mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.

/pdf/introducing-mothur-open-source-platform-independent-3tr77w6374.pdf

Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities

The Ribosomal Database Project (RDP) Classifier, a naive Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (≥95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.

/pdf/naive-bayesian-classifier-for-rapid-assignment-of-rrna-47oxvssngj.pdf

Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy

The human endogenous intestinal microflora is an essential “organ” in providing nourishment, regulating epithelial development, and instructing innate immunity; yet, surprisingly, basic features remain poorly described. We examined 13,355 prokaryotic ribosomal RNA gene sequences from multiple colonic mucosal sites and feces of healthy subjects to improve our understanding of gut microbial diversity. A majority of the bacterial sequences corresponded to uncultivated species and novel microorganisms. We discovered significant intersubject variability and differences between stool and mucosa community composition. Characterization of this immensely diverse ecosystem is the first step in elucidating its role in health and disease.

/pdf/diversity-of-the-human-intestinal-microbial-flora-55fejkfhx2.pdf

Diversity of the human intestinal microbial flora.

We introduce here a new method for computing differences between microbial communities based on phylogenetic information. This method, UniFrac, measures the phylogenetic distance between sets of taxa in a phylogenetic tree as the fraction of the branch length of the tree that leads to descendants from either one environment or the other, but not both. UniFrac can be used to determine whether communities are significantly different, to compare many communities simultaneously using clustering and ordination techniques, and to measure the relative contributions of different factors, such as chemistry and geography, to similarities between samples. We demonstrate the utility of UniFrac by applying it to published 16S rRNA gene libraries from cultured isolates and environmental clones of bacteria in marine sediment, water, and ice. Our results reveal that (i) cultured isolates from ice, water, and sediment resemble each other and environmental clone sequences from sea ice, but not environmental clone sequences from sediment and water; (ii) the geographical location does not correlate strongly with bacterial community differences in ice and sediment from the Arctic and Antarctic; and (iii) bacterial communities differ between terrestrially impacted seawater (whether polar or temperate) and warm oligotrophic seawater, whereas those in individual seawater samples are not more similar to each other than to those in sediment or ice samples. These results illustrate that UniFrac provides a new way of characterizing microbial communities, using the wealth of environmental rRNA sequences, and allows quantitative insight into the factors that underlie the distribution of lineages among environments.

/pdf/unifrac-a-new-phylogenetic-method-for-comparing-microbial-le79e9hmqd.pdf

UniFrac: a New Phylogenetic Method for Comparing Microbial Communities

The sequence of the mouse genome is a key informational tool for understanding the contents of the human genome and a key experimental tool for biomedical research. Here, we report the results of an international collaboration to produce a high-quality draft sequence of the mouse genome. We also present an initial comparative analysis of the mouse and human genomes, describing some of the insights that can be gleaned from the two sequences. We discuss topics including the analysis of the evolutionary forces shaping the size, structure and sequence of the genomes; the conservation of large-scale synteny across most of the genomes; the much lower extent of sequence orthology covering less than half of the genomes; the proportions of the genomes under selection; the number of protein-coding genes; the expansion of gene families related to reproduction and immunity; the evolution of proteins; and the identification of intraspecies polymorphism.

/pdf/initial-sequencing-and-comparative-analysis-of-the-mouse-5a9n62pifj.pdf

Initial sequencing and comparative analysis of the mouse genome.

The simple fool's guide to PCR

There is increasing evidence for variation in rates of nucleotide substitution among divergent taxonomic groups. Here, we summarize published rate data and show a strong relationship between substitution rate and body size. For instance, rates of nuclear and mtDNA evolution are slow in whales, intermediate in primates, and fast in rodents. A similar relationship exists for poikilothermic vertebrates. However, these taxa have slower mtDNA substitution rates overall than do homeotherms of similar size. A number of physiological and life history variables are highly correlated with body size. Of these, generation time and metabolic rate explain some patterns of rate heterogeneity equally well. In many cases, however, differences in metabolic rate explain important exceptions to the generation time model. Correlation between metabolic rate and nucleotide substitution may be mediated by (i) the mutagenic effects of oxygen radicals that are abundant by-products of aerobic respiration, and (ii) increased rates of DNA synthesis and nucleotide replacement in organisms with higher metabolic rates. Both of these factors increase mutation rate by decreasing the "nucleotide generation time," the average length of time before a nucleotide is copied either through replication or repair. Reconsideration of the generation time hypothesis to include physiological effects such as metabolic rate improves the theoretical underpinnings of molecular evolution.

https://www.pnas.org/content/pnas/90/9/4087.full.pdf

Body size, metabolic rate, generation time, and the molecular clock.

The finding that microbial communities are active under snow has changed the estimated global rates of biogeochemical processes beneath seasonal snow packs. We used microbiological and molecular techniques to elucidate the phylogenetic composition of undersnow microbial communities in Colorado, the United States. Here, we show that tundra soil microbial biomass reaches its annual peak under snow, and that fungi account for most of the biomass. Phylogenetic analysis of tundra soil fungi revealed a high diversity of fungi and three novel clades that constitute major new groups of fungi (divergent at the subphylum or class level). An abundance of previously unknown fungi that are active beneath the snow substantially broadens our understanding of both the diversity and biogeochemical functioning of fungi in cold environments.

https://science.sciencemag.org/content/sci/301/5638/1359.full.pdf

Seasonal dynamics of previously unknown fungal lineages in tundra soils.

Diversity is the hard currency of ecologists. Various statistics have been developed for summarizing the diversity of an ecological community. A commonly adopted summary statistic is the Shannon-Weiner index: H p ilnpi, where pi is the frequency of the ith species. In addition, species richness (the number of different species) often is reported, and recent work emphasizes the importance of accurate estimates of species richness when ecological communities and processes that affect the composition of communities and the function of ecosystems are described (5). The significance of diversity is often inferred by comparing communities characterized from different environments. Typically, such comparisons rely on standard measures of overlap, including the percentage of species shared by two communities or similarity indices. One of the indices used is Sorensen’s index: S S 12/[0.5(S1 S2)], where S 12 is the number of species common to both sites and Si is the number of species found at site i. A limitation of traditional statistics for describing and comparing diversity is that species (or operational taxonomic units [OTUs]) are defined inconsistently. For instance, Kroes et al. (6) defined an OTU as a 16S ribosomal DNA (rDNA) sequence group in which sequences differed by less than 1%. By contrast, the definition of McCaig et al. (11) included sequences that were less than 3% different, and other studies have used 5% as the magic number. The lack of consensus limits the comparative utility of statistics based solely on identification of species (or OTUs). A second, and perhaps more important, limitation of the standard statistics of diversity is that OTUs are counted equivalently even though some may be highly divergent and phylogenetically unique, whereas others may be part of a closely related group of species and are therefore phylogenetically redundant (4). The contrast can be illustrated by comparing two hypothetical communities in which the numbers of species, the richness profiles of species, and the rarefaction profiles are identical but which differ in the magnitude of phylogenetic diversity (i.e., the degree of divergence among the sampled sequences). Standard ecological statistics of diversity would miss the genetic difference between the two communities, and ecologists would most likely consider the two communities equally diverse when, in fact, one community harbors more genetic diversity (or disparity) than the other. Because genetic variation and phenotypic variance often are positively correlated in populations of animals (12), plants (7), and microbes (15), descriptions of microbial communities based on DNA data should include information about diversity and disparity. This is especially important in light of studies demonstrating an association between ecosystem function and community diversity (14, 28). In this review I introduce various statistics borrowed from population genetics and systematics for describing and comparing the diversity evident from samples of gene sequences. I briefly introduce the statistics and methodological underpinnings of tests for differences between communities, and I use the methods to analyze well-described microbial communities. I show that information gained from analysis of DNA sequences provides the basis for statistical analysis of communities in ways that advance inferences about the processes that may govern the compositions and functions of microbial communities. Furthermore, the advocated analytical approaches make it possible to accomplish broad comparisons of ecological communities. The methods of analysis explored in this paper are meant to be complementary to other methods, such as the robust estimation of richness advocated by Hughes et al. (5) and approaches for estimating functional properties of bacteria from phylogenetic inference (16).

Phylogenetic Approaches for Describing and Comparing the Diversity of Microbial Communities

THE rate of mitochondrial DNA (mtDNA) evolution has been carefully calibrated only in primates1. Similarity between the primate calibration and rates estimated for other vertebrates2–4 has led to widespread assumption of a constant molecular clock in vertebrates even though this has never been rigorously tested5. We report here the examination of mtDNA sequence variation for 13 species of sharks from two orders that are well represented in the fossil record to test the constancy hypothesis. Nucleotide substitution rates in the cytochrome b and cytochrome oxidase I genes in sharks are seven- to eightfold slower than in primates or ungulates. This difference in substitution rate cannot be explained by nucleotide composition bias, codon-usage bias, selection, or choice of genes sequenced, and was confirmed by comparing species recently separated by the rise of the Isthmus of Panama. Such differences in mtDNA substitution rates among taxa indicate that it is inappropriate to use a calibration for one group to estimate divergence times or demographic parameters for another group. High-resolution studies of molecular evolutionary rates require taxon-specific calibrations.

Andrew P. Martin

Papers

The simple fool's guide to PCR

Body size, metabolic rate, generation time, and the molecular clock.

Seasonal dynamics of previously unknown fungal lineages in tundra soils.

Phylogenetic Approaches for Describing and Comparing the Diversity of Microbial Communities

Rates of mitochondrial DNA evolution in sharks are slow compared with mammals