Differential colonization and functioning of microbial community in response to phosphate levels.

Microbes play a major role in phosphate cycling and regulate its availability in various environments. The metagenomic study highlights the microbial community divergence and interplay of phosphate metabolism functional genes in response to phosphate rich (100 mgL-1), limiting (25 mgL-1), and stressed (5 mgL-1) conditions at lab-scale bioreactor. Total five core phyla were found responsive toward different phosphate (Pi) levels. However, major variations were observed in Proteobacteria and Actinobacteria with 33-81% and 5-56% relative abundance, respectively. Canonical correspondence analysis reflects the colonization of Sinorhizobium (0.8-4%), Mesorhizobium (1-4%), Rhizobium (0.5-3%) in rich condition whereas, Pseudomonas (1-2%), Rhodococcus (0.2-2%), Flavobacterium (0.2-1%) and Streptomyces (0.3-4%) colonized in limiting and stress condition. The functional profiling demonstrates that Pi limiting and stress condition subjected biomass were characterized by abundant PQQ-Glucose dehydrogenase, alkaline phosphatase, 5'-nucleotidase, and phospholipases C genes. The finding implies that the major abundant genera belonging to phosphate solubilization enriched in limiting/stressed conditions decide the functional turnover by modulating the metabolic flexibility for Pi cycling. The study gives a better insight into intrinsic ecological responsiveness mediated by microbial communities in different Pi conditions that would help to design the microbiome according to the soil phosphate condition. Furthermore, this information assists in sustainably maintaining the ecological balance by omitting excessive chemical fertilizers and eutrophication.

Spatial Metagenomics of Three Geothermal Sites in Pisciarelli Hot Spring Focusing on the Biochemical Resources of the Microbial Consortia.

Terrestrial hot springs are of great interest to the general public and to scientists alike due to their unique and extreme conditions. These have been sought out by geochemists, astrobiologists, and microbiologists around the globe who are interested in their chemical properties, which provide a strong selective pressure on local microorganisms. Drivers of microbial community composition in these springs include temperature, pH, in-situ chemistry, and biogeography. Microbes in these communities have evolved strategies to thrive in these conditions by converting hot spring chemicals and organic matter into cellular energy. Following our previous metagenomic analysis of Pisciarelli hot springs (Naples, Italy), we report here the comparative metagenomic study of three novel sites, formed in Pisciarelli as result of recent geothermal activity. This study adds comprehensive information about phylogenetic diversity within Pisciarelli hot springs by peeking into possible mechanisms of adaptation to biogeochemical cycles, and high applicative potential of the entire set of genes involved in the carbohydrate metabolism in this environment (CAZome). This site is an excellent model for the study of biodiversity on Earth and biosignature identification, and for the study of the origin and limits of life.

MetaComp: comprehensive analysis software for comparative meta-omics including comparative metagenomics.

BACKGROUND: During the past decade, the development of high throughput nucleic sequencing and mass spectrometry analysis techniques have enabled the characterization of microbial communities through metagenomics, metatranscriptomics, metaproteomics and metabolomics data. To reveal the diversity of microbial communities and interactions between living conditions and microbes, it is necessary to introduce comparative analysis based upon integration of all four types of data mentioned above. Comparative meta-omics, especially comparative metageomics, has been established as a routine process to highlight the significant differences in taxon composition and functional gene abundance among microbiota samples. Meanwhile, biologists are increasingly concerning about the correlations between meta-omics features and environmental factors, which may further decipher the adaptation strategy of a microbial community. RESULTS: We developed a graphical comprehensive analysis software named MetaComp comprising a series of statistical analysis approaches with visualized results for metagenomics and other meta-omics data comparison. This software is capable to read files generated by a variety of upstream programs. After data loading, analyses such as multivariate statistics, hypothesis testing of two-sample, multi-sample as well as two-group sample and a novel function-regression analysis of environmental factors are offered. Here, regression analysis regards meta-omic features as independent variable and environmental factors as dependent variables. Moreover, MetaComp is capable to automatically choose an appropriate two-group sample test based upon the traits of input abundance profiles. We further evaluate the performance of its choice, and exhibit applications for metagenomics, metaproteomics and metabolomics samples. CONCLUSION: MetaComp, an integrative software capable for applying to all meta-omics data, originally distills the influence of living environment on microbial community by regression analysis. Moreover, since the automatically chosen two-group sample test is verified to be outperformed, MetaComp is friendly to users without adequate statistical training. These improvements are aiming to overcome the new challenges under big data era for all meta-omics data. MetaComp is available at: http://cqb.pku.edu.cn/ZhuLab/MetaComp/ and https://github.com/pzhaipku/MetaComp/ .

Extremely halophilic brine community manipulation shows higher robustness of microbiomes inhabiting human-driven solar saltern than naturally driven lake.

Hypersaline ecosystems display taxonomically similar assemblages with low diversities and highly dense accompanying viromes. The ecological implications of viral infection on natural microbial populations remain poorly understood, especially at finer scales of diversity. Here, we sought to investigate the influence of changes in environmental physicochemical conditions and viral predation pressure by autochthonous and allochthonous viruses on host dynamics. For this purpose, we transplanted two microbiomes coming from distant hypersaline systems (solar salterns of Es Trenc in Spain and the thalassohaline lake of Aran-Bidgol lake in Iran), by exchanging the cellular fractions with the sterile-filtered accompanying brines with and without the free extracellular virus fraction. The midterm exposure (1 month) of the microbiomes to the new conditions showed that at the supraspecific taxonomic range, the assemblies from the solar saltern brine more strongly resisted the environmental changes and viral predation than that of the lake. The metagenome-assembled genomes (MAGs) analysis revealed an intraspecific transition at the ecotype level, mainly driven by changes in viral predation pressure, by both autochthonous and allochthonous viruses. IMPORTANCE: Viruses greatly influence succession and diversification of their hosts, yet the effects of viral infection on the ecological dynamics of natural microbial populations remain poorly understood, especially at finer scales of diversity. By manipulating the viral predation pressure by autochthonous and allochthonous viruses, we uncovered potential phage-host interaction, and their important role in structuring the prokaryote community at an ecotype level.

Comparison of k-mer-based de novo comparative metagenomic tools and approaches.

Aim: Comparative metagenomic analysis requires measuring a pairwise similarity between metagenomes in the dataset. Reference-based methods that compute a beta-diversity distance between two metagenomes are highly dependent on the quality and completeness of the reference database, and their application on less studied microbiota can be challenging. On the other hand, de-novo comparative metagenomic methods only rely on the sequence composition of metagenomes to compare datasets. While each one of these approaches has its strengths and limitations, their comparison is currently limited. Methods: We developed sets of simulated short-reads metagenomes to (1) compare k-mer-based and taxonomy-based distances and evaluate the impact of technical and biological variables on these metrics and (2) evaluate the effect of k-mer sketching and filtering. We used a real-world metagenomic dataset to provide an overview of the currently available tools for de novo metagenomic comparative analysis. Results: Using simulated metagenomes of known composition and controlled error rate, we showed that k-mer-based distance metrics were well correlated to the taxonomic distance metric for quantitative Beta-diversity metrics, but the correlation was low for presence/absence distances. The community complexity in terms of taxa richness and the sequencing depth significantly affected the quality of the k-mer-based distances, while the impact of low amounts of sequence contamination and sequencing error was limited. Finally, we benchmarked currently available de-novo comparative metagenomic tools and compared their output on two datasets of fecal metagenomes and showed that most k-mer-based tools were able to recapitulate the data structure observed using taxonomic approaches. Conclusion: This study expands our understanding of the strength and limitations of k-mer-based de novo comparative metagenomic approaches and aims to provide concrete guidelines for researchers interested in applying these approaches to their metagenomic datasets.

Microbial and Viral Genome and Proteome Nitrogen Demand Varies across Multiple Spatial Scales within a Marine Oxygen Minimum Zone.

Nutrient availability can significantly influence microbial genomic and proteomic streamlining, for example, by selecting for lower nitrogen to carbon ratios. Oligotrophic open ocean microbes have streamlined genomic nitrogen requirements relative to those of their counterparts in nutrient-rich coastal waters. However, steep gradients in nutrient availability occur at meter-level, and even micron-level, spatial scales. It is unclear whether such gradients also structure genomic and proteomic stoichiometry. Focusing on the eastern tropical North Pacific oxygen minimum zone (OMZ), we use comparative metagenomics to examine how nitrogen availability shapes microbial and viral genome properties along the vertical gradient across the OMZ and between two size fractions, distinguishing free-living microbes versus particle-associated microbes. We find a substantial increase in the nitrogen content of encoded proteins in particle-associated over free-living bacteria and archaea across nitrogen availability regimes over depth. Within each size fraction, we find that bacterial and viral genomic nitrogen tends to increase with increasing nitrate concentrations with depth. In contrast to cellular genes, the nitrogen content of virus proteins does not differ between size fractions. We identified arginine as a key amino acid in the modulation of the C:N ratios of core genes for bacteria, archaea, and viruses. Functional analysis reveals that particle-associated bacterial metagenomes are enriched for genes that are involved in arginine metabolism and organic nitrogen compound catabolism. Our results are consistent with nitrogen streamlining in both cellular and viral genomes on spatial scales of meters to microns. These effects are similar in magnitude to those previously reported across scales of thousands of kilometers. IMPORTANCE The genomes of marine microbes can be shaped by nutrient cycles, with ocean-scale gradients in nitrogen availability being known to influence microbial amino acid usage. It is unclear, however, how genomic properties are shaped by nutrient changes over much smaller spatial scales, for example, along the vertical transition into oxygen minimum zones (OMZs) or from the exterior to the interior of detrital particles. Here, we measure protein nitrogen usage by marine bacteria, archaea, and viruses by using metagenomes from the nitracline of the eastern tropical North Pacific OMZ, including both particle-associated and nonassociated biomass. Our results show higher genomic and proteomic nitrogen content in particle-associated microbes and at depths with higher nitrogen availability for cellular and viral genomes. This discovery suggests that stoichiometry influences microbial and viral evolution across multiple scales, including the micrometer to millimeter scale associated with particle-associated versus free-living lifestyles.

Comparative Metagenomics Highlight a Widespread Pathway Involved in Catabolism of Phosphonates in Marine and Terrestrial Serpentinizing Ecosystems.

Serpentinizing hydrothermal systems result from water circulating into the subsurface and interacting with mantle-derived rocks notably near mid-ocean ridges or continental ophiolites. Serpentinization and associated reactions produce alkaline fluids enriched in molecular hydrogen, methane, and small organic molecules that are assumed to feed microbial inhabitants. In this study, we explored the relationships linking serpentinization to associated microbial communities by comparative metagenomics of serpentinite-hosted systems, basalt-hosted vents, and hot springs. The shallow Prony bay hydrothermal field (PBHF) microbiome appeared to be more related to those of ophiolitic sites than to the Lost City hydrothermal field (LCHF) microbiome, probably because of the meteoric origin of its fluid, like terrestrial alkaline springs. This study emphasized the ubiquitous importance of a set of genes involved in the catabolism of phosphonates and highly enriched in all serpentinizing sites compared to other ecosystems. Because most of the serpentinizing systems are depleted in inorganic phosphate, the abundance of genes involved in the carbon-phosphorus lyase pathway suggests that the phosphonates constitute a source of phosphorus in these ecosystems. Additionally, hydrocarbons such as methane, released upon phosphonate catabolism, may contribute to the overall budget of organic molecules in serpentinizing systems. IMPORTANCE This first comparative metagenomic study of serpentinite-hosted environments provides an objective framework to understand the functioning of these peculiar ecosystems. We showed a taxonomic similarity between the PBHF and other terrestrial serpentinite-hosted ecosystems. At the same time, the LCHF microbial community was closer to deep basalt-hosted hydrothermal fields than continental ophiolites, despite the influence of serpentinization. This study revealed shared functional capabilities among serpentinite-hosted ecosystems in response to environmental stress, the metabolism of abundant dihydrogen, and the metabolism of phosphorus. Our results are consistent with the generalized view of serpentinite environments but provide deeper insight into the array of factors that may control microbial activities in these ecosystems. Moreover, we show that metabolism of phosphonate is widespread among alkaline serpentinizing systems and could play a crucial role in phosphorus and methane biogeochemical cycles. This study opens a new line of investigation of the metabolism of reduced phosphorus compounds in serpentinizing environments.

Quality assessment, safety evaluation, and microbiome analysis of night-soil compost from Lahaul valley of northwestern Himalaya.

The Himalayan dry toilet system prevalent in the northwestern Himalaya is a traditional practice of converting human faeces into a compost-like soil amendment. The current study evaluated night-soil compost (NSC) for agricultural use by assessing the compost quality, safety, and microbiome properties. Based on the fertility and clean indices determined by the fertility and heavy metal parameters, NSC was categorized as good quality compost with high fertilizing potential and moderate concentration of heavy metals. With respect to pathogens, the faecal coliform levels in the NSC were categorized as safe according to the U.S. Environmental Protection Agency standards. The bacterial community structure based on 16S rRNA gene amplicons revealed a diverse taxonomy with 14 phyla and 54 genera in NSC. Compared to publicly available 16S rRNA gene amplicon data, NSC exhibited predominant phyla (Proteobacteria, Bacteriodetes, Actinobacteria, and Firmicutes) similar to human faeces, cattle manure, food waste compost, vermicompost, and activated sludge. However, statistically, NSC was distinct at the genus level from all other groups. Additionally, pathogenic bacteria with antimicrobial resistance (AMR) genes in the NSC metagenome were determined by performing a standalone BLASTN against the PATRIC database. The analysis revealed 139 pathogenic strains with most pathogens susceptible to antibiotics, indicating lower AMR in the predicted strains. The phytotoxicity of NSC with Pisum sativum var. AS-10 seeds showed a germination index of > 85%, indicating NSC's non-harmful effects on seed germination and root growth. Overall, NSC from Himalayan dry toilets can be used as a soil amendment for food and non-food plants.

Combined read- and assembly-based metagenomics to reconstruct a Dehalococcoides mccartyi genome from PCB-contaminated sediments and evaluate functional differences among organohalide-respiring consortia in the presence of different halogenated contaminants.

Microbial communities that support respiration of halogenated organic contaminants by Dehalococcoides sp. facilitate full-scale bioremediation of chlorinated ethenes and demonstrate the potential to aid in bioremediation of halogenated aromatics like polychlorinated biphenyls (PCBs). However, it remains unclear if Dehalococcoides-containing microbial community dynamics observed in sediment-free systems quantitatively resemble that of sediment environments. To evaluate that possibility we assembled, annotated, and analyzed a Dehalococcoides sp. metagenome-assembled genome (MAG) from PCB-contaminated sediments. Phylogenetic analysis of reductive dehalogenase gene (rdhA) sequences within the MAG revealed that pcbA1 and pcbA4/5-like rdhA were absent, while several candidate PCB dehalogenase genes and potentially novel rdhA sequences were identified. Using a compositional comparative metagenomics approach, we quantified Dehalococcoides-containing microbial community structure shifts in response to halogenated organics and the presence of sediments. Functional level analysis revealed significantly greater abundances of genes associated with cobamide remodeling and horizontal gene transfer in tetrachloroethene-fed cultures as compared to halogenated aromatic-exposed consortia with or without sediments, despite little evidence of statistically significant differences in microbial community taxonomic structure. Our findings support the use of a generalizable comparative metagenomics workflow to evaluate Dehalococcoides-containing consortia in sediments and sediment-free environments to eludicate functions and microbial interactions that facilitate bioremediation of halogenated organic contaminants.

Anna Karenina and the subgingival microbiome associated with periodontitis.

BACKGROUND: Although localized aggressive periodontitis (LAP), generalized aggressive periodontitis (GAP), and chronic periodontitis (CP) are microbially driven diseases, our inability to separate disease-specific associations from those common to all three forms of periodontitis has hampered biomarker discovery. Therefore, we aimed to map the genomic content of, and the biological pathways encoded by, the microbiomes associated with these clinical phenotypes. We also estimated the extent to which these biomes are governed by the Anna Karenina principle (AKP), which states that eubiotic communities are similar between individuals while disease-associated communities are highly individualized. METHODS: We collected subgingival plaque from 25 periodontally healthy individuals and diseased sites of 59 subjects with stage 3 periodontitis and used shotgun metagenomics to characterize the aggregate of bacterial genes. RESULTS: Beta-dispersion metrics demonstrated that AKP was most evident in CP, followed by GAP and LAP. We discovered broad dysbiotic signatures spanning the three phenotypes, with over-representation of pathways that facilitate life in an oxygen-poor, protein- and heme-rich, pro-oxidant environment and enhance capacity for attachment and biofilm formation. Phenotype-specific indicators were more readily evident in LAP microbiome than GAP or CP. Genes that enable acetate-scavenging lifestyle, utilization of alternative nutritional sources, oxidative and nitrosative stress responses, and siderophore production were unique to LAP. An attenuation of virulence-related functionalities and stress response from LAP to GAP to CP was apparent. We also discovered that clinical phenotypes of disease resolved variance in the microbiome with greater clarity than the newly established grading system. Importantly, we observed that one third of the metagenome of LAP is unique to this phenotype while GAP shares significant functional and taxonomic features with both LAP and CP, suggesting either attenuation of an aggressive disease or an early-onset chronic disease. CONCLUSION: Within the limitations of a small sample size and a cross-sectional study design, the distinctive features of the microbiomes associated with LAP and CP strongly persuade us that these are discrete disease entities, while calling into question whether GAP is a separate disease, or an artifact induced by cross-sectional study designs. Further studies on phenotype-specific microbial genes are warranted to explicate their role in disease etiology. Video Abstract.

Multiple Data Analyses and Statistical Approaches for Analyzing Data from Metagenomic Studies and Clinical Trials.

Metagenomics, also known as environmental genomics, is the study of the genomic content of a sample of organisms (microbes) obtained from a common habitat. Metagenomics and other "omics" disciplines have captured the attention of researchers for several decades. The effect of microbes in our body is a relevant concern for health studies. There are plenty of studies using metagenomics which examine microorganisms that inhabit niches in the human body, sometimes causing disease, and are often correlated with multiple treatment conditions. No matter from which environment it comes, the analyses are often aimed at determining either the presence or absence of specific species of interest in a given metagenome or comparing the biological diversity and the functional activity of a wider range of microorganisms within their communities. The importance increases for comparison within different environments such as multiple patients with different conditions, multiple drugs, and multiple time points of same treatment or same patient. Thus, no matter how many hypotheses we have, we need a good understanding of genomics, bioinformatics, and statistics to work together to analyze and interpret these datasets in a meaningful way. This chapter provides an overview of different data analyses and statistical approaches (with example scenarios) to analyze metagenomics samples from different medical projects or clinical trials.

Acid mine drainage affects the diversity and metal resistance gene profile of sediment bacterial community along a river.

Acid mine drainage (AMD) is one of the most hazardous byproducts of some types of mining. However, research on how AMD affects the bacterial community structure of downstream riverine ecosystems and the distribution of metal resistance genes (MRGs) along pollution gradient is limited. Comprehensive geochemical and high-throughput next-generation sequencing analyses can be integrated to characterize spatial distributions and MRG profiles of sediment bacteria communities along the AMD-contaminated Hengshi River. We found that (1) diversities of bacterial communities significantly and gradually increased along the river with decreasing contamination, suggesting community composition reflected changes in geochemical conditions; (2) relative abundances of phyla Proteobacteria and genus Halomonas and Planococcaceae that function in metal reduction decreased along the AMD gradient; (3) low levels of sediment salinity, sulfate, aquatic lead (Pb), and cadmium (Cd) were negatively correlated with bacterial diversity despite pH was in a positive manner with diversity; and (4) arsenic (As) and copper (Cu) resistance genes corresponded to sediment concentrations of As and Cu, respectively. Altogether, our findings offer initial insight into the distribution patterns of sediment bacterial community structure, diversity and MRGs along a lotic ecosystem contaminated by AMD, and the factors that affect them.

Comparative Metagenomic Profiling of Viromes Associated with Four Common Mosquito Species in China.

Vast viruses are thought to be associated with mosquitoes. Anopheles sinensis, Armigeres subalbatus, Culex quinquefasciatus, and Culex tritaeniorhynchus are very common mosquito species in China, and whether the virome structure in each species is species-specific has not been evaluated. In this study, a total of 2222 mosquitoes were collected from the same geographic location, and RNAs were sequenced using the Illumina Miseq platform. After querying to the Refseq database, a total of 3,435,781, 2,223,509, 5,727,523, and 6,387,867 paired-end reads were classified under viral sequences from An. sinensis, Ar. subalbatus, Cx. quinquefasciatus, and Cx. tritaeniorhynchus, respectively, with the highest prevalence of virus-associated reads being observed in Cx. quinquefasciatus. The metagenomic comparison analysis showed that the virus-related reads were distributed across 26 virus families, together with an unclassified group of viruses. Anelloviridae, Circoviridae, Genomoviridae, Iridoviridae, Mesoniviridae, Microviridae, Myoviridae, Parvoviridae, Phenuiviridae, and Podoviridae were the top ten significantly different viral families among the four species. Further analysis reveals that the virome is species-specific in four mosquito samples, and several viral sequences which maybe belong to novel viruses are discovered for the first time in those mosquitoes. This investigation provides a basis for a comprehensive knowledge on the mosquito virome status in China.

Comparative Metagenomics Provides Insight Into the Ecosystem Functioning of the Shark Bay Stromatolites, Western Australia.

Stromatolites are organosedimentary build-ups that have formed as a result of the sediment trapping, binding and precipitating activities of microbes. Today, extant systems provide an ideal platform for understanding the structure, composition, and interactions between stromatolite-forming microbial communities and their respective environments. In this study, we compared the metagenomes of three prevalent stromatolite-forming microbial mat types in the Spaven Province of Hamelin Pool, Shark Bay located in Western Australia. These stromatolite-forming mat types included an intertidal pustular mat as well as a smooth and colloform mat types located in the subtidal zone. Additionally, the metagenomes of an adjacent, non-lithifying mat located in the upper intertidal zone were also sequenced for comparative purposes. Taxonomic and functional gene analyses revealed distinctive differences between the lithifying and non-lithifying mat types, which strongly correlated with water depth. Three distinct populations emerged including the upper intertidal non-lithifying mats, the intertidal pustular mats associated with unlaminated carbonate build-ups, and the subtidal colloform and smooth mat types associated with laminated structures. Functional analysis of metagenomes revealed that amongst stromatolite-forming mats there was an enrichment of photosynthesis pathways in the pustular stromatolite-forming mats. In the colloform and smooth stromatolite-forming mats, however, there was an increase in the abundance of genes associated with those heterotrophic metabolisms typically associated with carbonate mineralization, such as sulfate reduction. The comparative metagenomic analyses suggest that stromatolites of Hamelin Pool may form by two distinctive processes that are highly dependent on water depth. These results provide key insight into the potential adaptive strategies and synergistic interactions between microbes and their environments that may lead to stromatolite formation and accretion.

Precise and Parallel Pairwise Metagenomic Comparisons.

The comparison and assessment of similarity across metagenomes are still an open problem. Uncultivated samples suffer from high variability, thus making it difficult for heuristic sequence comparison methods to find precise matches in reference databases. Finer methods are required to provide higher accuracy and certainty, although these come at the expense of larger computation times. Therefore, in this work, we present our software for the highly parallel, fine-grained pairwise alignment of metagenomes. First, an analysis of the computational limitations of performing coarse-grained global alignments in parallel manner is described, and a solution is discussed and employed by our proposal. Second, we show that our development is competitive with state-of-the-art software in terms of speed and consumption of resources, while achieving more accurate results. In addition, the parallel scheme adopted is tested, depicting a performance of up to 98% efficiency while using up to 64 cores. Sequential optimizations are also tested and show a speedup of 9× over our previous proposal.

Comparative Metagenomics.

Thanks in large part to newer, better, and cheaper DNA sequencing technologies, an enormous number of metagenomic sequence datasets have been and continue to be generated, covering a huge variety of environmental niches, including several different human body sites. Comparing these metagenomes and identifying their commonalities and differences is a challenging task, due not only to the large amounts of data, but also because there are several methodological considerations that need to be taken into account to ensure an appropriate and sound comparison between datasets. In this chapter, we describe current techniques aimed at comparing metagenomes generated by 16S ribosomal RNA and shotgun DNA sequencing, emphasizing methodological issues that arise in these comparative studies. We provide a detailed case study to illustrate some of these techniques using data from the Human Microbiome Project comparing the microbial communities from ten buccal mucosa samples with ten tongue dorsum samples in terms of alpha diversity, beta diversity, and their taxonomic and functional profiles.

Comparative metagenomics reveals different hydrocarbon degradative abilities from enriched oil-drilling waste.

The oil drilling process generates large volumes of waste with inadequate treatments. Here, oil drilling waste (ODW) microbial communities demonstrate different hydrocarbon degradative abilities when exposed to distinct nutrient enrichments as revealed by comparative metagenomics. The ODW was enriched in Luria Broth (LBE) and Potato Dextrose (PDE) media to examine the structure and functional variations of microbial consortia. Two metagenomes were sequenced on Ion Torrent platform and analyzed using MG-RAST. The STAMP software was used to analyze statistically significant differences amongst different attributes of metagenomes. The microbial diversity presented in the different enrichments was distinct and heterogeneous. The metabolic pathways and enzymes were mainly related to the aerobic hydrocarbons degradation. Moreover, our results showed efficient biodegradation after 15 days of treatment for aliphatic hydrocarbons (C8-C33) and polycyclic aromatic hydrocarbons (PAHs), with a total of about 50.5% and 46.4% for LBE and 44.6% and 37.9% for PDE, respectively. The results obtained suggest the idea that the enzymatic apparatus have the potential to degrade petroleum compounds.

Corrigendum: Characterization of Metagenomes in Urban Aquatic Compartments Reveals High Prevalence of Clinically Relevant Antibiotic Resistance Genes in Wastewaters.

[This corrects the article on p. 2200 in vol. 8, PMID: 29201017.].

A concurrent subtractive assembly approach for identification of disease associated sub-metagenomes.

Comparative analysis of metagenomes can be used to detect sub-metagenomes (species or gene sets) that are associated with specific phenotypes (e.g., host status). The typical workflow is to assemble and annotate metagenomic datasets individually or as a whole, followed by statistical tests to identify differentially abundant species/genes. We previously developed subtractive assembly (SA), a de novo assembly approach for comparative metagenomics that first detects differential reads that distinguish between two groups of metagenomes and then only assembles these reads. Application of SA to type 2 diabetes (T2D) microbiomes revealed new microbial genes associated with T2D. Here we further developed a Concurrent Subtractive Assembly (CoSA) approach, which uses a Wilcoxon rank-sum (WRS) test to detect k-mers that are differentially abundant between two groups of microbiomes (by contrast, SA only checks ratios of k-mer counts in one pooled sample versus the other). It then uses identified differential k-mers to extract reads that are likely sequenced from the sub-metagenome with consistent abundance differences between the groups of microbiomes. Further, CoSA attempts to reduce the redundancy of reads (from abundant common species) by excluding reads containing abundant k-mers. Using simulated microbiome datasets and T2D datasets, we show that CoSA achieves strikingly better performance in detecting consistent changes than SA does, and it enables the detection and assembly of genomes and genes with minor abundance difference. A SVM classifier built upon the microbial genes detected by CoSA from the T2D datasets can accurately discriminates patients from healthy controls, with an AUC of 0.94 (10-fold cross-validation), and therefore these differential genes (207 genes) may serve as potential microbial marker genes for T2D.

Comparative Metagenomics of Cellulose- and Poplar Hydrolysate-Degrading Microcosms from Gut Microflora of the Canadian Beaver (Castor canadensis) and North American Moose (Alces americanus) after Long-Term Enrichment.

To identify carbohydrate-active enzymes (CAZymes) that might be particularly relevant for wood fiber processing, we performed a comparative metagenomic analysis of digestive systems from Canadian beaver (Castor canadensis) and North American moose (Alces americanus) following 3 years of enrichment on either microcrystalline cellulose or poplar hydrolysate. In total, 9,386 genes encoding CAZymes and carbohydrate-binding modules (CBMs) were identified, with up to half predicted to originate from Firmicutes, Bacteroidetes, Chloroflexi, and Proteobacteria phyla, and up to 17% from unknown phyla. Both PCA and hierarchical cluster analysis distinguished the annotated glycoside hydrolase (GH) distributions identified herein, from those previously reported for grass-feeding mammals and herbivorous foragers. The CAZyme profile of moose rumen enrichments also differed from a recently reported moose rumen metagenome, most notably by the absence of GH13-appended dockerins. Consistent with substrate-driven convergence, CAZyme profiles from both poplar hydrolysate-fed cultures differed from cellulose-fed cultures, most notably by increased numbers of unique sequences belonging to families GH3, GH5, GH43, GH53, and CE1. Moreover, pairwise comparisons of moose rumen enrichments further revealed higher counts of GH127 and CE15 families in cultures fed with poplar hydrolysate. To expand our scope to lesser known carbohydrate-active proteins, we identified and compared multi-domain proteins comprising both a CBM and domain of unknown function (DUF) as well as proteins with unknown function within the 416 predicted polysaccharide utilization loci (PULs). Interestingly, DUF362, identified in iron-sulfur proteins, was consistently appended to CBM9; on the other hand, proteins with unknown function from PULs shared little identity unless from identical PULs. Overall, this study sheds new light on the lignocellulose degrading capabilities of microbes originating from digestive systems of mammals known for fiber-rich diets, and highlights the value of enrichment to select new CAZymes from metagenome sequences for future biochemical characterization.