Unravelling microbial communities with DNA-microarrays: challenges and future directions

Bacteriophage-based biosensors for detection of pathogenic microbes in wastewater

Wastewater is discarded from several sources, including industry, livestock, fertilizer application, and municipal waste. If the disposed of wastewater has not been treated and processed before discharge to the environment, pathogenic microorganisms and toxic chemicals are accumulated in the disposal area and transported into the surface waters. The presence of harmful microbes is responsible for thousands of human deaths related to water-born contamination every year. To be able to take the necessary step and quick action against the possible presence of harmful microorganisms and substances, there is a need to improve the effective speed of identification and treatment of these problems. Biosensors are such devices that can give quantitative information within a short period of time. There have been several biosensors developed to measure certain parameters and microorganisms. The discovered biosensors can be utilized for the detection of axenic and mixed microbial strains from the wastewaters. Biosensors can further be developed for specific conditions and environments with an in-depth understanding of microbial organization and interaction within that community. In this regard, bacteriophage-based biosensors have become a possibility to identify specific live bacteria in an infected environment. This paper has investigated the current scenario of microbial community analysis and biosensor development in identifying the presence of pathogenic microorganisms.

Current State and Challenges of the Global Outcomes of Dental Caries Research in the Meta-Omics Era

Despite significant healthcare advances in the 21st century, the exact etiology of dental caries remains unsolved. The past two decades have witnessed a tremendous growth in our understanding of dental caries amid the advent of revolutionary omics technologies. Accordingly, a consensus has been reached that dental caries is a community-scale metabolic disorder, and its etiology is beyond a single causative organism. This conclusion was based on a variety of microbiome studies following the flow of information along the central dogma of biology from genomic data to the end products of metabolism. These studies were facilitated by the unprecedented growth of the next- generation sequencing tools and omics techniques, such as metagenomics and metatranscriptomics, to estimate the community composition of oral microbiome and its functional potential. Furthermore, the rapidly evolving proteomics and metabolomics platforms, including nuclear magnetic resonance spectroscopy and/or mass spectrometry coupled with chromatography, have enabled precise quantification of the translational outcomes. Although the majority supports 'conserved functional changes' as indicators of dysbiosis, it remains unclear how caries dynamics impact the microbiota functions and vice versa, over the course of disease onset and progression. What compounds the situation is the host-microbiota crosstalk. Genome-wide association studies have been undertaken to elucidate the interaction of host genetic variation with the microbiome. However, these studies are challenged by the complex interaction of host genetics and environmental factors. All these complementary approaches need to be orchestrated to capture the key players in this multifactorial disease. Herein, we critically review the milestones in caries research focusing on the state-of-art singular and integrative omics studies, supplemented with a bibliographic network analysis to address the oral microbiome, the host factors, and their interactions. Additionally, we highlight gaps in the dental literature and shed light on critical future research questions and study designs that could unravel the complexities of dental caries, the most globally widespread disease.

Molecular Methods for Assessment of Antibiotic Resistance in Agricultural Ecosystems: Prospects and Challenges

Agricultural ecosystems are of special interest for monitoring the potential for antibiotic resistance to spread through the environment and contribute to human exposure. Molecular methods, which target DNA, RNA, and other molecular components of bacterial cells, present certain advantages for characterizing and quantifying markers of antibiotic resistance and their horizontal gene transfer. These include rapid, unambiguous detection of targets; consistent results; and avoidance of culture bias. However, molecular methods are also subject to limitations that are not always clearly addressed or taken into consideration in the interpretation of scientific data. In particular, DNA-based methods do not directly assess viability or presence within an intact bacterial host, but such information may be inferred based on appropriate experimental design or in concert with complementary methods. The purpose of this review is to provide an overview of existing molecular methods for tracking antibiotic resistance in agricultural ecosystems, to define their strengths and weaknesses, and to recommend a path forward for future applications of molecular methods and standardized reporting in the literature. This will guide research along the farm-to-fork continuum and support comparability of the growing number of studies in the literature in a manner that informs management decisions and policy development.

Probe Design Strategies for Oligonucleotide Microarrays

Oligonucleotide microarrays have been widely used for gene detection and/or quantification of gene expression in various samples ranging from a single organism to a complex microbial assemblage. The success of a microarray experiment, however, strongly relies on the quality of designed probes. Consequently, probe design is of critical importance and therefore multiple parameters should be considered for each probe in order to ensure high specificity, sensitivity, and uniformity as well as potentially quantitative power. Moreover, to assess the complete gene repertoire of complex biological samples such as those studied in the field of microbial ecology, exploratory probe design strategies must be also implemented to target not-yet-described sequences. To design such probes, two algorithms, KASpOD and HiSpOD, have been developed and they are available via two user-friendly web services. Here, we describe the use of this software necessary for the design of highly effective probes especially in the context of microbial oligonucleotide microarrays by taking into account all the crucial parameters.

Molecular techniques revealed highly diverse microbial communities in natural marine biofilms on polystyrene dishes for invertebrate larval settlement

Biofilm microbial communities play an important role in the larval settlement response of marine invertebrates. However, the underlying mechanism has yet to be resolved, mainly because of the uncertainties in characterizing members in the communities using traditional 16S rRNA gene-based molecular methods and in identifying the chemical signals involved. In this study, pyrosequencing was used to characterize the bacterial communities in intertidal and subtidal marine biofilms developed during two seasons. We revealed highly diverse biofilm bacterial communities that varied with season and tidal level. Over 3,000 operational taxonomic units with estimates of up to 8,000 species were recovered in a biofilm sample, which is by far the highest number recorded in subtropical marine biofilms. Nineteen phyla were found, of which Cyanobacteria and Proteobacteria were the most dominant one in the intertidal and subtidal biofilms, respectively. Apart from these, Actinobacteria, Bacteroidetes, and Planctomycetes were the major groups recovered in both intertidal and subtidal biofilms, although their relative abundance varied among samples. Full-length 16S rRNA gene clone libraries were constructed for the four biofilm samples and showed similar bacterial compositions at the phylum level to those revealed by pyrosequencing. Laboratory assays confirmed that cyrids of the barnacle Balanus amphitrite preferred to settle on the intertidal rather than subtidal biofilms. This preference was independent of the biofilm bacterial density or biomass but was probably related to the biofilm community structure, particularly, the Proteobacterial and Cyanobacterial groups.

Large scale explorative oligonucleotide probe selection for thousands of genetic groups on a computing grid: application to phylogenetic probe design using a curated small subunit ribosomal RNA gene database

Phylogenetic Oligonucleotide Arrays (POAs) were recently adapted for studying the huge microbial communities in a flexible and easy-to-use way. POA coupled with the use of explorative probes to detect the unknown part is now one of the most powerful approaches for a better understanding of microbial community functioning. However, the selection of probes remains a very difficult task. The rapid growth of environmental databases has led to an exponential increase of data to be managed for an efficient design. Consequently, the use of high performance computing facilities is mandatory. In this paper, we present an efficient parallelization method to select known and explorative oligonucleotide probes at large scale using computing grids. We implemented a software that generates and monitors thousands of jobs over the European Computing Grid Infrastructure (EGI). We also developed a new algorithm for the construction of a high-quality curated phylogenetic database to avoid erroneous design due to bad sequence affiliation. We present here the performance and statistics of our method on real biological datasets based on a phylogenetic prokaryotic database at the genus level and a complete design of about 20,000 probes for 2,069 genera of prokaryotes.

GPR-Analyzer: a simple tool for quantitative analysis of hierarchical multispecies microarrays

Monitoring of marine microalgae is important to predict and manage harmful algae blooms. It currently relies mainly on light-microscopic identification and enumeration of algal cells, yet several molecular tools are currently being developed to complement traditional methods. MIcroarray Detection of Toxic ALgae (MIDTAL) is an FP7-funded EU project aiming to establish a hierarchical multispecies microarray as one of these tools. Prototype arrays are currently being tested with field samples, yet the analysis of the large quantities of data generated by these arrays presents a challenge as suitable analysis tools or protocols are scarce. This paper proposes a two-part protocol for the analysis of the MIDTAL and other hierarchical multispecies arrays: Signal-to-noise ratios can be used to determine the presence or absence of signals and to identify potential false-positives considering parallel and hierarchical probes. In addition, normalized total signal intensities are recommended for comparisons between microarrays and in order to relate signals for specific probes to cell concentrations using external calibration curves. Hybridization- and probe-specific detection limits can be calculated to help evaluate negative results. The suggested analyses were implemented in "GPR-Analyzer", a platform-independent and graphical user interface-based application, enabling non-specialist users to quickly and quantitatively analyze hierarchical multispecies microarrays. It is available online at http://folk.uio.no/edvardse/gpranalyzer .

Archaeal community dynamics and abiotic characteristics in a mesophilic anaerobic co-digestion process treating fruit and vegetable processing waste sludge with chopped fresh artichoke waste

This study evaluated the feasibility of obtaining methane in anaerobic digestion (AD) from the waste products generated by the processing of fruit and vegetables. During the first phase (0-55 d) of the AD using sludge from fruit and vegetable processing, an average value of 244±88 L kg(-1) dry matter d(-1)of biogas production was obtained, and methane content reached 65% of the biogas. Co-digestion with chopped fresh artichoke wastes in a second phase (55-71 d) enhanced biogas production, and resulted in an average value of 354±68 L kg(-1) dry matter d(-1), with higher methane content (more than 70%). The archaeal community involved in methane production was studied using the ANAEROCHIP microarray and real-time PCR. Results indicated that species of Methanosaeta and Methanosarcina were important during the AD process. Methanosarcina numbers increased after the addition of chopped fresh artichoke, while Methanosaeta numbers decreased.

A low-cost, label-free DNA detection method in lab-on-chip format based on electrohydrodynamic instabilities, with application to long-range PCR

In order to evolve from a "chip in the lab" to a "lab on a chip" paradigm, there is still a strong demand for low-cost, portable detection technologies, notably for analytes at low concentrations. Here we report a new label-free DNA detection method with direct electronic read, and apply it to long-range PCR. This method uses a nonlinear electrohydrodynamic phenomenon: when subjected to high electric fields (typically above 100 V cm(-1)), suspensions of large polyelectrolytes, such as long DNA molecules, create "giant" dynamic concentration fluctuations. These fluctuations are associated with large conductivity inhomogeneities, and we use here a contact-mode local conductivity detector to detect these fluctuations. In order to decouple the detection electronics from the high voltage excitation one, an original "doubly symmetric" floating mode battery-operated detection scheme was developed. A wavelet analysis was then applied, to unravel from the chaotic character of the electohydrodynamic instabilities a scalar signal robustly reflecting the amplification of DNA. As a first proof of concept, we measured the products of the off-chip amplification of 10 kbp DNA from lambda phage DNA, achieving a sensitivity better than 100 fg DNA in the original 50 μl sample. This corresponds to the amplification products of less than 100 initial copies of target DNA. The companion enabling technologies developed to implement this new concept, i.e. the doubly symmetric contact conductivity detection and wavelet analysis, may also find various other applications in lab-on-chips.

KASpOD--a web service for highly specific and explorative oligonucleotide design

SUMMARY

KASpOD is a web service dedicated to the design of signature sequences using a k-mer-based algorithm. Such highly specific and explorative oligonucleotides are then suitable for various goals, including Phylogenetic Oligonucleotide Arrays.

AVAILABILITY

http://g2im.u-clermont1.fr/kaspod.

CONTACT

eric.peyretaillade@udamail.fr

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Introducing GUt low-density array (GULDA): a validated approach for qPCR-based intestinal microbial community analysis

Alterations in the human gut microbiota caused, for example, by diet, functional foods, antibiotics, or occurring as a function of age are now known to be of relevance for host health. Therefore, there is a strong need for methods to detect such alterations in a rapid and comprehensive manner. In the present study, we developed and validated a high-throughput real-time quantitative PCR-based analysis platform, termed 'GUt Low-Density Array' (GULDA). The platform was designed for simultaneous analysis of the change in the abundance of 31 different microbial 16S rRNA gene targets in fecal samples obtained from individuals at various points in time. The target genes represent important phyla, genera, species, or other taxonomic groups within the five predominant bacterial phyla of the gut, Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria, and Verrucomicrobia and also Euryarchaeota. To demonstrate the applicability of GULDA, analysis of fecal samples obtained from six healthy infants at both 9 and 18 months of age was performed and showed a significant increase over time of the relative abundance of bacteria belonging to Clostridial cluster IV (Clostridia leptum group) and Bifidobacterium bifidum and concurrent decrease in the abundance of Clostridium butyricum and a tendency for decrease in Enterobacteriaceae over the 9-month period.

Modeling formamide denaturation of probe-target hybrids for improved microarray probe design in microbial diagnostics

Application of high-density microarrays to the diagnostic analysis of microbial communities is challenged by the optimization of oligonucleotide probe sensitivity and specificity, as it is generally unfeasible to experimentally test thousands of probes. This study investigated the adjustment of hybridization stringency using formamide with the idea that sensitivity and specificity can be optimized during probe design if the hybridization efficiency of oligonucleotides with target and non-target molecules can be predicted as a function of formamide concentration. Sigmoidal denaturation profiles were obtained using fluorescently labeled and fragmented 16S rRNA gene amplicon of Escherichia coli as the target with increasing concentrations of formamide in the hybridization buffer. A linear free energy model (LFEM) was developed and microarray-specific nearest neighbor rules were derived. The model simulated formamide melting with a denaturant m-value that increased hybridization free energy (ΔG°) by 0.173 kcal/mol per percent of formamide added (v/v). Using the LFEM and specific probe sets, free energy rules were systematically established to predict the stability of single and double mismatches, including bulged and tandem mismatches. The absolute error in predicting the position of experimental denaturation profiles was less than 5% formamide for more than 90 percent of probes, enabling a practical level of accuracy in probe design. The potential of the modeling approach for probe design and optimization is demonstrated using a dataset including the 16S rRNA gene of Rhodobacter sphaeroides as an additional target molecule. The LFEM and thermodynamic databases were incorporated into a computational tool (ProbeMelt) that is freely available at http://DECIPHER.cee.wisc.edu.

Analysis of the microbial gene landscape and transcriptome for aromatic pollutants and alkane degradation using a novel internally calibrated microarray system

Despite various efforts to develop tools to detect and compare the catabolic potential and activity for pollutant degradation in environmental samples, there is still a need for an open-source, curated and reliable array method. We developed a custom array system including a novel normalization strategy that can be applied to any microarray design, allowing the calculation of the reliability of signals and make cross-experimental comparisons. Array probes, which are fully available to the scientific community, were designed from knowledge-based curated databases for key aromatic catabolic gene families and key alkane degradation genes. This design assigns signals to the respective protein subfamilies, thus directly inferring function and substrate specificity. Experimental procedures were optimized using DNA of four genome sequenced biodegradation strains and reliability of signals assessed through a novel normalization procedure, where a plasmid containing four artificial targets in increased copy numbers and co-amplified with the environmental DNA served as an internal calibration curve. The array system was applied to assess the catabolic gene landscape and transcriptome of aromatic contaminated environmental samples, confirming the abundance of catabolic gene subfamilies previously detected by functional metagenomics but also revealing the presence of previously undetected catabolic groups and specifically their expression under pollutant stress.

Use of DGGE and COMPOCHIP for investigating bacterial communities of various vermicomposts produced from different wastes under dissimilar conditions

This study describes the use of denaturing gradient gel electrophoresis (DGGE) and COMPOCHIP (i.e. a microarray targeting typical bacteria of stabilized organic materials and pathogenic bacteria) for investigating the bacterial communities of four different vermicomposts. These included a commercial vermicompost produced from cattle manure (CM) and three vermicomposts produced at pilot-scale by recycling: damaged tomato fruits (DT); olive-mill waste mixed with biosolids (OB); and winery wastes (WW). DGGE provided distinctive fingerprints of each vermicompost, which were statistically related to their particular chemical features. The comparison of the various vermicompost fingerprints showed that they contained bacterial communities with an average similarity coefficient of close to 80%. COMPOCHIP detected the presence of Sphingobacterium, Streptomyces, Alpha-Proteobacteria, Delta-Proteobacteria, and Firmicutes in all the vermicomposts. COMPOCHIP showed differences in the abundance of particular bacterial taxa among the vermicomposts, giving an idea about the usefulness of each vermicompost in the search for bacteria valuable to biotechnology. The joint use of DGGE and COMPOCHIP is a useful tool to compare vermicompost bacterial communities and to assess the potential of different vermicomposts as bioactive organic materials.

Detecting unknown sequences with DNA microarrays: explorative probe design strategies

Designing environmental DNA microarrays that can be used to survey the extreme diversity of microorganisms existing in nature, represents a stimulating challenge in the field of molecular ecology. Indeed, recent efforts in metagenomics have produced a substantial amount of sequence information from various ecosystems, and will continue to accumulate large amounts of sequence data given the qualitative and quantitative improvements in the next-generation sequencing methods. It is now possible to take advantage of these data to develop comprehensive microarrays by using explorative probe design strategies. Such strategies anticipate genetic variations and thus are able to detect known and unknown sequences in environmental samples. In this review, we provide a detailed overview of the probe design strategies currently available to construct both phylogenetic and functional DNA microarrays, with emphasis on those permitting the selection of such explorative probes. Furthermore, exploration of complex environments requires particular attention on probe sensitivity and specificity criteria. Finally, these innovative probe design approaches require exploiting newly available high-density microarray formats.

Systematic spatial bias in DNA microarray hybridization is caused by probe spot position-dependent variability in lateral diffusion

BACKGROUND

The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained.

METHODOLOGY/PRINCIPAL FINDINGS

This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias.

CONCLUSIONS

Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization.

Separation of fluorescence-labelled terminal restriction fragment DNA on a two-dimensional gel (T-RFs-2D) - an efficient approach for microbial consortium characterization

Fingerprinting techniques provide access to understanding the ecology of uncultured microbial consortia. However, the application of current techniques such as terminal restriction fragment length polymorphism (T-RFLP) and denaturing gradient gel electrophoresis (DGGE) has been hindered due to their limitations in characterizing complex microbial communities. This is due to that different populations possibly share the same terminal restriction fragments (T-RFs) and DNA fragments may co-migrate on DGGE gels. To overcome these limitations, a new approach was developed to separate terminal restriction fragments (T-RFs) of 16S rRNA genes on a two-dimensional gel (T-RFs-2D). T-RFs-2D involves restriction digestion of terminal fluorescence-labelled PCR amplified 16S rRNA gene products and their high-resolution separation via a two-dimensional (2D) gel electrophoresis based on the T-RF fragment size (1(st) D) and its sequence composition on the denaturing gradient gel (2(nd) D). The sequence information of interested T-RFs on 2D gels can be obtained through serial poly(A) tailing reaction, PCR amplification and subsequent DNA sequencing. By employing the T-RFs-2D method, bacteria with MspI digested T-RF size of 436 (±1) bp and 514 (±1) bp were identified to be a Lysobacter sp. and a Dehalococcoides sp. in a polychlorinated biphenyl (PCB) dechlorinating culture. With the high resolution of 2D separation, T-RFs-2D separated 63 DNA fragments in a complex river-sediment microbial community, while traditional DGGE detected only 41 DNA fragments in the same sample. In all, T-RFs-2D has its advantage in obtaining sequence information of interested T-RFs and also in characterization of complex microbial communities.

16S rRNA gene microarray analysis of microbial communities in ethanol-stimulated subsurface sediment

A high-density 16S rRNA gene microarray was used to analyze microbial communities in a slurry of ethanol-amended, uranium-contaminated subsurface sediment. Of specific interest was the extent to which the microarray could detect temporal patterns in the relative abundance of major metabolic groups (nitrate-reducing, metal-reducing, sulfate-reducing, and methanogenic taxa) that were stimulated by ethanol addition. The results show that the microarray, when used in conjunction with geochemical data and knowledge of the physiological properties of relevant taxa, provided accurate assessment of the response of key functional groups to biostimulation.

Phylogenetic microarrays for cultivation-independent identification and metabolic characterization of microorganisms in complex samples

High-throughput sequencing and hybridization technologies promise new insights into the natural diversity and dynamics of microorganisms. Among these new technologies are phylogenetic oligonucleotide microarrays (phylochips) that depend on the standard molecules for taxonomic and environmental studies of microorganisms: the ribosomal RNAs and their encoding genes. The beauty of phylochip hybridization is that a sample can be analyzed with hundreds to thousands of rRNA (gene)-targeted probes simultaneously, lending itself to the efficient diagnosis of many target organisms in many samples. An emerging application of phylochips is the highly parallel analysis of structure-function relationships of microbial community members by employing in vivo substrate-mediated isotope labeling of rRNA (via the isotope array approach). This chapter provides an introduction to phylochip and isotope array analysis and detailed wet-lab protocols for preparation, labeling, and hybridization of target nucleic acids.

Microorganisms with novel dissimilatory (bi)sulfite reductase genes are widespread and part of the core microbiota in low-sulfate peatlands

Peatlands of the Lehstenbach catchment (Germany) house as-yet-unidentified microorganisms with phylogenetically novel variants of the dissimilatory (bi)sulfite reductase genes dsrAB. These genes are characteristic of microorganisms that reduce sulfate, sulfite, or some organosulfonates for energy conservation but can also be present in anaerobic syntrophs. However, nothing is currently known regarding the abundance, community dynamics, and biogeography of these dsrAB-carrying microorganisms in peatlands. To tackle these issues, soils from a Lehstenbach catchment site (Schlöppnerbrunnen II fen) from different depths were sampled at three time points over a 6-year period to analyze the diversity and distribution of dsrAB-containing microorganisms by a newly developed functional gene microarray and quantitative PCR assays. Members of novel, uncultivated dsrAB lineages (approximately representing species-level groups) (i) dominated a temporally stable but spatially structured dsrAB community and (ii) represented "core" members (up to 1% to 1.7% relative abundance) of the autochthonous microbial community in this fen. In addition, denaturing gradient gel electrophoresis (DGGE)- and clone library-based comparisons of the dsrAB diversity in soils from a wet meadow, three bogs, and five fens of various geographic locations (distance of ∼1 to 400 km) identified that one Syntrophobacter-related and nine novel dsrAB lineages are widespread in low-sulfate peatlands. Signatures of biogeography in dsrB-based DGGE data were not correlated with geographic distance but could be explained largely by soil pH and wetland type, implying that the distribution of dsrAB-carrying microorganisms in wetlands on the scale of a few hundred kilometers is not limited by dispersal but determined by local environmental conditions.

High-throughput microarray technology in diagnostics of enterobacteria based on genome-wide probe selection and regression analysis

Background

The Enterobacteriaceae comprise a large number of clinically relevant species with several individual subspecies. Overlapping virulence-associated gene pools and the high overall genome plasticity often interferes with correct enterobacterial strain typing and risk assessment. Array technology offers a fast, reproducible and standardisable means for bacterial typing and thus provides many advantages for bacterial diagnostics, risk assessment and surveillance. The development of highly discriminative broad-range microbial diagnostic microarrays remains a challenge, because of marked genome plasticity of many bacterial pathogens.

Results

We developed a DNA microarray for strain typing and detection of major antimicrobial resistance genes of clinically relevant enterobacteria. For this purpose, we applied a global genome-wide probe selection strategy on 32 available complete enterobacterial genomes combined with a regression model for pathogen classification. The discriminative power of the probe set was further tested in silico on 15 additional complete enterobacterial genome sequences. DNA microarrays based on the selected probes were used to type 92 clinical enterobacterial isolates. Phenotypic tests confirmed the array-based typing results and corroborate that the selected probes allowed correct typing and prediction of major antibiotic resistances of clinically relevant Enterobacteriaceae, including the subspecies level, e.g. the reliable distinction of different E. coli pathotypes.

Conclusions

Our results demonstrate that the global probe selection approach based on longest common factor statistics as well as the design of a DNA microarray with a restricted set of discriminative probes enables robust discrimination of different enterobacterial variants and represents a proof of concept that can be adopted for diagnostics of a wide range of microbial pathogens. Our approach circumvents misclassifications arising from the application of virulence markers, which are highly affected by horizontal gene transfer. Moreover, a broad range of pathogens have been covered by an efficient probe set size enabling the design of high-throughput diagnostics.

Evaluating the microbial diversity of an in vitro model of the human large intestine by phylogenetic microarray analysis

A high-density phylogenetic microarray targeting small subunit rRNA (SSU rRNA) sequences of over 1000 microbial phylotypes of the human gastrointestinal tract, the HITChip, was used to assess the impact of faecal inoculum preparation and operation conditions on an in vitro model of the human large intestine (TIM-2). This revealed that propagation of mixed faecal donations for the production of standardized inocula has only a limited effect on the microbiota composition, with slight changes observed mainly within the Firmicutes. Adversely, significant shifts in several major groups of intestinal microbiota were observed after inoculation of the in vitro model. Hierarchical cluster analysis was able to show that samples taken throughout the inoculum preparation grouped with microbiota profiles observed for faecal samples of healthy adults. In contrast, the TIM-2 microbiota was distinct. While members of the Bacteroidetes and some groups within the Bacilli were increased in TIM-2 microbiota, a strong reduction in the relative abundance of other microbial groups, including Bifidobacterium spp., Streptococcus spp., and Clostridium clusters IV and XIVa, was observed. The changes detected with the HITChip could be confirmed using denaturing gradient gel electrophoresis (DGGE) of SSU rRNA amplicons.

Adaptation of methanogenic communities to the cofermentation of cattle excreta and olive mill wastes at 37 degrees C and 55 degrees C

The acclimatization of methanogens to two-phase olive mill wastes (TPOMW) was investigated in pilot fermenters started up with cattle excreta (37°C) and after changing their feed to excreta plus TPOMW (37°C or 55°C) or TPOMW alone (37°C) until a steady state was reached (28 days). Methanogenic diversity was screened using a phylogenetic microarray (AnaeroChip), and positive targets were quantified by real-time PCR. Results revealed high phylogenetic richness, with representatives of three out of the four taxonomic orders found in digesters. Methanosarcina dominated in the starting excreta (>96% of total 16S rRNA gene copies; over 45 times more abundant than any other methanogen) at high acetate (0.21 g liter(-1)) and ammonia N concentrations (1.3 g liter(-1)). Codigestion at 37°C induced a 6-fold increase of Methanosarcina numbers, correlated with CH(4) production (r(Pearson) = 0.94; P = 0.02). At 55°C, the rise in temperature and H(2) partial pressure induced a burst of Methanobacterium, Methanoculleus, Methanothermobacter, and a group of uncultured archaea. The digestion of excreta alone resulted in low but constant biogas production despite certain oscillations in the methanogenic biomass. Unsuccessful digestion of TPOMW alone was attributed to high Cu levels inducing inhibition of methanogenic activity. In conclusion, the versatile Methanosarcina immediately adapted to the shift from excreta to excreta plus TPOMW and was responsible for the stimulated CH(4) production at 37°C. Higher temperatures (55°C) fostered methanogenic diversity by promoting some H(2) scavengers while yielding the highest CH(4) production. Further testing is needed to find out whether there is a link between increased methanogenic diversity and reactor productivity.

Metatranscriptome analysis of the human fecal microbiota reveals subject-specific expression profiles, with genes encoding proteins involved in carbohydrate metabolism being dominantly expressed

The human gastrointestinal (GI) tract provides home to a complex microbial community, collectively termed microbiota. Although major efforts have been made to describe the diversity and stability of the microbiota, functional studies have been largely restricted to intestinal isolates and include few community studies. The aim of this study was to explore the in situ gene expression of the fecal microbiota and to evaluate the RNA fingerprinting method cDNA-AFLP (cDNA amplified fragment length polymorphism) for this purpose. To this end, cDNA-AFLP analysis of enriched mRNA revealed that two healthy subjects showed highly divergent expression profiles with considerable fluctuations in time. Subsequent excision and sequence determination of bands from the mRNA-enriched profiles resulted in 122 identifiable sequences (transcripts and rRNAs). The classification of retrieved transcripts into functional clusters based on COG (cluster of orthologous genes) annotation showed that most assigned transcripts belonged to the metabolism cluster (26% of all sequences), underlining that even at the very end of the intestinal tract the microbiota is still very active. This study furthermore revealed that cDNA-AFLP is a useful tool to compare gene expression profiles in time in complex microbial communities.

Advances in molecular and "-omics" technologies to gauge microbial communities and bioremediation at xenobiotic/anthropogen contaminated sites

Microbial bioremediation has been well-demonstrated as an ecofriendly and cost-competitive strategy for elimination of xenobiotic and or anthropogenic compounds from the polluted environments. However, successful execution of these versatile bioremediation strategies requires a thorough understanding of factors governing the growth, metabolism, dynamics and functions of indigenous microbial communities at contaminated sites. Recent innovative breakthroughs in genotypic profiling, ultrafast genome pyrosequencing, metagenomics, metatranscriptomics, metaproteomics and metabolomics along with bioinformatics tools have provided crucial in-sights of microbial communities and their mechanisms in bioremediation of environmental pollutants. Moreover, advances in these technologies have significantly improved the process of efficacy determination and implementation of microbial bioremediation strategies. The current review is focused on application of these molecular and "-omics" technologies in gauging the innate microbial community structures, dynamics and functions at contaminated sites or pollution containment facilities.

DNA chip analysis in diverse organisms with unsequenced genomes

Whether for basic research or biotechnology, DNA microarrays have become indispensable tools for studying the transcriptome. Normally, analyses begin with a set of known cDNA sequences to prepare microarray chips specific for a target organism with an extensively sequenced and annotated genome. For many organisms, however, genome programs are not complete or have not been initiated. The present study demonstrates that, whether using homologous or heterologous arrays, the chances of seeing interesting differences are similar. When a specific DNA microarray is not available, the results indicate that a reverse approach based on a heterologous array can be used to probe for interesting differences in gene expression. This may be sufficient in many studies but, if necessary, the genes exhibiting the most significant changes subsequently could be identified by traditional molecular approaches. Such a reverse strategy can provide a convenient and inexpensive approach to probe for significant genetic changes in many diverse studies, to monitor or mine critical biological information for basic or applied research, long before complete sequence data are available.

DNA signature-based approaches for bacterial detection and identification

During the late eighties, environmental microbiologists realized the potential of the polymerase chain reaction (PCR) for the design of innovative approaches to study microbial communities or to detect and identify microorganisms in diverse and complex environments. In contrast to long-established methods of cultivation-based microbial identification, PCR-based techniques allow for the identification of microorganisms regardless of their culturability. A large number of reports have been published that describe PCR-inspired methods, frequently complemented by sequencing or hybridization profiling, to infer taxonomic and clonal microbial diversity or to detect and identify microorganisms using taxa-specific genomic markers. Typing methods have been particularly useful for microbial ecology-driven studies; however, they are not suitable for diagnostic purposes, such as the detection of specific species, strains or clones. Recently, comprehensive reviews have been written describing the panoply of typing methods available and describing their advantages and limitations; however, molecular approaches for bacterial detection and identification were either not considered or only vaguely discussed. This review focuses on DNA-based methods for bacterial detection and identification, highlighting strategies for selecting taxa-specific loci and emphasizing the molecular techniques and emerging technological solutions for increasing the detection specificity and sensitivity. The massive and increasing number of available bacterial sequences in databases, together with already employed bioinformatics tools, hold promise of more reliable, fast and cost-effective methods for bacterial identification in a wide range of samples in coming years. This tendency will foster the validation and certification of these methods and their routine implementation by certified diagnostic laboratories.

A DNA array based assay for the characterization of microbial community in raw milk

An oligonucleotide array based on PCR method containing a combination of probes for taxonomic markers and species-specific virulence genes was developed for the simultaneous identification of 14 Lactic Acid Bacteria (LAB) and food-borne pathogenic bacteria in raw milk. The hypervariable regions V3 and V6 of 16S, together with a variable region of 23S rRNA genes and several genes specific for virulence factors were selected. Universal primers and multiplex PCR were used for the rapid differentiation of bacterial species and low concentration of specific pathogenic and spoilage bacteria were detected in milk. The dominant species such as Streptococcus thermophilus, Enterococcus faecalis, Lactococcus lactis, andLeuconostoc lactis were identified by indirect-labelling reactions based upon incorporation of amino-allyl dUTPs. The results regarding food-borne pathogens detection showed highly specific hybridisation patterns with the genomic DNA from Campylobacter jejuni, Escherichia coli, Salmonella thyphimurium, Listeria monocytogenes and Yersinia enterocolitica. A clear differentiation of dominant species present in a complex microbial community such as raw milk was achieved by the application of short oligonucleotide probes which discriminate sequences differing by few nucleotides.

16S rRNA gene-based phylogenetic microarray for simultaneous identification of members of the genus Burkholderia

For cultivation-independent and highly parallel analysis of members of the genus Burkholderia, an oligonucleotide microarray (phylochip) consisting of 131 hierarchically nested 16S rRNA gene-targeted oligonucleotide probes was developed. A novel primer pair was designed for selective amplification of a 1.3 kb 16S rRNA gene fragment of Burkholderia species prior to microarray analysis. The diagnostic performance of the microarray for identification and differentiation of Burkholderia species was tested with 44 reference strains of the genera Burkholderia, Pandoraea, Ralstonia and Limnobacter. Hybridization patterns based on presence/absence of probe signals were interpreted semi-automatically using the novel likelihood-based strategy of the web-tool Phylo- Detect. Eighty-eight per cent of the reference strains were correctly identified at the species level. The evaluated microarray was applied to investigate shifts in the Burkholderia community structure in acidic forest soil upon addition of cadmium, a condition that selected for Burkholderia species. The microarray results were in agreement with those obtained from phylogenetic analysis of Burkholderia 16S rRNA gene sequences recovered from the same cadmiumcontaminated soil, demonstrating the value of the Burkholderia phylochip for determinative and environmental studies.

Fate and transport of antibiotic residues and antibiotic resistance genes following land application of manure waste

Antibiotics are used in animal livestock production for therapeutic treatment of disease and at subtherapeutic levels for growth promotion and improvement of feed efficiency. It is estimated that approximately 75% of antibiotics are not absorbed by animals and are excreted in waste. Antibiotic resistance selection occurs among gastrointestinal bacteria, which are also excreted in manure and stored in waste holding systems. Land application of animal waste is a common disposal method used in the United States and is a means for environmental entry of both antibiotics and genetic resistance determinants. Concerns for bacterial resistance gene selection and dissemination of resistance genes have prompted interest about the concentrations and biological activity of drug residues and break-down metabolites, and their fate and transport. Fecal bacteria can survive for weeks to months in the environment, depending on species and temperature, however, genetic elements can persist regardless of cell viability. Phylogenetic analyses indicate antibiotic resistance genes have evolved, although some genes have been maintained in bacteria before the modern antibiotic era. Quantitative measurements of drug residues and levels of resistance genes are needed, in addition to understanding the environmental mechanisms of genetic selection, gene acquisition, and the spatiotemporal dynamics of these resistance genes and their bacterial hosts. This review article discusses an accumulation of findings that address aspects of the fate, transport, and persistence of antibiotics and antibiotic resistance genes in natural environments, with emphasis on mechanisms pertaining to soil environments following land application of animal waste effluent.

Development and application of the human intestinal tract chip, a phylogenetic microarray: analysis of universally conserved phylotypes in the abundant microbiota of young and elderly adults

In this paper we present the in silico assessment of the diversity of variable regions of the small subunit ribosomal RNA (SSU rRNA) gene based on an ecosystem-specific curated database, describe a probe design procedure based on two hypervariable regions with minimal redundancy and test the potential of such probe design strategy for the design of a flexible microarray platform. This resulted in the development and application of a phylogenetic microarray for studying the human gastrointestinal microbiota – referred as the human intestinal tract chip (HITChip). Over 4800 dedicated tiling oligonucleotide probes were designed based on two hypervariable regions of the SSU rRNA gene of 1140 unique microbial phylotypes (< 98% identity) following analysis of over 16 000 human intestinal SSU rRNA sequences. These HITChip probes were hybridized to a diverse set of human intestinal samples and SSU rRNA clones to validate its fingerprinting and quantification potential. Excellent reproducibility (median Pearson's correlation of 0.99) was obtained following hybridization with T7 polymerase transcripts generated in vitro from SSU rRNA gene amplicons. A linear dose–response was observed with artificial mixtures of 40 different representative amplicons with relative abundances as low as 0.1% of total microbiota. Analysis of three consecutively collected faecal samples from ten individuals (five young and five elderly adults) revealed temporal dynamics and confirmed that the adult intestinal microbiota is an individual-specific and relatively stable ecosystem. Further analysis of the stable part allowed for the identification of a universal microbiota core at the approximate genus level (90% sequence similarity). This core consists of members of Actinobacteria, Bacteroidetes and Firmicutes. Used as a phylogenetic fingerprinting tool with the possibility for relative quantification, the HITChip has the potential to bridge the gaps in our knowledge in the quantitative and qualitative description of the human gastrointestinal microbiota composition.

Universal ligation-detection-reaction microarray applied for compost microbes

BACKGROUND

Composting is one of the methods utilised in recycling organic communal waste. The composting process is dependent on aerobic microbial activity and proceeds through a succession of different phases each dominated by certain microorganisms. In this study, a ligation-detection-reaction (LDR) based microarray method was adapted for species-level detection of compost microbes characteristic of each stage of the composting process. LDR utilises the specificity of the ligase enzyme to covalently join two adjacently hybridised probes. A zip-oligo is attached to the 3'-end of one probe and fluorescent label to the 5'-end of the other probe. Upon ligation, the probes are combined in the same molecule and can be detected in a specific location on a universal microarray with complementary zip-oligos enabling equivalent hybridisation conditions for all probes. The method was applied to samples from Nordic composting facilities after testing and optimisation with fungal pure cultures and environmental clones.

RESULTS

Probes targeted for fungi were able to detect 0.1 fmol of target ribosomal PCR product in an artificial reaction mixture containing 100 ng competing fungal ribosomal internal transcribed spacer (ITS) area or herring sperm DNA. The detection level was therefore approximately 0.04% of total DNA. Clone libraries were constructed from eight compost samples. The LDR microarray results were in concordance with the clone library sequencing results. In addition a control probe was used to monitor the per-spot hybridisation efficiency on the array.

CONCLUSION

This study demonstrates that the LDR microarray method is capable of sensitive and accurate species-level detection from a complex microbial community. The method can detect key species from compost samples, making it a basis for a tool for compost process monitoring in industrial facilities.

Development of microbial genome-probing microarrays using digital multiple displacement amplification of uncultivated microbial single cells

A crucial problem in the use of previously developed genome-probing microarrays (GPM) has been the inability to use uncultivated bacterial genomes to take advantage of the high sensitivity and specificity of GPM in microbial detection and monitoring. We show here a method, digital multiple displacement amplification (MDA), to amplify and analyze various genomes obtained from single uncultivated bacterial cells. We used 15 genomes from key microbes involved in dichloromethane (DCM)-dechlorinating enrichment as microarray probes to uncover the bacterial population dynamics of samples without PCR amplification. Genomic DNA amplified from single cells originating from uncultured bacteria with 80.3-99.4% similarity to 16S rRNA genes of cultivated bacteria. The digital MDA-GPM method successfully monitored the dynamics of DCM-dechlorinating communities from different phases of enrichment status. Without a priori knowledge of microbial diversity, the digital MDA-GPM method could be designed to monitor most microbial populations in a given environmental sample.

Development of an oligonucleotide microarray method for Salmonella serotyping

Adequate identification of Salmonella enterica serovars is a prerequisite for any epidemiological investigation. This is traditionally obtained via a combination of biochemical and serological typing. However, primary strain isolation and traditional serotyping is time‐consuming and faster methods would be desirable. A microarray, based on two housekeeping and two virulence marker genes (atpD, gyrB, fliC and fljB), has been developed for the detection and identification of the two species of Salmonella (S. enterica and S. bongori), the five subspecies of S. enterica (II, IIIa, IIIb, IV, VI) and 43 S. enterica ssp. enterica serovars (covering the most prevalent ones in Austria and the UK). A comprehensive set of probes (n = 240), forming 119 probe units, was developed based on the corresponding sequences of 148 Salmonella strains, successfully validated with 57 Salmonella strains and subsequently evaluated with 35 blind samples including isolated serotypes and mixtures of different serotypes. Results demonstrated a strong discriminatory ability of the microarray among Salmonella serovars. Threshold for detection was 1 colony forming unit per 25 g of food sample following overnight (14 h) enrichment.

Monitoring aromatic hydrocarbon biodegradation by functional marker genes

The development of biological treatment technologies for contaminated environments requires tools for obtaining direct information about the biodegradation of specific contaminants. The potential of functional gene array analysis to monitor changes in the amount of functional marker genes as indicators of contaminant biodegradation was investigated. A prototype functional gene array was developed for targeting key functions in the biodegradation of naphthalene, toluene and xylenes. Internal standard probe based normalization was introduced to facilitate comparison across multiple samples. Coupled with one-colour hybridization, the signal normalization improved the consistency among replicate hybridizations resulting in better discrimination for the differences in the amount of target DNA. During the naphthalene biodegradation in a PAH-contaminated soil slurry microcosm, the normalized hybridization signals in naphthalene catabolic gene probes were in good agreement with the amount of naphthalene-degradation genes and the production of 14CO2. Gene arrays provide efficient means for monitoring of contaminant biodegradation in the environment.

Development of an oligonucleotide microarray to detect di- and monooxygenase genes for benzene degradation in soil

Diverse environmental genes have been identified recently. To characterize their functions, it is necessary to understand which genes and what combinations of those genes are responsible for the biodegradation of soil contaminants. In this article, a 60-mer oligonucleotide microarray was constructed to simultaneously detect di- and monooxygenase genes for benzene and related compounds. In total, 148 probes were designed and validated by pure-culture hybridizations using the following criteria to discriminate between highly homologous genes: < or =53-bp identities and < or =25-bp continuous stretch to nontarget sequences. Microarray hybridizations were performed using PCR products amplified from five benzene-amended soils and two oil-contaminated soils. Six of the probes gave a positive signal for more than six soils; thus, they may represent key sequences for benzene degradation in the environment. The microarray developed in this study will be a powerful tool for the screening of key genes involved in benzene degradation and for the rapid profiling of benzene oxygenase gene diversity in contaminated soils.

Culture-independent methods for identifying microbial communities in cheese

This review focuses on the culture-independent methods available for the description of both bacterial and fungal communities in cheese. Important steps of the culture-independent strategy, which relies on bulk DNA extraction from cheese and polymerase chain reaction (PCR) amplification of selected sequences, are discussed. We critically evaluate the identification techniques already used for monitoring microbial communities in cheese, including PCR-denaturing gradient gel electrophoresis (PCR-DGGE), PCR-temporal temperature gradient gel electrophoresis (PCR-TTGE) or single-strand conformation polymorphism-PCR (SSCP-PCR) as well as some other techniques that remain to be adapted to the study of cheese communities. Further, our analysis draws attention to the lack of data available on suitable DNA sequences for identifying fungal communities in cheese and proposes some potential DNA targets.

Who eats what, where and when? Isotope-labelling experiments are coming of age

Isotope-labelling experiments have changed the way microbial ecologists investigate the ecophysiology of microbial populations and cells in the environment. Insight into the 'uncultivated majority' accompanies methodology that involves the incorporation of stable isotopes or radioisotopes into sub-populations of environmental samples. Subsequent analysis of labelled biomarkers of sub-populations with stable-isotope probing (DNA-SIP, RNA-SIP, phospholipid-derived fatty acid-SIP) or individual cells with a combination of fluorescence in situ hybridization and microautoradiography reveals linked phylogenetic and functional information about the organisms that assimilated these compounds. Here, we review some of the most recent literature, with an emphasis on methodological improvements to the sensitivity and utility of these methods. We also highlight related isotope techniques that are in continued development and hold promise to transform the way we link phylogeny and function in complex microbial communities.