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Simultaneous quantification of multiple bacteria by the BactoChip microarray designed to target species-specific marker genes.

Ballarini A, Segata N, Huttenhower C, Jousson O - PLoS ONE (2013)

Bottom Line: The microarray successfully distinguished among bacterial species from 21 different genera using 60-mer probes targeting a novel set of in silico identified high-resolution marker genes.The BactoChip additionally proved accurate in determining species-level relative abundances over a 100-fold dynamic range in complex bacterial communities and with a low limit of detection (0.1%).In combination with the continually increasing number of sequenced bacterial genomes, future iterations of the technology could enable to highly accurate clinically-oriented tools for rapid assessment of bacterial community composition and relative abundances.

View Article: PubMed Central - PubMed

Affiliation: Centre for Integrative Biology, University of Trento, Trento, Italy. ballarini@science.unitn.it

ABSTRACT
Bacteria are ubiquitous throughout the environment, the most abundant inhabitants of the healthy human microbiome, and causal pathogens in a variety of diseases. Their identification in disease is often an essential step in rapid diagnosis and targeted intervention, particularly in clinical settings. At present, clinical bacterial detection and discrimination is primarily culture-based, requiring both time and microbiological expertise, especially for bacteria that are not easily cultivated. Higher-throughput molecular methods based on PCR amplification or, recently, microarrays are reaching the clinic as well. However, these methods are currently restricted to a small set of microbes or based on conserved phylogenetic markers such as the 16S rRNA gene, which are difficult to resolve at the species or strain levels. Here, we designed and experimentally validated the BactoChip, an oligonucleotide microarray for bacterial detection and quantification. The chip allows the culture-independent identification of bacterial species, also determining their relative abundances in complex communities as occur in the commensal microbiota or in clinical settings. The microarray successfully distinguished among bacterial species from 21 different genera using 60-mer probes targeting a novel set of in silico identified high-resolution marker genes. The BactoChip additionally proved accurate in determining species-level relative abundances over a 100-fold dynamic range in complex bacterial communities and with a low limit of detection (0.1%). In combination with the continually increasing number of sequenced bacterial genomes, future iterations of the technology could enable to highly accurate clinically-oriented tools for rapid assessment of bacterial community composition and relative abundances.

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Application of the BactoChip to the oral microbiome detects native Streptococcus spp. and correctly identified the introduced spike-in species.A) Species-level averaged intensities linearly correlate with the total measured DNA in the range 0.125–1.000 µg. B) BactoChip detected the presence of Streptococcus equi in the saliva samples of both subjects at abundances higher than 50%. The introduced spike-ins for five different species at different abundances (from about 0.1% to 10% of the total community) were successfully identified in all cases with accurate distinction between different Streptococcus species. Only the species with a relative abundance greater than 1.5% in at least one sample are reported. C) Quantitative evaluation of the predictions for the introduce spike-ins looking in terms of fold change between the abundances within and between samples. All comparison showed strong consistency with the expected fold changes.
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pone-0055764-g005: Application of the BactoChip to the oral microbiome detects native Streptococcus spp. and correctly identified the introduced spike-in species.A) Species-level averaged intensities linearly correlate with the total measured DNA in the range 0.125–1.000 µg. B) BactoChip detected the presence of Streptococcus equi in the saliva samples of both subjects at abundances higher than 50%. The introduced spike-ins for five different species at different abundances (from about 0.1% to 10% of the total community) were successfully identified in all cases with accurate distinction between different Streptococcus species. Only the species with a relative abundance greater than 1.5% in at least one sample are reported. C) Quantitative evaluation of the predictions for the introduce spike-ins looking in terms of fold change between the abundances within and between samples. All comparison showed strong consistency with the expected fold changes.

Mentions: Finally, we applied the BactoChip to profile the oral microbiomes of two healthy subjects. Saliva samples from two subjects were extracted and hybridized with and without spike-ins of one to three microbes present at relative abundances ranging from 10% to 0.1% of total DNA. The chip’s quantification of species-level hybridization intensities relative to the total microbial load (from 0.125 µg to 1.000 µg) was extremely linear across the assessed concentration ranges (Figure 5A). This allowed us to select a target of 0.250 µg of microbial DNA per sample for further experiments, which is thus also a reasonable recommendation for future microbial community studies on the BactoChip.


Simultaneous quantification of multiple bacteria by the BactoChip microarray designed to target species-specific marker genes.

Ballarini A, Segata N, Huttenhower C, Jousson O - PLoS ONE (2013)

Application of the BactoChip to the oral microbiome detects native Streptococcus spp. and correctly identified the introduced spike-in species.A) Species-level averaged intensities linearly correlate with the total measured DNA in the range 0.125–1.000 µg. B) BactoChip detected the presence of Streptococcus equi in the saliva samples of both subjects at abundances higher than 50%. The introduced spike-ins for five different species at different abundances (from about 0.1% to 10% of the total community) were successfully identified in all cases with accurate distinction between different Streptococcus species. Only the species with a relative abundance greater than 1.5% in at least one sample are reported. C) Quantitative evaluation of the predictions for the introduce spike-ins looking in terms of fold change between the abundances within and between samples. All comparison showed strong consistency with the expected fold changes.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3569451&req=5

pone-0055764-g005: Application of the BactoChip to the oral microbiome detects native Streptococcus spp. and correctly identified the introduced spike-in species.A) Species-level averaged intensities linearly correlate with the total measured DNA in the range 0.125–1.000 µg. B) BactoChip detected the presence of Streptococcus equi in the saliva samples of both subjects at abundances higher than 50%. The introduced spike-ins for five different species at different abundances (from about 0.1% to 10% of the total community) were successfully identified in all cases with accurate distinction between different Streptococcus species. Only the species with a relative abundance greater than 1.5% in at least one sample are reported. C) Quantitative evaluation of the predictions for the introduce spike-ins looking in terms of fold change between the abundances within and between samples. All comparison showed strong consistency with the expected fold changes.
Mentions: Finally, we applied the BactoChip to profile the oral microbiomes of two healthy subjects. Saliva samples from two subjects were extracted and hybridized with and without spike-ins of one to three microbes present at relative abundances ranging from 10% to 0.1% of total DNA. The chip’s quantification of species-level hybridization intensities relative to the total microbial load (from 0.125 µg to 1.000 µg) was extremely linear across the assessed concentration ranges (Figure 5A). This allowed us to select a target of 0.250 µg of microbial DNA per sample for further experiments, which is thus also a reasonable recommendation for future microbial community studies on the BactoChip.

Bottom Line: The microarray successfully distinguished among bacterial species from 21 different genera using 60-mer probes targeting a novel set of in silico identified high-resolution marker genes.The BactoChip additionally proved accurate in determining species-level relative abundances over a 100-fold dynamic range in complex bacterial communities and with a low limit of detection (0.1%).In combination with the continually increasing number of sequenced bacterial genomes, future iterations of the technology could enable to highly accurate clinically-oriented tools for rapid assessment of bacterial community composition and relative abundances.

View Article: PubMed Central - PubMed

Affiliation: Centre for Integrative Biology, University of Trento, Trento, Italy. ballarini@science.unitn.it

ABSTRACT
Bacteria are ubiquitous throughout the environment, the most abundant inhabitants of the healthy human microbiome, and causal pathogens in a variety of diseases. Their identification in disease is often an essential step in rapid diagnosis and targeted intervention, particularly in clinical settings. At present, clinical bacterial detection and discrimination is primarily culture-based, requiring both time and microbiological expertise, especially for bacteria that are not easily cultivated. Higher-throughput molecular methods based on PCR amplification or, recently, microarrays are reaching the clinic as well. However, these methods are currently restricted to a small set of microbes or based on conserved phylogenetic markers such as the 16S rRNA gene, which are difficult to resolve at the species or strain levels. Here, we designed and experimentally validated the BactoChip, an oligonucleotide microarray for bacterial detection and quantification. The chip allows the culture-independent identification of bacterial species, also determining their relative abundances in complex communities as occur in the commensal microbiota or in clinical settings. The microarray successfully distinguished among bacterial species from 21 different genera using 60-mer probes targeting a novel set of in silico identified high-resolution marker genes. The BactoChip additionally proved accurate in determining species-level relative abundances over a 100-fold dynamic range in complex bacterial communities and with a low limit of detection (0.1%). In combination with the continually increasing number of sequenced bacterial genomes, future iterations of the technology could enable to highly accurate clinically-oriented tools for rapid assessment of bacterial community composition and relative abundances.

Show MeSH
Related in: MedlinePlus