The effects of variable sample biomass on comparative metagenomics

Longitudinal studies that integrate samples with variable biomass are essential to understand microbial community dynamics across space or time. Shotgun metagenomics is widely used to investigate these communities at the functional level, but little is known about the effects of combining low and high biomass samples on downstream analysis. We investigated the interacting effects of DNA input and library amplification by polymerase chain reaction on comparative metagenomic analysis using dilutions of a single complex template from an Arabidopsis thaliana‐associated microbial community. We modified the Illumina Nextera kit to generate high‐quality large‐insert (680 bp) paired‐end libraries using a range of 50 pg to 50 ng of input DNA. Using assembly‐based metagenomic analysis, we demonstrate that DNA input level has a significant impact on community structure due to overrepresentation of low‐GC genomic regions following library amplification. In our system, these differences were largely superseded by variations between biological replicates, but our results advocate verifying the influence of library amplification on a case‐by‐case basis. Overall, this study provides recommendations for quality filtering and de‐replication prior to analysis, as well as a practical framework to address the issue of low biomass or biomass heterogeneity in longitudinal metagenomic surveys.     

Microarray-based analysis of subnanogram quantities of microbial community DNAs by using whole-community genome amplification

Microarray technology provides the opportunity to identify thousands of microbial genes or populations simultaneously, but low microbial biomass often prevents application of this technology to many natural microbial communities. We developed a whole-community genome amplification-assisted microarray detection approach based on multiple displacement amplification. The representativeness of amplification was evaluated using several types of microarrays and quantitative indexes. Representative detection of individual genes or genomes was obtained with 1 to 100 ng DNA from individual or mixed genomes, in equal or unequal abundance, and with 1 to 500 ng community DNAs from groundwater. Lower concentrations of DNA (as low as 10 fg) could be detected, but the lower template concentrations affected the representativeness of amplification. Robust quantitative detection was also observed by significant linear relationships between signal intensities and initial DNA concentrations ranging from (i) 0.04 to 125 ng (r2 = 0.65 to 0.99) for DNA from pure cultures as detected by whole-genome open reading frame arrays, (ii) 0.1 to 1,000 ng (r2 = 0.91) for genomic DNA using community genome arrays, and (iii) 0.01 to 250 ng (r2 = 0.96 to 0.98) for community DNAs from ethanol-amended groundwater using 50-mer functional gene arrays. This method allowed us to investigate the oligotrophic microbial communities in groundwater contaminated with uranium and other metals. The results indicated that microorganisms containing genes involved in contaminant degradation and immobilization are present in these communities, that their spatial distribution is heterogeneous, and that microbial diversity is greatly reduced in the highly contaminated environment.     

Microarray-Based Analysis of Subnanogram Quantities of Microbial Community DNAs by Using Whole-Community Genome Amplification

Microarray technology provides the opportunity to identify thousands of microbial genes or populations simultaneously, but low microbial biomass often prevents application of this technology to many natural microbial communities. We developed a whole-community genome amplification-assisted microarray detection approach based on multiple displacement amplification. The representativeness of amplification was evaluated using several types of microarrays and quantitative indexes. Representative detection of individual genes or genomes was obtained with 1 to 100 ng DNA from individual or mixed genomes, in equal or unequal abundance, and with 1 to 500 ng community DNAs from groundwater. Lower concentrations of DNA (as low as 10 fg) could be detected, but the lower template concentrations affected the representativeness of amplification. Robust quantitative detection was also observed by significant linear relationships between signal intensities and initial DNA concentrations ranging from (i) 0.04 to 125 ng (r² = 0.65 to 0.99) for DNA from pure cultures as detected by whole-genome open reading frame arrays, (ii) 0.1 to 1,000 ng (r² = 0.91) for genomic DNA using community genome arrays, and (iii) 0.01 to 250 ng (r² = 0.96 to 0.98) for community DNAs from ethanol-amended groundwater using 50-mer functional gene arrays. This method allowed us to investigate the oligotrophic microbial communities in groundwater contaminated with uranium and other metals. The results indicated that microorganisms containing genes involved in contaminant degradation and immobilization are present in these communities, that their spatial distribution is heterogeneous, and that microbial diversity is greatly reduced in the highly contaminated environment.     

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.     

Quantitative metagenomic analyses based on average genome size normalization

Over the past quarter-century, microbiologists have used DNA sequence information to aid in the characterization of microbial communities. During the last decade, this has expanded from single genes to microbial community genomics, or metagenomics, in which the gene content of an environment can provide not just a census of the community members but direct information on metabolic capabilities and potential interactions among community members. Here we introduce a method for the quantitative characterization and comparison of microbial communities based on the normalization of metagenomic data by estimating average genome sizes. This normalization can relieve comparative biases introduced by differences in community structure, number of sequencing reads, and sequencing read lengths between different metagenomes. We demonstrate the utility of this approach by comparing metagenomes from two different marine sources using both conventional small-subunit (SSU) rRNA gene analyses and our quantitative method to calculate the proportion of genomes in each sample that are capable of a particular metabolic trait. With both environments, to determine what proportion of each community they make up and how differences in environment affect their abundances, we characterize three different types of autotrophic organisms: aerobic, photosynthetic carbon fixers (the Cyanobacteria); anaerobic, photosynthetic carbon fixers (the Chlorobi); and anaerobic, nonphotosynthetic carbon fixers (the Desulfobacteraceae). These analyses demonstrate how genome proportionality compares to SSU rRNA gene relative abundance and how factors such as average genome size and SSU rRNA gene copy number affect sampling probability and therefore both types of community analysis.     

Amplification by PCR artificially reduces the proportion of the rare biosphere in microbial communities

The microbial world has been shown to hold an unimaginable diversity. The use of rRNA genes and PCR amplification to assess microbial community structure and diversity present biases that need to be analyzed in order to understand the risks involved in those estimates. Herein, we show that PCR amplification of specific sequence targets within a community depends on the fractions that those sequences represent to the total DNA template. Using quantitative, real-time, multiplex PCR and specific Taqman probes, the amplification of 16S rRNA genes from four bacterial species within a laboratory community were monitored. Results indicate that the relative amplification efficiency for each bacterial species is a nonlinear function of the fraction that each of those taxa represent within a community or multispecies DNA template. Consequently, the low-proportion taxa in a community are under-represented during PCR-based surveys and a large number of sequences might need to be processed to detect some of the bacterial taxa within the 'rare biosphere'. The structure of microbial communities from PCR-based surveys is clearly biased against low abundant taxa which are required to decipher the complete extent of microbial diversity in nature.     

Profiling and monitoring of microbial populations by denaturing high-performance liquid chromatography

We describe a new molecular technique for the analysis of microbial species and complex microbial populations based on the separation of PCR-amplified 16S rDNA fragments by denaturing high-performance liquid chromatography (DHPLC). Using marine bacterial samples, we determined the optimum conditions for the analysis of bacterial species and the examination of complex bacterial assemblages obtained from different environments. The incorporation of a 40-bp GC clamp into the amplification primer was essential to effectively discriminate genetic differences in DHPLC-primers with a 20-, 10-, or 0-bp GC clamp length were less efficient. A 64.5 degrees C column temperature in DHPLC allowed optimal separation of species in a complex bacterial population. PCR-DHPLC analysis of bacterial assemblages demonstrated profiles with distinguishable peaks, which constituted the different populations and their degree of abundance. Fraction collection and DNA sequencing from profile peaks enabled bacterial identification. PCR-DHPLC analysis can also provide opportunities for describing bacterial communities, cloning bacteria, and monitoring bacterial populations in environments of interest.     

Environments shape the nucleotide composition of genomes

To test the impact of environments on genome evolution, we analysed the relative abundance of the nucleotides guanine and cytosine ('GC content') of large numbers of sequences from four distinct environmental samples (ocean surface water, farm soil, an acidophilic mine drainage biofilm and deep-sea whale carcasses). We show that the GC content of complex microbial communities seems to be globally and actively influenced by the environment. The observed nucleotide compositions cannot be easily explained by distinct phylogenetic origins of the species in the environments; the genomic GC content may change faster than was previously thought, and is also reflected in the amino-acid composition of the proteins in these habitats.     

All together now: experimental multispecies biofilm model systems

Studies of microorganisms have traditionally focused on single species populations, which have greatly facilitated our understanding of the genetics and physiology that underpin microbial growth, adaptation and biofilm development. However, given that most microorganisms exist as multispecies consortia, the field is increasingly exploring microbial communities using a range of technologies traditionally limited to populations, including meta‐omics based approaches and high resolution imaging. The experimental communities currently being explored range from relatively low diversity, for example, two to four species, to significantly more complex systems, comprised of several hundred species. Results from both defined and undefined communities have revealed a number of emergent properties, including improved stress tolerance, increased biomass production, community level signalling and metabolic cooperation. Based on results published to date, we submit that community‐based studies are timely and increasingly reveal new properties associated with multispecies consortia that could not be predicted by studies of the individual component species. Here, we review a range of defined and undefined experimental systems used to study microbial community interactions.     

Punching above their weight: low-biomass non-native plant species alter soil properties during primary succession

Non‐native invasive plants can greatly alter community and ecosystem properties, but efforts to predict which invasive species have the greatest impacts on these properties have been generally unsuccessful. An hypothesis that has considerable promise for predicting the effects of invasive non‐native plant species is the mass ratio hypothesis (i.e. that dominant species exert the strongest effects). We tested this hypothesis using data from a four year removal experiment in which the presence of two dominant shrub species (one native and the other not), and subordinate plant species, were manipulated in factorial combinations over four years in a primary successional floodplain system. We measured the effects of these manipulations on the plant community, soil nutrient status and soil biota in different trophic levels of the soil food web. Our experiment showed that after four years, low‐biomass non‐native plant species exerted disproportionate belowground effects relative to their contribution to total biomass in the plant community, most notably by increasing soil C, soil microbial biomass, altering soil microbial community structure and increasing the abundance of microbial‐feeding and predatory nematodes. Low‐biomass, non‐native plant species had distinct life history strategies and foliar traits (higher foliar N concentrations and higher leaf area per unit mass) compared with the two dominant shrub species (97% of total plant mass). Our results have several implications for understanding species’ effects in communities and on soil properties. First, high‐biomass species do not necessarily exert the largest impacts on community or soil properties. Second, low‐biomass, inconspicuous non‐native species can influence community composition and have important trophic consequences belowground through effects on soil nutrient status or resource availability to soil biota. Our finding that low‐biomass non‐native species influence belowground community structure and soil properties more profoundly than dominant species demonstrates that the mass ratio hypothesis does not accurately predict the relative effects of different coexisting species on community‐ and ecosystem‐level properties.     

Assessing the utility of whole genome amplified DNA for next‐generation molecular ecology

DNA quantity can be a hindrance in ecological and evolutionary research programmes due to a range of factors including endangered status of target organisms, available tissue type, and the impact of field conditions on preservation methods. A potential solution to low‐quantity DNA lies in whole genome amplification (WGA) techniques that can substantially increase DNA yield. To date, few studies have rigorously examined sequence bias that might result from WGA and next‐generation sequencing of nonmodel taxa. To address this knowledge deficit, we use multiple displacement amplification (MDA) and double‐digest RAD sequencing on the grey mouse lemur (Microcebus murinus) to quantify bias in genome coverage and SNP calls when compared to raw genomic DNA (gDNA). We focus our efforts in providing baseline estimates of potential bias by following manufacturer's recommendations for starting DNA quantities (>100 ng). Our results are strongly suggestive that MDA enrichment does not introduce systematic bias to genome characterization. SNP calling between samples when genotyping both de‐novo and with a reference genome are highly congruent (>98%) when specifying a minimum threshold of 20X stack depth to call genotypes. Relative genome coverage is also similar between MDA and gDNA, and allelic dropout is not observed. SNP concordance varies based on coverage threshold, with 95% concordance reached at ~12X coverage genotyping de‐novo and ~7X coverage genotyping with the reference genome. These results suggest that MDA may be a suitable solution for next‐generation molecular ecological studies when DNA quantity would otherwise be a limiting factor.     

Primase-based whole genome amplification

In vitro DNA amplification methods, such as polymerase chain reaction (PCR), rely on synthetic oligonucleotide primers for initiation of the reaction. In vivo, primers are synthesized on-template by DNA primase. The bacteriophage T7 gene 4 protein (gp4) has both primase and helicase activities. In this study, we report the development of a primase-based Whole Genome Amplification (pWGA) method, which utilizes gp4 primase to synthesize primers, eliminating the requirement of adding synthetic primers. Typical yield of pWGA from 1 ng to 10 ng of human genomic DNA input is in the microgram range, reaching over a thousand-fold amplification after 1 h of incubation at 37 degrees C. The amplification bias on human genomic DNA is 6.3-fold among 20 loci on different chromosomes. In addition to amplifying total genomic DNA, pWGA can also be used for detection and quantification of contaminant DNA in a sample when combined with a fluorescent reporter dye. When circular DNA is used as template in pWGA, 10(8)-fold of amplification is observed from as low as 100 copies of input. The high efficiency of pWGA in amplifying circular DNA makes it a potential tool in diagnosis and genotyping of circular human DNA viruses such as human papillomavirus (HPV).     

Laboratory contamination over time during low‐biomass sample analysis

Bacteria are not only ubiquitous on earth but can also be incredibly diverse within clean laboratories and reagents. The presence of both living and dead bacteria in laboratory environments and reagents is especially problematic when examining samples with low endogenous content (e.g., skin swabs, tissue biopsies, ice, water, degraded forensic samples or ancient material), where contaminants can outnumber endogenous microorganisms within samples. The contribution of contaminants within high‐throughput studies remains poorly understood because of the relatively low number of contaminant surveys. Here, we examined 144 negative control samples (extraction blank and no‐template amplification controls) collected in both typical molecular laboratories and an ultraclean ancient DNA laboratory over 5 years to characterize long‐term contaminant diversity. We additionally compared the contaminant content within a home‐made silica‐based extraction method, commonly used to analyse low endogenous content samples, with a widely used commercial DNA extraction kit. The contaminant taxonomic profile of the ultraclean ancient DNA laboratory was unique compared to modern molecular biology laboratories, and changed over time according to researcher, month and season. The commercial kit also contained higher microbial diversity and several human‐associated taxa in comparison to the home‐made silica extraction protocol. We recommend a minimum of two strategies to reduce the impacts of laboratory contaminants within low‐biomass metagenomic studies: (a) extraction blank controls should be included and sequenced with every batch of extractions and (b) the contributions of laboratory contamination should be assessed and reported in each high‐throughput metagenomic study.     

Does genomic variation in a foundation species predict arthropod community structure in a riparian forest?

Understanding how genetic variation within a foundation species determines the structure of associated communities and ecosystem processes has been an emerging frontier in ecology. Previous studies in common gardens identified close links between intraspecific variation and multispecies community structure, and these findings are now being evaluated directly in the complex natural ecosystem. In this study, we examined to what extent genomic variation in a foundation tree species explains the structure of associated arthropod communities in the field, comparing with spatial, temporal and environmental factors. In a continuous mixed forest, arthropods were surveyed on 85 mature alders (Alnus hirsuta) in 2 years. Moreover, we estimated Nei's genetic distance among the alders based on 1,077 single nucleotide polymorphisms obtained from restricted‐site‐associated DNA sequencing of the alders’ genome. In both years, we detected significant correlations between genetic distance and dissimilarity of arthropod communities. A generalized dissimilarity modelling indicated that the genetic distance of alder populations was the most important predictor to explain the variance of arthropod communities. Among arthropod functional groups, carnivores were consistently correlated with genetic distance of the foundation species in both years. Furthermore, the extent of year‐to‐year changes in arthropod communities was more similar between more genetically closed alder populations. This study demonstrates that the genetic similarity rule would be primarily prominent in community assembly of plant‐associated arthropods under temporally and spatially variable environments in the field.     

Assessment of multiple displacement amplification in molecular epidemiology

Well-characterized epidemiological resources are generated with great effort, yet associated patient DNA samples can be limiting. The efficacy of the whole genome amplification (WGA) method, termed multiple displacement amplification (MDA), was assessed for detecting heterozygous sequence variants, mutation scanning, and PCR for challenging segments. Fifteen common polymorphisms from 10 genes located on 8 chromosomes were genotyped by direct sequencing of 300 PCR products from 115 high-quality MDA-amplified DNA samples extracted by different methods. The GC content of these analyzed segments ranges from 30% to 69%. Genotyping results demonstrate 100% accuracy. For heterozygotes, the relative intensity of peaks generated by the two alleles is highly similar for genomic and MDA-amplified genomic DNA, independent of GC content. In contrast, one of four heterozygous loci was mistyped when lower quality MDA-amplified DNA samples were used. The results of single-stranded conformation polymorphism (SSCP)-type of mutation scanningfor seven MDA-amplified DNA samples in four genes were concordant with the genomic DNA samples. PCR on MDA-amplified DNA was routinely successful for challenging 10- and 12-kb segments with GC content ranging from 30% to 80%, demonstrating that rather long segments, which are difficult to amplify with PCR, are amplified well with MDA. These results suggest that MDA is an effective method of WGA with utility in molecular epidemiology. Quality control of the MDA-amplified DNA is critical for high performance.     

Brugia malayi: whole genome amplification for genomic characterization of filarial parasites

Genetic characterization of field isolates and clinical specimens of filarial nematodes is often limited by a shortage of DNA; therefore, we evaluated a multiple displacement amplification (MDA) based whole genome amplification method. The quality of amplified DNA was examined by conventional PCR, real-time PCR, and DNA hybridization. MDA of 5.0 ng of adult Brugia malayi DNA and one-fifteenth of the DNA isolated from a single microfilaria resulted in 6.3 and 4.2 μg of amplified DNA, respectively. Amplified DNA was equivalent to native genomic DNA for hybridization to B. malayi BAC library clones or to an oligonucleotide microarray with approximately 18,000 filarial DNA sequences. MDA is useful for whole genome amplification of filarial DNA from very small amounts of starting material. This technology will permit detailed studies of genetic diversity that were not previously feasible.     

Sequence quality is maintained after multiple displacement amplification of non-invasively obtained macaque semen DNA

Whole genome amplification protocols are revolutionizing the fields of molecular and conservation biology as they open the possibility of obtaining a large number of copies of a complete genome from minute amounts of sample. Multiple displacement amplification (MDA) is a whole genome amplification technique based on the properties of the phi29 DNA polymerase, which leads to a uniform representation of the genome with very low error rates. In this study we performed MDA on 28 macaque DNA samples extracted from blood or non-invasively collected semen from which we obtained mitochondrial control region sequences both before and after MDA. The length of the readable sequences was longer for the original samples than for the MDA products, but the number of unresolved positions was comparable both before and after MDA. We conclude that the MDA technique is useful for increasing the amount of DNA for sequencing mitochondrial regions in the case of non-invasively collected semen samples.     

Environmental shaping of codon usage and functional adaptation across microbial communities

Microbial communities represent the largest portion of the Earth’s biomass. Metagenomics projects use high-throughput sequencing to survey these communities and shed light on genetic capabilities that enable microbes to inhabit every corner of the biosphere. Metagenome studies are generally based on (i) classifying and ranking functions of identified genes; and (ii) estimating the phyletic distribution of constituent microbial species. To understand microbial communities at the systems level, it is necessary to extend these studies beyond the species’ boundaries and capture higher levels of metabolic complexity. We evaluated 11 metagenome samples and demonstrated that microbes inhabiting the same ecological niche share common preferences for synonymous codons, regardless of their phylogeny. By exploring concepts of translational optimization through codon usage adaptation, we demonstrated that community-wide bias in codon usage can be used as a prediction tool for lifestyle-specific genes across the entire microbial community, effectively considering microbial communities as meta-genomes. These findings set up a ‘functional metagenomics’ platform for the identification of genes relevant for adaptations of entire microbial communities to environments. Our results provide valuable arguments in defining the concept of microbial species through the context of their interactions within the community.     

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.