Decoupled distance-decay patterns between dsrA and 16S rRNA genes among salt marsh sulfate-reducing bacteria
Summary In many habitats, microorganisms exhibit significant distance–decay patterns as determined by analysis of the 16S rRNA gene and various other genetic elements. However, there have been few studies that examine how the similarities of both taxonomic and functional genes co‐vary over geographi...
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| Published in | Environmental microbiology Vol. 18; no. 1; pp. 75 - 86 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Blackwell Publishing Ltd
01.01.2016
Wiley Subscription Services, Inc |
| Subjects | |
| Online Access | Get full text |
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| Summary: | Summary
In many habitats, microorganisms exhibit significant distance–decay patterns as determined by analysis of the 16S rRNA gene and various other genetic elements. However, there have been few studies that examine how the similarities of both taxonomic and functional genes co‐vary over geographic distance within a group of ecologically related microbes. Here, we determined the biogeographic patterns of the functional dissimilatory sulfite reductase gene (dsrA) and the 16S rRNA gene in sulfate‐reducing bacterial communities of US East Coast salt marsh sediments. Distance–decay, ordination and statistical analyses revealed that the distribution of 16S rRNA genes is strongly influenced by geographic distance and environmental factors, whereas the dsrA gene is not. Together, our results indicate that 16S rRNA genes are likely dispersal limited and under environmental selection, whereas dsrA genes appear randomly distributed and not selected for by any expected environmental variables. Selection, drift, dispersal and mutation are all factors that may help explain the decoupled biogeographic patterns for the two genes. These data suggest that both the taxonomic and functional elements of microbial communities should be considered in future studies of microbial biogeography to aid in our understanding of the diversity, distribution and function of microorganisms in the environment. |
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| Bibliography: | Fig. S1. Relative abundance of bacterial 97% 16S rRNA OTU sequences and the taxonomic assignment at the phylum level. Sites are separated by site from north to south (left to right) and labeled according to transect distance. Samples that did not amplify are indicated in grey. Fig. S2. Distance-decay plot for all 16S rRNA genes. OTUs were calculated at 97% similarity. Fig. S3. Histogram of dsrAB clone OTUs in descending order of occurrence across all salt marsh sites reveal a long-tail distribution of alleles. Inset pie charts further illustrate the relative breakdowns of singletons, doubletons, tripletons, and aggregated quadrupletons and greater by marsh. Fig. S4. Maximum likelihood phylogenetic tree of dsrAB DNA sequences (A) and dsrAB translated amino acid sequences (B). OTU thresholds are at 90% sequence similarity for DNA and 95% for amino acids. Archaeoglobus strains were used as outgroups. The scale bar indicates 10% sequence divergence. Collapsed nodes exclusively contain OTUs detected in this study and their labels indicate X number of OTUs contained within node and Y number of representative clones among all X OTUs. Each un-collapsed representative clone indicates the number total clones within that OTU. Black circles represent nodes with ≥75% bootstrap support, open circles are ≥50%. Fig. S5. Varclus redundancy correlations (Spearman's ρ2). Fig. S6. Distance-decay plots of 16S rRNA OTU data serially reduced in 10-fold increments keeping the most abundant taxa. Reductions were performed on singletonexcluded dataset. Numbers in brackets are remaining number of OTUs represented in each plot. A. All OTUs [56780]. B. All OTUs excluding singletons [34926]. C. Top 10% [3493]. D. Top 1% [349] E. Top 0.1% [35]. F. Top 0.01% [3]. Fig. S7. Distance-decay plots generated at various OTU clustering thresholds for 16S sequences (similarity cutoff) and dsrA T-RFs (base pair distance between peaks) data. All similarity scores are calculated using Bray-Curtis. 16S: A) 99% B) 97% C) 90%. dsrA: D) 0.5 bp E) 2 bp F) 5 bp. Table S1. ANCOVA significance p-values. A p-value indicates that two slopes in the matrix are significantly different from each other (at least P ≤ 0.05). Grayed-out squares are non-applicable comparisons. NS (not significant) indicates that two slopes are the same. istex:AA4882E10F222235B49ED557ACCEED2BBCA39E5A ArticleID:EMI12821 Neal Cornell Endowed Research Fund Brown-MBL Partnership SEED ark:/67375/WNG-F2ZRLD34-Z ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1462-2912 1462-2920 |
| DOI: | 10.1111/1462-2920.12821 |