Christopher B. Blackwood

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

ABSTRACT 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 Wards method and by the unweighted-pair group method using arithmetic averages (UPGMA) were compared. Wards 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 Wards 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.

Assessment of Bias Associated with Incomplete Extraction of Microbial DNA from Soil

ABSTRACT DNA extraction bias is a frequently cited but poorly understood limitation of molecular characterizations of environmental microbial communities. To assess the bias of a commonly used soil DNA extraction kit, we varied the cell lysis protocol and conducted multiple extractions on subsamples of clay, sand, and organic soils. DNA, as well as bacterial and fungal ribosomal gene copies as measured by quantitative PCR, continued to be isolated in successive extractions. When terminal restriction fragment length polymorphism was used, a significant shift in community composition due to extraction bias was detected for bacteria but not for fungi. Pyrosequencing indicated that the relative abundances of sequences from rarely cultivated groups such as Acidobacteria, Gemmatimonades, and Verrucomicrobia were higher in the first extraction than in the sixth but that the reverse was true for Proteobacteria and Actinobacteria. This suggests that the well-known phylum-level bacterial cultivation bias may be partially exaggerated by DNA extraction bias. We conclude that bias can be adequately reduced in many situations by pooling three successive extractions, and additional measures should be considered when divergent soil types are compared or when comprehensive community analysis is necessary.

Interpreting Ecological Diversity Indices Applied to Terminal Restriction Fragment Length Polymorphism Data: Insights from Simulated Microbial Communities

ABSTRACT Ecological diversity indices are frequently applied to molecular profiling methods, such as terminal restriction fragment length polymorphism (T-RFLP), in order to compare diversity among microbial communities. We performed simulations to determine whether diversity indices calculated from T-RFLP profiles could reflect the true diversity of the underlying communities despite potential analytical artifacts. These include multiple taxa generating the same terminal restriction fragment (TRF) and rare TRFs being excluded by a relative abundance (fluorescence) threshold. True community diversity was simulated using the lognormal species abundance distribution. Simulated T-RFLP profiles were generated by assigning each species a TRF size based on an empirical or modeled TRF size distribution. With a typical threshold (1%), the only consistently useful relationship was between Smith and Wilson evenness applied to T-RFLP data (TRF-Evar) and true Shannon diversity (H′), with correlations between 0.71 and 0.81. TRF-H′ and true H′ were well correlated in the simulations using the lowest number of species, but this correlation declined substantially in simulations using greater numbers of species, to the point where TRF-H′ cannot be considered a useful statistic. The relationships between TRF diversity indices and true indices were sensitive to the relative abundance threshold, with greatly improved correlations observed using a 0.1% threshold, which was investigated for comparative purposes but is not possible to consistently achieve with current technology. In general, the use of diversity indices on T-RFLP data provides inaccurate estimates of true diversity in microbial communities (with the possible exception of TRF-Evar). We suggest that, where significant differences in T-RFLP diversity indices were found in previous work, these should be reinterpreted as a reflection of differences in community composition rather than a true difference in community diversity.

Analysis of T-RFLP data using analysis of variance and ordination methods: A comparative study

The analysis of T-RFLP data has developed considerably over the last decade, but there remains a lack of consensus about which statistical analyses offer the best means for finding trends in these data. In this study, we empirically tested and theoretically compared ten diverse T-RFLP datasets derived from soil microbial communities using the more common ordination methods in the literature: principal component analysis (PCA), nonmetric multidimensional scaling (NMS) with Sørensen, Jaccard and Euclidean distance measures, correspondence analysis (CA), detrended correspondence analysis (DCA) and a technique new to T-RFLP data analysis, the Additive Main Effects and Multiplicative Interaction (AMMI) model. Our objectives were i) to determine the distribution of variation in T-RFLP datasets using analysis of variance (ANOVA), ii) to determine the more robust and informative multivariate ordination methods for analyzing T-RFLP data, and iii) to compare the methods based on theoretical considerations. For the 10 datasets examined in this study, ANOVA revealed that the variation from Environment main effects was always small, variation from T-RFs main effects was large, and variation from T-RFxEnvironment (TxE) interactions was intermediate. Larger variation due to TxE indicated larger differences in microbial communities between environments/treatments and thus demonstrated the utility of ANOVA to provide an objective assessment of community dissimilarity. The comparison of statistical methods typically yielded similar empirical results. AMMI, T-RF-centered PCA, and DCA were the most robust methods in terms of producing ordinations that consistently reached a consensus with other methods. In datasets with high sample heterogeneity, NMS analyses with Sørensen and Jaccard distance were the most sensitive for recovery of complex gradients. The theoretical comparison showed that some methods hold distinct advantages for T-RFLP analysis, such as estimations of variation captured, realistic or minimal assumptions about the data, reduced weight placed on rare T-RFs, and uniqueness of solutions. Our results lead us to recommend that method selection be guided by T-RFLP dataset complexity and the outlined theoretical criteria. Finally, we recommend using binary or relativized peak height data with soil-based T-RFLP data for ordination-based exploratory microbial analyses.

Phylum- and Class-Specific PCR Primers for General Microbial Community Analysis

ABSTRACT Amplification of a particular DNA fragment from a mixture of organisms by PCR is a common first step in methods of examining microbial community structure. The use of group-specific primers in community DNA profiling applications can provide enhanced sensitivity and phylogenetic detail compared to domain-specific primers. Other uses for group-specific primers include quantitative PCR and library screening. The purpose of the present study was to develop several primer sets targeting commonly occurring and important groups. Primers specific for the 16S ribosomal sequences of Alphaproteobacteria, Betaproteobacteria, Bacilli, Actinobacteria, and Planctomycetes and for parts of both the 18S ribosomal sequence and the internal transcribed spacer region of Basidiomycota were examined. Primers were tested by comparison to sequences in the ARB 2003 database, and chosen primers were further tested by cloning and sequencing from soil community DNA. Eighty-five to 100% of the sequences obtained from clone libraries were found to be placed with the groups intended as targets, demonstrating the specificity of the primers under field conditions. It will be important to reevaluate primers over time because of the continual growth of sequence databases and revision of microbial taxonomy.

Eubacterial community structure and population size within the soil light fraction, rhizosphere, and heavy fraction of several agricultural systems

The hypothesis that soil light fraction and heavy fraction harbor distinct eubacterial communities and have differing numbers and sizes of bacterial cells was tested in three agronomic cropping systems. This hypothesis would imply that these soil fractions are distinct microbial habitats. Shoot residue and rhizosphere soil were also included in the analysis. Terminal restriction fragment length polymorphism (T-RFLP) of 16S ribosomal DNA was used to assay eubacterial community structure. T-RFLP profiles were affected by both soil fraction and cropping system, accounting for 35 ‐ 50% of the variance in the profiles. T-RFLP profiles separated samples into two distinct eubacterial habitats: soil heavy fraction, which includes the mineral particles and associated humified organic matter, and soil light fraction/shoot residue and rhizosphere, which includes particulate soil organic matter. Differences were not based on organic C content of fractions alone; T-RFLP profiles were also differentiated by cropping system and by rhizosphere versus light fraction/shoot residue. Heavy fraction communities had the least amount of random variability in T-RFLP profiles, resulting in the clearest cropping system effects, while rhizosphere and shoot residue communities were the most variable. Profiles from organically managed corn soil were more variable than for either conventionally managed corn or alfalfa. The log number of bacterial cells per gram fraction was affected by soil fraction but not cropping system, being highest in the light fraction. The percentage of cells . 0.18 mm 3 was also greater in the light fraction than in other fractions. While bacterial cell density was generally correlated with C content of the soil fraction, heavy fraction did have a significantly greater number of cells per mg C than other soil fractions. The results show that habitat diversity in soil, related both to the amounts and types of organic matter, as well as other potential factors, are important in maintaining the high soil bacterial species diversity and evenness that is found in soil. q 2003 Elsevier Ltd. All rights reserved.

Are Basidiomycete Laccase Gene Abundance and Composition Related to Reduced Lignolytic Activity Under Elevated Atmospheric NO3− Deposition in a Northern Hardwood Forest?

Anthropogenic release of biologically available N has increased atmospheric N deposition in forest ecosystems, which may slow decomposition by reducing the lignolytic activity of white-rot fungi. We investigated the potential for atmospheric N deposition to reduce the abundance and alter the composition of lignolytic basidiomycetes in a regional network of four northern hardwood forest stands receiving experimental NO3− deposition (30 kg NO3−−N ha−1 year−1) for a decade. To estimate the abundance of basidiomycetes with lignolytic potential, we used PCR primers targeting laccase (polyphenol oxidase) and quantitative fluorescence PCR to estimate gene copy number. Natural variation in laccase gene size permitted use of length heterogeneity PCR to profile basidiomycete community composition across two sampling dates in forest floor and mineral soil. Although past work has identified significant and consistent negative effects of NO3− deposition on lignolytic enzyme activity, microbial biomass, soil respiration, and decomposition rate, we found no consistent effect of NO3− deposition on basidiomycete laccase gene abundance or community profile. Rather, laccase abundance under NO3− deposition was lower (−52%), higher (+223%), or unchanged, depending on stand. Only a single stand exhibited a significant change in basidiomycete laccase gene profile. Basidiomycete laccase genes occurring in mineral soil were a subset of the genes observed in the forest floor. Moreover, significant effects on laccase abundance were confined to the forest floor, suggesting that species composition plays some role in determining how lignolytic basidiomycetes are affected by N deposition. Community profiles differed between July and October sampling dates, and basidiomycete communities sampled in October had lower laccase gene abundance in the forest floor, but higher laccase abundance in mineral soil. Although experimental N deposition significantly suppresses lignolytic activity in these forests, this change is not related to the abundance or community composition of basidiomycete fungi with laccase genes. Understanding the expression of laccases and other lignolytic enzymes by basidiomycete fungi and other lignin-decaying organisms appears to hold promise for explaining the consistent decline in lignolytic activity elicited by experimental N deposition.

Metacommunity organization of soil microorganisms depends on habitat defined by presence of Lobelia siphilitica plants

We tested regional-scale spatial patterns in soil microbial community composition for agreement with species sorting and dispersal limitation, two alternative mechanisms behind different models of metacommunity organization. Furthermore, we tested whether regional metacommunity organization depends on local habitat type. We sampled from sites across Ohio and West Virginia hosting populations of Lobelia siphilitica, and compared the metacommunity organization of soil microbial communities under L. siphilitica to those in adjacent areas at each site. In the absence of L. siphilitica, bacterial community composition across the region was consistent with species sorting. However, under L. siphilitica, bacterial community composition was consistent with dispersal limitation. Fungal community composition remained largely unexplained, although fungal communities under L. siphilitica were both significantly different in composition and less variable in composition than in adjacent areas. Our results show that communities in different local habitat types (e.g., in the presence or absence of a particular plant) may be structured on a regional scale by different processes, despite being separated by only centimeters at the local scale.

The distribution of below‐ground traits is explained by intrinsic species differences and intraspecific plasticity in response to root neighbours

Summary 1. Large variation in tree root architecture and morphology has been reported for temperate forest communities. However, it is not clear whether this variation represents adaptation of species to specific soil properties, alternative resource acquisition strategies among co-occurring species, or canalized traits without a strong impact on the success of individuals in different environments. Here, our goal was to test these alternative hypotheses and quantify how community-aggregated and intraspecific root trait variations are explained by biotic versus abiotic mechanisms in a temperate deciduous forest. 2. We conducted our study in an Acer-Fagus-dominated forest in north-east Ohio, USA. Using molecular barcoding techniques, we identified 738 root systems belonging to 14 tree species. We measured seven functional root traits related to root architecture and morphology at the species and community-aggregated levels. 3. Although we found significant relationships between soil resource gradients and root trait distributions, intrinsic differences between coexisting species were more important than soil factors in explaining the distribution of root traits in the community. Additionally, root trait variation at the species level was also influenced by the presence of other species within cores. 4. Community-aggregated variation was more influenced by the combination of species present than soil properties in each sample, suggesting that biotic interactions play an important role in controlling community root trait distribution. 5. Synthesis. We propose that root trait differentiation between coexisting species is the result of inherent differences between species and plasticity-mediated responses to neighbours. Hence, the large variation in root traits reported in temperate forest seems to reflect alternative evolutionary pathways that allow individuals to exploit distinct niches in relatively close proximity.

Fine root morphology is phylogenetically structured, but nitrogen is related to the plant economics spectrum in temperate trees

Summary Plant functional traits have revealed trade-offs related to life-history adaptations, geographical distributions, and ecosystem processes. Fine roots are essential in plant resource acquisition and play an important role in soil carbon cycling. Nonetheless, root trait variation is still poorly quantified and rarely related to the rest of the plant. We examined chemical and morphological traits of 34 temperate arbuscular mycorrhizal tree species, representing three main angiosperm clades (super-orders asterid, magnoliid and rosid). We tested to what extent fine root chemical and morphological traits were correlated similarly to the leaf economical spectrum (LES) or were structured by ancestral affiliations among species. Root traits did not display the same trade-offs as leaves (e.g. specific root length was not correlated with root N, whereas specific leaf area was correlated with leaf N). Moreover, 75% of below-ground traits were phylogenetically structured according to Pagels λ and Abouheifs Cmean autocorrelation tests, as opposed to 28% of above-ground traits. Magnoliids showed thicker, less branched roots than asterids or rosids, but rosid roots exhibited lower N and higher non-acid-hydrolysable (e.g. lignin) content than other species. In contrast, leaf traits did not differ significantly among super-orders. At the whole-tree level, chemical traits such as nitrogen tissue content and lignin content were correlated between above and below-ground organs. The distribution of root traits in woody temperate trees was better explained by shared ancestry than by the nutrient content and structural trade-offs expected by the LES hypothesis. Root chemistry and morphology differed substantially among species belonging to different super-orders, suggesting deep divergences in resource acquisition strategies among major angiosperm groups. Although we found partial support for the idea of whole-plant integration based on corresponding nitrogen content across all organs (i.e. a plant economics spectrum), our study stresses phylogenetic affiliation as the primary driver of root trait distributions among angiosperms, a pattern that could be easily overlooked based solely on above-ground observations.