Metagenomic microbial community profiling using unique clade-specific marker genes

Metagenomic shotgun sequencing data can identify microbes populating a microbial community and their proportions, but existing taxonomic profiling methods are inefficient for increasingly large data sets. We present an approach that uses clade-specific marker genes to unambiguously assign reads to microbial clades more accurately and >50× faster than current approaches. We validated our metagenomic phylogenetic analysis tool, MetaPhlAn, on terabases of short reads and provide the largest metagenomic profiling to date of the human gut. It can be accessed at http://huttenhower.sph.harvard.edu/metaphlan/.     

Amplification of uncultured single-stranded DNA viruses from rice paddy soil

Viruses are known to be the most numerous biological entities in soil; however, little is known about their diversity in this environment. In order to explore the genetic diversity of soil viruses, we isolated viruses by centrifugation and sequential filtration before performing a metagenomic investigation. We adopted multiple-displacement amplification (MDA), an isothermal whole-genome amplification method with phi29 polymerase and random hexamers, to amplify viral DNA and construct clone libraries for metagenome sequencing. By the MDA method, the diversity of both single-stranded DNA (ssDNA) viruses and double-stranded DNA viruses could be investigated at the same time. On the contrary, by eliminating the denaturing step in the MDA reaction, only ssDNA viral diversity could be explored selectively. Irrespective of the denaturing step, more than 60% of the soil metagenome sequences did not show significant hits (E-value criterion, 0.001) with previously reported viral sequences. Those hits that were considered to be significant were also distantly related to known ssDNA viruses (average amino acid similarity, approximately 34%). Phylogenetic analysis showed that replication-related proteins (which were the most frequently detected proteins) related to those of ssDNA viruses obtained from the metagenomic sequences were diverse and novel. Putative circular genome components of ssDNA viruses that are unrelated to known viruses were assembled from the metagenomic sequences. In conclusion, ssDNA viral diversity in soil is more complex than previously thought. Soil is therefore a rich pool of previously unknown ssDNA viruses.     

Environmental Whole-Genome Amplification To Access Microbial Populations in Contaminated Sediments

Low-biomass samples from nitrate and heavy metal contaminated soils yield DNA amounts that have limited use for direct, native analysis and screening. Multiple displacement amplification (MDA) using 29 DNA polymerase was used to amplify whole genomes from environmental, contaminated, subsurface sediments. By first amplifying the genomic DNA (gDNA), biodiversity analysis and gDNA library construction of microbes found in contaminated soils were made possible. The MDA method was validated by analyzing amplified genome coverage from approximately five Escherichia coli cells, resulting in 99.2% genome coverage. The method was further validated by confirming overall representative species coverage and also an amplification bias when amplifying from a mix of eight known bacterial strains. We extracted DNA from samples with extremely low cell densities from a U.S. Department of Energy contaminated site. After amplification, small-subunit rRNA analysis revealed relatively even distribution of species across several major phyla. Clone libraries were constructed from the amplified gDNA, and a small subset of clones was used for shotgun sequencing. BLAST analysis of the library clone sequences showed that 64.9% of the sequences had significant similarities to known proteins, and “clusters of orthologous groups” (COG) analysis revealed that more than half of the sequences from each library contained sequence similarity to known proteins. The libraries can be readily screened for native genes or any target of interest. Whole-genome amplification of metagenomic DNA from very minute microbial sources, while introducing an amplification bias, will allow access to genomic information that was not previously accessible.     

Genome coverage and sequence fidelity of phi29 polymerase-based multiple strand displacement whole genome amplification

Major efforts are underway to systematically define the somatic and germline genetic variations causally associated with disease. Genome-wide genetic analysis of actual clinical samples is, however, limited by the paucity of genomic DNA available. Here we have tested the fidelity and genome representation of phi29 polymerase-based genome amplification (phi29MDA) using direct sequencing and high density oligonucleotide arrays probing >10,000 SNP alleles. Genome representation was comprehensive and estimated to be 99.82% complete, although six regions encompassing a maximum of 5.62 Mb failed to amplify. There was no degradation in the accuracy of SNP genotyping and, in direct sequencing experiments sampling 500,000 bp, the estimated error rate (9.5 x 10(-6)) was the same as in paired unamplified samples. The detection of cancer-associated loss of heterozygosity and copy number changes, including homozygous deletion and gene amplification, were similarly robust. These results suggest that phi29MDA yields high fidelity, near-complete genome representation suitable for high resolution genetic analysis.     

Environmental whole-genome amplification to access microbial populations in contaminated sediments

Low-biomass samples from nitrate and heavy metal contaminated soils yield DNA amounts that have limited use for direct, native analysis and screening. Multiple displacement amplification (MDA) using phi29 DNA polymerase was used to amplify whole genomes from environmental, contaminated, subsurface sediments. By first amplifying the genomic DNA (gDNA), biodiversity analysis and gDNA library construction of microbes found in contaminated soils were made possible. The MDA method was validated by analyzing amplified genome coverage from approximately five Escherichia coli cells, resulting in 99.2% genome coverage. The method was further validated by confirming overall representative species coverage and also an amplification bias when amplifying from a mix of eight known bacterial strains. We extracted DNA from samples with extremely low cell densities from a U.S. Department of Energy contaminated site. After amplification, small-subunit rRNA analysis revealed relatively even distribution of species across several major phyla. Clone libraries were constructed from the amplified gDNA, and a small subset of clones was used for shotgun sequencing. BLAST analysis of the library clone sequences showed that 64.9% of the sequences had significant similarities to known proteins, and "clusters of orthologous groups" (COG) analysis revealed that more than half of the sequences from each library contained sequence similarity to known proteins. The libraries can be readily screened for native genes or any target of interest. Whole-genome amplification of metagenomic DNA from very minute microbial sources, while introducing an amplification bias, will allow access to genomic information that was not previously accessible. The reported SSU rRNA sequences and library clone end sequences are listed with their respective GenBank accession numbers, DQ 404590 to DQ 404652, DQ 404654 to DQ 404938, and DX 385314 to DX 389173.     

Single-cell genomic sequencing using Multiple Displacement Amplification

Single microbial cells can now be sequenced using DNA amplified by the Multiple Displacement Amplification (MDA) reaction. The few femtograms of DNA in a bacterium are amplified into micrograms of high molecular weight DNA suitable for DNA library construction and Sanger sequencing. The MDA-generated DNA also performs well when used directly as template for pyrosequencing by the 454 Life Sciences method. While MDA from single cells loses some of the genomic sequence, this approach will greatly accelerate the pace of sequencing from uncultured microbes. The genetically linked sequences from single cells are also a powerful tool to be used in guiding genomic assembly of shotgun sequences of multiple organisms from environmental DNA extracts (metagenomic sequences).     

SIP metagenomics identifies uncultivated Methylophilaceae as dimethylsulphide degrading bacteria in soil and lake sediment

Dimethylsulphide (DMS) has an important role in the global sulphur cycle and atmospheric chemistry. Microorganisms using DMS as sole carbon, sulphur or energy source, contribute to the cycling of DMS in a wide variety of ecosystems. The diversity of microbial populations degrading DMS in terrestrial environments is poorly understood. Based on cultivation studies, a wide range of bacteria isolated from terrestrial ecosystems were shown to be able to degrade DMS, yet it remains unknown whether any of these have important roles in situ. In this study, we identified bacteria using DMS as a carbon and energy source in terrestrial environments, an agricultural soil and a lake sediment, by DNA stable isotope probing (SIP). Microbial communities involved in DMS degradation were analysed by denaturing gradient gel electrophoresis, high-throughput sequencing of SIP gradient fractions and metagenomic sequencing of phi29-amplified community DNA. Labelling patterns of time course SIP experiments identified members of the Methylophilaceae family, not previously implicated in DMS degradation, as dominant DMS-degrading populations in soil and lake sediment. Thiobacillus spp. were also detected in ¹³C-DNA from SIP incubations. Metagenomic sequencing also suggested involvement of Methylophilaceae in DMS degradation and further indicated shifts in the functional profile of the DMS-assimilating communities in line with methylotrophy and oxidation of inorganic sulphur compounds. Overall, these data suggest that unlike in the marine environment where gammaproteobacterial populations were identified by SIP as DMS degraders, betaproteobacterial Methylophilaceae may have a key role in DMS cycling in terrestrial environments.     

A Model-Based Approach for Species Abundance Quantification Based on Shotgun Metagenomic Data

The human microbiome, which includes the collective microbes residing in or on the human body, has a profound influence on the human health. DNA sequencing technology has made the large-scale human microbiome studies possible by using shotgun metagenomic sequencing. One important aspect of data analysis of such metagenomic data is to quantify the bacterial abundances based on the metagenomic sequencing data. Existing methods almost always quantify such abundances one sample at a time, which ignore certain systematic differences in read coverage along the genomes due to GC contents, copy number variation and the bacterial origin of replication. In order to account for such differences in read counts, we propose a multi-sample Poisson model to quantify microbial abundances based on read counts that are assigned to species-specific taxonomic markers. Our model takes into account the marker-specific effects when normalizing the sequencing count data in order to obtain more accurate quantification of the species abundances. Compared to currently available methods on simulated data and real data sets, our method has demonstrated an improved accuracy in bacterial abundance quantification, which leads to more biologically interesting results from downstream data analysis.     

Metagenomic Data Utilization and Analysis (MEDUSA) and Construction of a Global Gut Microbial Gene Catalogue

Metagenomic sequencing has contributed important new knowledge about the microbes that live in a symbiotic relationship with humans. With modern sequencing technology it is possible to generate large numbers of sequencing reads from a metagenome but analysis of the data is challenging. Here we present the bioinformatics pipeline MEDUSA that facilitates analysis of metagenomic reads at the gene and taxonomic level. We also constructed a global human gut microbial gene catalogue by combining data from 4 studies spanning 3 continents. Using MEDUSA we mapped 782 gut metagenomes to the global gene catalogue and a catalogue of sequenced microbial species. Hereby we find that all studies share about half a million genes and that on average 300 000 genes are shared by half the studied subjects. The gene richness is higher in the European studies compared to Chinese and American and this is also reflected in the species richness. Even though it is possible to identify common species and a core set of genes, we find that there are large variations in abundance of species and genes.     

Mining the metagenome of activated biomass of an industrial wastewater treatment plant by a novel method

Metagenomic libraries herald the era of magnifying the microbial world, tapping into the vast metabolic potential of uncultivated microbes, and enhancing the rate of discovery of novel genes and pathways. In this paper, we describe a method that facilitates the extraction of metagenomic DNA from activated sludge of an industrial wastewater treatment plant and its use in mining the metagenome via library construction. The efficiency of this method was demonstrated by the large representation of the bacterial genome in the constructed metagenomic libraries and by the functional clones obtained. The BAC library represented 95.6 times the bacterial genome, while, the pUC library represented 41.7 times the bacterial genome. Twelve clones in the BAC library demonstrated lipolytic activity, while four clones demonstrated dioxygenase activity. Four clones in pUC library tested positive for cellulase activity. This method, using FTA cards, not only can be used for library construction, but can also store the metagenome at room temperature.     

Estimating the total genome length of a metagenomic sample using k-mers

Background

Metagenomic sequencing is a powerful technology for studying the mixture of microbes or the microbiomes on human and in the environment. One basic task of analyzing metagenomic data is to identify the component genomes in the community. This task is challenging due to the complexity of microbiome composition, limited availability of known reference genomes, and usually insufficient sequencing coverage.

Results

As an initial step toward understanding the complete composition of a metagenomic sample, we studied the problem of estimating the total length of all distinct component genomes in a metagenomic sample. We showed that this problem can be solved by estimating the total number of distinct k-mers in all the metagenomic sequencing data. We proposed a method for this estimation based on the sequencing coverage distribution of observed k-mers, and introduced a k-mer redundancy index (KRI) to fill in the gap between the count of distinct k-mers and the total genome length. We showed the effectiveness of the proposed method on a set of carefully designed simulation data corresponding to multiple situations of true metagenomic data. Results on real data indicate that the uncaptured genomic information can vary dramatically across metagenomic samples, with the potential to mislead downstream analyses.

Conclusions

We proposed the question of how long the total genome length of all different species in a microbial community is and introduced a method to answer it.

     

Random Whole Metagenomic Sequencing for Forensic Discrimination of Soils

Here we assess the ability of random whole metagenomic sequencing approaches to discriminate between similar soils from two geographically distinct urban sites for application in forensic science. Repeat samples from two parklands in residential areas separated by approximately 3 km were collected and the DNA was extracted. Shotgun, whole genome amplification (WGA) and single arbitrarily primed DNA amplification (AP-PCR) based sequencing techniques were then used to generate soil metagenomic profiles. Full and subsampled metagenomic datasets were then annotated against M5NR/M5RNA (taxonomic classification) and SEED Subsystems (metabolic classification) databases. Further comparative analyses were performed using a number of statistical tools including: hierarchical agglomerative clustering (CLUSTER); similarity profile analysis (SIMPROF); non-metric multidimensional scaling (NMDS); and canonical analysis of principal coordinates (CAP) at all major levels of taxonomic and metabolic classification. Our data showed that shotgun and WGA-based approaches generated highly similar metagenomic profiles for the soil samples such that the soil samples could not be distinguished accurately. An AP-PCR based approach was shown to be successful at obtaining reproducible site-specific metagenomic DNA profiles, which in turn were employed for successful discrimination of visually similar soil samples collected from two different locations.     

Whole-metagenome amplification of a microbial community associated with scleractinian coral by multiple displacement amplification using phi29 polymerase

Limitations in obtaining sufficient specimens and difficulties in extracting high quality DNA from environmental samples have impeded understanding of the structure of microbial communities. In this study, multiple displacement amplification (MDA) using phi29 polymerase was applied to overcome these hindrances. Optimization of the reaction conditions for amplification of the bacterial genome and evaluation of the MDA product were performed using cyanobacterium Synechocystis sp. strain PCC6803. An 8-h MDA reaction yielded a sufficient quantity of DNA from an initial amount of 0.4 ng, which is equivalent to approximately 10(5) cells. Uniform amplification of genes randomly selected from the cyanobacterial genome was confirmed by real-time polymerase chain reaction. The metagenome from bacteria associated with scleractinian corals was used for whole-genome amplification using phi29 polymerase to analyse the microbial diversity. Unidentified bacteria with less than 93% identity to the closest 16S rDNA sequences deposited in DNA Data Bank of Japan were predominantly detected from the coral-associated bacterial community before and after the MDA procedures. Sequencing analysis indicated that alpha-Proteobacteria was the dominant group in Pocillopora damicornis. This study demonstrates that MDA techniques are efficient for genome wide investigation to understand the actual microbial diversity in limited bacterial samples.     

Whole genome sequencing of environmental Vibrio cholerae O1 from 10 nanograms of DNA using short reads

Multiple Displacement Amplification (MDA) of DNA using φ29 (phi29) DNA polymerase amplifies DNA several billion-fold, which has proved to be potentially very useful for evaluating genome information in a culture-independent manner. Whole genome sequencing using DNA from a single prokaryotic genome copy amplified by MDA has not yet been achieved due to the formation of chimeras and skewed amplification of genomic regions during the MDA step, which then precludes genome assembly. We have hereby addressed the issue by using 10 ng of genomic Vibrio cholerae DNA extracted within an agarose plug to ensure circularity as a starting point for MDA and then sequencing the amplified yield using the SOLiD platform. We successfully managed to assemble the entire genome of V. cholerae strain LMA3984-4 (environmental O1 strain isolated in urban Amazonia) using a hybrid de novo assembly strategy. Using our method, only 178 out of 16,713 (1%) of contigs were not able to be inserted into either chromosome scaffold, and out of these 178, only 3 appeared to be chimeras. The other contigs seem to be the result of template-independent non-specific amplification during MDA, yielding spurious reads. Extraction of genomic DNA within an agarose plug in order to ensure circularity of the extracted genome might be key to minimizing amplification bias by MDA for WGS.     

Structure-based search reveals hammerhead ribozymes in the human microbiome

Deep sequencing of viral or bacterial nucleic acids monitors the presence and diversity of microbes in select populations and locations. Metagenomic study of mammalian viromes can help trace paths of viral transmissions within or between species. High throughput sequencing of patient and untreated sewage microbiomes showed many sequences with no similarity to genomic sequences of known function or origin. To estimate the distribution of functional RNAs in these microbiomes, we used the hammerhead ribozyme (HHR) motif to search for sequences capable of assuming its three-way junction fold. Although only two of the three possible natural HHR topologies had been known, our analysis revealed highly active ribozymes that terminated in any of the three stems. The most abundant of these are type II HHRs, one of which is the fastest natural cis-acting HHR yet discovered. Altogether, 13 ribozymes were confirmed in vitro, but only one showed sequence similarity to previously described HHRs. Sequences surrounding the ribozymes do not generally show similarity to known genes, except in one case, where a ribozyme is immediately preceded by a bacterial RadC gene. We demonstrate that a structure-based search for a known functional RNA is a powerful tool for analysis of metagenomic datasets, complementing sequence alignments.     

An overview of major metagenomic studies on human microbiomes in health and disease

Many microbes are important symbiotes of human. They form specific microbiota communities, participate in various kinds of biological processes of their host and thus deeply affect human health status. Metagenomic sequencing has been widely used in human microbiota study due to its capacity of studying all genetic materials in an environment as a whole without any extra need of isolation or cultivation of microorganisms. Many efforts have been made by researchers in this area trying to dig out interesting knowledge from various metagenome data. In this review, we go through some prominent studies in the metagenomic area. We summarize them into three categories, constructing taxonomy and gene reference, characterization of microbiome distribution patterns, and detection of microbiome alternations associated with specific human phenotypes or diseases. Some available data resources are also provided. This review can serve as an entrance to this exciting and rapidly developing field for researchers interested in human microbiomes.     

Novel strain-level resolution of Crohn’s disease mucosa-associated microbiota via an ex vivo combination of microbe culture and metagenomic sequencing

The mucosa-associated microbiota is widely recognized as a potential trigger for Crohn’s disease pathophysiology but remains largely uncharacterised beyond its taxonomic composition. Unlike stool microbiota, the functional characterisation of these communities using current DNA/RNA sequencing approaches remains constrained by the relatively small microbial density on tissue, and the overwhelming amount of human DNA recovered during sample preparation. Here, we have used a novel ex vivo approach that combines microbe culture from anaerobically preserved tissue with metagenome sequencing (MC-MGS) to reveal patient-specific and strain-level differences among these communities in post-operative Crohn’s disease patients. The 16 S rRNA gene amplicon profiles showed these cultures provide a representative and holistic representation of the mucosa-associated microbiota, and MC-MGS produced both high quality metagenome-assembled genomes of recovered novel bacterial lineages. The MC-MGS approach also produced a strain-level resolution of key Enterobacteriacea and their associated virulence factors and revealed that urease activity underpins a key and diverse metabolic guild in these communities, which was confirmed by culture-based studies with axenic cultures. Collectively, these findings using MC-MGS show that the Crohn’s disease mucosa-associated microbiota possesses taxonomic and functional attributes that are highly individualistic, borne at least in part by novel bacterial lineages not readily isolated or characterised from stool samples using current sequencing approaches.Subject terms: Biomarkers, Microbiome, Next-generation sequencing, Clinical microbiology, Metagenomics     

DNA提取过程中混入的实验室空气微生物DNA定量

元基因组测序方法为微生物研究提供了有力的工具。但其中的DNA提取过程,会不可避免地混入实验室中的空气微生物。这些微生物DNA,是否会对一些极微量的元基因组检测 (如皮肤样本等) 结果造成影响,有多大影响,仍没有明确结论。本研究首先收集了实验室空气样品,用16S rRNA引物建立了基于qPCR的标准曲线,并检测了在开放环境下提取DNA过程中可掺杂的环境微生物DNA量。然后在开放环境下提取纯水DNA样品并进行元基因组分析,以确定掺杂环境微生物的种类。最后分别在生物安全柜和实验室开放环境下提取皮肤样本,并用鸟枪测序方法对样本的微生物组成进行分析,以评估掺杂环境微生物对元基因组检测结果的影响。结果显示,在实验室开放环境的DNA提取过程中,环境微生物的DNA残留可达28.9 pg,可达某些极微量样本DNA总量的30%。元基因组分析显示,样品中掺杂的环境微生物主要是痤疮杆菌Cutibacterium acnes、大肠杆菌Escherichia coli等皮肤常见细菌。与洁净皮肤样本的信息相比,开放环境下提取掺杂了数十种环境微生物,并导致主要菌种的丰度大幅降低,从而影响结果的真实性。因此,微量样品的DNA提取应在洁净环境下执行。     

Regional mucosa-associated microbiota determine physiological expression of TLR2 and TLR4 in murine colon

Many colonic mucosal genes that are highly regulated by microbial signals are differentially expressed along the rostral-caudal axis. This would suggest that differences in regional microbiota exist, particularly mucosa-associated microbes that are less likely to be transient. We therefore explored this possibility by examining the bacterial populations associated with the normal proximal and distal colonic mucosa in context of host Toll-like receptors (TLR) expression in C57BL/6J mice housed in specific pathogen-free (SPF) and germ-free (GF) environments. 16S rRNA gene-based terminal restriction fragment length polymorphism (T-RFLP) and clone library analysis revealed significant differences in the community structure and diversity of the mucosa-associated microbiota located in the distal colon compared to proximal colon and stool, the latter two clustering closely. Differential expression of colonic TLR2 and TLR4 along the proximal-distal axis was also found in SPF mice, but not in GF mice, suggesting that enteric microbes are essential in maintaining the regional expression of these TLRs. TLR2 is more highly expressed in proximal colon and decreases in a gradient to distal while TLR4 expression is highest in distal colon and a gradient of decreased expression to proximal colon is observed. After transfaunation in GF mice, both regional colonization of mucosa-associated microbes and expression of TLRs in the mouse colon were reestablished. In addition, exposure of the distal colon to cecal (proximal) microbiota induced TLR2 expression. These results demonstrate that regional colonic mucosa-associated microbiota determine the region-specific expression of TLR2 and TLR4. Conversely, region-specific host assembly rules are essential in determining the structure and function of mucosa-associated microbial populations. We believe this type of host-microbial mutualism is pivotal to the maintenance of intestinal and immune homeostasis.