scholarly journals Rapid Phenotypic Antibiotic Susceptibility Testing Through RNA Detection

2017 ◽  
Vol 4 (suppl_1) ◽  
pp. S33-S33 ◽  
Author(s):  
Roby Bhattacharyya ◽  
Jamin Liu ◽  
Peijun Ma ◽  
Nirmalya Bandyopadhyay ◽  
Jonathan Livny ◽  
...  
Keyword(s):  
Antibiotic Susceptibility ◽  
Susceptibility Testing ◽  
Genetic Resistance ◽  
Resistance Mechanisms ◽  
Resistant Isolate ◽  
Antibiotic Susceptibility Testing ◽  
Acinetobacter Baumanii ◽  
Rna Detection ◽  
Culture Bottle ◽  
Phenotypic Assay

Abstract Background Culture-based antibiotic susceptibility testing, the gold standard, is too slow to guide early antibiotic selection, while newer genotypic methods require comprehensive knowledge of resistance mechanisms to predict phenotype. Quantitative measurement of key antibiotic-responsive transcripts offers a rapid, phenotypic assay for assessing antibiotic susceptibility, agnostic to the genetic basis for resistance. Methods We performed RNA-Seq on Klebsiella pneumoniae and Acinetobacter baumanii treated with ciprofloxacin, gentamicin, or meropenem for 0, 10, 30, and 60 minutes. For each, we identified 50 responsive transcripts whose expression levels differ most between susceptible and resistant organisms upon antibiotic exposure. We measured their expression using a multiplexed fluorescent RNA hybridization assay (NanoString) in 69 clinical isolates, including a “test set” of multidrug-resistant strains from the CDC, in an 8-hour assay. Gene expression data from test strains were compared against known susceptible and resistant isolates to generate a transcriptional susceptibility metric. We also designed NanoString probes to detect 5 carbapenemase genes (KPC-2, KPC-3, NDM-1, OXA-48, and CTX-M15). Results Across all bacteria-antibiotic pairs tested, a susceptibility metric derived from these transcriptional assays correctly grouped isolates in 167 of 173 tests (Table 1), with only 1 of 88 resistant isolates misclassified as susceptible. Five of six incorrectly grouped isolates were within one dilution of the breakpoint MIC, including the misclassified resistant isolate. Conclusion We demonstrate phenotypic antibiotic resistance detection based on fluorescent RNA detection in an 8-hour assay. We have previously published proof-of-concept studies that this assay may be run on a positive blood culture bottle with minimal sample processing. By coupling this phenotypic assay with detection of genetic resistance determinants (demonstrated for carbapenemases) in a single assay, strains with unexplained resistance can be prioritized for further study. Disclosures All authors: No reported disclosures.

scholarly journals Fast Antibiotic Susceptibility Testing via Raman Microspectrometry on Single Bacteria: An MRSA Case Study

ACS Omega ◽  
2021 ◽  
Author(s):  
Armelle Novelli Rousseau ◽  
Nicolas Faure ◽  
Fabian Rol ◽  
Zohreh Sedaghat ◽  
Joël Le Galudec ◽  
...  
Keyword(s):  
Antibiotic Susceptibility ◽  
Susceptibility Testing ◽  
Antibiotic Susceptibility Testing ◽  
Raman Microspectrometry

scholarly journals Longitudinal Characterization and Transmission Dynamics of Antibiotic-Resistant Organisms in an ICU (LOCATE AROs)

2020 ◽  
Vol 41 (S1) ◽  
pp. s42-s43
Author(s):  
Kimberley Sukhum ◽  
Candice Cass ◽  
Meghan Wallace ◽  
Caitlin Johnson ◽  
Steven Sax ◽  
...  
Keyword(s):  
Antibiotic Susceptibility ◽  
Environmental Samples ◽  
Susceptibility Testing ◽  
Marrow Transplant ◽  
Transmission Dynamics ◽  
Hospital Environment ◽  
Antibiotic Susceptibility Testing ◽  
Antibiotic Resistant ◽  
Clonal Group ◽  
Communal Areas

Background: Healthcare-associated infections caused by antibiotic-resistant organisms (AROs) are a major cause of significant morbidity and mortality. To create and optimize infection prevention strategies, it is crucial to delineate the role of the environment and clinical infections. Methods: Over a 14-month period, we collected environmental samples, patient feces, and patient bloodstream infection (BSI) isolates in a newly built bone marrow transplant (BMT) intensive care unit (ICU). Samples were collected from 13 high-touch areas in the patient room and 4 communal areas. Samples were collected from the old BMT ICU, in the new BMT ICU before patients moved in, and for 1 year after patients moved in. Selective microbiologic culture was used to isolate AROs, and whole-genome sequencing (WGS) was used to determine clonality. Antibiotic susceptibility testing was performed using Kirby-Bauer disk diffusion assays. Using linear mixed modeling, we compared ARO recovery across time and sample area. Results: AROs were collected and cultured from environmental samples, patient feces, and BSI isolates (Fig. 1a). AROs were found both before and after a patient entered the ICU (Fig. 1b). Sink drains had significantly more AROs recovered per sample than any other surface area (P < .001) (Fig. 1c). The most common ARO isolates were Pseudomonas aeruginosa and Stenotrophomonas maltophila (Fig. 1d). The new BMT ICU had fewer AROs recovered per sample than the old BMT ICU (P < .001) and no increase in AROs recovered over the first year of opening (P > .05). Furthermore, there was no difference before versus after patients moved into the hospital (P > .05). Antibiotic susceptibility testing reveal that P. aeruginosa isolates recovered from the old ICU were resistant to more antibiotics than isolates recovered from the new ICU (Fig. 2a). ANI and clonal analyses of P. aeruginosa revealed a large cluster of clonal isolates (34 of 76) (Fig. 2b). This clonal group included isolates found before patients moved into the BMT ICU and patient blood isolates. Furthermore, this clonal group was initially found in only 1 room in the BMT ICU, and over 26 weeks, it was found in sink drains in all 6 rooms sampled (Fig. 2b). Conclusions: AROs are present before patients move into a new BMT ICU, and sink drains act as a reservoir for AROs over time. Furthermore, sink-drain P. aeruginosa isolates are clonally related to isolates found in patient BSIs. Overall, these results provide insight into ARO transmission dynamics in the hospital environment.Funding: Research reported in this publication was supported by the Washington University Institute of Clinical and Translational Sciences grant UL1TR002345 from the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH). The content is solely the responsibility of the authors and does not necessarily represent the official view of the NIH.Disclosures: None

scholarly journals Reproducibility of Control Strains for Antibiotic Susceptibility Testing

1976 ◽  
Vol 10 (3) ◽  
pp. 436-440 ◽  
Author(s):  
M. B. Coyle ◽  
M. F. Lampe ◽  
C. L. Aitken ◽  
P. Feigl ◽  
J. C. Sherris
Keyword(s):  
Antibiotic Susceptibility ◽  
Susceptibility Testing ◽  
Antibiotic Susceptibility Testing

Nocardiosis With Brain Abscess Due to an Unusual Species, Nocardia transvalensis

2003 ◽  
Vol 127 (2) ◽  
pp. 224-226 ◽  
Author(s):  
Rebecca F. Yorke ◽  
Emilie Rouah
Keyword(s):  
Early Identification ◽  
Antibiotic Susceptibility ◽  
Susceptibility Testing ◽  
Subsequent Development ◽  
Pulmonary Involvement ◽  
Antibiotic Susceptibility Testing ◽  
Nocardia Species ◽  
Pathologic Findings ◽  
Brain Abscesses ◽  
Clinically Significant

Abstract The identification of Nocardia transvalensis, an unusual and probably underrecognized cause of nocardial infection, is clinically significant because of this species' resistance to aminoglycosides, a standard antinocardial therapy. Diagnosis requires analytic methods available predominately in reference laboratories. We report a case of disseminated infection with N transvalensis with primary pulmonary involvement and subsequent development of brain abscesses, and review the literature to date. Familiarity with the epidemiology, pathologic findings, and clinical significance of this and other unusual Nocardia species may increase early identification and antibiotic susceptibility testing in cases of nocardial infection.

scholarly journals Emerging Microtechnologies and Automated Systems for Rapid Bacterial Identification and Antibiotic Susceptibility Testing

2017 ◽  
Vol 22 (6) ◽  
pp. 585-608 ◽  
Author(s):  
Yiyan Li ◽  
Xing Yang ◽  
Weian Zhao
Keyword(s):  
Antibiotic Susceptibility ◽  
Susceptibility Testing ◽  
Point Of Care ◽  
Single Cells ◽  
Turnaround Time ◽  
Resistant Bacteria ◽  
Representative Point ◽  
Antibiotic Susceptibility Testing ◽  
Bacterial Identification ◽  
Automated Systems

Rapid bacterial identification (ID) and antibiotic susceptibility testing (AST) are in great demand due to the rise of drug-resistant bacteria. Conventional culture-based AST methods suffer from a long turnaround time. By necessity, physicians often have to treat patients empirically with antibiotics, which has led to an inappropriate use of antibiotics, an elevated mortality rate and healthcare costs, and antibiotic resistance. Recent advances in miniaturization and automation provide promising solutions for rapid bacterial ID/AST profiling, which will potentially make a significant impact in the clinical management of infectious diseases and antibiotic stewardship in the coming years. In this review, we summarize and analyze representative emerging micro- and nanotechnologies, as well as automated systems for bacterial ID/AST, including both phenotypic (e.g., microfluidic-based bacterial culture, and digital imaging of single cells) and molecular (e.g., multiplex PCR, hybridization probes, nanoparticles, synthetic biology tools, mass spectrometry, and sequencing technologies) methods. We also discuss representative point-of-care (POC) systems that integrate sample processing, fluid handling, and detection for rapid bacterial ID/AST. Finally, we highlight major remaining challenges and discuss potential future endeavors toward improving clinical outcomes with rapid bacterial ID/AST technologies.

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