MultiPhATE2: code for functional annotation and comparison of phage genomes.

To address a need for improved tools for annotation and comparative genomics of bacteriophage genomes, we developed multiPhATE2. As an extension of multiPhATE, a functional annotation code released previously, multiPhATE2 performs gene finding using multiple algorithms, compares the results of the algorithms, performs functional annotation of coding sequences, and incorporates additional search algorithms and databases to extend the search space of the original code. MultiPhATE2 performs gene matching among sets of closely related bacteriophage genomes, and uses multiprocessing to speed computations. MultiPhATE2 can be re-started at multiple points within the workflow to allow the user to examine intermediate results and adjust the subsequent computations accordingly. In addition, multiPhATE2 accommodates custom gene calls and sequence databases, again adding flexibility. MultiPhATE2 was implemented in Python 3.7 and runs as a command-line code under Linux or MAC operating systems. Full documentation is provided as a README file and a Wiki website.

Utilizing Amino Acid Composition and Entropy of Potential Open Reading Frames to Identify Protein-Coding Genes.

One of the main steps in gene-finding in prokaryotes is determining which open reading frames encode for a protein, and which occur by chance alone. There are many different methods to differentiate the two; the most prevalent approach is using shared homology with a database of known genes. This method presents many pitfalls, most notably the catch that you only find genes that you have seen before. The four most popular prokaryotic gene-prediction programs (GeneMark, Glimmer, Prodigal, Phanotate) all use a protein-coding training model to predict protein-coding genes, with the latter three allowing for the training model to be created ab initio from the input genome. Different methods are available for creating the training model, and to increase the accuracy of such tools, we present here GOODORFS, a method for identifying protein-coding genes within a set of all possible open reading frames (ORFS). Our workflow begins with taking the amino acid frequencies of each ORF, calculating an entropy density profile (EDP), using KMeans to cluster the EDPs, and then selecting the cluster with the lowest variation as the coding ORFs. To test the efficacy of our method, we ran GOODORFS on 14,179 annotated phage genomes, and compared our results to the initial training-set creation step of four other similar methods (Glimmer, MED2, PHANOTATE, Prodigal). We found that GOODORFS was the most accurate (0.94) and had the best F1-score (0.85), while Glimmer had the highest precision (0.92) and PHANOTATE had the highest recall (0.96).

multiPhATE: bioinformatics pipeline for functional annotation of phage isolates.

SUMMARY: To address the need for improved phage annotation tools that scale, we created an automated throughput annotation pipeline: multiple-genome Phage Annotation Toolkit and Evaluator (multiPhATE). multiPhATE is a throughput pipeline driver that invokes an annotation pipeline (PhATE) across a user-specified set of phage genomes. This tool incorporates a de novo phage gene calling algorithm and assigns putative functions to gene calls using protein-, virus- and phage-centric databases. multiPhATE's modular construction allows the user to implement all or any portion of the analyses by acquiring local instances of the desired databases and specifying the desired analyses in a configuration file. We demonstrate multiPhATE by annotating two newly sequenced Yersinia pestis phage genomes. Within multiPhATE, the PhATE processing pipeline can be readily implemented across multiple processors, making it adaptable for throughput sequencing projects. Software documentation assists the user in configuring the system. AVAILABILITY AND IMPLEMENTATION: multiPhATE was implemented in Python 3.7, and runs as a command-line code under Linux or Unix. multiPhATE is freely available under an open-source BSD3 license from https://github.com/carolzhou/multiPhATE. Instructions for acquiring the databases and third-party codes used by multiPhATE are included in the distribution README file. Users may report bugs by submitting to the github issues page associated with the multiPhATE distribution. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A compendium of multi-omic sequence information from the Saanich Inlet water column.

Marine oxygen minimum zones (OMZs) are widespread regions of the ocean that are currently expanding due to global warming. While inhospitable to most metazoans, OMZs are hotspots for microbial mediated biogeochemical cycling of carbon, nitrogen and sulphur, contributing disproportionately to marine nitrogen loss and climate active trace gas production. Our current understanding of microbial community responses to OMZ expansion is limited by a lack of time-resolved data sets linking multi-omic sequence information (DNA, RNA, protein) to geochemical parameters and process rates. Here, we present six years of time-resolved multi-omic observations in Saanich Inlet, a seasonally anoxic fjord on the coast of Vancouver Island, British Columbia, Canada that undergoes recurring changes in water column oxygenation status. This compendium provides a unique multi-omic framework for studying microbial community responses to ocean deoxygenation along defined geochemical gradients in OMZ waters.

Major changes in microbial diversity and community composition across gut sections of a juvenile Panchlora cockroach.

Investigations of gut microbiomes have shed light on the diversity and genetic content of these communities, and helped shape our understanding of how host-associated microorganisms influence host physiology, behavior, and health. Despite the importance of gut microbes to metazoans, our understanding of the changes in diversity and composition across the alimentary tract, and the source of the resident community are limited. Here, using community metagenomics and 16S rRNA gene sequencing, we assess microbial community diversity and coding potential in the foregut, midgut, and hindgut of a juvenile Panchlora cockroach, which resides in the refuse piles of the leaf-cutter ant species Atta colombica. We found a significant shift in the microbial community structure and coding potential throughout the three gut sections of Panchlora sp., and through comparison with previously generated metagenomes of the cockroach's food source and niche, we reveal that this shift in microbial community composition is influenced by the ecosystems in which Panchlora sp. occurs. While the foregut is composed of microbes that likely originate from the symbiotic fungus gardens of the ants, the midgut and hindgut are composed of a microbial community that is likely cockroach-specific. Analogous to mammalian systems, the midgut and hindgut appear to be dominated by Firmicutes and Bacteroidetes with the capacity for polysaccharide degradation, suggesting they may assist in the degradation of dietary plant material. Our work underscores the prominence of community changes throughout gut microbiomes and highlights ecological factors that underpin the structure and function of the symbiotic microbial communities of metazoans.

A comprehensive multi-omics approach uncovers adaptations for growth and survival of Pseudomonas aeruginosa on n-alkanes.

BACKGROUND: Examination of complex biological systems has long been achieved through methodical investigation of the system's individual components. While informative, this strategy often leads to inappropriate conclusions about the system as a whole. With the advent of high-throughput "omic" technologies, however, researchers can now simultaneously analyze an entire system at the level of molecule (DNA, RNA, protein, metabolite) and process (transcription, translation, enzyme catalysis). This strategy reduces the likelihood of improper conclusions, provides a framework for elucidation of genotype-phenotype relationships, and brings finer resolution to comparative genomic experiments. Here, we apply a multi-omic approach to analyze the gene expression profiles of two closely related Pseudomonas aeruginosa strains grown in n-alkanes or glycerol. RESULTS: The environmental P. aeruginosa isolate ATCC 33988 consumed medium-length (C10-C16) n-alkanes more rapidly than the laboratory strain PAO1, despite high genome sequence identity (average nucleotide identity >99%). Our data shows that ATCC 33988 induces a characteristic set of genes at the transcriptional, translational and post-translational levels during growth on alkanes, many of which differ from those expressed by PAO1. Of particular interest was the lack of expression from the rhl operon of the quorum sensing (QS) system, resulting in no measurable rhamnolipid production by ATCC 33988. Further examination showed that ATCC 33988 lacked the entire lasI/lasR arm of the QS response. Instead of promoting expression of QS genes, ATCC 33988 up-regulates a small subset of its genome, including operons responsible for specific alkaline proteases and sphingosine metabolism. CONCLUSION: This work represents the first time results from RNA-seq, microarray, ribosome footprinting, proteomics, and small molecule LC-MS experiments have been integrated to compare gene expression in bacteria. Together, these data provide insights as to why strain ATCC 33988 is better adapted for growth and survival on n-alkanes.

Prospects for Fungal Bioremediation of Acidic Radioactive Waste Sites: Characterization and Genome Sequence of Rhodotorula taiwanensis MD1149.

Highly concentrated radionuclide waste produced during the Cold War era is stored at US Department of Energy (DOE) production sites. This radioactive waste was often highly acidic and mixed with heavy metals, and has been leaking into the environment since the 1950s. Because of the danger and expense of cleanup of such radioactive sites by physicochemical processes, in situ bioremediation methods are being developed for cleanup of contaminated ground and groundwater. To date, the most developed microbial treatment proposed for high-level radioactive sites employs the radiation-resistant bacterium Deinococcus radiodurans. However, the use of Deinococcus spp. and other bacteria is limited by their sensitivity to low pH. We report the characterization of 27 diverse environmental yeasts for their resistance to ionizing radiation (chronic and acute), heavy metals, pH minima, temperature maxima and optima, and their ability to form biofilms. Remarkably, many yeasts are extremely resistant to ionizing radiation and heavy metals. They also excrete carboxylic acids and are exceptionally tolerant to low pH. A special focus is placed on Rhodotorula taiwanensis MD1149, which was the most resistant to acid and gamma radiation. MD1149 is capable of growing under 66 Gy/h at pH 2.3 and in the presence of high concentrations of mercury and chromium compounds, and forming biofilms under high-level chronic radiation and low pH. We present the whole genome sequence and annotation of R. taiwanensis strain MD1149, with a comparison to other Rhodotorula species. This survey elevates yeasts to the frontier of biology's most radiation-resistant representatives, presenting a strong rationale for a role of fungi in bioremediation of acidic radioactive waste sites.

Transcriptomic analysis of the highly efficient oil-degrading bacterium Acinetobacter venetianus RAG-1 reveals genes important in dodecane uptake and utilization.

The hydrocarbonoclastic bacterium Acinetobacter venetianus RAG-1 has attracted substantial attention due to its powerful oil-degrading capabilities and its potential to play an important ecological role in the cleanup of alkanes. In this study, we compare the transcriptome of the strain RAG-1 grown in dodecane, the corresponding alkanol (dodecanol), and sodium acetate for the characterization of genes involved in dodecane uptake and utilization. Comparison of the transcriptional responses of RAG-1 grown on dodecane led to the identification of 1074 genes that were differentially expressed relative to sodium acetate. Of these, 622 genes were upregulated when grown in dodecane. The highly upregulated genes were involved in alkane catabolism, along with stress response. Our data suggest AlkMb to be primarily involved in dodecane oxidation. Transcriptional response of RAG-1 grown on dodecane relative to dodecanol also led to the identification of permease, outer membrane protein and thin fimbriae coding genes potentially involved in dodecane uptake. This study provides the first model for key genes involved in alkane uptake and metabolism in A. venetianus RAG-1.

Genome-wide selective sweeps and gene-specific sweeps in natural bacterial populations.

Multiple models describe the formation and evolution of distinct microbial phylogenetic groups. These evolutionary models make different predictions regarding how adaptive alleles spread through populations and how genetic diversity is maintained. Processes predicted by competing evolutionary models, for example, genome-wide selective sweeps vs gene-specific sweeps, could be captured in natural populations using time-series metagenomics if the approach were applied over a sufficiently long time frame. Direct observations of either process would help resolve how distinct microbial groups evolve. Here, from a 9-year metagenomic study of a freshwater lake (2005-2013), we explore changes in single-nucleotide polymorphism (SNP) frequencies and patterns of gene gain and loss in 30 bacterial populations. SNP analyses revealed substantial genetic heterogeneity within these populations, although the degree of heterogeneity varied by >1000-fold among populations. SNP allele frequencies also changed dramatically over time within some populations. Interestingly, nearly all SNP variants were slowly purged over several years from one population of green sulfur bacteria, while at the same time multiple genes either swept through or were lost from this population. These patterns were consistent with a genome-wide selective sweep in progress, a process predicted by the 'ecotype model' of speciation but not previously observed in nature. In contrast, other populations contained large, SNP-free genomic regions that appear to have swept independently through the populations prior to the study without purging diversity elsewhere in the genome. Evidence for both genome-wide and gene-specific sweeps suggests that different models of bacterial speciation may apply to different populations coexisting in the same environment.

PLANT MICROBIOME. Salicylic acid modulates colonization of the root microbiome by specific bacterial taxa.

Immune systems distinguish "self" from "nonself" to maintain homeostasis and must differentially gate access to allow colonization by potentially beneficial, nonpathogenic microbes. Plant roots grow within extremely diverse soil microbial communities but assemble a taxonomically limited root-associated microbiome. We grew isogenic Arabidopsis thaliana mutants with altered immune systems in a wild soil and also in recolonization experiments with a synthetic bacterial community. We established that biosynthesis of, and signaling dependent on, the foliar defense phytohormone salicylic acid is required to assemble a normal root microbiome. Salicylic acid modulates colonization of the root by specific bacterial families. Thus, plant immune signaling drives selection from the available microbial communities to sculpt the root microbiome.

Patterns in wetland microbial community composition and functional gene repertoire associated with methane emissions.

UNLABELLED: Wetland restoration on peat islands previously drained for agriculture has potential to reverse land subsidence and sequester atmospheric carbon dioxide as peat accretes. However, the emission of methane could potentially offset the greenhouse gas benefits of captured carbon. As microbial communities play a key role in governing wetland greenhouse gas fluxes, we are interested in how microbial community composition and functions are associated with wetland hydrology, biogeochemistry, and methane emission, which is critical to modeling the microbial component in wetland methane fluxes and to managing restoration projects for maximal carbon sequestration. Here, we couple sequence-based methods with biogeochemical and greenhouse gas measurements to interrogate microbial communities from a pilot-scale restored wetland in the Sacramento-San Joaquin Delta of California, revealing considerable spatial heterogeneity even within this relatively small site. A number of microbial populations and functions showed strong correlations with electron acceptor availability and methane production; some also showed a preference for association with plant roots. Marker gene phylogenies revealed a diversity of major methane-producing and -consuming populations and suggested novel diversity within methanotrophs. Methanogenic archaea were observed in all samples, as were nitrate-, sulfate-, and metal-reducing bacteria, indicating that no single terminal electron acceptor was preferred despite differences in energetic favorability and suggesting spatial microheterogeneity and microniches. Notably, methanogens were negatively correlated with nitrate-, sulfate-, and metal-reducing bacteria and were most abundant at sampling sites with high peat accretion and low electron acceptor availability, where methane production was highest. IMPORTANCE: Wetlands are the largest nonanthropogenic source of atmospheric methane but also a key global carbon reservoir. Characterizing belowground microbial communities that mediate carbon cycling in wetlands is critical to accurately predicting their responses to changes in land management and climate. Here, we studied a restored wetland and revealed substantial spatial heterogeneity in biogeochemistry, methane production, and microbial communities, largely associated with the wetland hydraulic design. We observed patterns in microbial community composition and functions correlated with biogeochemistry and methane production, including diverse microorganisms involved in methane production and consumption. We found that methanogenesis gene abundance is inversely correlated with genes from pathways exploiting other electron acceptors, yet the ubiquitous presence of genes from all these pathways suggests that diverse electron acceptors contribute to the energetic balance of the ecosystem. These investigations represent an important step toward effective management of wetlands to reduce methane flux to the atmosphere and enhance belowground carbon storage.

Gill bacteria enable a novel digestive strategy in a wood-feeding mollusk.

Bacteria play many important roles in animal digestive systems, including the provision of enzymes critical to digestion. Typically, complex communities of bacteria reside in the gut lumen in direct contact with the ingested materials they help to digest. Here, we demonstrate a previously undescribed digestive strategy in the wood-eating marine bivalve Bankia setacea, wherein digestive bacteria are housed in a location remote from the gut. These bivalves, commonly known as shipworms, lack a resident microbiota in the gut compartment where wood is digested but harbor endosymbiotic bacteria within specialized cells in their gills. We show that this comparatively simple bacterial community produces wood-degrading enzymes that are selectively translocated from gill to gut. These enzymes, which include just a small subset of the predicted wood-degrading enzymes encoded in the endosymbiont genomes, accumulate in the gut to the near exclusion of other endosymbiont-made proteins. This strategy of remote enzyme production provides the shipworm with a mechanism to capture liberated sugars from wood without competition from an endogenous gut microbiota. Because only those proteins required for wood digestion are translocated to the gut, this newly described system reveals which of many possible enzymes and enzyme combinations are minimally required for wood degradation. Thus, although it has historically had negative impacts on human welfare, the shipworm digestive process now has the potential to have a positive impact on industries that convert wood and other plant biomass to renewable fuels, fine chemicals, food, feeds, textiles, and paper products.

Convergent bacterial microbiotas in the fungal agricultural systems of insects.

UNLABELLED: The ability to cultivate food is an innovation that has produced some of the most successful ecological strategies on the planet. Although most well recognized in humans, where agriculture represents a defining feature of civilization, species of ants, beetles, and termites have also independently evolved symbioses with fungi that they cultivate for food. Despite occurring across divergent insect and fungal lineages, the fungivorous niches of these insects are remarkably similar, indicating convergent evolution toward this successful ecological strategy. Here, we characterize the microbiota of ants, beetles, and termites engaged in nutritional symbioses with fungi to define the bacterial groups associated with these prominent herbivores and forest pests. Using culture-independent techniques and the in silico reconstruction of 37 composite genomes of dominant community members, we demonstrate that different insect-fungal symbioses that collectively shape ecosystems worldwide have highly similar bacterial microbiotas comprised primarily of the genera Enterobacter, Rahnella, and Pseudomonas. Although these symbioses span three orders of insects and two phyla of fungi, we show that they are associated with bacteria sharing high whole-genome nucleotide identity. Due to the fine-scale correspondence of the bacterial microbiotas of insects engaged in fungal symbioses, our findings indicate that this represents an example of convergence of entire host-microbe complexes. IMPORTANCE: The cultivation of fungi for food is a behavior that has evolved independently in ants, beetles, and termites and has enabled many species of these insects to become ecologically important and widely distributed herbivores and forest pests. Although the primary fungal cultivars of these insects have been studied for decades, comparatively little is known of their bacterial microbiota. In this study, we show that diverse fungus-growing insects are associated with a common bacterial community composed of the same dominant members. Furthermore, by demonstrating that many of these bacteria have high whole-genome similarity across distantly related insect hosts that reside thousands of miles apart, we show that these bacteria are an important and underappreciated feature of diverse fungus-growing insects. Because of the similarities in the agricultural lifestyles of these insects, this is an example of convergence between both the life histories of the host insects and their symbiotic microbiota.

Metagenomic analysis of microbial consortium from natural crude oil that seeps into the marine ecosystem offshore Southern California.

Crude oils can be major contaminants of the marine ecosystem and microorganisms play a significant role in the degradation of its main constituents. To increase our understanding of the microbial hydrocarbon degradation process in the marine ecosystem, we collected crude oil from an active seep area located in the Santa Barbara Channel (SBC) and generated a total of about 52 Gb of raw metagenomic sequence data. The assembled data comprised ~500 Mb, representing ~1.1 million genes derived primarily from chemolithoautotrophic bacteria. Members of Oceanospirillales, a bacterial order belonging to the Deltaproteobacteria, recruited less than 2% of the assembled genes within the SBC metagenome. In contrast, the microbial community associated with the oil plume that developed in the aftermath of the Deepwater Horizon (DWH) blowout in 2010, was dominated by Oceanospirillales, which comprised more than 60% of the metagenomic data generated from the DWH oil plume. This suggests that Oceanospirillales might play a less significant role in the microbially mediated hydrocarbon conversion within the SBC seep oil compared to the DWH plume oil. We hypothesize that this difference results from the SBC oil seep being mostly anaerobic, while the DWH oil plume is aerobic. Within the Archaea, the phylum Euryarchaeota, recruited more than 95% of the assembled archaeal sequences from the SBC oil seep metagenome, with more than 50% of the sequences assigned to members of the orders Methanomicrobiales and Methanosarcinales. These orders contain organisms capable of anaerobic methanogenesis and methane oxidation (AOM) and we hypothesize that these orders - and their metabolic capabilities - may be fundamental to the ecology of the SBC oil seep.

Temporal dynamics of fibrolytic and methanogenic rumen microorganisms during in situ incubation of switchgrass determined by 16S rRNA gene profiling.

The rumen microbial ecosystem is known for its biomass-degrading and methane-producing phenotype. Fermentation of recalcitrant plant material, comprised of a multitude of interwoven fibers, necessitates the synergistic activity of diverse microbial taxonomic groups that inhabit the anaerobic rumen ecosystem. Although interspecies hydrogen (H2) transfer, a process during which bacterially generated H2 is transferred to methanogenic Archaea, has obtained significant attention over the last decades, the temporal variation of the different taxa involved in in situ biomass-degradation, H2 transfer and the methanogenesis process remains to be established. Here we investigated the temporal succession of microbial taxa and its effect on fiber composition during rumen incubation using 16S rRNA amplicon sequencing. Switchgrass filled nylon bags were placed in the rumen of a cannulated cow and collected at nine time points for DNA extraction and 16S pyrotag profiling. The microbial community colonizing the air-dried and non-incubated (0 h) switchgrass was dominated by members of the Bacilli (recruiting 63% of the pyrotag reads). During in situ incubation of the switchgrass, two major shifts in the community composition were observed: Bacilli were replaced within 30 min by members belonging to the Bacteroidia and Clostridia, which recruited 34 and 25% of the 16S rRNA reads generated, respectively. A second significant shift was observed after 16 h of rumen incubation, when members of the Spirochaetes and Fibrobacteria classes became more abundant in the fiber-adherent community. During the first 30 min of rumen incubation ~13% of the switchgrass dry matter was degraded, whereas little biomass degradation appeared to have occurred between 30 min and 4 h after the switchgrass was placed in the rumen. Interestingly, methanogenic members of the Euryarchaeota (i.e., Methanobacteria) increased up to 3-fold during this period of reduced biomass-degradation, with peak abundance just before rates of dry matter degradation increased again. We hypothesize that during this period microbial-mediated fibrolysis was temporarily inhibited until H2 was metabolized into CH4 by methanogens. Collectively, our results demonstrate the importance of inter-species interactions for the biomass-degrading and methane-producing phenotype of the rumen microbiome-both microbially facilitated processes with global significance.

Metagenomes from two microbial consortia associated with Santa Barbara seep oil.

The metagenomes from two microbial consortia associated with natural oils seeping into the Pacific Ocean offshore the coast of Santa Barbara (California, USA) were determined to complement already existing metagenomes generated from microbial communities associated with hydrocarbons that pollute the marine ecosystem. This genomics resource article is the first of two publications reporting a total of four new metagenomes from oils that seep into the Santa Barbara Channel.

Tackling soil diversity with the assembly of large, complex metagenomes.

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.

The epsomitic phototrophic microbial mat of Hot Lake, Washington: community structural responses to seasonal cycling.

Phototrophic microbial mats are compact ecosystems composed of highly interactive organisms in which energy and element cycling take place over millimeter-to-centimeter-scale distances. Although microbial mats are common in hypersaline environments, they have not been extensively characterized in systems dominated by divalent ions. Hot Lake is a meromictic, epsomitic lake that occupies a small, endorheic basin in north-central Washington. The lake harbors a benthic, phototrophic mat that assembles each spring, disassembles each fall, and is subject to greater than tenfold variation in salinity (primarily Mg(2+) and SO(2-) 4) and irradiation over the annual cycle. We examined spatiotemporal variation in the mat community at five time points throughout the annual cycle with respect to prevailing physicochemical parameters by amplicon sequencing of the V4 region of the 16S rRNA gene coupled to near-full-length 16S RNA clone sequences. The composition of these microbial communities was relatively stable over the seasonal cycle and included dominant populations of Cyanobacteria, primarily a group IV cyanobacterium (Leptolyngbya), and Alphaproteobacteria (specifically, members of Rhodobacteraceae and Geminicoccus). Members of Gammaproteobacteria (e.g., Thioalkalivibrio and Halochromatium) and Deltaproteobacteria (e.g., Desulfofustis) that are likely to be involved in sulfur cycling peaked in summer and declined significantly by mid-fall, mirroring larger trends in mat community richness and evenness. Phylogenetic turnover analysis of abundant phylotypes employing environmental metadata suggests that seasonal shifts in light variability exert a dominant influence on the composition of Hot Lake microbial mat communities. The seasonal development and organization of these structured microbial mats provide opportunities for analysis of the temporal and physical dynamics that feed back to community function.

Polynucleobacter necessarius, a model for genome reduction in both free-living and symbiotic bacteria.

We present the complete genomic sequence of the essential symbiont Polynucleobacter necessarius (Betaproteobacteria), which is a valuable case study for several reasons. First, it is hosted by a ciliated protist, Euplotes; bacterial symbionts of ciliates are still poorly known because of a lack of extensive molecular data. Second, the single species P. necessarius contains both symbiotic and free-living strains, allowing for a comparison between closely related organisms with different ecologies. Third, free-living P. necessarius strains are exceptional by themselves because of their small genome size, reduced metabolic flexibility, and high worldwide abundance in freshwater systems. We provide a comparative analysis of P. necessarius metabolism and explore the peculiar features of a genome reduction that occurred on an already streamlined genome. We compare this unusual system with current hypotheses for genome erosion in symbionts and free-living bacteria, propose modifications to the presently accepted model, and discuss the potential consequences of translesion DNA polymerase loss.

Metagenomes of tropical soil-derived anaerobic switchgrass-adapted consortia with and without iron.

Tropical forest soils decompose litter rapidly with frequent episodes of anoxia, making it likely that bacteria using alternate terminal electron acceptors (TEAs) such as iron play a large role in supporting decomposition under these conditions. The prevalence of many types of metabolism in litter deconstruction makes these soils useful templates for improving biofuel production. To investigate how iron availability affects decomposition, we cultivated feedstock-adapted consortia (FACs) derived from iron-rich tropical forest soils accustomed to experiencing frequent episodes of anaerobic conditions and frequently fluctuating redox. One consortium was propagated under fermenting conditions, with switchgrass as the sole carbon source in minimal media (SG only FACs), and the other consortium was treated the same way but received poorly crystalline iron as an additional terminal electron acceptor (SG + Fe FACs). We sequenced the metagenomes of both consortia to a depth of about 150 Mb each, resulting in a coverage of 26× for the more diverse SG + Fe FACs, and 81× for the relatively less diverse SG only FACs. Both consortia were able to quickly grow on switchgrass, and the iron-amended consortium exhibited significantly higher microbial diversity than the unamended consortium. We found evidence of higher stress in the unamended FACs and increased sugar transport and utilization in the iron-amended FACs. This work provides metagenomic evidence that supplementation of alternative TEAs may improve feedstock deconstruction in biofuel production.