C. Titus Brown

Ribosomal Database Project: data and tools for high throughput rRNA analysis

Ribosomal Database Project (RDP; http://rdp.cme.msu.edu/) provides the research community with aligned and annotated rRNA gene sequence data, along with tools to allow researchers to analyze their own rRNA gene sequences in the RDP framework. RDP data and tools are utilized in fields as diverse as human health, microbial ecology, environmental microbiology, nucleic acid chemistry, taxonomy and phylogenetics. In addition to aligned and annotated collections of bacterial and archaeal small subunit rRNA genes, RDP now includes a collection of fungal large subunit rRNA genes. RDP tools, including Classifier and Aligner, have been updated to work with this new fungal collection. The use of high-throughput sequencing to characterize environmental microbial populations has exploded in the past several years, and as sequence technologies have improved, the sizes of environmental datasets have increased. With release 11, RDP is providing an expanded set of tools to facilitate analysis of high-throughput data, including both single-stranded and paired-end reads. In addition, most tools are now available as open source packages for download and local use by researchers with high-volume needs or who would like to develop custom analysis pipelines.

Sequencing of the sea lamprey (Petromyzon marinus) genome provides insights into vertebrate evolution.

Lampreys are representatives of an ancient vertebrate lineage that diverged from our own ∼500 million years ago. By virtue of this deeply shared ancestry, the sea lamprey (P. marinus) genome is uniquely poised to provide insight into the ancestry of vertebrate genomes and the underlying principles of vertebrate biology. Here, we present the first lamprey whole-genome sequence and assembly. We note challenges faced owing to its high content of repetitive elements and GC bases, as well as the absence of broad-scale sequence information from closely related species. Analyses of the assembly indicate that two whole-genome duplications likely occurred before the divergence of ancestral lamprey and gnathostome lineages. Moreover, the results help define key evolutionary events within vertebrate lineages, including the origin of myelin-associated proteins and the development of appendages. The lamprey genome provides an important resource for reconstructing vertebrate origins and the evolutionary events that have shaped the genomes of extant organisms.

Diverse syntrophic partnerships from deep-sea methane vents revealed by direct cell capture and metagenomics

Microorganisms play a fundamental role in the cycling of nutrients and energy on our planet. A common strategy for many microorganisms mediating biogeochemical cycles in anoxic environments is syntrophy, frequently necessitating close spatial proximity between microbial partners. We are only now beginning to fully appreciate the diversity and pervasiveness of microbial partnerships in nature, the majority of which cannot be replicated in the laboratory. One notable example of such cooperation is the interspecies association between anaerobic methane oxidizing archaea (ANME) and sulfate-reducing bacteria. These consortia are globally distributed in the environment and provide a significant sink for methane by substantially reducing the export of this potent greenhouse gas into the atmosphere. The interdependence of these currently uncultured microbes renders them difficult to study, and our knowledge of their physiological capabilities in nature is limited. Here, we have developed a method to capture select microorganisms directly from the environment, using combined fluorescence in situ hybridization and immunomagnetic cell capture. We used this method to purify syntrophic anaerobic methane oxidizing ANME-2c archaea and physically associated microorganisms directly from deep-sea marine sediment. Metagenomics, PCR, and microscopy of these purified consortia revealed unexpected diversity of associated bacteria, including Betaproteobacteria and a second sulfate-reducing Deltaproteobacterial partner. The detection of nitrogenase genes within the metagenome and subsequent demonstration of 15N2 incorporation in the biomass of these methane-oxidizing consortia suggest a possible role in new nitrogen inputs by these syntrophic assemblages.

FunGene: the functional gene pipeline and repository

Ribosomal RNA genes have become the standard molecular markers for microbial community analysis for good reasons, including universal occurrence in cellular organisms, availability of large databases, and ease of rRNA gene region amplification and analysis. As markers, however, rRNA genes have some significant limitations. The rRNA genes are often present in multiple copies, unlike most protein-coding genes. The slow rate of change in rRNA genes means that multiple species sometimes share identical 16S rRNA gene sequences, while many more species share identical sequences in the short 16S rRNA regions commonly analyzed. In addition, the genes involved in many important processes are not distributed in a phylogenetically coherent manner, potentially due to gene loss or horizontal gene transfer. While rRNA genes remain the most commonly used markers, key genes in ecologically important pathways, e.g., those involved in carbon and nitrogen cycling, can provide important insights into community composition and function not obtainable through rRNA analysis. However, working with ecofunctional gene data requires some tools beyond those required for rRNA analysis. To address this, our Functional Gene Pipeline and Repository (FunGene; http://fungene.cme.msu.edu/) offers databases of many common ecofunctional genes and proteins, as well as integrated tools that allow researchers to browse these collections and choose subsets for further analysis, build phylogenetic trees, test primers and probes for coverage, and download aligned sequences. Additional FunGene tools are specialized to process coding gene amplicon data. For example, FrameBot produces frameshift-corrected protein and DNA sequences from raw reads while finding the most closely related protein reference sequence. These tools can help provide better insight into microbial communities by directly studying key genes involved in important ecological processes.

Scaling metagenome sequence assembly with probabilistic de Bruijn graphs

Deep sequencing has enabled the investigation of a wide range of environmental microbial ecosystems, but the high memory requirements for de novo assembly of short-read shotgun sequencing data from these complex populations are an increasingly large practical barrier. Here we introduce a memory-efficient graph representation with which we can analyze the k-mer connectivity of metagenomic samples. The graph representation is based on a probabilistic data structure, a Bloom filter, that allows us to efficiently store assembly graphs in as little as 4 bits per k-mer, albeit inexactly. We show that this data structure accurately represents DNA assembly graphs in low memory. We apply this data structure to the problem of partitioning assembly graphs into components as a prelude to assembly, and show that this reduces the overall memory requirements for de novo assembly of metagenomes. On one soil metagenome assembly, this approach achieves a nearly 40-fold decrease in the maximum memory requirements for assembly. This probabilistic graph representation is a significant theoretical advance in storing assembly graphs and also yields immediate leverage on metagenomic assembly.

Tackling soil diversity with the assembly of large, complex metagenomes

Significance Investigations of complex environments rely on large volumes of sequence data to adequately sample the genetic diversity of a microbial community. The assembly of short-read data into longer, more interpretable sequence currently is not possible for much of the research community because it requires specialized computational facilities. We present approaches that make de novo assembly of complex metagenomes more accessible. These approaches scale data size with community richness and subdivide the data into tractable subsets representing individual species. We applied these methods toward the assembly of two large soil metagenomes to identify important metagenomic references and show that considerably more data are needed to study the terrestrial microbiome comprehensively. The large volumes of sequencing data required to sample deeply the microbial communities of complex environments pose new challenges to sequence analysis. De novo metagenomic assembly effectively reduces the total amount of data to be analyzed but requires substantial computational resources. We combine two preassembly filtering approaches—digital normalization and partitioning—to generate previously intractable large metagenome assemblies. Using a human-gut mock community dataset, we demonstrate that these methods result in assemblies nearly identical to assemblies from unprocessed data. We then assemble two large soil metagenomes totaling 398 billion bp (equivalent to 88,000 Escherichia coli genomes) from matched Iowa corn and native prairie soils. The resulting assembled contigs could be used to identify molecular interactions and reaction networks of known metabolic pathways using the Kyoto Encyclopedia of Genes and Genomes Orthology database. Nonetheless, more than 60% of predicted proteins in assemblies could not be annotated against known databases. Many of these unknown proteins were abundant in both corn and prairie soils, highlighting the benefits of assembly for the discovery and characterization of novelty in soil biodiversity. Moreover, 80% of the sequencing data could not be assembled because of low coverage, suggesting that considerably more sequencing data are needed to characterize the functional content of soil.

Meeting Report: The Terabase Metagenomics Workshop and the Vision of an Earth Microbiome Project

Between July 18th and 24th 2010, 26 leading microbial ecology, computation, bioinformatics and statistics researchers came together in Snowbird, Utah (USA) to discuss the challenge of how to best characterize the microbial world using next-generation sequencing technologies. The meeting was entitled “Terabase Metagenomics” and was sponsored by the Institute for Computing in Science (ICiS) summer 2010 workshop program. The aim of the workshop was to explore the fundamental questions relating to microbial ecology that could be addressed using advances in sequencing potential. Technological advances in next-generation sequencing platforms such as the Illumina HiSeq 2000 can generate in excess of 250 billion base pairs of genetic information in 8 days. Thus, the generation of a trillion base pairs of genetic information is becoming a routine matter. The main outcome from this meeting was the birth of a concept and practical approach to exploring microbial life on earth, the Earth Microbiome Project (EMP). Here we briefly describe the highlights of this meeting and provide an overview of the EMP concept and how it can be applied to exploration of the microbiome of each ecosystem on this planet.

The genome and developmental transcriptome of the strongylid nematode Haemonchus contortus

BackgroundThe barbers pole worm, Haemonchus contortus, is one of the most economically important parasites of small ruminants worldwide. Although this parasite can be controlled using anthelmintic drugs, resistance against most drugs in common use has become a widespread problem. We provide a draft of the genome and the transcriptomes of all key developmental stages of H. contortus to support biological and biotechnological research areas of this and related parasites.ResultsThe draft genome of H. contortus is 320 Mb in size and encodes 23,610 protein-coding genes. On a fundamental level, we elucidate transcriptional alterations taking place throughout the life cycle, characterize the parasites gene silencing machinery, and explore molecules involved in development, reproduction, host-parasite interactions, immunity, and disease. The secretome of H. contortus is particularly rich in peptidases linked to blood-feeding activity and interactions with host tissues, and a diverse array of molecules is involved in complex immune responses. On an applied level, we predict drug targets and identify vaccine molecules.ConclusionsThe draft genome and developmental transcriptome of H. contortus provide a major resource to the scientific community for a wide range of genomic, genetic, proteomic, metabolomic, evolutionary, biological, ecological, and epidemiological investigations, and a solid foundation for biotechnological outcomes, including new anthelmintics, vaccines and diagnostic tests. This first draft genome of any strongylid nematode paves the way for a rapid acceleration in our understanding of a wide range of socioeconomically important parasites of one of the largest nematode orders.

The khmer software package: enabling efficient nucleotide sequence analysis

The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at https://github.com/dib-lab/khmer/.

Standing genetic variation in contingency loci drives the rapid adaptation of Campylobacter jejuni to a novel host

The genome of the food-borne pathogen Campylobacter jejuni contains multiple highly mutable sites, or contingency loci. It has been suggested that standing variation at these loci is a mechanism for rapid adaptation to a novel environment, but this phenomenon has not been shown experimentally. In previous work we showed that the virulence of C. jejuni NCTC11168 increased after serial passage through a C57BL/6 IL-10-/- mouse model of campylobacteriosis. Here we sought to determine the genetic basis of this adaptation during passage. Re-sequencing of the 1.64Mb genome to 200-500X coverage allowed us to define variation in 23 contingency loci to an unprecedented depth both before and after in vivo adaptation. Mutations in the mouse-adapted C. jejuni were largely restricted to the homopolymeric tracts of thirteen contingency loci. These changes cause significant alterations in open reading frames of genes in surface structure biosynthesis loci and in genes with only putative functions. Several loci with open reading frame changes also had altered transcript abundance. The increase in specific phases of contingency loci during in vivo passage of C. jejuni, coupled with the observed virulence increase and the lack of other types of genetic changes, is the first experimental evidence that these variable regions play a significant role in C. jejuni adaptation and virulence in a novel host.