scholarly journals A portable and high-integrated 3D microfluidic chip for bacterial quantification and antibiotic susceptibility testing

2021 ◽  
Author(s):  
Wenshuai Wu ◽  
Gaozhe Cai ◽  
Yang Liu

On-site single-cell antibiotic susceptibility testing (sc-AST) provides unprecedented technical potential to improve the treatment of bacterial infections and study heterogeneous resistance to antibiotics. Herein, we developed a portable and high-integrated 3D polydimethylsiloxane (PDMS) chip to perform fast and on-site bacteria quantification and sc-AST. The 3D arrangement of the chambers significantly improved the integration of reaction units (~10000/cm2) and widened the dynamic range to 5 orders of magnitude. A capillary valve-based flow distributor was adopted for flow equidistribution in 64 parallel channels and uniform sample loading in as short as 2 s. The degassed PDMS enabled this device to independently dispense the sample into 3D chamber array with almost 100% efficiency. The quantification of Escherichia coli (E. coli) strains with various activity was accomplished in 0.5-2 h, shortened by 20 h in comparison to the traditional plate counting. The functionality of our platform was demonstrated with several effective antibiotics by determining minimum inhibitory concentrations at single-cell level. Furthermore, we utilized the lyophilization of test reagents and needle-mediated reagents rehydration to realize one-step on-site sc-AST. The results indicate that the proposed sc-AST platform is portable, highly sensitive, fast, accurate and user-friendly, thus it has the potential to facilitate precise therapy in time and monitor the treatment. Meanwhile, it could serve as an approach for investigating the mechanisms of heteroresistance at single-cell resolution.

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Xuzhi Zhang ◽  
Xiaoyu Jiang ◽  
Qianqian Yang ◽  
Yong Xu ◽  
Xiaochun Wang ◽  
...  

AbstractUser-friendly phenotypic antibiotic susceptibility testing (AST) methods are urgently needed in many fields including clinical medicine, epidemiological studies and drug research. Herein, we report a convenient and cost-effective phenotypic AST method based on online monitoring bacterial growth with a developed 8-channel contactless conductometric sensor (CCS). Using E. coli and V. parahaemolyticus as microorganism models, as well as enoxacin, florfenicol, ampicillin, kanamycin and sulfadiazine as antibiotic probes. The minimum inhibitory concentration (MIC) determination was validated in comparison with standard broth microdilution (BMD) assay. The total essential agreements between the CCS AST assays and the reference BMD AST assays are 68.8–92.3%. The CCS has an approximate price of $9,000 (USD). Requiring neither chemical nor biotic auxiliary materials for the assay makes the cost of each sample < $1. The MICs obtained with the automated CCS AST assays are more precise than those obtained with the manual BMD. Moreover, in 72 percent of the counterpart, the MICs obtained with the CCS AST assays are higher than that obtained with the BMD AST assays. The proposed CCS AST method has advantages in affordability, accuracy, sensitivity and user-friendliness.


mBio ◽  
2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Pikkei Wistrand-Yuen ◽  
Christer Malmberg ◽  
Nikos Fatsis-Kavalopoulos ◽  
Moritz Lübke ◽  
Thomas Tängdén ◽  
...  

ABSTRACT Many patients with severe infections receive inappropriate empirical treatment, and rapid detection of bacterial antibiotic susceptibility can improve clinical outcome and reduce mortality. To this end, we have developed a multiplex fluidic chip for rapid phenotypic antibiotic susceptibility testing of bacteria. A total of 21 clinical isolates of Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus were acquired from the EUCAST Development Laboratory and tested against amikacin, ceftazidime, and meropenem (Gram-negative bacteria) or gentamicin, ofloxacin, and tetracycline (Gram-positive bacteria). The bacterial samples were mixed with agarose and loaded in an array of growth chambers in the chip where bacterial microcolony growth was monitored over time using automated image analysis. MIC values were automatically obtained by tracking the growth rates of individual microcolonies in different regions of antibiotic gradients. Stable MIC values were obtained within 2 to 4 h, and the results showed categorical agreement with reference MIC values as determined by broth microdilution in 86% of the cases. IMPORTANCE Prompt and effective antimicrobial therapy is crucial for the management of patients with severe bacterial infections but is becoming increasingly difficult to provide due to emerging antibiotic resistance. The traditional methods for antibiotic susceptibility testing (AST) used in most clinical laboratories are reliable but slow with turnaround times of 2 to 3 days, which necessitates the use of empirical therapy with broad-spectrum antibiotics. There is a great need for fast and reliable AST methods that enable starting targeted treatment within a few hours to improve patient outcome and reduce the overuse of broad-spectrum antibiotics. The multiplex fluidic chip for phenotypic AST described in the present study may enable data on antimicrobial resistance within 2 to 4 h, allowing for an early initiation of appropriate antibiotic therapy.


Lab on a Chip ◽  
2013 ◽  
Vol 13 (2) ◽  
pp. 280-287 ◽  
Author(s):  
Jungil Choi ◽  
Yong-Gyun Jung ◽  
Jeewoo Kim ◽  
Sungbum Kim ◽  
Yushin Jung ◽  
...  

2021 ◽  
Author(s):  
Petra Jusková ◽  
Steven Schmitt ◽  
André Kling ◽  
Darius G. Rackus ◽  
Martin Held ◽  
...  

ABSTRACTRapid identification of a pathogen and the measurement of its antibiotic susceptibility are key elements in the diagnostic process of bacterial infections. Microfluidic technologies offer great control over handling and manipulation of low sample volumes with the possibility to study microbial cultures on the single-cell level. Downscaling the dimensions of cultivation systems directly results in a lower number of bacteria required for antibiotic susceptibility testing (AST) and thus in a reduction of the time to result. The developed platform presented in this work allows the reading of pathogen resistance profiles within 2-3 hours based on the changes of the dissolved oxygen levels during bacterial cultivation. The platform contains hundreds of individual growth chambers prefilled with a hydrogel containing oxygen-sensing nanoprobes and different concentrations of antibiotic compounds. The performance of the microfluidic platform is tested using quality control Escherichia coli strains (ATCC 25922 and ATCC 35218) in response to different clinically relevant antibiotics. The achieved results are in agreement with values given in clinical reference guides and independent measurements using a clinical AST protocol. Finally, the platform is successfully used for AST of an E. coli clinical isolate obtained from a patient blood culture.


2019 ◽  
Author(s):  
Pikkei Wistrand-Yuen ◽  
Christer Malmberg ◽  
Nikos Fatsis-Kavalopoulos ◽  
Moritz Lübke ◽  
Thomas Tängdén ◽  
...  

AbstractMany patients with severe infections receive inappropriate empirical treatment and rapid detection of bacterial antibiotic susceptibility can in this context improve clinical outcome and reduce mortality. We have to this end developed a high-throughput fluidic chip for rapid phenotypic antibiotic susceptibility testing of bacteria. A total of 21 clinical isolates of Escherichia coli, Klebsiella pneumoniae and Staphylococcus aureus were acquired from the EUCAST Development Laboratory and tested against amikacin, ceftazidime and meropenem (Gramnegative bacteria) or gentamicin, ofloxacin and tetracycline (Gram-positive bacteria). The bacterial samples were mixed with agarose and loaded in 8 separate growth chambers in the fluidic chip. The chip was thereafter connected to a reservoir lid containing different antibiotics and a pump used to draw growth media with or without antibiotics into the chip for generation of diffusion-limited antibiotic gradients in the growth chambers. Bacterial microcolony growth was monitored using darkfield time-lapse microscopy and quantified using a cluster image analysis algorithm. Minimum inhibitory concentration (MIC) values were automatically obtained by tracking the growth rates of individual microcolonies in different regions of antibiotic gradients. Stable MIC values were obtained within 2-4 hours and the results showed categorical agreement to reference MIC values as determined with broth microdilution in 86% of the cases.ImportancePrompt and effective antimicrobial therapy is crucial for the management of patients with severe bacterial infections but is becoming increasingly difficult to provide due to emerging antibiotic resistance. The traditional methods for antibiotic susceptibility testing (AST) used in most clinical laboratories are reliable but slow with turnaround times of 2-3 days, which necessitates the use of empirical therapy with broad-spectrum antibiotics. There is a great need for fast and reliable AST methods that enable start of targeted treatment within a few hours to improve patient outcome and reduce overuse of broad-spectrum antibiotics. The high-throughput fluidic chip for phenotypic AST described in the present study enables data on antimicrobial resistance within 2-4 hours allowing for an early initiation of appropriate antibiotic therapy.


ACS Omega ◽  
2021 ◽  
Author(s):  
Armelle Novelli Rousseau ◽  
Nicolas Faure ◽  
Fabian Rol ◽  
Zohreh Sedaghat ◽  
Joël Le Galudec ◽  
...  

2020 ◽  
Vol 41 (S1) ◽  
pp. s42-s43
Author(s):  
Kimberley Sukhum ◽  
Candice Cass ◽  
Meghan Wallace ◽  
Caitlin Johnson ◽  
Steven Sax ◽  
...  

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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