Strengths and Limitations of 16S rRNA Gene Amplicon Sequencing in Revealing Temporal Microbial Community Dynamics

<div><p>This study explored the short-term planktonic microbial community structure and resilience in Lake Lanier (GA, USA) while simultaneously evaluating the technical aspects of identifying taxa via 16S rRNA gene amplicon and metagenomic sequence data. 16S rRNA gene amplicons generated from four temporally discrete samples were sequenced with 454 GS-FLX-Ti yielding ∼40,000 rRNA gene sequences from each sample and representing ∼300 observed OTUs. Replicates obtained from the same biological sample clustered together but several biases were observed, linked to either the PCR or sequencing-preparation steps. In comparisons with companion whole-community shotgun metagenome datasets, the estimated number of OTUs at each timepoint was concordant, but 1.5 times and ∼10 times as many phyla and genera, respectively, were identified in the metagenomes. Our analyses showed that the 16S rRNA gene captures broad shifts in community diversity over time, but with limited resolution and lower sensitivity compared to metagenomic data. We also identified OTUs that showed marked shifts in abundance over four close timepoints separated by perturbations and tracked these taxa in the metagenome vs. 16S rRNA amplicon data. A strong summer storm had less of an effect on community composition than did seasonal mixing, which revealed a distinct succession of organisms. This study provides insights into freshwater microbial communities and advances the approaches for assessing community diversity and dynamics <i>in situ</i>.</p></div

Individual genera abundance shifts over time based on 16S and metagenomes.

<p>Genus-level taxonomic trends for a subset of genera identified within the metagenomic contigs (A) and 16S rRNA amplicon (B) datasets, based on NCBI taxonomy, are shown. The lines represent the general temporal trends of two genera, <i>Synechococcus</i> and <i>Legionella</i>, in each dataset.</p

Sequence diversity of the samples used in this study

<p>. Chao1 diversity estimates of datasets based on phylum (A) and genus (B) level taxonomic classification are shown for all four metagenomic timepoints and seven selected 16S amplicon datasets.</p

Diversity estimates for the four Lake Lanier timepoints

<p>. A) Alpha diversity based on observed species (97% OTUs) from 16S amplicons for each of the nine samples. Error bars represent the variation observed among duplicate sequencing runs. B) Redundancy curves of the metagenomes of the four timepoints using (see Methods for details). The curves show that NOV is a more diverse sample, e.g., with the same sequencing effort it results in a lower coverage.</p

Community composition shifts over time as revealed by 16S data.

<p>Taxonomic binning of 16S amplicon sequences for each of the 14 individual datasets at the phylum (top) and genus (middle) levels were based on the July 2011 version of the Greengenes database <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0093827#pone.0093827-DeSantis1" target="_blank">[31]</a>. Freshwater lineages (bottom) were based on a freshwater database according to the taxonomy framework described in Newton et al., 2011. Datasets are ordered left to right by date, technical sequencing replicate (lane 1 and lane 2), and DNA replicate (A, B and C). Taxa identified as major drivers of the differences between timepoints (SIMPER analysis) are labeled (see figure key).</p

TALEs from multiple <i>Xoo</i> strains may converge onto three distinct MtN3 gene family members.

<p>Panels (<b>A</b>), (<b>B</b>) and (<b>C</b>) summarize Talvez predictions and expression data respectively for <i>Os11N3</i>, <i>Os12N3 (Xa25)</i> and <i>Os8N3</i> (<i>Xa13</i>). From top to bottom: data in bar plots derive from our analysis of microarray data from different rice genotypes and 24 hours after infection time points (hpi). Relevant treatments comparisons are indicated above the graphs. logFC values correspond to log2-transformed fold-change ratios. In the Talvez prediction network snapshots, the rank and score values along the edges represent Talvez prediction output for the connected gene (EBE) in target searches for the corresponding TALE. The bottom part of each panel contains a manual alignment of the RVD sequences from TALEs that are predicted to target the gene under consideration in the panel. Individual residues highlighted in bold deviate from the consensus at that position. The locations of the predicted EBEs on the upstream sequences of the rice gene are marked by lines colored following the same pattern as on the RVD alignment. Numbers on the left indicate the distance in base pair between the most upstream nucleotide of the reported sequence and the ATG. TalC from the African Xoo strain BAI3 which has been reported to target <i>Os11N3</i> <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0068464#pone.0068464-Yu1" target="_blank">[18]</a> was included in panel A to illustrate the notion of convergence on gene susceptibility targets at the level of distinct EBEs.</p

An Improved Method for TAL Effectors DNA-Binding Sites Prediction Reveals Functional Convergence in TAL Repertoires of <i>Xanthomonas oryzae</i> Strains

<div><p>Transcription Activators-Like Effectors (TALEs) belong to a family of virulence proteins from the <i>Xanthomonas</i> genus of bacterial plant pathogens that are translocated into the plant cell. In the nucleus, TALEs act as transcription factors inducing the expression of susceptibility genes. A code for TALE-DNA binding specificity and high-resolution three-dimensional structures of TALE-DNA complexes were recently reported. Accurate prediction of TAL Effector Binding Elements (EBEs) is essential to elucidate the biological functions of the many sequenced TALEs as well as for robust design of artificial TALE DNA-binding domains in biotechnological applications. In this work a program with improved EBE prediction performances was developed using an updated specificity matrix and a position weight correction function to account for the matching pattern observed in a validation set of TALE-DNA interactions. To gain a systems perspective on the large TALE repertoires from <i>X. oryzae</i> strains, this program was used to predict rice gene targets for 99 sequenced family members. Integrating predictions and available expression data in a TALE-gene network revealed multiple candidate transcriptional targets for many TALEs as well as several possible instances of functional convergence among TALEs.</p></div

Distribution of perfect matches (PM) in the TALE-EBE validation set.

<p>(<b>A</b>) Box plot of the distribution of the number of perfect RVD-nucleotide matches computed for individual negative and positive control TALE-EBE pairs. (<b>B</b>) Distribution of perfect match frequency of individual control TALE-EBE pairs. The frequency corresponds to the ratio of the number of perfect RVD-nucleotide matches to TALE length expressed in number of RVD. (<b>C</b>) Frequency of perfect matches across TALE-DNA positions. The frequency corresponds to the ratio of the number of perfect RVD-nucleotide at the considered position to the total number of RVD-nucleotide pairs at this position in TALE-EBE pairs of the positive or negative control set. (<b>D</b>) Frequency of perfect RVD-nucleotide match between positions 1 and 15 ( = number of PM/15). (<b>E</b>) Frequency of perfect match for TALE-DNA positions beyond 15 ( = number of PM/(length-15)). The p-value of the corresponding two-tailed Wilcoxon test in this comparison is 0.371. ** significant differences, one-tailed Wilcoxon test p-value<0.001; *** significant differences one-tailed Wilcoxon p-value<1e-7.</p

Performances of the EBE prediction software in the TALE-EBE validation set.

<p>(<b>A</b>) Boxplot showing the median (thick line), the lower and upper quartiles (box) and the minimum and maximum (whiskers) of the prediction scores for the set of positive (+) and negative (−) control TALE-DNA interactions using three programs for EBE prediction. Scores were scaled down according to the maximum score on the set to facilitate comparison. Talent scores were scaled x⁻¹ since they follow an inverse scale relative to the other programs, this transformation maintains data structure. ** Indicates significant positive vs. negative differences (one-tailed t-test p-value<0.001). (<b>B</b>) ROC graph showing the true positive and false positive rate of the three EBE predictors based on validation set screenings. Dashed line indicates the theoretical performance of a random classifying program where true positive rate = false positive rate. The inset in the upper right corner shows the rates for Talvez and Storyteller at a higher scale to highlight the differences between the two programs.</p

Comparison of the TALE-candidate target gene network with random networks obtained with shuffled TALEs.

<p>Properties of the TALE-gene network are compared to average values from 100 randomized controls (error bars indicate standard deviation): (<b>A</b>) percent frequency distribution of Talvez prediction ranks of TALE-gene pairs, the percentage of top (#1) ranking TALE-gene pairs is indicated for the TALE-gene network. (<b>B</b>) Number of genes and TALEs in the TALE-gene network compared to control random networks.</p