Negative effects of sample pooling on PCR-based estimates of soil microbial richness and community structure

Metabarcoding read abundances of orchid mycorrhizal fungi are correlated to copy numbers estimated using ddPCR

Quantifying the abundances of fungi is key to understanding natural variation in mycorrhizal communities in relation to plant ecophysiology and environmental heterogeneity. High-throughput metabarcoding approaches have transformed our ability to characterize and compare complex mycorrhizal communities. However, it remains unclear how well metabarcoding read counts correlate with actual read abundances in the sample, potentially limiting their use as a proxy for species abundances. Here, we use droplet digital PCR (ddPCR) to evaluate the reliability of ITS2 metabarcoding data for quantitative assessments of mycorrhizal communities in the orchid species Neottia ovata sampled at multiple sites. We performed specific ddPCR assays for eight families of orchid mycorrhizal fungi and compared the results with read counts obtained from metabarcoding. Our results demonstrate a significant correlation between DNA copy numbers measured by ddPCR assays and metabarcoding read counts of major mycorrhizal partners of N. ovata, highlighting the usefulness of metabarcoding for quantifying the abundance of orchid mycorrhizal fungi. Yet, the levels of correlation between the two methods and the numbers of false zero values varied across fungal families, which warrants cautious evaluation of the reliability of low-abundance families. This study underscores the potential of metabarcoding data for more quantitative analyses of mycorrhizal communities and presents practical workflows for metabarcoding and ddPCR to achieve a more comprehensive understanding of orchid mycorrhizal communities.

Ranking environmental and edaphic attributes driving soil microbial community structure and activity with special attention to spatial and temporal scales

The incredibly complex soil microbial communities at small scales make their analysis and identification of reasons for the observed structures challenging. Microbial community structure is mainly a result of the inoculum (dispersal), the selective advantages of those organisms under the habitat-based environmental attributes, and the ability of those colonizers to sustain themselves over time. Since soil is protective, and its microbial inhabitants have long adapted to varied soil conditions, significant portions of the soil microbial community structure are likely stable. Hence, a substantial portion of the community will not correlate to often measured soil attributes. We suggest that the drivers be ranked on the basis of their importance to the fundamental needs of the microbes: (i) those that supply energy, i.e., organic carbon and electron acceptors; (ii) environmental effectors or stressors, i.e., pH, salt, drought, and toxic chemicals; (iii) macro-organism associations, i.e., plants and their seasonality, animals and their fecal matter, and soil fauna; and (iv) nutrients, in order, N, P, and probably of lesser importance, other micronutrients, and metals. The relevance of drivers also varies with spatial and time scales, for example, aggregate to field to regional, and persistent to dynamic populations to transcripts, and with the extent of phylogenetic difference, hence phenotypic differences in organismal groups. We present a summary matrix to provide guidance on which drivers are important for particular studies, with special emphasis on a wide range of spatial and temporal scales, and illustrate this with genomic and population (rRNA gene) data from selected studies.

Key factors to consider in the use of environmental DNA metabarcoding to monitor terrestrial ecological restoration

Ecological restoration of terrestrial environments is a globally important process to combat the loss of biodiversity and ecosystem services. Holistic monitoring of restored biota and active management of restoration is necessary to improve restoration processes and outcomes, and provide evidence to stakeholders that targets are being achieved. Increasingly, environmental DNA (eDNA) metabarcoding is used as a restoration monitoring tool because it is able to generate biodiversity data rapidly, accurately, non-destructively, and reliably, on a wide breadth of organisms from soil microbes to mammals. The overall objective of this review is to discuss the key factors to consider in the use of environmental DNA for monitoring of restored terrestrial ecosystems, hopefully improving monitoring, and ultimately, restoration outcomes. We identified that the majority of eDNA based studies of ecosystem restoration are currently conducted in Europe, North America, and Australia, and that almost half of total studies were published in 2021-22. Soil was the most popular sample substrate, soil microbial communities the most targeted taxa, and forests the most studied ecosystem. We suggest there is no 'one size fits all' approach to restoration monitoring using eDNA, and discuss survey design. Factors to consider include substrate selection, sample collection and storage, assay selection, and data interpretation, all of which require careful planning to obtain reliable, and accurate information that can be used for restoration monitoring and decision making. We explore future directions for research and argue that eDNA metabarcoding can be a useful tool in the restoration monitoring 'toolkit', but requires informed application and greater accessibility to data by a wide spectrum of stakeholders.

Land-use types shape soil microbial compositions under rapid urbanization in the Xiong'an New Area, China

For urban planning and infrastructural projects, considerable attention has been paid to the relationship between soil biota, especially protists, and edaphic conditions in various land-use types having different plant species in the Xiong'an New Area of China. To elucidate this relationship, we assessed edaphic variables and soil biota compositions and compared them among 5 habitat types: human-made forests, crop cultivations, arid rivers, Baiyangdian (BYD) Lake, and around oil wells. In all, 12 experimental plots from terrestrial and aquatic ecosystems were assessed using high-throughput sequencing of environmental DNA, targeting the V3-V4 region of the 16S rRNA gene, internal transcribed spacer 1, and V4 region of the 18S rRNA gene for bacteria, fungi, and protists, respectively. The abundance of bacterial and protist communities was higher than fungi, possibly because fungi prefer acidic soil conditions and likely have greater susceptibility to anthropogenic activities. Across all experimental plots, land-use types contributed the most to the β-diversity of soil biota, followed by soil moisture. Diversity and richness were significantly higher at aquatic habitats than at terrestrial habitats. Predictive metagenomic analysis of trophic groups predicted relatively high frequency of functional genes from bacterial metabolism pathways (carbohydrate and amino acid); contrary to expectation, phototrophic protists, but not fungal symbionts and protistan consumers, were the dominant group at the BYD Lake. Geographical coordinates showed significant (P < 0.05) relationships with all microbiome taxa (nodes at network) from all land-use types. Moreover, soil-microbiome relationships were more complex and more intense at crop habitats. Links between protist and fungal taxa were the highest at the petroleum-contaminated sampling sites, indicating the importance of these two soil microbiomes in polluted soil. Thus, our findings suggest that human manipulation and land-use types are crucial factors for soil biota structure and composition across our sampling sites.

Comparing Quantitative Methods for Analyzing Sediment DNA Records of Cyanobacteria in Experimental and Reference Lakes

Sediment DNA (sedDNA) analyses are rapidly emerging as powerful tools for the reconstruction of environmental and evolutionary change. While there are an increasing number of studies using molecular genetic approaches to track changes over time, few studies have compared the coherence between quantitative polymerase chain reaction (PCR) methods and metabarcoding techniques. Primer specificity, bioinformatic analyses, and PCR inhibitors in sediments could affect the quantitative data obtained from these approaches. We compared the performance of droplet digital polymerase chain reaction (ddPCR) and high-throughput sequencing (HTS) for the quantification of target genes of cyanobacteria in lake sediments and tested whether the two techniques similarly reveal expected patterns through time. Absolute concentrations of cyanobacterial 16S rRNA genes were compared between ddPCR and HTS using dated sediment cores collected from two experimental (Lake 227, fertilized since 1969 and Lake 223, acidified from 1976 to 1983) and two reference lakes (Lakes 224 and 442) in the Experimental Lakes Area (ELA), Canada. Relative abundances of Microcystis 16S rRNA (MICR) genes were also compared between the two methods. Moderate to strong positive correlations were found between the molecular approaches among all four cores but results from ddPCR were more consistent with the known history of lake manipulations. A 100-fold increase in ddPCR estimates of cyanobacterial gene abundance beginning in ~1968 occurred in Lake 227, in keeping with experimental addition of nutrients and increase in planktonic cyanobacteria. In contrast, no significant rise in cyanobacterial abundance associated with lake fertilization was observed with HTS. Relative abundances of Microcystis between the two techniques showed moderate to strong levels of coherence in top intervals of the sediment cores. Both ddPCR and HTS approaches are suitable for sedDNA analysis, but studies aiming to quantify absolute abundances from complex environments should consider using ddPCR due to its high tolerance to PCR inhibitors.

Short-lived detection of an introduced vertebrate eDNA signal in a nearshore rocky reef environment

Environmental DNA (eDNA) is increasingly used to measure biodiversity of marine ecosystems, yet key aspects of the temporal dynamics of eDNA remain unknown. Of particular interest is in situ persistence of eDNA signals in dynamic marine environments, as eDNA degradation rates have predominantly been quantified through mesocosm studies. To determine in situ eDNA residence times, we introduced an eDNA signal from a non-native fish into a protected bay of a Southern California rocky reef ecosystem, and then measured changes in both introduced and background eDNA signals across a fixed transect over 96 hours. Foreign eDNA signal was no longer detected only 7.5 hours after introduction, a time substantially shorter than the multi-day persistence times in laboratory studies. Moreover, the foreign eDNA signal spread along the entire 38 m transect within 1.5 hours after introduction, indicating that transport and diffusion play a role in eDNA detectability even in protected low energy marine environments. Similarly, native vertebrate eDNA signals varied greatly over the 96 hours of observation as well as within two additional nearby fixed transects sampled over 120 hours. While community structure did significantly change across time of day and tidal direction, neither accounted for the majority of observed variation. Combined, results show that both foreign and native eDNA signatures can exhibit substantial temporal heterogeneity, even on hourly time scales. Further work exploring eDNA decay from lagrangian perspective and quantifying effects of sample and technical replication are needed to better understand temporal variation of eDNA signatures in nearshore marine environments.

Sampling forest soils to describe fungal diversity and composition. Which is the optimal sampling size in mediterranean pure and mixed pine oak forests?

Soil sampling is a critical step affecting perceived fungal diversity, however sampling optimization for high-throughput-DNA sequencing studies have never been tested in Mediterranean forest ecosystems. We identified the minimum number of pooled samples needed to obtain a reliable description of fungal communities in terms of diversity and composition in three different Mediterranean forests (pine, oak, and mixed-pine-oak). Twenty soil samples were randomly selected in each of the three plots per type. Samples obtained in 100 m² plots were pooled to obtain mixtures of 3, 6, 10, 15, 20 samples, and sequenced using Illumina MiSeq of fungal ITS2 amplicons. Pooling three soil samples in Pinus and Quercus stands provided consistent richness estimations, while at least six samples were needed in mixed-stands. β-diversity decreased with increasing sample pools in monospecific-stands, while there was no effect of sample pool size on mixed-stands. Soil sample pooling had no effect over species composition. We estimate that three samples would be already optimal to describe fungal richness and composition in Mediterranean pure stands, while at least six samples would be needed in mixed stands.

A framework to bridge scales in distribution modeling of soil microbiota

Creating accurate habitat suitability and distribution models (HSDMs) for soil microbiota is far more challenging than for aboveground organism groups. In this perspective paper, we propose a conceptual framework that addresses several of the critical issues holding back further applications. Most importantly, we tackle the mismatch between the broadscale, long-term averages of environmental variables traditionally used, and the environment as experienced by soil microbiota themselves. We suggest using nested sampling designs across environmental gradients and objectively integrating spatially hierarchic heterogeneity as covariates in HSDMs. Second, to incorporate the crucial role of taxa co-occurrence as driver of soil microbial distributions, we promote the use of joint species distribution models, a class of models that jointly analyze multiple species’ distributions, quantifying both species-specific environmental responses (i.e. the environmental niche) and covariance among species (i.e. biotic interactions). Our approach allows incorporating the environmental niche and its associated distribution across multiple spatial scales. The proposed framework facilitates the inclusion of the true relationships between soil organisms and their abiotic and biotic environments in distribution models, which is crucial to improve predictions of soil microbial redistributions as a result of global change.

Impacts of Sampling Design on Estimates of Microbial Community Diversity and Composition in Agricultural Soils

Soil microbiota play important and diverse roles in agricultural crop nutrition and productivity. Yet, despite increasing efforts to characterize soil bacterial and fungal assemblages, it is challenging to disentangle the influences of sampling design on assessments of communities. Here, we sought to determine whether composite samples-often analyzed as a low cost and effort alternative to replicated individual samples-provide representative summary estimates of microbial communities. At three Minnesota agricultural research sites planted with an oat cover crop, we conducted amplicon sequencing for soil bacterial and fungal communities (16S_V4 and ITS2) of replicated individual or homogenized composite soil samples. We compared soil microbiota from within and among plots and then among agricultural sites using both sampling strategies. Results indicated that single or multiple replicated individual samples, or a composite sample from each plot, were sufficient for distinguishing broad site-level macroecological differences among bacterial and fungal communities. Analysis of a single sample per plot captured only a small fraction of the distinct OTUs, diversity, and compositional variability detected in the analysis of multiple individual samples or a single composite sample. Likewise, composite samples captured only a fraction of the diversity represented by the six individual samples from which they were formed, and, on average, analysis of two or three individual samples offered greater compositional coverage (i.e., greater number of OTUs) than a single composite sample. We conclude that sampling design significantly impacts estimates of bacterial and fungal communities even in homogeneously managed agricultural soils, and our findings indicate that while either strategy may be sufficient for broad macroecological investigations, composites may be a poor substitute for replicated samples at finer spatial scales.

Dairy soil bacterial responses to nitrogen application in simulated Italian ryegrass and white clover pasture

Through clearing and use of fertilizer and legumes, areas of southwestern Australia's unique coastal sand plains can support relatively low-cost dairies. However, the ancient, highly weathered nature of the soils in this region makes the dairies susceptible to a range of threats, including nutrient leaching and erosion. Despite this, Western Australian dairy cows typically produce up to 5,500 L of milk per head annually supported by inorganic nitrogen (N) fertilizer (commonly 50:50 urea and ammonium sulfate) at rates up to <320 kg of N/ha per year. Where hotspots exist (up to 2,000 kg of N/ha per year), total N exceeds pasture requirements. We investigated plant and soil bacteria responses to N fertilizer rates consistent with Australian legislated production practices on dairy farms for pure and mixed swards of white clover (Trifolium repens) and Italian ryegrass (Lolium multiflorum) in a long-term pasture experiment in controlled glasshouse conditions. Although the soil bacterial community structure at phylum level was similar for white clover and Italian ryegrass, relative abundances of specific subgroups of bacteria differed among plant species according to the N fertilizer regimen. Marked increases in relative abundance of some bacterial phyla and subphyla indicated potential inhibition of N cycling, especially for N hotspots in soil. Ammonium concentration in soil was less correlated with dominance of some N-cycling bacterial phyla than was nitrate concentration. Changes in bacterial community structure related to altered nutrient cycling highlight the potential for considering this area of research in policy assessment frameworks related to nutrient loads in dairy soils, especially for N.

Towards robust and repeatable sampling methods in eDNA-based studies

DNA-based techniques are increasingly used for measuring the biodiversity (species presence, identity, abundance and community composition) of terrestrial and aquatic ecosystems. While there are numerous reviews of molecular methods and bioinformatic steps, there has been little consideration of the methods used to collect samples upon which these later steps are based. This represents a critical knowledge gap, as methodologically sound field sampling is the foundation for subsequent analyses. We reviewed field sampling methods used for metabarcoding studies of both terrestrial and freshwater ecosystem biodiversity over a nearly three-year period (n = 75). We found that 95% (n = 71) of these studies used subjective sampling methods and inappropriate field methods and/or failed to provide critical methodological information. It would be possible for researchers to replicate only 5% of the metabarcoding studies in our sample, a poorer level of reproducibility than for ecological studies in general. Our findings suggest greater attention to field sampling methods, and reporting is necessary in eDNA-based studies of biodiversity to ensure robust outcomes and future reproducibility. Methods must be fully and accurately reported, and protocols developed that minimize subjectivity. Standardization of sampling protocols would be one way to help to improve reproducibility and have additional benefits in allowing compilation and comparison of data from across studies.

Half-lives of PAHs and temporal microbiota changes in commonly used urban landscaping materials

Background

Polycyclic aromatic hydrocarbons (PAHs) accumulate in urban soils, and PAH contamination can change soil microbial community composition. Environmental microbiota is associated with human commensal microbiota, immune system and health. Therefore, studies investigating the degradation of PAHs, and the consequences of soil pollution on microbial communities in urban landscaping materials, are crucial.

Methods

Four landscaping materials (organic matter 1, 2, 13 and 56%) were contaminated with PAHs commonly found at urban sites (phenanthrene, fluoranthene, pyrene, chrysene and benzo(b)fluoranthene) in PAH concentrations that reflect urban soils in Finland (2.4 µg g ^-1 soil dry weight). PAHs were analyzed initially and after 2, 4, 8 and 12 weeks by gas chromatography-mass spectrometry. Half-lives of PAHs were determined based on 12-weeks degradation. Bacterial communities were analyzed at 1 and 12 weeks after contamination using Illumina MiSeq 16S rRNA gene metabarcoding.

Results

Half-lives ranged from 1.5 to 4.4 weeks for PAHs with relatively low molecular weights (phenanthrene, fluoranthene and pyrene) in landscaping materials containing 1–2% organic matter. In contrast, in materials containing 13% and 56% organic matter, the half-lives ranged from 2.5 to 52 weeks. Shorter half-lives of phenanthrene and fluoranthene were thus associated with low organic matter content. The half-life of pyrene was inversely related to the relative abundance of Beta-, Delta- and Gammaproteobacteria, and diversity of Bacteroidetes and Betaprotebacteria. Compounds with higher molecular weights followed compound-specific patterns. Benzo(b)fluoranthene was resistant to degradation and half-life of chrysene was shorter when the relative abundance of Betaproteobacteria was high. Temporal microbiota changes involved increase in the relative abundance of Deltaproteobacteria and decrease in genera Flavobacterium and Rhodanobacter. Exposure to PAHs seems to adjust microbial community composition, particularly within class Beta- and Deltaproteobacteria.

Conclusions

In this study, PAH degradation depended on the organic matter content and bacterial community composition of landscaping materials. Contamination seems to alter bacterial community composition in landscaping materials depending on material type. This alteration includes changes in bacterial phyla associated with human health and immune system. This may open new possibilities for managing urban environments by careful selection of landscaping materials, to benefit health and wellbeing.

Usefulness and limitations of sample pooling for environmental DNA metabarcoding of freshwater fish communities

Environmental DNA (eDNA) metabarcoding has been used increasingly to assess biodiversity of aquatic vertebrates. However, there still remains to be developed a sampling design of eDNA metabarcoding that can ensure high detection rates of species with minimum total survey effort, especially for large-scale surveys of aquatic organisms. We here tested whether pooling of eDNA samples can be used to evaluate biodiversity of freshwater fishes in four satellite lakes of Lake Biwa, Japan. Fish communities detected by eDNA metabarcoding of the mitochondrial 12S region were compared between the individual and pooled samples. In the individual samples, 31, 22, 33, and 31 fish lineages (proxies for species) were observed at the respective sites, within which moderate spatial autocorrelation existed. In the pooled samples, 30, 20, 29, and 27, lineages were detected, respectively, even after 15 PCR replicates. Lineages accounting for < 0.05% of the total read count of each site’s individual samples were mostly undetectable in the pooled samples. Moreover, fish communities detected were similar among PCR replicates in the pooled samples. Because of the decreased detection rates, the pooling strategy is unsuitable for estimating fish species richness. However, this procedure is useful potentially for among-site comparison of representative fish communities.

Soil DNA pyrosequencing and fruitbody surveys reveal contrasting diversity for various fungal ecological guilds in chestnut orchards

Fungal diversity in Mediterranean forest soils is poorly documented, particularly when considering saprobic and pathogenic organisms. Next-generation sequencing (NGS) methods applied to soil fungi provide the opportunity to unveil the most inconspicuous functional guilds (e.g. saprobes) and life forms (e.g. Corticiaceae) of this tremendous diversity. We used fruitbody surveys over 2 years and soil 454 metabarcoding in Castanea sativa orchards to evaluate respectively the reproductive (fruitbodies) and vegetative (mycelia) parts of fungal communities in three 100-year-old stands. Analysis of 839 fruitbodies and 210 291 ITS1 reads revealed high fungal diversity, mainly shown by belowground analysis, with high (dominant) abundance of mycorrhizal fruitbodies and reads. Both methods displayed contrasted composition and structure of fungal communities, with Basidio- and Ascomycetes dominating above- and belowground, respectively. For the two dominant fungal guilds (i.e. ectomycorrhizal and saprobic), diversity above- and belowground overlapped weakly. This study is the first assessment of the complementarity of fruitbody surveys and NGS for analysing fungal diversity in Mediterranean ecosystems and shows that belowground methods still need to be completed by fruiting diversity to provide a comprehensive overview of the different fungal guilds. The results shed light on chestnut soil biodiversity and question the spatial distribution and synergies among fungal guilds.

Subgingival microbiome in smokers and non-smokers in Korean chronic periodontitis patients

Smoking is a major environmental factor associated with periodontal diseases. However, we still have a very limited understanding of the relationship between smoking and subgingival microflora in the global population. Here, we investigated the composition of subgingival bacterial communities from the pooled plaque samples of smokers and non-smokers, 134 samples in each group, in Korean patients with moderate chronic periodontitis using 16S rRNA gene-based pyrosequencing. A total of 17,927 reads were analyzed and classified into 12 phyla, 126 genera, and 394 species. Differences in bacterial communities between smokers and non-smokers were examined at all phylogenetic levels. The genera Fusobacterium, Fretibacterium, Streptococcus, Veillonella, Corynebacterium, TM7, and Filifactor were abundant in smokers. On the other hand, Prevotella, Campylobacter, Aggregatibacter, Veillonellaceae GQ422718, Haemophilus, and Prevotellaceae were less abundant in smokers. Among species-level taxa occupying > 1% of whole subgingival microbiome of smokers, higher abundance (≥ 2.0-fold compared to non-smokers) of seven species or operational taxonomic units (OTUs) was found: Fusobacterium nucleatum, Neisseria sicca, Neisseria oralis, Corynebacterium matruchotii, Veillonella dispar, Filifactor alocis, and Fretibacterium AY349371. On the other hand, lower abundance of 11 species or OTUs was found in smokers: Neisseria elongata, six Prevotella species or OTUs, Fusobacterium canifelinum, Aggregatibacter AM420165, Selenomonas OTU, and Veillonellaceae GU470897. Species richness and evenness were similar between the groups whereas diversity was greater in smokers than non-smokers. Collectively, the results of the present study indicate that differences exist in the subgingival bacterial community between smoker and non-smoker patients with chronic moderate periodontitis in Korea, suggesting that cigarette smoking considerably affects subgingival bacterial ecology.

DNA extraction protocols cause differences in 16S rRNA amplicon sequencing efficiency but not in community profile composition or structure

The recent development of methods applying next-generation sequencing to microbial community characterization has led to the proliferation of these studies in a wide variety of sample types. Yet, variation in the physical properties of environmental samples demands that optimal DNA extraction techniques be explored for each new environment. The microbiota associated with many species of insects offer an extraction challenge as they are frequently surrounded by an armored exoskeleton, inhibiting disruption of the tissues within. In this study, we examine the efficacy of several commonly used protocols for extracting bacterial DNA from ants. While bacterial community composition recovered using Illumina 16S rRNA amplicon sequencing was not detectably biased by any method, the quantity of bacterial DNA varied drastically, reducing the number of samples that could be amplified and sequenced. These results indicate that the concentration necessary for dependable sequencing is around 10,000 copies of target DNA per microliter. Exoskeletal pulverization and tissue digestion increased the reliability of extractions, suggesting that these steps should be included in any study of insect-associated microorganisms that relies on obtaining microbial DNA from intact body segments. Although laboratory and analysis techniques should be standardized across diverse sample types as much as possible, minimal modifications such as these will increase the number of environments in which bacterial communities can be successfully studied.

Leaf and root-associated fungal assemblages do not follow similar elevational diversity patterns

The diversity of fungi along environmental gradients has been little explored in contrast to plants and animals. Consequently, environmental factors influencing the composition of fungal assemblages are poorly understood. The aim of this study was to determine whether the diversity and composition of leaf and root-associated fungal assemblages vary with elevation and to investigate potential explanatory variables. High-throughput sequencing of the Internal Transcribed Spacer 1 region was used to explore fungal assemblages along three elevation gradients, located in French mountainous regions. Beech forest was selected as a study system to minimise the host effect. The variation in species richness and specific composition was investigated for ascomycetes and basidiomycetes assemblages with a particular focus on root-associated ectomycorrhizal fungi. The richness of fungal communities associated with leaves or roots did not significantly relate to any of the tested environmental drivers, i.e. elevation, mean temperature, precipitation or edaphic variables such as soil pH or the ratio carbon∶nitrogen. Nevertheless, the ascomycete species richness peaked at mid-temperature, illustrating a mid-domain effect model. We found that leaf and root-associated fungal assemblages did not follow similar patterns of composition with elevation. While the composition of the leaf-associated fungal assemblage correlated primarily with the mean annual temperature, the composition of root-associated fungal assemblage was explained equally by soil pH and by temperature. The ectomycorrhizal composition was also related to these variables. Our results therefore suggest that above and below-ground fungal assemblages are not controlled by the same main environmental variables. This may be due to the larger amplitude of climatic variables in the tree foliage compared to the soil environment.

Recommendations following a multi-laboratory comparison of microbial source tracking methods

Microbial source tracking (MST) methods were evaluated in the Source Identification Protocol Project (SIPP), in which 27 laboratories compared methods to identify host sources of fecal pollution from blinded water samples containing either one or two different fecal types collected from California. This paper details lessons learned from the SIPP study and makes recommendations to further advance the field of MST. Overall, results from the SIPP study demonstrated that methods are available that can correctly identify whether particular host sources including humans, cows and birds have contributed to contamination in a body of water. However, differences between laboratory protocols and data processing affected results and complicated interpretation of MST method performance in some cases. This was an issue particularly for samples that tested positive (non-zero Ct values) but below the limits of quantification or detection of a PCR assay. Although false positives were observed, such samples in the SIPP study often contained the fecal pollution source that was being targeted, i.e., the samples were true positives. Given these results, and the fact that MST often requires detection of targets present in low concentrations, we propose that such samples be reported and identified in a unique category to facilitate data analysis and method comparisons. Important data can be lost when such samples are simply reported as positive or negative. Actionable thresholds were not derived in the SIPP study due to limitations that included geographic scope, age of samples, and difficulties interpreting low concentrations of target in environmental samples. Nevertheless, the results of the study support the use of MST for water management, especially to prioritize impaired waters in need of remediation. Future integration of MST data into quantitative microbial risk assessments and other models could allow managers to more efficiently protect public health based on site conditions.

Microbes on the cliff: alpine cushion plants structure bacterial and fungal communities

Plants affect the spatial distribution of soil microorganisms, but the influence of the local abiotic context is poorly documented. We investigated the effect of a single plant species, the cushion plant Silene acaulis, on habitat conditions, and microbial community. We collected soil from inside (In) and outside (Out) of the cushions on calcareous and siliceous cliffs in the French Alps along an elevation gradient (2,000–3,000 masl). The composition of the microbial communities was assessed by Capillary-Electrophoresis Single Strand Conformation Polymorphism (CE-SSCP). Univariate and multivariate analyses were conducted to characterize the response of the microbial beta-diversity to soil parameters (total C, total N, soil water content, N-NH4+,N-NO3-, and pH). Cushions affected the microbial communities, modifying soil properties. The fungal and bacterial communities did not respond to the same abiotic factors. Outside the cushions, the bacterial communities were strongly influenced by bedrock. Inside the cushions, the bacterial communities from both types of bedrock were highly similar, due to the smaller pH differences than in open areas. By contrast, the fungal communities were equally variable inside and outside of the cushions. Outside the cushions, the fungal communities responded weakly to soil pH. Inside the cushions, the fungal communities varied strongly with bedrock and elevation as well as increases in soil nutrients and water content. Furthermore, the dissimilarities in the microbial communities between the In and Out habitats increased with increasing habitat modification and environmental stress. Our results indicate that cushions act as a selective force that counteracts the influence of the bedrock and the resource limitations on the bacterial and fungal communities by buffering soil pH and enhancing soil nutrients. Cushion plants structure microbial communities, and this effect increases in stressful, acidic and nutrient-limited environments.

Nutrient removal and greenhouse gas emissions in duckweed treatment ponds

Stormwater treatment ponds provide a variety of functions including sediment retention, organic and nutrient removal, and habitat restoration. The treatment ponds are, however, also a source of greenhouse gases. The objectives of this study were to assess greenhouse gas (CH(4), CO(2) and N(2)O) emissions in duckweed treatment ponds (DWPs) treating simulated stormwater and to determine the role of ammonia-oxidizing organisms in nutrient removal and methanogens in greenhouse gas emissions. Two replicated DWPs operated at a hydraulic retention time (HRT) of 10 days were able to remove 84% (± 4% [standard deviation]) chemical oxygen demand (COD), 79% (± 3%) NH(4)(+)-N, 86% (± 2%) NO(3)(-)-N and 56% (± 7%) orthophosphate. CH(4) emission rates in the DWPs ranged from 502 to 1900 mg CH(4) m(-2) d(-1) while those of nitrous oxide (N(2)O) ranged from 0.63 to 4 mg N(2)O m(-2) d(-1). The CO(2) emission rates ranged from 1700 to 3300 mg CO(2) m(-2) day(-1). Duckweed coverage on water surface along with the continued deposit of duckweed debris in the DWPs and low-nutrient influent water created a low dissolved oxygen environment for the growth of unique ammonia-oxidizing organisms and methanogens. Archaeal and bacterial amoA abundance in the DWPs ranged from (1.5 ± 0.2) × 10(7) to (1.7 ± 0.2) × 10(8) copies/g dry soil and from (1.0 ± 0.3) × 10(3) to (1.5 ± 0.4) × 10(6) copies/g dry soil, respectively. The 16S rRNA acetoclastic and hydrogenotrophic methanogens ranged from (5.2 ± 0.2) × 10(5) to (9.0 ± 0.3) × 10(6) copies/g dry soil and from (1.0 ± 0.1) × 10(2) to (5.5 ± 0.4) × 10(3) copies/g dry soil, respectively. Ammonia-oxidizing archaea (AOA) appeared to be the dominant nitrifiers and acetoclastic Methanosaeta was the major methanogenic genus. The results suggest that methane is the predominant (>90%) greenhouse gas in the DWPs, where the relatively low stormwater nutrient inputs facilitate the growth of K-strategists such as AOA and Methanosaeta that may be responsible for ammonia removal and greenhouse gas emissions, respectively.

Temporal and spatial distributions of ammonia-oxidizing archaea and bacteria and their ratio as an indicator of oligotrophic conditions in natural wetlands

Ammonia-oxidizing organisms play an important role in wetland water purification and nitrogen cycling. We determined soil nitrification rates and investigated the seasonal and spatial distributions of ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) in three freshwater wetlands by using specific primers targeting the amoA genes of AOA and AOB and real-time quantitative polymerase chain reaction (qPCR). The nitrifying potentials of wetland soils ranged from 1.4 to 4.0 μg g(-1) day(-1). The specific rates of ammonia oxidation activity by AOA and AOB at the Bee Hollow wetlands were 1.9 fmol NH(3) cell(-1) day(-1) and 36.8 fmol NH(3) cell(-1) day(-1), respectively. Soil nitrification potential was positively correlated with both archaeal and bacterial amoA abundance. However, the gene copies of AOA amoA were higher than those of AOB amoA by at least an order of magnitude in wetland soils and water in both summer and winter over a three year study period. AOB were more sensitive to low temperature than AOA. The amoA gene copy ratios of AOA to AOB in top soils (0-10 cm) ranged from 19 ± 4 to 100 ± 11 among the wetland sites. In contrast, the ratio of the wetland boundary soil was 10 ± 2, which was significantly lower than that of the wetland soils (P < 0.001). The NH(4)(+)-N concentrations in wetland water were lower than 2 mg/L throughout the study. The results suggest that ammonium concentration is a major factor influencing AOA and AOB population in wetlands, although other factors such as temperature, dissolved oxygen, and soil organic matter are involved. AOA are more persistent and more abundant than AOB in the nutrient-depleted oligotrophic wetlands. Therefore, ratio of AOA amoA gene copies to AOB amoA gene copies may serve as a new biological indicator for wetland condition assessment and wetland restoration applications.

Rare target enrichment for ultrasensitive PCR detection using cot-rehybridization and duplex-specific nuclease

Nucleic acid detection by polymerase chain reaction (PCR) is invaluable for the detection of dilute and rare sequences, including pathogens and infrequent species in complex clinical and environmental backgrounds. The presence of excess complex background nucleic acid can reduce sensitivity and specificity. This is because mispriming can cause failure of the amplification reaction. Here we describe a new approach to ultrasensitive PCR detection, using enrichment of rare target nucleic acid from abundant background by combining the classic technique of cot-rehybridization to convert the abundant background to double-stranded form, with the use of a newly described, highly processive duplex-specific crab nuclease. We show that trace sequences in a vast excess of background DNA can be undetectable by PCR, independent of the amount of the mixture added to the PCR, and that these sequences can be made detectable by background suppression using this method.

Evaluation of methods for the extraction of DNA from drinking water distribution system biofilms

While drinking water biofilms have been characterized in various drinking water distribution systems (DWDS), little is known about the impact of different DNA extraction methods on the subsequent analysis of microbial communities in drinking water biofilms. Since different DNA extraction methods have been shown to affect the outcome of microbial community analysis in other environments, it is necessary to select a DNA extraction method prior to the application of molecular tools to characterize the complex microbial ecology of the DWDS. This study compared the quantity and quality of DNA yields from selected DWDS bacteria with different cell wall properties using five widely used DNA extraction methods. These were further selected and evaluated for their efficiency and reproducibility of DNA extraction from DWDS samples. Terminal restriction fragment length analysis and the 454 pyrosequencing technique were used to interpret the differences in microbial community structure and composition, respectively, from extracted DNA. Such assessments serve as a concrete step towards the determination of an optimal DNA extraction method for drinking water biofilms, which can then provide a reliable comparison of the meta-analysis results obtained in different laboratories.

The influence of sampling strategies and spatial variation on the detected soil bacterial communities under three different land-use types

To determine the influence of pooling strategies on detected soil bacterial communities, we sampled 45 soil cores each from a eucalypt woodland, a sown pasture and a revegetated site in an Australian landscape. We assessed the spatial variation within each land-use plot, including the influence of sampling distance, soil chemical characteristics and, where appropriate, proximity to trees on the soil bacterial community, by generating terminal restriction fragment length polymorphism profiles of the bacterial 16S rRNA genes. The soil bacterial community under the revegetated site was more similar to the original woodland than the pasture, and this result was found regardless of the soil- or the DNA-pooling strategy used. Analyzing as few as eight cores per plot was sufficient to detect significant differences between the bacterial communities under the different plots to be distinguished. Soil pH was found to be most strongly associated with soil bacterial community composition within the plots and there was no association found with proximity to trees. This study has investigated sampling strategies for further research into the transitions of soil microbial communities with land-use change across broader temporal and spatial scales.

Genotype is a stronger determinant than sex of the mouse gut microbiota

The mammalian gut microbiota is considered to be determined mostly by diet, while the effect of genotype is still controversial. Here, we examined the effect of genotype on the gut microbiota in normal populations, exhibiting only natural polymorphisms, and evaluated this effect in comparison to the effect of sex. DNA fingerprinting approaches were used to profile the gut microbiota of eight different recombinant inbred mouse lines of the collaborative cross consortium, whose level of genetic diversity mimics that of a natural human population. Analyses based on automated ribosomal internal transcribed spacer analysis demonstrated significant higher similarity of the gut microbiota composition within mouse lines than between them or within same-gender groups. Thus, genetic background significantly impacts the microbiota composition and is a stronger determinant than gender. These findings imply that genetic polymorphisms help shape the intestinal microbiota of mammals and consequently could affect host susceptibility to diseases.

Animal-to-animal variation in fecal microbial diversity among beef cattle

The intestinal microbiota of beef cattle are important for animal health, food safety, and methane emissions. This full-length sequencing survey of 11,171 16S rRNA genes reveals animal-to-animal variation in communities that cannot be attributed to breed, gender, diet, age, or weather. Beef communities differ from those of dairy. Core bovine taxa are identified.