An Improved Methodology to Overcome Key Issues in Human Fecal Metagenomic DNA Extraction

Microbes are ubiquitously distributed in nature, and recent culture-independent studies have highlighted the significance of gut microbiota in human health and disease. Fecal DNA is the primary source for the majority of human gut microbiome studies. However, further improvement is needed to obtain fecal metagenomic DNA with sufficient amount and good quality but low host genomic DNA contamination. In the current study, we demonstrate a quick, robust, unbiased,and cost-effective method for the isolation of high molecular weight(23 kb) metagenomic DNA(260/280 ratio 1.8) with a good yield(55.8 ± 3.8 ng/mg of feces). We also confirm that there is very low human genomic DNA contamination(eubacterial: human genomic DNA marker genes = 2~(27.9):1) in the human feces. The newly-developed method robustly performs for fresh as well as stored fecal samples as demonstrated by 16 S r RNA gene sequencing using 454 FLX+.Moreover, 16 S r RNA gene analysis indicated that compared to other DNA extraction methods tested, the fecal metagenomic DNA isolated with current methodology retains species richnessand does not show microbial diversity biases, which is further confirmed by q PCR with a known quantity of spike-in genomes. Overall, our data highlight a protocol with a balance between quality,amount, user-friendliness, and cost effectiveness for its suitability toward usage for cultureindependent analysis of the human gut microbiome, which provides a robust solution to overcome key issues associated with fecal metagenomic DNA isolation in human gut microbiome studies.     

Turkey fecal microbial community structure and functional gene diversity revealed by 16S rRNA gene and metagenomic sequences

The primary goal of this study was to better understand the microbial composition and functional genetic diversity associated with turkey fecal communities. To achieve this, 16S rRNA gene and metagenomic clone libraries were sequenced from turkey fecal samples. The analysis of 382 16S rRNA gene sequences showed that the most abundant bacteria were closely related to Lactobacillales (47%), Bacillales (31%), and Clostridiales (11%). Actinomycetales, Enterobacteriales, and Bacteroidales sequences were also identified, but represented a smaller part of the community. The analysis of 379 metagenomic sequences showed that most clones were similar to bacterial protein sequences (58%). Bacteriophage (10%) and avian viruses (3%) sequences were also represented. Of all metagenomic clones potentially encoding for bacterial proteins, most were similar to low G+C Gram-positive bacterial proteins, particularly from Lactobacillales (50%), Bacillales (11%), and Clostridiales (8%). Bioinformatic analyses suggested the presence of genes encoding for membrane proteins, lipoproteins, hydrolases, and functional genes associated with the metabolism of nitrogen and sulfur containing compounds. The results from this study further confirmed the predominance of Firmicutes in the avian gut and highlight the value of coupling 16S rRNA gene and metagenomic sequencing data analysis to study the microbial composition of avian fecal microbial communities.     

肠道微生物培养的研究进展及应用

肠道中栖居着组成复杂、功能多样的微生物群,这些微生物群在宿主免疫、营养吸收、代谢调节等方面发挥着重要作用。随着测序技术的快速发展,肠道微生物研究通过16S rRNA基因测序和宏基因组测序产生了大量的数据,其中许多未组装的序列成为微生物“暗物质”。近年来,不少研究利用多种不同微生物分离培养方法,结合高通量鉴定技术,从人、小鼠、猪肠道中分离了大量的微生物,丰富了菌株资源,为解析微生物“暗物质”以及后续肠道微生物功能和应用研究提供了基础和保障。尽管微生物的可培养性受到多种因素的影响,大部分微生物尚处于“未培养”的状态,但无论是病因研究还是生理和遗传特征的解析都离不开微生物实体资源的获取。肠道微生物的分离培养对微生物研究从关联分析向菌群功能验证、因果机制解析和功能菌株开发的深入研究具有重要意义。本文旨在探讨和综述影响微生物可培养性的因素,总结回顾肠道微生物的培养方法并阐述肠道微生物培养研究的进展,以期为肠道微生物培养研究提供新的视角。     

Metagenomic analysis reveals a functional signature for biomass degradation by cecal microbiota in the leaf-eating flying squirrel (Petaurista alborufus lena)

ABSTRACT: BACKGROUND: Animals co-evolve with their gut microbiota; the latter can perform complex metabolic reactions that cannot be done independently by the host. Although the importance of gut microbiota has been well demonstrated, there is a paucity of research regarding its role in foliage-foraging mammals with a specialized digestive system. RESULTS: In this study, a 16S rRNA gene survey and metagenomic sequencing were used to characterize genetic diversity and functional capability of cecal microbiota of the folivorous flying squirrel (Petaurista alborufus lena). Phylogenetic compositions of the cecal microbiota derived from 3 flying squirrels were dominated by Firmicutes. Based on end-sequences of fosmid clones from 1 flying squirrel, we inferred that microbial metabolism greatly contributed to intestinal functions, including degradation of carbohydrates, metabolism of proteins, and synthesis of vitamins. Moreover, 33 polysaccharide-degrading enzymes and 2 large genomic fragments containing a series of carbohydrate-associated genes were identified. CONCLUSIONS: Cecal microbiota of the leaf-eating flying squirrel have great metabolic potential for converting diverse plant materials into absorbable nutrients. The present study should serve as the basis for future investigations, using metagenomic approaches to elucidate the intricate mechanisms and interactions between host and gut microbiota of the flying squirrel digestive system, as well as other mammals with similar adaptations.     

The gut microbiome and microbial metabolites in acute myocardial infarction

Emerging evidence has highlighted the role of gut microbiome in human health. However, the integrative role of gut microbiome and microbial metabolites in acute myocardial infarction (AMI) remains unclear. The current study profiles the microbial community through 16S rRNA gene sequencing and shotgun metagenomic sequencing and measures fecal short-chain fatty acids and circulating choline pathway metabolites among 117 new-onset AMI cases and 78 controls. Significant microbial alternations are observed in AMI patients compared with controls (P = 0.001). The abundances of nine species (e.g., Streptococcus salivarius and Klebsiella pneumoniae) are positively associated, and one species (Roseburia hominis) is inversely associated with AMI status and severity. A gut microbial score at disease onset is associated with the risk of major adverse cardiovascular events in 3.2 years (hazard ratio [95% CI]: 2.01 [1.04–4.24]) in AMI patients. The molar proportions of fecal acetate and butyrate are higher, and the circulating levels of choline and carnitine are lower in AMI patients than in controls. In addition, disease classifiers show that AMI cases and controls have a more distinct pattern in taxonomical composition than in pathways or metabolites. Our findings suggest that microbial composition and functional potentials are associated with AMI status and severity.     

Differential Effects of Antibiotic Therapy on the Structure and Function of Human Gut Microbiota

The human intestinal microbiota performs many essential functions for the host. Antimicrobial agents, such as antibiotics (AB), are also known to disturb microbial community equilibrium, thereby having an impact on human physiology. While an increasing number of studies investigate the effects of AB usage on changes in human gut microbiota biodiversity, its functional effects are still poorly understood. We performed a follow-up study to explore the effect of ABs with different modes of action on human gut microbiota composition and function. Four individuals were treated with different antibiotics and samples were taken before, during and after the AB course for all of them. Changes in the total and in the active (growing) microbiota as well as the functional changes were addressed by 16S rRNA gene and metagenomic 454-based pyrosequencing approaches. We have found that the class of antibiotic, particularly its antimicrobial effect and mode of action, played an important role in modulating the gut microbiota composition and function. Furthermore, analysis of the resistome suggested that oscillatory dynamics are not only due to antibiotic-target resistance, but also to fluctuations in the surviving bacterial community. Our results indicated that the effect of AB on the human gut microbiota relates to the interaction of several factors, principally the properties of the antimicrobial agent, and the structure, functions and resistance genes of the microbial community.     

Stochastic changes over time and not founder effects drive cage effects in microbial community assembly in a mouse model

Maternal transmission and cage effects are powerful confounding factors in microbiome studies. To assess the consequences of cage microenvironment on the mouse gut microbiome, two groups of germ-free (GF) wild-type (WT) mice, one gavaged with a microbiota harvested from adult WT mice and another allowed to acquire the microbiome from the cage microenvironment, were monitored using Illumina 16S rRNA sequencing over a period of 8 weeks. Our results revealed that cage effects in WT mice moved from GF to specific pathogen free (SPF) conditions take several weeks to develop and are not eliminated by the initial gavage treatment. Initial gavage influenced, but did not eliminate a successional pattern in which Proteobacteria became less abundant over time. An analysis in which 16S rRNA sequences are mapped to the closest sequenced whole genome suggests that the functional potential of microbial genomes changes significantly over time shifting from an emphasis on pathogenesis and motility early in community assembly to metabolic processes at later time points. Functionally, mice allowed to naturally acquire a microbial community from their cage, but not mice gavaged with a common biome, exhibit a cage effect in Dextran Sulfate Sodium-induced inflammation. Our results argue that while there are long-term effects of the founding community, these effects are mitigated by cage microenvironment and successional community assembly over time, which must both be explicitly considered in the interpretation of microbiome mouse experiments.     

Gene-targeted metagenomic analysis of glucan-branching enzyme gene profiles among human and animal fecal microbiota

Glycoside hydrolases (GHs), the enzymes that breakdown complex carbohydrates, are a highly diversified class of key enzymes associated with the gut microbiota and its metabolic functions. To learn more about the diversity of GHs and their potential role in a variety of gut microbiomes, we used a combination of 16S, metagenomic and targeted amplicon sequencing data to study one of these enzyme families in detail. Specifically, we employed a functional gene-targeted metagenomic approach to the 1-4-α-glucan-branching enzyme (gBE) gene in the gut microbiomes of four host species (human, chicken, cow and pig). The characteristics of operational taxonomic units (OTUs) and operational glucan-branching units (OGBUs) were distinctive in each of hosts. Human and pig were most similar in OTUs profiles while maintaining distinct OGBU profiles. Interestingly, the phylogenetic profiles identified from 16S and gBE gene sequences differed, suggesting the presence of different gBE genes in the same OTU across different vertebrate hosts. Our data suggest that gene-targeted metagenomic analysis is useful for an in-depth understanding of the diversity of a particular gene of interest. Specific carbohydrate metabolic genes appear to be carried by distinct OTUs in different individual hosts and among different vertebrate species'' microbiomes, the characteristics of which differ according to host genetic background and/or diet.     

Impact of training sets on classification of high-throughput bacterial 16s rRNA gene surveys

Taxonomic classification of the thousands–millions of 16S rRNA gene sequences generated in microbiome studies is often achieved using a naïve Bayesian classifier (for example, the Ribosomal Database Project II (RDP) classifier), due to favorable trade-offs among automation, speed and accuracy. The resulting classification depends on the reference sequences and taxonomic hierarchy used to train the model; although the influence of primer sets and classification algorithms have been explored in detail, the influence of training set has not been characterized. We compared classification results obtained using three different publicly available databases as training sets, applied to five different bacterial 16S rRNA gene pyrosequencing data sets generated (from human body, mouse gut, python gut, soil and anaerobic digester samples). We observed numerous advantages to using the largest, most diverse training set available, that we constructed from the Greengenes (GG) bacterial/archaeal 16S rRNA gene sequence database and the latest GG taxonomy. Phylogenetic clusters of previously unclassified experimental sequences were identified with notable improvements (for example, 50% reduction in reads unclassified at the phylum level in mouse gut, soil and anaerobic digester samples), especially for phylotypes belonging to specific phyla (Tenericutes, Chloroflexi, Synergistetes and Candidate phyla TM6, TM7). Trimming the reference sequences to the primer region resulted in systematic improvements in classification depth, and greatest gains at higher confidence thresholds. Phylotypes unclassified at the genus level represented a greater proportion of the total community variation than classified operational taxonomic units in mouse gut and anaerobic digester samples, underscoring the need for greater diversity in existing reference databases.     

Shallow shotgun sequencing of the microbiome recapitulates 16S amplicon results and provides functional insights

Prevailing 16S rRNA gene-amplicon methods for characterizing the bacterial microbiome of wildlife are economical, but result in coarse taxonomic classifications, are subject to primer and 16S copy number biases, and do not allow for direct estimation of microbiome functional potential. While deep shotgun metagenomic sequencing can overcome many of these limitations, it is prohibitively expensive for large sample sets. Here we evaluated the ability of shallow shotgun metagenomic sequencing to characterize taxonomic and functional patterns in the faecal microbiome of a model population of feral horses (Sable Island, Canada). Since 2007, this unmanaged population has been the subject of an individual-based, long-term ecological study. Using deep shotgun metagenomic sequencing, we determined the sequencing depth required to accurately characterize the horse microbiome. In comparing conventional vs. high-throughput shotgun metagenomic library preparation techniques, we validate the use of more cost-effective laboratory methods. Finally, we characterize similarities between 16S amplicon and shallow shotgun characterization of the microbiome, and demonstrate that the latter recapitulates biological patterns first described in a published amplicon data set. Unlike for amplicon data, we further demonstrate how shallow shotgun metagenomic data provide useful insights regarding microbiome functional potential which support previously hypothesized diet effects in this study system.     

Characterization of the fecal bacteria communities of forage-fed horses by pyrosequencing of 16S rRNA V4 gene amplicons

The diversity of the equine fecal bacterial community was evaluated using pyrosequencing of 16S rRNA gene amplicons. Fecal samples were obtained from horses fed cool-season grass hay. Fecal bacteria were characterized by amplifying the V4 region of bacterial 16S rRNA gene. Of 5898 mean unique sequences, a mean of 1510 operational taxonomic units were identified in the four fecal samples. Equine fecal bacterial richness was higher than that reported in humans, but lower than that reported in either cattle feces or soil. Bacterial classified sequences were assigned to 16 phyla, of which 10 were present in all samples. The largest number of reads belonged to Firmicutes (43.7% of total bacterial sequences), Verrucomicrobia (4.1%), Proteobacteria (3.8%), and Bacteroidetes (3.7%). The less abundant Actinobacteria, Cyanobacteria, and TM7 phyla presented here have not been previously described in the gut contents or feces of horses. Unclassified sequences represented 38.1% of total bacterial sequences; therefore, the equine fecal microbiome diversity is likely greater than that described. This is the first study to characterize the fecal bacterial community in horses by the use of 16S rRNA gene amplicon pyrosequencing, expanding our knowledge of the fecal microbiota of forage-fed horses.     

Metabolic reconstruction for metagenomic data and its application to the human microbiome

Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities' metagenomes provides information complementary to organismal abundances from taxonomic markers, but the resulting data typically comprise short reads from hundreds of different organisms and are at best challenging to assemble comparably to single-organism genomes. Here, we describe an alternative approach to infer the functional and metabolic potential of a microbial community metagenome. We determined the gene families and pathways present or absent within a community, as well as their relative abundances, directly from short sequence reads. We validated this methodology using a collection of synthetic metagenomes, recovering the presence and abundance both of large pathways and of small functional modules with high accuracy. We subsequently applied this method, HUMAnN, to the microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals as part of the Human Microbiome Project (HMP). This provided a means to compare functional diversity and organismal ecology in the human microbiome, and we determined a core of 24 ubiquitously present modules. Core pathways were often implemented by different enzyme families within different body sites, and 168 functional modules and 196 metabolic pathways varied in metagenomic abundance specifically to one or more niches within the microbiome. These included glycosaminoglycan degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. An implementation of our methodology is available at http://huttenhower.sph.harvard.edu/humann. This provides a means to accurately and efficiently characterize microbial metabolic pathways and functional modules directly from high-throughput sequencing reads, enabling the determination of community roles in the HMP cohort and in future metagenomic studies.     

Gut microbiota-mediated xanthine metabolism is associated with resistance to high-fat diet-induced obesity

Resistance to high-fat diet-induced obesity (DIR) has been observed in mice fed a high-fat diet and may provide a potential approach for anti-obesity drug discovery. However, the metabolic status, gut microbiota composition, and its associations with DIR are still unclear. Here, ultraperformance liquid chromatography-tandem mass spectrometry-based urinary metabolomic and 16S rRNA gene sequencing-based fecal microbiome analyses were conducted to investigate the relationship between metabolic profile, gut microbiota composition, and body weight of C57BL/6J mice on chow or a high-fat diet for 8 weeks. PICRUSt analysis of 16S rRNA gene sequences predicted the functional metagenomes of gut bacteria. The results demonstrated that feeding a high-fat diet increased body weight and fasting blood glucose of high-fat diet-induced obesity (DIO) mice and altered the host-microbial co-metabolism and gut microbiota composition. In DIR mice, high-fat diet did not increase body weight while fasting blood glucose was increased significantly compared to chow fed mice. In DIR mice, the urinary metabolic pattern was shifted to a distinct direction compared to DIO mice, which was mainly contributed by xanthine. Moreover, high-fat diet caused gut microbiota dysbiosis in both DIO and DIR mice, but in DIR mice, the abundance of Bifidobacteriaceae, Roseburia, and Escherichia was not affected compared to mice fed a chow diet, which played an important role in the pathway coverage of FormylTHF biosynthesis I. Meanwhile, xanthine and pathway coverage of FormylTHF biosynthesis I showed significant positive correlations with mouse body weight. These findings suggest that gut microbiota-mediated xanthine metabolism correlates with resistance to high-fat DIO.     

Novel bacterial taxa in the human microbiome

The human gut harbors thousands of bacterial taxa. A profusion of metagenomic sequence data has been generated from human stool samples in the last few years, raising the question of whether more taxa remain to be identified. We assessed metagenomic data generated by the Human Microbiome Project Consortium to determine if novel taxa remain to be discovered in stool samples from healthy individuals. To do this, we established a rigorous bioinformatics pipeline that uses sequence data from multiple platforms (Illumina GAIIX and Roche 454 FLX Titanium) and approaches (whole-genome shotgun and 16S rDNA amplicons) to validate novel taxa. We applied this approach to stool samples from 11 healthy subjects collected as part of the Human Microbiome Project. We discovered several low-abundance, novel bacterial taxa, which span three major phyla in the bacterial tree of life. We determined that these taxa are present in a larger set of Human Microbiome Project subjects and are found in two sampling sites (Houston and St. Louis). We show that the number of false-positive novel sequences (primarily chimeric sequences) would have been two orders of magnitude higher than the true number of novel taxa without validation using multiple datasets, highlighting the importance of establishing rigorous standards for the identification of novel taxa in metagenomic data. The majority of novel sequences are related to the recently discovered genus Barnesiella, further encouraging efforts to characterize the members of this genus and to study their roles in the microbial communities of the gut. A better understanding of the effects of less-abundant bacteria is important as we seek to understand the complex gut microbiome in healthy individuals and link changes in the microbiome to disease.     

Adapting functional genomic tools to metagenomic analyses: investigating the role of gut bacteria in relation to obesity

With the expanding availability of sequencing technologies, research previously centered on the human genome can now afford to include the study of humans' internal ecosystem (human microbiome). Given the scale of the data involved in this metagenomic research (two orders of magnitude larger than the human genome) and their importance in relation to human health, it is crucial to guarantee (along with the appropriate data collection and taxonomy) proper tools for data analysis. We propose to adapt the approaches defined for the analysis of gene-expression microarray in order to infer information in metagenomics. In particular, we applied SAM, a broadly used tool for the identification of differentially expressed genes among different samples classes, to a reported dataset on a research model with mice of two genotypes (a high density lipoprotein knockout mouse and its wild-type counterpart). The data contain two different diets (high-fat or normal-chow) to ensure the onset of obesity, prodrome of metabolic syndromes (MS). By using 16S rRNA gene as a genomic diversity marker, we illustrate how this approach can identify bacterial populations differentially enriched among different genetic and dietary conditions of the host. This approach faithfully reproduces highly-relevant results from phylogenetic and standard statistical analyses, used to explain the role of the gut microbiome in relation to obesity. This represents a promising proof-of-principle for using functional genomic approaches in the fast growing area of metagenomics, and warrants the availability of a large body of thoroughly tested and theoretically sound methodologies to this exciting new field.     

The gut microbiome composition and degradation enzymes activity of black Amur bream (Megalobrama terminalis) in response to breeding migratory behavior

Black Amur bream (Megalobrama terminalis), a dominant species, resides in the Pearl River basin, known for its high plasticity in digestive ability. During spawning season, M. terminalis individuals with large body size and high fertility undergo a spawn migratory phase, while other smaller individuals prefer to settlement over migration. It is well known that gut microbial community often underpins the metabolic capability and regulates a wide variety of important functions in fish. However, little was known about how the gut microbiomes affect fish breeding migration. To investigate the variations in the gut microbiome of M. terminalis during the migration, we used high‐throughput 16S rRNA gene sequencing to reveal the distinct composition and diversity of the whole gut microbiome of migrated and nonmigrated population during period of peak reproduction, respectively. Our results indicated that nonmigrated population in estuary had a higher alpha diversity than that of migrated population in main stem. Additionally, an obvious abundant taxa shift between the gut microbiota community of nonmigrated and migrated M. terminalis was also observed. Change of dominant gut taxa from nonmigrated to migrated population was thought to be closely related to their degradation enzymes. Our results suggested that amino acid metabolism and lipid metabolism in migrated population were higher than that in nonmigrated population, providing a line of evidence for that M. terminalis change from partial herbivorous to partial carnivorous diet during breeding migration. We further concluded that, in order to digest foods of higher nutrition to supply energy to spawning migration, M. terminalis regulate activities of the gut microbiome and degradation enzymes, considered to be a key physiological strategy for reproduction.     

Metabonomic and microbiological analysis of the dynamic effect of vancomycin-induced gut microbiota modification in the mouse

The effects of the antibiotic vancomycin (2 x 100 mg/kg/day) on the gut microbiota of female mice (outbred NMRI strain) were studied, in order to assess the relative contribution of the gut microbiome to host metabolism. The host's metabolic phenotype was characterized using (1)H NMR spectroscopy of urine and fecal extract samples. Time-course changes in the gut microbiotal community after administration of vancomycin were monitored using 16S rRNA gene PCR and denaturing gradient gel electrophoresis (PCR-DGGE) analysis and showed a strong effect on several species, mostly within the Firmicutes. Vancomycin treatment was associated with fecal excretion of uracil, amino acids and short chain fatty acids (SCFAs), highlighting the contribution of the gut microbiota to the production and metabolism of these dietary compounds. Clear differences in gut microbial communities between control and antibiotic-treated mice were observed in the current study. Reduced urinary excretion of gut microbial co-metabolites phenylacetylglycine and hippurate was also observed. Regression of urinary hippurate and phenylacetylglycine concentrations against the fecal metabolite profile showed a strong association between these urinary metabolites and a wide range of fecal metabolites, including amino acids and SCFAs. Fecal choline was inversely correlated with urinary hippurate. Metabolic profiling, coupled with the metagenomic study of this antibiotic model, illustrates the close inter-relationship between the host and microbial "metabotypes", and will provide a basis for further experiments probing the understanding of the microbial-mammalian metabolic axis.     

Comparative (meta)genomic analysis and ecological profiling of human gut-specific bacteriophage φB124-14

Bacteriophage associated with the human gut microbiome are likely to have an important impact on community structure and function, and provide a wealth of biotechnological opportunities. Despite this, knowledge of the ecology and composition of bacteriophage in the gut bacterial community remains poor, with few well characterized gut-associated phage genomes currently available. Here we describe the identification and in-depth (meta)genomic, proteomic, and ecological analysis of a human gut-specific bacteriophage (designated φB124-14). In doing so we illuminate a fraction of the biological dark matter extant in this ecosystem and its surrounding eco-genomic landscape, identifying a novel and uncharted bacteriophage gene-space in this community. φB124-14 infects only a subset of closely related gut-associated Bacteroides fragilis strains, and the circular genome encodes functions previously found to be rare in viral genomes and human gut viral metagenome sequences, including those which potentially confer advantages upon phage and/or host bacteria. Comparative genomic analyses revealed φB124-14 is most closely related to φB40-8, the only other publically available Bacteroides sp. phage genome, whilst comparative metagenomic analysis of both phage failed to identify any homologous sequences in 136 non-human gut metagenomic datasets searched, supporting the human gut-specific nature of this phage. Moreover, a potential geographic variation in the carriage of these and related phage was revealed by analysis of their distribution and prevalence within 151 human gut microbiomes and viromes from Europe, America and Japan. Finally, ecological profiling of φB124-14 and φB40-8, using both gene-centric alignment-driven phylogenetic analyses, as well as alignment-free gene-independent approaches was undertaken. This not only verified the human gut-specific nature of both phage, but also indicated that these phage populate a distinct and unexplored ecological landscape within the human gut microbiome.