Optimizing the analysis of human intestinal microbiota with phylogenetic microarray

Phylogenetic microarrays present an attractive strategy to high-throughput interrogation of complex microbial communities. In this work, we present several approaches to optimize the analysis of intestinal microbiota with the recently developed Microbiota Array. First, we determined how 16S rDNA-specific PCR amplification influenced bacterial detection and the consistency of measured abundance values. Bacterial detection improved with an increase in the number of PCR amplification cycles, but 25 cycles were sufficient to achieve the maximum possible detection. A PCR-caused deviation in the measured abundance values was also observed. We also developed two mathematical algorithms that aimed to account for a predicted cross-hybridization of 16S rDNA fragments among different species, and to adjust the measured hybridization signal based on the number of 16S rRNA gene copies per species genome. The 16S rRNA gene copy adjustment indicated that the presence of members of the class Clostridia might be overestimated in some 16S rDNA-based studies. Finally, we show that the examination of total community RNA with phylogenetic microarray can provide estimates of the relative metabolic activity of individual community members. Complementary profiling of genomic DNA and total RNA isolated from the same sample presents an opportunity to assess population structure and activity in the same microbial community.     

Mathematical modeling of 16S ribosomal DNA amplification reveals optimal conditions for the interrogation of complex microbial communities with phylogenetic microarrays

MOTIVATION: Many current studies of complex microbial communities rely on the isolation of community genomic DNA, amplification of 16S ribosomal RNA genes (rDNA) and subsequent examination of community structure through interrogation of the amplified 16S rDNA pool by high-throughput sequencing, phylogenetic microarrays or quantitative PCR. RESULTS: Here we describe the development of a mathematical model aimed to simulate multitemplate amplification of 16S ribosomal DNA sample and subsequent detection of these amplified 16S rDNA species by phylogenetic microarray. Using parameters estimated from the experimental results obtained in the analysis of intestinal microbial communities with Microbiota Array, we show that both species detection and the accuracy of species abundance estimates depended heavily on the number of PCR cycles used to amplify 16S rDNA. Both parameters initially improved with each additional PCR cycle and reached optimum between 15 and 20 cycles of amplification. The use of more than 20 cycles of PCR amplification and/or more than 50 ng of starting genomic DNA template was, however, detrimental to both the fraction of detected community members and the accuracy of abundance estimates. Overall, the outcomes of the model simulations matched well available experimental data. Our simulations also showed that species detection and the accuracy of abundance measurements correlated positively with the higher sample-wide PCR amplification rate, lower template-to-template PCR bias and lower number of species in the interrogated community. The developed model can be easily modified to simulate other multitemplate DNA mixtures as well as other microarray designs and PCR amplification protocols.     

Semi-automated extraction of microbial DNA from feces for qPCR and phylogenetic microarray analysis

The human gastrointestinal tract (GI-tract) harbors a complex microbial ecosystem, largely composed of so far uncultured species, which can be detected only by using techniques such as PCR and by different hybridization techniques including phylogenetic microarrays. Manual DNA extraction from feces is laborious and is one of the bottlenecks holding up the application of microarray and other DNA-based techniques in large cohort studies. In order to enhance the DNA extraction step we combined mechanical disruption of microbial cells by repeated bead-beating (RBB) with two automated DNA extraction methods, KingFisher with InviMag Stool DNA kit (KF) and NucliSENS easyMAG (NeM). The semi-automated DNA extraction methods, RBB combined with either KF or NeM, were compared to the manual extraction method currently considered the most suited method for fecal DNA extraction by assessing the yield of 16S rRNA gene copies by qPCR and total microbiota composition by the HITChip, a phylogenetic microarray. Parallel DNA extractions from infant fecal samples by using the three methods showed that the KF and manual methods gave comparable yields of 16S rRNA gene copies as assessed by qPCR, whereas NeM showed a significantly lower yield. All three methods showed highly similar microbiota profiles in HITChip. Both KF and NeM were found to be suitable methods for DNA extraction from fecal samples after the mechanical disruption of microbial cells by bead-beating. The semi-automated methods could be performed in half of the time required for the manual protocol, while being comparable to the manual method in terms of reagent costs.     

mRNA-Based Parallel Detection of Active Methanotroph Populations by Use of a Diagnostic Microarray

A method was developed for the mRNA-based application of microbial diagnostic microarrays to detect active microbial populations. DNA- and mRNA-based analyses of environmental samples were compared and confirmed via quantitative PCR. Results indicated that mRNA-based microarray analyses may provide additional information on the composition and functioning of microbial communities.     

mRNA-based parallel detection of active methanotroph populations by use of a diagnostic microarray

A method was developed for the mRNA-based application of microbial diagnostic microarrays to detect active microbial populations. DNA- and mRNA-based analyses of environmental samples were compared and confirmed via quantitative PCR. Results indicated that mRNA-based microarray analyses may provide additional information on the composition and functioning of microbial communities.     

Diagnostic microbial microarrays in soil ecology

Soil microbial communities are responsible for important physiological and metabolic processes. In the last decade soil microorganisms have been frequently analysed by cultivation-independent techniques because only a minority of the natural microbial communities are accessible by cultivation. Cultivation-independent community analyses have revolutionized our understanding of soil microbial diversity and population dynamics. Nevertheless, many methods are still laborious and time-consuming, and high-throughput methods have to be applied in order to understand population shifts at a finer level and to be better able to link microbial diversity with ecosystems functioning. Microbial diagnostic microarrays (MDMs) represent a powerful tool for the parallel, high-throughput identification of many microorganisms. Three categories of MDMs have been defined based on the nature of the probe and target molecules used: phylogenetic oligonucleotide microarrays with short oligonucleotides against a phylogenetic marker gene; functional gene arrays containing probes targeting genes encoding specific functions; and community genome arrays employing whole genomes as probes. In this review, important methodological developments relevant to the application of the different types of diagnostic microarrays in soil ecology will be addressed and new approaches, needs and future directions will be identified, which might lead to a better insight into the functional activities of soil microbial communities.     

Microarray analysis and barcoded pyrosequencing provide consistent microbial profiles depending on the source of human intestinal samples

Large-scale and in-depth characterization of the intestinal microbiota necessitates application of high-throughput 16S rRNA gene-based technologies, such as barcoded pyrosequencing and phylogenetic microarray analysis. In this study, the two techniques were compared and contrasted for analysis of the bacterial composition in three fecal and three small intestinal samples from human individuals. As PCR remains a crucial step in sample preparation for both techniques, different forward primers were used for amplification to assess their impact on microbial profiling results. An average of 7,944 pyrosequences, spanning the V1 and V2 region of 16S rRNA genes, was obtained per sample. Although primer choice in barcoded pyrosequencing did not affect species richness and diversity estimates, detection of Actinobacteria strongly depended on the selected primer. Microbial profiles obtained by pyrosequencing and phylogenetic microarray analysis (HITChip) correlated strongly for fecal and ileal lumen samples but were less concordant for ileostomy effluent. Quantitative PCR was employed to investigate the deviations in profiling between pyrosequencing and HITChip analysis. Since cloning and sequencing of random 16S rRNA genes from ileostomy effluent confirmed the presence of novel intestinal phylotypes detected by pyrosequencing, especially those belonging to the Veillonella group, the divergence between pyrosequencing and the HITChip is likely due to the relatively low number of available 16S rRNA gene sequences of small intestinal origin in the DNA databases that were used for HITChip probe design. Overall, this study demonstrated that equivalent biological conclusions are obtained by high-throughput profiling of microbial communities, independent of technology or primer choice.     

Microarray Applications in Microbial Ecology Research

Microarray technology has the unparalleled potential to simultaneously determine the dynamics and/or activities of most, if not all, of the microbial populations in complex environments such as soils and sediments. Researchers have developed several types of arrays that characterize the microbial populations in these samples based on their phylogenetic relatedness or functional genomic content. Several recent studies have used these microarrays to investigate ecological issues; however, most have only analyzed a limited number of samples with relatively few experiments utilizing the full high-throughput potential of microarray analysis. This is due in part to the unique analytical challenges that these samples present with regard to sensitivity, specificity, quantitation, and data analysis. This review discusses specific applications of microarrays to microbial ecology research along with some of the latest studies addressing the difficulties encountered during analysis of complex microbial communities within environmental samples. With continued development, microarray technology may ultimately achieve its potential for comprehensive, high-throughput characterization of microbial populations in near real time.

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Homogeneous versus heterogeneous probes for microbial ecological microarrays

Microbial ecological microarrays have been developed for investigating the composition and functions of microorganism communities in environmental niches. These arrays include microbial identification microarrays, which use oligonucleotides, gene fragments or microbial genomes as probes. In this article, the advantages and disadvantages of each type of probe are reviewed. Oligonucleotide probes are currently useful for probing uncultivated bacteria that are not amenable to gene fragment probing, whereas the functional gene fragments amplified randomly from microbial genomes require phylogenetic and hierarchical categorization before use as microbial identification probes, despite their high resolution for both specificity and sensitivity. Until more bacteria are sequenced and gene fragment probes are thoroughly validated, heterogeneous bacterial genome probes will provide a simple, sensitive and quantitative tool for exploring the ecosystem structure.     

Rapid quantitative profiling of complex microbial populations

Diverse and complex microbial ecosystems are found in virtually every environment on earth, yet we know very little about their composition and ecology. Comprehensive identification and quantification of the constituents of these microbial communities—a ‘census’—is an essential foundation for understanding their biology. To address this problem, we developed, tested and optimized a DNA oligonucleotide microarray composed of 10 462 small subunit (SSU) ribosomal DNA (rDNA) probes (7167 unique sequences) selected to provide quantitative information on the taxonomic composition of diverse microbial populations. Using our optimized experimental approach, this microarray enabled detection and quantification of individual bacterial species present at fractional abundances of <0.1% in complex synthetic mixtures. The estimates of bacterial species abundance obtained using this microarray are similar to those obtained by phylogenetic analysis of SSU rDNA sequences from the same samples—the current ‘gold standard’ method for profiling microbial communities. Furthermore, probes designed to represent higher order taxonomic groups of bacterial species reliably detected microbes for which there were no species-specific probes. This simple, rapid microarray procedure can be used to explore and systematically characterize complex microbial communities, such as those found within the human body.     

Novel Polyfermentor Intestinal Model (PolyFermS) for Controlled Ecological Studies: Validation and Effect of pH

In vitro gut fermentation modeling offers a useful platform for ecological studies of the intestinal microbiota. In this study we describe a novel Polyfermentor Intestinal Model (PolyFermS) designed to compare the effects of different treatments on the same complex gut microbiota. The model operated in conditions of the proximal colon is composed of a first reactor containing fecal microbiota immobilized in gel beads, and used to continuously inoculate a set of parallel second-stage reactors. The PolyFermS model was validated with three independent intestinal fermentations conducted for 38 days with immobilized human fecal microbiota obtained from three child donors. The microbial diversity of reactor effluents was compared to donor feces using the HITChip, a high-density phylogenetic microarray targeting small subunit rRNA sequences of over 1100 phylotypes of the human gastrointestinal tract. Furthermore, the metabolic response to a decrease of pH from 5.7 to 5.5, applied to balance the high fermentative activity in inoculum reactors, was studied. We observed a reproducible development of stable intestinal communities representing major taxonomic bacterial groups at ratios similar to these in feces of healthy donors, a high similarity of microbiota composition produced in second-stage reactors within a model, and a high time stability of microbiota composition and metabolic activity over 38 day culture. For all tested models, the pH-drop of 0.2 units in inoculum reactors enhanced butyrate production at the expense of acetate, but was accompanied by a donor-specific reorganization of the reactor community, suggesting a concerted metabolic adaptation and trigger of community-specific lactate or acetate cross-feeding pathways in response to varying pH. Our data showed that the PolyFermS model allows the stable cultivation of complex intestinal microbiota akin to the fecal donor and can be developed for the direct comparison of different experimental conditions in parallel reactors continuously inoculated with the exact same microbiota.     

Phylogenetic Specificity and Reproducibility and New Method for Analysis of Terminal Restriction Fragment Profiles of 16S rRNA Genes from Bacterial Communities

Terminal restriction fragment (TRF) analysis of 16S rRNA genes is an increasingly popular method for rapid comparison of microbial communities, but analysis of the data is still in a developmental stage. We assessed the phylogenetic resolution and reproducibility of TRF profiles in order to evaluate the limitations of the method, and we developed an essential analysis technique to improve the interpretation of TRF data. The theoretical phylogenetic resolution of TRF profiles was determined based on the specificity of TRFs predicted from 3,908 16S rRNA gene sequences. With sequences from the Proteobacteria or gram-positive division, as much as 73% of the TRFs were phylogenetically specific (representing strains from at most two genera). However, the fraction decreased when sequences from the two divisions were combined. The data show that phylogenetic inference will be most effective if TRF profiles represent only a single bacterial division or smaller group. The analytical precision of the TRF method was assessed by comparing nine replicate profiles of a single soil DNA sample. Despite meticulous care in producing the replicates, numerous small, irreproducible peaks were observed. As many as 85% of the 169 distinct TRFs found among the profiles were irreproducible (i.e., not present in all nine replicates). Substantial variation also occurred in the height of synonymous peaks. To make comparisons of microbial communities more reliable, we developed an analytical procedure that reduces variation and extracts a reproducible subset of data from replicate TRF profiles. The procedure can also be used with other DNA fingerprinting techniques for microbial communities or microbial genomes.     

The next generation of microarray research: applications in evolutionary and ecological genomics

Microarray technology is one of the key developments in recent years that has propelled biological research into the post-genomic era. With the ability to assay thousands to millions of features at the same time, microarray technology has fundamentally changed how biological questions are addressed, from examining one or a few genes to a collection of genes or the whole genome. This technology has much to offer in the study of genome evolution. After a brief introduction on the technology itself, we then focus on the use of microarrays to examine genome dynamics, to uncover novel functional elements in genomes, to unravel the evolution of regulatory networks, to identify genes important for behavioral and phenotypic plasticity, and to determine microbial community diversity in environmental samples. Although there are still practical issues in using microarrays, they will be alleviated by rapid advances in array technology and analysis methods, the availability of many genome sequences of closely related species and flexibility in array design. It is anticipated that the application of microarray technology will continue to better our understanding of evolution and ecology through the examination of individuals, populations, closely related species or whole microbial communities.     

Phylogenetic specificity and reproducibility and new method for analysis of terminal restriction fragment profiles of 16S rRNA genes from bacterial communities

Terminal restriction fragment (TRF) analysis of 16S rRNA genes is an increasingly popular method for rapid comparison of microbial communities, but analysis of the data is still in a developmental stage. We assessed the phylogenetic resolution and reproducibility of TRF profiles in order to evaluate the limitations of the method, and we developed an essential analysis technique to improve the interpretation of TRF data. The theoretical phylogenetic resolution of TRF profiles was determined based on the specificity of TRFs predicted from 3,908 16S rRNA gene sequences. With sequences from the Proteobacteria or gram-positive division, as much as 73% of the TRFs were phylogenetically specific (representing strains from at most two genera). However, the fraction decreased when sequences from the two divisions were combined. The data show that phylogenetic inference will be most effective if TRF profiles represent only a single bacterial division or smaller group. The analytical precision of the TRF method was assessed by comparing nine replicate profiles of a single soil DNA sample. Despite meticulous care in producing the replicates, numerous small, irreproducible peaks were observed. As many as 85% of the 169 distinct TRFs found among the profiles were irreproducible (i.e., not present in all nine replicates). Substantial variation also occurred in the height of synonymous peaks. To make comparisons of microbial communities more reliable, we developed an analytical procedure that reduces variation and extracts a reproducible subset of data from replicate TRF profiles. The procedure can also be used with other DNA fingerprinting techniques for microbial communities or microbial genomes.     

Intestinal microbiota in healthy adults: temporal analysis reveals individual and common core and relation to intestinal symptoms

Background

While our knowledge of the intestinal microbiota during disease is accumulating, basic information of the microbiota in healthy subjects is still scarce. The aim of this study was to characterize the intestinal microbiota of healthy adults and specifically address its temporal stability, core microbiota and relation with intestinal symptoms. We carried out a longitudinal study by following a set of 15 healthy Finnish subjects for seven weeks and regularly assessed their intestinal bacteria and archaea with the Human Intestinal Tract (HIT)Chip, a phylogenetic microarray, in conjunction with qPCR analyses. The health perception and occurrence of intestinal symptoms was recorded by questionnaire at each sampling point.

Principal Findings

A high overall temporal stability of the microbiota was observed. Five subjects showed transient microbiota destabilization, which correlated not only with the intake of antibiotics but also with overseas travelling and temporary illness, expanding the hitherto known factors affecting the intestinal microbiota. We identified significant correlations between the microbiota and common intestinal symptoms, including abdominal pain and bloating. The most striking finding was the inverse correlation between Bifidobacteria and abdominal pain: subjects who experienced pain had over five-fold less Bifidobacteria compared to those without pain. Finally, a novel computational approach was used to define the common core microbiota, highlighting the role of the analysis depth in finding the phylogenetic core and estimating its size. The in-depth analysis suggested that we share a substantial number of our intestinal phylotypes but as they represent highly variable proportions of the total community, many of them often remain undetected.

Conclusions/Significance

A global and high-resolution microbiota analysis was carried out to determine the temporal stability, the associations with intestinal symptoms, and the individual and common core microbiota in healthy adults. The findings provide new approaches to define intestinal health and to further characterize the microbial communities inhabiting the human gut.     

Diversity of the human gastrointestinal tract microbiota revisited

Since the early days of microbiology, more than a century ago, representatives of over 400 different microbial species have been isolated and fully characterized from human gastrointestinal samples. However, during the past decade molecular ecological studies based on ribosomal RNA (rRNA) sequences have revealed that cultivation has been able only to access a small fraction of the microbial diversity within the gastrointestinal tract. The increasing number of deposited rRNA sequences calls for the setting up a curated database that allows handling of the excessive degree of redundancy that threatens the usability of public databases. The integration of data from cultivation-based studies and molecular inventories of small subunit (SSU) rRNA diversity, presented here for the first time, provides a systematic framework of the microbial diversity in the human gastrointestinal tract of more than 1000 different species-level phylogenetic types (phylotypes). Such knowledge is essential for the design of high-throughput approaches such as phylogenetic DNA microarrays for the comprehensive analysis of gastrointestinal tract microbiota at multiple levels of taxonomic resolution. Development of such approaches is likely to be pivotal to generating novel insights in microbiota functionality in health and disease.     

The bacterial community in the gut of the Cockroach Shelfordella lateralis reflects the close evolutionary relatedness of cockroaches and termites

Termites and cockroaches are closely related, with molecular phylogenetic analyses even placing termites within the radiation of cockroaches. The intestinal tract of wood-feeding termites harbors a remarkably diverse microbial community that is essential for the digestion of lignocellulose. However, surprisingly little is known about the gut microbiota of their closest relatives, the omnivorous cockroaches. Here, we present a combined characterization of physiological parameters, metabolic activities, and bacterial microbiota in the gut of Shelfordella lateralis, a representative of the cockroach family Blattidae, the sister group of termites. We compared the bacterial communities within each gut compartment using terminal-restriction fragment length polymorphism (T-RFLP) analysis and made a 16S rRNA gene clone library of the microbiota in the colon-the dilated part of the hindgut with the highest density and diversity of bacteria. The colonic community was dominated by members of the Bacteroidetes, Firmicutes (mainly Clostridia), and some Deltaproteobacteria. Spirochaetes and Fibrobacteres, which are abundant members of termite gut communities, were conspicuously absent. Nevertheless, detailed phylogenetic analysis revealed that many of the clones from the cockroach colon clustered with sequences previously obtained from the termite gut, which indicated that the composition of the bacterial community reflects at least in part the phylogeny of the host.     

Unravelling Microbial Communities with DNA-Microarrays: Challenges and Future Directions

High-throughput technologies are urgently needed for monitoring the formidable biodiversity and functional capabilities of microorganisms in the environment. Ten years ago, DNA microarrays, miniaturized platforms for highly parallel hybridization reactions, found their way into environmental microbiology and raised great expectations among researchers in the field. In this article, we briefly summarize the state-of-the-art of microarray approaches in microbial ecology research and discuss in more detail crucial problems and promising solutions. Finally, we outline scenarios for an innovative combination of microarrays with other molecular tools for structure-function analysis of complex microbial communities.     

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.     

Phylogenetic and Metabolic Tracking of Gut Microbiota during Perinatal Development

The colonization and development of gut microbiota immediately after birth is highly variable and depends on several factors, such as delivery mode and modality of feeding during the first months of life. A cohort of 31 mother and neonate pairs, including 25 at-term caesarean (CS) and 6 vaginally (V) delivered neonates (DNs), were included in this study and 121 meconium/faecal samples were collected at days 1 through 30 following birth. Operational taxonomic units (OTUs) were assessed in 69 stool samples by phylogenetic microarray HITChip and inter- and intra-individual distributions were established by inter-OTUs correlation matrices and OTUs co-occurrence or co-exclusion networks. ¹H-NMR metabolites were determined in 70 stool samples, PCA analysis was performed on 55 CS DNs samples, and metabolome/OTUs co-correlations were assessed in 45 CS samples, providing an integrated map of the early microbiota OTUs-metabolome. A microbiota “core” of OTUs was identified that was independent of delivery mode and lactation stage, suggesting highly specialized communities that act as seminal colonizers of microbial networks. Correlations among OTUs, metabolites, and OTUs-metabolites revealed metabolic profiles associated with early microbial ecological dynamics, maturation of milk components, and host physiology.