Metagenomics: Concept,methodology, ecological inference and recent advances

Microorganisms constitute two third of the Earth's biological diversity. As many as 99% of the microorganisms present in certain environments cannot be cultured by standard techniques. Culture-independent methods are required to understand the genetic diversity, population structure and ecological roles of the majority of organisms. Metagenomics is the genomic analysis of microorganisms by direct extraction and cloning of DNA from their natural environment. Protocols have been developed to capture unexplored microbial diversity to overcome the existing barriers in estimation of diversity. New screening methods have been designed to select specific functional genes within metagenomic libraries to detect novel biocatalysts as well as bioactive molecules applicable to mankind. To study the complete gene or operon clusters, various vectors including cosmid, fosmid or bacterial artificial chromosomes are being developed. Bioinformatics tools and databases have added much to the study of microbial diversity. This review describes the various methodologies and tools developed to understand the biology of uncultured microbes including bacteria, archaea and viruses through metagenomic analysis.     

Targeted metagenomics: a high-resolution metagenomics approach for specific gene clusters in complex microbial communities

A major research goal in microbial ecology is to understand the relationship between gene organization and function involved in environmental processes of potential interest. Given that more than an estimated 99% of microorganisms in most environments are not amenable to culturing, methods for culture-independent studies of genes of interest have been developed. The wealth of metagenomic approaches allows environmental microbiologists to directly explore the enormous genetic diversity of microbial communities. However, it is extremely difficult to obtain the appropriate sequencing depth of any particular gene that can entirely represent the complexity of microbial metagenomes and be able to draw meaningful conclusions about these communities. This review presents a summary of the metagenomic approaches that have been useful for collecting more information about specific genes. Specific subsets of metagenomes that focus on sequence analysis were selected in each metagenomic studies. This 'targeted metagenomics' approach will provide extensive insight into the functional, ecological and evolutionary patterns of important genes found in microorganisms from various ecosystems.     

Competitive metagenomic DNA hybridization identifies host-specific microbial genetic markers in cow fecal samples

Several PCR methods have recently been developed to identify fecal contamination in surface waters. In all cases, researchers have relied on one gene or one microorganism for selection of host-specific markers. Here we describe the application of a genome fragment enrichment (GFE) method to identify host-specific genetic markers from fecal microbial community DNA. As a proof of concept, bovine fecal DNA was challenged against a porcine fecal DNA background to select for bovine-specific DNA sequences. Bioinformatic analyses of 380 bovine enriched metagenomic sequences indicated a preponderance of Bacteroidales-like regions predicted to encode membrane-associated and secreted proteins. Oligonucleotide primers capable of annealing to select Bacteroidales-like bovine GFE sequences exhibited extremely high specificity (>99%) in PCR assays with total fecal DNAs from 279 different animal sources. These primers also demonstrated a broad distribution of corresponding genetic markers (81% positive) among 148 different bovine sources. These data demonstrate that direct metagenomic DNA analysis by the competitive solution hybridization approach described is an efficient method for identifying potentially useful fecal genetic markers and for characterizing differences between environmental microbial communities.     

Statistical assessment of DNA extraction methodology for culture-independent analysis of microbial community associated with diverse environmental samples

Cost-effectiveness, quality, time-effectiveness and ease of the methodology are the most crucial factors in isolating quality DNA from wide variety of samples. Thus, research efforts focusing on the development of an efficient DNA extraction protocol is the need of the hour. The present study therefore, focuses on development of an efficient, rapid and free of inhibitory substances based methodology for extracting metagenomic DNA from diverse environmental samples viz. anaerobic biogas digesta, ruminant stomach, human feces, soil, and microbial starter cultures used for preparation of fermented food. PCR–DGGE based analysis and quality metagenomic library preparation, using DNA extraction methodology, validates the developed protocol. The developed protocol is cost effective, capable of isolating DNA from small sample size (100–1000 µl), time efficient (1.5–2.0 h protocol) and results in significantly higher DNA yield (4–8 times increased yield) when compared to previously available DNA extraction method and a commercial DNA extraction kit. The DNA extracted from the samples using different protocols was evaluated based on its ability to identify diverse microbial species using PCR–DGGE profiles targeting variable region within the 16S rRNA gene. The results of microbial community analysis revealed comparability of the developed protocol to commercial kits, in effectively identifying dominant representatives of the microbial community in different samples. Using the DNA extracted from the presented methodology, metagenomic libraries were prepared, which were found suitable for sequencing on Illumina platform.     

Competitive Metagenomic DNA Hybridization Identifies Host-Specific Microbial Genetic Markers in Cow Fecal Samples

Several PCR methods have recently been developed to identify fecal contamination in surface waters. In all cases, researchers have relied on one gene or one microorganism for selection of host-specific markers. Here we describe the application of a genome fragment enrichment (GFE) method to identify host-specific genetic markers from fecal microbial community DNA. As a proof of concept, bovine fecal DNA was challenged against a porcine fecal DNA background to select for bovine-specific DNA sequences. Bioinformatic analyses of 380 bovine enriched metagenomic sequences indicated a preponderance of Bacteroidales-like regions predicted to encode membrane-associated and secreted proteins. Oligonucleotide primers capable of annealing to select Bacteroidales-like bovine GFE sequences exhibited extremely high specificity (>99%) in PCR assays with total fecal DNAs from 279 different animal sources. These primers also demonstrated a broad distribution of corresponding genetic markers (81% positive) among 148 different bovine sources. These data demonstrate that direct metagenomic DNA analysis by the competitive solution hybridization approach described is an efficient method for identifying potentially useful fecal genetic markers and for characterizing differences between environmental microbial communities.     

Reconstruction of ribosomal RNA genes from metagenomic data

Direct sequencing of environmental DNA (metagenomics) has a great potential for describing the 16S rRNA gene diversity of microbial communities. However current approaches using this 16S rRNA gene information to describe community diversity suffer from low taxonomic resolution or chimera problems. Here we describe a new strategy that involves stringent assembly and data filtering to reconstruct full-length 16S rRNA genes from metagenomicpyrosequencing data. Simulations showed that reconstructed 16S rRNA genes provided a true picture of the community diversity, had minimal rates of chimera formation and gave taxonomic resolution down to genus level. The strategy was furthermore compared to PCR-based methods to determine the microbial diversity in two marine sponges. This showed that about 30% of the abundant phylotypes reconstructed from metagenomic data failed to be amplified by PCR. Our approach is readily applicable to existing metagenomic datasets and is expected to lead to the discovery of new microbial phylotypes.     

Combining gene prediction methods to improve metagenomic gene annotation

Background  

Traditional gene annotation methods rely on characteristics that may not be available in short reads generated from next generation technology, resulting in suboptimal performance for metagenomic (environmental) samples. Therefore, in recent years, new programs have been developed that optimize performance on short reads. In this work, we benchmark three metagenomic gene prediction programs and combine their predictions to improve metagenomic read gene annotation.     

Metagenomic analysis of Surti buffalo (Bubalus bubalis) rumen: a preliminary study

The complex microbiome of the rumen functions as an effective system for the conversion of plant cell wall biomass to microbial proteins, short chain fatty acids and gases. In this study, metagenomic approaches were used to study the microbial populations and metabolic potential of the microbial community. DNA was extracted from Surti Buffalo rumen samples (four treatments diet) and sequenced separately using a 454 GS FLX Titanium system. We used comparative metagenomics to examine metabolic potential and phylogenetic composition from pyrosequence data generated in four samples, considering phylogenetic composition and metabolic potentials in the rumen may remarkably be different with respect to nutrient utilization. Assignment of metagenomic sequences to SEED categories of the Metagenome Rapid Annotation using Subsystem Technology (MG-RAST) server revealed a genetic profile characteristic of fermentation of carbohydrates in a high roughage diet. The distribution of phylotypes and environmental gene tags (EGTs) detected within each rumen sample were dominated by Bacteroidetes/Chlorobi, Firmicutes and Proteobacteria in all the samples. The results of this study could help to determine the role of rumen microbes and their enzymes in plant polysaccharide breakdown is fundamental to understanding digestion and maximising productivity in ruminant animals.     

The phylogenetic diversity of metagenomes

Phylogenetic diversity--patterns of phylogenetic relatedness among organisms in ecological communities--provides important insights into the mechanisms underlying community assembly. Studies that measure phylogenetic diversity in microbial communities have primarily been limited to a single marker gene approach, using the small subunit of the rRNA gene (SSU-rRNA) to quantify phylogenetic relationships among microbial taxa. In this study, we present an approach for inferring phylogenetic relationships among microorganisms based on the random metagenomic sequencing of DNA fragments. To overcome challenges caused by the fragmentary nature of metagenomic data, we leveraged fully sequenced bacterial genomes as a scaffold to enable inference of phylogenetic relationships among metagenomic sequences from multiple phylogenetic marker gene families. The resulting metagenomic phylogeny can be used to quantify the phylogenetic diversity of microbial communities based on metagenomic data sets. We applied this method to understand patterns of microbial phylogenetic diversity and community assembly along an oceanic depth gradient, and compared our findings to previous studies of this gradient using SSU-rRNA gene and metagenomic analyses. Bacterial phylogenetic diversity was highest at intermediate depths beneath the ocean surface, whereas taxonomic diversity (diversity measured by binning sequences into taxonomically similar groups) showed no relationship with depth. Phylogenetic diversity estimates based on the SSU-rRNA gene and the multi-gene metagenomic phylogeny were broadly concordant, suggesting that our approach will be applicable to other metagenomic data sets for which corresponding SSU-rRNA gene sequences are unavailable. Our approach opens up the possibility of using metagenomic data to study microbial diversity in a phylogenetic context.     

元基因组学及其在转化医学中的应用

微生物群落遍布于人体的每个角落,与人共生并对人体健康产生重要和深刻的影响。与人类共生的全部微生物的基因组总和称为“元基因组”或“人类第二基因组”。研究人体微生物群落及相关元基因组数据,对转化医学领域的基础研究和临床应用具有重要的价值。通过对生物医学相关的高通量元基因组数据进行分析,不仅能为基础医学研究向医学临床应用转化提供新思路和新方法,而且具有广阔的应用前景。基于新一代测序技术产生的数据,元基因组分析技术和方法能够弥补以往人体微生物先培养后鉴定方法的缺陷,同时能有效鉴定和分析微生物群落的组成及功能,从而进一步探究和揭示微生物群落与机体生理状态之间的关系,为解决许多医学领域的难题提供了全新的切入角度和思维方法。文章系统介绍了元基因组研究的现状,包括元基因组的方法概念和研究进展,并以元基因组在医学研究中的应用为着眼点,综述了元基因组在转化医学方面的研究进展,进一步阐述了元基因组研究在转化医学应用领域中具有的重要地位。     

Comparison of Metagenomic DNA Extraction Methods for Soil Sediments of High Elevation Puga Hot Spring in Ladakh,India to Explore Bacterial Diversity

Extraction of good-quality metagenomic DNA from extreme environments is quite challenging, particularly from high elevation hot spring sediments. Low microbial load, high humic acid content and other contaminants complicate the process of extraction of metagenomic DNA from hot spring sediments. In the present study, efficacy of five manual DNA extraction protocols with modifications has been evaluated for metagenomic DNA extraction from boron–sulfur rich high elevation Puga hot spring sediments. Best suited protocol was identified based on the cell lysis efficiency, DNA yield, humic acid content, PCR reproducibility and representation of bacterial diversity. Quantity as well as quality of crude metagenomic DNA differed remarkably between various protocols used and were not pure enough to give PCR amplification using 16S rRNA bacterial and archaeal primers. Crude metagenomic DNA extracted using five different DNA extraction protocols was purified using spin column based purification method. Even after purification, only three protocols C, D and E yielded metagenomic DNA that could be amplified using both archaeal and bacterial primers. To evaluate the degree of microbial diversity represented by protocols C, D and E, phylogenetic genes amplified were subjected to amplified ribosomal DNA restriction analysis (ARDRA) and denaturing gradient gel electrophoresis analysis (DGGE) analysis. ARDRA banding pattern of amplicons generated for all the three extraction protocols, i.e., C, D and E were found to be similar. DGGE of protocol E derived amplicons resulted in the similar number of dominant bands but a greater number of non-dominant bands, i.e., the highest microbial diversity in comparison to protocols C and D, respectively. In the present study, protocol E developed from Yeates et al. protocol has been found to be best in terms of DNA yield, DNA purity and bacterial diversity depiction associated with boron–sulfur rich sediment of high elevation hot springs.     

Cloning the soil metagenome: a strategy for accessing the genetic and functional diversity of uncultured microorganisms

Recent progress in molecular microbial ecology has revealed that traditional culturing methods fail to represent the scope of microbial diversity in nature, since only a small proportion of viable microorganisms in a sample are recovered by culturing techniques. To develop methods to investigate the full extent of microbial diversity, we used a bacterial artificial chromosome (BAC) vector to construct libraries of genomic DNA isolated directly from soil (termed metagenomic libraries). To date, we have constructed two such libraries, which contain more than 1 Gbp of DNA. Phylogenetic analysis of 16S rRNA gene sequences recovered from one of the libraries indicates that the BAC libraries contain DNA from a wide diversity of microbial phyla, including sequences from diverse taxa such as the low-G+C, gram-positive Acidobacterium, Cytophagales, and Proteobacteria. Initial screening of the libraries in Escherichia coli identified several clones that express heterologous genes from the inserts, confirming that the BAC vector can be used to maintain, express, and analyze environmental DNA. The phenotypes expressed by these clones include antibacterial, lipase, amylase, nuclease, and hemolytic activities. Metagenomic libraries are a powerful tool for exploring soil microbial diversity, providing access to the genetic information of uncultured soil microorganisms. Such libraries will be the basis of new initiatives to conduct genomic studies that link phylogenetic and functional information about the microbiota of environments dominated by microorganisms that are refractory to cultivation.     

Identification and characterization of metagenomic fragments from tidal flat sediment

Phylogenetic surveys based on cultivation-independent methods have revealed that tidal flat sediments are environments with extensive microbial diversity. Since most of prokaryotes in nature cannot be easily cultivated under general laboratory conditions, our knowledge on prokaryotic dwellers in tidal flat sediment is mainly based on the analysis of metagenomes. Microbial community analysis based on the 16S rRNA gene and other phylogenetic markers has been widely used to provide important information on the role of microorganisms, but it is basically an indirect means, compared with direct sequencing of metagenomic DNAs. In this study, we applied a sequence-based metagenomic approach to characterize uncultivated prokaryotes from tidal flat sediment. Two large-insert genomic libraries based on fosmid were constructed from tidal flat metagenomic DNA. A survey based on end-sequencing of selected fosmid clones resulted in the identification of clones containing 274 bacterial and 16 archaeal homologs in which majority were of proteobacterial origins. Two fosmid clones containing large metagenomic DNAs were completely sequenced using the shotgun method. Both DNA inserts contained more than 20 genes encoding putative proteins which implied their ecological roles in tidal flat sediment. Phylogenetic analyses of evolutionary conserved proteins indicate that these clones are not closely related to known prokaryotes whose genome sequence is known, and genes in tidal flat may be subjected to extensive lateral gene transfer, notably between domains Bacteria and Archaea. This is the first report demonstrating that direct sequencing of metagenomic gene library is useful in underpinning the genetic makeup and functional roles of prokaryotes in tidal flat sediments.     

Culture-independent discovery of natural products from soil metagenomes

Bacterial natural products have proven to be invaluable starting points in the development of many currently used therapeutic agents. Unfortunately, traditional culture-based methods for natural product discovery have been deemphasized by pharmaceutical companies due in large part to high rediscovery rates. Culture-independent, or “metagenomic,” methods, which rely on the heterologous expression of DNA extracted directly from environmental samples (eDNA), have the potential to provide access to metabolites encoded by a large fraction of the earth’s microbial biosynthetic diversity. As soil is both ubiquitous and rich in bacterial diversity, it is an appealing starting point for culture-independent natural product discovery efforts. This review provides an overview of the history of soil metagenome-driven natural product discovery studies and elaborates on the recent development of new tools for sequence-based, high-throughput profiling of environmental samples used in discovering novel natural product biosynthetic gene clusters. We conclude with several examples of these new tools being employed to facilitate the recovery of novel secondary metabolite encoding gene clusters from soil metagenomes and the subsequent heterologous expression of these clusters to produce bioactive small molecules.     

Statistical Approach of Functional Profiling for a Microbial Community

Background

Metagenomics is a relatively new but fast growing field within environmental biology and medical sciences. It enables researchers to understand the diversity of microbes, their functions, cooperation, and evolution in a particular ecosystem. Traditional methods in genomics and microbiology are not efficient in capturing the structure of the microbial community in an environment. Nowadays, high-throughput next-generation sequencing technologies are powerfully driving the metagenomic studies. However, there is an urgent need to develop efficient statistical methods and computational algorithms to rapidly analyze the massive metagenomic short sequencing data and to accurately detect the features/functions present in the microbial community. Although several issues about functions of metagenomes at pathways or subsystems level have been investigated, there is a lack of studies focusing on functional analysis at a low level of a hierarchical functional tree, such as SEED subsystem tree.

Results

A two-step statistical procedure (metaFunction) is proposed to detect all possible functional roles at the low level from a metagenomic sample/community. In the first step a statistical mixture model is proposed at the base of gene codons to estimate the abundances for the candidate functional roles, with sequencing error being considered. As a gene could be involved in multiple biological processes the functional assignment is therefore adjusted by utilizing an error distribution in the second step. The performance of the proposed procedure is evaluated through comprehensive simulation studies. Compared with other existing methods in metagenomic functional analysis the new approach is more accurate in assigning reads to functional roles, and therefore at more general levels. The method is also employed to analyze two real data sets.

Conclusions

metaFunction is a powerful tool in accurate profiling functions in a metagenomic sample.     

Phylogenetic classification of short environmental DNA fragments

Metagenomics is providing striking insights into the ecology of microbial communities. The recently developed massively parallel 454 pyrosequencing technique gives the opportunity to rapidly obtain metagenomic sequences at a low cost and without cloning bias. However, the phylogenetic analysis of the short reads produced represents a significant computational challenge. The phylogenetic algorithm CARMA for predicting the source organisms of environmental 454 reads is described. The algorithm searches for conserved Pfam domain and protein families in the unassembled reads of a sample. These gene fragments (environmental gene tags, EGTs), are classified into a higher-order taxonomy based on the reconstruction of a phylogenetic tree of each matching Pfam family. The method exhibits high accuracy for a wide range of taxonomic groups, and EGTs as short as 27 amino acids can be phylogenetically classified up to the rank of genus. The algorithm was applied in a comparative study of three aquatic microbial samples obtained by 454 pyrosequencing. Profound differences in the taxonomic composition of these samples could be clearly revealed.     

An assessment of actinobacterial diversity in the marine environment

The 16S rRNA gene sequence diversity within the Phylum Actinobacteria was assessed from four sources: PCR-generated V6 sequence tags derived from seawater samples, metagenomic data from the Global Ocean Sampling (GOS) expedition, marine-derived sequences maintained in the Ribosomal Database Project (RDP), and select cultured strains for which sequence data is not yet available in the RDP. This meta-analysis revealed remarkable levels of phylogenetic diversity and confirms the existence of major, deeply rooted, and as of yet uncharacterized lineages within the phylum. A dramatic incongruence among cultured strains and those detected using culture-independent techniques was also revealed. Redundancy among the actinobacteria detected using culture-independent techniques suggests that greater sequence coverage or improved DNA extraction efficiencies may be required to detect the rare phylotypes that can be readily cultured from marine samples. Conversely, new strategies need to be developed for the cultivation of frequently observed but yet to be cultured marine actinobacteria.     

Metagenomic Sequencing of an In Vitro-Simulated Microbial Community

Background

Microbial life dominates the earth, but many species are difficult or even impossible to study under laboratory conditions. Sequencing DNA directly from the environment, a technique commonly referred to as metagenomics, is an important tool for cataloging microbial life. This culture-independent approach involves collecting samples that include microbes in them, extracting DNA from the samples, and sequencing the DNA. A sample may contain many different microorganisms, macroorganisms, and even free-floating environmental DNA. A fundamental challenge in metagenomics has been estimating the abundance of organisms in a sample based on the frequency with which the organism''s DNA was observed in reads generated via DNA sequencing.

Methodology/Principal Findings

We created mixtures of ten microbial species for which genome sequences are known. Each mixture contained an equal number of cells of each species. We then extracted DNA from the mixtures, sequenced the DNA, and measured the frequency with which genomic regions from each organism was observed in the sequenced DNA. We found that the observed frequency of reads mapping to each organism did not reflect the equal numbers of cells that were known to be included in each mixture. The relative organism abundances varied significantly depending on the DNA extraction and sequencing protocol utilized.

Conclusions/Significance

We describe a new data resource for measuring the accuracy of metagenomic binning methods, created by in vitro-simulation of a metagenomic community. Our in vitro simulation can be used to complement previous in silico benchmark studies. In constructing a synthetic community and sequencing its metagenome, we encountered several sources of observation bias that likely affect most metagenomic experiments to date and present challenges for comparative metagenomic studies. DNA preparation methods have a particularly profound effect in our study, implying that samples prepared with different protocols are not suitable for comparative metagenomics.     

土壤宏基因组学技术及其应用

传统的基于培养的研究方法只能反映土壤中少数(0.1%～10 %)微生物的信息,而大部分微生物目前还不能培养,因而这部分微生物资源尚难以被有效地开发利用.宏基因组学是分子生物学技术应用于环境微生物生态学研究而形成的一个新概念,主要技术包括土壤DNA的提取、文库的构建和目标基因克隆的筛选.它可为揭示微生物生态功能及其分子基础提供更全面的遗传信息,并已在微生物新功能基因筛选、活性物质开发和微生物多样性研究等方面取得了显著成果.本文对土壤宏基因组学技术的方法和应用作了详细介绍.     

Cloning the Soil Metagenome: a Strategy for Accessing the Genetic and Functional Diversity of Uncultured Microorganisms

Recent progress in molecular microbial ecology has revealed that traditional culturing methods fail to represent the scope of microbial diversity in nature, since only a small proportion of viable microorganisms in a sample are recovered by culturing techniques. To develop methods to investigate the full extent of microbial diversity, we used a bacterial artificial chromosome (BAC) vector to construct libraries of genomic DNA isolated directly from soil (termed metagenomic libraries). To date, we have constructed two such libraries, which contain more than 1 Gbp of DNA. Phylogenetic analysis of 16S rRNA gene sequences recovered from one of the libraries indicates that the BAC libraries contain DNA from a wide diversity of microbial phyla, including sequences from diverse taxa such as the low-G+C, gram-positive Acidobacterium, Cytophagales, and Proteobacteria. Initial screening of the libraries in Escherichia coli identified several clones that express heterologous genes from the inserts, confirming that the BAC vector can be used to maintain, express, and analyze environmental DNA. The phenotypes expressed by these clones include antibacterial, lipase, amylase, nuclease, and hemolytic activities. Metagenomic libraries are a powerful tool for exploring soil microbial diversity, providing access to the genetic information of uncultured soil microorganisms. Such libraries will be the basis of new initiatives to conduct genomic studies that link phylogenetic and functional information about the microbiota of environments dominated by microorganisms that are refractory to cultivation.