PhylOTU: a high-throughput procedure quantifies microbial community diversity and resolves novel taxa from metagenomic data.

Microbial diversity is typically characterized by clustering ribosomal RNA (SSU-rRNA) sequences into operational taxonomic units (OTUs). Targeted sequencing of environmental SSU-rRNA markers via PCR may fail to detect OTUs due to biases in priming and amplification. Analysis of shotgun sequenced environmental DNA, known as metagenomics, avoids amplification bias but generates fragmentary, non-overlapping sequence reads that cannot be clustered by existing OTU-finding methods. To circumvent these limitations, we developed PhylOTU, a computational workflow that identifies OTUs from metagenomic SSU-rRNA sequence data through the use of phylogenetic principles and probabilistic sequence profiles. Using simulated metagenomic data, we quantified the accuracy with which PhylOTU clusters reads into OTUs. Comparisons of PCR and shotgun sequenced SSU-rRNA markers derived from the global open ocean revealed that while PCR libraries identify more OTUs per sequenced residue, metagenomic libraries recover a greater taxonomic diversity of OTUs. In addition, we discover novel species, genera and families in the metagenomic libraries, including OTUs from phyla missed by analysis of PCR sequences. Taken together, these results suggest that PhylOTU enables characterization of part of the biosphere currently hidden from PCR-based surveys of diversity

Global marine bacterial diversity peaks at high latitudes in winter.

Genomic approaches to characterizing bacterial communities are revealing significant differences in diversity and composition between environments. But bacterial distributions have not been mapped at a global scale. Although current community surveys are way too sparse to map global diversity patterns directly, there is now sufficient data to fit accurate models of how bacterial distributions vary across different environments and to make global scale maps from these models. We apply this approach to map the global distributions of bacteria in marine surface waters. Our spatially and temporally explicit predictions suggest that bacterial diversity peaks in temperate latitudes across the world's oceans. These global peaks are seasonal, occurring 6 months apart in the two hemispheres, in the boreal and austral winters. This pattern is quite different from the tropical, seasonally consistent diversity patterns observed for most macroorganisms. However, like other marine organisms, surface water bacteria are particularly diverse in regions of high human environmental impacts on the oceans. Our maps provide the first picture of bacterial distributions at a global scale and suggest important differences between the diversity patterns of bacteria compared with other organisms

Existing climate change will lead to pronounced shifts in the diversity of soil prokaryotes

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in mSystems 3 (2018): e00167-18, doi:10.1128/mSystems.00167-18.Soil bacteria are key to ecosystem function and maintenance of soil fertility. Leveraging associations of current geographic distributions of bacteria with historic climate, we predict that soil bacterial diversity will increase across the majority (∼75%) of the Tibetan Plateau and northern North America if bacterial communities equilibrate with existing climatic conditions. This prediction is possible because the current distributions of soil bacteria have stronger correlations with climate from ∼50 years ago than with current climate. This lag is likely associated with the time it takes for soil properties to adjust to changes in climate. The predicted changes are location specific and differ across bacterial taxa, including some bacteria that are predicted to have reductions in their distributions. These findings illuminate the widespread potential of climate change to influence belowground diversity and the importance of considering bacterial communities when assessing climate impacts on terrestrial ecosystems.This work was supported by the Strategic Priority Research Program (XDB15010101, XDA05050404) of the Chinese Academy of Sciences, the National Program on Key Basic Research Project (2014CB954002, 2014CB954004), the National Natural Science Foundation of China (41701298, 41371254), the “135” Plan and Frontiers Projects of Institute of Soil Science (ISSASIP1641), and the National Science and Technology Foundation project (2015FY110100). J.A.G. was supported by the U.S. Dept. of Energy under contract DE-AC02-06CH11357. N.F. was supported by a grant from the National Science Foundation (DEB-0953331). K.S.P. and J.L. were supported by the National Science Foundation (DMS-1069303), the Gordon and Betty Moore Foundation (grant no. 3300), the Gladstone Institutes, and a gift from the San Simeon Fund

A Communal Catalogue Reveals Earth\u27s Multiscale Microbial Diversity

Our growing awareness of the microbial world\u27s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth\u27s microbial diversity

American Gut: an Open Platform for Citizen Science Microbiome Research

McDonald D, Hyde E, Debelius JW, et al. American Gut: an Open Platform for Citizen Science Microbiome Research. mSystems. 2018;3(3):e00031-18

A communal catalogue reveals Earth’s multiscale microbial diversity

Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity

Robust Statistical Tests for Detecting the Effects of Interspecific Competition on Ecological Communities

For seventy years ecologists have debated to what extent competition affects the composition of ecological communities. At one extreme, species have been proposed to assemble independently of each other, while at the other extreme, competition and other interspecific interactions have been proposed to account almost solely for the composition of communities. Although the debate bears broadly on applied and basic ecology, it has been challenging to resolve. The most practical approach toward resolving the debate has been null model testing. The testing begins by assuming a null hypothesis that is reflective of an absence of competitive effects, which is then used to make a statistical prediction about the observed data. If observations are inconsistent with the prediction, then the null hypothesis is rejected, and effects of competition are inferred. Unfortunately, as I show here, all existing null model tests are biased or non-robust. Although both qualities are problematic, the non-robustness is particularly troubling, because it means that when assumptions of the tests cannot be verified ? as is usually the case ? the tests will incorrectly indicate competitive effects unacceptably often. Thus, the tests are unreliable. To fix the problem, I derive robust tests. Letting i and j denote the ith and jth colonists to arrive at a site, respectively, and W(i,j) the event that i and j belong to the same ?unit? (e.g., functional group, genus), I derive how partitions of colonists into units will be distributed if for all i and j, W(i,j) is conditionally independent of whether i and j share unit membership with the other colonists. Because the distribution can be derived without parametric assumptions, it can be used to test robustly for competitive effects. I conclude by applying one of the tests to seven large data sets. In no cases does this test suggest effects of competition, although it does sometimes suggest effects of other interspecific interactions (e.g., facilitation). Overall, the predicted distribution accounts for over 95% of the variation in frequencies of partitions. Hence, the results suggest that although interspecific interactions may discernibly affect the composition of communities, those effects are generally minor.National Science Foundation Graduate Research Fellowship Progra