Rapid identification and phylogenetic classification of diverse bacterial pathogens in a multiplexed hybridization assay targeting ribosomal RNA

Bhattacharyya, Roby P.; Walker, Mark; Boykin, Rich; Son, Sophie S.; Liu, Jamin; Hachey, Austin C.; Ma, Peijun; Wu, Lidan; Choi, Kyungyong; Cummins, Kaelyn C.; Benson, Maura; Skerry, Jennifer; Ryu, Hyunryul; Wong, Sharon Y.; Goldberg, Marcia B.; Han, Jongyoon; Pierce, Virginia; Cosimi, Lisa A.; Shoresh, Noam; Livny, Jonathan; Beechem, Joseph M.; Hung, Deborah T.

doi:10.1038/s41598-019-40792-3

Cited by 12 publications

(18 citation statements)

References 47 publications

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“…These features present unique opportunities to leverage both the conserved regions for amplification across a broad panel of bacterial species as well as the unique regions to distinguish individual species. While the 16s ribosomal gene might seem ideal for this purpose and has indeed been used extensively for taxonomic classification (22 , 23 ), we found that it provided insufficient resolution to distinguish relevant bacterial pathogens. We, thus turned to a set of housekeeping genes present in most bacterial species ( 24 ).…”

Section: Introductionmentioning

confidence: 86%

Multiplexed detection of bacterial nucleic acids using Cas13 in droplet microarrays

et al. 2022

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Section: Introductionmentioning

confidence: 86%

Multiplexed detection of bacterial nucleic acids using Cas13 in droplet microarrays

et al. 2022

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“…We were unable to design probes predicted to specifically recognize the C. guilliermondii 28S subunit, or either subunit for C. dubliniensis , due to their similarity with other species (see Methods for details). However, we included these species in subsequent experiments, since our experience with bacterial species suggested that the overall probeset reactivity profile (PSRP) may still uniquely identify closely related species, even without a species-specific probe (18). In addition, we designed two genus-level “pan- Candida ” probes intended to recognize the 18S and 28S subunits from all Candida species while excluding non- Candida fungi.…”

Section: Resultsmentioning

confidence: 99%

“…Even with the advent of mass spectrometry-based pathogen identification, delays in clinical diagnosis often result from slow subculture steps required for optimal accuracy (5, 12). We recently developed Phirst-ID, a novel approach for amplification-free, multiplexed fluorescence-based rRNA hybridization to identify bacteria directly from clinical specimens (18). Here, we extend this Phirst-ID approach, designing a 21-plex probeset that can rapidly and accurately identify 11 common pathogenic Candida species from both isolated colonies (33/33 on a reference panel, 33/33 in an independent validation set) and positive clinical blood culture broths (concordant identification of 58/59 Candida species included in the reference panel, where the only discordant sample was a mixed specimen that included the species identified by Phirst-ID; no mis-identifications of 3 additional yeast species that were not in the reference panel).…”

Section: Discussionmentioning

confidence: 99%

“…Since 28S rRNA data are less well annotated across non-pathogenic fungi, we did not include them among our outgroup sequences. We then profiled each desired target sequence using NanoString’s probe design algorithm to identify all putative pairs of consecutive 50mer probe-binding regions within the 18S and 28S subunits of each species that meet parameter specifications for predicted binding kinetics and thermodynamics, secondary structure, and sequence composition for the desired targets while minimizing predicted cross-reactivity against non-targeted species within these databases, or the human genome (18, 21). The resulting probeset is shown in Supplementary Figure S1 ; species-specific probes tended to cluster in variable regions of each rRNA subunit and often overlapped.…”

Section: Methodsmentioning

confidence: 99%

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A novel rRNA hybridization-based approach to rapid, accurate Candida identification directly from blood culture

Matzko¹,

Sephton-Clark

Young

et al. 2022

Preprint

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Invasive fungal infections are increasingly common and carry high morbidity and mortality, yet fungal diagnostics lag behind bacterial diagnostics in rapidly identifying the causal pathogen. We previously devised a fluorescent hybridization-based assay to identify bacteria within hours directly from blood culture bottles without subculture, called phylogeny-informed rRNA-based strain identification (Phirst-ID). Here, we adapt this approach to unambiguously identify 11 common pathogenic Candida species, including C. auris, with 100% accuracy from laboratory culture (33 of 33 strains in a reference panel, plus 33 of 33 additional isolates tested in a validation panel). In a pilot study on 62 consecutive positive clinical blood cultures from two hospitals that showed yeast on Gram stain, Candida Phirst-ID matched the clinical laboratory result for 58 of 59 specimens represented in the 11-species reference panel, without misclassifying the 3 off-panel species. It also detected mixed Candida species in 2 of these 62 specimens, including the one discordant classification, that were not identified by standard clinical microbiology workflows; in each case the presence of both species was validated by both clinical and experimental data. Finally, in three specimens that grew both bacteria and yeast, we paired our prior bacterial probeset with this new Candida probeset to detect both pathogen types using Phirst-ID. This simple, robust assay can provide accurate Candida identification within hours directly from blood culture bottles, and the conceptual approach holds promise for pan-microbial identification in a single workflow.

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“…21 These features present unique opportunities to leverage both the conserved regions for amplification across a broad panel of bacterial species as well as the unique regions to distinguish individual species. While the 16s ribosomal gene might seem ideal for this purpose and has indeed been used extensively for taxonomic classification, 22,23 we found that it provided insufficient resolution to distinguish relevant bacterial pathogens. We thus turned to a set of housekeeping genes present in most bacterial species 24 .…”

Section: Introductionmentioning

confidence: 87%

Multiplexed detection of bacterial nucleic acids using Cas13 in droplet microarrays

Thakku

Ackerman

Myhrvold

et al. 2021

Preprint

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Rapid and accurate diagnosis of infections is fundamental to individual patient care and public health management. Nucleic acid detection methods are critical to this effort, but are limited either in the breadth of pathogens targeted or by the expertise and infrastructure required. We present here a high-throughput system that enables rapid identification of bacterial pathogens, bCARMEN, which utilizes: (1) modular CRISPR-Cas13-based nucleic acid detection with enhanced sensitivity and specificity; and (2) a droplet microfluidic system that enables thousands of simultaneous, spatially multiplexed detection reactions at nanoliter volumes; and (3) a novel pre-amplification strategy that further enhances sensitivity and specificity. We demonstrate bCARMEN is capable of detecting and discriminating 52 clinically relevant bacterial species and several key antibiotic resistance genes. We further develop a proof of principle system for use with stabilized reagents and a simple workflow with optical readout using a cell phone camera, opening up the possibility of a rapid point-of-care multiplexed bacterial pathogen identification and antibiotic susceptibility testing.Significance StatementIn this paper, we use a novel primer design method combined with droplet-based CRISPR Cas13 detection to distinguish 52 clinically relevant bacterial pathogens in a single assay. We also apply the method to detect and distinguish a panel of major antibiotic resistance genes, which is of critical importance in this era of rising antibiotic resistance. Finally, we make key advances towards making our diagnostic assay deployable at the point-of-care, with a simplified emulsion-free assay process that uses mobile phone camera for detection and reduces infrastructure/skilled labor requirements.

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Rapid identification and phylogenetic classification of diverse bacterial pathogens in a multiplexed hybridization assay targeting ribosomal RNA

Cited by 12 publications

References 47 publications

Multiplexed detection of bacterial nucleic acids using Cas13 in droplet microarrays

Multiplexed detection of bacterial nucleic acids using Cas13 in droplet microarrays

A novel rRNA hybridization-based approach to rapid, accurate Candida identification directly from blood culture

Multiplexed detection of bacterial nucleic acids using Cas13 in droplet microarrays

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