Microbial Maintenance: A Critical Review on Its Quantification

Microbial maintenance is an important concept in microbiology. Its quantification, however, is a subject of continuous debate, which seems to be caused by (1) its definition, which includes nongrowth components other than maintenance; (2) the existence of partly overlapping concepts; (3) the evolution of variables as constants; and (4) the neglect of cell death in microbial dynamics. The two historically most important parameters describing maintenance, the specific maintenance rate and the maintenance coefficient, are based on partly different nongrowth components. There is thus no constant relation between these parameters and previous equations on this subject are wrong. In addition, the partial overlap between these parameters does not allow the use of a simple combination of these parameters. This also applies for combinations of a threshold concentration with one of the other estimates of maintenance. Maintenance estimates should ideally explicitly describe each nongrowth component. A conceptual model is introduced that describes their relative importance and reconciles the various concepts and definitions. The sensitivity of maintenance on underlying components was analyzed and indicated that overall maintenance depends nonlinearly on relative death rates, relative growth rates, growth yield, and endogenous metabolism. This quantitative sensitivity analysis explains the felt need to develop growth-dependent adaptations of existing maintenance parameters, and indicates the importance of distinguishing the various nongrowth components. Future experiments should verify the sensitivity of maintenance components under cellular and environmental conditions.     

Statistical Approach of Functional Profiling for a Microbial Community

Background

Metagenomics is a relatively new but fast growing field within environmental biology and medical sciences. It enables researchers to understand the diversity of microbes, their functions, cooperation, and evolution in a particular ecosystem. Traditional methods in genomics and microbiology are not efficient in capturing the structure of the microbial community in an environment. Nowadays, high-throughput next-generation sequencing technologies are powerfully driving the metagenomic studies. However, there is an urgent need to develop efficient statistical methods and computational algorithms to rapidly analyze the massive metagenomic short sequencing data and to accurately detect the features/functions present in the microbial community. Although several issues about functions of metagenomes at pathways or subsystems level have been investigated, there is a lack of studies focusing on functional analysis at a low level of a hierarchical functional tree, such as SEED subsystem tree.

Results

A two-step statistical procedure (metaFunction) is proposed to detect all possible functional roles at the low level from a metagenomic sample/community. In the first step a statistical mixture model is proposed at the base of gene codons to estimate the abundances for the candidate functional roles, with sequencing error being considered. As a gene could be involved in multiple biological processes the functional assignment is therefore adjusted by utilizing an error distribution in the second step. The performance of the proposed procedure is evaluated through comprehensive simulation studies. Compared with other existing methods in metagenomic functional analysis the new approach is more accurate in assigning reads to functional roles, and therefore at more general levels. The method is also employed to analyze two real data sets.

Conclusions

metaFunction is a powerful tool in accurate profiling functions in a metagenomic sample.     

Evaluating DNA Extraction Methods for Community Profiling of Pig Hindgut Microbial Community

Recovery of high quality PCR-amplifiable DNA has been the general minimal requirement for DNA extraction methods for bulk molecular analysis. However, modern high through-put community profiling technologies are more sensitive to representativeness and reproducibility of DNA extraction method. Here, we assess the impact of three DNA extraction methods (with different levels of extraction harshness) for assessing hindgut microbiomes from pigs fed with different diets (with different physical properties). DNA extraction from each sample was performed in three technical replicates for each extraction method and sequenced by 16S rRNA amplicon sequencing. Host was the primary driver of molecular sequencing outcomes, particularly on samples analysed by wheat based diets, but higher variability, with one failed extraction occurred on samples from a barley fed pig. Based on these results, an effective method will enable reproducible and quality outcomes on a range of samples, whereas an ineffective method will fail to generate extract, but host (rather than extraction method) remains the primary factor.     

Profiling In Situ Microbial Community Structure with an Amplification Microarray

The objectives of this study were to unify amplification, labeling, and microarray hybridization chemistries within a single, closed microfluidic chamber (an amplification microarray) and verify technology performance on a series of groundwater samples from an in situ field experiment designed to compare U(VI) mobility under conditions of various alkalinities (as HCO₃⁻) during stimulated microbial activity accompanying acetate amendment. Analytical limits of detection were between 2 and 200 cell equivalents of purified DNA. Amplification microarray signatures were well correlated with 16S rRNA-targeted quantitative PCR results and hybridization microarray signatures. The succession of the microbial community was evident with and consistent between the two microarray platforms. Amplification microarray analysis of acetate-treated groundwater showed elevated levels of iron-reducing bacteria (Flexibacter, Geobacter, Rhodoferax, and Shewanella) relative to the average background profile, as expected. Identical molecular signatures were evident in the transect treated with acetate plus NaHCO₃, but at much lower signal intensities and with a much more rapid decline (to nondetection). Azoarcus, Thaurea, and Methylobacterium were responsive in the acetate-only transect but not in the presence of bicarbonate. Observed differences in microbial community composition or response to bicarbonate amendment likely had an effect on measured rates of U reduction, with higher rates probable in the part of the field experiment that was amended with bicarbonate. The simplification in microarray-based work flow is a significant technological advance toward entirely closed-amplicon microarray-based tests and is generally extensible to any number of environmental monitoring applications.     

Genotypic and Phenotypic Responses of a Riverine Microbial Community to Polycyclic Aromatic Hydrocarbon Contamination

The phenotypic and genotypic adaptation of a freshwater sedimentary microbial community to elevated (22 to 217 μg g [dry weight] of sediment⁻¹) levels of polycyclic aromatic hydrocarbons (PAHs) was determined by using an integrated biomolecular approach. Central to the approach was the use of phospholipid fatty acid (PLFA) profiles to characterize the microbial community structure and nucleic acid analysis to quantify the frequency of degradative genes. The study site was the Little Scioto River, a highly impacted, channelized riverine system located in central Ohio. This study site is a unique lotic system, with all sampling stations having similar flow and sediment characteristics both upstream and downstream from the source of contamination. These characteristics allowed for the specific analysis of PAH impact on the microbial community. PAH concentrations in impacted sediments ranged from 22 to 217 μg g (dry weight) of sediment⁻¹, while PAH concentrations in ambient sediments ranged from below detection levels to 1.5 μg g (dry weight) of sediment⁻¹. Total microbial biomass measured by phospholipid phosphate (PLP) analysis ranged from 95 to 345 nmol of PLP g (dry weight) of sediment⁻¹. Nucleic acid analysis showed the presence of PAH-degradative genes at all sites, although observed frequencies were typically higher at contaminated sites. Principal component analysis of PLFA profiles indicated that moderate to high PAH concentrations altered microbial community structure and that seasonal changes were comparable in magnitude to the effects of PAH pollution. These data indicate that this community responded to PAH contamination at both the phenotypic and the genotypic level.     

PLFA Profiling of Microbial Community Structure and Seasonal Shifts in Soils of a Douglas-fir Chronosequence

The impact and frequency of forest harvesting could significantly affect soil microbial community (SMC) structure and functioning. The ability of soil microorganisms to perform biogeochemical processes is critical for sustaining forest productivity and has a direct impact on decomposition dynamics and carbon storage potential. The Wind River Canopy Crane Research Forest in SW, WA, provided a unique opportunity to study a forest chronosequence and the residual effects of harvesting on the SMC in comparison to old-growth forests. The objective of this study was to determine the effect of clear-cutting and stand age on temporal dynamics of SMC and physiological stress markers using phospholipid fatty acid (PLFA) profiling. Soil microbial PLFA profiles were determined seven times over 22 months (Nov. 02 to Sep. 04) in old-growth coniferous forest stands (300–500 years) and 8 (CC8)- or 25 (CC25)-year-old replanted clear-cuts. PLFA patterns of the SMC shifted because of clear-cutting, but seasonal temporal changes had greater shifts than differences among stand age. The microbial biomass (total PLFA) and bacterial, fungal, and selected other PLFAs were significantly reduced in CC8 but not in CC25 sites relative to the old-growth sites. An increase in stress indicators [PLFA ratios of saturated/monsaturated and (cy17:0 + cy19:0)/(16:1ω7 + 18:1ω7)] in late summer was related to water stress. Although the canopy and litter input are quite different for a 25-year clear-cut compared to virgin old-growth forest, we conclude that the composition of the microbial communities, 25 years after clear-cutting, has recovered sufficiently to be much more similar to old-growth forests than a recent clear-cut at this Pacific Northwest forest site. The study shows the potential of PLFA analysis for profiling microbial communities and their stress status under field conditions, but wide temporal shifts emphasize the need for sampling over seasons to fully interpret ecosystem management impacts on microbial populations.     

Prey-Dependent Mortality Rate: A Critical Parameter in Microbial Models

Protozoa are key components of a wide range of ecosystems, but ecological models that incorporate these microbes often suffer from poor parameterisation, specifically of top-level predator loss rates. We (1) suggest that top-level predator mortality is prey-dependent, (2) provide a novel approach to assess this response, and (3) illustrate the ecological relevance of these findings. Ciliates, Paramecium caudatum (prey) and Didinium nasutum (predator), were used to evaluate predator mortality at varying prey levels. To assess mortality, multiple (>100) predators were individually examined (in 2-ml wells), daily (for 3 days), between 0 and 120 preys ml⁻¹. Data were used to determine non-linear mortality and growth responses over a range of prey abundances. The responses, plus literature data were then used to parameterise a predator–prey model, based on the Rosenzweig–MacArthur structure. The model assessed the impact of variable and three levels of constant (high, average and low) mortality rates on P. caudatum–D. nasutum population dynamics. Our method to determine variable mortality rate revealed a strong concave decline in mortality with increasing prey abundance. The model indicated: (1) high- and low-constant mortality rates yielded dynamics that deviate substantially from those obtained from a variable rate; (2) average mortality rate superficially produced dynamics similar to the variable rate, but there were differences in the period of predator–prey cycles, and the lowest abundance of prey and predators (by ~2 orders of magnitude). The differences between incorporating variable and constant mortality rate indicate that including a variable rate could substantially improve microbial-based ecological models.     

宏蛋白质组学:研究微生物群落的一种新策略

宏蛋白质组学是一种运用蛋白质组技术对特定微生物群落所产生的全部蛋白质进行大规模研究与分析的新技术。简要概述宏蛋白组学的产生、研究策略及其应用情况,并对其应用前景进行展望。     

Microbial Community Metabolic Modeling: A Community Data‐Driven Network Reconstruction

Metabolic network modeling of microbial communities provides an in‐depth understanding of community‐wide metabolic and regulatory processes. Compared to single organism analyses, community metabolic network modeling is more complex because it needs to account for interspecies interactions. To date, most approaches focus on reconstruction of high‐quality individual networks so that, when combined, they can predict community behaviors as a result of interspecies interactions. However, this conventional method becomes ineffective for communities whose members are not well characterized and cannot be experimentally interrogated in isolation. Here, we tested a new approach that uses community‐level data as a critical input for the network reconstruction process. This method focuses on directly predicting interspecies metabolic interactions in a community, when axenic information is insufficient. We validated our method through the case study of a bacterial photoautotroph–heterotroph consortium that was used to provide data needed for a community‐level metabolic network reconstruction. Resulting simulations provided experimentally validated predictions of how a photoautotrophic cyanobacterium supports the growth of an obligate heterotrophic species by providing organic carbon and nitrogen sources. J. Cell. Physiol. 231: 2339–2345, 2016. © 2016 The Authors. Journal of Cellular Physiology Published by Wiley Periodicals, Inc.     

Microbial Community Composition in a Rehabilitated Bauxite Residue Disposal Area: A Case Study for Improving Microbial Community Composition

The chemical composition of rehabilitated Bauxite Residue Disposal Areas (BRDA) remains the primary indicator of rehabilitation success, with little consideration of microbial community development. We investigated links between the chemical and microbial components of rehabilitated residue at the Aughinish Alumina BRDA (Ireland). Rehabilitated was compared to unamended residue and to an analogy reference soil from unmanaged grassland within the refinery boundary. Bauxite residue comprised of areas with 1, 11, and 12 years following rehabilitation establishment, and gypsum applied at 45 and 90 t/ha. The unamended residue was typical of bauxite residues with high pH (10), sodicity (exchangeable sodium percentage [ESP]‐79), exchangeable sodium (19 cmol/kg), salinity (electrical conductivity [EC] 2.6 mS/cm), and low/negligible nutrient content, microbial biomass (71 µg‐C/g), and fungal phospholipid fatty acid (PLF). Microbial biomass increased 10‐fold with only 1 year of rehabilitation. Gypsum application rate had no effect on microbial biomass. Phospholipid fatty acid analysis (PLFA) demonstrated the emergence of distinct microbial community dependent on rehabilitation time and gypsum application rates. Changes of PLFA profiles were correlated (multiple regressions analysis) to shifts in residue chemical properties (sodicity, organic C, total C, total N, salinity, Mg). An increase of the arbuscular mycorrhizal fungi fatty acid (16:1ω5) with reducing pH has implications on rehabilitation practices. The microbial characteristics of the rehabilitated residue were approaching that of a soil from an unmanaged reference site adjacent to the working site. Gypsum affected PLFA properties, and thereby application has implications for rehabilitation success. For successful ecosystem reconstruction, it is critical that rehabilitation practices consider microbial development.     

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.     

Taxonomic Profiling and Metagenome Analysis of a Microbial Community from a Habitat Contaminated with Industrial Discharges

Industrial units, manufacturing dyes, chemicals, solvents, and xenobiotic compounds, produce liquid and solid wastes, which upon conventional treatment are released in the nearby environment and thus are the major cause of pollution. Soil collected from contaminated Kharicut Canal bank (N 22°57.878′; E 072°38.478′), Ahmedabad, Gujarat, India was used for metagenomic DNA preparation to study the capabilities of intrinsic microbial community in dealing with xenobiotics. Sequencing of metagenomic DNA on the Genome Sequencer FLX System using titanium chemistry resulted in 409,782 reads accounting for 133,529,997 bases of sequence information. Taxonomic analyses and gene annotations were carried out using the bioinformatics platform Sequence Analysis and Management System for Metagenomic Datasets. Taxonomic profiling was carried out by three different complementary approaches: (a) 16S rDNA, (b) environmental gene tags, and (c) lowest common ancestor. The most abundant phylum and genus were found to be “Proteobacteria” and “Pseudomonas,” respectively. Metagenome reads were mapped on sequenced microbial genomes and the highest numbers of reads were allocated to Pseudomonas stutzeri A1501. Assignment of obtained metagenome reads to Gene Ontology terms, Clusters of Orthologous Groups of protein categories, protein family numbers, and Kyoto Encyclopedia of Genes and Genomes hits revealed genomic potential of indigenous microbial community. In total, 157,024 reads corresponded to 37,028 different KEGG hits, and amongst them, 11,574 reads corresponded to 131 different enzymes potentially involved in xenobiotic biodegradation. These enzymes were mapped on biodegradation pathways of xenobiotics to elucidate their roles in possible catalytic reactions. Consequently, information obtained from the present study will act as a baseline which, subsequently along with other “-omic” studies, will help in designing future bioremediation strategies in effluent treatment plants and environmental clean-up projects.     

Insights into Biodegradation Through Depth-Resolved Microbial Community Functional and Structural Profiling of a Crude-Oil Contaminant Plume

Small-scale geochemical gradients are a key feature of aquifer contaminant plumes, highlighting the need for functional and structural profiling of corresponding microbial communities on a similar scale. The purpose of this study was to characterize the microbial functional and structural diversity with depth across representative redox zones of a hydrocarbon plume and an adjacent wetland, at the Bemidji Oil Spill site. A combination of quantitative PCR, denaturing gradient gel electrophoresis, and pyrosequencing were applied to vertically sampled sediment cores. Levels of the methanogenic marker gene, methyl coenzyme-M reductase A (mcrA), increased with depth near the oil body center, but were variable with depth further downgradient. Benzoate degradation N (bzdN) hydrocarbon-degradation gene, common to facultatively anaerobic Azoarcus spp., was found at all locations, but was highest near the oil body center. Microbial community structural differences were observed across sediment cores, and bacterial classes containing known hydrocarbon degraders were found to be low in relative abundance. Depth-resolved functional and structural profiling revealed the strongest gradients in the iron-reducing zone, displaying the greatest variability with depth. This study provides important insight into biogeochemical characteristics in different regions of contaminant plumes, which will aid in improving models of contaminant fate and natural attenuation rates.