Sensitive Identification of Bacterial DNA in Clinical Specimens by Broad-Range 16S rRNA Gene Enrichment.

The broad-range detection and identification of bacterial DNA from clinical specimens are a foundational approach in the practice of molecular microbiology. However, there are circumstances under which conventional testing may yield false-negative or otherwise uninterpretable results, including the presence of multiple bacterial templates or degraded nucleic acids. Here, we describe an alternative, next-generation sequencing approach for the broad range detection of bacterial DNA using broad-range 16S rRNA gene hybrid capture ("16S Capture"). The method is able to deconvolute multiple bacterial species present in a specimen, is compatible with highly fragmented templates, and can be readily implemented when the overwhelming majority of nucleic acids in a specimen derive from the human host. We find that this approach is sensitive to detecting as few as 17 Staphylococcus aureus genomes from a background of 100 ng of human DNA, providing 19- to 189-fold greater sensitivity for identifying bacterial sequences than standard shotgun metagenomic sequencing, and is able to successfully recover organisms from across the eubacterial tree of life. Application of 16S Capture to a proof-of-principle case series demonstrated its ability to identify bacterial species that were consistent with histological evidence of infection, even when diagnosis could not be established using conventional broad range bacterial detection assays. 16S Capture provides a novel means for the efficient and sensitive detection of bacteria embedded in human tissues and for specimens containing highly fragmented template DNA.

Improved Species-Level Clinical Identification of Enterobacteriaceae through Broad-Range dnaJ PCR and Sequencing.

Enterobacteriaceae represent a diverse and medically important family of bacteria that are difficult to identify to the species level using the standard molecular method of 16S rRNA gene sequencing. Prior work has demonstrated the value of dnaJ gene sequence analysis in resolving different members of the family. However, existing protocols are not optimized for clinical use and exhibit several limitations in practice. Here, we describe an improved assay for dnaJ-based identification of Enterobacteriaceae which boasts increased broad-range specificity across genera, shorter amplicon sizes that are suitable for use with formalin-fixed or direct patient specimens, and enhanced amplification efficiency and assay sensitivity through the incorporation of locked nucleic acid chemistries. Sequence analysis of public databases indicates that the partial dnaJ sequence interrogated by this design retains high discriminatory power among Enterobacteriaceae genera and species, with only particular lineages of Shigella sp. and Escherichia coli proving unresolvable. Limits of detection studies using 8 disparate species indicated that amplification was consistently achievable across organisms and allowed robust dideoxynucleotide chain terminator sequencing from as little as 10 genome equivalents of template, depending on the species interrogated. Retrospective application of the dnaJ assay to patient specimens enabled unambiguous classification of Enterobacteriaceae to the species level in 22 of 27 (81.5%) positive specimens examined, with most remaining cases representing unresolvable calls between closely related Escherichia coli and Shigella species. We expect that this assay will facilitate the accurate molecular identification of species from the Enterobacteriaceae family in a variety of clinical specimens and diagnostic contexts.

Clinical Next Generation Sequencing Outperforms Standard Microbiological Culture for Characterizing Polymicrobial Samples.

BACKGROUND: Humans suffer from infections caused by single species or more complex polymicrobial communities. Identification of infectious bacteria commonly employs microbiological culture, which depends upon the in vitro propagation and isolation of viable organisms. In contrast, detection of bacterial DNA using next generation sequencing (NGS) allows culture-independent microbial profiling, potentially providing important new insights into the microbiota in clinical specimens. METHODS: NGS 16S rRNA gene sequencing (NGS16S) was compared with culture using (a) synthetic polymicrobial samples for which the identity and abundance of organisms present were precisely defined and (b) primary clinical specimens. RESULTS: Complex mixtures of at least 20 organisms were well resolved by NGS16S with excellent reproducibility. In mixed bacterial suspensions (107 total genomes), we observed linear detection of a target organism over a 4-log concentration range (500-3 × 106 genomes). NGS16S analysis more accurately recapitulated the known composition of synthetic samples than standard microbiological culture using nonselective media, which distorted the relative abundance of organisms and frequently failed to identify low-abundance pathogens. However, extended quantitative culture using selective media for each of the component species recovered the expected organisms at the proper abundance, validating NGS16S results. In an analysis of sputa from cystic fibrosis patients, NGS16S identified more clinically relevant pathogens than standard culture. CONCLUSIONS: Biases in standard, nonselective microbiological culture lead to a distorted characterization of polymicrobial mixtures. NGS16S demonstrates enhanced reproducibility, quantification, and classification accuracy compared with standard culture, providing a more comprehensive, accurate, and culture-free analysis of clinical specimens.

Performance comparison of Illumina and ion torrent next-generation sequencing platforms for 16S rRNA-based bacterial community profiling.

High-throughput sequencing of the taxonomically informative 16S rRNA gene provides a powerful approach for exploring microbial diversity. Here we compare the performances of two common "benchtop" sequencing platforms, Illumina MiSeq and Ion Torrent Personal Genome Machine (PGM), for bacterial community profiling by 16S rRNA (V1-V2) amplicon sequencing. We benchmarked performance by using a 20-organism mock bacterial community and a collection of primary human specimens. We observed comparatively higher error rates with the Ion Torrent platform and report a pattern of premature sequence truncation specific to semiconductor sequencing. Read truncation was dependent on both the directionality of sequencing and the target species, resulting in organism-specific biases in community profiles. We found that these sequencing artifacts could be minimized by using bidirectional amplicon sequencing and an optimized flow order on the Ion Torrent platform. Results of bacterial community profiling performed on the mock community and a collection of 18 human-derived microbiological specimens were generally in good agreement for both platforms; however, in some cases, results differed significantly. Disparities could be attributed to the failure to generate full-length reads for particular organisms on the Ion Torrent platform, organism-dependent differences in sequence error rates affecting classification of certain species, or some combination of these factors. This study demonstrates the potential for differential bias in bacterial community profiles resulting from the choice of sequencing platform alone.

Molecular diagnosis of Actinomadura madurae infection by 16S rRNA deep sequencing.

Next-generation DNA sequencing can be used to catalog individual organisms within complex, polymicrobial specimens. Here, we utilized deep sequencing of 16S rRNA to implicate Actinomadura madurae as the cause of mycetoma in a diabetic patient when culture and conventional molecular methods were overwhelmed by overgrowth of other organisms.

MaLiAmPi enables generalizable and taxonomy-independent microbiome features from technically diverse 16S-based microbiome studies.

For studies using microbiome data, the ability to robustly combine data from technically and biologically distinct microbiome studies is a crucial means of supporting more robust and clinically relevant inferences. Formidable technical challenges arise when attempting to combine data from technically diverse 16S rRNA gene variable region amplicon sequencing (16S) studies. Closed operational taxonomic units and taxonomy are criticized as being heavily dependent upon reference sets and with limited precision relative to the underlying biology. Phylogenetic placement has been demonstrated to be a promising taxonomy-free manner of harmonizing microbiome data, but it has lacked a validated count-based feature suitable for use in machine learning and association studies. Here we introduce a phylogenetic-placement-based, taxonomy-independent, compositional feature of microbiota: phylotypes. Phylotypes were predictive of clinical outcomes such as obesity or pre-term birth on technically diverse independent validation sets harmonized post hoc. Thus, phylotypes enable the rigorous cross-validation of 16S-based clinical prognostic models and associative microbiome studies.

Characterizing the molecular composition and diagnostic potential of Mycobacterium tuberculosis urinary cell-free DNA using next-generation sequencing.

BACKGROUND: Urine cell-free DNA (cfDNA) is an attractive target for diagnosing pulmonary Mycobacterium tuberculosis (MTB) infection, but has not been thoroughly characterized as a biomarker. METHODS: This study was performed to investigate the size and composition of urine cfDNA from tuberculosis (TB) patients with minimal bias using next-generation sequencing (NGS). A combination of DNA extraction and single-stranded sequence library preparation methods demonstrated to recover short, highly degraded cfDNA fragments was employed. Urine cfDNA from 10 HIV-positive patients with pulmonary TB and two MTB-negative controls was examined. RESULTS: MTB-derived cfDNA was identifiable by NGS from all MTB-positive patients and was absent from negative controls. MTB cfDNA was significantly shorter than human cfDNA, with median fragment lengths of ≤19-52 bp and 42-92 bp, respectively. MTB cfDNA abundance increased exponentially with decreased fragment length, having a peak fragment length of ≤19 bp in most samples. In addition, we identified a larger fraction of short human genomic cfDNA, ranging from 29 to 53 bp, than previously reported. Urine cfDNA fragments spanned the MTB genome with relative uniformity, but nucleic acids derived from multicopy elements were proportionately over-represented. CONCLUSIONS: TB urine cfDNA is a potentially powerful biomarker but is highly fragmented, necessitating special procedures to maximize its recovery and detection.

Comprehensive evaluation of complex polymicrobial specimens using next generation sequencing and standard microbiological culture.

Optimal clinical decision-making depends on identification of clinically relevant organisms present in a sample. Standard microbiological culture may fail to identify unusual or fastidious organisms and can misrepresent relative abundance of sample constituents. Culture-independent methods have improved our ability to deconvolute polymicrobial patient samples. We used next-generation 16S rRNA gene sequencing (NGS16S) to determine how often cultivatable organisms in complex polymicrobial samples are not reported by standard culture. Twenty consecutive bronchoalveolar lavage (BAL) samples were plated to standard and additional media; bacteria were identified by NGS16S analysis of DNA extracted directly from samples or from washed culture plates. 96% of organisms identified were cultivable, but only 21% were reported by standard culture, indicating that standard work-up provides an incomplete assessment of microbial constituents. Direct NGS16S correlated well with standard culture, identifying the same predominant organism in 50% of samples. When predominant organisms differed, NGS16S most often detected anaerobes, whose growth is unsupported by standard culture conditions for this specimen. NGS16S identified more organisms per sample and allowed identification of fastidious organisms, while culture was better at capturing organisms when bacterial load was low, and allowed incidental recovery of non-bacterial pathogens. Molecular and culture-based methods together detect more organisms than either method alone.

Rapid 16S rRNA next-generation sequencing of polymicrobial clinical samples for diagnosis of complex bacterial infections.

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.