Analyzing Dehalochip: A functional DNA microarray for reductive dichlorination in chloroethene-contaminated sites

Interpreting high-throughput transcriptomic and metagenomic data from non-model microorganisms presents a challenge due to the significant number of genes with unknown functions and sequences. In this study, we applied an innovative microarray, Dehalochip, for detecting the expression of genes in various microorganisms, particularly focusing on genes involved in chloroethene degradation. Our results demonstrated that this approach can effectively identify dechlorination genes, such as 16S rRNA, tceA, bvcA, and vcrA, in Dehalococcoides mccartyi from samples of groundwater contaminated with chloroethene. Noticeably, the sensitivity and specificity of our Dehalochip are comparable to that of quantitative PCR. However, it stands out as a more viable option for in-situ applications due to its greater capacity to infer potential dechlorination genes. Consequently, we believe our dechlorination microarray offers valuable insights into the role of known microorganisms and their associated functional genes in chloroethene-contaminated environments. This contributes to a deeper understanding of the in-situ reductive dechlorination process.

A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project

High-throughput DNA sequencing techniques enable time- and cost-effective sequencing of large portions of the genome. Instead of sequencing and annotating whole genomes, many phylogenetic studies focus sequencing effort on large sets of pre-selected loci, which further reduces costs and bioinformatic challenges while increasing coverage. One common approach that enriches loci before sequencing is often referred to as target sequence capture. This technique has been shown to be applicable to phylogenetic studies of greatly varying evolutionary depth. Moreover, it has proven to produce powerful, large multi-locus DNA sequence datasets suitable for phylogenetic analyses. However, target capture requires careful considerations, which may greatly affect the success of experiments. Here we provide a simple flowchart for designing phylogenomic target capture experiments. We discuss necessary decisions from the identification of target loci to the final bioinformatic processing of sequence data. We outline challenges and solutions related to the taxonomic scope, sample quality, and available genomic resources of target capture projects. We hope this review will serve as a useful roadmap for designing and carrying out successful phylogenetic target capture studies.

DNA microarray technology and bioinformatic web services

The pan-genomic microarray technique is used for environmental and/or clinical studies. Although microarray is an accurate and sharp diagnostic tool, the expertized bioinformaticians were able to minimize the outcome biases and maximize the flexibility and accuracy of the technique. The knowledge of bioinformatics plays a key role in association with probe designing and the utilization of correct probe sets and platforms. This technique is divided into two parts as dry lab (in silico studies) and wet lab (in vitro studies). Each part covers the other and are known as complementary divisions. In the case of microarray probe designing, a wide range of software, tools, and databases are necessary. Obviously, the application of right databases, software, and tools decreases the probable biases in the outcomes. Due to the importance of suitable probe designing, this article has focused its look onto a variety of online/offline databases, software, and tools.

FibroChip, a Functional DNA Microarray to Monitor Cellulolytic and Hemicellulolytic Activities of Rumen Microbiota

Ruminants fulfill their energy needs for growth primarily through microbial breakdown of plant biomass in the rumen. Several biotic and abiotic factors influence the efficiency of fiber degradation, which can ultimately impact animal productivity and health. To provide more insight into mechanisms involved in the modulation of fibrolytic activity, a functional DNA microarray targeting genes encoding key enzymes involved in cellulose and hemicellulose degradation by rumen microbiota was designed. Eight carbohydrate-active enzyme (CAZyme) families (GH5, GH9, GH10, GH11, GH43, GH48, CE1, and CE6) were selected which represented 392 genes from bacteria, protozoa, and fungi. The DNA microarray, designated as FibroChip, was validated using targets of increasing complexity and demonstrated sensitivity and specificity. In addition, FibroChip was evaluated for its explorative and semi-quantitative potential. Differential expression of CAZyme genes was evidenced in the rumen bacterium Fibrobacter succinogenes S85 grown on wheat straw or cellobiose. FibroChip was used to identify the expressed CAZyme genes from the targeted families in the rumen of a cow fed a mixed diet based on grass silage. Among expressed genes, those encoding GH43, GH5, and GH10 families were the most represented. Most of the F. succinogenes genes detected by the FibroChip were also detected following RNA-seq analysis of RNA transcripts obtained from the rumen fluid sample. Use of the FibroChip also indicated that transcripts of fiber degrading enzymes derived from eukaryotes (protozoa and anaerobic fungi) represented a significant proportion of the total microbial mRNA pool. FibroChip represents a reliable and high-throughput tool that enables researchers to monitor active members of fiber degradation in the rumen.

OCaPPI-Db: an oligonucleotide probe database for pathogen identification through hybridization capture

The detection and identification of bacterial pathogens involved in acts of bio- and agroterrorism are essential to avoid pathogen dispersal in the environment and propagation within the population. Conventional molecular methods, such as PCR amplification, DNA microarrays or shotgun sequencing, are subject to various limitations when assessing environmental samples, which can lead to inaccurate findings. We developed a hybridization capture strategy that uses a set of oligonucleotide probes to target and enrich biomarkers of interest in environmental samples. Here, we present Oligonucleotide Capture Probes for Pathogen Identification Database (OCaPPI-Db), an online capture probe database containing a set of 1,685 oligonucleotide probes allowing for the detection and identification of 30 biothreat agents up to the species level. This probe set can be used in its entirety as a comprehensive diagnostic tool or can be restricted to a set of probes targeting a specific pathogen or virulence factor according to the user’s needs.

Database URL: http://ocappidb.uca.works

Targeted Gene Capture by Hybridization to Illuminate Ecosystem Functioning

Microbial communities are extremely abundant and diverse on earth surface and play key role in the ecosystem functioning. Thus, although next-generation sequencing (NGS) technologies have greatly improved knowledge on microbial diversity, it is necessary to reduce the biological complexity to better understand the microorganism functions. To achieve this goal, we describe a promising approach, based on the solution hybrid selection (SHS) method for the selective enrichment in a target-specific biomarker from metagenomic and metatranscriptomic samples. The success of this method strongly depends on the determination of sensitive, specific, and explorative probes to assess the complete targeted gene repertoire. Indeed, in this method, RNA probes were used to capture large DNA or RNA fragments harboring biomarkers of interest that potentially allow to link structure and function of communities of interest.

Sequence capture by hybridization to explore modern and ancient genomic diversity in model and nonmodel organisms

The recent expansion of next-generation sequencing has significantly improved biological research. Nevertheless, deep exploration of genomes or metagenomic samples remains difficult because of the sequencing depth and the associated costs required. Therefore, different partitioning strategies have been developed to sequence informative subsets of studied genomes. Among these strategies, hybridization capture has proven to be an innovative and efficient tool for targeting and enriching specific biomarkers in complex DNA mixtures. It has been successfully applied in numerous areas of biology, such as exome resequencing for the identification of mutations underlying Mendelian or complex diseases and cancers, and its usefulness has been demonstrated in the agronomic field through the linking of genetic variants to agricultural phenotypic traits of interest. Moreover, hybridization capture has provided access to underexplored, but relevant fractions of genomes through its ability to enrich defined targets and their flanking regions. Finally, on the basis of restricted genomic information, this method has also allowed the expansion of knowledge of nonreference species and ancient genomes and provided a better understanding of metagenomic samples. In this review, we present the major advances and discoveries permitted by hybridization capture and highlight the potency of this approach in all areas of biology.

Functional and structural characterization of two Bacillus megaterium nitroreductases biotransforming the herbicide mesotrione

Mesotrione is a selective herbicide belonging to the triketone family, commonly used on maize cultures since 2003. A mesotrione-transforming Bacillus megaterium Mes11 strain isolated from an agricultural soil was used as a model to identify the key enzymes initiating the biotransformation of this herbicide. Two enzymes (called NfrA1 and NfrA2/YcnD) were identified, and functionally and structurally characterized. Both belong to the NfsA FRP family of the nitro-FMN reductase superfamily (type I oxygen-insensitive nitroreductase) and show optimal pH and temperature of 6–6.5 and 23–25°C, respectively. Both undergo a Ping Pong Bi Bi mechanism, with NADPH and NADPH/NADH as cofactors for NfrA1 and NfrA2/YcnD, respectively. It is interesting that both can also reduce various nitro compounds including pesticides, antibiotics, one prodrug and 4-methylsulfonyl-2-nitrobenzoic acid, one of the mesotrione metabolites retrieved from the environment. The present study constitutes the first identification of mesotrione-transforming enzymes. These enzymes (or their corresponding genes) could be used as biomarkers to predict the capacity of ecosystems to transform mesotrione and assess their contamination by both the parent molecule and/or the metabolites.

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.

Impact of clay mineral, wood sawdust or root organic matter on the bacterial and fungal community structures in two aged PAH-contaminated soils

The high organic pollutant concentration of aged polycyclic aromatic hydrocarbon (PAH)-contaminated wasteland soils is highly recalcitrant to biodegradation due to its very low bioavailability. In such soils, the microbial community is well adapted to the pollution, but the microbial activity is limited by nutrient availability. Management strategies could be applied to modify the soil microbial functioning as well as the PAH contamination through various amendment types. The impact of amendment with clay minerals (montmorillonite), wood sawdust and organic matter plant roots on microbial community structure was investigated on two aged PAH-contaminated soils both in laboratory and 1-year on-site pot experiments. Total PAH content (sum of 16 PAHs of the US-EPA list) and polar polycyclic aromatic compounds (pPAC) were monitored as well as the available PAH fraction using the Tenax method. The bacterial and fungal community structures were monitored using fingerprinting thermal gradient gel electrophoresis (TTGE) method. The abundance of bacteria (16S rRNA genes), fungi (18S rRNA genes) and PAH degraders (PAH-ring hydroxylating dioxygenase and catechol dioxygenase genes) was followed through qPCR assays. Although the treatments did not modify the total and available PAH content, the microbial community density, structure and the PAH degradation potential changed when fresh organic matter was provided as sawdust and under rhizosphere influence, while the clay mineral only increased the percentage of catechol-1,2-dioxygenase genes. The abundance of bacteria and fungi and the percentage of fungi relative to bacteria were enhanced in soil samples supplemented with wood sawdust and in the plant rhizospheric soils. Two distinct fungal populations developed in the two soils supplemented with sawdust, i.e. fungi related to Chaetomium and Neurospora genera and Brachyconidiellopsis and Pseudallescheria genera, in H and NM soils respectively. Wood sawdust amendment favoured the development of PAH-degrading bacteria holding Gram-negative PAH-ring hydroxylating dioxygenase, catechol-1,2-dioxygenase and catechol-2,3-dioxygenase genes. Regarding the total community structure, bacteria closely related to Thiobacillus (β-Proteobacteria) and Steroidobacter (γ-Proteobacteria) genera were favoured by wood sawdust amendment. In both soils, plant rhizospheres induced the development of fungi belonging to Ascomycota and related to Alternaria and Fusarium genera. Bacteria closely related to Luteolibacter (Verrucomicrobia) and Microbacterium (Actinobacteria) were favoured in alfalfa and ryegrass rhizosphere.

Capturing prokaryotic dark matter genomes

Prokaryotes are the most diverse and abundant cellular life forms on Earth. Most of them, identified by indirect molecular approaches, belong to microbial dark matter. The advent of metagenomic and single-cell genomic approaches has highlighted the metabolic capabilities of numerous members of this dark matter through genome reconstruction. Thus, linking functions back to the species has revolutionized our understanding of how ecosystem function is sustained by the microbial world. This review will present discoveries acquired through the illumination of prokaryotic dark matter genomes by these innovative approaches.

MetCap: a bioinformatics probe design pipeline for large-scale targeted metagenomics

Background

Massive sequencing of genes from different environments has evolved metagenomics as central to enhancing the understanding of the wide diversity of micro-organisms and their roles in driving ecological processes. Reduced cost and high throughput sequencing has made large-scale projects achievable to a wider group of researchers, though complete metagenome sequencing is still a daunting task in terms of sequencing as well as the downstream bioinformatics analyses. Alternative approaches such as targeted amplicon sequencing requires custom PCR primer generation, and is not scalable to thousands of genes or gene families.

Results

In this study, we are presenting a web-based tool called MetCap that circumvents the limitations of amplicon sequencing of multiple genes by designing probes that are suitable for large-scale targeted metagenomics sequencing studies. MetCap provides a novel approach to target thousands of genes and genomic regions that could be used in targeted metagenomics studies. Automatic analysis of user-defined sequences is performed, and probes specifically designed for metagenome studies are generated. To illustrate the advantage of a targeted metagenome approach, we have generated more than 300,000 probes that match more than 400,000 publicly available sequences related to carbon degradation, and used these probes for target sequencing in a soil metagenome study. The results show high enrichment of target genes and a successful capturing of the majority of gene families. MetCap is freely available to users from: http://soilecology.biol.lu.se/metcap/.

Conclusion

MetCap is facilitating probe-based target enrichment as an easy and efficient alternative tool compared to complex primer-based enrichment for large-scale investigations of metagenomes. Our results have shown efficient large-scale target enrichment through MetCap-designed probes for a soil metagenome. The web service is suitable for any targeted metagenomics project that aims to study several genes simultaneously. The novel bioinformatics approach taken by the web service will enable researchers in microbial ecology to tap into the vast diversity of microbial communities using targeted metagenomics as a cost-effective alternative to whole metagenome sequencing.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0501-8) contains supplementary material, which is available to authorized users.

Solution hybrid selection capture for the recovery of functional full-length eukaryotic cDNAs from complex environmental samples

Eukaryotic microbial communities play key functional roles in soil biology and potentially represent a rich source of natural products including biocatalysts. Culture-independent molecular methods are powerful tools to isolate functional genes from uncultured microorganisms. However, none of the methods used in environmental genomics allow for a rapid isolation of numerous functional genes from eukaryotic microbial communities. We developed an original adaptation of the solution hybrid selection (SHS) for an efficient recovery of functional complementary DNAs (cDNAs) synthesized from soil-extracted polyadenylated mRNAs. This protocol was tested on the Glycoside Hydrolase 11 gene family encoding endo-xylanases for which we designed 35 explorative 31-mers capture probes. SHS was implemented on four soil eukaryotic cDNA pools. After two successive rounds of capture, >90% of the resulting cDNAs were GH11 sequences, of which 70% (38 among 53 sequenced genes) were full length. Between 1.5 and 25% of the cloned captured sequences were expressed in Saccharomyces cerevisiae. Sequencing of polymerase chain reaction-amplified GH11 gene fragments from the captured sequences highlighted hundreds of phylogenetically diverse sequences that were not yet described, in public databases. This protocol offers the possibility of performing exhaustive exploration of eukaryotic gene families within microbial communities thriving in any type of environment.

Exploiting the architecture and the features of the microsporidian genomes to investigate diversity and impact of these parasites on ecosystems

Fungal species play extremely important roles in ecosystems. Clustered at the base of the fungal kingdom are Microsporidia, a group of obligate intracellular eukaryotes infecting multiple animal lineages. Because of their large host spectrum and their implications in host population regulation, they influence food webs, and accordingly, ecosystem structure and function. Unfortunately, their ecological role is not well understood. Present also as highly resistant spores in the environment, their characterisation requires special attention. Different techniques based on direct isolation and/or molecular approaches can be considered to elucidate their role in the ecosystems, but integrating environmental and genomic data (for example, genome architecture, core genome, transcriptional and translational signals) is crucial to better understand the diversity and adaptive capacities of Microsporidia. Here, we review the current status of Microsporidia in trophic networks; the various genomics tools that could be used to ensure identification and evaluate diversity and abundance of these organisms; and how these tools could be used to explore the microsporidian life cycle in different environments. Our understanding of the evolution of these widespread parasites is currently impaired by limited sampling, and we have no doubt witnessed but a small subset of their diversity.

Inferring community dynamics of organohalide-respiring bacteria in chemostats by covariance of rdhA gene abundance

We have developed a novel approach to identifying and quantifying closely related organohalide-respiring bacteria. Our approach made use of the unique genomic associations of specific reductive dehalogenase subunit A encoding genes (rdhA) that exist in known strains of Dehalococcoides mccartyi and Desulfitobacterium and the distinguishing covariance pattern of observed rdhA genes to assign genes to unknown strains. To test this approach, we operated five anaerobic reductively dechlorinating chemostats for 3-4 years with tetrachloroethene and trichloroethene as terminal electron acceptors and lactate/formate as electron donors. The presence and abundance of rdhA genes were determined comprehensively at the community level using a custom-developed Reductive Dehalogenase Chip (RDH Chip) DNA microarray and used to define putative strains of Dehalococcoides mccartyi and Desulfitobacterium sp. This monitoring revealed that stable chemical performance of chemostats was reflected by a stable community of reductively dechlorinating bacteria. However, perturbations introduced by, for example, electron donor limitation or addition of the competing electron acceptor sulfate led to overall changes in the chemostat performance, including incomplete reduction in the chloroethene substrates, and in the population composition of reductively dehalogenating bacteria. Interestingly, there was a high diversity of operationally defined D. mccartyi strains between the chemostats with almost all strains unique to their specific chemostats in spite of similar selective pressure and similar inocula shared between chemostats.

StressChip as a high-throughput tool for assessing microbial community responses to environmental stresses

Microbial community responses to environmental stresses are critical for microbial growth, survival, and adaptation. To fill major gaps in our ability to discern the influence of environmental changes on microbial communities from engineered and natural environments, a functional gene-based microarray, termed StressChip, has been developed. First, 46 functional genes involved in microbial responses to environmental stresses such as changes to temperature, osmolarity, oxidative status, nutrient limitation, or general stress response were selected and curated. A total of 22,855 probes were designed, covering 79,628 coding sequences from 985 bacterial, 76 archaeal, and 59 eukaryotic species/strains. Probe specificity was computationally verified. Second, the usefulness of functional genes as indicators of stress response was examined by surveying their distribution in metagenome data sets. The abundance of individual stress response genes is consistent with expected distributions based on respective habitats. Third, the StressChip was used to analyze marine microbial communities from the Deepwater Horizon oil spill. That functional stress response genes were detected in higher abundance (p < 0.05) in oil plume compared to nonplume samples indicated shifts in community composition and structure, consistent with previous results. In summary, StressChip provides a new tool for accessing microbial community functional structure and responses to environmental changes.

Strain/species-specific probe design for microbial identification microarrays

Specific identification of microorganisms in the environment is important but challenging, especially at the species/strain level. Here, we have developed a novel k-mer-based approach to select strain/species-specific probes for microbial identification with diagnostic microarrays. Application of this approach to human microbiome genomes showed that multiple (≥10 probes per strain) strain-specific 50-mer oligonucleotide probes could be designed for 2,012 of 3,421 bacterial strains of the human microbiome, and species-specific probes could be designed for most of the other strains. The method can also be used to select strain/species-specific probes for sequenced genomes in any environments, such as soil and water.

Gene capture coupled to high-throughput sequencing as a strategy for targeted metagenome exploration

Next-generation sequencing (NGS) allows faster acquisition of metagenomic data, but complete exploration of complex ecosystems is hindered by the extraordinary diversity of microorganisms. To reduce the environmental complexity, we created an innovative solution hybrid selection (SHS) method that is combined with NGS to characterize large DNA fragments harbouring biomarkers of interest. The quality of enrichment was evaluated after fragments containing the methyl coenzyme M reductase subunit A gene (mcrA), the biomarker of methanogenesis, were captured from a Methanosarcina strain and a metagenomic sample from a meromictic lake. The methanogen diversity was compared with direct metagenome and mcrA-based amplicon pyrosequencing strategies. The SHS approach resulted in the capture of DNA fragments up to 2.5 kb with an enrichment efficiency between 41 and 100%, depending on the sample complexity. Compared with direct metagenome and amplicons sequencing, SHS detected broader mcrA diversity, and it allowed efficient sampling of the rare biosphere and unknown sequences. In contrast to amplicon-based strategies, SHS is less biased and GC independent, and it recovered complete biomarker sequences in addition to conserved regions. Because this method can also isolate the regions flanking the target sequences, it could facilitate operon reconstructions.

In situ TCE degradation mediated by complex dehalorespiring communities during biostimulation processes

The bioremediation of chloroethene contaminants in groundwater polluted systems is still a serious environmental challenge. Many previous studies have shown that cooperation of several dechlorinators is crucial for complete dechlorination of trichloroethene to ethene. In the present study, we used an explorative functional DNA microarray (DechloArray) to examine the composition of specific functional genes in groundwater samples in which chloroethene bioremediation was enhanced by delivery of hydrogen‐releasing compounds. Our results demonstrate for the first time that complete biodegradation occurs through spatial and temporal variations of a wide diversity of dehalorespiring populations involving both Sulfurospirillum, Dehalobacter, Desulfitobacterium, Geobacter and Dehalococcoides genera. Sulfurospirillum appears to be the most active in the highly contaminated source zone, while Geobacter was only detected in the slightly contaminated downstream zone. The concomitant detection of both bvcA and vcrA genes suggests that at least two different Dehalococcoides species are probably responsible for the dechlorination of dichloroethenes and vinyl chloride to ethene. These species were not detected on sites where cis‐dichloroethene accumulation was observed. These results support the notion that monitoring dechlorinators by the presence of specific functional biomarkers using a powerful tool such as DechloArray will be useful for surveying the efficiency of bioremediation strategies.

Development of functional gene microarrays for microbial community analysis

Functional gene arrays (FGAs) are a special type of microarrays containing probes for key genes involved in microbial functional processes, such as biogeochemical cycling of carbon, nitrogen, sulfur, phosphorus and metals, virulence and antibiotic resistance, biodegradation of environmental contaminants, and stress responses. FGAs have been demonstrated to be a specific, sensitive, and quantitative tool for rapid analysis of microbial communities from different habitats, such as waters, soils, extreme environments, bioreactors, and human microbiomes. In this review, we first summarize currently reported FGAs, and then focus on the FGA development. We will also discuss several key issues of FGA technology as well as challenges and directions in future FGA development.

The Hydrogenase Chip: a tiling oligonucleotide DNA microarray technique for characterizing hydrogen-producing and -consuming microbes in microbial communities

We developed a broad-ranging method for identifying key hydrogen-producing and consuming microorganisms through analysis of hydrogenase gene content and expression in complex anaerobic microbial communities. The method is based on a tiling hydrogenase gene oligonucleotide DNA microarray (Hydrogenase Chip), which implements a high number of probes per gene by tiling probe sequences across genes of interest at 1.67 × -2 × coverage. This design favors the avoidance of false positive gene identification in samples of DNA or RNA extracted from complex microbial communities. We applied this technique to interrogate interspecies hydrogen transfer in complex communities in (i) lab-scale reductive dehalogenating microcosms enabling us to delineate key H(2)-consuming microorganisms, and (ii) hydrogen-generating microbial mats where we found evidence for significant H(2) production by cyanobacteria. Independent quantitative PCR analysis on selected hydrogenase genes showed that this Hydrogenase Chip technique is semiquantitative. We also determined that as microbial community complexity increases, specificity must be traded for sensitivity in analyzing data from tiling DNA microarrays.

Improving probe set selection for microbial community analysis by leveraging taxonomic information of training sequences

Background

Population levels of microbial phylotypes can be examined using a hybridization-based method that utilizes a small set of computationally-designed DNA probes targeted to a gene common to all. Our previous algorithm attempts to select a set of probes such that each training sequence manifests a unique theoretical hybridization pattern (a binary fingerprint) to a probe set. It does so without taking into account similarity between training gene sequences or their putative taxonomic classifications, however. We present an improved algorithm for probe set selection that utilizes the available taxonomic information of training gene sequences and attempts to choose probes such that the resultant binary fingerprints cluster into real taxonomic groups.

Results

Gene sequences manifesting identical fingerprints with probes chosen by the new algorithm are more likely to be from the same taxonomic group than probes chosen by the previous algorithm. In cases where they are from different taxonomic groups, underlying DNA sequences of identical fingerprints are more similar to each other in probe sets made with the new versus the previous algorithm. Complete removal of large taxonomic groups from training data does not greatly decrease the ability of probe sets to distinguish those groups.

Conclusions

Probe sets made from the new algorithm create fingerprints that more reliably cluster into biologically meaningful groups. The method can readily distinguish microbial phylotypes that were excluded from the training sequences, suggesting novel microbes can also be detected.

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.