Gene W. Tyson

Community structure and metabolism through reconstruction of microbial genomes from the environment

Microbial communities are vital in the functioning of all ecosystems; however, most microorganisms are uncultivated, and their roles in natural systems are unclear. Here, using random shotgun sequencing of DNA from a natural acidophilic biofilm, we report reconstruction of near-complete genomes of Leptospirillum group II and Ferroplasma type II, and partial recovery of three other genomes. This was possible because the biofilm was dominated by a small number of species populations and the frequency of genomic rearrangements and gene insertions or deletions was relatively low. Because each sequence read came from a different individual, we could determine that single-nucleotide polymorphisms are the predominant form of heterogeneity at the strain level. The Leptospirillum group II genome had remarkably few nucleotide polymorphisms, despite the existence of low-abundance variants. The Ferroplasma type II genome seems to be a composite from three ancestral strains that have undergone homologous recombination to form a large population of mosaic genomes. Analysis of the gene complement for each organism revealed the pathways for carbon and nitrogen fixation and energy generation, and provided insights into survival strategies in an extreme environment.

Microbial community gene expression in ocean surface waters

Metagenomics is expanding our knowledge of the gene content, functional significance, and genetic variability in natural microbial communities. Still, there exists limited information concerning the regulation and dynamics of genes in the environment. We report here global analysis of expressed genes in a naturally occurring microbial community. We first adapted RNA amplification technologies to produce large amounts of cDNA from small quantities of total microbial community RNA. The fidelity of the RNA amplification procedure was validated with Prochlorococcus cultures and then applied to a microbial assemblage collected in the oligotrophic Pacific Ocean. Microbial community cDNAs were analyzed by pyrosequencing and compared with microbial community genomic DNA sequences determined from the same sample. Pyrosequencing-based estimates of microbial community gene expression compared favorably to independent assessments of individual gene expression using quantitative PCR. Genes associated with key metabolic pathways in open ocean microbial species—including genes involved in photosynthesis, carbon fixation, and nitrogen acquisition—and a number of genes encoding hypothetical proteins were highly represented in the cDNA pool. Genes present in the variable regions of Prochlorococcus genomes were among the most highly expressed, suggesting these encode proteins central to cellular processes in specific genotypes. Although many transcripts detected were highly similar to genes previously detected in ocean metagenomic surveys, a significant fraction (≈50%) were unique. Thus, microbial community transcriptomic analyses revealed not only indigenous gene- and taxon-specific expression patterns but also gene categories undetected in previous DNA-based metagenomic surveys.

Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes

Reference genomes are required to understand the diverse roles of microorganisms in ecology, evolution, human and animal health, but most species remain uncultured. Here we present a sequence composition–independent approach to recover high-quality microbial genomes from deeply sequenced metagenomes. Multiple metagenomes of the same community, which differ in relative population abundances, were used to assemble 31 bacterial genomes, including rare (<1% relative abundance) species, from an activated sludge bioreactor. Twelve genomes were assembled into complete or near-complete chromosomes. Four belong to the candidate bacterial phylum TM7 and represent the most complete genomes for this phylum to date (relative abundances, 0.06–1.58%). Reanalysis of published metagenomes reveals that differential coverage binning facilitates recovery of more complete and higher fidelity genome bins than other currently used methods, which are primarily based on sequence composition. This approach will be an important addition to the standard metagenome toolbox and greatly improve access to genomes of uncultured microorganisms.

STAMP: Statistical analysis of taxonomic and functional profiles.

UNLABELLED STAMP is a graphical software package that provides statistical hypothesis tests and exploratory plots for analysing taxonomic and functional profiles. It supports tests for comparing pairs of samples or samples organized into two or more treatment groups. Effect sizes and confidence intervals are provided to allow critical assessment of the biological relevancy of test results. A user-friendly graphical interface permits easy exploration of statistical results and generation of publication-quality plots. AVAILABILITY AND IMPLEMENTATION STAMP is licensed under the GNU GPL. Python source code and binaries are available from our website at: http://kiwi.cs.dal.ca/Software/STAMP.

Community Proteomics of a Natural Microbial Biofilm

One proposed strategy for controlling the transmission of insect-borne pathogens uses a drive mechanism to ensure the rapid spread of transgenes conferring disease refractoriness throughout wild populations. Here, we report the creation of maternal-effect selfish genetic elements in Drosophila that drive population replacement and are resistant to recombination-mediated dissociation of drive and disease refractoriness functions. These selfish elements use microRNA-mediated silencing of a maternally expressed gene essential for embryogenesis, which is coupled with early zygotic expression of a rescuing transgene.The phosphoinositide phosphatase PTEN is mutated in many human cancers. Although the role of PTEN has been studied extensively, the relative contributions of its numerous potential downstream effectors to deregulated growth and tumorigenesis remain uncertain. We provide genetic evidence in Drosophila melanogaster for the paramount importance of the protein kinase Akt [also called protein kinase B (PKB)] in mediating the effects of increased phosphatidylinositol 3,4,5-trisphosphate (PIP3) concentrations that are caused by the loss of PTEN function. A mutation in the pleckstrin homology (PH) domain of Akt that reduces its affinity for PIP3 sufficed to rescue the lethality of flies devoid of PTEN activity. Thus, Akt appears to be the only critical target activated by increased PIP3 concentrations in Drosophila.Using genomic and mass spectrometry-based proteomic methods, we evaluated gene expression, identified key activities, and examined partitioning of metabolic functions in a natural acid mine drainage (AMD) microbial biofilm community. We detected 2033 proteins from the five most abundant species in the biofilm, including 48% of the predicted proteins from the dominant biofilm organism, Leptospirillum group II. Proteins involved in protein refolding and response to oxidative stress appeared to be highly expressed, which suggests that damage to biomolecules is a key challenge for survival. We validated and estimated the relative abundance and cellular localization of 357 unique and 215 conserved novel proteins and determined that one abundant novel protein is a cytochrome central to iron oxidation and AMD formation.

Anaerobic oxidation of methane coupled to nitrate reduction in a novel archaeal lineage

Anaerobic oxidation of methane (AOM) is critical for controlling the flux of methane from anoxic environments. AOM coupled to iron, manganese and sulphate reduction have been demonstrated in consortia containing anaerobic methanotrophic (ANME) archaea. More recently it has been shown that the bacterium Candidatus ‘Methylomirabilis oxyfera’ can couple AOM to nitrite reduction through an intra-aerobic methane oxidation pathway. Bioreactors capable of AOM coupled to denitrification have resulted in the enrichment of ‘M. oxyfera’ and a novel ANME lineage, ANME-2d. However, as ‘M. oxyfera’ can independently couple AOM to denitrification, the role of ANME-2d in the process is unresolved. Here, a bioreactor fed with nitrate, ammonium and methane was dominated by a single ANME-2d population performing nitrate-driven AOM. Metagenomic, single-cell genomic and metatranscriptomic analyses combined with bioreactor performance and 13C- and 15N-labelling experiments show that ANME-2d is capable of independent AOM through reverse methanogenesis using nitrate as the terminal electron acceptor. Comparative analyses reveal that the genes for nitrate reduction were transferred laterally from a bacterial donor, suggesting selection for this novel process within ANME-2d. Nitrite produced by ANME-2d is reduced to dinitrogen gas through a syntrophic relationship with an anaerobic ammonium-oxidizing bacterium, effectively outcompeting ‘M. oxyfera’ in the system. We propose the name Candidatus ‘Methanoperedens nitroreducens’ for the ANME-2d population and the family Candidatus ‘Methanoperedenaceae’ for the ANME-2d lineage. We predict that ‘M. nitroreducens’ and other members of the ‘Methanoperedenaceae’ have an important role in linking the global carbon and nitrogen cycles in anoxic environments.

Investigation of Candidate Division TM7, a Recently Recognized Major Lineage of the Domain Bacteria with No Known Pure-Culture Representatives

ABSTRACT A molecular approach was used to investigate a recently described candidate division of the domain Bacteria, TM7, currently known only from environmental 16S ribosomal DNA sequence data. A number of TM7-specific primers and probes were designed and evaluated. Fluorescence in situ hybridization (FISH) of a laboratory scale bioreactor using two independent TM7-specific probes revealed a conspicuous sheathed-filament morphotype, fortuitously enriched in the reactor. Morphologically, the filament matched the description of the Eikelboom morphotype 0041-0675 widely associated with bulking problems in activated-sludge wastewater treatment systems. Transmission electron microscopy of the bioreactor sludge demonstrated that the sheathed-filament morphotype had a typical gram-positive cell envelope ultrastructure. Therefore, TM7 is only the third bacterial lineage recognized to have gram-positive representatives. TM7-specific FISH analysis of two full-scale wastewater treatment plant sludges, including the one used to seed the laboratory scale reactor, indicated the presence of a number of morphotypes, including sheathed filaments. TM7-specific PCR clone libraries prepared from the two full-scale sludges yielded 23 novel TM7 sequences. Three subdivisions could be defined based on these data and publicly available sequences. Environmental sequence data and TM7-specific FISH analysis indicate that members of the TM7 division are present in a variety of terrestrial, aquatic, and clinical habitats. A highly atypical base substitution (Escherichia coli position 912; C to U) for bacterial 16S rRNAs was present in almost all TM7 sequences, suggesting that TM7 bacteria, like Archaea, may be streptomycin resistant at the ribosome level.

Fast, accurate error-correction of amplicon pyrosequences using Acacia

To the Editor: Microbial diversity metrics based on high-throughput amplicon sequencing are compromised by read errors. Roche 454 GS FLX Titanium pyrosequencing is currently the most widely used technology for amplicon-based microbial community studies, despite high homopolymer-associated insertion-deletion error rates1,2. Currently, there are two software packages, AmpliconNoise3 and Denoiser4, that are commonly used to correct amplicon pyrosequencing errors. AmpliconNoise applies an approximate likelihood using empirically derived error distributions to remove pyrosequencing noise from reads. AmpliconNoise is highly effective at noise removal but is computationally intensive3. Denoiser is a faster algorithm that uses frequency-based heuristics rather than statistical modeling to cluster reads. Neither tool modifies individual reads; instead both select an ‘error-free’ read to represent reads in a given cluster. We developed a tool for homopolymer error-correction that has greater scalability than existing tools. We explored whether there was sufficient information in the FASTA files alone to achieve the sensitivity and specificity of AmpliconNoise and Denoiser, which both use raw flowgrams. Our error-correction tool, Acacia, meets these objectives. First, Acacia reduces the number and complexity of alignments. Rather than performing all-against-all alignments in a cluster, each read in the cluster is aligned to a dynamically updated cluster consensus; the alignment algorithm is made more efficient using heuristics that only consider homopolymer overand under-calls. Secondly, Acacia uses a quicker but less sensitive statistical approach to distinguish between error and genuine sequence differences (Supplementary Methods and Supplementary Notes 1–3). We measured the performance of Acacia relative to AmpliconNoise and Denoiser using three synthetic small subunit ribosomal RNA (SSU rRNA) gene amplicon data sets (‘artificial’, ‘divergent’ and ‘titanium’) previously used to benchmark the latter tools3,4. For each data set, we recorded the peak memory usage and CPU run time (Supplementary Table 1). We benchmarked AmpliconNoise using only the smaller artificial data set, which was sufficient to indicate that this software was impractical for analyzing larger data sets. The peak memory used by Acacia was 1–4× higher than that used by Denoiser and ~14× lower than by AmpliconNoise. Acacia ran on all data sets in under 1 minute, was up to ~500× faster than Denoiser for the titanium data set, and more than 2,000× faster than AmpliconNoise for the artificial data set. Acacia processed larger contemporary data sets (200,000 GS FLX Titanium reads) in under 80 CPU minutes. We next benchmarked the error-correction sensitivity and specificity of Acacia. For convenience, we refer to correction of individual reads although corrections are derived from either a cluster consensus (Acacia) or representative read (AmpliconNoise and Denoiser). Despite working with the less precise rounded flow values, Acacia corrected the majority of GS FLX Titanium homopolymer errors corrected by AmpliconNoise and Denoiser (Fig. 1a). As expected, Acacia has less sensitivity than AmpliconNoise and Denoiser for correcting substitution errors because it only attempts to correct homopolymer errors. Acacia did, however, correct ~40% of the AmpliconNoiseand Denoiser-corrected substitutions in the titanium data set (Fig. 1b) because these errors were the consequence of consecutive over-under calls or vice versa. We found that AmpliconNoise and Denoiser introduced a substantial number of errors, most of them non-homopolymer substitutions, during error-correction (Fig. 1c). Notably, Acacia introduced 2× and 12× fewer errors than AmpliconNoise and Denoiser, respectively. Errors

Metatranscriptomics reveals unique microbial small RNAs in the ocean’s water column

Microbial gene expression in the environment has recently been assessed via pyrosequencing of total RNA extracted directly from natural microbial assemblages. Several such ‘metatranscriptomic’ studies have reported that many complementary DNA sequences shared no significant homology with known peptide sequences, and so might represent transcripts from uncharacterized proteins. Here we report that a large fraction of cDNA sequences detected in microbial metatranscriptomic data sets are comprised of well-known small RNAs (sRNAs), as well as new groups of previously unrecognized putative sRNAs (psRNAs). These psRNAs mapped specifically to intergenic regions of microbial genomes recovered from similar habitats, displayed characteristic conserved secondary structures and were frequently flanked by genes that indicated potential regulatory functions. Depth-dependent variation of psRNAs generally reflected known depth distributions of broad taxonomic groups, but fine-scale differences in the psRNAs within closely related populations indicated potential roles in niche adaptation. Genome-specific mapping of a subset of psRNAs derived from predominant planktonic species such as Pelagibacter revealed recently discovered as well as potentially new regulatory elements. Our analyses show that metatranscriptomic data sets can reveal new information about the diversity, taxonomic distribution and abundance of sRNAs in naturally occurring microbial communities, and indicate their involvement in environmentally relevant processes including carbon metabolism and nutrient acquisition.

Strain-resolved community proteomics reveals recombining genomes of acidophilic bacteria

Microbes comprise the majority of extant organisms, yet much remains to be learned about the nature and driving forces of microbial diversification. Our understanding of how microorganisms adapt and evolve can be advanced by genome-wide documentation of the patterns of genetic exchange, particularly if analyses target coexisting members of natural communities. Here we use community genomic data sets to identify, with strain specificity, expressed proteins from the dominant member of a genomically uncharacterized, natural, acidophilic biofilm. Proteomics results reveal a genome shaped by recombination involving chromosomal regions of tens to hundreds of kilobases long that are derived from two closely related bacterial populations. Inter-population genetic exchange was confirmed by multilocus sequence typing of isolates and of uncultivated natural consortia. The findings suggest that exchange of large blocks of gene variants is crucial for the adaptation to specific ecological niches within the very acidic, metal-rich environment. Mass-spectrometry-based discrimination of expressed protein products that differ by as little as a single amino acid enables us to distinguish the behaviour of closely related coexisting organisms. This is important, given that microorganisms grouped together as a single species may have quite distinct roles in natural systems and their interactions might be key to ecosystem optimization. Because proteomic data simultaneously convey information about genome type and activity, strain-resolved community proteomics is an important complement to cultivation-independent genomic (metagenomic) analysis of microorganisms in the natural environment.