ORMA: a tool for identification of species-specific variations in 16S rRNA gene and oligonucleotides design

Design and validation of a DNA-microarray for phylogenetic analysis of bacterial communities in different oral samples and dental implants

The quali-quantitative characterization of the oral microbiota is crucial for an exhaustive knowledge of the oral ecology and the modifications of the microbial composition that occur during periodontal pathologies. In this study, we designed and validated a new phylogenetic DNA-microarray (OralArray) to quickly and reliably characterize the most representative bacterial groups that colonize the oral cavity. The OralArray is based on the Ligation Detection Reaction technology associated to Universal Arrays (LDR-UA), and includes 22 probe sets targeted to bacteria belonging to the phyla Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes, Fusobacteria, and Spirochaete. The tool is characterized by high specificity, sensitivity and reproducibility. The OralArray was successfully tested and validated on different oral samples (saliva, lingual plaque, supragingival plaque, and healing cap) collected from 10 healthy subjects. For each specimen, a microbial signature was obtained, and our results established the presence of an oral microbial profile specific for each subject. Moreover, the tool was applied to evaluate the efficacy of a disinfectant treatment on the healing caps before their usage. The OralArray is, thus, suitable to study the microbiota associated with various oral sites and to monitor changes arising from therapeutic treatments.

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.

Development of a microarray-based tool to characterize vaginal bacterial fluctuations and application to a novel antibiotic treatment for bacterial vaginosis

The healthy vaginal microbiota is generally dominated by lactobacilli that confer antimicrobial protection and play a crucial role in health. Bacterial vaginosis (BV) is the most prevalent lower genital tract infection in women in reproductive age and is characterized by a shift in the relative abundances of Lactobacillus spp. to a greater abundance of strictly anaerobic bacteria. In this study, we designed a new phylogenetic microarray-based tool (VaginArray) that includes 17 probe sets specific for the most representative bacterial groups of the human vaginal ecosystem. This tool was implemented using the ligase detection reaction-universal array (LDR-UA) approach. The entire probe set properly recognized the specific targets and showed an overall sensitivity of 6 to 12 ng per probe. The VaginArray was applied to assess the efficacy of rifaximin vaginal tablets for the treatment of BV, analyzing the vaginal bacterial communities of 22 BV-affected women treated with rifaximin vaginal tablets at a dosage of 25 mg/day for 5 days. Our results showed the ability of rifaximin to reduce the growth of various BV-related bacteria (Atopobium vaginae, Prevotella, Megasphaera, Mobiluncus, and Sneathia spp.), with the highest antibiotic susceptibility for A. vaginae and Sneathia spp. Moreover, we observed an increase of Lactobacillus crispatus levels in the subset of women who maintained remission after 1 month of therapy, opening new perspectives for the treatment of BV.

PhylOPDb: a 16S rRNA oligonucleotide probe database for prokaryotic identification

In recent years, high-throughput molecular tools have led to an exponential growth of available 16S rRNA gene sequences. Incorporating such data, molecular tools based on target-probe hybridization were developed to monitor microbial communities within complex environments. Unfortunately, only a few 16S rRNA gene-targeted probe collections were described. Here, we present PhylOPDb, an online resource for a comprehensive phylogenetic oligonucleotide probe database. PhylOPDb provides a convivial and easy-to-use web interface to browse both regular and explorative 16S rRNA-targeted probes. Such probes set or subset could be used to globally monitor known and unknown prokaryotic communities through various techniques including DNA microarrays, polymerase chain reaction (PCR), fluorescent in situ hybridization (FISH), targeted gene capture or in silico rapid sequence identification. PhylOPDb contains 74 003 25-mer probes targeting 2178 genera including Bacteria and Archaea. Database URL: http://g2im.u-clermont1.fr/phylopdb/

Detection of food spoilage and pathogenic bacteria based on ligation detection reaction coupled to flow-through hybridization on membranes

Traditional culturing methods are still commonly applied for bacterial identification in the food control sector, despite being time and labor intensive. Microarray technologies represent an interesting alternative. However, they require higher costs and technical expertise, making them still inappropriate for microbial routine analysis. The present study describes the development of an efficient method for bacterial identification based on flow-through reverse dot-blot (FT-RDB) hybridization on membranes, coupled to the high specific ligation detection reaction (LDR). First, the methodology was optimized by testing different types of ligase enzymes, labeling, and membranes. Furthermore, specific oligonucleotide probes were designed based on the 16S rRNA gene, using the bioinformatic tool Oligonucleotide Retrieving for Molecular Applications (ORMA). Four probes were selected and synthesized, being specific for Aeromonas spp., Pseudomonas spp., Shewanella spp., and Morganella morganii, respectively. For the validation of the probes, 16 reference strains from type culture collections were tested by LDR and FT-RDB hybridization using universal arrays spotted onto membranes. In conclusion, the described methodology could be applied for the rapid, accurate, and cost-effective identification of bacterial species, exhibiting special relevance in food safety and quality.

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.

The human gut chip "HuGChip", an explorative phylogenetic microarray for determining gut microbiome diversity at family level

Evaluating the composition of the human gut microbiota greatly facilitates studies on its role in human pathophysiology, and is heavily reliant on culture-independent molecular methods. A microarray designated the Human Gut Chip (HuGChip) was developed to analyze and compare human gut microbiota samples. The PhylArray software was used to design specific and sensitive probes. The DNA chip was composed of 4,441 probes (2,442 specific and 1,919 explorative probes) targeting 66 bacterial families. A mock community composed of 16S rRNA gene sequences from intestinal species was used to define the threshold criteria to be used to analyze complex samples. This was then experimentally verified with three human faecal samples and results were compared (i) with pyrosequencing of the V4 hypervariable region of the 16S rRNA gene, (ii) metagenomic data, and (iii) qPCR analysis of three phyla. When compared at both the phylum and the family level, high Pearson's correlation coefficients were obtained between data from all methods. The HuGChip development and validation showed that it is not only able to assess the known human gut microbiota but could also detect unknown species with the explorative probes to reveal the large number of bacterial sequences not yet described in the human gut microbiota, overcoming the main inconvenience encountered when developing microarrays.

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.

Comprehensive and relaxed search for oligonucleotide signatures in hierarchically clustered sequence datasets

MOTIVATION

PCR, hybridization, DNA sequencing and other important methods in molecular diagnostics rely on both sequence-specific and sequence group-specific oligonucleotide primers and probes. Their design depends on the identification of oligonucleotide signatures in whole genome or marker gene sequences. Although genome and gene databases are generally available and regularly updated, collections of valuable signatures are rare. Even for single requests, the search for signatures becomes computationally expensive when working with large collections of target (and non-target) sequences. Moreover, with growing dataset sizes, the chance of finding exact group-matching signatures decreases, necessitating the application of relaxed search methods. The resultant substantial increase in complexity is exacerbated by the dearth of algorithms able to solve these problems efficiently.

RESULTS

We have developed CaSSiS, a fast and scalable method for computing comprehensive collections of sequence- and sequence group-specific oligonucleotide signatures from large sets of hierarchically clustered nucleic acid sequence data. Based on the ARB Positional Tree (PT-)Server and a newly developed BGRT data structure, CaSSiS not only determines sequence-specific signatures and perfect group-covering signatures for every node within the cluster (i.e. target groups), but also signatures with maximal group coverage (sensitivity) within a user-defined range of non-target hits (specificity) for groups lacking a perfect common signature. An upper limit of tolerated mismatches within the target group, as well as the minimum number of mismatches with non-target sequences, can be predefined. Test runs with one of the largest phylogenetic gene sequence datasets available indicate good runtime and memory performance, and in silico spot tests have shown the usefulness of the resulting signature sequences as blueprints for group-specific oligonucleotide probes.

AVAILABILITY

Software and Supplementary Material are available at http://cassis.in.tum.de/.

UPS 2.0: unique probe selector for probe design and oligonucleotide microarrays at the pangenomic/genomic level

Background

Nucleic acid hybridization is an extensively adopted principle in biomedical research, in which the performance of any hybridization-based method depends on the specificity of probes to their targets. To determine the optimal probe(s) for detecting target(s) from a sample cocktail, we developed a novel algorithm, which has been implemented into a web platform for probe designing. This probe design workflow is now upgraded to satisfy experiments that require a probe designing tool to take the increasing volume of sequence datasets.

Results

Algorithms and probe parameters applied in UPS 2.0 include GC content, the secondary structure, melting temperature (Tm), the stability of the probe-target duplex estimated by the thermodynamic model, sequence complexity, similarity of probes to non-target sequences, and other empirical parameters used in the laboratory. Several probe background options,Unique probe within a group,Unique probe in a specific Unigene set,Unique probe based onthe pangenomic level, and Unique Probe in the user-defined genome/transcriptome, are available to meet the scenarios that the experiments will be conducted. Parameters, such as salt concentration and the lower-bound Tm of probes, are available for users to optimize their probe design query. Output files are available for download on the result page. Probes designed by the UPS algorithm are suitable for generating microarrays, and the performance of UPS-designed probes has been validated by experiments.

Conclusions

The UPS 2.0 evaluates probe-to-target hybridization under a user-defined condition to ensure high-performance hybridization with minimal chance of non-specific binding at the pangenomic and genomic levels. The UPS algorithm mimics the target/non-target mixture in an experiment and is very useful in developing diagnostic kits and microarrays. The UPS 2.0 website has had more than 1,300 visits and 360,000 sequences performed the probe designing task in the last 30 months. It is freely accessible at http://array.iis.sinica.edu.tw/ups/.

Screen cast: http://array.iis.sinica.edu.tw/ups/demo/demo.htm

High taxonomic level fingerprint of the human intestinal microbiota by ligase detection reaction--universal array approach

Background

Affecting the core functional microbiome, peculiar high level taxonomic unbalances of the human intestinal microbiota have been recently associated with specific diseases, such as obesity, inflammatory bowel diseases, and intestinal inflammation.

Results

In order to specifically monitor microbiota unbalances that impact human physiology, here we develop and validate an original DNA-microarray (HTF-Microbi.Array) for the high taxonomic level fingerprint of the human intestinal microbiota. Based on the Ligase Detection Reaction-Universal Array (LDR-UA) approach, the HTF-Microbi.Array enables specific detection and approximate relative quantification of 16S rRNAs from 30 phylogenetically related groups of the human intestinal microbiota. The HTF-Microbi.Array was used in a pilot study of the faecal microbiota of eight young adults. Cluster analysis revealed the good reproducibility of the high level taxonomic microbiota fingerprint obtained for each of the subject.

Conclusion

The HTF-Microbi.Array is a fast and sensitive tool for the high taxonomic level fingerprint of the human intestinal microbiota in terms of presence/absence of the principal groups. Moreover, analysis of the relative fluorescence intensity for each probe pair of our LDR-UA platform can provide estimation of the relative abundance of the microbial target groups within each samples. Focusing the phylogenetic resolution at division, order and cluster levels, the HTF-Microbi.Array is blind with respect to the inter-individual variability at the species level.