionally stable microbial populations.     

Phospholipid fatty acid profiling of microbial communities–a review of interpretations and recent applications

Profiling of microbial communities in environmental samples often utilizes phospholipid fatty acid (PLFA) analysis. This method has been used for more than 35 years and is still popular as a means to characterize microbial communities in a diverse range of environmental matrices. This review examines the various recent applications of PLFA analysis in environmental studies with specific reference to the interpretation of the PLFA results. It is evident that interpretations of PLFA results do not always correlate between different investigations. These discrepancies in interpretation and their subsequent applications to environmental studies are discussed. However, in spite of limitations to the manner in which PLFA data are applied, the approach remains one with great potential for improving our understanding of the relationship between microbial populations and the environment. This review highlights the caveats and provides suggestions towards the practicable application of PLFA data interpretation.     

The generation of variation in bacterial genomes

In the context of a general overview of molecular mechanisms of microbial evolution, several genetic systems known to either promote or restrain the generation of genetic variations are discussed. Particular attention is given to functions involved in DNA rearrangements and DNA acquisition. Sporadic actions by a variety of such systems influencing genetic stability in either way result in a level of genetic plasticity which is tolerable to the overall wealth of microbial populations but which allows for evolutionary change needed for a steady adaptation to variable selective forces. Although these evolutionarily relevant biological functions are encoded by the genome of each individual, their actions are exerted to some degree randomly in rare individuals and are therefore seemingly nondeterministic and become manifest at the population level.     

daime, a novel image analysis program for microbial ecology and biofilm research

Combinations of microscopy and molecular techniques to detect, identify and characterize microorganisms in environmental and medical samples are widely used in microbial ecology and biofilm research. The scope of these methods, which include fluorescence in situ hybridization (FISH) with rRNA-targeted probes, is extended by digital image analysis routines that extract from micrographs important quantitative data. Here we introduce daime (digital image analysis in microbial ecology), a new computer program integrating 2-D and 3-D image analysis and visualization functionality, which has previously not been available in a single open-source software package. For example, daime automatically finds 2-D and 3-D objects in images and confocal image stacks, and offers special functions for quantifying microbial populations and evaluating new FISH probes. A novel feature is the quantification of spatial localization patterns of microorganisms in complex samples like biofilms. In combination with '3D-FISH', which preserves the 3-D structure of samples, this stereological technique was applied in a proof of principle experiment on activated sludge and provided quantitative evidence that functionally linked ammonia and nitrite oxidizers cluster together in their habitat. This image analysis method complements recent molecular techniques for analysing structure-function relationships in microbial communities and will help to characterize symbiotic interactions among microorganisms.     

Dynamics of chemostat in which one microbial population grows on multiple complementary nutrients

The equations of a chemostat in which one microbial population grows on multiple rate-limiting nutrients are formulated. The dynamics of a chemostat involving growth on complementary nutrients is studied through stability analysis of the system of equations. Some conditions are derived that relate the dynamic behavior of the chemostat to its operating conditions and can be applied to any model for the specific growth rate of the population. It is shown that, if maintenance of the population is neglected, the system exhibits no sustained or damped oscillations. If maintenance of the population is considered, damped oscillations are observed for some operating conditions.     

Sparse and Compositionally Robust Inference of Microbial Ecological Networks

16S ribosomal RNA (rRNA) gene and other environmental sequencing techniques provide snapshots of microbial communities, revealing phylogeny and the abundances of microbial populations across diverse ecosystems. While changes in microbial community structure are demonstrably associated with certain environmental conditions (from metabolic and immunological health in mammals to ecological stability in soils and oceans), identification of underlying mechanisms requires new statistical tools, as these datasets present several technical challenges. First, the abundances of microbial operational taxonomic units (OTUs) from amplicon-based datasets are compositional. Counts are normalized to the total number of counts in the sample. Thus, microbial abundances are not independent, and traditional statistical metrics (e.g., correlation) for the detection of OTU-OTU relationships can lead to spurious results. Secondly, microbial sequencing-based studies typically measure hundreds of OTUs on only tens to hundreds of samples; thus, inference of OTU-OTU association networks is severely under-powered, and additional information (or assumptions) are required for accurate inference. Here, we present SPIEC-EASI (SParse InversE Covariance Estimation for Ecological Association Inference), a statistical method for the inference of microbial ecological networks from amplicon sequencing datasets that addresses both of these issues. SPIEC-EASI combines data transformations developed for compositional data analysis with a graphical model inference framework that assumes the underlying ecological association network is sparse. To reconstruct the network, SPIEC-EASI relies on algorithms for sparse neighborhood and inverse covariance selection. To provide a synthetic benchmark in the absence of an experimentally validated gold-standard network, SPIEC-EASI is accompanied by a set of computational tools to generate OTU count data from a set of diverse underlying network topologies. SPIEC-EASI outperforms state-of-the-art methods to recover edges and network properties on synthetic data under a variety of scenarios. SPIEC-EASI also reproducibly predicts previously unknown microbial associations using data from the American Gut project.     

Assessment of Microbial Populations Dynamics in a Blue Cheese by Culturing and Denaturing Gradient Gel Electrophoresis

The composition and development of microbial population during the manufacture and ripening of two batches of a blue-veined cheese was examined by culturing and polymerase chain reaction (PCR) denaturing gradient gel electrophoresis (DGGE) (PCR-DGGE). Nine selective and/or differential media were used to track the cultivable populations of total and indicator microbial groups. For PCR-DGGE, the V3 hyper variable region of the bacterial 16S rRNA gene and the eukaryotic D1 domain of 28S rDNA were amplified with universal primers, specific for prokaryotes and eukaryotes, respectively. Similarities and differences between the results obtained by the culturing and the molecular method were recorded for some populations. Culturing analysis allows minority microbial groups (coliforms, staphylococci) to be monitored, although in this study PCR-DGGE identified a population of Streptococcus thermophilus that went undetected by culturing. These results show that the characterization of the microbial populations interacting and evolving during the cheese-making process is improved by combining culturing and molecular methods.     

16S rRNA序列分析法在大气微生物检测中的应用

随首微生物核糖体数据库的日益完善,１６Ｓ ｒＲＮＡ序列分析技术已应用于海洋、湖泊和土壤等环境微生物多样性的分析,但尚未见其在大气微生物菌群分析中的应用报道。本研究选择５株大气中采集分离的菌株,通过细胞１６Ｓ ｒＲＮＡ通过引物ＰＣＲ扩增其对应序列,直接对ＰＣＲ产物进行测序,分析鉴定其对应细胞的种属,并将该结果同细胞表型鉴定、全自动微生物分析仪以及相色谱分析结果加以比较。结果表明１６Ｓ ｒＲＮＡ序列分