Evaluation of 96-well high-throughput DNA extraction methods for 16S rRNA gene metabarcoding

Gaining meaningful insights into bacterial communities associated with animal hosts requires the provision of high-quality nucleic acids. Although many studies have compared DNA extraction methods for samples with low bacterial biomass (e.g. water) or specific PCR inhibitors (e.g. plants), DNA extraction bias in samples without inherent technical constraint (e.g. animal samples) has received little attention. Furthermore, there is an urgent need to identify a DNA extraction methods in a high-throughput format that decreases the cost and time for processing large numbers of samples. We here evaluated five DNA extraction protocols, using silica membrane-based spin columns and a 96-well microplate format and based on either mechanical or enzymatic lysis or a combination of both, using three bacterial mock communities and Illumina sequencing of the V4 region of the 16SrRNA gene. Our results showed that none of the DNA extraction methods fully eliminated bias associated with unequal lysis efficiencies. However, we identified a DNA extraction method with a lower bias for each mock community standard. Of these methods, those including an enzymatic lysis showed biases specific to some bacteria. Altogether, these results again demonstrate the importance of DNA extraction standardization to be able to compare the microbiome results of different samples. In this attempt, we advise for the use of the 96-well DNeasy Blood and Tissue kit (Qiagen) with a zirconia bead-beating procedure, which optimizes altogether the cost, handling time and bacteria-specific effects associated with enzymatic lysis.     

Culture enriched molecular profiling of the cystic fibrosis airway microbiome

The microbiome of the respiratory tract, including the nasopharyngeal and oropharyngeal microbiota, is a dynamic community of microorganisms that is highly diverse. The cystic fibrosis (CF) airway microbiome refers to the polymicrobial communities present in the lower airways of CF patients. It is comprised of chronic opportunistic pathogens (such as Pseudomonas aeruginosa) and a variety of organisms derived mostly from the normal microbiota of the upper respiratory tract. The complexity of these communities has been inferred primarily from culture independent molecular profiling. As with most microbial communities it is generally assumed that most of the organisms present are not readily cultured. Our culture collection generated using more extensive cultivation approaches, reveals a more complex microbial community than that obtained by conventional CF culture methods. To directly evaluate the cultivability of the airway microbiome, we examined six samples in depth using culture-enriched molecular profiling which combines culture-based methods with the molecular profiling methods of terminal restriction fragment length polymorphisms and 16S rRNA gene sequencing. We demonstrate that combining culture-dependent and culture-independent approaches enhances the sensitivity of either approach alone. Our techniques were able to cultivate 43 of the 48 families detected by deep sequencing; the five families recovered solely by culture-independent approaches were all present at very low abundance (<0.002% total reads). 46% of the molecular signatures detected by culture from the six patients were only identified in an anaerobic environment, suggesting that a large proportion of the cultured airway community is composed of obligate anaerobes. Most significantly, using 20 growth conditions per specimen, half of which included anaerobic cultivation and extended incubation times we demonstrate that the majority of bacteria present can be cultured.     

Comparison of DNA extraction methods for human gut microbial community profiling

The human gut harbors a vast range of microbes that have significant impact on health and disease. Therefore, gut microbiome profiling holds promise for use in early diagnosis and precision medicine development. Accurate profiling of the highly complex gut microbiome requires DNA extraction methods that provide sufficient coverage of the original community as well as adequate quality and quantity. We tested nine different DNA extraction methods using three commercial kits (TianLong Stool DNA/RNA Extraction Kit (TS), QIAamp DNA Stool Mini Kit (QS), and QIAamp PowerFecal DNA Kit (QP)) with or without additional bead-beating step using manual or automated methods and compared them in terms of DNA extraction ability from human fecal sample. All methods produced DNA in sufficient concentration and quality for use in sequencing, and the samples were clustered according to the DNA extraction method. Inclusion of bead-beating step especially resulted in higher degrees of microbial diversity and had the greatest effect on gut microbiome composition. Among the samples subjected to bead-beating method, TS kit samples were more similar to QP kit samples than QS kit samples. Our results emphasize the importance of mechanical disruption step for a more comprehensive profiling of the human gut microbiome.     

Comprehensive single-PCR 16S and 18S rRNA community analysis validated with mock communities,and estimation of sequencing bias against 18S

Universal primers for SSU rRNA genes allow profiling of natural communities by simultaneously amplifying templates from Bacteria, Archaea, and Eukaryota in a single PCR reaction. Despite the potential to show relative abundance for all rRNA genes, universal primers are rarely used, due to various concerns including amplicon length variation and its effect on bioinformatic pipelines. We thus developed 16S and 18S rRNA mock communities and a bioinformatic pipeline to validate this approach. Using these mocks, we show that universal primers (515Y/926R) outperformed eukaryote-specific V4 primers in observed versus expected abundance correlations (slope = 0.88 vs. 0.67–0.79), and mock community members with single mismatches to the primer were strongly underestimated (threefold to eightfold). Using field samples, both primers yielded similar 18S beta-diversity patterns (Mantel test, p < 0.001) but differences in relative proportions of many rarer taxa. To test for length biases, we mixed mock communities (16S + 18S) before PCR and found a twofold underestimation of 18S sequences due to sequencing bias. Correcting for the twofold underestimation, we estimate that, in Southern California field samples (1.2–80 μm), there were averages of 35% 18S, 28% chloroplast 16S, and 37% prokaryote 16S rRNA genes. These data demonstrate the potential for universal primers to generate comprehensive microbiome profiles.     

Culture and molecular-based profiles show shifts in bacterial communities of the upper respiratory tract that occur with age

The upper respiratory tract (URT) is a crucial site for host defense, as it is home to bacterial communities that both modulate host immune defense and serve as a reservoir of potential pathogens. Young children are at high risk of respiratory illness, yet the composition of their URT microbiota is not well understood. Microbial profiling of the respiratory tract has traditionally focused on culturing common respiratory pathogens, whereas recent culture-independent microbiome profiling can only report the relative abundance of bacterial populations. In the current study, we used both molecular profiling of the bacterial 16S rRNA gene and laboratory culture to examine the bacterial diversity from the oropharynx and nasopharynx of 51 healthy children with a median age of 1.1 years (range 1–4.5 years) along with 19 accompanying parents. The resulting profiles suggest that in young children the nasopharyngeal microbiota, much like the gastrointestinal tract microbiome, changes from an immature state, where it is colonized by a few dominant taxa, to a more diverse state as it matures to resemble the adult microbiota. Importantly, this difference in bacterial diversity between adults and children accompanies a change in bacterial load of three orders of magnitude. This indicates that the bacterial communities in the nasopharynx of young children have a fundamentally different structure from those in adults and suggests that maturation of this community occurs sometime during the first few years of life, a period that includes ages at which children are at the highest risk for respiratory disease.     

Evaluation of magnetic cellulose bead-based DNA extraction from faecal materials for high-throughput bacterial community analyses

Studies on host-associated microbial communities using faecal samples has been providing important insights into the health, ecology and evolution of various animals. Many gut microbiome studies currently use manual kit-based DNA extraction methods, yet new methods that allow high-throughput sample processing are in demand. In this study, we evaluated magnetic cellulose bead-based DNA extraction methods, which can be automated in a work station, using mouse, Mus musculus (Linnaeus), and bovine, Bos taurus (Linnaeus), faeces as a model. Our data showed that those methods can provide good quantity and quality of extracted DNA suitable for 16S-rRNA-based microbiome analyses for a wide variety of samples, comparable to or more efficiently than the widely used standard method. The automated extraction requires less time and fewer manual steps, which makes these methods suitable for high-throughput faecal microbiome analyses.     

Objective criteria to assess representativity of soil fungal community profiles

Soil fungal community structures are often highly heterogeneous even among samples taken from small field plots. Sample pooling is widely used in order to overcome this heterogeneity, however, no objective criteria have yet been defined on how to determine the number of samples to be pooled for representatively profiling a field plot. In the present study PCR/RFLP and T-RFLP analysis of fungal 18S rDNA in ten soil samples obtained from a grassland plot of 400 m(2) also revealed this known heterogeneity in fungal community structures. Based on these data a three-step approach to assess representativity of fungal community profiles was established. First, soil DNA quantities needed for robust community profiling were determined. Second, profiles of single or multiple samples were theoretically averaged to test for statistically significant clustering in order to determine the minimal number of samples to be pooled to achieve representativity. Third, DNA extracts of single or multiple samples were pooled prior to profiling in order to test for statistically significant clustering. Analyses revealed robust profiles for 50 ng soil DNA but not for 5 ng. Averaged T-RFLP profiles from five or more soil samples and experimental T-RFLP profiles from pools of seven or more samples formed one significant branch. Theoretical averaging and experimental pooling revealed that five to seven samples have to be pooled for robustly representing the field plot. Our results demonstrate that representativity of soil fungal community profiles can objectively be determined for a field plot with only little deviation between theoretical and experimental approaches. This three-step approach will be of assistance for designing sampling and pooling strategies for comparative analyses of soil fungal communities in ecological studies.     

Optimal extraction methods for the simultaneous analysis of DNA from diverse organisms and sample types

Using environmental DNA (eDNA) to assess the distribution of micro‐ and macroorganisms is becoming increasingly popular. However, the comparability and reliability of these studies is not well understood as we lack evidence on how different DNA extraction methods affect the detection of different organisms, and how this varies among sample types. Our aim was to quantify biases associated with six DNA extraction methods and identify one which is optimal for eDNA research targeting multiple organisms and sample types. We assessed each methods’ ability to simultaneously extract bacterial, fungal, plant, animal and fish DNA from soil, leaf litter, stream water, stream sediment, stream biofilm and kick‐net samples, as well as from mock communities. Method choice affected alpha‐diversity for several combinations of taxon and sample type, with the majority of the differences occurring in the bacterial communities. While a single method performed optimally for the extraction of DNA from bacterial, fungal and plant mock communities, different methods performed best for invertebrate and fish mock communities. The consistency of methods, as measured by the similarity of community compositions resulting from replicate extractions, varied and was lowest for the animal communities. Collectively, these data provide the first comprehensive assessment of the biases associated with DNA extraction for both different sample types and taxa types, allowing us to identify DNeasy PowerSoil as a universal DNA extraction method. The adoption of standardized approaches for eDNA extraction will ensure that results can be more reliably compared, and biases quantified, thereby advancing eDNA as an ecological research tool.     

Analysis of the lung microbiome in the "healthy" smoker and in COPD

Although culture-independent techniques have shown that the lungs are not sterile, little is known about the lung microbiome in chronic obstructive pulmonary disease (COPD). We used pyrosequencing of 16S amplicons to analyze the lung microbiome in two ways: first, using bronchoalveolar lavage (BAL) to sample the distal bronchi and air-spaces; and second, by examining multiple discrete tissue sites in the lungs of six subjects removed at the time of transplantation. We performed BAL on three never-smokers (NS) with normal spirometry, seven smokers with normal spirometry ("healthy smokers", HS), and four subjects with COPD (CS). Bacterial 16 s sequences were found in all subjects, without significant quantitative differences between groups. Both taxonomy-based and taxonomy-independent approaches disclosed heterogeneity in the bacterial communities between HS subjects that was similar to that seen in healthy NS and two mild COPD patients. The moderate and severe COPD patients had very limited community diversity, which was also noted in 28% of the healthy subjects. Both approaches revealed extensive membership overlap between the bacterial communities of the three study groups. No genera were common within a group but unique across groups. Our data suggests the existence of a core pulmonary bacterial microbiome that includes Pseudomonas, Streptococcus, Prevotella, Fusobacterium, Haemophilus, Veillonella, and Porphyromonas. Most strikingly, there were significant micro-anatomic differences in bacterial communities within the same lung of subjects with advanced COPD. These studies are further demonstration of the pulmonary microbiome and highlight global and micro-anatomic changes in these bacterial communities in severe COPD patients.     

ANCHOR: a 16S rRNA gene amplicon pipeline for microbial analysis of multiple environmental samples

Analysis of 16S ribosomal RNA (rRNA) gene amplification data for microbial barcoding can be inaccurate across complex environmental samples. A method, ANCHOR, is presented and designed for improved species-level microbial identification using paired-end sequences directly, multiple high-complexity samples and multiple reference databases. A standard operating procedure (SOP) is reported alongside benchmarking against artificial, single sample and replicated mock data sets. The method is then directly tested using a real-world data set from surface swabs of the International Space Station (ISS). Simple mock community analysis identified 100% of the expected species and 99% of expected gene copy variants (100% identical). A replicated mock community revealed similar or better numbers of expected species than MetaAmp, DADA2, Mothur and QIIME1. Analysis of the ISS microbiome identified 714 putative unique species/strains and differential abundance analysis distinguished significant differences between the Destiny module (U.S. laboratory) and Harmony module (sleeping quarters). Harmony was remarkably dominated by human gastrointestinal tract bacteria, similar to enclosed environments on earth; however, Destiny module bacteria also derived from nonhuman microbiome carriers present on the ISS, the laboratory's research animals. ANCHOR can help substantially improve sequence resolution of 16S rRNA gene amplification data within biologically replicated environmental experiments and integrated multidatabase annotation enhances interpretation of complex, nonreference microbiomes.     

Assessment of microbial diversity in four southwestern United States soils by 16S rRNA gene terminal restriction fragment analysis

The ability of terminal restriction fragment (T-RFLP or TRF) profiles of 16S rRNA genes to provide useful information about the relative diversity of complex microbial communities was investigated by comparison with other methods. Four soil communities representing two pinyon rhizosphere and two between-tree (interspace) soil environments were compared by analysis of 16S rRNA gene clone libraries and culture collections (Dunbar et al., Appl. Environ. Microbiol. 65:1662-1669, 1998) and by analysis of 16S rDNA TRF profiles of community DNA. The TRF method was able to differentiate the four communities in a manner consistent with previous comparisons of the communities by analysis of 16S rDNA clone libraries. TRF profiles were not useful for calculating and comparing traditional community richness or evenness values among the four soil environments. Statistics calculated from RsaI, HhaI, HaeIII, and MspI profiles of each community were inconsistent, and the combined data were not significantly different between samples. The detection sensitivity of the method was tested. In standard PCRs, a seeded population comprising 0.1 to 1% of the total community could be detected. The combined results demonstrate that TRF analysis is an excellent method for rapidly comparing the relationships between bacterial communities in environmental samples. However, for highly complex communities, the method appears unable to provide classical measures of relative community diversity.     

A direct PCR approach to accelerate analyses of human-associated microbial communities

Since the composition of the human microbiome is highly variable both within and between individuals, researchers are increasingly reliant on high-throughput molecular approaches to identify linkages between the composition of these communities and human health. While new sequencing technologies have made it increasingly feasible to analyze large numbers of human-associated samples, the extraction of DNA from samples often remains a bottleneck in the process. Here we tested a direct PCR approach using the Extract-N-Amp Plant PCR Kit to accelerate the 16S rRNA gene-based analyses of human-associated bacterial communities, directly comparing this method to a more commonly-used approach whereby DNA is first extracted and purified from samples using a series of steps prior to PCR amplification. We used both approaches on replicate samples collected from each of five body habitats (tongue surface, feces, forehead skin, underarm skin, and forearm skin) from four individuals. With the exception of the tongue samples, there were few significant differences in the estimates of taxon richness or phylogenetic diversity obtained using the two approaches. Perhaps more importantly, there were no significant differences between the methods in their ability resolve body habitat differences or inter-individual differences in bacterial community composition and the estimates of the relative abundances of individual taxa were nearly identical with the two methods. Overall, the two methods gave very similar results and the direct PCR approach is clearly advantageous for many studies exploring the diversity and composition of human-associated bacterial communities given that large numbers of samples can be processed far more quickly and efficiently.     

Analysis of Lung Microbiota in Bronchoalveolar Lavage,Protected Brush and Sputum Samples from Subjects with Mild-To-Moderate Cystic Fibrosis Lung Disease

Individuals with cystic fibrosis (CF) often acquire chronic lung infections that lead to irreversible damage. We sought to examine regional variation in the microbial communities in the lungs of individuals with mild-to-moderate CF lung disease, to examine the relationship between the local microbiota and local damage, and to determine the relationships between microbiota in samples taken directly from the lung and the microbiota in spontaneously expectorated sputum. In this initial study, nine stable, adult CF patients with an FEV₁>50% underwent regional sampling of different lobes of the right lung by bronchoalveolar lavage (BAL) and protected brush (PB) sampling of mucus plugs. Sputum samples were obtained from six of the nine subjects immediately prior to the procedure. Microbial community analysis was performed on DNA extracted from these samples and the extent of damage in each lobe was quantified from a recent CT scan. The extent of damage observed in regions of the right lung did not correlate with specific microbial genera, levels of community diversity or composition, or bacterial genome copies per ml of BAL fluid. In all subjects, BAL fluid from different regions of the lung contained similar microbial communities. In eight out of nine subjects, PB samples from different regions of the lung were also similar in microbial community composition, and were similar to microbial communities in BAL fluid from the same lobe. Microbial communities in PB samples were more diverse than those in BAL samples, suggesting enrichment of some taxa in mucus plugs. To our knowledge, this study is the first to examine the microbiota in different regions of the CF lung in clinically stable individuals with mild-to-moderate CF-related lung disease.     

Comparison of DNA Extraction Methods in Analysis of Salivary Bacterial Communities

Culture-independent high-throughput sequencing-based methods are widely used to study bacterial communities. Although these approaches are superior to traditional culture-based methods, they introduce bias at the experimental and bioinformatics levels. We assessed the diversity of the human salivary microbiome by pyrosequencing of the 16S rDNA V1–3 amplicons using metagenomic DNA extracted by two different protocols: a simple proteinase K digestion without a subsequent DNA clean-up step, and a bead-beating mechanical lysis protocol followed by column DNA purification. A high degree of congruence was found between the two extraction methods, most notably in regard to the microbial community composition. The results showed that for a given bioinformatics pipeline, all the taxa with an average proportion >0.12% in samples processed using one extraction method were also detected in samples extracted using the other method. The same taxa tended to be abundant and frequent for both extraction methods. The relative abundance of sequence reads assigned to the phyla Actinobacteria, Spirochaetes, TM7, Synergistetes, and Tenericutes was significantly higher in the mechanically-treated samples than in the enzymatically-treated samples, whereas the phylum Firmicutes showed the opposite pattern. No significant differences in diversity indices were found between the extraction methods, although the mechanical lysis method revealed higher operational taxonomic unit richness. Differences between the extraction procedures outweighed the variations due to the bioinformatics analysis pipelines used.     

Cultivation-dependent and -independent approaches for determining bacterial diversity in heavy-metal-contaminated soil

In recent years, culture-independent methods have been used in preference to traditional isolation techniques for microbial community analysis. However, it is questionable whether uncultured organisms from a given sample are important for determining the impact of anthropogenic stress on indigenous communities. To investigate this, soil samples were taken from a site with patchy metal contamination, and the bacterial community structure was assessed with a variety of approaches. There were small differences in microscopic epifluorescence bacterial counts. Denaturing gradient gel electrophoresis (DGGE) profiles of 16S rRNA gene fragments (16S-DGGE) amplified directly from soil samples were highly similar. A clone library generated from the most contaminated sample revealed a diverse bacterial community, which showed similarities to pristine soil communities from other studies. However, the proportion of bacteria from the soil samples that were culturable on standard plate-counting media varied between 0.08 and 2.2%, and these values correlated negatively with metal concentrations. The culturable communities from each sample were compared by 16S-DGGE of plate washes and by fatty acid profiling of individual isolates. Each approach indicated that there were considerable differences between the compositions of the culturable communities from each sample. DGGE bands from both culture-based and culture-independent approaches were sequenced and compared. These data indicated that metal contamination did not have a significant effect on the total genetic diversity present but affected physiological status, so that the number of bacteria capable of responding to laboratory culture and their taxonomic distribution were altered. Thus, it appears that plate counts may be a more appropriate method for determining the effect of heavy metals on soil bacteria than culture-independent approaches.     

Cultivation-Dependent and -Independent Approaches for Determining Bacterial Diversity in Heavy-Metal-Contaminated Soil

In recent years, culture-independent methods have been used in preference to traditional isolation techniques for microbial community analysis. However, it is questionable whether uncultured organisms from a given sample are important for determining the impact of anthropogenic stress on indigenous communities. To investigate this, soil samples were taken from a site with patchy metal contamination, and the bacterial community structure was assessed with a variety of approaches. There were small differences in microscopic epifluorescence bacterial counts. Denaturing gradient gel electrophoresis (DGGE) profiles of 16S rRNA gene fragments (16S-DGGE) amplified directly from soil samples were highly similar. A clone library generated from the most contaminated sample revealed a diverse bacterial community, which showed similarities to pristine soil communities from other studies. However, the proportion of bacteria from the soil samples that were culturable on standard plate-counting media varied between 0.08 and 2.2%, and these values correlated negatively with metal concentrations. The culturable communities from each sample were compared by 16S-DGGE of plate washes and by fatty acid profiling of individual isolates. Each approach indicated that there were considerable differences between the compositions of the culturable communities from each sample. DGGE bands from both culture-based and culture-independent approaches were sequenced and compared. These data indicated that metal contamination did not have a significant effect on the total genetic diversity present but affected physiological status, so that the number of bacteria capable of responding to laboratory culture and their taxonomic distribution were altered. Thus, it appears that plate counts may be a more appropriate method for determining the effect of heavy metals on soil bacteria than culture-independent approaches.     

High-Resolution Taxonomic Profiling of the Subgingival Microbiome for Biomarker Discovery and Periodontitis Diagnosis

The oral microbiome plays a key role for caries, periodontitis, and systemic diseases. A method for rapid, high-resolution, robust taxonomic profiling of subgingival bacterial communities for early detection of periodontitis biomarkers would therefore be a useful tool for individualized medicine. Here, we used Illumina sequencing of the V1-V2 and V5-V6 hypervariable regions of the 16S rRNA gene. A sample stratification pipeline was developed in a pilot study of 19 individuals, 9 of whom had been diagnosed with chronic periodontitis. Five hundred twenty-three operational taxonomic units (OTUs) were obtained from the V1-V2 region and 432 from the V5-V6 region. Key periodontal pathogens like Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia could be identified at the species level with both primer sets. Principal coordinate analysis identified two outliers that were consistently independent of the hypervariable region and method of DNA extraction used. The linear discriminant analysis (LDA) effect size algorithm (LEfSe) identified 80 OTU-level biomarkers of periodontitis and 17 of health. Health- and periodontitis-related clusters of OTUs were identified using a connectivity analysis, and the results confirmed previous studies with several thousands of samples. A machine learning algorithm was developed which was trained on all but one sample and then predicted the diagnosis of the left-out sample (jackknife method). Using a combination of the 10 best biomarkers, 15 of 17 samples were correctly diagnosed. Training the algorithm on time-resolved community profiles might provide a highly sensitive tool to detect the onset of periodontitis.     

Influence of long-term repeated prescribed burning on mycelial communities of ectomycorrhizal fungi

To demonstrate the efficacy of direct DNA extraction from hyphal ingrowth bags for community profiling of ectomycorrhizal (ECM) mycelia in soil, we applied the method to investigate the influence of long-term repeated prescribed burning on an ECM fungal community. DNA was extracted from hyphal ingrowth bags buried in forest plots that received different prescribed burning treatments for 30 yr, and denaturing gradient gel electrophoresis (DGGE) profiles of partial fungal rDNA internal transcribed spacer (ITS) regions were compared. Restriction fragment length polymorphism (RFLP) and sequence analyses were also used to compare clone assemblages between the treatments. The majority of sequences derived from the ingrowth bags were apparently those of ECM fungi. DGGE profiles for biennially burned plots were significantly different from those of quadrennially burned and unburned control plots. Analysis of clone assemblages indicated that this reflected altered ECM fungal community composition. The results indicate that hyphal ingrowth bags represent a useful method for investigation of ECM mycelial communities, and that frequent long-term prescribed burning can influence below-ground ECM fungal communities.     

Impacts of abiotic factors on the fungal communities of ‘Honeycrisp’ apples in Canada

The maintenance of the beneficial plant microbiome to control plant pathogens is an emerging concept of disease management, and necessitates a clear understanding of these microbial communities and the environmental factors that affect their diversity and compositional structure. As such, studies investigating the microbiome of economically significant cultivars within each growing region are necessary to develop adequate disease management strategies. Here, we assessed the relative impacts of growing season, management strategy, and geographical location on the fungal microbiome of ‘Honeycrisp’ apples from seven different orchard locations in the Atlantic Maritime Ecozone for two consecutive growing years. Though apple fruit tissue was dominated by relatively few fungal genera, significant changes in their fungal communities were observed as a result of environmental factors, including shifts in genera with plant-associated lifestyles (symbionts and pathogens), such as Aureobasidium, Alternaria, Penicillium, Diplodia, and Mycosphaerella. Variation in fungal composition between different tissues of fruit was also observed. We demonstrate that growing season is the most significant factor affecting fungal community structure and diversity of apple fruit, suggesting that future microbiome studies should take place for multiple growing seasons to better represent the host–microbiome of perennial crops under different environmental conditions.     

Evaluation of methods for the extraction and purification of DNA from the human microbiome

Background

DNA extraction is an essential step in all cultivation-independent approaches to characterize microbial diversity, including that associated with the human body. A fundamental challenge in using these approaches has been to isolate DNA that is representative of the microbial community sampled.

Methodology/Principal Findings

In this study, we statistically evaluated six commonly used DNA extraction procedures using eleven human-associated bacterial species and a mock community that contained equal numbers of those eleven species. These methods were compared on the basis of DNA yield, DNA shearing, reproducibility, and most importantly representation of microbial diversity. The analysis of 16S rRNA gene sequences from a mock community showed that the observed species abundances were significantly different from the expected species abundances for all six DNA extraction methods used.

Conclusions/Significance

Protocols that included bead beating and/or mutanolysin produced significantly better bacterial community structure representation than methods without both of them. The reproducibility of all six methods was similar, and results from different experimenters and different times were in good agreement. Based on the evaluations done it appears that DNA extraction procedures for bacterial community analysis of human associated samples should include bead beating and/or mutanolysin to effectively lyse cells.