Electrochemical metabolic activity detecting device
1. A method for detecting metabolic activity of target cells in a sample, the method comprising:
- concentrating the target cells in a nanoliter well;
introducing into the well a reporter compound that exhibits a change in electrochemical state in response to metabolic activity of the target cells;
determining any change in an electrochemical state of contents in the well over a time period; and
detecting metabolic activity or viability of the target cells based on a determined change in the electrochemical state of contents in the well.
Methods and devices for detecting metabolic activity of target cells in a sample. The target cells are concentrated in a nanoliter well having a microfilter. A reporter compound that exhibits a change in electrochemical state in response to metabolic activity of the target cells is introduced. Metabolic activity or viability of the target cells is detected based on a determined change in the electrochemical state of contents in the well.
|NANOSTRUCTURED MICROELECTRODES AND BIOSENSING DEVICES INCORPORATING THE SAME|
Patent #US 20110233075A1
Current AssigneeThe Governing Council of the University of Toronto
Sponsoring EntityThe Governing Council of the University of Toronto
|Device and methods for detecting the response of a plurality of cells to at least one analyte of interest|
Patent #US 20050014129A1
Current AssigneeVanderbilt University
Sponsoring EntityVanderbilt University
|SYSTEMS AND METHODS FOR MULTIPLEXED ELECTROCHEMICAL DETECTION|
Patent #US 20130316340A1
Current AssigneeThe Governing Council of the University of Toronto
Sponsoring EntityShana O. Kelley, Edward H. Sargent, Brian Lam
|VERSATILE AND SENSITIVE BIOSENSOR|
Patent #US 20140342359A1
Current AssigneeThe Governing Council of the University of Toronto
Sponsoring EntityThe Governing Council of the University of Toronto
|DEVICE FOR CAPTURE OF PARTICLES IN A FLOW|
Patent #US 20160061811A1
Current AssigneeThe Governing Council of the University of Toronto
Sponsoring EntityThe Governing Council of the University of Toronto
- 1. A method for detecting metabolic activity of target cells in a sample, the method comprising:
concentrating the target cells in a nanoliter well; introducing into the well a reporter compound that exhibits a change in electrochemical state in response to metabolic activity of the target cells; determining any change in an electrochemical state of contents in the well over a time period; and detecting metabolic activity or viability of the target cells based on a determined change in the electrochemical state of contents in the well.
- View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
The present disclosure claims priority from U.S. provisional patent application No. 62/069,601, filed Oct. 28, 2014, the entirety of which is hereby incorporated by reference.
The present disclosure relates to methods and systems for detecting metabolic activity of targets cells in a sample. In some examples, the present disclosure relates to electrochemical detection of antibiotic susceptibility.
The overuse of antibiotics and the prescription of first-line antibiotics to which a pathogen is not susceptible, contribute to rising antibiotic resistance rates, which is a growing threat to public health worldwide.1 Urinary tract infections are among the most prevalent bacterial infections.2 Gold-standard antibiotic susceptibility tests for urinary tract infections rely on culture and typically require 1-3 days in order to allow the bacteria to multiply to detectable levels.3 After pre-culture of the bacteria, an additional 18 hours are typically required to perform standard susceptibility tests. Reducing the time needed to determine the susceptibility profile of urinary tract infections could improve clinical outcomes, especially in the case of the most severe infections that lead to urosepsis.4 Rapid testing could also contribute to decreased unnecessary antibiotic use,5 and could increase the efficiency of centralized diagnostic laboratories. Treatment of other infections may similarly benefit from improved susceptibility testing.
Tests for antibiotic resistance that rely on enzymatic amplification of antibiotic-resistance genes have been found to reduce turnaround times compared to culture.6,7,8,9 Unfortunately, these assays often require a pre-incubation step to allow the bacteria to multiply, and, further, often require several hours to amplify the genes of interest. Gene-based assays are also typically limited by the requirement of knowing a priori which genes confer resistance. Dozens of constantly-evolving genes may be implicated in resistance to a given antibiotic, and it may be impractical to test for all possible mutations simultaneously.10
Assays that monitor bacterial viability in response to antibiotics may overcome at least some limitations of genetic tests. These tests report directly on the question of greatest clinical importance: whether a given antibiotic decreases bacterial survival. New assays for antibiotic resistance include the detection of bacterial motion using AFM cantilevers,11 electrochemical measurements of bacterial growth,12,13,14,15,16 optical detection of bacterialgrowth,17,18 and optical detection of redox reporters of bacterial metabolism.19,20,21,22 In assays that detect metabolically-active pathogens, the bacteria are typically incubated with the antibiotic and a redox reporter of metabolism such as resazurin or methylene blue. Metabolically-active bacteria create a reducing environment and either directly or indirectly reduce the compound, and the change in redox state is read out as a change in color or fluorescence. Resistant bacteria continue to multiply and metabolize the compound, while susceptible bacteria do not.
Successful detection using this type of approach typically hinges on the requirement that a sufficient quantity of the reduced form of the reporter compound accumulates above the detection threshold, a delay that may take at least 12 hours in milliliter-scale culture.19 Strategies have been proposed that seek to confine bacteria in microliter and nanoliter volumes with the goal of reducing the time of detection by increasing the local concentration of the bacteria.20,21,23,24,25 In the most sensitive of these optical techniques, the sample is divided into millions of nanoliter droplets and the signal is readout sequentially from each droplet with a high-powered fluorescence microscope.20,21,25 Despite the increase in local effective concentration provided by this approach, several hours are typically still required for analysis. Moreover, many of these devices only detect the presence or absence of a pathogen and not its antibiotic susceptibility profile.25,26,27
In some examples, the present disclosure describes a device suitable for detecting metabolic activity of target cells in a sample. The device includes: a nanoliter well including: an inlet for receiving the sample; a microfilter for inhibiting the target cells from exiting the well through an outlet of the well; and electrodes in the well for sensing an electrochemical state of contents in the well.
In some examples, the device may further include: a plurality of the wells.
In some examples, the present disclosure describes a method for detecting metabolic activity of target cells in a sample. The method includes: concentrating the target cells in a nanoliter well; introducing into the well a reporter compound that exhibits a change in electrochemical state in response to metabolic activity of the target cells; determining any change in an electrochemical state of contents in the well over a time period; and detecting metabolic activity or viability of the target cells based on a determined change in the electrochemical state of contents in the well.
Reference will now be made, by way of example, to the accompanying drawings which show example embodiments of the present application, and in which:
Similar reference numerals may have been used in different figures to denote similar components.
Despite several recent advances in ultrasensitive electrochemical detection of bacteria,28,29,30 few devices have been reported for direct electrochemical detection of antibiotic resistance. Electrochemical readout typically requires only simple electronics, which may allow direct electronic detection of antibiotic susceptibility from confined nanoliter droplets without bulky optical instrumentation for readout.
The present disclosure describes example methods and devices for electrochemical detection of metabolic activity of biological agents, such as bacteria. Examples of the present disclosure may be used to help identify the antibiotic susceptibility profile of bacteria. The present disclosure describes development of an example assay that may use electrochemical readout to detect metabolically active bacteria. In examples described herein, the electrochemical reduction of a reporter compound, such as resazurin, is monitored to establish the presence of live bacteria, and further may be analyzed in the presence of antibiotics to determine resistance profiles.
In various examples discussed herein, resazurin may be used as the reporter compound. Generally, the reporter compound may be any compound that exhibits an electrochemical change (e.g., change in oxidation state) in response to metabolic activity of the cells of interest (e.g., bacteria). For a given concentration or amount of the reporter compound, the degree to which the electrochemical state of the reporter compound has changed over a given time period may be indicative of the metabolic activity of the cells of interest. The reporter compound may be resazurin, methylene blue, formazan, or tetrazolium salts, or any other compound having a redox response to metabolic activity of the target cell.
Redox dyes that are reduced by metabolically-active bacteria have been used as optical indicators of bacterial viability in the presence of antibiotics,19 but have not offered significant improvement in the delivery of rapid profiling results. In the present disclosure, resazurin, a commonly-employed reporter used to optically assess cell viability,19 may be used for electrochemical detection of bacterial antibiotic susceptibility.
When implemented using the disclosed device, the sensitivity of this readout method may produce improvements in assay speed. Although examples described herein use resazurin as a reporter compound, other compounds that have an electrochemical change (e.g., change in oxidation state) in response to metabolic activity of the target bacterial (or other target cell) may be used.
In the presence of an ineffective antibiotic, resistant bacteria will continue to multiply and create a reducing environment which converts resazurin to resorufin. On the other hand, since effective antibiotics hinder bacterial metabolism, they will prevent or inhibit reduction of the dye by susceptible bacteria. As resazurin and resorufin have different electrochemical signatures (as discussed below),31′32 using differential pulse voltammetry it is possible to distinguish between the two electrochemical states of the dye and thus determine whether the bacteria is susceptible.
The above characterization of resazurin illustrates the suitability of this compound as an indicator of bacterial metabolic activity. In examples described herein, this characteristic of resazurin may be used as the basis of methods and devices for detecting susceptibility of bacteria to antibiotics.
In general, by sealing off the well inlets 120 and outlets 125 (e.g., using oil plugs, valves or a combination thereof), the contents of each well are isolated. By restricting the solution volume to that of the well, after trapping the target cells, the effective concentration of the target cells is increased.
The device can then be incubated at 37° C. to allow the captured bacteria to multiply. The reporter compound will exhibit a change in electrochemical state if there are metabolically active target cells in the well. For example, if testing for antibiotic susceptibility of bacteria and using resazurin as the reporter compound, then antibiotic-susceptible bacteria captured within a well 105 will exhibit decreased or no metabolic activity (e.g., inhibited from reproducing) due to the presence of the introduced antibiotic, while resistant bacteria will exhibit greater metabolic activity (e.g., continue to multiply unhindered) compared to the antibiotic-susceptible bacteria. Accordingly, the antibiotic-resistant bacteria will reduce the resazurin to a greater extent than the antibiotic-susceptible bacteria (e.g., the antibiotic-susceptible bacteria may not reduce resazurin at all while the antibiotic-resistant bacteria will). The degree to which reduction has occurred can be distinguished by measuring the current using the electrodes in each well 105.
As discussed further below, in some examples, the disclosed device may be used to detect a clinically relevant concentration of bacteria with a relatively short (e.g., 30 minute) incubation. In examples discussed below, it may be shown that the antibiotic susceptibility profile of a clinically-relevant concentration of bacteria in urine can be determined using a 1 hour incubation without a pre-incubation step. Thus, examples of the present disclosure may enable antibiotic resistance phenotyping on a relatively short time scale.
In some examples, the disclosed device may enable a decrease in detection time, to improve the clinical utility of reporter compounds such as resazurin as an indicator of metabolic activity. In examples of the disclosed device, the target cells (e.g., bacteria) may be concentrated in a nanoliter well. By conducting the resazurin assay within this small volume, the time required to detect the presence of viable bacteria was found to be reduced to less than one hour. The integration of electrochemical sensors (e.g., electrodes) directly into each of the wells may allow for relatively rapid and direct readout of the antibiotic susceptibility profile in a relatively small volume, without requiring bulky optical instrumentation to sequentially readout thousands of nanoliter droplets.
The present disclosure may provide advantages over conventional approaches. By concentrating the bacteria inside miniaturized wells, the local effective concentration of the bacteria may be increased. For example, 10 bacteria captured in a 1 nL well is equivalent to 10 000 cfu/μL, while 10 bacteria captured in 1 μL well gives a concentration of only 10 cfu/μL. The greater the concentration of bacteria per well, the faster the turnover of resazurin and accumulation of the target redox molecule. As the signal from DPV is directly proportional to the concentration of the redox molecule, an increase in local concentration of bacteria increases the magnitude of the signal change acquired, and hence easier and/or quicker detection. Confinement of the assay within a nanoliter volume may provide another advantage. As resazurin is reduced, it is prevented from diffusing into bulk solution, thus allowing the reduced form to rapidly accumulate to detectable levels.
In examples discussed herein, the device may be configured with wells having dimensions of about 100 μm×50 μm×550 μm, which is equivalent to a volume of about 2.75 nL. By providing a plurality of such wells in a single example device, multiple measurements (e.g., one from each well) may be obtained per single sample, which may help to increase the accuracy of the device. For example, 15 measurements may be performed per sample. A single measurement from a given well may vary from the mean measurement by as much as 40%. However, the standard error after 15 measurements may be reduced to as little as 5%. In some examples, additionally, each well may include a plurality of working electrodes, to obtain multiple measurements from each well, which may be averaged for each well.
An example process for fabricating the example disclosed device is now discussed. Fabrication may be performed by patterning gold electrodes on a glass substrate to act as the working, counter and reference electrodes.
The fabricated device may be further processed, for example to remove air bubbles. For example, prior to use, the device may be filled with EtOH and flushed with phosphate buffered saline (PBS). In this example, 100 μL of microbeads (Sigma Aldrich, St. Louis, Mo.) with a 5 μm diameter diluted 1:100 in PBS were introduced at 10 μL/min to form the in-well filters.
Various example studies were carried out to characterize and investigate performance of the example device discussed above.
The pore size of the in-well filters, in these examples using microbeads, may be characterized. As the microbeads are substantially spherical, equations pertaining to the packing of spherical objects may be useful. The densest possible packing of spheres is hexagonal close packing, illustrated in
where Dp is the diameter of the pores and Ds is the diameter of the spheres. For 5 μm diameter beads, assuming hexagonal close packing, the pore diameter is 0.77 μm (represented by the small dark circle in
To verify the utility of the microbeads for capturing bacteria in the wells, capture efficiency of bacteria was measured for wells with and without microbead filters.
As the microbeads assemble randomly, there is expected to be a distribution of pore sizes, which may allow some bacteria to escape the filter. Accordingly, the capture efficiency of E. coli was also investigated as a function of flow rate. Example results are shown in
To measure the stability of the microbead filters, 100 μL of microbeads was injected at 20 μL/min into a test version of the device without the in-well electrodes. The outer-channel inlet and the inner-channel outlet were blocked, forcing the fluid through the wells. After stopping the flow, microscope images were acquired over the course of 1 hour. Examples of these images are shown in
In some examples, the filter may comprise microbeads of different sizes, which may be useful to decrease the pore size of the filter. For example, microbeads may be introduced in decreasing sizes (e.g., 5 μm microbeads are first introduced, then 2 μm microbeads), in order to achieve pore size smaller than using a single microbead size, while ensuring that smaller sized microbeads do not inadvertently wash out of the well.
To calculate the capture efficiency of the in-well filters, the captured bacteria was eluted and incubated off-chip on agar plates. To elute the bacteria, a buffer was injected while directing the fluid flow backwards through the filters. This was accomplished by blocking the outer-channel inlet and the inner-channel outlet, resulting in backflow of buffer from the outer-channel outlet, entering the wells via the well outlets and exiting via the well inlets, and finally exiting the example device from the inner-channel inlet. The backflow of buffer forces bacteria out of the filters back towards the inlet. The eluent was cultured overnight at 37° C. and the colonies were counted.
Effect of electrodeposition and surface fouling on the on-chip electrodes was also studied for the example device.
As described above with reference to
An example study was carried out to determine bacterial capture efficiency. In this study, a 100 μL volume of serial dilutions of E. coli were introduced into the capture device at 10 μL/min. After capture, the device was washed with 100 μL of PBS buffer. Finally the bacteria were eluted in sterile PBS buffer. The eluted volume was plated on LB agar plates overnight at 37° C. and the colonies were counted.
Another example study was carried out to investigate electrochemical detection of bacteria using the example device. Serial dilutions of E. coli were spiked in buffer and introduced into the chip at 20 μL/min followed by 200 μL of 1 mM resazurin in LB broth. Air was flushed through the device to form the wells followed by FC-40, a fluorinated oil. The device was incubated in a water bath at 37° C.
An antibiotic susceptibility microdilution assay was also performed using the example device. Cultured E. coli were diluted to 100 cfu/μL and incubated at 37° C. in a 96 well plate in Nutrient Broth with serial dilutions of ciprofloxacin and ampicillin. After 24 hours, the absorbance at 600 nm was measured.
The performance of the example device for electrochemical detection in urine was investigated. Human urine (BioreclamationIVT) was centrifuged at 5000 g for 5 min to remove large particulates. E. coli and K. pneumoniae were diluted to 100 cfu/μL and spiked in the urine. Samples (200 μL) were introduced at 20 μL/min. Next, 200 μL of either ampicillin or ciprofloxacin in 1 mM resazurin and LB media were introduced at 20 μL/min. Air was flushed through the device to form the wells followed by FC-40 (200 μL) (Sigma Aldrich, St. Louis, Mo.). Thus the total volume of all solutions introduced is 600 μL which requires 30 min to process at 20 μL/min. The device was incubated in a water bath at 37° C. for 1 hour. 10 minutes were required to scan the leads. Thus the total time for the assay from sample introduction to readout was 1 hour and 40 minutes.
The performance of the example device was also investigated for electrochemical detection in unpurified urine. E. coli were diluted to 100 cfu/μL and spiked in the unpurified human urine (BioreclamationIVT). The spiked urine (200 μL) was passed through a 10 μm filter to remove large particulates and directly introduced at 20 μL/min into the chip. Next, 200 μL of either ampicillin or ciprofloxacin in 1 mM resazurin and LB media were introduced at 20 μL/min. Air was flushed through the device to form the wells followed by FC-40 (Sigma Aldrich, St. Louis, Mo.). The device was incubated in a water bath at 37° C.
One example study tested the limit of detection that could be achieved by monitoring the electrochemical signal of resazurin by incubating serial dilutions of Escherichia coli (E. coli) with 1 mM resazurin in LB culture media for 5 hours at 37° C.
The average peak currents at −0.35 V as a function of bacterial concentration are plotted in
In the example study, a detection limit of 100 CFU/μL was found, which may be clinically relevant and has been used as a threshold level for the presence of bacteriuria.33,2 The peak signals was found to decrease with increasing bacterial concentration, as expected given that viable bacteria convert resazurin to resorufin. As there is significant overlap between peaks I and II, a decrease in the height of peak I causes peak II to decrease as well.
The detection limit of electrochemical and fluorescent detection of bacterial viability using resazurin was also compared. This comparison found a similar limit of detection of 100 CFU/μL indicating that electrochemical detection of resazurin may be just as sensitive as fluorescent readout.
Compared to detection using fluorescence, using electrochemistry for detection may be more useful in that it typically does not require complicated or bulky instrumentation for readout and the sensors (e.g., electrodes) may be integrated directly into the culture chambers. In contrast, in the most sensitive fluorescence assays, the assay is typically performed in a series of nanoliter droplets which usually require a high-powered fluorescence microscope for sequential readout of the droplets. Using electrochemistry, it may be possible to integrate the sensors directly into the nanoliter culture chambers, eliminating the need for expensive optical equipment for readout. The electronics required for electrochemical readout may be integrated into a small benchtop or handheld device, which may help to lower the cost and/or footprint of the device.
Another study was carried out for validation of in-well bacterial capture using the example device.
To quantitate the capture efficiency of the example device, serial dilutions of a 100 μL volume of GFP E. coli were introduced at a flow rate of 10 μL/min. After capture, bacteria were introduced onto agar plates and the E. coli colonies were counted after incubating the plates overnight.
With effective capture demonstrated by the example studies discussed above, other studies were carried out to test the ability of the disclosed device and method to detect viable bacteria captured within the wells. The example device was challenged with E. coli at 100 cfu/μL, a clinically relevant concentration in urinary tract infections.2 This concentration corresponds to over 100 bacteria per well. The time dependence of the signal was studied to determine the minimum time necessary to detect a clinically relevant concentration of viable bacteria.
The above-discussed studies demonstrated the suitability of the disclosed device and method for detection of viable bacteria. Other studies were carried out to assess the suitability of the example device to rapidly determine the antibiotic resistance profile of bacteria in undiluted urine. To better simulate a clinical sample the study tested uropathogenic strains of E. coli (UPEC) and Klebsiella pneumoniae (K. pneumoniae), two of the most common pathogens implicated in urinary tract infections.2 The K. pneumoniae strain was isolated from the urine of an infected patient and produces extended spectrum β-lactamase enzymes which confer resistance to a wide variety of β-lactam antibiotics.2 In this study, susceptibility to two commonly used antibiotics to treat urinary tract infections—ampicillin, a β-lactam antibiotic; and ciprofloxacin, a fluoroquinolone—were tested.35
In order to choose a suitable incubation period for the susceptibility test, the time required for the antibiotics to begin inhibiting bacterial metabolic activity was investigated. To study this, a high concentration of bacteria was used in order to determine the minimum time required for the bacteria to exhibit differential metabolic activity in response to the tested antibiotics. K. pneumoniae at 1×105 cfu/μL were incubated at 37° C. in the presence of ampicillin and ciprofloxacin at 100 μg/mL in LB media and 1 mM resazurin. The increase in fluorescence induced by the conversion of resazurin by metabolically active bacteria was recorded.
As discussed above, the effect of surface fouling induced by incubating the devices with LB media was also studied, with example results shown in
E. coli (UPEC) and K. pneumoniae present at 100 cfu/μL in undiluted urine were introduced into the example device. After capture, a culture medium, resazurin, and either ampicillin or ciprofloxacin were introduced.
For the E. coli strain, the signal was found to be low for all ciprofloxacin concentrations, indicating the bacteria are susceptible to the antibiotic at concentrations above 1 μg/mL (see
For both strains, these results obtained using the example device show good agreement with the MIC determined using the gold standard method which required incubation times over 20 times longer than the on-chip assay using the example device. Good correlation was found between the on-chip susceptibility assay and standard assays with r2 values of 0.81 and 0.82 for E. coli and K. pneumoniae respectively (see
A series of experiments were also performed to determine the antibiotic susceptibility of bacteria in unpurified urine.
E. coli were spiked directly into undiluted and unpurified urine at 100 cfu/μL. The sample was passed through a 10 μm filter that removed large particulates while allowing bacteria to pass.
Representative electrochemical scans acquired using the example device are shown in
To test undiluted urine on chip, large particulates were removed from urine while allowing bacteria to pass through the filter. Various pre-filter sizes were tested to ensure that bacteria spiked in whole urine could be recovered. E. coli were spiked at 1×102 cfu/μL into whole urine and 100 μL of the urine was passed through the pre-filters with various pore diameters. The filtrate was plated on agar plates and incubated overnight at 37° C. The number of bacterial colonies was counted and it was found that using a 10 μm pre-filter, nearly 75% of bacteria could be recovered directly from whole urine.
In various examples, the present disclosure describes methods and devices that may offer faster reported detection of antibiotic susceptibility at clinically relevant concentrations directly from unpurified urine, compared to conventional approaches. The rapid turnaround time may be facilitated by concentrating the bacteria in a nanoliter volume which increases the local effective concentration of bacteria. The turnaround time may be further reduced by incubating the bacteria in isolated nanoliter compartments which allows the reduced form of resazurin to rapidly accumulate to detectable levels by confining diffusion. The disclosed approach is also purely electronic, which may facilitate the development of antibiotic susceptibility tests at the point-of-care by reducing or eliminating the need for expensive and bulky optical equipment.
In a clinical setting, an example of the disclosed device could serve as an alternative to standard susceptibility tests to provide results, for example with a 1 hour incubation, after initial culture-based identification of the bacteria. Currently, conventional antibiotic susceptibility tests typically require an additional 18-24 hours after the initial culture step.
Examples of the disclosed device could also be used in conjunction with standard culture-based antibiotic susceptibility tests to provide point-of-care susceptibility results directly from undiluted urine with a 1 hour incubation period. This may permit the rapid administration of an effective antibiotic in the interim until the results of standard antibiotic susceptibility tests are available 2-3 days later, at which point the therapy could be refined. This may allow doctors to administer a targeted antibiotic almost immediately, which may improve patient outcomes and may curb the rise of antibiotic resistance by decreasing the use of broad spectrum antibiotics. In infections which lead to urosepsis, the most severe UTIs, the disclosed method and device may have clinical utility as these infections typically require immediate administration of effective antibiotics.4
In example studies discussed above, it was found that, when challenged with a sample containing a single bacterial strain, the example disclosed device accurately and rapidly determined the susceptibility to various antibiotics. To enable accurate detection in the case of multiple infecting species (although polymicrobial infections are not common (5%-11%) in urosepsis36), the multiple nanoliter chambers of the example device may be devoted to multiplexed combinations of bacteria combined with local metabolic sensing.
Using an electrochemical approach capable of detecting metabolically active bacteria, the example disclosed method and device was able to achieve the detection of live bacteria using a relatively short 30 minute incubation period. By concentrating and analysing the bacteria within miniaturized compartments in the example device, the time required to detect viable bacteria may be reduced. The assay disclosed herein may be used to monitor bacterial metabolism in response to antibiotics to rapidly readout the antibiotic susceptibility profile. This approach may allow for rapid administration of antibiotics before the results of standard culture-based susceptibility testing are available.
The present disclosure describes examples for detecting the metabolic activity of bacteria, to test susceptibility to antibiotics. However, the present disclosure may also be suitable for detecting the metabolic activity of other target cells. For example, the present disclosure may be used, with modifications as appropriate, for detecting mammalian cells (e.g., cancer cells), fungus (e.g., yeast), and may be used to test for their susceptibility to compounds designed to inhibit their activity. For example, a similar resazurin-based assay may be used to detect metabolic activity of mammalian cells, or fungus. Other reporter compounds, such as methylene blue, formazan or tetrazolium salts, may also be used. The sample may also be other than a buffer or a urine sample; for example, the sample may be any suitable biological or non-biological sample, including biological samples such as a blood sample (which may be pre-treated as appropriate to avoid clogging the microfilters in the example device), a sputum sample, a plasma sample, or other tissue sample, or non-biological samples such as a water sample (e.g., for testing bacteria levels in a water supply) or a buffer sample. Pre-processing may be carried out as appropriate to isolate cells of interest from these samples.
Since the disclosed device and method may provide measurements representing metabolic activity of target cells in each well, the disclosed device and method may be used as a measurement of the relative amount of metabolically active target cells in a sample, compared to a control, for example.
Examples of the present disclosure may be useful for estimating a mean number of cells in a sample, since the change in detectable electrochemical signal may be dependent (e.g., proportional) to the number of cells that affect the reporting compound. To improve such an estimate, measurements from a plurality of wells may be averaged together; additionally or alternatively, a well may have a plurality of electrodes to obtain multiple measurements from the same well, which may all be averaged together. The measurement may be compared against a lookup-table or reference chart that indicates the expected measurement for a known concentration of cells, for example.
Examples of the present disclosure may be used to determine the minimum inhibitory concentration (MIC) of a given antibiotic against a given microorganism. As part of an antimicrobial susceptibility testing (AST) report, the MIC value may be included to guide prescription, for example.
The embodiments of the present disclosure described above are intended to be examples only. The present disclosure may be embodied in other specific forms. Alterations, modifications and variations to the disclosure may be made without departing from the intended scope of the present disclosure. While the systems, devices and processes disclosed and shown herein may comprise a specific number of elements/components, the systems, devices and assemblies could be modified to include additional or fewer of such elements/components. For example, while any of the elements/components disclosed may be referenced as being singular, the embodiments disclosed herein could be modified to include a plurality of such elements/components. Selected features from one or more of the above-described embodiments may be combined to create alternative embodiments not explicitly described. All values and sub-ranges within disclosed ranges are also disclosed. The subject matter described herein intends to cover and embrace all suitable changes in technology. All references mentioned are hereby incorporated by reference in their entirety.
- 1. S. B. Levy and B. Marshall, Nat. Med., 2004, 10, S122-9.
- 2. B. Foxman, Nat. Rev. Urol., 2010, 7, 653-60.
- 3. M. A. Pfaller and R. N. Jones, Arch. Pathol. Lab. Med., 2006, 130, 767-778.
- 4. F. M. E. Wagenlehner, A. Pilatz, and W. Weidner, Int. J. Antimicrob. Agents, 2011, 38, 51-57.
- 5. W. J. McIsaac and C. L. Hunchak, Med. Decis. Making, 2011, 31, 405-11.
- 6. V. Perreten, L. Vorlet-fawer, P. Slickers, R. Ehricht, P. Kuhnert, and J. Frey, J. Clin. Microbiol., 2005, 43, 2291.
- 7. B. Strommenger, C. Kettlitz, G. Werner, and W. Witte, J. Clin. Microbiol., 2003, 41, 4089.
- 8. S. Shenai, F. Krapp, J. Allen, R. Tahirli, R. Blakemore, R. Rustomjee, A. Milovic, M. Jones, S. M. O. Brien, D. H. Persing, S. Ruesch-gerdes, E. Gotuzzo, C. Rodrigues, D. Alland, and M. D. Perkins, N. Engl. J. Med., 2010, 363, 1005-1015.
- 9. K. E. Mach, R. Mohan, E. J. Baron, M.-C. Shih, V. Gau, P. K. Wong, and J. C. Liao, J. Urol., 2011, 185, 148-53.
- 10. M. C. Roberts, S. Schwarz, and H. J. M. Aarts, Front. Microbiol., 2012, 3, 384.
- 11. G. Longo, L. Alonso-Sarduy, L. M. Rio, A. Bizzini, A. Trampuz, J. Notz, G. Dietler, and S. Kasas, Nat. Nanotechnol., 2013, 8, 522-6.
- 12. T. S. Mann and S. R. Mikkelsen, Anal. Chem., 2008, 80, 843-8.
- 13. Y. Lu, J. Gao, D. D. Zhang, V. Gau, J. C. Liao, and P. K. Wong, Anal. Chem., 2013, 85, 3971-6.
- 14. P. Ertl, B. Unterladstaetter, K. Bayer, and S. R. Mikkelsen, Anal. Chem., 2000, 72, 4949-4956.
- 15. P. Ertl, M. Wagner, E. Corton, and S. R. Mikkelsen, Biosens. Bioelectron., 2003, 18, 907-916.
- 16. K. Chotinantakul, W. Suginta, and A. Schulte, Anal. Chem., 2014, 86, 10315-10322.
- 17. B. Li, Y. Qiu, A. Glidle, D. Mcllvenna, Q. Luo, J. Cooper, H.-C. Shi, and H. Yin, Anal. Chem., 2014, 86, 3131-3137.
- 18. M. W. Kadlec, D. You, J. C. Liao, and P. K. Wong, J. Lab. Autom., 2013, 19, 258-266.
- 19. J. Palomino, A. Martin, M. Camacho, H. Guerra, J. Swings, and F. Portaels, Antimicrob. Agents Chemother., 2002, 42, 2720-2722.
- 20. J. Q. Boedicker, L. Li, T. R. Kline, and R. F. Ismagilov, Lab Chip., 2008, 8, 1265-72.
- 21. K. Churski, T. S. Kaminski, S. Jakiela, W. Kamysz, W. Baranska-Rybak, D. B. Weibel, and P. Garstecki, Lab Chip., 2012, 12, 1629-37.
- 22. F. Deiss, M. E. Funes-Huacca, J. Bal, K. F. Tjhung, and R. Derda, Lab Chip., 2014, 14, 167-71.
- 23. N. J. Cira, J. Y. Ho, M. E. Dueck, and D. B. Weibel, Lab Chip., 2012, 12, 1052-9.
- 24. C. H. Chen, Y. Lu, M. L. Y. Sin, K. E. Mach, D. D. Zhang, V. Gau, J. C. Liao, and P. K. Wong, Anal. Chem., 2010, 82, 1012-9.
- 25. D.-K. Kang, M. M. Ali, K. Zhang, S. S. Huang, E. Peterson, M. a. Digman, E. Gratton, and W. Zhao, Nat. Commun., 2014, 5, 5427.
- 26. M. Safavieh, M. U. Ahmed, M. Tolba, and M. Zourob, Biosens. Bioelectron., 2012, 31, 523-8.
- 27. M. Varshney, Y. Li, B. Srinivasan, and S. Tung, Sensors Actuators B Chem., 2007, 128, 99-107.
- 28. K. Hsieh, A. S. Patterson, B. S. Ferguson, K. W. Plaxco, and H. T. Soh, Angew. Chem. Int. Ed., 2012, 51, 4896-900.
- 29. A. S. Patterson, K. Hsieh, H. T. Soh, and K. W. Plaxco, Trends Biotechnol., 2013, 31, 704-12.
- 30. L. Soleymani, Z. Fang, B. Lam, X. Bin, E. Vasilyeva, A. Ross, E. H. Sargent, and S. O. Kelley, ACS Nano., 2011, 5, 3360.
- 31. S. çakir and E. Y. Arslan, Chem. Pap., 2010, 64, 386-394.
- 32. S. Khazalpour and D. Nematollahi, RSC Adv., 2014, 4, 8431.
- 33. J. W. Warren, E. Abrutyn, J. R. Hebei, J. R. Johnson, A. J. Schaeffer, and W. E. Stamm, Clin. Infect. Dis., 1998, 29, 745-758.
- 34. N. Bao, B. Jagadeesan, A. K. Bhunia, Y. Yao, and C. Lu, J. Chrom. A., 2008, 1181, 153-8.
- 35. K. Gupta, T. M. Hooton, K. G. Naber, B. Wullt, R. Colgan, L. G. Miller, G. J. Moran, L. E. Nicolle, R. Raz, A. J. Schaeffer, and D. E. Soper, Clin. Infect. Dis., 2011, 52, e103-20.
- 36. O. Braissant, G. Müller, A. Egli, A. Widmer, R. Frei, A. Halla, D. Wirz, T. C. Gasser, A. Bachmann, F. Wagenlehner, and G. Bonkat, J. Clin. Microbiol., 2014, 52, 624-6.
- 37. R. Greenwood, P. F. Luckham, and T. Gregory, J. Colloid Interface Sci., 1997, 191, 11-21.