Dhruba J. Sengupta

Performance Comparison of Illumina and Ion Torrent Next-Generation Sequencing Platforms for 16S rRNA-Based Bacterial Community Profiling

ABSTRACT 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.

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.

Application of Whole-Genome Sequencing for Bacterial Strain Typing in Molecular Epidemiology

ABSTRACT Nosocomial infections pose a significant threat to patient health; however, the gold standard laboratory method for determining bacterial relatedness (pulsed-field gel electrophoresis [PFGE]) remains essentially unchanged 20 years after its introduction. Here, we explored bacterial whole-genome sequencing (WGS) as an alternative approach for molecular strain typing. We compared WGS to PFGE for investigating presumptive outbreaks involving three important pathogens: vancomycin-resistant Enterococcus faecium (n = 19), methicillin-resistant Staphylococcus aureus (n = 17), and Acinetobacter baumannii (n = 15). WGS was highly reproducible (average ≤ 0.39 differences between technical replicates), which enabled a functional, quantitative definition for determining clonality. Strain relatedness data determined by PFGE and WGS roughly correlated, but the resolution of WGS was superior (P = 5.6 × 10−8 to 0.016). Several discordant results were noted between the methods. A total of 28.9% of isolates which were indistinguishable by PFGE were nonclonal by WGS. For A. baumannii, a species known to undergo rapid horizontal gene transfer, 16.2% of isolate pairs considered nonidentical by PFGE were clonal by WGS. Sequencing whole bacterial genomes with single-nucleotide resolution demonstrates that PFGE is prone to false-positive and false-negative results and suggests the need for a new gold standard approach for molecular epidemiological strain typing.

Identification of RNAs that bind to a specific protein using the yeast three-hybrid system

We have adapted the yeast three-hybrid system to identify RNA ligands for an RNA-binding protein. In this assay system, a protein-RNA interaction is detected by the reconstitution of a transcriptional activator using two hybrid proteins and a hybrid RNA. The RNA molecule is tethered to the promoter of a reporter gene by binding to a hybrid protein consisting of the bacteriophage MS2 coat protein fused to the DNA-binding protein LexA; the RNA-binding domain to be analyzed is fused to the transcriptional activation domain of the yeast Gal4 protein; and the bifunctional RNA consists of binding sites for the coat protein and for the other RNA-binding domain. We built an RNA library such that short fragments of genomic DNA from yeast were transcribed in yeast together with binding sites for the coat protein. We screened this hybrid RNA library for RNAs that bound to the yeast Snp1 protein, a homolog of the human U1-70K protein. The screen yielded as the strongest positive the fragment of U1 RNA that contains loop I, which is known to bind to Snp1 in U1 snRNP. We also identified four other RNA ligands that produced weaker three-hybrid signals, suggesting lower affinities for Snp1 as compared to U1 RNA. In addition, this search also yielded a set of RNA sequences that can activate transcription on their own when bound to a promoter through a protein interaction.

Yeast three-hybrid system to detect and analyze interactions between RNA and protein.

Publisher Summary This article describes the use of a different genetic approach to detect RNA protein-interactions. In this method, termed the three-hybrid system, the binding of a hybrid RNA to each of two hybrid proteins activates transcription of a reporter gene in vivo . The method can be used to detect and analyze RNA-protein interaction when both partners are known or to find a mate when only one is known. One asset of the three-hybrid method, shared with other genetic approaches to finding protein partners, is that a DNA clone of the interacting protein is obtained. With the proliferation of sequence data bases and genomic information, a small bit of sequence information may be enough to help determine whether that protein is a legitimate partner or shed light on its function.

Genome Sequence of a Novel Species, Propionibacterium humerusii

As part of a larger project to sequence multiple clinical isolates of Propionibacterium acnes, we have produced a draft genome sequence of a novel Propionibacterium species that is closely related to, yet distinct (by sequence) from P. acnes. We have tentatively named this new species Propionibacterium humerusii.

Mutation of leucine-92 selectively reduces the apparent affinity of inosine, guanosine, NBMPR [S6-(4-nitrobenzyl)-mercaptopurine riboside] and dilazep for the human equilibrative nucleoside transporter, hENT1.

We developed a yeast-based assay for selection of hENT1 (human equilibrative nucleoside transporter 1) mutants that have altered affinity for hENT1 inhibitors and substrates. In this assay, expression of hENT1 in a yeast strain deficient in adenine biosynthesis (ade2) permits yeast growth on a plate lacking adenine but containing adenosine, a hENT1 substrate. This growth was prevented when inhibitors of hENT1 [e.g. NBMPR [S6-(4-nitrobenzyl)-mercaptopurine riboside], dilazep or dipyridamole] were included in the media. To identify hENT1 mutants resistant to inhibition by these compounds, hENT1 was randomly mutagenized and introduced into this strain. Mutation(s) that allowed growth of yeast cells in the presence of these inhibitors were then identified and characterized. Mutants harbouring amino acid changes at Leu92 exhibited resistance to NBMPR and dilazep but not dipyridamole. The IC50 values of NBMPR and dilazep for [3H]adenosine transport by one of these mutants L92Q (Leu92-->Gln) were approx. 200- and 4-fold greater when compared with the value for the wild-type hENT1, whereas that for dipyridamole remained unchanged. Additionally, when compared with the wild-type transporter, [3H]adenosine transport by L92Q transporter was significantly resistant to inhibition by inosine and guanosine but not by adenosine or pyrimidines. The Km value for inosine transport was approx. 4-fold greater for the L92Q mutant (260+/-16 mM) when compared with the wild-type transporter (65+/-7.8 mM). We have identified for the first time an amino acid residue (Leu92) of hENT1 that, when mutated, selectively alters the affinity of hENT1 to transport the nucleosides inosine and guanosine and its sensitivity to the inhibitors NBMPR and dilazep.

Rapid Detection of Vancomycin-Intermediate Staphylococcus aureus by Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

ABSTRACT Vancomycin is the standard of care for the treatment of invasive methicillin-resistant Staphylococcus aureus (MRSA) infections. Infections with vancomycin-nonsusceptible MRSA, including vancomycin-intermediate S. aureus (VISA) and heterogeneous VISA (hVISA), are clinically challenging and are associated with poor patient outcomes. The identification of VISA in the clinical laboratory depends on standard susceptibility testing, which takes at least 24 h to complete after isolate subculture, whereas hVISA is not routinely detected in clinical labs. We therefore sought to determine whether VISA and hVISA can be differentiated from vancomycin-susceptible S. aureus (VSSA) using the spectra produced by matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS). Strains of MRSA were characterized for vancomycin susceptibility phenotype by broth microdilution and modified population analysis. We tested 21 VISA, 21 hVISA, and 38 VSSA isolates by MALDI-TOF MS. Susceptibility phenotypes were separated by using a support vector machine (SVM) machine learning algorithm. The resulting model was validated by leave-one-out cross validation. Models were developed and validated by using spectral profiles generated under various subculture conditions, as well as with and without hVISA strains. Using SVM, we correctly identified 100% of the VISA and 97% of the VSSA isolates with an overall classification accuracy of 98%. Addition of hVISA to the model resulted in 76% hVISA identification, 100% VISA identification, and 89% VSSA identification, for an overall classification accuracy of 89%. We conclude that VISA/hVISA and VSSA isolates are separable by MALDI-TOF MS with SVM analysis.

Diagnosis of Neurocysticercosis by Detection of Taenia solium DNA Using a Global DNA Screening Platform

Neurocysticercosis is caused by Taenia solium infection of the brain. Diagnosis is most often made by visualization of the parasitic scolex by magnetic resonance imaging of the brain or by characteristic neuroimaging findings with serologic test results positive for T. solium. A patient who presents with a solitary brain lesion usually poses a diagnostic dilemma, because the differential diagnosis often includes neurocysticercosis and other infections or neoplasm. Although the sensitivity of serologic testing for T. solium approaches 100% in patients with multiple intraparenchymal cysts, the sensitivity of testing for patients with solitary cysts is <50%, which makes serologic testing a less useful diagnostic tool for patients with solitary central nervous system (CNS) lesions. We describe 2 patients with solitary CNS lesions who received a neurocysticercosis diagnosis after identification of T. solium DNA in brain biopsy tissue with use of a global DNA screening platform. Global screening is a promising tool for the diagnosis of CNS infection, especially when traditional diagnostic tools are insensitive.

Whole-Genome Sequencing for High-Resolution Investigation of Methicillin-Resistant Staphylococcus aureus Epidemiology and Genome Plasticity

ABSTRACT Methicillin-resistant Staphylococcus aureus (MRSA) infections pose a major challenge in health care, yet the limited heterogeneity within this group hinders molecular investigations of related outbreaks. Pulsed-field gel electrophoresis (PFGE) has been the gold standard approach but is impractical for many clinical laboratories and is often replaced with PCR-based methods. Regardless, both approaches can prove problematic for identifying subclonal outbreaks. Here, we explore the use of whole-genome sequencing for clinical laboratory investigations of MRSA molecular epidemiology. We examine the relationships of 44 MRSA isolates collected over a period of 3 years by using whole-genome sequencing and two PCR-based methods, multilocus variable-number tandem-repeat analysis (MLVA) and spa typing. We find that MLVA offers higher resolution than spa typing, as it resolved 17 versus 12 discrete isolate groups, respectively. In contrast, whole-genome sequencing reproducibly cataloged genomic variants (131,424 different single nucleotide polymorphisms and indels across the strain collection) that uniquely identified each MRSA clone, recapitulating those groups but enabling higher-resolution phylogenetic inferences of the epidemiological relationships. Importantly, whole-genome sequencing detected a significant number of variants, thereby distinguishing between groups that were considered identical by both spa typing (minimum, 1,124 polymorphisms) and MLVA (minimum, 193 polymorphisms); this suggests that these more conventional approaches can lead to false-positive identification of outbreaks due to inappropriate grouping of genetically distinct strains. An analysis of the distribution of variants across the MRSA genome reveals 47 mutational hot spots (comprising ∼2.5% of the genome) that account for 23.5% of the observed polymorphisms, and the use of this selected data set successfully recapitulates most epidemiological relationships in this pathogen group.