Bacterial classification and antibiotic susceptibility testing on an integrated microfluidic platform

Lab on a Chip ◽  
2021 ◽  
Author(s):  
Alexandros A. Sklavounos ◽  
Carine R. Nemr ◽  
Shana O. Kelley ◽  
Aaron R. Wheeler
Keyword(s):  
Antibiotic Susceptibility ◽  
Susceptibility Testing ◽  
Microfluidic System ◽  
Antibiotic Susceptibility Testing ◽  
Metabolic Markers ◽  
Microfluidic Platform ◽  
Bacterial Classification ◽  
Digital Microfluidic

An ‘all in one’ digital microfluidic system is reported that automates the preparation and testing of samples for antibiotic susceptibility and bacterial classification, relying on three metabolic markers.

scholarly journals A microfluidic platform for rapid, stress-induced antibiotic susceptibility testing of Staphylococcus aureus

Lab on a Chip ◽  
2012 ◽  
Vol 12 (21) ◽  
pp. 4523 ◽  
Author(s):  
Maxim Kalashnikov ◽  
Jean C. Lee ◽  
Jennifer Campbell ◽  
Andre Sharon ◽  
Alexis F. Sauer-Budge
Keyword(s):  
Staphylococcus Aureus ◽  
Antibiotic Susceptibility ◽  
Susceptibility Testing ◽  
Antibiotic Susceptibility Testing ◽  
Microfluidic Platform

Nanoliter-Sized Microchamber/Microarray Microfluidic Platform for Antibiotic Susceptibility Testing

2018 ◽  
Vol 90 (24) ◽  
pp. 14137-14144 ◽  
Author(s):  
Morteza Azizi ◽  
Meisam Zaferani ◽  
Belgin Dogan ◽  
Shiying Zhang ◽  
Kenneth W. Simpson ◽  
...  
Keyword(s):  
Antibiotic Susceptibility ◽  
Susceptibility Testing ◽  
Antibiotic Susceptibility Testing ◽  
Microfluidic Platform

A multiplexed microfluidic platform for rapid antibiotic susceptibility testing

2013 ◽  
Vol 49 ◽  
pp. 118-125 ◽  
Author(s):  
Ritika Mohan ◽  
Arnab Mukherjee ◽  
Selami E. Sevgen ◽  
Chotitath Sanpitakseree ◽  
Jaebum Lee ◽  
...  
Keyword(s):  
Antibiotic Susceptibility ◽  
Susceptibility Testing ◽  
Antibiotic Susceptibility Testing ◽  
Microfluidic Platform

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

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