Conversion of the Amazon rainforest to agriculture results in biotic homogenization of soil bacterial communities.

The Amazon rainforest is the Earth's largest reservoir of plant and animal diversity, and it has been subjected to especially high rates of land use change, primarily to cattle pasture. This conversion has had a strongly negative effect on biological diversity, reducing the number of plant and animal species and homogenizing communities. We report here that microbial biodiversity also responds strongly to conversion of the Amazon rainforest, but in a manner different from plants and animals. Local taxonomic and phylogenetic diversity of soil bacteria increases after conversion, but communities become more similar across space. This homogenization is driven by the loss of forest soil bacteria with restricted ranges (endemics) and results in a net loss of diversity. This study shows homogenization of microbial communities in response to human activities. Given that soil microbes represent the majority of biodiversity in terrestrial ecosystems and are intimately involved in ecosystem functions, we argue that microbial biodiversity loss should be taken into account when assessing the impact of land use change in tropical forests.

Bacterial community comparisons by taxonomy-supervised analysis independent of sequence alignment and clustering.

High-throughput sequencing of 16S rRNA genes has increased our understanding of microbial community structure, but now even higher-throughput methods to the Illumina scale allow the creation of much larger datasets with more samples and orders-of-magnitude more sequences that swamp current analytic methods. We developed a method capable of handling these larger datasets on the basis of assignment of sequences into an existing taxonomy using a supervised learning approach (taxonomy-supervised analysis). We compared this method with a commonly used clustering approach based on sequence similarity (taxonomy-unsupervised analysis). We sampled 211 different bacterial communities from various habitats and obtained ∼1.3 million 16S rRNA sequences spanning the V4 hypervariable region by pyrosequencing. Both methodologies gave similar ecological conclusions in that ß-diversity measures calculated by using these two types of matrices were significantly correlated to each other, as were the ordination configurations and hierarchical clustering dendrograms. In addition, our taxonomy-supervised analyses were also highly correlated with phylogenetic methods, such as UniFrac. The taxonomy-supervised analysis has the advantages that it is not limited by the exhaustive computation required for the alignment and clustering necessary for the taxonomy-unsupervised analysis, is more tolerant of sequencing errors, and allows comparisons when sequences are from different regions of the 16S rRNA gene. With the tremendous expansion in 16S rRNA data acquisition underway, the taxonomy-supervised approach offers the potential to provide more rapid and extensive community comparisons across habitats and samples.

Microbial Community Structure and Functional Potential in Cultivated and Native Tallgrass Prairie Soils of the Midwestern United States.

The North American prairie covered about 3.6 million-km2 of the continent prior to European contact. Only 1-2% of the original prairie remains, but the soils that developed under these prairies are some of the most productive and fertile in the world, containing over 35% of the soil carbon in the continental United States. Cultivation may alter microbial diversity and composition, influencing the metabolism of carbon, nitrogen, and other elements. Here, we explored the structure and functional potential of the soil microbiome in paired cultivated-corn (at the time of sampling) and never-cultivated native prairie soils across a three-states transect (Wisconsin, Iowa, and Kansas) using metagenomic and 16S rRNA gene sequencing and lipid analysis. At the Wisconsin site, we also sampled adjacent restored prairie and switchgrass plots. We found that agricultural practices drove differences in community composition and diversity across the transect. Microbial biomass in prairie samples was twice that of cultivated soils, but alpha diversity was higher with cultivation. Metagenome analyses revealed denitrification and starch degradation genes were abundant across all soils, as were core genes involved in response to osmotic stress, resource transport, and environmental sensing. Together, these data indicate that cultivation shifted the microbiome in consistent ways across different regions of the prairie, but also suggest that many functions are resilient to changes caused by land management practices - perhaps reflecting adaptations to conditions common to tallgrass prairie soils in the region (e.g., soil type, parent material, development under grasses, temperature and rainfall patterns, and annual freeze-thaw cycles). These findings are important for understanding the long-term consequences of land management practices to prairie soil microbial communities and their genetic potential to carry out key functions.

Forest-to-pasture conversion increases the diversity of the phylum Verrucomicrobia in Amazon rainforest soils.

The Amazon rainforest is well known for its rich plant and animal diversity, but its bacterial diversity is virtually unexplored. Due to ongoing and widespread deforestation followed by conversion to agriculture, there is an urgent need to quantify the soil biological diversity within this tropical ecosystem. Given the abundance of the phylum Verrucomicrobia in soils, we targeted this group to examine its response to forest-to-pasture conversion. Both taxonomic and phylogenetic diversities were higher for pasture in comparison to primary and secondary forests. The community composition of Verrucomicrobia in pasture soils was significantly different from those of forests, with a 11.6% increase in the number of sequences belonging to subphylum 3 and a proportional decrease in sequences belonging to the class Spartobacteria. Based on 99% operational taxonomic unit identity, 40% of the sequences have not been detected in previous studies, underscoring the limited knowledge regarding the diversity of microorganisms in tropical ecosystems. The abundance of Verrucomicrobia, measured with quantitative PCR, was strongly correlated with soil C content (r = 0.80, P = 0.0016), indicating their importance in metabolizing plant-derived carbon compounds in soils.