Strain Identification and Quantitative Analysis in Microbial Communities

Microbiology has long studied the ways in which subtle genetic differences between closely related microbial strains can have profound impacts on their phenotypes and those of their surrounding environments and communities. Despite the growth in high-throughput microbial community profiling, however, such strain-level differences remain challenging to detect. Once detected, few quantitative approaches have been well-validated for associating strain variants from microbial communities with phenotypes of interest, such as medication usage, treatment efficacy, host environment, or health. First, the term “strain” itself is not used consistently when defining a highly-resolved taxonomic or genomic unit from within a microbial community. Second, computational methods for identifying such strains directly from shotgun metagenomics are difficult, with several possible reference- and assembly-based approaches available, each with different sensitivity/specificity tradeoffs. Finally, statistical challenges exist in using any of the resulting strain profiles for downstream analyses, which can include strain tracking, phylogenetic analysis, or genetic association studies. We provide an in depth discussion of recently available computational tools that can be applied for this task, as well as statistical models and gaps in performing and interpreting any of these three main types of studies using strain-resolved shotgun metagenomic profiling of microbial communities.     

Microbial Consortia for Hydrogen Production Enhancement

Ten efficient hydrogen-producing strains affiliated to the Clostridium genus were used to develop consortia for hydrogen production. In order to determine their saccharolytic and proteolytic activities, glucose and meat extract were tested as fermentation substrates, and the best hydrogen-producing strains were selected. The C. roseum H5 (glucose-consuming) and C. butyricum R4 (protein-degrading) co-culture was the best hydrogen-producing co-culture. The end-fermentation products for the axenic cultures and co-cultures were analyzed. In all cases, organic acids, mainly butyrate and acetate, were produced lowering the pH and thus inhibiting further hydrogen production. In order to replace the need for reducing agents for the anaerobic growth of clostridia, a microbial consortium including Clostridium spp. and an oxygen-consuming microorganism able to form dense granules (Streptomyces sp.) was created. Increased yields of hydrogen were achieved. The effect of adding a butyrate-degrading bacteria and an acetate-consuming archaea to the consortia was also studied.     

Comparative Molecular Analysis of Endoevaporitic Microbial Communities

A phylogenetic comparison of microbial communities in hypersaline evaporites was conducted on crusts from Guerrero Negro, Mexico, and Lindsey Lake, New Mexico, using culture-independent rRNA gene sequence analysis. Many sequences were shared between evaporites, which suggests that similar environments select for specific microbial lineages from a global metacommunity.     

Direct rRNA Fingerprinting,a Novel Method to Profile Low Diversity Microbial Communities

In the past decade, an increasing number of methods in microbial ecology have been developed that address the questions of which microbes exist in the environment, what their roles are and, to some extent, what their abundance is. In the present paper, we propose and describe the proof of principle of a novel method for analysing shifts in microbial community composition that uses small RNA fragments directly derived from 16S rRNA. Community fingerprints are generated on the basis of sequence-dependent conformational differences of rRNA fragments. We applied this method to profile artificial and natural communities and to detect changes in community structure in enrichment cultures. This method constitutes a PCR-free alternative to microbial community characterisation and can provide information on the relative abundance of rRNA from individual phylotypes in low diversity samples.     

Characterization of Microbial Communities and Composition in Constructed Dairy Wetland Wastewater Effluent

Constructed wetlands have been recognized as a removal treatment option for high concentrations of contaminants in agricultural waste before land application. The goal of this study was to characterize microbial composition in two constructed wetlands designed to remove contaminants from dairy washwater. Water samples were collected weekly for 11 months from two wetlands to determine the efficiency of the treatment system in removal of chemical contaminants and total and fecal coliforms. The reduction by the treatment was greatest for biological oxygen demand, suspended solids, chemical oxygen demand, nitrate, and coliforms. There was only moderate removal of total nitrogen and phosphorus. Changes in the total bacterial community and ammonia-oxidizing bacterial composition were examined by using denaturing gradient gel electrophoresis (DGGE) and sequencing of PCR-amplified fragments of the gene carrying the α subunit of the ammonia monooxygenase gene (amoA) recovered from soil samples and DGGE bands. DGGE analysis of wetlands and manure samples revealed that the total bacterial community composition was dominated by bacteria from phylogenetic clusters related to Bacillus, Clostridium, Mycoplasma, Eubacterium, and Proteobacteria originally retrieved from the gastrointestinal tracts of mammals. The population of ammonia-oxidizing bacteria showed a higher percentage of Nitrosospira-like sequences from the wetland samples, while a higher percentage of Nitrosomonas-like sequences from manure, feces, raw washwater, and facultative pond was found. These results show that the wetland system is a natural process dependent upon the development of healthy microbial communities for optimal wastewater treatment.     

Terminal Restriction Fragment Length Polymorphism Data Analysis for Quantitative Comparison of Microbial Communities

Terminal restriction fragment length polymorphism (T-RFLP) is a culture-independent method of obtaining a genetic fingerprint of the composition of a microbial community. Comparisons of the utility of different methods of (i) including peaks, (ii) computing the difference (or distance) between profiles, and (iii) performing statistical analysis were made by using replicated profiles of eubacterial communities. These samples included soil collected from three regions of the United States, soil fractions derived from three agronomic field treatments, soil samples taken from within one meter of each other in an alfalfa field, and replicate laboratory bioreactors. Cluster analysis by Ward's method and by the unweighted-pair group method using arithmetic averages (UPGMA) were compared. Ward's method was more effective at differentiating major groups within sets of profiles; UPGMA had a slightly reduced error rate in clustering of replicate profiles and was more sensitive to outliers. Most replicate profiles were clustered together when relative peak height or Hellinger-transformed peak height was used, in contrast to raw peak height. Redundancy analysis was more effective than cluster analysis at detecting differences between similar samples. Redundancy analysis using Hellinger distance was more sensitive than that using Euclidean distance between relative peak height profiles. Analysis of Jaccard distance between profiles, which considers only the presence or absence of a terminal restriction fragment, was the most sensitive in redundancy analysis, and was equally sensitive in cluster analysis, if all profiles had cumulative peak heights greater than 10,000 fluorescence units. It is concluded that T-RFLP is a sensitive method of differentiating between microbial communities when the optimal statistical method is used for the situation at hand. It is recommended that hypothesis testing be performed by redundancy analysis of Hellinger-transformed data and that exploratory data analysis be performed by cluster analysis using Ward's method to find natural groups or by UPGMA to identify potential outliers. Analyses can also be based on Jaccard distance if all profiles have cumulative peak heights greater than 10,000 fluorescence units.     

Microbial Communities of Deep Marine Subsurface Sediments: Molecular and Cultivation Surveys

Recent molecular analyses show that microbial communities of deep marine sediments harbor members of distinct, uncultured bacterial and archaeal lineages, in addition to Gram-positive bacteria and Proteobacteria that are detected by cultivation surveys. Several of these subsurface lineages show cosmopolitan occurrence patterns; they can be found in cold marine sediments and also in hydrothermal habitats, suggesting a continuous deep subsurface and hydrothermal biosphere with shared microbiota. The physiologies and activities of these uncultured subsurface lineages remain to be explored by innovative combinations of genomic and biogeochemical approaches.     

Comparisons of Different Hypervariable Regions of rrs Genes for Use in Fingerprinting of Microbial Communities by PCR-Denaturing Gradient Gel Electrophoresis

Denaturing gradient gel electrophoresis (DGGE) has become a widely used tool to examine microbial diversity and community structure, but no systematic comparison has been made of the DGGE profiles obtained when different hypervariable (V) regions are amplified from the same community DNA samples. We report here a study to make such comparisons and establish a preferred choice of V region(s) to examine by DGGE, when community DNA extracted from samples of digesta is used. When the members of the phylogenetically representative set of 218 rrs genes archived in the RDP II database were compared, the V1 region was found to be the most variable, followed by the V9 and V3 regions. The temperature of the lowest-melting-temperature (T_m(L)) domain for each V region was also calculated for these rrs genes, and the V1 to V4 region was found to be most heterogeneous with respect to T_m(L). The average T_m(L) values and their standard deviations for each V region were then used to devise the denaturing gradients suitable for separating 95% of all the sequences, and the PCR-DGGE profiles produced from the same community DNA samples with these conditions were compared. The resulting DGGE profiles were substantially different in terms of the number, resolution, and relative intensity of the amplification products. The DGGE profiles of the V3 region were best, and the V3 to V5 and V6 to V8 regions produced better DGGE profiles than did other multiple V-region amplicons. Introduction of degenerate bases in the primers used to amplify the V1 or V3 region alone did not improve DGGE banding profiles. Our results show that DGGE analysis of gastrointestinal microbiomes is best accomplished by the amplification of either the V3 or V1 region of rrs genes, but if a longer amplification product is desired, then the V3 to V5 or V6 to V8 region should be targeted.     

藏灵菇微生物种群结构的分子特性研究

用PCR—DGGE指纹技术,研究了藏灵菇中微生物多样性及藏灵菇发酵奶发酵过程微生物种群动力学。结果表明,藏灵菇中细菌的种群结构较酵母菌的复杂,不同来源的藏灵菇中细菌种群结构的相似性为78％-84％,酵母菌种群结构的相似性为80％-92％。发酵过程中细菌种群结构变化图谱中的条带B和条带E,以及酵母菌种群结构变化图谱中的条带N贯穿于整个发酵过程,是发酵过程的优势菌。序列分析表明,细菌种群结构的DGGE图谱中的绝大多数条带与乳酸菌相对应,其中最亮条带（条带E）的序列与乳酸乳球菌的相似性为100％。     

Comparison and Characterization of Microbial Communities in Sulfide-rich Wastewater with and without Propidium Monoazide Treatment

A 16S rRNA gene-based culture-independent approach was used to study the bacterial and archaeal communities in a sulfide-rich wastewater. Propidium Monoazide (PMA) treatment was applied to limit the analysis to the fraction of viable cells in environment. A total of 104 and 68 clones respective from bacterial clone library and archaeal library were picked and analyzed by restriction fragment length polymorphism (RFLP). 35 RFLP patterns from bacterial clone library and 10 RFLP patterns from archaeal clone library were unique and the respective clones were selected for sequencing. BLAST analysis and RFLP analysis showed that the bacterial clone library mainly consisted of Gammaproteobacteria (73%), Anaerolineae (6%), Bacilli (5%), Deltaproteobacteria (7%), Clostridia (4%), Bacteroidetes (1%), and Chlorobia (1%); Methanomicrobia (99%) and Thermococci (1%) were the only two lineages of the archaeal domains. This study gave a first insight into the overall microbial structure in a cloth printing and dyeing wastewater treatment plant with high concentration of sulfide and increased knowledge on the applicability of the PMA treatment in combination with PCR-based molecular techniques to analyze only viable cells in microbial ecology.     

Biofuel Cells Select for Microbial Consortia That Self-Mediate Electron Transfer

Microbial fuel cells hold great promise as a sustainable biotechnological solution to future energy needs. Current efforts to improve the efficiency of such fuel cells are limited by the lack of knowledge about the microbial ecology of these systems. The purposes of this study were (i) to elucidate whether a bacterial community, either suspended or attached to an electrode, can evolve in a microbial fuel cell to bring about higher power output, and (ii) to identify species responsible for the electricity generation. Enrichment by repeated transfer of a bacterial consortium harvested from the anode compartment of a biofuel cell in which glucose was used increased the output from an initial level of 0.6 W m⁻² of electrode surface to a maximal level of 4.31 W m⁻² (664 mV, 30.9 mA) when plain graphite electrodes were used. This result was obtained with an average loading rate of 1 g of glucose liter⁻¹ day⁻¹ and corresponded to 81% efficiency for electron transfer from glucose to electricity. Cyclic voltammetry indicated that the enhanced microbial consortium had either membrane-bound or excreted redox components that were not initially detected in the community. Dominant species of the enhanced culture were identified by denaturing gradient gel electrophoresis and culturing. The community consisted mainly of facultative anaerobic bacteria, such as Alcaligenes faecalis and Enterococcus gallinarum, which are capable of hydrogen production. Pseudomonas aeruginosa and other Pseudomonas species were also isolated. For several isolates, electrochemical activity was mainly due to excreted redox mediators, and one of these mediators, pyocyanin produced by P. aeruginosa, could be characterized. Overall, the enrichment procedure, irrespective of whether only attached or suspended bacteria were examined, selected for organisms capable of mediating the electron transfer either by direct bacterial transfer or by excretion of redox components.     

Molecular Fingerprinting of Dairy Microbial Ecosystems by Use of Temporal Temperature and Denaturing Gradient Gel Electrophoresis

Numerous microorganisms, including bacteria, yeasts, and molds, constitute the complex ecosystem present in milk and fermented dairy products. Our aim was to describe the bacterial ecosystem of various cheeses that differ by production technology and therefore by their bacterial content. For this purpose, we developed a rapid, semisystematic approach based on genetic profiling by temporal temperature gradient electrophoresis (TTGE) for bacteria with low-G+C-content genomes and denaturing gradient gel electrophoresis (DGGE) for those with medium- and high-G+C-content genomes. Bacteria in the unknown ecosystems were assigned an identity by comparison with a comprehensive bacterial reference database of ~150 species that included useful dairy microorganisms (lactic acid bacteria), spoilage bacteria (e.g., Pseudomonas and Enterobacteriaceae), and pathogenic bacteria (e.g., Listeria monocytogenes and Staphylococcus aureus). Our analyses provide a high resolution of bacteria comprising the ecosystems of different commercial cheeses and identify species that could not be discerned by conventional methods; at least two species, belonging to the Halomonas and Pseudoalteromonas genera, are identified for the first time in a dairy ecosystem. Our analyses also reveal a surprising difference in ecosystems of the cheese surface versus those of the interior; the aerobic surface bacteria are generally G+C rich and represent diverse species, while the cheese interior comprises fewer species that are generally low in G+C content. TTGE and DGGE have proven here to be powerful methods to rapidly identify a broad range of bacterial species within dairy products.     

Coamplification of Eukaryotic DNA with 16S rRNA Gene-Based PCR Primers: Possible Consequences for Population Fingerprinting of Complex Microbial Communities

The main aim of this study was to evaluate the specificity of three commonly used 16S rRNA gene-based polymerase chain reaction (PCR) primer sets for bacterial community analysis of samples contaminated with eukaryotic DNA. The specificity of primer sets targeting the V₃, V₃-V₅, and V₆-V₈ hypervariable regions of the 16S rRNA gene was investigated in silico and by community fingerprinting of human and fish intestinal samples. Both in silico and PCR-based analysis revealed cross-reactivity of the V₃ and V₃-V₅ primers with the 18S rRNA gene of human and sturgeon. The consequences of this primer anomaly were illustrated by denaturing gradient gel electrophoresis (DGGE) profiling of microbial communities in human feces and mixed gut of Siberian sturgeon. DGGE profiling indicated that the cross-reactivity of 16S rRNA gene primers with nontarget eukaryotic DNA might lead to an overestimation of bacterial biodiversity. This study has confirmed previous sporadic indications in literature indicating that several commonly applied 16S rRNA gene primer sets lack specificity toward bacteria in the presence of eukaryotic DNA. The phenomenon of cross-reactivity is a potential source of systematic error in all biodiversity studies where no subsequent analysis of individual community amplicons by cloning and sequencing is performed.     

Development of Steady-State Diffusion Gradients for the Cultivation of Degradative Microbial Consortia

A diffusion gradient plate was constructed and evaluated for its potential use in the isolation of degradative microbial consortia from natural habitats. In this model, a steady-state concentration gradient of diclofop methyl, established by diffusion through an agarose gel, provided the carbon for microbial growth. Colonization of the gel surface was observed with epifluorescence and scanning confocal laser microscopy to determine microbial responses to the diclofop gradient. A detectable gradient developed over a narrow band (<10 mm). Consequently, quantitative analyses of the microbial response to the gradient were difficult to obtain. A two-dimensional, finite-element numerical transport model for advective-diffusive transport was used to simulate concentration and flux profiles in the physical model. The simulated profiles were correlated with the measured concentration gradient (R² = 0.89) and the cell numbers on the gel surface (R² = 0.85). The numerical model was subsequently used to redesign the physical model. The detectable concentration gradient in the modified physical model extended over the length of the gel (38 mm). The simulated profile again showed a good correlation with the measured profile (R² = 0.96) and the microbial responses to the concentration gradient (R² = 0.99). It was concluded that these gradients provide the steady-state environments needed to sustain steady-state consortia. They also provide a physical pathway for the development of degradative biofilms from low to high concentrations of toxicants and simulate conditions under which low concentrations of toxicant are supplied at a constant flux over long periods of time, such as the conditions that could occur in natural environments.     

Aspects of Diversity Measurement for Microbial Communities

A useful measure of diversity was calculated for microbial communities collected from lake water and sediment samples using the Shannon index (H′) and rarefaction [E(S)]. Isolates were clustered by a numerical taxonomy approach in which limited (<20) tests were used so that the groups obtained represented a level of resolution other than species. The numerical value of diversity for each sample was affected by the number of tests used; however, the relative diversity compared among several sampling locations was the same whether 11 or 19 characters were examined. The number of isolates (i.e., sample size) strongly influenced the value of H′ so that unequal sized samples could not be compared. Rarefaction accounts for differences in sample size inherently so that such comparisons are made simple. Due to the type of sampling carried out by microbiologists, H′ is estimated and not determined and therefore requires a statement of error associated with it. Failure to report error provided potentially misleading results. Calculation of the variance of H′ is not a simple matter and may be impossible when handling a large number of samples. With rarefaction, the variance of E(S) is readily determined, facilitating the comparison of many samples.