Abstract
Classifying individual bacterial species comprising complex, polymicrobial patient specimens remains a challenge for culture-based and molecular microbiology techniques in common clinical use. We therefore adapted practices from metagenomics research to rapidly catalog the bacterial composition of clinical specimens directly from patients, without need for prior culture. We have combined a semiconductor deep sequencing protocol that produces reads spanning 16S ribosomal RNA gene variable regions 1 and 2 (∼360 bp) with a de-noising pipeline that significantly improves the fraction of error-free sequences. The resulting sequences can be used to perform accurate genus- or species-level taxonomic assignment. We explore the microbial composition of challenging, heterogeneous clinical specimens by deep sequencing, culture-based strain typing, and Sanger sequencing of bulk PCR product. We report that deep sequencing can catalog bacterial species in mixed specimens from which usable data cannot be obtained by conventional clinical methods. Deep sequencing a collection of sputum samples from cystic fibrosis (CF) patients reveals well-described CF pathogens in specimens where they were not detected by standard clinical culture methods, especially for low-prevalence or fastidious bacteria. We also found that sputa submitted for CF diagnostic workup can be divided into a limited number of groups based on the phylogenetic composition of the airway microbiota, suggesting that metagenomic profiling may prove useful as a clinical diagnostic strategy in the future. The described method is sufficiently rapid (theoretically compatible with same-day turnaround times) and inexpensive for routine clinical use.
Highlights
In nature, microbes exist in complex communities shared with other species rather than as pure cultures dominating an ecological niche
As a proof of principle, we explore the utility of this assay in comparison to existing clinical microbiology techniques across a collection of challenging clinical samples and cystic fibrosis sputum samples
To minimize errors attributable to low-levels of sequences originating from contaminating DNA in PCR reagents, we excluded raw reads having a Z-score,580 in a pairwise alignment with a reference sequence, a cutoff which we found to exclude reads that were dissimilar to reference sequences but similar to exogenous sequences based on BLAST searches against a database of 16S ribosomal RNA (rRNA) gene sequences
Summary
Microbes exist in complex communities shared with other species rather than as pure cultures dominating an ecological niche. The ability of existing methods in clinical microbiology to rapidly enumerate and thoroughly classify the diversity of organisms present in such patient specimens is lacking. 16S ribosomal RNA (rRNA) gene sequencing is a popular alternative to traditional methods and provides several advantages [6,7]. DNA sequencing can provide more definitive taxonomic classification than culture-based approaches for many organisms [6,7], while proving less time consuming and labor intensive [6,8]. 16S rRNA gene sequencing using bulk PCR products cannot be applied to polymicrobial specimens: the presence of multiple templates results in superimposed Sanger reads that are generally uninterpretable [8], [9]
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